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Test of alternative domains of attraction in the dynamics of a fishless oligotrophic lake Ouimet, Chantal 1998

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Test of alternative domains of attraction in the dynamics of a fishless oligotrophic lake By Chantal O u i m e t B. Sc., Universite de Montreal, 1982 M . Sc., Universite de Montreal, 1986  A-THESIS SUBMITTED I N P A R T I A L F U L F I L L M E N T OF THE REQUIREMENTS FOR T H E DEGREE OF DOCTOR OF PHILOSOPHY in T H E F A C U L T Y O F G R A D U A T E STUDIES (Department of Zoology)  We accept this thesis as conforming to the required standard  T H E U N I V E R S I T Y O F BRITISH C O L U M B I A July 19,1998 © Chantal Ouimet, 1998  In presenting degree  at the  this thesis  in partial fulfilment  of the  requirements  University of British Columbia, 1 agree that the  for an advanced  Library shall make it  freely available for reference and study. I further agree that permission for extensive copying of this thesis for scholarly purposes department  or  by  his  or  her  representatives.  may be granted It  is  by the  understood  that  head  of my  copying  or  publication of this thesis for financial gain shall not be allowed without my written permission.  Department of ~Z.Co[o The University of British Columbia Vancouver, Canada  DE-6 (2/88)  ABSTRACT The theory of domains of attraction (alternative "stable" states) allows variability, thresholds and persistence as integral parts of ecological system functioning. T h i s thesis investigates the potential for alternative  domains  of attraction i n a  zooplankton community. T w o alternative states have been proposed for the zooplankton community of small Ashless, oligotrophic, m o u n t a i n lakes. In the "competition  state", Daphnia  (Cladocera) outcompete  solitary rotifers  and  impede predator recruitment. This state is persistent and resilient to disturbance. In the "predation state", predation by Chaoborus  (Diptera) on both prey types  alters community dynamics to favor rotifers over Daphnia.  Persistence of the  predation state requires reduced prey competition, enhanced  young predator  recruitment i n summer and predator survival i n h i g h densities overwinter.  I carried out graded field experiments using reduced Daphnia  densities and  predator additions i n the spring to generate and test the predator  state. I  monitored lake and enclosure communities for three consecutive years using a n adaptive sampling concept. Chaoborus recruitment was enhanced i n enclosures and the new predator cohorts survived overwinter i n h i g h densities. H o w e v e r , developmental delays prior to the winter period prevented persistence of the predator state over several generations. Enhanced predator densities i n the spring, as well as cold temperature,  delayed Daphnia  population onset and  increase, w h i c h released solitary rotifer populations needed  to feed y o u n g  ii  predator recruits i n early summer. However, i n the higher predator treatments, both prey types stayed depleted till late summer w h i c h resulted i n delayed predator development.  Laboratory experiments showed that although Chaoborus americanus can pupate at 5 ° C , they could not metamorphose into adults below 9 ° C . C o l d water can delay their reproductive phase and delay timing of young predator recruitment.  I conclude that Shirley Lake, under current nutrient levels, does not have two domains of attraction. Nonetheless the presence of a threshold between states enlarges the w i n d o w for coexistence of weaker competitors or rare species. Thresholds lead to alternative domains of attraction i n some systems, and to transient state i n others. From a management  perspective, extended transient  states can either lead to misleading interpretation and erroneous interventions if permanent  changes are expected or be used as tools to produce temporary  changes.  iii  Table of Contents  ABSTRACT  ii  TABLE OF C O N T E N T S  iv  LIST O F T A B L E S  viii  LIST O F F I G U R E S  x  ACKNOWLEDGMENTS  xiii  CHAPTER 1  1  GENERAL INTRODUCTION  1  1.1 D O M A I N S O F A T T R A C T I O N A N D T H R E S H O L D S I N T H E O R Y A N D I N T H E F I E L D 1.2 Z O O P L A N K T O N C O M M U N I T Y C O M P O S I T I O N D O M A I N V E R S U S CHAOBORUS DOMAIN  A N D FUNCTIONING:  1  DAPHNIA 13  CHAPTER 2  30  TRANSIENT STATE OR DOMAIN OF ATTRACTION: TESTING THE PERSISTENCE OF THE CHAOBORUS  STATE  30  2.1 I N T R O D U C T I O N  30  2.2 M A T E R I A L A N D M E T H O D S  32  2.2.1 Field site and enclosure design  33  2.2.2 Experimental design  39  2.2.3 Variable sampling interval: towards an adaptive sampling design  45  2.2.4 Sampling methods, identification, and counts for Chaoborus:  48  2.2.5 Laboratory experiments  50  2.2.6 Initial experimental conditions and general seasonal patterns i n enclosures  51  2.2.7 Predictions based on experimental design  56  iv  2.3 R E S U L T S  61  2.3.1 Second instar predator recruitment i n summer 1992: density, duration  61  2.3.2 Fourth instar ability to resist starvation: s u r v i v a l i n the laboratory and i n f i e l d experiments  67  2.3.2.1 Survival in laboratory experiments at 5°C  67  2.3.2.2 Survival overwinter in field enclosure experiments  68  2.3.3 A signal i n transition: third instar and fall fourth instar predator dynamics i n 1992  73  2.3.4 Result summary  82  2.4  DISCUSSION  84  2.5 C O N C L U S I O N  89  CHAPTER 3 PREY DYNAMICS, SHORT TIME SCALES,  91 AND PREDATOR RECRUITMENT  91  3.1 I N T R O D U C T I O N  91  3.2 M A T E R I A L S A N D M E T H O D S  94  3.2.1 Field experiments  94  3.2.2 Identification and counts  96  3.2.3 Predictions for prey dynamics based on experimental design  97  3.3 R E S U L T S  101  3.3.1 General trends i n prey population dynamics  101  3.3.2 Daphnia population dynamics: influence of spring predator density and temperature ...107 3.3.2.1 Impact of the 1992 spring predator density gradient on Daphnia densities  107  3.3.2.2 Daphnia population onset: influence of water temperature and predator density in the spring  113  3.3.3 Relationship between Daphnia population and solitary rotifer population dynamics...121 3.4 D I S C U S S I O N  131  3.4.2 Rotifer population dynamics  136  3.5 C O N C L U S I O N  138  V  CHAPTER 4  140  CHAOBORUS PUPATION IN COLD WATER: IMPLICATIONS FOR LIFE HISTORY, DISTRIBUTION AND POPULATION DYNAMICS  140  4.1 INTRODUCTION  140  4.2 MATERIAL AND METHODS  141  4.2.1 Field collection and laboratory set up  141  4.2.2 Data analysis methods  144  4.3 RESULTS  145  4.4 DISCUSSION  150  4.5 CONCLUSION  155  CHAPTER 5  156  GENERAL DISCUSSION AND CONCLUSION 5.1 The makings of an extended transient state  156 156  5.2 Dynamical thresholds: the role of nutrient availability, temperature and species composition ; 161 5.3 Alternative domains and states: importance of the threshold perspective  165  5.4 Hysteresis: one threshold when going up, another when going down  167  5.5 Management issues in a threshold perspective  169  CONCLUSION  171  APPENDDC A Enclosure construction design  173  APPENDIX B Method for enclosure fill up with pumps  174  APPENDIX C Comments on predator time series 1992-1994 175 APPENDIX C-l Monthly sample time series for total Chaoborus first instar larva density in Shirley Lake and in experimental enclosures from 1992 to 1994 177 APPENDIX C-2 Monthly sample time series for total Chaoborus second instar larva density in Shirley Lake and in experimental enclosures from 1992 to 1994 178 APPENDIX C-3 Monthly sample time series for total Chaoborus third instar larva density in Shirley Lake and in experimental enclosures from 1992 to 1994 179 APPENDIX C-4 Monthly sample time series for total Chaoborus fourth instar larva density in Shirley Lake and in experimental enclosures from 1992 to 1994 180 vi  APPENDIX D Monthly sample time series for total Daphnia density in Shirley lake and in experimental predator addition enclosures from 1992 to 1994  181  APPENDIX E Monthly sample time series for total solitary rotifer density in Shirley lake and in experimental predator addition enclosures from 1992 to 1994  182  BIBLIOGRAPHY  183  vii  LIST OF TABLES  Table 1.1  Requirements for the persistence of Chaoborus state as an alternative domain of attraction to the Daphnia d o m a i n  27  Table 2.1  Experimental design for predator and nutrient additions  42  Table 2.2  T i m i n g of enclosure recruitment failure  57  Table 2.3  Predictions for the relationships i n predator densities and i n prey densities between the lake and the enclosures, and between the l o w and high treatments i n relation to the experimentally imposed predator gradient 59  Table 2.4  Test of the hypothesis that enclosures have crossed the threshold and switched to Chaoborus state: Chaoborus second instar larvae summer recruitment period 1992 64  Table 2.5  Results from overwinter survival laboratory experiments on Chaoborus  69  Table 2.6  Test of the hypothesis that enclosures have crossed the threshold and switched to Chaoborus state: Chaoborus fourth instar larvae mean density, A p r i l - M a y 1993 72  Table 2.7  Test of the hypothesis that enclosures have crossed the threshold and switched to Chaoborus state: Chaoborus third instar larvae, summer recruitment period 1992 78  Table 2.8  Test of the hypothesis that enclosures have crossed the threshold and switched to Chaoborus state: Chaoborus fourth instar larvae, fall 1992 80  Table 2.9  Overall results of the impact of the spring fourth instar predator density gradient on the predator dynamics throughout the life cycle83  Table 3.1  Predictions for the relationships i n prey densities between the lake and the enclosures, and between the l o w and h i g h treatments i n relation to the experimentally-imposed predator gradient 99 viii  Table 3.2  Impact of fourth instar predator density gradient on Daphnia population increase: Delays (in weeks) i n enclosure Daphnia population i n reaching densities similar to those found i n the lake at the time w h e n first instars appeared 110  Table 3.3  Test of the hypothesis that enclosures have crossed the threshold and switched to Chaoborus state: Testing the difference i n Daphnia density (June 1992) between the lake and the enclosures, and between the l o w and h i g h predation enclosures 112  Table 3.4  Test of the hypothesis that enclosures have crossed the threshold and switched to Chaoborus state: Testing the difference i n Daphnia density (August 1992) between the lake and the enclosures, and between the l o w and h i g h predation enclosures 120  Table 3.5  Test of the hypothesis that enclosures have crossed the threshold and switched to Chaoborus state: Testing the difference i n solitary rotifer density between the lake and the enclosures, and between the low and high predation enclosures, i n relation to Daphnia densitiesl24  Table 3.6  Overall results of the impact of the 1992 spring density gradient i n fourth instar predators on the prey dynamics 129  Table 4.1  Laboratory experimental conditions for raising Chaoborus  Table 4.2  Status of Chaoborus larvae i n laboratory experiments at different temperatures 146  Table 4.3  Duration of pupation at the i n d i v i d u a l level  142  147  ix  LIST OF FIGURES Figure 1.1  Schematic representation of global stability, local stability and domains of attraction  3  Figure 1.2  Small prey: solitary rotifers (Rotifera)  14  Figure 1.3  Large prey: Daphnia rosea (Cladocera: Daphnidae)  16  Figure 1.4  Relative size: Daphnia(on the right) versus solitary rotifer Keratella (on the lower left) 18  Figure 1.5  The predator close up  Chaoborus sp. (Diptera: Chaoboridae): head and jaw 19  Figure 1.6  Family portrait: Chaoborus larval instars and pupa  Figure 1.7  Schematic of interactions i n the Daphnia domain of attraction: the competition state 23  Figure 1.8  Schematic of interactions i n the hypothesized Chaoborus domain of attraction: the predation state 24  Figure 2.1  M a p of Shirley Lake i n the M a l c o l m K n a p p U B C Research Forest, Maple Ridge, B.C., Canada (after Butler, 1990) 34  Figure 2.2  Life histories of Chaoborus americanus Lake from spring 1992 to spring 1995  Figure 2.3  Enclosure set up and experimental design  Figure 2.4  Daphnia reduction: densities of Daphnia i n enclosures after water p u m p i n g and before predator additions. Density i n lake for the same time period is provided for reference 41  Figure 2.5  Initial densities of fourth instar predators i n Shirley Lake and i n the enclosures on M a y 26th, 1992 52  Figure 2.6  Large prey density reduction: percentage of Daphnia density removed from enclosures relative to Daphnia density i n the lake after predator additions (May 26th, 1992) 54  Figure 2.7  Duration of Chaoborus populations i n experimental enclosures and i n Shirley lake 55  and C. trivittatus  20  i n Shirley 36 38  x  Figure 2.8  Recruitment of second instar predators i n summer 1992 i n relation to the density gradient i n fourth instar predators i n spring 1992 62  Figure 2.9  Duration of the recruitment period for second instar predators i n 1992 66  Figure 2.10  Chaoborus fourth instar densities i n spring 1993 i n relation to the experimental density gradient i n fourth instar predators i n spring 1992 70  Figure 2.11  Proportion of second instars surviving to fourth instars (summer 1992 to spring 1993) i n relation to the density gradient i n fourth instar predators i n spring 1992 74  Figure 2.12  Signal transmission through the life history of the larval instars of Chaoborus americanus. The x-axis (except for panel (a)) represents the experimental density gradient i n fourth instar predators i n spring 1992 76  Figure 2.13  Duration of the main recruitment period for third instar larvae of C. americanus i n Shirley Lake and i n enclosures 79  Figure 2.14  Relative difference i n fourth instar Chaoborus density between fall 1992 and the subsequent spring (1993) 81  Figure 3.1  Daphnia density on the date when first instar predators appeared i n Shirley Lake and i n the enclosures each year i n relation to the density of fourth instar predators i n each spring 102  Figure 3.2  Density of solitary rotifers on the date when first instar predators appeared i n Shirley Lake and i n the enclosures each year i n relation to the density of fourth instar predators each spring 103  Figure 3.3  Time series for total Daphnia density M a y to October 1992 following a variable sampling interval 104  Figure 3.4  Time series for total Solitary rotifer density M a y to October 1992 following a variable sampling interval 105  Figure 3.5  Initial Daphnia densities i n the lake and i n the enclosures after predator additions (May 26th, 1992)  Figure 3.6  108  M e a n density of Daphnia (for Julian days 154 to 168, June 1992) i n relation to the experimental gradient i n fourth instar predator i n spring 1992 111  xi  Figure 3.7  Delay i n Daphnia population onset i n 1992 to 1994 i n relation to (A) mean water temperature i n Shirley Lake i n springtime (mid-May to mid-June), (B) predator density i n Shirley Lake i n spring 1992 to 1994 115  Figure 3.8  M a x i m u m and yearly mean Daphnia density i n 1992 to 1994 i n relation to yearly mean temperature 116  Figure 3.9  Delay i n Daphnia onset i n the spring i n relation to the density of fourth instar predators i n springtime of each year 118  Figure 3.10  Daphnia densities i n August 1992, w h e n third instar predators reached their m a x i m u m density, i n relation to the density gradient in fourth instar predator i n spring 1992 119  Figure 3.11  M e a n density of solitary rotifers i n relation to Daphnia mean densities for Julian days 154 to 168 (June 1992)  123  Figure 3.12  Solitary rotifer densities and Daphnia densities i n 1992, initially i n M a y , during y o u n g predator recruitment i n June, and d u r i n g third instar recruitment i n August i n relation to density gradient i n fourth instar predators i n spring 1992 126  Figure 3.13  Solitary rotifer densities i n relation to Daphnia m a x i m u m densities after enclosures have lost their predator cohort (A) for enclosures that failed in 1993, (B) for enclosures that failed i n 1994 128  Figure 4.1  Comparison of survival rates for Chaoborus americanus larvae raised at 5, 9, and 12 °C 148  Figure 4.2  Schematic representing the effect of developmental rate acceleration due to fluctuating temperature i n the l o w part of the range of developmental temperature of an insect 153  Figure 5.1  Schematic representation of the bottlenecks i n Chaoborus recruitment  Figure 5.2  158  Schematic representation of a hysteresis loop and the area of dynamic unpredictability i n system w i t h two domains of attraction.168  xii  ACKNOWLEDGMENTS This project is the result of the involvement of numerous people. I am deeply indebted to Dr. Bill Neill who shared openly his knowledge about science and more importantly how to do science. I would like to express my gratitude for his support and his anchoring influence throughout this long adventure. I appreciated his generosity in allowing me extensive use of his laboratory and office space, and of his field and laboratory equipment. I owe a thousand thanks to Danusia Dolecki, for her friendship, for her great technical abilities, and for sharing her vast knowledge of all that is aquatic; without her, a green horn such as I would have been swept under by the complexity of the task. I acknowledge with gratitude the help provided by my research committee: Dr. Don Ludwig, Dr. Bill Neill, Dr. Tom Northcote, Dr. John Post, Dr. John Richardson, Dr. Dolph Schluter, and Dr. Carl Walters. They encouraged me to focus and clarify my ideas. The comments of Drs. Ludwig, Neill, Richardson and Schluter greatly improved my writing and the resultant thesis while allowing me the freedom to make my own mistakes. I am thankful for the diligence with which they perused successive versions of this work. I thank Carolyn Cornish, Bill Graham, Rose Murphy, Ole Olson, and Peter Troffe, student employees who participated enthusiastically in the field and laboratory work. Many thanks to Dr. Ken Hall, Dr. Paul. J. Harrisson, Dr. A l Lewis, Dr. Don McPhail, Dr. B i l l Neill, Dr. Tom Northcote, Dr. Tim Parsson, Dr. John Post who generously lent me field and laboratory equipment. Thanks to Catriona, John and Quedong for help on nutrient analysis, and to Keith McDougall for microscopic photography and image handling. I want to thank staff from the Zoology Department, Fisheries Centre and Malcolm Knapp Research Forest who guided me through the administrative jungle or helped with some technical aspects of the project. I must acknowledge Dr. Carl Walters, my supervisor, for the laboratory space he provided and for generously funding this project out of his research grants. Other funding for this project was provided by N.S.E.R.C. through a two-year scholarship, by the University of British Columbia through a two-year University Graduate Fellowship and several Teaching Assistantships. Supplemental support was provided as student loans by the Government of Canada and the Government of Alberta. Finally, I offer my sincere thanks to over three dozen volunteers who visited Shirley Lake over the years and helped with installing, sampling (especially at night), and removing the enclosures: Rob Ahrens, Lance Barrett-Lennard, Shannon Bennet, Sarah Beukema, Alice Cassidy, Maggie Cobbett, Carolyn Cornish, Danusia Dolecki, Lech Dolecki, Richard Dolecki, Reuven Dukas, Melissa Fletcher, David Ghan, Kathy Gorkoff, Elvira Harms, Steve Heard, David Hik, Wes Hochachka, Leonardo Huato, Xavier Lambin, Anna Lindholm, Karl Mallory, Keith McDougall, Maura Mclnnis, Jeff and Irene Mclnnon, Matt McLeod, Bill Neill, JeanMichel Pianotti, John Post, John Pritchard, Jordan Rosenfeld, Dick Repasky, Beth Scott, Susan Shirley, Lisa Thompson, Carl Walters, David Ward, Crystal, Forrest, Kerry, Maria, Michael, Mike, Regina, William. To those I omitted by oversight, I thank you earnestly for your help and support. Thank you all. xiii  TO KEITH, N o t h i n g is more patient than love.  A LYSE, C L A U D E , A L A I N , L Y N E , M I C H E L ,  MANON,  O h ! combien de loin Mais avec grand soin Vos pensees ont voyagees Et m'ont accompagnees Tout au long de m o n sejour, De mes nombreux detours, Dans les montagnes d u vecu, A u pays de l'inconnu.  xiv  "The history of ecology is a history of changing criteria for imposing order o n nature and resisting the alternative that all is really chaotic and contingent" Sharon K I N G S L A N D (1985) " M o d e l i n g nature: Episodes i n the history of population ecology, p.5"  xv  CHAPTER 1  GENERAL INTRODUCTION  Ecological systems persist i n the face of repeated disturbances despite variation i n species abundance and composition. However, emphasis on linear dynamics and trends i n interpretation of ecological data fails to take account of such v a r i a t i o n . The linear model represents w e l l systems w i t h continuous behavior and for w h i c h a small disturbance always results i n a small response of the system. I n nonlinear dynamics, response of the system is not always proportional to the size of the disturbance, but the model is still continuous. Recently, some ecological systems have been shown to have discontinuous behaviors or thresholds where even a small disturbance can generate large changes i n dynamics, behaviors w h i c h cannot be explained i n terms of linear dynamics.  1.1  D O M A I N S O F A T T R A C T I O N A N D T H R E S H O L D S IN T H E O R Y A N D IN  T H E FIELD  The concept of multiple domains of attraction can integrate both variability and the potential for discontinuities i n ecological dynamics. Domains are represented in phase space, a graph where  dynamical trajectories  resulting from  the  interactions of two variables of the system can be represented. Examples of phase space are predator-prey graphs or competitor interaction graphs w i t h  their  1  dynamical isoclines and their equilibrium points. A d o m a i n of attraction is a n area of phase space that includes the set of a l l trajectories leading back to the attractor (or reference state, or dynamic) after a disturbance (Figure 1.1). A system w i t h multiple domains of attraction has local, but not global stability. Global stability occurs i n a system w i t h a single stable equilibrium (Figure 1.1-A); a l l trajectories i n phase space lead to this attractor. O n the other hand, local stability means that more than one stable equilibrium is present (Figure 1.1-B); different trajectories lead to different attractors, and thus the system can have more t h a n one behavior. Domains are separated by boundaries, w h i c h are thresholds for the variables of interest. Ecological systems have been modeled using the concept of multiple domains of attraction to describe c o m m u n i t y dynamics and explain discontinuities (e.g., L u d w i g et al. 1978; Peterman et al. 1979; Harrison 1986; A d a m s and DeAngelis 1987; Scheffer 1989; 1991a; Carpenter and C o t t i n g h a m 1997; 1998). However, the evidence for multiple domains of attraction i n the field is sparse (Edmonson and L e h m a n 1981; Sinclair  1995; Scheffer 1998), and  questions arise: h o w ubiquitous are they and do they play an important role i n ecological systems?  Thresholds play an important role at several scales i n ecology. Furthermore, thresholds  at one  physiological  level  scale can affect dynamics at the (individual  level),  ectotherms,  scale above. such  as  At  the  insects  or  zooplankton, have temperature thresholds. The thresholds are associated w i t h on/off switches, for example, a temperature above w h i c h development can take  2  Figure 1.1  Schematic representation of global stability, local stability and domains of attraction.  A ) Global stability: all trajectories lead to a single attractor  Predator density  Prey density  B) Local stability: different trajectories lead to different attractors. The b o l d line represents the boundary separating the two domains of attraction.  Predator density  Prey density  3  place and below w h i c h there is no development  (Hoffmann  1985). Other  thresholds are associated w i t h additive processes (time or energy dependent), such as accumulation of degree-days or accumulation of body mass, where development  takes place but is only completed w h e n the time or energy  threshold is crossed. W h e n the degree-day threshold is reached, for example, zooplankton can molt to move between stages, and insects can metamorphose into  adults  and reproduce.  These  physiological  thresholds  often  synchronized emergence of aquatic insects that facilitate mating and predation losses. Furthermore,  from  lead  to  reduce  a predator's perspective, synchronized  emergence improves predation success and potentially reproductive success. Thus, physiological thresholds  have  implications for population dynamics.  Moreover, they can have a rippling effect on other species i n the system and potentially change community dynamics. H o w c o m m o n  are discontinuous  behaviors at the community scale?  Ecological systems were modeled as multiple domains of attraction starting i n the mid-1970s (Pasture productivity: N o y - M e i r 1975; competition i n birds: G i l p i n and Case 1976;  Budworm  epidemics: L u d w i g et al. 1978;  Fish and insect:  Peterman et al. 1979). The early model by N o y - M e i r (1975) showed alternative domains of attraction, w h i c h he called "alternative stable states". H e suggested that different herbivore characteristics (e.g. sheep versus goats as grazers) w o u l d lead to different results, w i t h efficient grazers more likely to create discontinuity in the behavior of the system. In such a system, overgrazing could reduce the  4  productivity of a pasture, but r e m o v i n g grazing pressure w o u l d not necessarily return productivity to higher levels (hysteresis). H e also suggested  management  practices w h i c h w o u l d preserve pasture productivity.  L u d w i g et al. (1978), emphasized the importance of the interactions of different scales, i.e., fast and slow variables, i n their simulation model of spruce b u d w o r m outbreaks. The build-up of the c r o w n foliage could take several decades (slow variable) before it w o u l d reach a level at w h i c h the spruce b u d w o r m larvae could escape the predation influence and produce a sudden population outbreak (fast variable) w h i c h w o u l d disappear w i t h i n a single decade. W i t h this model, the authors suggested that spraying the insect larvae w o u l d maintain the forest at high food quality, thus maintaining the epidemic conditions year after year.  Other models have been developed more recently (Fish populations: A d a m s and DeAngelis  1987;  pike-bream-phytoplankton-macrophytes:  Scheffer  1989;  Jeppesen et al. 1990 i n Blindow et al. 1993; phytoplankton-macrophytes: M o s s 1990; 1990; 1991a; Blindow et al. 1993; Fish-zooplankton: Rudstam et al. 1993; lake eutrophy-dystrophy: Carpenter and Cottingham 1997; 1998). Each of these models is based on phenomena taking place over more than one scale, temporal or  spatial.  phytoplankton  For has  example, several  in  the  generations  phytoplankton-macrophyte per  year  (fast  variable),  system, while  macrophytes have only one (slow variable). The fast variable (phytoplankton) under a small disturbance (increased phosphorus loading) can feed back and  5  multiply the effect of the small disturbance into a large observable impact on the species, population or community under observation. The phytoplankton b l o o m can eliminate macrophytes through shading, a competitive interaction. T h e impact of a disturbance on a system depends both on characteristics of the species in presence  and on the size and  characteristics  of the  disturbance  itself,  characteristics such as type (pulse, press), or extent (e.g. time duration, space coverage, density range) (Pahl-Wostl 1995; G r i m m and Wissel 1997).  Thresholds have been observed i n the field and described more frequently o v e r the last decade. Two systems have been studied i n sufficient details to define domains of attraction: 1) phytoplankton vs. macrophyte phases i n shallow lakes (Moss 1990; Scheffer 1998), and 2) w o o d l a n d vs. savannas i n Serengeti (Africa) (Dublin et al. 1990; Sinclair 1995). Other systems present the mechanisms leading to potential or demonstrated thresholds i n goose-plant interactions (Hik et al. 1992), piscivore-planktivore fish communities  (Persson and Greenberg 1990;  Mittelbach et al. 1995; Olson et al. 1995), and i n a zooplankton c o m m u n i t y ( N e i l l 1988a; 1988b). I review below some of these examples to portrait the type of interactions and the amount of information required to evaluate the dynamics of systems w i t h discontinuities.  A w e l l studied system leading to two domains of attraction occurs i n s h a l l o w lakes where dominance  alternates between  phytoplankton  and  macrophyte  phases, between turbid and clear water phases. Enclosures and whole lake  6  experiments have revealed a threshold between the turbid state, due to large concentrations  of  phytoplankton,  versus  the  clear  water  state,  where  macrophytes dominate (Scheffer 1989, 1990,1991a, 1998; Moss 1990; Blindow et al. 1993). Relative abilities i n plant nutrient uptake and the effect of z o o p l a n k t o n grazing affect the state of the lake. W h e n nutrient loading increases sufficiently, phytoplankton production can overcome losses to zooplankton grazing. Large blooms of phytoplankton decrease water clarity, thus shading the macrophytes, w h i c h die. W h e n macrophytes disappear, zooplankton lose their refugia from fish predation, and the turbid state can become persistent.  In the plant-fire-elephant  interactions  which  lead to alternative  states of  savannas and woodlands i n the Serengeti landscape, social history (rinderpest epidemic, ivory and slave trades, poaching) and natural history (wildebeest migration, grazing interaction and impact on plant community) were interlaced to gain insights on past landscapes, and give insight for current management for the preservation of this complex and dynamic ecosystem (Dublin et al. 1990; D u b l i n 1995; Sinclair 1995). Ecological studies revealed that fire, often set by h u m a n activities, could increase mature tree mortality while elephant grazing increased tree sapling mortality. W h e n fires are frequent, savannas are created. W h e n fires are rare, savannas can be maintained by a large elephant p o p u l a t i o n . Only w h e n both elements decreased d i d savannas change to woodlands. In the 1890s, a rinderpest epizootic reduced savanna grazers and destroyed tribal cattle herds. The latter reduced h u m a n activity and fire frequency. A t the same time,  7  slave and ivory trade further reduced human-set  fires and reduced  elephant  populations. This combination led to increased cover of woodlands i n the East African landscape. In the 1950s and 1960s, the h u m a n  population increased  dramatically, thus increasing fire frequency. Moreover, the increase i n h u m a n populations also resulted i n the compression of elephants to smaller areas. T h i s led to a decline i n woodland cover. In the Serengeti-Mara ecosystem,  the  rebuilding of large populations of wildebeests after the rinderpest reduced dry tall grass fuel and reduced fire frequency but woodlands d i d not recover because of elephants grazing on tree saplings. Thus, two alternative  states exist i n the  Serengeti landscape.  In some systems, the information gathered so far reveals  the existence of  thresholds without determining if the states present are domains of attraction. Factors that differentially influence i n d i v i d u a l and population growth rates of the predator and prey species can affect community structure  (Persson 1987;  Persson 1988 : cited i n Olson et a l , 1995; Olson et al. 1995). In these studies different species of fish were observed, yet c o m m o n characteristics arise. 1) T h e predator life history has an ontogenetic shift i n feeding, i.e., smaller/younger individuals eat different resources than older ones. 2) Larger predators feed o n prey species that compete for resources w i t h the smaller-sized predators. 3) T h e predator ontogenetic shift is flexible, i.e., it is based not on a specific time or size but is rather based on relative size between the predator species i n d i v i d u a l s and the species w h i c h can function either as a prey or a competitor. 4) Young-of-the-  8  year of predatory fish are planktivores u n t i l they reach a size at w h i c h they can feed on fish. 5) Y o u n g predators must  compete w i t h fish  planktivory, w h i c h are better competitors  w h e n a food resource is l i m i t i n g  (Olson et al. 1995). This competition is detrimental  specialized i n  to the young predators'  growth rate, and their shift to piscivory is delayed, favoring a planktivoredominated community. W h e n plankton resources are not limiting, the y o u n g predators grow quickly to the relative size at w h i c h they can start feeding on the planktivorous  fish.  The  community  is  then  piscivore-dominated  and  zooplankton can bloom. Here again, temperature change is not necessary for a shift to take place, but could play a role, w i t h a cool year reducing p l a n k t o n productivity, thus increasing the likelihood  of competition, and favoring a  planktivore dominated community.  Simple differences i n consumption versus production rates, such as i n the CiscoDaphnia  interaction i n Lake Mendota (Rudstam et al. 1993), can also result i n  discontinuous community dynamics. In early spring, Cisco (Coregonus cold-water planktivore fish, consume Daphnia  can reproduce  Daphnia  artedi), a  at a higher rate than the rate  i n cold water. Thus, planktivory controls the  population. A s water temperature increases, Daphnia  prey  reproduction rate increases  to levels exceeding the consumption rate of the planktivore. Thus, later i n the spring, Daphnia  population  escapes control by Cisco, blooms  and  reduces  phytoplankton populations, leading to the classic clear-water phase where water transparency increases. The rates of the predator and the prey are mediated by  9  both a biotic factor, density of planktivores, and  an abiotic factor,  water  temperature. A switch i n the dominance of one factor, predation on Daphnia, to another, recruitment of Daphnia, due to the physiological ecology of the two interacting species leads to changes i n population and community dynamics.  There are at least three reasons w h y few examples of thresholds i n c o m m u n i t y dynamics are present i n the literature: first, a perspective centered on stability combined w i t h multiple definitions of stability, second, the need for ecologists to w o r k at multiple scales and w i t h multiple factors, third, the need for researchers and managers for a large amount of information and synthesis to link  those  different scales and factors. H o l l i n g (1973 , p.15), an early proponent of the first point, suggested that a very different view of the w o r l d could be obtained " i f we concentrate on the boundaries of the domains of attraction rather than  on  equilibrium states." However, based on the deeply-rooted belief i n the "balance of nature" (Egerton 1973), research has long been focused on the pursuit of ecological system equilibria, a view represented by the use of the expressions "multiple stables states" and "alternative stables states". A major  assumption  w i t h i n this perspective is that ecological systems are able to reach and stay at equilibrium. Yet, ecological systems, under repeated disturbances both from biotic and abiotic variables, rarely achieve equilibrium. Over time, the "concept" of stability developed into a frenzy of definitions. W h i l e  Lewontin  (1969)  recognized five definitions related to the notion of ecosystem stability, G r i m m and Wissel (1997) catalogued 70 concepts and 163 definitions relating to stability.  10  They summarized this multitude into six m a i n concepts: constancy, elasticity, persistence, resilience, resistance, and domain of attraction, of w h i c h the last four w i l l be useful to this study. Persistence is a characteristic of an ecological system in w h i c h the system is maintained  through time as an identifiable entity,  without reference to its dynamics. Resilience is the ability of a system to return to the reference state after a temporary disturbance. Resistance is the ability of a n ecological  system  to  stay  essentially  unchanged  despite  the  presence of  disturbances. A domain of attraction is the set of conditions from w h i c h  the  reference state (or dynamic) can be reached again after a temporary disturbance. Ecological systems vary continually, but their variability is generally bounded. Determining those boundaries could be more informative than pursuing ever evasive equilibria.  Secondly, the focus on a single factor, such as predation, or competition, or production, i n isolation (as criticized by Polis 1994), and often over a single scale of observation (as criticized by H o l l i n g 1992; Polis 1994; Schneider  1994) is  another reason for the fact that communities are rarely described i n terms of multiple domains of attraction. For example, i n the 1980s, i n aquatic ecology, there was a controversy about w h i c h of top-down (predation) or bottom-up (production) was the dominant  force i n structuring communities.  Trophic  cascades i m p l y a dominant impact of predation on the structure of c o m m u n i t i e s (Fretwell 1987; Carpenter 1988a; Carpenter and Kitchell 1993), w h i l e nutrient levels and primary production i m p l y bottom-up structuring factors. S i m i l a r l y ,  11  competition was seen as the d r i v i n g force w i t h i n proposed the idea of apparent  guilds until  H o l t (1977)  competition, where dynamics resembling a  competitive interaction between two species of a guild are i n fact driven by a predator switching prey species, based on the most abundant species present. I n such a case predation, not competition, structures the community. A m o r e fruitful approach looks at the relative strength of these processes under different conditions to determine what the community structure or dynamic w i l l be (e.g. N e i l l and Peacock 1980; Leibold 1989; McQueen et al. 1989; Power 1992; H u n t e r 1992b). This approach implies the study of multiple processes simultaneously, w h i c h means more complex studies i n v o l v i n g multiple species or categories, at more than one scale of observation, temporal or spatial (Addicott et al. 1987; Polis 1994; Polis and Strong 1996).  Thirdly, the inclusion of multiple factors and multiple scales i n the study of ecological systems increases the difficulty of the collection, representation and analysis of data (Addicott et al. 1987; Polis 1994). Large amounts of i n f o r m a t i o n regarding community interactions and the timing of events are required to detect and test the presence, resilience and persistence of alternative states. In t u r n , thoughtful synthesis of this information allows the assessment of two criteria that are essential to demonstrate the existence of multiple domains of attraction in a system. The first is to determine the presence of a threshold between two states, while  the  second is to demonstrate  the  persistence  over  several  generations of each of the two (or more) states. Some evidence has been obtained  12  for two states i n a zooplankton c o m m u n i t y predator, and Daphnia  composed of Chaoborus,  the  and rotifers, the prey. This system is the focus of m y  research.  1.2  Z O O P L A N K T O N C O M M U N I T Y COMPOSITION A N D FUNCTIONING:  DAPHNIA  D O M A I N V E R S U S CHAOBORUS  DOMAIN  In Gwendoline Lake, i n the M a l c o l m K n a p p Research Forest (British C o l u m b i a , Canada), N e i l l (1981b; 1985; 1988a) demonstrated  the presence of a threshold  w h i c h highlighted the potential of the zooplankton c o m m u n i t y to harbor two domains  of attraction. The  lake community  was generally found  in  the  competition domain, where competition between Daphnia and rotifers was the main interaction. U n d e r experimental conditions i n enclosures, the c o m m u n i t y was observed to switch to a different state, where predation of Chaoborus on both prey types became more important than the competition between prey. T h e switch was based on sufficient resources being directed to the rotifers i n late spring.  Rotifers (Figure 1.2) are generally suspension feeders. They feed on a range of small particles (0.5 - 20 um) (Bogdan and Gilbert 1982; Gilbert 1988a; A r n d t 1993), w h i c h include bacteria, protista, small ciliates and small algae. Genera, such as Polyarthra,  feed on larger particles (1-40 um) (Arndt et al. 1990; Gilbert and Jack  1993) and have poor ability to filter bacteria and small particles (Bogdan and Gilbert 1982). Under favorable conditions, rotifers reproduce parthenogenetically, 13  Figure 1.2  Small prey: solitary rotifers (Rotifera).  ROTIFERS: general body size: 50 - 200 urn  S u s p e n s i o n feeders:  on 0.5- 20 um particle range  Keratella sp  (Brachionidae)  w i t h females quickly producing new females without sexual reproduction. They reproduce sexually w h e n conditions deteriorate (Gilbert 1988a). In early spring, their population densities bloom before Daphnia (Gilbert 1988a). A s the  Daphnia  population  hatch out of resting eggs  increases  i n late spring,  the  populations of rotifers decline (Neill 1985; Gilbert 1988a; 1988a). Rotifers b l o o m again i n the fall w h e n Daphnia  enter the resting egg stage and the  latter  disappear from the water column (Gilbert 1988a).  Daphnia are also suspension feeders. They can ingest a wide variety of particles — bacteria, ciliates, phytoplankton and even rotifers — of different sizes (Range: 0.5 - 60 um) (J0rgens0n 1966, cited i n Hebert 1978; Jiirgens 1994a) w i t h preference for cells 20 um or less (Edmonson 1959). Daphnia hatch from resting eggs i n spring. In the Research Forest lakes, Daphnia rosea (Figure 1.3) generally appear i n the samples i n M a y , and b l o o m to high densities through  parthenogenetic  reproduction by the end of June (Walters et al. 1987). In the fall, males  are  produced, sexual reproduction takes place, and resting eggs are released  to  survive unfavorable conditions (Edmonson 1959) such as those brought u p o n by winter under ice. W i t h  their wide ranging diet, Daphnia  are a d o m i n a n t  competitor of several species of zooplankton, i n c l u d i n g the rotifers (Gilbert and Stemberger  1985; Gilbert  1988a). The  impact  of Daphnia  on  the  populations is two-fold. These cladocerans can affect rotifers through  rotifer resource  competition for the small size particles (Gilbert 1985; Gilbert 1988a; Jack and Gilbert 1993). Large Daphnia have a major size advantage over rotifers  (see  15  Figure 1.3 Large prey: Daphnia rosea (Cladocera: Daphnidae).  Suspension feeders on 0.5 - 60 um particle range  Daphnia rosea  Female with young in brood chamber  Body size: 1200-1600um, up to 2000 u.m  (excluding spine)  Figure 1.4) and can also affect them directly by preying on them, or by battering them w i t h i n their "filtering" appendages while feeding on other food particles (Gilbert and Stemberger 1985; Burns and Gilbert 1986a; Gilbert 1988a). In the latter case, the rotifers are not necessarily ingested. They can be rejected w i t h  the  feeding water current or i n the bolus w i t h other rejected particles. A l t h o u g h the rotifers might not be killed immediately by the process, they can be gravely injured (Gilbert and Stemberger 1985), w h i c h makes them more susceptible to predation, reduces their ability to feed, or prevents their reproduction. A l l of this leads to reduced rotifer population growth and density.  The third player i n this system is the phantom  midge Chaoborus  (Diptera:  Chaoboridae) (see Figure 1.5), a predatory aquatic larva w h i c h changes body size and mouth gape size between each of four larval instars (see Figure 1.6). Y o u n g instars  are limited  to small prey sizes, while older instars  can feed  on  increasingly larger prey. Y o u n g instar larvae can grow fast, but are prone to starvation w h e n prey of the right size category are rare. They have a relatively short life span, for example, one to two weeks i n the first instar (Neill 1988a). Older instar larvae grow slower but can survive without a meal for a longer period of time than the younger instar larvae. These differences i n metabolic characteristics and i n diet of each instar can lead to different  community  dynamics, depending on the prey assemblage, prey density available to the predator, and environmental conditions.  17  Figure 1.4  Relative size: Daphnia(on the right) versus solitary rotifer Keratella (on the lower left).  18  Figure 1.5  The predator Chaoborus sp. (Diptera: Chaoboridae): head and jaw close up.  Chaoborus trivittatus  fourth instar larva  Variation in head capsule length between individuals : 1.5 - 2.8 mm  (length from the articulation of the second antennae with the head (a) to the furthest point on head exoskeleton (b))  (a)  jaw secondary antennae with chetinous teeth (used for prey capture)  19  Figure 1.6  Family portrait: Chaoborus larval instars and pupa,  third instar  second instar  first instar  fourth instar  pupa  Chaoborus sp. First instar:  head length* 400 um gape width unavailable  Chaoborus americanus Instar 2 3 4  head* (|im)  gape width (urn +  550 1000 1600  300 430 710  Chaoborustrivittatus Instar  head* (u.m) gape width (urn +  2  700  360  3 4  1350 2200  510 850  * Fedorenko and Swift, 1972  +  Fedorenko, 1975 20  Both the rotifers and Daphnia  are prey for the voracious phantom  midge,  Chaoborus (Fedorenko 1975b; Kajak and Rybak 1979; Smyly 1980; V i n y a r d and Menger 1980; Pastorok 1980a; Pastorok 1981; N e i l l 1981b; M o o r e and Gilbert 1987; Riessen et al. 1988; Walton 1988; 1988a; Moore 1988b; Christoffersen 1990; H a v e n s 1990; Moore et al. 1994). Figure 1.6 represents the different instars of Chaoborus, and the head and gape size (based on Fedorenko and Swift, 1972) for the two species present i n the lake. In lakes w i t h higher productivity, Chaoborus  can  produce several generations per growing season. In the oligotrophic lakes of the U B C Research Forest, this predator reproduces once a year (e.g. C. americanus)  or  even once every two years (e.g. C. trivittatus). Generally, emergence of flying adults occurs i n late spring (May-June: Fedorenko and Swift, 1972; and this study), from aquatic pupae floating at the water surface. They mate and females lay egg rafts on the water surface. The eggs hatch w i t h i n a few to 48 hours, depending on temperature (pers. observ.), into small first instar larvae, w h i c h feed mainly on rotifers and other small-sized prey (Moore and Gilbert 1987; Walton 1988; Moore 1988b; Havens 1990; Moore et al. 1994) because of their s m a l l gape size. W i t h i n a few days, the first instars molt to second instars w h i c h also feed on small prey, including small copepod nauplii (Moore and Gilbert 1987; Moore 1988b; Moore et al. 1994). W h e n the second instars molt to the t h i r d instars, they can feed on larger prey i n c l u d i n g young Daphnia,  other s m a l l  cladocerans, copepodites and adults of small copepod species. By late s u m m e r , most larvae reach the last, largest and most voracious fourth instar. A t this stage, the diet spans a wide range of prey species and sizes, from small rotifers to larger  21  prey such as Daphnia (1 m m i n size head to base of tail spine) (Fedorenko and Swift 1972), other cladocerans and copepods (Riessen et al. 1988). overwinter mainly as fourth instar larvae. In the pupating, and metamorphosing  Chaoborus  spring, they feed  before  into flying adults to start the new generation.  For species that take two years to complete their life cycle, such as C. trivittatus, the larvae spend a second summer i n the lake as fourth instar larvae, and o n l y metamorphose  during the second spring. W i t h their longer life history, the  predators represent a slow variable w h i l e the fast growing Daphnia and rotifer populations represent the fast variables i n the dynamics of this z o o p l a n k t o n community.  The thoughtful synthesis of the direct and indirect interaction between rotifers and Chaoborus  was started by N e i l l  and  Daphnia,  Peacock (1980) and  the  community dynamics were elaborated by N e i l l (1981b; 1984; 1985; 1988a; 1988b). I represent these dynamics i n schematics (Figure 1.7 and Figure 1.8). By late spring, w h e n Daphnia blooms, the rotifer populations decline. This reduces the density of small prey available to the newly hatched young instars of Chaoborus  (Figure  1.7). Drastic Chaoborus larval mortality occurs during the first and second instar stages (Neill 1988a). Because the number  of third and fourth instars is l o w ,  Chaoborus have a limited impact on the population of Daphnia,  which then  dominate the dynamics of the whole community, including that of the predator (Figure 1.7). The main interaction i n this system is one of competition between the suspension feeders. Predation plays only a minor role. This configuration of  22  Figure 1.7  Schematic of interactions in the Daphnia domain of attraction: the competition state  zooplankton  c o m m u n i t y interactions  Size of a r r o w represents relativeimpact o f A o n B (see text f o r explanation)  ROTIFERS  DAPHNIA  competition  i  predation  predation  recruitment CHAOBORUS  instars 1 & 2  CHAOBORUS  Main interaction:  COMPETITION Daphnia  Stability:  instars 3 & 4  depresses rotifer population  persistence and resilience  23  Figure 1.8  Schematic of interactions i n the hypothesized Chaoborus domain of attraction: the predation state  zooplankton c o m m u n i t y interactions Size of arrow represents relativeimpact of A on B (see text for explanation) ROTIFERS  DAPHNIA  ..  competition  recruitment CHAOBORUS instars 1&2  Main interaction: Chaoborus  Stability:  CHAOBORUS instars3 &4  PREDATION depresses Daphnia  and rotifer populations  persistence? (need to be tested)  24  the food web is persistent over several generations, and is resilient to even large disturbance such as substantial Daphnia biomass removal (Neill 1985). This is what I refer to as the Daphnia domain of attraction, the "competition state" of the community.  Under experimental conditions, a different state has been observed (Neill 1988a; 1988b). Through reduced competition between the suspension feeders caused by Daphnia  reduction, or through increased predation on Daphnia,  the rotifer  populations bloom over a longer period of time. If this takes place d u r i n g the time w h e n Chaoborus is reproducing, the recruitment of the young  Chaoborus  instars is improved (Figure 1.8). M o r e of them grow into third and fourth instars by the end of the summer. W h e n the fourth instars are numerous, their impact on prey populations is large. The predators can now reduce the population of Daphnia,  and this results i n reduced competition on the rotifer  populations  w h i c h remain high (Neill 1985; 1988a; 1988b). Thus, by the fall, the c o m m u n i t y is switched from the Daphnia domain to a new state I call where  the  main  interaction  i n the  system  is n o w  the Chaoborus predation  state,  instead  of  competition between the prey. Here I use the expression "Chaoborus state" rather than "Chaoborus d o m a i n " because the persistence over several generations of this new state still remains to be tested.  The work described above revealed evidence satisfying the first criterion, the presence of a threshold, and partially satisfying the second criteria, persistence of  25  the "competition" state. N o evidence exists that the alternative "predation" state can persist i n oligotrophic conditions. If this new state could be shown to persist over several predator generations, the c o m m u n i t y w o u l d have two domains of attraction. O n the other hand, if the predation state does not persist it w o u l d instead represent a transient dynamic. Such transients, especially w h e n relatively long, can play an important role i n ecosystem dynamics.  Here, I test the hypothesis that the zooplankton c o m m u n i t y of an oligotrophic lake has two domains of attraction, the Daphnia domain. In particular, I carry out enclosures to test whether  an  d o m a i n and the  inter-seasonal  Chaoborus  experiment  in  the zooplankton c o m m u n i t y can persist i n  "predation state" first, over the winter, and second, over several  large the  predator  generations.  Persistence of the "predation state" requires that four assumptions, w h i c h f o r m the key research issues i n this thesis, are met (Table 1.1). The first two concern predator dynamics. First, recruitment of y o u n g predators i n the summer s h o u l d be enhanced i n the Chaoborus Daphnia  state compared to their recruitment levels i n the  domain. Second, fourth instar predator larvae should be able to s u r v i v e  overwinter at high density so as to continue to suppress the Daphnia  population  when these cladocerans hatch from resting eggs i n the spring. A b i l i t y of the predator to survive overwinter was tested i n laboratory experiments as well as i n  26  Table 1.1  Predator dynamics  Prey dynamics  Requirements for the persistence of Chaoborus state alternative domain of attraction to the Daphnia domain  as  •  Y o u n g predator instars must recruit i n higher density i n summer i n Chaoborus state than i n Daphnia d o m a i n  •  Fourth instar larvae must be able to survive at h i g h density over the winter  •  L o w e r Daphnia density prior to young predator recruitment  •  Higher solitary rotifer densities prior to young predator recruitment  an  27  the field. I w i l l test these two criteria for predator dynamics i n Chapter 2. T h e next two elements involve prey dynamics. Third, Daphnia population density prior to the young predator  recruitment  period should be lower i n  the  Chaoborus state than i n the Daphnia domain. Lastly, i n response to the l o w Daphnia density, solitary rotifers should be released from competition and be found at higher densities prior to the young predator recruitment period i n the Chaoborus state. I w i l l test the response of the prey i n relation to each other and in relation to predator densities throughout the predator life cycle i n Chapter 3.  Analysis of field data for systems w i t h thresholds i n their dynamics m i g h t require new or combined methods. Already i n 1966, Morley (1966a and b, cited i n Noy-Meir  1975)  had pointed out that conventional statistical analysis of  "average effects" w o u l d mask the discontinuity i n the results, and the theoretical insight derived from them. Scheffer (1998, p. xvii) went further and stated: "The classic ideas about hypothesis testing are of rather limited use i n ecology." H e explains that this is because strong inference assumes that competing hypotheses are  general  independent  and  mutually  mechanisms  exclusive. can  However,  contribute  to  an  in  ecosystems,  observed  several  phenomenon.  Moreover, one mechanism can dominate, but its dominance w i l l differ from case to case and may even shift i n time. In Chapter 2 and 3, I use linear regressions and correlations to underline  the problems  generated  in  data  interpretation when these techniques are used for data sets i n c l u d i n g alternative states.  28  D u r i n g m y field work, I found that water temperature  i n Shirley Lake c o u l d  have a greater influence than first anticipated on the predator and prey, and o n their interactions. Information on the role of cold temperature i n the spring o n Daphnia population dynamics is included i n Chapter 3. Laboratory experiments on the effect of cold temperature  on the development  and s u r v i v a l  of the  predator revealed important differences between the two species of Chaoborus present i n the lake. These differences could affect the persistence of the predation state. The results of those experiments are presented i n Chapter 4.  Finally, i n Chapter 5, I link the information gathered from different scales of observation from Chapters 2, 3 and 4 to discuss the mutual impact of the predators and the prey on each other. I discuss also the impact of different disturbances on the potential for multiple domains of attraction i n Shirley lake zooplankton community, and i n other lakes at similar and different  nutrient  levels. Other biological systems show the presence  in  of thresholds  their  dynamics. Determining if these thresholds lead to alternative domains or to transient states could be important for ecological management.  I conclude that  using a variability perspective rather than a focus on equilibrium, allows us to include i n our repertoire of explained c o m m u n i t y behaviors the discontinuous observations which have so far been discarded as exceptional events.  29  CHAPTER 2 TRANSIENT STATE OR DOMAIN OF ATTRACTION: TESTING THE PERSISTENCE OF THE CHAOBORUS STATE  2.1 INTRODUCTION Fishless lakes containing the predator Chaoborus,  the phantom midge, s h o w  great variability regarding the impact of this aquatic insect  larva on  the  zooplankton community. In eutrophic lakes, the phantom midge Chaoborus can have a large impact on the zooplankton c o m m u n i t y structure and dynamics (Kajak and Ranke-Rybicka 1970; Hillbricht-Ilkowska et al. 1975). In lakes where Chaoborus are numerous, the community is dominated by smaller z o o p l a n k t o n species, such as rotifers and Bosmina, while Daphnia are l o w i n density or absent (Havens 1990). In oligotrophic lakes on the other hand, Chaoborus was found to have little impact on the zooplankton c o m m u n i t y (Neill 1981b; 1988a) unless Daphnia was absent (Stenson 1990). W h e n present i n large numbers,  Daphnia  dominate the dynamics of the community (Figure 1.7). M y goal is to determine if these communities, the one where Daphnia Chaoborus  does, are two different  dominate and the one  and independent  entities  with  where separate  structure and dynamics or if they are two facets of a single community w h i c h can switch between alternative domains of attraction.  Enclosure experiments using a gradient of disturbances have shown that i n environments  with  higher  nutrients  than  found  in  oligotrophic  lakes, 30  Chaoborus can have a large impact on the zooplankton c o m m u n i t y (Neill and Peacock 1980; N e i l l 1988a). These graded experiments suggested that the change from Daphnia to Chaoborus state is discontinuous, that is the response of the system is disproportionate  with  the  change  applied to  the  system.  The  zooplankton community can be, at least seasonally, switched to a state where predation rather than prey competition dominate the community dynamics.  Persistence of the predator state requires that the  starvation-prone  young  predator instars overcome a recruitment bottleneck generated by size-structured prey competition. Even w h e n young predator recruitment  is i m p r o v e d , the  predator state can persist only if the older larvae, n o w i n higher densities than i n the Daphnia domain, can survive through the l o w food period created by w i n t e r conditions. The predators must survive i n sufficient density to prevent rapid Daphnia population growth i n the spring and to allow rotifer populations to multiply prior to the next predator recruitment period. Thus, a feedback loop can be established w h i c h could promote persistence of the new state as an alternative domain of attraction to the Daphnia domain.  The mechanisms leading to the change i n community state and w h i c h led to the hypothesized conditions required for persistence  were uncovered  through  within-season (i.e., w i t h i n predator cohort) experiments (Neill and Peacock 1980; N e i l l 1981b; N e i l l 1984; N e i l l 1985). However, only experiments m o n i t o r i n g changes over several predator generations (i.e., between cohorts) can address the  31  persistence of the predator state. To test the hypothesis that the Chaoborus state is an alternative domain of attraction for the zooplankton community, I used field enclosure experiments to create a gradient along a disturbance strength axis. These experiments allowed me to assess the presence and relative location of the threshold i n community dynamics and to test the persistence and resilience of the Chaoborus state. Daphnia density reduction and predator additions generated a pulsed disturbance on the community. I monitored c o m m u n i t y responses i n the enclosures and the lake over three years using a variable sampling i n t e r v a l to address community dynamics at different time scales through the seasons. A s a complement, I used a laboratory experiment to better evaluate the ability of the predator to survive i n cold temperature at l o w food level (winter conditions). I n this chapter I address the impact of the enclosure experimental treatments on the predator dynamics.  2.2 MATERIAL AND METHODS I briefly present the main methods used i n this study. The detailed descriptions are presented i n the sections below. Experimental enclosures were set i n Shirley Lake, B.C. (see section 2.2.1) to test the presence of the alternative predator state and to determine  its persistence. Experimental treatments  included partial  Daphnia removal, predator additions and nutrient additions (see section 2.2.2). The lake and the enclosures were monitored for three years during the ice-free season following an adaptive sampling design where the sampling pace v a r i e d 32  depending on predator developmental stage and water temperature (see Section 2.2.3). The zooplankton community was sampled by hauling vertically a 102 i i m mesh zooplankton net for the predator and large zooplankton such as  Daphnia,  and a 50 u m mesh zooplankton net for rotifers (see section 2.2.4). P h y t o p l a n k t o n was sampled using a small diaphragm p u m p to collect water from 1 m layers from the surface d o w n to 3 m (see section 2.2.4). Temperature was sampled o n each sampling date while water for nutrient analysis was collected twice per year in June and i n October (see section 2.2.4). Techniques for counting predators are detailed i n section 2.2.4 while those for counting zooplankton and rotifers are presented i n section 3.2.2. Predictions based on the experimental  design are  presented i n section 2.2.7.  2.2.1 Field site and enclosure design Shirley Lake (Figure 2.1) is a small, fishless, oligotrophic,  mountain  lake  ( N 49° 20' 42", W 122° 33' 37") i n the M a l c o l m K n a p p Research Forest (Maple Ridge, B.C.) of the University of British  C o l u m b i a (Vancouver, B.C.). The  composition of its zooplankton community is similar to that of its close neighbor Gwendoline Lake (where the community interactions  had previously  been  worked out) prior to 1982, after w h i c h fish introduced i n 1979 had modified the zooplankton community. The zooplankton community i n the limnetic zone of Shirley Lake is composed of several species of rotifers, cladocerans, copepods, and aquatic insects. The rotifers included several genera of solitary rotifers,  Keratella  33  Figure 2.1  M a p of Shirley Lake in the M a l c o l m K n a p p U B C Reseasch Forest, M a p l e Ridge, B . C . , Canada (after Butler, 1990)  and Kellicottia  (Brachionidae), and Polyarthra  one colonial genus, Conochilus  (Synchaetidae) (Figure 1.2), and  (Chonochiloidae). Cladocerans included several  different genera of w h i c h Daphnia (Daphnidae) (Figure 1.3) was found to be the predominant one. Holopedium appeared regularly, sometimes i n h i g h numbers, but seemed to play a minor role i n the c o m m u n i t y  functioning as a weak  suspension feeder and competitor. It was w e l l protected i n its gelatinous coating. Bosmina (Bosminidae) and Diaphanosoma (Sididae) were found to be rare i n the lake. Copepods included mainly two species of calanoid copepods,  Diaptomus  kenai and D. leptopus (Diaptomidae), w i t h the occasional presence,  at l o w  densities, of a cyclopoid copepod, Cyclops (Cyclopidae). The m a i n aquatic insect larva found i n the samples was the dipteran Chaoborus called the phantom  (Chaoboridae), also  midge. Notonectids (Hemiptera: Notonectidae), and  occasional d i v i n g beetle (Coleoptera: Dysticidae) were also found samples. N o fish occurred i n Shirley Lake and salamander larvae  in  the  some  (Ambystoma  gracile) were present. The generalities about the life style and life history of the rotifers, Daphnia and Chaoborus, the m a i n players i n the community dynamics, were described i n Chapter 1. Details of the life histories of the predators specific to Shirley Lake are described below.  In Shirley Lake, the life history of C. americanus (Figure 2.2 A ) followed a pattern w i t h pupation i n June (Figure 2.2 B) and one generation per year, similar to that described above for studies  done previously on neighboring lakes i n  the  Research Forest (Teraguchi and Northcote 1966; Fedorenko and Swift 1972; N e i l l  35  Figure 2.2  Life histories of Chaoborus americanus and C. trivittatus in Shirley Lake from spring 1992 to spring 1995  Fourth instar  Third instar  Second instar  ^- americanus C. trivittatus  Pupation t i m i n g  1992 MJ JASON  1993 AM JJASON  i <i •i >i 'i «• ii. »i |  First instar (both species)  1994 1995 AMJJ A SON .... AM J  C. americanus  t  :i (  120  210  300  ..JI. 390  480  _j  i*  570  660  A' I \ 750  840  930  1020  1110  1200  1290  • • i—  1st instar  MJJASON  120  210  1992  300  AMJJASON  390  480  570  1993  660  AMJJASON  750  840  930  1994  1020  AMJ  1110  1200  1290  1995 36  1988a; 1988b). C. trivittatus,  however,  showed  a different  life history  than  observed i n those lakes. In Shirley Lake, C. trivittatus had two pupation periods per year, i n early spring and i n mid-summer (Figure 2.2 B). This generated a n unusual life history w i t h more than one peak per instar, and w i t h second and third instars present overwinter i n addition to the fourth instars (Figure 2.2 C). I have not been able to determine if C. trivittatus i n Shirley Lake has a one-year or two-year, or an even more complex life history. The life history of C. trivittatus, although unusual, leads to the presence of fourth instar larvae year round just as in the lakes w i t h the two year life cycle.  In Shirley lake, I set up field experiments i n large enclosures where I generated a series of different  initial  conditions. I gathered  information  on  inter-year  dynamics, such as predator overwinter s u r v i v a l , and on intra-year dynamics such as early summer young predator recruitment.  I installed ten enclosures (Figure 2.3) i n the spring of 1992 before the start of the reproductive period for the predatory aquatic insect, Chaoborus. The enclosures were translucent and made of 4 m i l w o v e n , white polyethylene plastic. They were sewn by False Creek Industries (Vancouver, B.C.), into cylindrical bags w i t h a bottom sheet to close them off to the sediment (see A p p e n d i x A for details of enclosure design). The top of the enclosure (first 1 m) was made of yellow-coated polyethylene plastic to better resist U V light damage w h i c h , otherwise, renders the plastic brittle and prone to breaks. The yellow plastic was sown into a sleeve  37  Figure 2.3  Enclosure set up and experimental design  Experimental set up diagram •.Lake station 2 Medium predation Low nutrient p  High predation Low nutrient  Low predation High nutrient  Low predation High nutrient  Low predation Low nutrient  Low predation Low nutrient  Medium predation Low nutrient  Lake station 3. High predation High nutrient  •..Lake station t' High predation Low nutrient High predation High nutrient 38  in which an extruded polyurethane plastic float (17.5 m long X 15 c m high X 5 c m wide) was inserted to keep the enclosure afloat i n the lake. Each enclosure (5.6 m in diameter, 4 m deep) contained approximately 95,000 litres of water. Each enclosure was surrounded and attached to an hexagonal 2X4 inches cedar w o o d frame to protect them from floating debris, and allow boat docking w i t h o u t damaging the enclosures. The enclosures were installed i n two side-by-side columns i n the middle of the lake (Figure 2.3), maintained i n place by ropes tied to shore and by cement block anchors on the bottom of the lake.  Unfiltered  water from  the lake was p u m p e d  into the enclosures  by five  diaphragm pumps w i t h 7.5-cm diameter hoses. Each p u m p was used to fill two adjacent enclosures i n alternation over several hours to provide equivalent mixtures of zooplankton (see A p p e n d i x B for details). After filling up, enclosure communities  were allowed three weeks to acclimate, before  the  predator  additions were started.  2.2.2 Experimental design  Experimental treatments included first Daphnia reduction, followed by predator enhancement  and nutrient increase to insure that a Chaoborus state could be  generated i n at least some of the enclosures. The goal was to investigate the conditions required for persistence of the Chaoborus  state over one or m o r e  continuous Chaoborus generations. Simply by p u m p i n g water containing the zooplankton community into the enclosures, I achieved i n all of them  a 39  fortuitous but substantial Daphnia reduction (Figure 2.4). These reduced Daphnia populations, lower than i n the lake, were allowed to grow for three weeks and were subsequently suppressed further by additions of different levels of predators and nutrients to create the final experimental design. W i t h i n the predation and nutrient addition experiments (see Table 2.1), I used different levels of treatment to explore aspects of the resilience and resistance of the system and to try to locate the boundary between the Daphnia (competition) d o m a i n and the  Chaoborus  (predation) state. I randomly assigned each enclosure to a treatment c o m b i n a t i o n (predation X nutrient) using one of three predation levels (low, m e d i u m , high), and two nutrient  levels (low, high) (Table 2.1). H i g h and  low  predation  treatments at both levels of nutrients were replicated. If replicate treatments (predation X nutrient) were selected for the same c o l u m n i n the side-by-side enclosure set up (Figure 2.3), the draw was redone to assign a new location. Daphnia reduction and predator additions were one time pulse disturbances to create different initial conditions. Nutrient treatments were repeated additions to maintain two different productivity levels. The enclosures were then m o n i t o r e d for three years without restarting the experiments.  Predation levels were set once at the start of the three-year experiment by adding different numbers of fourth instar Chaoborus  larvae. To set up the required  predation levels, I collected predators at night from  the lake by towing a  Wisconsin type net w i t h a i m diameter mouth opening behind a boat w i t h a 3horse power motor. The animals were stored i n 20 litre carboys. They were sorted  40  Figure 2.4  reduction: densities of Daphnia in enclosures after water pumping and before predator additions. Density in lake for the same time period is provided for reference. Daphnia  10  3  Daphnia CO  I  g •i  i o M  T3  -a 1  .ft:  Lake  ft"?l  ft'  9  10°.  ft"  ft^  10 J  B  fti fti fti ft' ft' D  ft' ft' fti ft' fti fti  si G  H  I  |  J  pumping pairs  41  Table 2.1  Experimental design for predator and nutrient additions.  Predation ( X lake level):  2-3 LOW  6-8 MEDIUM  13-16 HIGH  LOW  C, J  F  A, D  HIGH  B, G  I  E, H  Fertilization: (0.02ug P / L; N:P =30)*  (0.2ug  P/ L; N:P =30)  * added at start for a few weeks; nutrient additions were then stopped to maintain nutrient level close to lake levels  42  in the lab to remove most prey, and kept cold till they were returned to the field site, w i t h i n 60 hours from capture. The water containing highly concentrated Chaoborus densities was split at lake side into equal amounts and added to the different enclosures until the different predation levels were obtained. T h e entire process, from  Chaoborus  captures and sorting to introductions, was  accomplished over a 9 day period (May 14 - 22,1992).  Once fourth instar predators had been introduced to the enclosures they were allowed to finish their life cycle without interference. Note that recruitment of first instars early each summer was done naturally. A e r i a l adults from the lake and surrounding area, not only those emerging from w i t h i n an enclosure, contributed the eggs for the new cohort i n this enclosure. Egg deposition was assumed to be random between enclosures. I personally observed numerous egg rafts deposited on the water surface i n all enclosures and on the lake. There seemed to be no preference on the part of laying females for enclosures w i t h good rearing conditions. For example, eggs were laid even i n enclosures where, over time, prey populations failed altogether. Thus, larval recruitment of instars other than the first instar i n an enclosure is most likely due to higher l a r v a l survival and not higher egg deposition from emerged adults of the p r e v i o u s enclosure generation.  The fertilizer additions were started i n July 1992 and were repeated regularly. The aim  was to maintain  two  different  levels  of nutrients  throughout  the  43  experimental period: l o w nutrient levels as i n Shirley Lake and h i g h n u t r i e n t level,  above  the  Shirley  Lake nutrient  concentration.  The  low  nutrient  enclosures received additions of potassium phosphate ( K H P 0 ) and s o d i u m 2  4  nitrate ( N a N 0 ) based on adding 0.02 ug P l " week" i n an atomic ratio of 30 N : P . 1  1  3  The low nutrient enclosures received weekly nutrient additions till the end of July and then they were not fertilized again i n an attempt to keep the n u t r i e n t levels as l o w as i n the lake. The h i g h nutrient treatment received weekly or b i weekly fertilizer additions (depending on the sampling interval) based on 0.2 fig P l " week" i n an atomic ratio of 30 N : P . Both fertilization levels are relatively 1  1  low on the oligotrophic to eutrophic scale. Based on a pilot experiment I d i d i n the year previous to this experiment, I found that the use of nutrients concentration of 2 (ig P l " week" 1  1  at a  (atomic ratio of 30 N:P) w o u l d generated blue-  green algae bloom and the collapse of the zooplankton community. To a v o i d this undesirable state, I limited the nutrient  levels to the levels m e n t i o n e d  above.  In addition to the enclosures, three permanent lake stations were sampled and their location was marked w i t h a float anchored to the bottom of the lake (Figure 2.3). I w i l l report here only the results for the deepest station, Lake Station 2. Because Shirley Lake is small, the three station were close to each other (25-30 m apart). N o difference in species composition was recorded i n samples where a l l three station were counted. Qualitative differences observed i n z o o p l a n k t o n density were temporary and generally occurred at the onset of the increase phase 44  of a species population dynamic i n the spring. Station 2 was sampled from 0-3 m to compare w i t h enclosure  samples  and from 0-6 m  to record additional  information on Chaoborus life history i n Shirley Lake.  2.2.3 Variable sampling interval: towards an adaptive sampling design  Chaoborus,  zooplankton, rotifers, phytoplankton and water temperature were  sampled between M a y 1992 and June 1995. Nutrient samples were taken i n June and i n October each year. The ice-free sampling season started i n M a r c h / A p r i l and ended i n October/November (see section 2.2.4 for Chaoborus field s a m p l i n g methods and section 2.1.1 for other  field sampling techniques).  I chose a  sampling design w i t h a variable sample interval for three reasons.  First, slow dynamics (long time scales) can be followed using long s a m p l i n g intervals  while fast  dynamics  (short  time  scales)  require  short  sampling  intervals. Zooplankton communities have the potential to respond n o n l i n e a r l y to even small disturbances i n environmental or biotic conditions, thus dynamics could suddenly change gear from slow to fast. Second, generation times between species can differ resulting i n dynamics functioning at different time scales, often simultaneously. Third, under  the  influence  of environmental  factors  (e.g.,  temperature), generation time w i t h i n a species can vary from season to season or lead to population dynamics (e.g., Daphnia  population bloom, or  Chaoborus  reproduction) taking place on different dates from year to year, both of w h i c h require distinct sampling intervals rather than an average regular s a m p l i n g 45  interval. I adapted, for m y study, a general design w i t h variable  sampling  interval as suggested by Ouimet and Legendre (1988). The sampling i n t e r v a l varies depending on the levels observed for a specific variable such as presence or absence of certain species or instar, or such as chosen levels of biomass for a species or of an abiotic factor.  Thompson (1992) refers to sampling designs w i t h variable pace as  "adaptive  sampling". H e emphasized that this type of sampling design maximizes  the  information gathered and m i n i m i z e s the costs, while allowing one to follow organisms or dynamics w h i c h are variable i n time a n d / o r space. A d a p t i v e sampling designs allow efficient  sampling of systems w i t h a potential  for  nonlinear responses, however the rules pointing out w h i c h sampling interval to use should be decided a priori.  I designed my sampling plan as follows. First I chose a m i n i m u m sampling interval: once per four weeks, w h i c h I refer  systematic  to hereafter  as  the  "monthly" sampling. Second, I varied the sampling interval I used depending on the period i n the life history of Chaoborus, and on temperature. The m o n t h l y samples included daytime sampling of all the variables (water temperature, phytoplankton, rotifer, zooplankton and Chaoborus), Chaoborus  and night sampling for  older instars. T h i r d and fourth instar Chaoborus  vertically migrate  (Teraguchi and Northcote 1966; L a R o w 1968; Fedorenko and Swift 1972; Swift 1976). Descending deeper as light increases, they spend the day near the bottom of  46  the lake, while at night they gather and feed i n the surface layers, at w h i c h time I sampled their densities more accurately. The monthly  night samples  were  collected on the same date as the daytime samples. The initial monthly s a m p l i n g date for each year was chosen i n such a way that most monthly sampling dates for that year w o u l d fall closer to the new moon than to the full moon. S a m p l i n g intervals were shortened  during Chaoborus  reproduction period and y o u n g  instar growth, and as temperature warmed up i n the spring and early summer. I lengthened the interval i n late summer and fall as water temperature cooled d o w n and community dynamics were expected to slow d o w n .  D u r i n g Chaoborus emergence, and d u r i n g the period w i t h first and second instar stages, dynamics take place at a faster  pace and  sampling was  adjusted  accordingly. These high intensity samples were collected only d u r i n g daytime because the young Chaoborus  instars  do not migrate at that time  of the  year(Goldspink, 1971; Parma, 1971; Fedorenko, 1975a; Pastorok, 1981; but see comments i n A p p e n d i x C on y o u n g instar reverse diel migration i n the fall).  I sampled the daytime categories mentioned above weekly d u r i n g  Chaoborus  pupation, semi-weekly (twice per week) during the first instar period, and back to weekly during the second instar phase. D u r i n g the third and fourth instar stages, I sampled bi-weekly or monthly depending on water temperature. In 1992, the first year of the experiment, I sampled weekly through the entire season, and semi-weekly during the Chaoborus  reproduction period, to record a m o r e  47  detailed picture of the seasonal dynamics and acquire basic information on the behavior of the community i n Shirley Lake.  The adaptive sampling design ensures that samples are collected i n relation to dynamic events rather than to the calendar, and that important events are not missed, even if for example they are delayed by environmental factors. T h i s means that not all of the samples collected need to be counted. A g a i n I used a n "adaptive" strategy to choose the samples to be counted (see section 2.2.4 for details of the counting method). One replicate sample for the full series of monthly samples were counted. Furthermore, for June and October of each year, the second replicate monthly samples were counted. Where change i n density was large, bi-weekly, weekly a n d / o r semi-weekly samples were counted required. Due to time limitation, I was not able to implement a full  as  adaptive  sampling strategy for counted samples.  2.2.4 S a m p l i n g methods, identification, and counts for Chaoborus: Below I describe methods relating to Chaoborus  sampling, identification, and  counting. I detail the methods relating to zooplankton, and rotifer sampling and counts i n Chapter 3.  Chaoborus  were collected, i n the lake and i n the enclosures, by hauling a  Wisconsin type zooplankton net (mesh size: 102 \im; m o u t h diameter: 0.4 m ) vertically from 3 m to the surface. M e a n sieving efficiency for the net was 48  determined i n 1992 w i t h an electronic flowmeter outfitted on the net r i m w i t h w h i c h ten readings were made and averaged. The zooplankton net was new and sieved at a mean efficiency of 95%. The volume sampled was approximately 377 1. Complementary samples were taken on some dates where I collected hauls, at the deep lake station 2, from 6 m to the surface. Day samples were generally taken between 10:00 and 13:00, while night samples were generally collected between 23:00 and 1:00 Pacific Daylight Saving time. Samples were preserved i n 100 m l glass jars w i t h plastic lids, using 5% sugared formaldehyde solution.  Chaoborus identification was done under a W i l d M 5 stereoscope at 12X to 40X power depending on the instar, and under a N i k o n inverted microscope at 100X for pupal species identification using Saether  (1970) and Borkent (1979). T o  identify larvae to species, I used Fedorenko and Swift (1972). First instar larvae are indistinguishable between species (Fedorenko and Swift 1972).  Counts were done i n grided petri dishes (Edmonson 1971b) under a W i l d M 5 stereoscope. Chaoborus third and fourth instar larvae were counted at 12X i n entire samples. Samples w i t h large numbers of first and second instars were split using a 250 m l Folsom plankton splitter (splitting wheel) w i t h 4 divisions (4 X 1/4 subsamples) (Edmonson 1971b). They were then counted at 12X a n d / o r 25X. The data were used to produce a three-year time series for each larval instar of each Chaoborus species, data on w h i c h results from section 2.3 are based. I  49  present the detail of these time series and some idiosyncrasies of  Chaoborus  dynamics through time i n A p p e n d i x C .  2.2.5 Laboratory experiments I set up laboratory experiments to investigate the overwinter s u r v i v a l abilities of fourth instars of Chaoborus americanus and C. trivittatus w i t h and without food. Hypothetically, if the predator can survive overwinter at h i g h density, the topd o w n signal can be passed from one predator generation to the next, and the predation state can persist as a potential domain of attraction.  Just before the lake froze at the end of N o v e m b e r 1992, I collected fourth instar larvae from Shirley Lake, at night, using the 0.4 m  Chaoborus diameter  Wisconsin type zooplankton net w i t h a 102am mesh size. I stored the collected larvae i n environmental chambers at 5°C, i n 20 1 plastic containers filled w i t h lake water containing a high density of zooplankton. After two days, I selected individuals w i t h visible food in their crop or gut. I set the larvae i n d i v i d u a l l y i n 150 m l plastic containers filled w i t h lake water filtered through 20 u m m e s h netting and assigned them randomly to " F E D " or " N O T F E D " treatments. I put all the larvae i n a single environmental chamber at 5°C, i n the dark (0 hr. light : 24 hr. dark) to simulate winter conditions under ice i n the lake. I recorded the status of each larva weekly: alive or dead, w i t h / w i t h o u t food i n crop or gut, and its life stage (larva, pupa, adult). In the " F e d " treatment, I also recorded the number of dead a n d / o r eaten prey, and replaced them w i t h fresh prey. Prey 50  consisted of a variety of nauplii,  small  copepodites or adults of Diaptomus  Daphnia,  leptopus,  other  small  cladocerans,  depending on availability. I  terminated the experiment w h e n the last larva finally pupated, 70 weeks f r o m the start of the experiment.  2.2.6 Initial experimental conditions and general seasonal patterns in enclosures  Predator additions, w h i c h included fourth instars of both C. americanus  and C.  trivittatus, were finalized on M a y 22, 1992. The first night samples, to evaluate initial predator experimental levels and monitor the system's responses, were taken on M a y 26, 1992, four days later (Figure 2.5). I averaged the density measurements of two night sample replicates for each enclosure and for the lake station. Fourth instar Chaoborus density i n Shirley Lake was 42,individuals m " . 3  M e a n densities for the four l o w predation enclosures varied from a m i n i m u m of 84 to a m a x i m u m of 139 fourth instars m "  3  (2-3 times lake density). M e a n  densities for the two m e d i u m predation enclosures were 289 and 361 fourth instars m" (6-8 times lake density). The four h i g h predation enclosures showed, as expected, the highest mean densities and the greatest variability, w i t h levels varying from 549 to 703 fourth instars m " (13-16 times lake density). Predator 3  density between predator treatment  levels were distinct ( A N O V A  on  the  logarithm of the density: d.f. (2,7); p « 0 . 0 5 ) . A clear predator density gradient was thus set (Figure 2.5).  51  Figure 2.5  Initial densities of fourth instar predators i n ShirleyLake and i n the enclosures on M a y 26th, 1992. Data points represent means of two replicate night samples per station.  1992 Predator additions ^  Low  Medium  High  10 - i 3  CO c X!  o  CO co  "° e:  g S  • •  3 .S—^ -t-»  •  CO  o  fin 10  ~i  I — I — I — I  L 2 C J  I—I  B G F I  1 — i — i — r  A D E H  Lake station and enclosures  52  The combination of Daphnia  density reduction through  p u m p i n g and  the  predator density gradient through additions of fourth instars resulted i n Daphnia densities lower by 65% to 99% i n enclosures than i n the lake at the beginning of the experiment (Figure 2.6).  C. americanus life history pattern i n the enclosures was roughly the same as i n the lake (see Section 2.2) w i t h a single reproductive period per year i n the summer. However, C. trivittatus d i d not recruit w e l l i n the enclosures. T h i s species d i d not survive past mid-summer 1992, leaving C. americanus  as the  main predator i n the enclosures. Thus, w h e n comparing total numbers predators, this total includes both C. americanus  of  and C. trivittatus for the lake  data, while i n the enclosures, the total number of predators includes both species up to mid-1992 and thereafter includes only C. americanus.  Over the three year monitoring period, 1992 to 1994, different  enclosures  maintained their community for different duration (Figure 2.7). T w o enclosures, A and F, w h i c h had been filled w i t h the same p u m p (see A p p e n d i x B), failed w i t h i n two months  (mid-summer 1992) of the start of the experiment. A n  enclosure was deemed to have failed w h e n it lost its predator cohort, i.e. w h e n the density of predators i n the enclosure was m u c h lower than the lake predator density. Enclosures A and F d i d not recruit a new predator cohort because of prey population failure. I do not use the results from these two enclosures i n analysis.  53  Figure 2.6  Fvl  Large prey density reduction: percentage of Daphnia density removed from enclosures relative to Daphnia density i n the lake after predator additions (May 26th, 1992)  H  Low predator additions  C  J  Medium predator additions |  B  G  F  I  A  D  E  High predator additions  H  Enclosure  54  Figure 2.7 Duration of Chaoborus populations in experimental enclosures and in Shirley lake.  High Nut.  X  a CO  X  Low Nut.  §  HighNut. I  c o  CO  Q UJ  Low Nut. F  CC  "D  a> a.  High Nut  Low Nut.  Lake -mr A MJ J A SON  i i i i i MJ J A S O N  92  93  94  55  Three of the four low predation enclosures (C, B, G), the m e d i u m  predation  enclosure (I) and one high predation enclosure (D) had functional  Chaoborus  populations until mid-summer 1993 (Figure 2.7). In enclosure J (low predation), the Chaoborus population d w i n d l e d i n early summer 1994. T w o h i g h predation Chaoborus populations (E, H ) lasted till early and mid-summer 1994 respectively. Chaoborus lake populations persisted through the whole study period. Note that enclosure failure most often occurred i n mid-summer, during the young instar recruitment (Table 2.2). This was usually accompanied or preceded by failure i n prey populations and by visual cues such as proliferation of blue-green colonial green algae i n sufficient densities as to reduce light penetration  and depth  and reduce the sieving capacity of the sampling nets. Thus, i n the results section presented below I make use of different enclosures to address the c o m m u n i t y dynamics over different periods of time.  2.2.7 Predictions based on experimental design I test the hypothesis that the zooplankton community  i n Shirley Lake can  function i n two different domains of attraction. The zooplankton c o m m u n i t y i n the enclosures should be able to switch from the Daphnia domain, as found i n the lake, to the Chaoborus functioning).  state (see Section 2.2, for details of c o m m u n i t y  The latter must persist for several predator generations  to be  declared an alternative domain. If persistence is not achieved, Chaoborus state is considered a transient state of the Daphnia domain, i.e., a non-persistent  state  w i t h a different functioning than that of the Daphnia domain. 56  Table 2.2  T i m i n g of enclosure recruitment failure  YEAR  at C l stage  at C2 stage  at C3 stage  at C4 stage  92  —  —  —  93  —  B  —  94  —  A, F CAGJ E,H,J  —  —  The switch to Chaoborus state requires i m p r o v e d young predator recruitment i n relation to decreased Daphnia densities and enhanced solitary rotifer densities prior to the young predator recruitment period i n the summer (Table 2.1). T h e persistence of the state necessitates that fourth instar larvae possess the ability to overwinter i n high densities such that they can prevent rapid population g r o w t h of Daphnia early i n the season.  Experimentally, communities  I imposed  a predator  and monitored  density gradient  on  the  enclosure  the transmission of this signal through  the  different life history stages of the predator and the related prey dynamics. I made the following predictions for the predator and prey dynamics (Table 2.3). In terms of predator dynamics, under the two d o m a i n hypothesis, I expected that m o r e fourth instar predators i n the spring w o u l d generate more young recruits i n the summer and more fourth instar larvae i n the subsequent spring, not because of more eggs but because of better survival. Thus, I expected for both size categories that densities w o u l d be higher i n the enclosures than i n the lake. I also expected higher densities of predators i n the high predator treatments than i n the l o w predator treatments i n relation to the imposed predator density gradient. I n other words, correlations between the predator gradient and the recruitment of young instars i n the summer  and the s u r v i v a l of fourth instars until  the  subsequent spring should be positive.  58  Table 2.3  Predictions for the relationships in predator densities and in prey densities between the lake and the enclosures, and between the low and high treatments in relation to the experimentally imposed predator gradient.  Hypothesis: Under reduced Daphnia density and enhanced predator densities, all enclosures are expected to cross the threshold and switch to Chaoborus state  Variable  PREDICTIONS  Lake vs. Enclosures  Predator Dynamics  Prey Dynamics  Y o u n g predator recruitment density  Enclosures: L o w vs. high  Correlation with predator gradient  Lake < Enclosures L O W < H I G H  +  Fourth instar density Lake < Enclosures L O W < H I G H in spring prior to recruitment of y o u n g instars  +  Daphnia density prior to recruitment Lake > Enclosures L O W > H I G H of young instars  Solitary rotifer Lake < Enclosures L O W < H I G H density prior to recruitment of y o u n g instars  -  +  59  I included here, for the sake of completeness, the predictions for the prey dynamics, although those w i l l only be addressed i n Chapter 3. I expected a negative correlation between the predator gradient and Daphnia  densities, and a  positive correlation between the gradient and the solitary rotifer densities. T h u s , I expected to find higher Daphnia  densities i n the lake than i n the enclosures,  and i n the l o w predator density treatment than i n the high treatments. I expected the solitary rotifer density dynamics to be inversely related to the  Daphnia  population dynamics and to follow the same type of patterns as described for the predator dynamics above, that is higher densities i n the enclosures than i n the lake, and i n high predator treatments than i n l o w treatments.  A l l of the predictions above for the predator and the prey dynamics must be met to support the hypothesis that the zooplankton c o m m u n i t y i n Shirley lake has two domains  of attraction based on a switch between  the  dominance  of  competition and predation processes.  60  2.3 R E S U L T S  Predator additions resulted i n substantial impacts on the community dynamics in the enclosures while nutrient additions provided divergent dynamics w i t h i n treatments.  For example, the time series representing fourth instar  predator  larvae i n l o w predator treatments (see A p p e n d i x C-4, panel 2) are entangled throughout the season, irrespective of the nutrient treatment (Low: C , J; H i g h : B , G). Moreover, enclosure J, a low nutrient treatment, outlasted the h i g h n u t r i e n t enclosures (B, G), while enclosure C , its replicate lost its predator cohort early. Impacts of the nutrient additions on the enclosure community dynamics were inconclusive and were not analyzed further.  Predator additions i n spring 1992 affected differently the recruitment of each larval instars of the predator. I present the detailed time series based on predator densities for each instar and for each enclosure and the lake for 1992 to 1994 i n A p p e n d i x C ( C - l to C-4). The results presented below are based on these t i m e series to w h i c h I refer to underline specific observations as needed.  2.3.1  Second instar predator recruitment i n summer 1992: density, duration  A l l enclosures (8/8) shifted to higher densities of second instar larvae than i n the lake i n summer 1992 (Figure 2.8). The enclosures recruited 4 to 11 times higher densities of second instars than the lake. Moreover, h i g h predator treatments recruited, as predicted, higher densities of second instar larvae than the l o w treatment. 61  Figure 2.8  Recruitment of second instar predators i n summer 1992 i n relation to the density gradient i n fourth instar predators i n sprping 1992.  Regression lines (a)with and (b) without the Lake station data point (a) log Y = 1.71 + 0.573 log X ; R = 0.582; p=0.009 (b) log Y = 2.40 + 0.297 log X ; R = 0.429; p<0.001 2  2  Predator addition treatments Lake  Low  Medium  •  •  A  High •  10  4  Summer 1992 Second instar predator density (ind. m" ) io 4 3  A  3  • 10  2  10  1  10  10  2  3  Spring 1992 Fourth instar predator density gradient (ind. m ~ ) 3  62  I present i n Table 2.4 the statistical results from tests used to address the predictions presented previously i n Table 2.3. I also test one more variable, the duration of the recruitment period, the importance of w h i c h I d i d not establish a priori. I used a binomial test to address the significance of the number  of  enclosures w h i c h responded differently than the lake. I used the nonparametric M a n n - W h i t n e y U test for two samples to compare densities between replicated treatment levels (low versus high). I used correlation and linear regressions to test the direction and the strength of the relationship between the  predator  density gradient and the chosen variable i n the experiment, both i n c l u d i n g and excluding the lake data point. This allowed me to explore more systematically the presence of a difference i n d r i v i n g factors i n the Chaoborus  state. A l l tests  were one-tailed tests w i t h significance level set at a= 0.05. The same type of analysis was done for different stages i n the life history of Chaoborus.  A l l the tests on the second instar density data are statistically significant (Table 2.4). A l l predictions were met for a switch to and for the persistence of the Chaoborus state i n summer 1992. Enclosures recruited higher densities of young predators and so d i d the h i g h predation  treatments compared  to the  treatments. The linear regressions, w h i c h included l o w , m e d i u m  low  and h i g h  predator treatments, w i t h and without the lake data point, were also statistically significant, and the relation was positive as predicted. Thus, the increase i n fourth instar predator larvae i n the spring generated higher recruitment  of 63  S5 ^  •H + 01 T J  (5 ra  s  ra cu  © tH  44 ra  tf)  6  o  (5 ra  C ra  2 £  tH  r tf) S o tfi  ra H-»  tf)  c. o u  cu tf)  bO  o  "bJD  hJ  cu cu -t-> cu  T J  TJ  CU T J  (5  c  u «-»  w  jS «  G  cu 45  0)  45  CH  °0  T J  CU  Oi  tf)  ^  ^  tH  CH  o «  ON  CH r £  T J  • rH  tf)  O  HJ  II  II  r Q  T J  a,  o  CU  o o o  'tH  cu  CN  o o o  o  OH  u  u  o> oi  >  Oi  tf) S oi 3 W w  | tf)  ra C> w  >-.  tf) tf)  £ .2 ^ c tf) 2 £ -5 tH  ^  •rH rr<  CO  T J O  tf) tf)  "3 .S 01  X TJ  1°  01  45 cn bo T J  cu S5 be ra s5 ra r 45  u o cu  ^ s ° © oi  c  w  s  -K  cu 45  tf) -M cu cu  •4->  tf)  j  3 o  CH  O  «  f>T rH  ^  .429  'ATI  II  CO  rH  CH  'tf? 4->  CU  tf)  II  < N  j  rH  1  CH  CU  H-»  CU  H -rf  45  i  cu  CH  o •l-H  CH  tH  tf)  00  _o 'tf)  QO  <u  -<->  ra  tf)  a  tH  o  CH  CO  o  tf) tf) CU 1-1  • rH  00  tH  ra cu ,CH — 1  CH CH  ra  • rH  6 o CH  ra CU  1 •—1  ' H  pa  tH  T J CU  tf)  45  p  H->  tH  cn w & P  bO tf) (5 O  i 1 +1 cu  • rH  cu i  -1  tf) 01  cu  CU OH O  DH  o  cw  cu  cu  fi  In  >  >  CQ  red :tion  OI  1  CH  •«->  i-H  o (N  T J  o  CN  II  tH  ra  •rH  45 « oi  ^  CU CM  CU  m  £ 13  tH  •- 5  CO  II N  ial:  tH  ° <N  II  j  ' ree  H  s?  cu  rH  po siti  O  tH  •  •WhiLtnc  cn  CO LO  [IGH  tf)S  cu ^ co . cu  J  g v  V LOW  oi  0)  3  reer  TJ  <H-»  po siti  c  ial: !  H_>  CJ 4 - >  r-1 + ~.  AKE  45  cu cu  o o  r>.  CH CU  densit  c  aobo  X *- 'C &  isti sul  CU  TES taile  r>-(  tf)  IT) CO  o o o o ©  ON  -S  <  p  3O acu HUJ ow e v  ratio  V)  ' .15 cj\  cu 45  _ H  pa  AKE  ra  + +->  young predators i n the new cohort. The recruitment was proportional to the density of the fourth instar predator i n the spring.  Another factor indicative of an improvement  i n the conditions for y o u n g  predator recruitment is the duration of the recruitment period. The y o u n g predators are starvation-prone (Neill 1988a). W h e n food is limited, as i n the Daphnia  domain where rotifer populations are reduced by competition w i t h  Daphnia, most young predators w i l l not live long enough to grow and switch to the next instar. The recruitment recruitment Chaoborus americanus  period is truncated.  is expected to be shorter i n the Daphnia  Thus, the period of domain than  in  the  state. In the lake, i n 1992, the summer second instar peak for C. was restricted to June (Figure 2.2, top panel). In the  enclosures  (Appendix C-2, panels 2, 3, 4), the peaks were wider, lasting until July, w i t h some enclosures w i t h l o w density peaks extending into August. The duration of the main recruitment period for Chaoborus americanus  second instar (Figure 2.9)  was longer i n 7 out of 8 enclosures than i n the lake (one-tailed b i n o m i a l test: p < 0.035).  65  Figure 2.9 D u r a t i o n of the recruitment p e r i o d for second instar predators i n 1992. Longer periods with high densities of second instars indicate relatively better recruitment conditions than in the lake. Long periods of low density recruitment indicate conditions where food is sufficient for maintenance but not for fast growth to the next instar.  H i g h density period — ,  14  28  42  d  u  r  a  t  i  o  n  o  f  ^ second instar recruitment  L o w density period  0  ^  56  i  70  1  84  Duration (days)  1  98  1  r  112 126 140  2.3.2  Fourth instar ability to resist starvation: survival in the laboratory and i n  field experiments  2.3.2.1 Survival in laboratory experiments at 5 ° C  Survival  of h i g h densities  of Chaoborus  fourth  instar  larvae  until  the  subsequent spring is a key factor i n the persistence of the Chaoborus state. F o u r t h instar larvae must survive i n sufficient densities to significantly and negatively impact Daphnia densities prior to the recruitment of the new predator cohort. I n the fall, many zooplankton species, including Daphnia, retreat from the water c o l u m n i n the form of resting eggs. Thus over the winter, zooplankton food level availability is highly reduced for the predator Chaoborus. hand, water temperature development  and  is also lower (4°C). L o w temperature  survival  of predator  larvae  (see  Chapter  O n the other affected  the  4). A t l o w  temperature, the predator requires lower food levels for maintenance. L o w temperature  i n the spring also affected prey development  and p o p u l a t i o n  dynamics (see Chapter 3).  In the laboratory, I was able to test directly the ability of the fourth instar larvae to survive i n cold temperature w i t h ("FED") or without ("NOTfed") z o o p l a n k t o n food. The predator larvae were kept at a constant temperature of 5°C, i n the dark (for methods see section 2.2.5). A l l but one " F E D " larva survived for at least 30 weeks w i t h a median s u r v i v a l time as larvae of 36.5 weeks, while  "NOTfed"  larvae survived a m i n i m u m of 23 weeks w i t h a median time of 35 weeks (Table  67  2.5 A ) . There was no significant difference i n the median time that fourth instar larvae survived w i t h or without zooplankton food (2-tailed test: z=0.98; p = 0.327). Moreover, most fourth instar larvae were able to pupate at 5°C, w i t h or without zooplankton prey (Table 2.5 B). Surprisingly, over half the trivittatus pupae were able to emerge at such cold temperature.  Chaoborus  N o n e of C.  americanus pupae emerged. The fact that both species could pupate means that development still takes place even if the temperature is very l o w . However, the two species must have  different emergence  temperature  requirements  (see  Chapter 4). In summary, Chaoborus fourth instar larvae for both species h a v e tremendous  ability to withstand starvation i n cold temperature.  survive a median time of almost 9 months  i n 5°C water even  They can when  no  zooplankton food is present.  2.3.2.2 Survival overwinter in field enclosure experiments  In the field, 7 out of 8 enclosures maintained higher densities of fourth instar predators over the winter than i n the lake (Figure 2.10). The 1:1 line on the figure indicates that densities i n the lake between the two years changed  little.  However, i n the enclosures, l o w predator treatments increased i n density i n 1993 compared to 1992, except for enclosure C w h i c h decreased to predator density similar to that of the lake. Interestingly, enclosure C had the lowest i n i t i a l Daphnia reduction level (65%) and the second lowest predator addition level (89 fourth  instar larvae  m" ) amongst  the  enclosures.  In m e d i u m  and  high  68  Table 2.5  Results from Chaoborus  overwinter  survival  laboratory experiments  on  A) Number of larvae at different stages B) Time alive as larva i n F E D and ' N O T F E D ' experiments for the total number of larvae (both species combined)  A) 5°C  Number of larvae Species  C. C.  at start  died  alive at end  pupated  emerged  24 25  4 2  0 1*  20 23  11 0  trivittatus americanus  *as p u p a not larva (pupated on week #69, last week of experiment)  B) A l i v e as L A R V A (larva to pupa) Total-FED Total-NOTfed  M e d i a n two-sample test:  TIME (weeks)  M i n . Time (weeks)  Max. T i m e (weeks)  36.5 35  8  52  23  68  Prob. > I z I = 0.3272  (S = 12; z=0.97980)  69  Figure 2.10  Chaoborus fourth instar densities i n spring 1993 relation to the experimental density gradient fourth instar predators i n spring 1992.  Regression line for enclosures (except C) log Y = 3.41 - 0.47 log X  Predator addition treatments  10  Lake  ^Low  Medium  High!  •  •  A  •  4  Spring 1993  Fourth instar predator density 10 (ind. m ~ )  3  3  io 4 2  io  1  Spring 1992  Fouth instar predator density gradient (ind. m ~ ) 3  treatments, predator densities declined from the level that had been imposed o n them experimentally, but they remained at densities 2 to 4 times higher than the lake. Table 2.6 summarizes the results of the statistical tests on the predictions made previously i n Table 2.3 i n relation to fourth instar predator dynamics. A b i n o m i a l test confirms that enclosures maintained higher fourth instar larvae densities than the lake. A linear regression including all enclosure treatments and the lake showed a positive trend between the experimental predator gradient and the density of fourth instar predator i n spring 1993 but was not significant (Table 2.6). Based on figure 2.10, enclosure C d i d not remain i n the predator state. Enclosure C was excluded from  the  l o w versus  h i g h predator  treatment  comparison meant to ascertain the dynamics w i t h i n the Chaoborus state. A onetailed Mann-Whitney test. There is a significant difference between l o w and h i g h predator treatments however all lowest ranks were found i n the h i g h treatments and all highest ranks were found i n l o w treatments, contrary to expectation. I analyze this pattern using a two-tailed linear regression on the enclosure data including the m e d i u m predator treatment. Enclosure C was excluded for the same reason as mentioned above. The linear regression was significant, h o w e v e r the relationship between treatments was negative, contrary to expectation. L o w treatment maintained higher densities of fourth instar predators than m e d i u m and high predator treatments.  The survival rate from second instar i n summer 1992 to fourth instar i n spring 1993 was higher i n l o w predator enclosures (26-41%) and i n the lake (26%) t h a n  71  co  CO  S  S p. o •a o  01  p-  cs +, •si tN  CO cn 3  ON PH T-H  o  o  ^  o  +  PC> T-H  U  bo c .£ -3 w  O  <3 U  lH  JS  £ ON T-H 60  .a -p  3 -a  PC co  a -a  TJ  CU  ,e  o to 00 <o a)  bog  cj  PJ  TJ  i—l T j  CO  C CS  'o  .  05  OH  s<  s a CO  •£S  CO  II  00  O  NO  ^  II  A d  rH II N  QJ TJ  >  II  £H  o 'co  aj  CO  QJ  Tj  PH  bO QJ  CD • pH  g o g  PH  OJ  QJ  w  O  P tn  * 2 *+H° * -S §~  O (A CU  .-s u (0  w  cu V  o CN  H  c  CN  P2  p*  CO  LO  CN  TJ QJ  01 VI  3  ON  H  3 o  S.S  CU  CN  CO  ^  CO CO II II ,  CO  -S  CO  H  *CO s-t-  cy  ©  cu  si  co «  o o  00 CO H LO o p + o ^ II  •+-» ^ to  'u cu  ^  CM  QJ  Si C co c 0 c  •PH  in  O  o  to <T> CU ON  -a ^  ID  73 cu P4  co  o O  5  pH  CC QJ  C  ca  O OH  pJ  E u  £ ~ 0 -H  ^  >  PH CO  CO  PC PC CJ • pH  PC  u  QJ PH CO  o E U p—i E v  w  <  lj5  QJ  OH O  o  co  S  QJ  OH  QJ >  2^ QJ * ^ b O cu  c c  PH  QJ  O  PJ  QJ > CO  O OH  PH  QJ b0  C TJ  ' u X QJ  i n the m e d i u m (11%) and the high predator treatments (6-9%). Enclosure C h a d the lowest survival rate (3%). Thus, the l o w predator treatments (excluding C) had survival rates from second to fourth instars similar to those of the lake, and higher than those of enclosures w h i c h received larger densities of predators initially (Figure 2.11).  In short, predator additions i n spring 1992 i n the enclosures led to higher densities of fourth instars i n the subsequent spring than i n the lake, except for enclosure C . Laboratory experiments showed that fourth instar predators have a strong ability to withstand starvation at cold temperature. For predator fourth instar larvae i n enclosures, survival over the winter period was not a problem. However, initially high predator treatments maintained  lower densities of  fourth instar larvae than initially low predator treatments, excluding C . S u r v i v a l before the winter period but after the second instar recruitment period was a critical point i n the persistence of the predator state.  2.3.3 A signal i n transition: third instar and fall fourth instar predator dynamics i n 1992 The spring predator density gradient imposed experimentally i n 1992 sent a disturbance through the community. By comparing the signal sent out and h o w the predator population responded sequentially through  each instar, I can  uncover the factors(s) leading to the fourth instar densities i n 1993, and the unexpected reversal between l o w and h i g h treatments.  Because o v e r w i n t e r 73  Figure 2.11  Proportion of second instars surviving to fourth instars (summer 1992 to spring 1993) i n relation to the density gradient in fourth instar predators i n spring 1992. (Survival in Low and High predator treatments are means ± 1 S.D)  50  Survival (%)  40  -I  30 H  20 H  •  Lake  O  enclosure C (low)  ^  Low (Mean, excluding C)  A  Medium  •  High (Mean)  io H  Spring 1992 predator density gradient (ind. m ~ ) 3  74  survival was not a problem for fourth instar larvae, the fourth instar densities observed i n 1993 must have been set earlier i n the life history of the predator. I determined where and h o w the signal changed by graphing the experimental response at different points i n the life history of C. americanus  (Figure 2.12).  Three panels have already been shown i n previous figures: the initial predator density gradient (a), the second instar (c) and the spring 1993 fourth instar (f) panels. The first instar information (panel b) is shown for continuity i n the data and the picture. First instar densities i n enclosures were higher than i n the lake. First instar larvae were not expected to exhibit the experimental gradient signal because of the random and donor-controlled nature of the egg laying w h i c h masks the survival process of the larvae. I looked at the third instar recruitment densities and the duration of the recruitment period using the same types of tests as in the second instar larvae analysis.  Third instar larval densities were expected to reflect the experimental gradient signal as d i d the second instar w i t h higher m a x i m u m densities i n enclosures than i n the lake and higher m a x i m u m densities i n the h i g h predator treatments than i n the l o w treatments. This was not the case. In total, 5 out of 8 enclosures had higher third instar m a x i m u m densities than i n the lake, w h i c h is not statistically significant. O n l y maximum  one  enclosure  recruited  substantially  higher  densities of third instars than i n the lake (Figure 2.12, panel d).  Between enclosures, there was also no significant difference between the l o w and high predator treatments. Thus, there was no significant relationship w i t h the  75  CO co  ON ON  pti  a K  T-H  bi)  5 * o c s Z « c <S  PH  Pl  C  C/JT  cy  CO  PC  CN  4J  rS  o  u -s o  PH  ON ON  cti  cy  co PH  JS rt  aa *2  £  fi  .3 <u  cn PH  P3 •4-1 CA  c  <U QJ  -=! ^ + . -> cu 0  TJ  **  H  b -S i ; cy  CA JH  to  CO  rH  •pH  CA  o  PH  _c  -t-» CN  f i g 1 S.g> PH  (Tj  r o  o  a>  u  rH  CJ  0) CD  P H  CO  O  •H  CL  Cr-  co S T " * u « -  C <£  w  "«  2 cu^ "rt  cy  r o  o Ts  CA  U  • PH PH  > < SJ  X  C8  -h  M)_S co • pH  p*H  tfl  h .5  CN rH CN  cy PH  60  pi  fN ON ON  O  H  bi) •PH  SH  P.  •U  ni TJ TJ crj CU  PH  PH CH  C/JT  e  . u i spnpiATpui  initial positive predator density gradient. N o n e of the changes i n density i n enclosures versus the lake and between enclosures were statistically significant (Table 2.7). However, the duration of the recruitment period  was longer i n a l l  enclosures (8 out of 8) than i n the lake (Figure 2.13). In some enclosures, t h i r d instars of C. americanus  were found late i n the fall (Appendix C-3), w h e n most  predator larvae were expected to have transformed to their fourth instar; some even survived overwinter. The third instar period seemed to be the time w h e n major changes took place i n the initial signal.  In the fall 1992, i n the new fourth instar cohort, the signal started to differentiate anew. Trends, although not statistically significant (Table 2.8), were apparent. F o r example, regression slopes were negative, opposite to the  original positive  predator density gradient. Between the fall and the subsequent spring, densities should have declined through mortality as no reproduction took place. Figure 2.14 represents the relative difference i n density between the fall peak i n 1992 and the spring peak i n 1993. Lake fourth instar densities declined by 39% between the fall and the spring. In enclosures, the response was surprisingly variable. T h e largest decline, similar to that i n the lake, was observed i n the h i g h treatment enclosure H (46%). Densities declined by 10 to 25%, i n three enclosures, and density declined by only 5% i n another one. M e a n w h i l e , densities increased i n two enclosures by less than 10%, and by almost 40% i n another  one. S m a l l  declines, and increases of any size i n fourth instar density i n the enclosures were unexpected as there was no reproduction period for C. americanus  i n the fall or  77  a t-  01  ra T J  cu  (5 ra  o  cu  S5  44  cu  4H  cu  cu  MM  TJ  45  ri  45 ^ TJ 15 Oi o> tf) g  O  • r-H  tH  u  oi Ol  > n  45  tf>  Oi tH  tH tH  OI g  o  ra « H->  tH  «) «5 « J2 CU  1* tn  O tH &H-2  45  *  4) tf)  HJ  T J  .-r.  bO O J  4-  o o  NO  CN  tH  cu T J  S5 «U  tH  ^ .2 ra T J cu  •JH  u cu tH  X  S «  3  4H  +-> cn  CO  +  Cfl  45 -C • i-H S5 ^ T J  cu  (5  bO  ra  ra is 45 o cj —H  II  ra tf)  II  CN II  M  00 II S5  II CH  cn cu  CU  cu  45  00 LO  T J  r2 •rH  CH  H  _o ra  C/3 cu W CH H  tH  Tcu J  45  tH  _o  o lCHj  cu  cn cu  CQ  o  c • rH CQ  CU  tf) tf) tH bC cu  b o cu  tH  tH  tH  tH  a o  (5  •rH  CU  *- cn  ra cu  ra cu  S5 cu  QH  o  c  CQ  2  cu  CJ CH  tf) Ol  > tf)  o  CL  cu  E > tf) t-H  E v O  rJ  TJ  01  o  S  P ."S cn g  o  1  00  tH  15  o>  00  'cn  O  r  CU  o  .2 6  cn  tf) cu  SP!i  • H M  ra i  C  CH O  • rH  tH  45 +•>  cu  00  o+ o rH rH  ON  tH  rJ  4->  "  TCH J  cu  C  X rH  > _ |  tH  Q-,  o  o  c  tf) g  x* O  CO  CL,  tf)  ~  jcu T J  cu  *I  T J  J^> -rH tf)  00  cu  CU  — '  "tH  cu  cu  U  ci cu  N  _o  45  tf)  H  CJ  M-l  T J  tH  (5 ra  45  J^>  42  cu  tf) g  3  bO  CH  .a -c  cu  44 ra  C  «  «  O  rH  iS bo  su  Oi  ON tH  H-»  cu  rH  U 2^  rH be  . „ 'cn  cu cu  15  45  +  45 tf) n S5  (5  TJ (5 ra  TJ fs|  1  .S  45  45  rt  r£J CD  £  • ?H  tf)  r C CN tH  T J  tf)  TJ  ^ rH  ON  tH  0)  0 -Q  U 2^  45 cu  45 u  -C) r H  © +  (5 ra  o -a o «  a t.  oj CJ  CM  15  v  O m  v> rt  0rJ tH  pa  < rJ  Figure 2.13  Duration of the main recruitment period for third instar larvae of C. americanus in Shirley Lake and in enclosures.  1992  •  1993  HA CT3 O C "•4—'  E  CTJ  CO _ T3 E CD 3 Q.T3  «s  1994  •  '  1  i: •! i! i!•:i:•:•:•:i:•!•!•!•:i:•!i!i! i! i! i: i! i :r  D  I  c o  "•4—»  CO T3 CD  B  C4 Lake -\ .  T—!—s—i—p-T—r"T""r™'r™'t  t  ~T~  0  T T x  y . y . y . y . y . y . y ,  1  2  1  ~~r 2  3  4  Recruitment period duration (Months)  79  cu  co S  CO  p. S  H->  -a  CO  P .  o  -a  H  § ,  a v. o -a o cs  PS;  CS  PH  -C  QJ  cj  PC  * pH  G  PH  PH  H p-H  r*  >^  oG CO  O P J  bO O  QJ Tj  QJ  T J  H J  II  X  QJ CS '— 1  to cu  ON ON  •+-> • PH  bog  cS  O  +  CN  _d l a PC +->  PC co  TS  TJ  CO  A  H-» CO  ca  H->  G -  o u  QJ  PH  rH  JS bfj  CO  cu  u  CJN  cu PH  TJ  i—1  CN  U £  v CO  U  +  CN  00  QJ  PC  PH  >  to to  QJ  PQ  O  -4-»  CU  'CO  > 2 CN - C ON ON  • PH  CU  cu *n  CO  to cu *H  n  HH  PH  PO O  <s  cu p« H  oo  H  "ce • i—t  ca ID  s  aj  o G  • i—i  o  CQ  QJ  PC  u  bO C  c  -t->  QJ •> QJ  QJ  H-» QJ  •PH  CO  H  >  PQ  G O  • PH CO CO  • rH  pH  PH  QJ  CO CO CU  bO  bO QJ  PH  PH  PH  ca  PH  G  QJ  QJ  QJ  OH  OH  o  O  ca  QJ  G  QJ  to cu  to G cu  TJ co 3 p.  o  C N  CU  LO  TJ QJ  PC  c QJ  00  X bO  bO G ca  P5H  II  O  a,  TJ  QJ TJ 'QJ > QJ  II  TJ PC QJ  G  £  G  ca  la  .O HH  CN T-H  P*  ON  H->  o  CO  <N  G  d  X, CJ  CO  II  QJ  QJ  CO  CN  CD  d  d II  ^  a  G  CO  H4  9  •rt co 15  8 r^l  O  PH  PH  J5  QJ CO  CO  ca  cu  CO  PH  co <HH  J5  pH  QJ TJ  w  HH  QJ  C  ca -4-t  u  CO  >^  M U  to cu  S  -pJ  (U  CO  o  X  QJ QJ  TJ  LO  d  H-» CU  00 LO  TJ QJ PH  CH  O -O  o «  >  co O  a,  QJ  TJ QJ H-> PH  QJ  > QJ PH  CO  ca  X, X cj  PC  u QJ PH  CO  O  G CD  V  QJ  bO OH  G  TJ  1J  X  O  QJ  Figure 2.14  Relative difference i n fourth instar Chaoborus density between fall 1992 and the subsequent spring (1993).  H E D  1  G B  C  L (50)%  (25)%  0%  25%  50%  Relative density difference  81  winter. N e w fourth instar larvae of C. americanus  might have been recruited  from the lengthy recruitment period for the third instar larvae, period w h i c h unexpectedly encompassed the winter and early spring (see time series for Chaoborus third instar larvae, A p p e n d i x C-3).  2.3.4 Result s u m m a r y Second instar predators i n 1992 responded as expected w i t h increased densities i n the enclosures (Table 2.9) and the signal recorded was positively related to the predator density signal set experimentally. Increased fourth instar larval density i n the spring enhanced summer recruitment of young predators. However, the subsequent third instar response was not related to the initial density gradient. Only recruitment  duration showed a difference between the lake and  the  enclosure community responses. In fall 1992, a weak signal reappeared i n fourth instar  larva  densities  but  the  trend  was  now  inversely  related  to  the  experimental gradient. Finally, the fourth instar densities i n the subsequent spring showed higher densities than i n then lake. The fourth instar predators had the ability to withstand starvation for long periods of time  at cold  temperature and survived overwinter at h i g h densities. However, l o w predator treatments maintained higher densities than the high treatments, reversing the expected trend. Thus, some  requirements  necessary for persistence  of  the  Chaoborus state (Table 2.3) were observed. However, these requirements p r o v e d not to be sufficient to allow persistence of the predator state over several predator generations. 82  Table 2.9  Overall results of the impact of the spring fourth instar predator density gradient on the predator dynamics throughout the life cycle Hypothesis: Under reduced Daphnia density and enhanced predator densities, all enclosures are expected to cross the threshold and switch to Chaoborus state  Variable  PREDICTIONS Lake Enclosures  Predator Dynamics  Y o u n g predator recruitment density  YES/NO vs. Enclosures: L o w vs. h i g h  Lake < Enclosures LOW < HIGH  Fourth instar density Lake < Enclosures in spring prior to LOW < HIGH recruitment of y o u n g instars  YES YES  YES NO  83  2.4 D I S C U S S I O N The persistence of the Chaoborus state as an alternative d o m a i n of attraction to the Daphnia domain requires first that young predator recruitment i n s u m m e r be enhanced and second, that fourth instar larvae overwinter w e l l at h i g h densities. Both of these requirements experiment.  However, these  were met  requirements  were  i n the not  first year of  sufficient  to  the  allow  persistence of the predator state over several generations. Developmental delays in the third instar, especially i n h i g h density experiments, counteracted  the  enhanced recruitment of first and second instar predators. The predator density gradient signal was strong enough to travel from one spring to the  next,  however, i n high density predator treatments, the strong signal introduced negative feedback and predator densities were lower than expected.  Increased predator  density i n the  spring led to i m p r o v e d  conditions  for  recruitment of second instar in summer. This, i n turn, led to higher fourth instar densities i n subsequent spring, except i n enclosure C , one of the l o w predator addition treatments. Enclosure C d i d not recruit fourth instar w e l l but did recruit second instar to a level comparable to that of the other enclosures. Thus, the community crossed the dynamical threshold from  the  Daphnia  domain to the Chaoborus state but the latter d i d not persist past the fall fourth instar recruitment.  84  The  limitation i n enclosure C pointed towards the possible location of the  threshold  between  the  Daphnia  domain  and  the  Chaoborus  state.  The  community i n enclosure C was started w i t h the lowest Daphnia reduction (65%) and the second least fourth instar density addition (2.1 times lake level) amongst my experimental enclosures. Based on experiments by N e i l l (1981b; 1985) i n enclosures i n Gwendoline Lake, these perturbations were unlikely to yield a switch to the predator state. N e i l l (1985) used Daphnia reductions (25%, 60%, 90%, 99%) as a method to perturb the zooplankton c o m m u n i t y i n his enclosure experiments i n Gwendoline Lake. H e reported that a 60% reduction was not sufficient to bring the community to switch states; a 90% reduction was needed. In his predator addition experiments (IX, 2X, 3.5X) (Neill 1981b), he showed that a 2 times lake level addition was not sufficient to change the community to the predator state. O n l y after additions 3.5 times lake level was the threshold crossed. In  enclosure  C, values  indicating the  presence  of the  threshold  in  the  community dynamics are w i t h i n a comparable range but tend to be on the l o w side of the range. Because I combined both types of treatments, the interactions potentially produced a stronger impact than each disturbance alone.  O n the other hand, the difference i n response could also be due to differences i n size and depth of the two lakes, or other local conditions. For example, as Shirley Lake is a m u c h smaller and shallower lake (1.2 ha; 10 m max. depth)  than  Gwendoline (13 ha; 27 m max. depth), it potentially had more nutrient available to the community, which could lead to greater zooplankton productivity. Thus if  85  Shirley Lake zooplankton community sat closer to the threshold, it might h a v e required smaller perturbations to switch states. G w e n d o l i n e Lake might require stronger perturbations than Shirley Lake to cross the threshold.  Finally, the lack of recruitment of fourth instar larvae i n enclosure C i n spring 1993 could have arisen i n at least two different ways. This enclosure might h a v e responded the least to the experimental disturbance, i.e. although it crossed the threshold, it might have remained close to it, i n w h i c h case a small disturbance could have reverted the community to the Daphnia domain. O n the other h a n d , the community i n enclosure C could have  simply d w i n d l e d away due  to  u n k n o w n factors, and was on its way to extinction w h e n sampled i n spring 1993, rather than displaying Daphnia domain characteristics. I cannot eliminate this explanation especially given that the community d i d not recruit second instars, not even up to lake level, i n early summer 1993 (Appendix C-2).  The see-saw i n predator densities between the l o w and the high  predator  treatments is a strong indication of the presence of the alternative attractor. L o w treatment fourth instar densities recruited higher densities i n 1993 than their initial predator densities i n spring 1992. H i g h treatment densities, on the other hand, recruited lower densities than their initial densities but remained  at  higher densities than the lake and thus d i d not return to the Daphnia d o m a i n . The p u l l i n opposite directions points to a potential attractor located at a different density level than the Daphnia domain i n the lake.  86  In the enclosures (excluding C), s u r v i v a l from second instar i n summer 1992 to fourth instar i n spring 1993 was inversely proportional to the initial  predator  density gradient set initially i n spring 1992. This density-dependent relationship indicates an upper limit to predator density i n the predator state. This key result, combined w i t h information on prey dynamics presented later i n Chapter 3, w i l l have important implications concerning persistence of the Chaoborus state  The negative impact of initial predator density on the final density of fourth instar larvae d i d not take place overwinter. Fourth instar larvae are h i g h l y resistant to starvation at cold temperature. C o l d temperature allowed Chaoborus to survive well overwinter. Bradshaw (1969; 1970) indicated that larvae enter a quiescent phase, a winter diapause, although an "active" one. M y o w n laboratory observations showed that, under winter conditions, the animals were still active. They ate fewer prey than at warmer temperature (pers. observ.), and  they  developed and pupated at a slower rate (See Chapter 4). Because fourth instar larvae have lower respiration rates i n cold temperature (Swift 1976) and greater assimilation rates (Giguere 1980a; Giguere 1981), larvae needed less food and could survive under lower prey density. In A p p e n d i x C-4, I showed a dip i n larval density i n samples from 0-3 m . There was a decrease i n October-November and an increase i n A p r i l - M a y although no reproduction took place between these dates. W h e n larvae do not need to feed they stay near the bottom of the lake, beyond the reach of the sampling net. This is one explanation for the dip i n  87  sampled  numbers  observed  i n the  winter.  L o w metabolism  and  higher  assimilation rates i n cold water allowed fourth instar larvae to survive w i t h little or no food for several months (Table 2.5 A ) . Chaoborus can thus s u r v i v e from late fall to spring even w h e n prey densities are low. The negative densitydependent impact must have taken place prior to entering winter conditions.  A long recruitment  period relates to i m p r o v e d recruitment  conditions for  second instars while indicating bad conditions for third instar recruitment. T h e length of the first instar recruitment period depends on food conditions and o n the duration of the egg laying period. Because first and second instar larvae are starvation-prone (Neill and Peacock 1980), the second instar recruitment period can only be increased if first instar have eaten sufficiently to molt into the second instar and the latter also have sufficient food available to survive rather t h a n starve and die. The recruitment period at the third instar is longer for at least two reasons: first, because the second instar recruitment is longer, and second because third instars encounter delays i n development i n late summer and fall due to prey shortage. A longer second instar period leads to a longer third instar recruitment period. But third instar recruitment period was m u c h longer t h a n produced by the lengthening of the second instar recruitment  period. T h i r d  instar were found late i n the fall, and fourth instar densities were seen to increase  or decrease very little  overwinter,  although  natural  background  mortality should have been present. The transformation of all members of the cohort from third to fourth instars was not yet complete i n the fall. G r o w t h and  88  transformation to new instar took place sometime d u r i n g the winter or earlyspring, a clear indication of developmental delays. Such delays, rather t h a n death, are expected i n starvation-resistant animals. Thus, the length of the t h i r d instar recruitment period was likely due to a combination of a longer second instar recruitment period and third instar developmental delays. I tested the idea of l o w prey availability for third instar i n late summer i n Chapter 3.  From a theoretical point of view, delays i n dynamics can be representative of the vicinity of a boundary between states ( L u d w i g et al. 1997). The increase i n second instar represented the crossing of the threshold between the Daphnia  domain  and the Chaoborus state. However, the h i g h densities used i n the h i g h predation enclosures might have pushed the dynamics of the system close to an upper boundary for the Chaoborus state. This response to 15X increase i n predators could be indicative of a system w i t h a small d o m a i n and l o w resilience to disturbance and presents a potential explanation for the fact that the  Chaoborus  state d i d not persist over several predator generations.  2.5 C O N C L U S I O N Increasing the predator densities i n the spring i n the enclosures resulted i n higher densities of second instars i n all enclosures and i n higher densities of fourth instars i n most enclosures than i n the lake. Higher densities of fourth instar larvae i n the spring allowed for better recruitment of the starvation-prone first and second instars i n enclosures  than  i n the lake. Fourth instar  are 89  starvation-resistant and can survive overwinter at higher densities than i n the lake. However, developmental delays indicated that l i m i t a t i o n i n the system occurred before the winter period. The bottleneck, previously experienced by the first and second instar larvae, moved to the third instar larvae. Enhanced recruitment of young instars and good overwinter survival are necessary but not sufficient elements to guarantee persistence of the predation state over several predator generations.  Next, I examine the prey dynamics i n the light of the predator responses above to understand the lack of persistence of the Chaoborus state under the experimental conditions.  90  CHAPTER 3 PREY D Y N A M I C S , S H O R T T I M E S C A L E S , A N D PREDATOR RECRUITMENT  3.1 I N T R O D U C T I O N  Dynamics of Daphnia  and solitary rotifers, the prey populations,  play a n  important and intricate role i n the community switch from the Daphnia d o m a i n to the Chaoborus state, and i n the potential for persistence of the latter. T h e switch between states depends on a rerouting of the food resource for the prey from the Daphnia  population to the solitary rotifers, the small prey. T h i s  resource redirection must take place prior to and during the recruitment period of the young predator  instars. O n the other  hand, the persistence  of the  Chaoborus state depends on the feedback of the predator dynamics on the prey assemblage. H i g h predator densities, expected i n the Chaoborus  state, require  sustaining high prey production, from one predator generation to the next.  In this chapter, I test that increased predator densities i n the spring reduces the competitive impact of the Daphnia population on the solitary rotifers prior to young predator recruitment (see Table 1.1). I also test the impact of h i g h predator densities on the prey dynamics throughout the predator life cycle and on the persistence of the Chaoborus state. Specific predictions related to the enclosure experiments are presented i n section 3.2.3.  91  Redirection of the food resource to small prey depends on the ability of Daphnia to sequester resources, ability w h i c h can be reduced or enhanced by different factors such as temperature and predation. Daphnia has a big potential for food consumption and can reduce resources  below the level  required by other  zooplankton (Lampert et al. 1986, cited i n Jiirgens 1994a; Glide 1988)  such as  small cladocerans (e.g. Daphnia vs. Bosmina: Jiirgens et al. 1994b), copepods and rotifers (Gilbert and Stemberger 1985; Gilbert 1988a). Daphnia  can reproduce  quickly and have a major impact on phytoplankton resources as demonstrated b y the spring clear water phase i n many lakes where reduction i n p h y t o p l a n k t o n density by Daphnia feeding produces h i g h water transparency (e.g., E d m o n s o n and Litt 1982; Lampert et al. 1986; Rudstam et al. 1993; Jiirgens 1994a). In lakes where Daphnia is low or absent (Havens 1990; Stenson 1990), other species, such as rotifers, or Bosmina,  are abundant throughout  the season instead of being  limited to early spring a n d / o r fall peaks. Daphnia is a key player i n d e t e r m i n i n g zooplankton community structure.  Water temperature affects metabolism and thus consumption  rate. A t l o w  temperatures, Daphnia reproductive, developmental and growth rates decline (Hebert 1978; N e i l l 1981a; Orcutt and Porter 1983; Berberovic et al. 1990). These declines i n physiological rates reduce food requirement for s u r v i v a l and growth. Daphnia rosea is a cold water species (Neill 1981a; Walters et al. 1987), compared to species such as D. pulex. C o l d temperature is even less of an impediment for  92  many rotifers. They are present and reproduce before Daphnia  emerge  from  resting eggs i n the spring and are also present and reproduce i n the fall after Daphnia, having produced resting eggs, disappear from the water column. T h u s , i n cold temperature, the competitive influence of Daphnia is reduced or absent altogether. C o o l years could facilitate the switch from the Daphnia domain to the Chaoborus state.  The impact of the predator on Daphnia  resource  consumption  is indirect.  Predators reduce Daphnia population density and modify its population size structure w h i c h then affects Daphnia per capita feeding and reproductive rates. Predators such as fish deplete the larger size Daphnia (Brooks and Dodson 1965; G l i w i c z 1985). This reduces both the reproductive output and the per capita feeding rate as larger Daphnia are generally the reproductive i n d i v i d u a l s i n the population and they can clear a larger v o l u m e of water per unit time  than  smaller individuals (Borsheim and Andersen 1987; Peterson et al. 1987). Fish is absent from Shirley Lake. Instead, invertebrate predators, such as  Chaoborus,  feed on small size classes (Fedorenko 1975b; N e i l l 1981b; Buns and Ratte 1991) compared  to  population.  fish  and  Predation  reduce can  Daphnia  reduce  recruitment  resource  to  the  consumption  reproductive by  Daphnia  populations.  In m y enclosure experiments, started i n 1992, reduction of Daphnia density and additions of Chaoborus were combined to study the impacts on both the  Daphnia  93  population and the solitary rotifer populations. In 1993, fourth instar predator densities, recruited from the previous season, and cool spring temperature combined to delay the onset and slow d o w n the increase i n Daphnia  abundance  w h i c h i n turn was expected to affect the solitary rotifer population dynamics. Both the strength of the disturbance and its t i m i n g play a large role i n the resulting dynamics and i n determining presence and persistence of alternative states for the zooplankton community.  3.2 M A T E R I A L S A N D M E T H O D S 3.2.1 Field experiments Details for the setup and design of the field enclosure experiments i n Shirley Lake are described i n Chapter 2 (section 2.2.1 to 2.2.3). Samples for z o o p l a n k t o n and rotifer i n enclosures and the lake were collected o n the same schedule as for the predators (for details, see Chapter 2, section 2.2.3). Generally, predator daytime samples, large zooplankton samples, rotifer samples, and the  water  temperature data were collected between 10:00 and 14:00 Pacific Daylight S a v i n g time.  I collected predator and large zooplankton samples by vertically hauling a 0.4 m mouth diameter Wisconsin type net, 102^im mesh size, from a depth of 3 m. A t the deep lake station 2, a 6 m vertical haul was also collected. The rotifer samples were collected i n the same manner but w i t h a 0.3 m m o u t h diameter W i s c o n s i n  94  net, w i t h a 50 urn mesh size. I preserved all samples i n glass jars using 5% sugared formaldehyde solution.  A three-year time series was collated from monthly samples for 1992 to 1994 for total Daphnia and total solitary rotifer densities for each enclosure and for the lake station (Appendices D and E). The solitary rotifer data represented total densities for non-colonial rotifer genera Keratella, Kellicottia  and  Polyarthra,  genera w h i c h are potential prey for all Chaoborus instars and necessary prey for younger instar larvae (Moore and Gilbert 1987; 1988a; 1988b). Solitary rotifer t i m e series for 1992 to 1994 were erratic and difficult to interpret (Appendix E). T h e monthly  sample interval d i d not provide the required details to test the  predictions presented i n the next section. The shorter interval samples (semiweekly, weekly and bi-weekly) provided better information w h i c h is presented later i n the Results section. Daphnia  time series showed that Daphnia  was  present seasonally i n the lake throughout the study period from 1992 to 1994 (Appendix D). Most enclosures recruited Daphnia seasonally throughout study period. However, no substantial densities of Daphnia  the  were found i n  enclosure G from the onset, and i n enclosure C after A u g u s t 1992. Daphnia recruitment failure was evident i n enclosure G where peak m o n t h l y density only reached about 30 Daphnia m" (10- to 200-fold lower than densities reached in the other enclosures and the lake), and where the population disappeared from the water column i n September, rather than later i n the fall.  95  Water temperature at 1 m interval was sampled using a Par battery operated bilge p u m p and a thermometer (±1°C). M e a n m o n t h l y water c o l u m n  temperatures  were calculated using the recorded temperature profiles from the surface d o w n to 7 m for each date w i t h i n a month. I also calculated the mean seasonal water temperature using the monthly mean water c o l u m n  temperatures  for dates  between M a y and October inclusively.  3.2.2 Identification and counts I used Edmonson (1959) as a reference for identification. Macrozooplankton (e.g. cladocerans, copepods) were identified to species under a W i l d M 5 stereoscope at 40X. The rotifers were identified to genera, under a N i k o n inverted microscope at 100X. I counted macrozooplankton and rotifers under a W i l d M 5 stereoscope at 12X, 25X or 40X depending on zooplankton size and sample density. Chaoborus were identified to species, using Saether (1970) and Borkent (1979), and identified to instars using Fedorenko and Swift (1972), under a stereoscope at 25X, and at 40X for younger instars.  Counts were done i n grided petri dishes (Edmonson 1971b), under a W i l d M 5 stereoscope for all animal categories. Samples estimated to contain less than 400 individuals of the most abundant species i n the sample, were counted i n their entirety. Samples estimated to contain greater than 400 individuals were split, and  one or two subsamples were counted, as required, to count about 100  individuals of the most abundant species i n the sample (Edmonson 1971b). 96  Chaoborus third and fourth instar larvae were counted at 12X i n entire samples, as their elongated shapes prevented random sample splitting. For all other categories, dense samples were split using a 250 m l Folsom splitting wheel w i t h 4 divisions  (4 X 1/4 subsamples)  (Edmonson 1971b). W h e n  necessary dense  subsamples were resplit and the v o l u m e to count was reduced to 1/16 or 1/64. Here again, the subsamples to resplit and to count were chosen randomly.  3.2.3  Predictions for prey dynamics based on experimental design  Based on the hypothesis that the zooplankton c o m m u n i t y i n Shirley Lake can function  i n two different domains of attraction and based on the  current  experimental design of Daphnia reduction, directly and indirectly by predator additions, I expected that the zooplankton c o m m u n i t y i n enclosures s h o u l d switch from the Daphnia domain, as present i n the lake, to the Chaoborus state (see Section 2.2, for details of c o m m u n i t y functioning). The switch to  the  predator state was expected to reduce Daphnia densities and increase solitary rotifer densities prior to the recruitment of second instar predators (Table 3.1). Enhanced Chaoborus fourth instar densities i n spring were expected to reduce and maintain lower Daphnia densities i n the enclosures than i n the lake prior to the young predator recruitment period. A m o n g s t enclosures, l o w treatments were expected to yield higher  Daphnia  densities  than  the  high  predator  treatments.  97  In response to these low Daphnia densities, I expected that the solitary rotifer populations w o u l d increase during the same time period. Thus, rotifer densities should be higher i n the enclosures than i n the lake, and higher i n h i g h predator treatments than i n l o w treatments (see Table 3.1).  Persistence of the Chaoborus  state requires that h i g h densities of predators  survive overwinter and that they affect negatively the Daphnia population i n the spring. The predators have short-term impact on the Daphnia population by delaying the onset of the population a n d / o r longer-term impacts by affecting population growth rates. Thus, i n enclosures w h i c h recruited fourth predators  i n higher  densities  than  i n the  lake, I expected  that  instar  Daphnia  population onset w o u l d take place later, a n d / o r that Daphnia densities w o u l d be lower for a longer period of time than onset time and densities i n the lake. I addressed these points by using the date of appearance of Daphnia  in  the  samples.  A potential problem is that Daphnia could have been present i n the lake before I detected it. Presence of Daphnia was detected i n my samples w h e n their density in the water column exceeded 2-3 Daphnia m" . A second problem is that, i n 1992, the enclosures were started when Daphnia was already present i n the lake, thus I could not use this information to study the influence of the density of predators on the onset of the Daphnia population. Instead, I used data from spring 1993 where predators were present at different density levels i n the enclosures prior to 98  Table 3.1  Predictions for the relationships in prey densities between the lake and the enclosures, and between the low and high treatments in relation to the experimentally-imposed predator gradient.  Hypothesis: Under reduced Daphnia density and enhanced predator densities, all enclosures are expected to cross the threshold and switch to Chaoborus state  Variable  PREDICTIONS  Lake vs. Enclosures Daphnia  Daphnia density prior to recruitment of young instars  Enclosures: L o w vs. h i g h  Lake > Enclosures L O W > H I G H  Correlation w i t h spring predator gradient  -  Daphnia appearance date (Julian day) i n Lake < Enclosures samples Solitary Rotifers  Solitary rotifer density prior to recruitment of y o u n g instars  Lake < Enclosures L O W < H I G H  +  99  Daphnia coming out of resting eggs. Thus, I could study their impact on the beginning of the Daphnia population growth. I expected that Daphnia  would  appear sooner i n the lake than i n the enclosures w i t h h i g h fourth instar recruit densities (Table 3.1). Delays i n the onset of Daphnia  population and l o w e r  Daphnia densities compared to the lake prior to recruitment of young predator instars w o u l d support the idea that feedback loops w i t h the potential to generate alternative states were present.  100  3.3 R E S U L T S 3.3.1 General trends i n prey population dynamics The full time series (1992-1994) are presented i n Appendices D and E for Daphnia and rotifer densities respectively. Figure 3.1 represents Daphnia densities on the date w h e n first instar predators appeared i n the samples (indicated by inverted triangles i n A p p e n d i x D) i n relation to density of fourth instar predators earlier in the spring for each year of the study. Over the three-year monitoring period, the Daphnia population i n the lake reached at least 1000 individuals m " at the 3  time w h e n  first instar  predators  appeared  i n the  samples  while,  in  the  enclosures, densities were generally lower than 1000 Daphnia m" (Figure 3.1). I n enclosures, such densities were reached only later d u r i n g the predator second instar, if at all (Appendix D). The solitary rotifer densities at the time w h e n the first instars appear each year showed no specific relationship between solitary rotifers and fourth instar densities i n lake and enclosure samples (Figure 3.2). Interpretable patterns related to predictions from Table 3.1 appeared only w h e n looking at data on the time scale shorter than one m o n t h and are addressed below.  The 1992 time series presents bi-weekly to monthly samples for Daphnia (Figure 3.3) and for the solitary rotifers (Figure 3.4). The inverted triangles represent the date of appearance of the different predator instars i n the lake samples. First instars appeared i n enclosures on the same date as i n the lake. However, date of  101  Figure 3.1  Daphnia density on the date w h e n first instar predators appeared in Shirley Lake and i n the enclosures each year i n relation to the density of fourth instar predators i n each spring. (Appearance date in monthly samples: June 30,1992; June22,1993; July 5,1994)  Predator addition treatments  Lake  Low  10  Medium  -i  4  3  1 0  2 "  L93^  [94 B94 •  •  • • •  L94|  L92  Daphnia density (ind. m" )  •  High  E93  B92 • J92 C92^ *  H94  10 J 23  E92 J93 •  ^2  H92 D92  D93 •  10 J 1  10  J94 •  E94  1  10  J  H93 B93 • • • .  10'  10  J  Fourth instar predator density in spring (ind. m ) - 3  102  Figure 3.2  Density of solitary rotifers on the datewhen first instar predators appeared i n Shirley Lake and i n the enclosures each year i n relation to the density of fourth instar predators each spring. (Appearance date i n m o n t h l y samples: June 30,1992; June22,1993; July 5,1994)  Predator addition treatments  Lake  •  Low  A  Medium  •  High  Solitary rotifer density (ind. m " ) 3  Fourth instar predator density i n spring (ind. m " ) 3  103  Figure 3.3  Time series for total Daphnia density May to October 1992 following a variable sampling interval. (a) in medium (I) and high (D, E, H) predator treatment enclosures (b) in Shirley Lake (L) and low (C, J, B, G) predator treatment enclosures (Inverted triangles represent onset of instar recruitment in the lake) Vertical guidelines: Julian day 154 : fourth instar predators have been reduced through pupation after Julian day 168 : appearance of second instar larvae in enclosures Julian day 266 : Daphnia population decline due to environmental factors Horizontal guidelines: 1000 Daphnia m "  3  Julian Days 104  Figure 3.4  Time series for total Solitary rotifer density May to October 1992 following a variable sampling interval. (a) in medium (I) and high (D, E, H) predator treatment enclosures (b) in Shirley Lake (L) and low (C, J, B, G) predator treatment enclosures (Inverted triangles represent onset of instar recruitment i n the lake) Vertical guidelines: Julian days 154 to 168: period where predation was low and where the relative strength of competition by the Daphnia population on the rotifers can be tested Horizontal guidelines: 10 000 solitary rotifers m "  3  Julian Days 105  appearance of second, third and fourth instars i n enclosure samples could take place earlier or later than i n the lake samples. The lake and l o w predator treatment enclosures J and B followed a similar seasonal pattern w i t h the l o w predator enclosures showing lower Daphnia densities than the lake till w e l l into the second instar recruitment period. O n the other hand, the m e d i u m and h i g h predator enclosures showed l o w Daphnia densities (below 1000 i n d i v i d u a l s m" ) 3  throughout the summer and d i d not reach a plateau before the fall p o p u l a t i o n decline.  Solitary rotifer densities also showed patterns that were strikingly different for the m e d i u m and h i g h predator treatments (Figure 3.4, panel A ) than for the l o w treatments and the lake (Figure 3.4, panel B). In the latter two categories, solitary rotifer densities oscillated around 10 000 i n d i v i d u a l s m" w i t h rotifer densities above 10 000 individuals m" at the end of the second instar and the beginning of the third instar recruitment periods. In the h i g h predator treatments,  rotifer  densities showed a d o w n w a r d trend from spring to September, w h e n they showed an increasing trend till the end of the ice-free season. This means that contrary to the lake and l o w predator treatments,  h i g h predator treatments  showed a dip i n rotifer densities below 10 000 i n d i v i d u a l s m " at the end of the 3  second instar and the beginning of the third instar recruitment period.  In the following sections I use data from 1992 to demonstrate the impact of the predator gradient on the prey populations prior to young predator recruitment 106  and data from  1993 to highlight the impact of the predator  on  Daphnia  populations early i n the spring.  3.3.2  Daphnia  population dynamics: influence of spring predator density and  temperature  3.3.2.1 Impact of the 1992 spring predator density gradient on Daphnia densities  The initial impact of the experimental treatments (Daphnia  reduction  and  predator additions) was to decrease the Daphnia densities i n M a y 1992 i n the enclosures compared to the lake (Figure 3.5). A l l the enclosures are functional i n may 1992 and are represented on figure 3.5. However, enclosures A , F and G failed early i n the experiment. subsequent analyses.  I excluded these enclosures  Here, I analyzed the  from  this  data using a one-tailed  and  linear  regression. The relationship between the logarithm of Daphnia density versus the logarithm of fourth instar density initially present i n the enclosures was negative (p=0.008, R =0.64; one-tailed test; df: (1,6)) as expected from  predation  theory. Thus, the predator density gradient applied experimentally i n the spring resulted i n a Daphnia density gradient.  Higher densities of fourth instar predators i n the spring introduced delays i n the increase phase of Daphnia population i n enclosures. Larger delays i n  Daphnia  increase represent larger w i n d o w s of time for young predators to recruit. I used the date when first instar predator appeared i n the samples as day 0. U s i n g  107  Figure 3.5  Initial Daphnia densities i n the lake and i n the enclosures after predator additions (May 26th, 1992).  Regression line for a l l data points except for those between parenthesis (G, F, A ) where Daphnia or the predators failed to recruit early i n the experiments L o g (Daphnia +1) = 5.1 -1.5 Log(predator +1) R = 0.642 2  Predator addition treatments  High  10  1  10  2  10  3  Spring 1992 Fourth instar predator density gradient (ind. m~3)  108  Daphnia  density i n the lake at day 0, I calculated the  populations i n enclosures to reach equivalent  delays for  Daphnia  or higher densities. The l o w  predator treatment enclosures (B, J) required four weeks i n 1992 and 8 weeks i n 1993 (Table 3.2) to reach Daphnia densities equivalent to those i n the lake w h e n first instar predators appeared (see Figure 3.1). The m e d i u m (I) and high (D, E, H ) predator treatment enclosures required at least twelve weeks to reach those same Daphnia density, except for enclosure E i n 1993 w h i c h reached high densities of Daphnia at the same time as i n the lake.  Higher densities of fourth instar predators i n spring 1992 resulted i n l o w e r Daphnia densities prior to second instar recruitment  (June) i n the  enclosures  than i n the lake (Figure 3.6). I selected the time period after most fourth instars had pupated, but before the m a i n recruitment period of young predators (from Julian day 154 to 168) (Figure 3.3). This period included three daytime s a m p l i n g dates (June 2nd, 9th and 16th, 1992). For the lake station and each enclosure, except G which d i d not recruit substantial Daphnia, I plotted the average density over this two-week period (Figure 3.6). A l l the enclosures recruited lower density than the lake. A one-tailed binomial test (Table 3.3) was statistically significant. The linear regression (Table 3.3) was significant and the slope was negative as predicted i n Table 3.1.  Amongst enclosures, the predictions were also upheld w i t h higher  Daphnia  densities i n l o w predator treatment than i n h i g h treatments. The results of a  109  Table 3.2  Impact of fourth instar predator density gradient on Daphnia population increase: Delays (in weeks) i n enclosure Daphnia population i n reaching densities similar to those found in the lake at the time when first instars appeared.  Treatment High  Station  H E D  Medium Low  I B  Lake  J L  1992  1993  delay (weeks)  delay (weeks)  >12 >12 12 >12 4 4  12 0 12 8 8 >8  —  —  110  Figure 3.6  M e a n density of Daphnia (for Julian days 154 to 168, June 1992) i n relation to the experimental gradient i n fourth instar predator i n spring 1992.  Log(Daphnia +1) = 4.5 - 0.93 * Log(predator +1) R = 0.785 2  Predator addition treatments  Lake  •  Low (excl. G)  Medium  High  June 1992  Daphnia density (ind. m ' ) 3  1 q 3  ,  Spring 1992  Fourth instar predator density gradient (ind. m "^)  111  CN  3 cu cu •w (A CO  CU  g  +  O  CN ON  "S  -o TJ  U  3  o « EA o CU « 1H CO  tH  CA  ^-3 s  TJ cu CU  TJ  3  TJ  45  •  CN  (5 °O^N S  bO  3  TJ  1 - 1  «  CU c:  CO  s  3  •i-H  Q  CM  .S 3  O  45 u  -4->  '55  | S  tH  --H  3  CA  MH  O) T J  bO O  o c  TJ  3 rt cu  * —  bC O  4<, rt  r J  cu  x*  o o  H-»  "o 3 co CU  cu  cu  H-> CU CA CA  CM ON ON  CO  cn  CU  II  3 tH cu &  CU  3  cu  to  is  CA  a  -s  3  3, o  4H  m  S  4-> I  CU 4 H  .2 B o 3  CU  TJ  ^  00  '3  ** .3 «  ^  00  w  • »H  PO  H  CO  OH MH —H  MH  cn  60 £  O  ° .S 5  H-> CA  CU  H  CA  CU  H  m  =  S  CO  cu 3  CO  o  CO  CU  •8  TJ CU (H  CH  H->  m 3 A cu W TJ *CA  <S s 4K H H a . •i-H  <  «  _g 'CA CO  N  >"  5  LO  3  cu tH bO cu tH tH  CO CU  3  cu  3  - M • rH  45 I  3 3  cs  O  • -H  CA CO  OJ tH  bO cu tH tH  cd  3  cu  cu  O  CM O  cu  cu >  CM  > CO  o CM  o l-H  A  o  NO  ^t  CM  3  T J  Q  m  CN  3  cu  o  lx  I  CO  CN  CO  O  13 Q o CA  o  00  CU I-i  CA  CU  LX  ON  S3 TJ S 3  00  NO  NC  CA  X  8 LO 9 ^ LO o  o 3  s *S  o ©  ©  X  ra u  45  TJ  o o  o  cu cu  tH  H->  CN|  CM O  CO  O CM  PH  linear regression showed significant and negative relationship (Table 3.3). T h u s , more fourth instar predator i n the spring resulted i n lower Daphnia  densities  prior to recruitment of the second instar predators.  Increased densities of fourth instar Chaoborus  i n the spring delayed  Daphnia  population increase i n early summer, and provided lower Daphnia densities at the time w h e n young predators started recruiting. Higher densities of predators enlarged the delay i n reaching high densities of Daphnia.  3.3.2.2 Daphnia population onset: influence of water temperature and predator density in the spring  The 1992 data presented above addressed the impact of the spring fourth instar predators on Daphnia densities prior to second predator instar recruitment. T o address the impact of the predators on the Daphnia population i n early spring, I needed to use 1993 data because enclosure experiments i n 1992 were started after Daphnia had already appeared i n the lake. In 1993, predators overwintered i n the enclosures and were present i n high densities i n most enclosures before hatched out of resting eggs. I thus could observe  the  Daphnia  impact of naturally  recruited, but different densities of fourth instar predators on the onset of Daphnia population dynamics early i n the spring.  Daphnia could have been present i n the lake before I could detect them i n the samples. Daphnia  population onset was defined as the Daphnia  population 113  reaching a m i n i m u m  level of 1 Daphnia  per sample, i.e. 2-3 Daphnia  m' . I 3  expected that the predator could delay the start of Daphnia population increase by predating either on Daphnia hatching out of resting eggs or o n their offspring.  Delays i n the onset of Daphnia population increase, and differences i n t i m i n g and densities of Daphnia population peaks occurred between years, and between enclosures (Appendix D). Because 1993 was a colder year than 1992, and because cold temperature can slow invertebrate  metabolism, I first determined  the  impact of temperature on the time of appearance on Daphnia i n the spring. T o evaluate the impact of temperature on the onset of Daphnia population, I used as day zero the first day when Daphnia  appeared i n the lake samples i n the  spring of 1992. I calculated the difference i n Julian days i n the onset of Daphnia population. I graphed the delay i n the date of appearance of Daphnia i n the lake samples between years i n relation to mean spring temperature of the column, and i n relation to densities of fourth instar Chaoborus  water  larvae i n the  spring (Figure 3.7). The longest delay i n Daphnia appearance i n the lake between years was 19 days (Figure 3.7 A ) , and occurred i n 1993, w h i c h had the coldest spring and was the coldest year overall i n the study. There  was no  clear  relationship between the length of the delay i n Daphnia population appearance and the fourth instar larval densities over the range observed i n the lake i n the spring (Figure 3.7 B). The yearly mean temperature of the water c o l u m n related well to Daphnia m a x i m u m and yearly mean density (Figure 3.8).  114  Figure 3.7  Delay i n Daphnia population onset i n 1992 to 1994 i n relation to A ) mean water temperature i n Shirley Lake i n springtime (mid-May to mid-June) B) predator density i n Shirley Lake i n spring 1992 to 1994  A)  CO  D  9.5  01 ( 0  G O  Temperature (°C)  o 3  PH  o  B)  OH  <3 K  -s: a. cs Q d • r-l  D  Predator density (Chaoborus fourth instar larvae m  115  Figure 3.8  M a x i m u m and yearly mean Daphnia density i n 1992 to 1994 i n relation to yearly mean temperature. Dotted lines below the temperature axis represent ± 1 s.e. of the yearly mean temperature for each year.  -9  Maximum  •  Yearly mean  6000  Daphnia density (ind. m " ) 3  5000 H  4000 H  3000 H  2000 H  1000  Temperature  (°C)  116  U s i n g the same approach, I examined the influence of spring predator density i n the enclosures, and i n the lake, on the timing of the onset of the  Daphnia  population. The longest total delays were 75 days and occurred for two enclosures (B and H ) w i t h densities of Chaoborus greater than 155 predators m" combined w i t h the cold spring temperature of 1993. I used the total delay obtained for each enclosure and subtracted the delay associated w i t h temperature as observed i n Figure 3.7 (e.g., 19 days for 1993 data) to obtain the delay associated w i t h the predator effect. I graphed the predator-induced predator  density after  Enclosures w i t h  removing  the  delays equal to zero  delay i n relation to spring  effect of temperature had  i n Figure 3.9.  delays indistinguishable  from  temperature delays alone. Stations B93 and H93 showed delays almost four times greater than the delay observed i n lake (L93) for that year. Predator densities higher than 155 fourth instar larvae m" i n the spring delayed the onset of Daphnia population i n the enclosures.  A n important predation pressure was removed from Daphnia population after fourth  instar  predators  pupated  and metamorphosed  i n early June  1992.  However, Daphnia densities i n enclosures d i d not recover to levels equivalent to that of the lake by the time the third instar predator reached their m a x i m u m recruitment i n August (Figure 3.10). H i g h predator treatments maintained l o w e r Daphnia densities than the l o w treatments (Table 3.4ii).  117  Figure 3.9  Delay i n Daphnia onset i n the spring i n relation to the density of fourth instar predators i n springtime of each year.  Predator addition treatments  Lake  -3  •  Low  A  Medium  High  ro Oi co  60 A  D cy CO  G  o el  *•*•>  40 TT  OH  O  PO  —I — i  OH  <S •w  s »« a.  20  Q c «a 'cy  D  0  l  l  200  • l  l  250  Fourth instar predator density in springtime (ind. m ") 3  118  Figure 3.10  Daphnia densities i n A u g u s t 1992, w h e n t h i r d instar predators reached their m a x i m u m density, i n relation to the density gradient i n fourth instar predator i n spring 1992.  Regression line for all data points except (C) where Daphnia recruitment had failed by this date L o g (Daphnia +1) = 5.1 - 0.95 Log(predator +1) R = 0.815 2  Predator addition treatments  High  10  1  10  2  10  3  Spring 1992 fourth instar predator density gradient (ind. m  119  H-I  TJ  to to 3 V O -a  " to" 01  0  o  vj  oi  i. +  T—I ^  U bo  u  c3  3 to  Tj  n  s«  o c  43 TJ * * O" T j >  bh  PK  0 01  H-l  +  bO O t-J  QJ "~^Tj MH  bO O  U  II  II  X  ft)  CO  TJ  C  18 ,  o ON oi  8 « •rt co  J3 ^ H-l  CD O O  OH  ^  H_»  Oj CN w Jto 3 °^ 0 1  X LO  ?! to  II CN  LO  3 o  «  5  a. *  <"  «  OH  x c go 'j?  C  c  OHMH  O  _^TJ 43  ° oi  w  00  o e "  CO  i-H  CN  O (N  04  II  C _o QJ  to to 0)  QJ  SH  bO  bo  QJ  QJ lH  -H  w ° w  CS QJ  c  H  s3  CS  cs  53  QJ  OH  TD CD >  cn o o  •a « A  o  •S3  TJ Oi  a.^ « Q  -H  H-»  CS  cn U .2  QJ  QJ  OH  to cy  'co  co  -H  H-l I QJ  0 1  • lH  H-l  •— . t  TJ  (3  H  >H  CO  o  S  0) ft, to tU to tU Hft, H«• 42  43 rt  N  (3  0»  H-l  *a « « J H  Oi  CO  II  II  CO  d  J3 S3  CO  o  0  H-l  d  VO tx  CN CO LX  OI w  c  3 TJ  0 1  00  LO  -H  •is  to  CN O  O  to rv to M ON -3 -H  ft) >  LO  CM  CS  bO  bO  O  E  r—I  A  o  QJ  S3  3.3.3 Relationship between Daphnia p o p u l a t i o n and solitary rotifer p o p u l a t i o n dynamics The spring predator density gradient generated a Daphnia density gradient i n the enclosures w h i c h was maintained at least till the recruitment period of second instar predators, and longer i n some enclosures. I expected solitary rotifer densities to vary inversely i n proportion w i t h the Daphnia gradient (Table 3.1).  To evaluate rotifer dynamics i n relation to the Daphnia  density gradient, I  focused on a period, prior to second instar recruitment, where both c o m p e t i t i o n and predation on the rotifers should have been limited. I used the period including Julian day 154 to 168, a fourteen day period w i t h three sampling dates (Figure 3.4). The inverted triangles on this figure represent timing of appearance of the predator instars i n the lake. Previous to day 154, rotifer densities were declining i n the lake and most enclosures. In the lake, the decline may have been associated w i t h the increase i n Daphnia density. In the enclosures,  Daphnia  densities were l o w (generally fewer than 300 i n d i v i d u a l s m" ; Figure 3.3) and 3  rotifer densities were expected to increase. However, fourth instar  predator  larvae added to the enclosures may have exerted sufficient predation pressure to exceed effects of the competitive release on the rotifer population. Fourth instar predators can feed on rotifers (Moore and Gilbert 1987; 1988b; 1994), especially when other prey such as Daphnia are rare. A s the predators entered the p u p a t i o n period, their density declined rapidly, thus lowering the predation pressure o n the rotifer populations. After day 168, second instars started to recruit i n larger 121  densities i n most enclosures, bringing a sharp increase i n predation  pressure.  Thus, between day 154 and 168 on figure 3.4, rotifer populations were expected to be under reduced predation pressure from Chaoborus,  and rotifer populations  are free to vary i n relation to the strength of the competitive pressure f r o m Daphnia.  Based on competition theory, I w o u l d expect a negative relationship w i t h m o r e rotifers present as Daphnia  densities were lowered. Thus the lowest rotifer  densities were expected i n the Daphnia domain, and the higher rotifer densities in the Chaoborus  state, where competition was hypothetically reduced by  predation on Daphnia, the dominant competitor.  For each station, I averaged the density of both Daphnia and of solitary rotifers over the three sampling dates (Figure 3.11). The relationship between  Daphnia  and rotifer densities showed a negative trend but was not significant (Table 3.5 i). The relationship is not linear. A three-fold decrease i n Daphnia densities i n the lake compared to the enclosures, resulted i n a five-fold  increase i n rotifer  densities (Figure 3.11 A ) . A linear regression on the data was not significant but a second order p o l y n o m i a l model fit relatively w e l l (Table 3.5 i). A m o n g s t enclosures  alone, a fourteen-fold  decrease i n Daphnia  densities  (700 - 50  individuals m" ) from l o w to high predator experiments resulted i n a two-fold decrease i n rotifers (33 000 - 18 000 i n d i v i d u a l s m" ) (Figure 3.11 B). Both a linear 3  122  Figure 3.11  M e a n density of solitary rotifers i n relation to Daphnia mean densities for Julian days 154 to 168 (June 1992). A ) Lake and enclosures: second order polynomial relationship. B) Enclosures only: linear and second order p o l y n o m i a l relationships. Regression equations are presented i n Table 3.6  Predator addition treatments  •  Lake  *  Low  A  Medium  •  High  A)  V CO  -t-> ; O T3 5-1  O CD  B)  10'  I C  Daphnia density (ind. m~ ) 3  123  41  +  43 . . +*  CO  ii e CO  >  CO  £  S  C  cu  °£  PS:  »© T j  o  <S 42  cu  U  _  To J  3  pH  '  PX.  o•  bO O  bO O  HJ  PJ  O  II  II  CO  rH  cu  PH  cu —i  X  *% CJ  PH  Q  CO  ON ON  co S 3 CU TJ  cu  CS  e  H^^  •13  P H  TJ  cu  ca cl  CM ON ON  *H  "tf O  S 43 TJ s  S $  « 3 « T J cu .-a  2 a -C ^ £ _H  -S «  d cu TJ CS  — S « cu cu -5  5  I J  'sg H  U  © o  TJ  .H  CO pH  CU « gj CU  ItQ !  2  CO  H-»  o  X  d  QJ  di  PH  X  00 rH  CJ  d I  oo "tf  <a cn  X  o  X  "ca  co  LO CO  rH  O II CH*  rH  ^  ON  + CM  00  NO  00 CO  d d 1 1  r-J  P4  I'I II >H  4,  C  cu -3  "H  sC! S  — .cl  O  4, c ca X V TJ ° ii S  00 00  ca  T& •PH  -pJ  s o  cu I-,  g  c  W H  ca  >  ft) ft, > HP5  ircn •5 O  'co co QJ bC QJ PH  PH PH  ca QJ  QJ S3  x la  P2  6  <i  o c pb 'o  S3  PH  QJ  TJ  QJ > co  CO  cu S3  o CO  S w  a  v  p  pq  H->  TJ  CU PH  OH  H  CN  II  S3 S3  ca  o  CO  y  V  -I-H  •pH CO  co QJ PH bO QJ pH PH  PH  • i—I  CO  i-H  S3 O  X  U  HH  X v  O r J  fr< •rH r-H  O OH  o  QJ >  ca cu $3  II  "tf  CM  OH O  QJ  CN  CM  ca QJ QJ S3  c  rH  + "tf  >*  S3  _o  OH O  5 ?1  cu  d  CM  ON  S3 S3  PH  h  O  00  NO  LO PH  P^H •PH  £  CO  ON  +  LO  O  TJ  -"Si  •PH  LO  N  S3  a o co 5 *H cu  CO  rx o  II  CN NO  X  "tf ^ o  «  4H  43  o d V  X  "2  TJ  m  LO  o o  00  ON  CO  3  co  CO  "PH  CO  co  00  d  ca  x  in o d V  LO  O OH  ca  a  o S3 pb IS PH  TJ £3 QJ pH -pH  PH  ca QJ  S3  2o  and a second order polynomial model fit the data, and the nonlinear pattern has a higher coefficient of determination (Table 3.5 ii). The observed pattern amongst enclosures, more rotifers w h e n more Daphnia were present, was contrary to expectations based on competition theory. This pattern might be related to predator recruitment.  Later i n the summer, when third instar predators were recruiting, both Daphnia and  solitary rotifer  densities  generally decreased  with  increased  predator  densities i n the community i n the spring (Figure 3.12, panel c and f). T h e negative trend i n Daphnia relationship to the spring predator gradient d i d not change qualitatively between June and August, except for a gradual increase i n density i n the lake and i n most enclosures through the summer (Figure 3.12, panels b and c). In the case of the solitary rotifers i n M a y , there is no clear relationship w i t h the spring predator gradient (Figure 3.12, panel d). M o r e o v e r , the qualitative relationship w i t h the predator gradient was altered dramatically between June and August (Figure 3.12, panels e and f). In the lake, rotifer densities increased slightly from June to August while i n most enclosures there was a drastic decline (1 to 2 orders of magnitude). The lake had higher densities of both Daphnia and rotifers than most enclosures (Figure 3.12, panels c and f). This d i d not follow the predicted trend.  Finally, I address the response of the prey populations i n 1993 and 1994 after the fourth instar predators had disappeared from the water c o l u m n but where,  125  Figure 3.12  Solitary rotifer densities and Daphnia densities i n 1992, initially i n M a y , during young predator recruitment i n June, and during third instar recruitment i n August i n relation to density gradient in fourth instar predators i n spring 1992.  Prey dynamics in 1992 Predator addition treatments  Lake  Low  Medium  May  High  Aug  June  Daphnia density (ind. m " ) 3  1 0  1  10° 10  Solitary Rotifers density  10  (ind. m ~ ) 3  i  1  d)  1  '  •  3  AH • •  r  1  e)  f)  •  4  10 10  5  1  1  •  10  -  •  1  10  2  10  3  10  1  10  2  10  3  1  •  2  10  10  1  10  o  2  1  o  4  o  10  5  3  2  3  Spring 1992 Fourth instar predator density gradient (ind.  m ") 3  126  contrary to the case discussed previously for day 154 to 168 i n 1992, a n e w predator cohort has failed to recruit. Based o n their competitive interaction and the lack of predation by Chaoborus, I expected a negative relationship between m a x i m u m Daphnia density and solitary rotifer densities. Enclosures B (low), I (medium) and D (high predator treatment) lost their predator cohort i n 1993 while enclosures J ( l o w ) , E and H (high) d i d so i n 1994. In 1993, only enclosure I, compared to the lake, followed the expected trend (Figure 3.13). Enclosures B and D had lower densities of both Daphnia and solitary rotifers compared to the lake. In 1994, enclosure J and E recruited l o w densities of solitary rotifers considering that their Daphnia densities were 10 to 25 times lower than i n enclosure H and in the lake (Figure 3.13). Enclosures, such as B, D , E , J, w i t h l o w densities of both Daphnia and solitary rotifers after the predator impact had weakened had most likely become dysfunctional. Populations of Daphnia and rotifers i n enclosure I in 1993 and i n 1994 (see Appendices D and E) seemed to vary inversely from each other. In enclosure H , rotifers increased as Daphnia density decreased at the end of the 1994 season.  In summary (Table 3.6), Daphnia densities i n 1992 responded as expected to the spring predator density gradient. The negative relationship was m a i n t a i n e d through the season till the Daphnia population declined i n the fall. In response to reduced Daphnia densities i n enclosures, solitary rotifer densities i n 1992 increased and reached higher levels than i n the lake prior to y o u n g predator recruitment.  However, i n the h i g h predator treatments, solitary rotifers  in  127  Figure 3.13  Solitary rotifer densities i n relation to Daphnia m a x i m u m densities after enclosures have lost their predator cohort A ) for enclosures that failed i n 1993 B) for enclosures that failed i n 1994  102  10  10  3  i  •  .  4  . . . . .. 1  10 -: 5  •  L  io 4  •  ro  B  10 -: 3  A  I  13  & •rH  CO  1  0  -i  2  •  D  10 ' 1  C 0) 13 u  0)  o SH  O  cn  Daphnia maximum density (ind. m " ) 3  128  Table 3.6  Overall results of the impact of the 1992 spring density gradient i n fourth instar predators on the prey dynamics Hypothesis: Under reduced Daphnia density and enhanced predator densities, all enclosures are expected to cross the threshold and switch to Chaoborus state  Variable  PREDICTIONS Lake vs. Enclosures  Prey Dynamics  Daphnia  density prior to recruitment of young instars Solitary rotifer density prior to recruitment of young instars  YES/NO Enclosures: L o w vs. h i g h YES  Lake > Enclosures LOW > HIGH  YES  YES  Lake < Enclosures LOW < HIGH  NO  129  enclosures d i d not reach higher densities than the l o w treatments, contrary to expectation. Finally, by August 1992, most enclosures contained lower densities of prey than the lake and higher densities of Chaoborus.  130  3.4 D I S C U S S I O N Daphnia  females hatching  out  of resting eggs i n the  spring, also  called  exephippial females, are the product of sexual reproduction i n previous seasons. They have tremendous growth and reproductive abilities, p r o v i d i n g this group w i t h intrinsic growth rates 2-4 fold larger, i n the case of Daphnia longispina D. galeata, than  the  subsequent  generations  of  parthenogenetic  and  females  (Arbaciauskas and Gasiunaite 1996). Exephippial Daphnia mature earlier, h a v e clutch size that are 3 to 4 times larger than those of parthenogenetic  females.  Moreover, the former produce offspring w h i c h themselves w i l l grow faster and mature  earlier  than  offspring from  parthenogenetic  females  from  later  generations. This combination of characteristics results i n higher p o p u l a t i o n growth than what can be achieved under equivalent environmental conditions by parthenogenetic  females born a few generations  later. W h e n  Chaoborus  predation on exephippial females and their progeny i n the spring is h i g h , predator impact could reduce Daphnia densities and could lower the p o p u l a t i o n growth rate. This could result i n substantial delays i n reaching the  Daphnia  population m a x i m u m , and can also result i n a lower m a x i m u m density for the season. If exephippial Daphnia  rosea also possess these h i g h growth  reproduction characteristics, this could explain the differences population  onset  and maxima  observed  between  the  and  i n delays of  different  predation  treatments within a year.  131  The timing of Chaoborus predation i n spring seems to have had at least as large an effect on Daphnia dynamics as the numerical losses imposed by predation. I n 1993, lower predator densities i n the spring than started experimentally i n the previous spring apparently resulted i n similar or greater delays i n  Daphnia  population growth, and Daphnia density reduction, than i n 1992. Enhanced predator  densities  i n 1992 were experimentally applied after  the  Daphnia  population had had a chance to increase i n density i n M a y . By contrast,  the  predator density levels i n spring 1993 had already been i n place, v i a natural recruitment from the previous year, throughout the winter. For example, the predator density in enclosure H was enhanced to over 400 m" i n spring 1992, at the end of M a y . In spring 1993, only about 150 Chaoborus m " were present, but 3  this as early as A p r i l . Daphnia population density at the time w h e n first instar Chaoborus appeared, was larger i n 1992, than i n 1993 (1000 Daphnia m" vs. <10 Daphnia  m" , respectively). Increased  levels  of predation  in  early  spring  potentially removed Daphnia individuals p r o v i d i n g the highest potential for fast population growth which w o u l d have changed the Daphnia densities at the onset of population growth. Moreover, the spring predation impact could h a v e been felt later i n the season, even after the predators had pupated, because predation might also have changed Daphnia population growth rate and t i m i n g of maximal densities.  The delays i n Daphnia population growth are essential to provide a w i n d o w of high abundance of small prey species to promote and enhance recruitment of 132  young predators. A t l o w temperatures, predation  impact was increased  on  recruiting young Daphnia, w h i c h generated delays i n population growth ( N e i l l 1981b). Under colder conditions, Daphnia reproductive rate declines (Orcutt and Porter 1983), and the young Daphnia  developmental rate (Hebert 1978; N e i l l  1981a; Berberovic et al. 1990) and growth rate also decrease (Orcutt and Porter 1983) w h i c h keep the young Daphnia i n size categories sensitive to invertebrate predation for a longer period of time. Thus, i n colder water fourth  instar  Chaoborus could delay the onset of Daphnia population increase and slow d o w n their population growth by eating a greater proportion of Daphnia (Neill  1981a). Planktivorous  fish,  such  recruitment  as Cisco, can also delay  Daphnia  population increase and the timing of its m a x i m u m density because at l o w temperature the feeding rate of the predator exceeds Daphnia's recruitment rate (Rudstam et al. 1993).  In l o w predation enclosures i n Shirley Lake i n 1992, abundance of  Daphnia  populations were delayed temporarily, but finally converged to lake density levels later i n the summer. The increase i n Daphnia population was sufficiently delayed to release rotifers from competition and improve recruitment of young predators. Similarly, i n the Gwendoline Lake experiments, spring predation i n a cool year delayed, but d i d not eliminate, the timing of food limitation for Daphnia (Neill 1981a); zooplankton biomass was reduced and young predator recruitment improved (Neill 1988a). If the predator levels were able to reach this enhanced predation level every spring, a persistent Chaoborus state w o u l d occur  133  provided sufficient prey were subsequently available to third and fourth instar predators.  Alternatively, i n a cold spring year, the same density of predators on a slowly growing Daphnia population could generate a larger predator impact w h i c h could also result i n negative feedback on the predator dynamics if prey became too scarce. This presents a different mechanism than the one observed i n h i g h predation experiments by w h i c h Daphnia population w o u l d not reach density levels similar  to the lake. This mechanism  could also lead to l o w prey  availability for third and fourth instars resulted i n predator d e v e l o p m e n t a l delays. Thus, the persistence of the Chaoborus state relies on a limited loss of Daphnia population resilience. The loss must be sufficient to lower, Daphnia densities at the time when Chaoborus first and second instar recruit, but the loss cannot be so high as to result i n food shortage for third and fourth instar growth and development. The negative feedback of h i g h predator densities establishes an upper limit on the Chaoborus densities, i.e. on the upper end of the potential Chaoborus domain. Above this upper limit the system crashes.  Over the three year time period recorded for the experiments, all the enclosures lost their predator cohort although enclosures failed at different times. Enclosure dynamics were comparable to lake dynamics early i n the experiment  but  dynamics became more difficult to interpret and less comparable to the lake dynamics i n the later part of the experiment as enclosure failure increased.  134  D u r i n g the first half of the experiment, Daphnia  dynamics i n l o w predator  treatments and i n the lake are similar w i t h a fast increase phase after f o u r t h instar larvae predators have pupated, and w i t h h i g h Daphnia  densities reached  i n the summer. In the latter part of the experiment, only a few enclosures maintained viable Daphnia populations w h i c h , i n the absence of predator recruitment, reached high densities throughout the summer and fall. In the enclosures w i t h predators still present, delays i n development incurred u n d e r experimental conditions might interfere w i t h the normal life history of C. americanus development recruitment  , for example, through on  recruiting  failure  and  the  young timing  cannibalism of delayed fourth predators.  The  of enclosure  sequence failures  in  instar species  and p r o v i d e d  information on the key interactions i n the community. Overall, the enclosures provided information about the ability of the predator to overwinter i n h i g h density and about the limitations to the predator state i n oligotrophic conditions. This information w i l l be useful to m o d e l the community to explore the dynamics (size and shape) of the predator state over an increasing n u t r i e n t gradient.  In summary, because the nutrient  levels i n m y enclosures were still l o w  compared to mesotrophic and eutrophic lakes, the balance between the positive and negative feedback generated by reducing Daphnia  population t h r o u g h  increased predator densities might only occur for a narrow range of disturbances.  135  Beyond that range, the community bounces out of the Chaoborus state to go to extinction or to return to the Daphnia domain.  3.4.2 Rotifer population dynamics Lower Daphnia densities should release rotifers from competition pressure, and bring about higher rotifer densities (Neill 1984; Gilbert 1988a; 1989). W i t h higher predator densities, and associated lower Daphnia densities, the enclosures were expected to display larger densities of rotifers than the lake. The monthly t i m e scale data revealed no such trend (Appendix E), most likely due to the rapid population recovery that rotifers can exhibit (Edmonson 1965; Stemberger and Gilbert 1985; W a l z 1995) through their short generation time. A t smaller t i m e scales, I observed the expected lower rotifer densities i n spring 1992 i n the lake and i n the enclosures up to day 182 (end of June) (Figure 3.4).  A s s u m i n g that the rotifers responded to reduced Daphnia competition i n the enclosures as Daphnia d i d to the enhanced predation pressure (Figure 3.6), I expected the highest rotifer densities and the lowest Daphnia densities i n the high predation enclosures (Figure 3.11). However, rotifer densities i n m e d i u m and high predation enclosures were no higher than those i n l o w predation enclosures, but they were higher than i n the lake. The lowest densities of Daphnia generated rotifer densities w h i c h were lower than expected from linear projections from lake to l o w predation enclosures. The rotifer density increase i n relation to Daphnia l o w densities was limited by a factor other than  Daphnia 136  competition  i n the  medium  and h i g h predation  enclosures.  A  potential  explanation for this observation is that fourth instar larvae had become less selective w h e n densities of their preferred prey, such as crustaceans, were l o w (Pastorok 1980a; b). Chaoborids readily feed on rotifers (Fedorenko 1975b; M o o r e and Gilbert 1987; 1988b), or any other motile prey small enough to be captured and ingested (Moore et al. 1994).  Under high spring predation levels, the rotifer assemblage had only a very short period of time, between fourth instar pupation and first and second instar appearance, to increase to sufficient levels to support the new predator recruits. Unless the m e d i u m and high predation enclosures are assumed to have had deficient phytoplankton resources, enhanced  predation levels i n the  spring  might play a wider role than solely reducing Daphnia populations. That is direct predation  mortality may have  reduced  the  benefits  of enhancement  in  reproduction from competitive release that rotifers experienced. After fourth instar predators pupated, the rotifer densities increased quickly but had only a short period of time for population growth before the appearance of first and second instars increased predation pressure again on the rotifer populations. Such a limitation imposed by predation was underlined by the fact that, between day 182 and 210 (Figure 3.4), rotifer densities i n the h i g h predation enclosures continued  to decrease below 10 000 individuals m"  w h i l e they  increased  substantially i n the lake (to 46 000 rotifer i n d i v i d u a l s m" ) and i n the l o w predation enclosures (up to 38 000 rotifer individuals m" ), even under relatively 137  higher  Daphnia  densities  i n the  lake and the  l o w Chaoborus  treatments.  Predation rather than Daphnia competition probably limited rotifer p o p u l a t i o n increases i n high spring predator treatments.  After predation by Chaoborus instars,  followed  communities  out  by young of the  was removed, predator  six w h i c h  through  recruitment persisted  till  emergence of fourth  failure, 1993 or  two  enclosure  1994,  showed  relationships representative of the competition interaction between Daphnia and the solitary rotifers. After their predator cohort failed, enclosures  I and  H  maintained community interactions representative of the Daphnia domain.  3.5 C O N C L U S I O N The density of fourth instar larvae i n the spring influenced Daphnia and solitary rotifer population dynamics for the season. Enhanced predation levels resulted in both immediate and long-lasting effects on the Daphnia population dynamics. Immediate effects included delays i n Daphnia population onset, w h i c h resulted in lower Daphnia densities at the time w h e n young predator instars hatched and recruited. Longer-term effects resulted i n lower Daphnia  population  later i n summer. The longer delays, and the long-lasting effect under  densities higher  predation were likely due to the fact that i n early spring, fourth instar predators were feeding on the Daphnia i n d i v i d u a l s w i t h the highest potential for rapid growth and reproduction, i.e., the Daphnia females w h i c h hatch out of resting ephippial eggs and their progeny. 138  Increases i n solitary rotifer densities i n relation to reduced Daphnia populations were limited to a short period of time, after w h i c h y o u n g predator recruitment could apparently depress rotifer numbers.  In m e d i u m  and h i g h predation  treatments, during the time w h e n Daphnia population growth was delayed, rotifer densities d i d not respond so strongly as expected to the release  from  Daphnia competition. Excess predation i n these enclosures, potentially by fourth instar predators earlier i n the season and certainly by enhanced  densities of  young predator recruits, reduced rotifer population growth. Such  negative  feedback brought about by the impact of enhanced predator densities on the prey community could be an indication of an upper limit to the predation state.  139  CHAPTER 4  CHAOBORUS P U P A T I O N IN C O L D W A T E R : I M P L I C A T I O N S F O R LIFE HISTORY, DISTRIBUTION A N D P O P U L A T I O N D Y N A M I C S .  4.1 I N T R O D U C T I O N  The phantom midge, Chaoborus  (Diptera: Chaoboridae), is a voracious aquatic  predatory insect larva that feeds on zooplankton. The influence of larvae predation, on prey population  and community  addressed by several studies (Pastorok 1980a;  b; N e i l l  Chaoborus  dynamics, has  been  1981b; M o o r e 1988b;  Christoffersen 1990; Havens 1990). In this chapter, I address the influence of the pupal stage, the non-feeding  stage i n Chaoborus  dynamics, and indirectly on the recruitment  life history, on the  prey  of the young predators. In the  spring, Chaoborus larvae feed on Daphnia as they hatch from resting eggs, and Daphnia start their population increase. A s the larvae pupate, predation pressure is reduced, and the Daphnia  population can increase rapidly, thus reducing  rotifers, w h i c h are prey for the young predators. The longer the period between the onset of pupation and emergence, the lower is the potential for good predator recruitment, and for persistence of the predation state.  Unfortunately, little information is available on Chaoborus pupation, and w h e n available, it relates to pupation i n warmer conditions (> 12°C) (Luecke 1988; Christoffersen et al. 1993 b). Considering that at least one generation of nearctic 140  multivoltine populations, and all generations of u n i v o l t i n e populations, w i l l have to undergo pupation and metamorphosis i n the relatively cold waters of springtime, little information is available to evaluate temperature  on pupation.  In the  the impact of water  laboratory, I show  that the  impact  of  temperature can be substantial, but is different for the two species of Chaoborus, C. americanus understanding  and C. trivittatus. I relate the influence of temperature to o u r of the life history of these two species, their  geographical  distribution, and their potential impact on the prey population and their o w n recruitment.  4.2 M A T E R I A L A N D M E T H O D S  4.2.1 Field collection and laboratory set up  Four experiments were set up (Table 4.1). The first two, at 5°C, were devised to study the winter s u r v i v a l americanus.  abilities of Chaoborus  and  Chaoborus  The next two, at 9°C and 12 °C, were set up to investigate, i n m o r e  detail, the limitations of C. americanus fourth  trivittatus  development i n cold water. In all cases,  instar larvae were collected at night,  from  Shirley  oligotrophic fishless lake i n the Coast Range mountains  Lake, a s m a l l  of British C o l u m b i a ,  Canada. They were collected using a 102 |xm mesh zooplankton net (diameter: 0.4 m) hauled from 6-8m below the surface, at the deepest spot i n the lake. Larvae for the 5°C experiment were captured at the end of the season, shortly before the lake froze, on November 17th, 1992. For the  9°C and 12°C experiments,  the  larvae were collected i n springtime, on M a y 4th, 1995. After capture, the larvae 141  Table 4.1  Temperature  Laboratory experimental conditions for raising  Chaoborus.  (°C)  Light Regime (hr. light: hr. dark)  Food Regime  Chaoborus Species  Dates (StartEnd)  Number of Larvae at start  5  0:24  weekly  C. trivittatus  Dec92Mar94  24  5  0:24  weekly  C. americanus  Dec92Mar94  25  9  16:8  every 1-2 days  C. americanus  May95Sept95  32  12  16:8  every 1-2 days  C. americanus  May95Sept95  32  142  were transported to the laboratory i n 20 L carboys, w i t h zooplankton collected i n the same hauls, and were put i n an incubator at 5°C on arrival (between 1-2 hours after collection). The larvae were left to feed for 48 hours, then separated individually into 250 m l plastic containers containing lake water sieved t h r o u g h a 20 | i m mesh net. O n l y larvae w i t h food i n their gut were chosen for the experiments. D u r i n g the experiment, larvae were provided w i t h small prey, either small Daphnia, nauplii, or copepodites, depending on availability.  The 5°C experiment started i n early December 1992 and ended i n M a r c h 1994. Larvae were identified to species and put i n 250 m l plastic containers w i t h lake water. The containers were put on trays to facilitate future  handling and  observations, and were all put into an unlighted incubator (0 hr. light : 24 hr. dark) at 5°C, to simulate winter conditions under ice i n the lake. The larvae were taken out once per week and the following observations were made: 1) stage of i n d i v i d u a l : larva, pupa or adult; 2) alive or dead; 3) food trace i n gut or empty gut; 4) the number of prey eaten. Prey (eaten or dead) were replenished as needed. Larvae were returned to the cool unlighted regime incubator as soon as possible (15-45 minutes).  The 9-12°C experiments took place from early M a y 1995 to late November 1995. O n l y larvae w i t h food i n their gut were used. The larvae were assigned randomly to the 9 and 12°C incubators. Larvae were kept i n d i v i d u a l l y i n lake water i n 250 m l plastic containers. The containers were grouped i n 4L pails to  143  facilitate handling and observation. The incubators were set w i t h a 16 hr. light: 8 hr. dark cycle. Larvae were generally provided w i t h as m u c h food as they could eat. Zooplankton prey included, depending o n the season and source of supply, small and m e d i u m size Daphnia, nauplii, small and m e d i u m size copepodites of Diaptomus kenai and D . leptopus, and adult copepods of D . leptopus, collected  from Shirley lake, or when the mountain lake was inaccessible i n winter, f r o m ponds o n the U B C campus. Larvae were observed and food replenished every 1-2 days. Observations included: presence/absence of food i n the gut, number of prey eaten, signs of approaching pupation or metamorphosis, stage (larva, pupa o r adult), alive/dead.  4.2.2 Data analysis methods The proportion of larvae w h i c h died, pupated and metamorphosed was analyzed w i t h a % test. The life span, or stage duration data, were explored using medians and box plots, and further analyzed using survival analysis (Pyke and T h o m p s o n 1986). I used the Kaplan-Meier product limit (program "Pollock" by Dr. C . J. Krebs, Zoology, U B C ) to calculate the s u r v i v a l  rates over  time,  for each  experiment (Pollock et al. 1989). Time was defined either i n days, or i n degreedays, depending o n the question investigated. I traced the s u r v i v a l curves, a n d tested the distribution underlining these curves, using a two sample test (Pyke and Thompson 1986) based o n Cox's model (S-Plus 1995).  144  4.3 RESULTS Chaoborus  americanus  pupated at 5, 9, and 12 °C, w i t h substantial emergence  only at 12°C (Table 4.2 ). O n the other hand. C. trivittatus,  at 5°C, showed quite a  different pattern. Over half of the larvae that pupated, emerged.  A % test showed no significant difference amongst the experiments, for the number of larvae w h i c h died (% = 5.33, df=3, p=0.15). O n the other hand, the number of pupae w h i c h died versus emerged was highly significant (% = 63.55, 2  df=3, p « 0 . 0 0 0 1 ) . C o l d water temperature does not affect the switch from larva to pupa, but can have a drastic effect on the switch from p u p a to adult emergence.  The median number of days individuals spent as pupae was inversely related to the water temperature (Table 4.3). Moreover, variability i n duration of pupae i n Chaoborus  americanus  was also inversely related to temperature. The m e d i a n  number of days spent as pupae at 5°C, was the same (28 days or 140 degree-days), for the two species, but over half of C. trivittatus all C. americanus  pupae  pupae metamorphosed, w h i l e  died (Table 4.2). C. americanus  variability i n pupation duration compared to C. trivittatus  The Chaoborus  americanus  showed  greater  (Table 4.3).  larvae held at 5°C, and those held at 9°C, had  survival curves w i t h similar shapes (Figure 4.1). One important difference was  145  Table 4.2  Status of Chaoborus larvae i n laboratory experiments at different temperatures. The larvae which pupated but did not emerged died in the pupal stage, except for the one C. americanus pupa still alive when the 5°C experiment was terminated.  Number of larvae Experimental Temperature (°C)  Species Chaoborus  at start  which died  alive at end  which pupated  which emerged  5 5 9 12  trivittatus americanus americanus americanus  24 25 32 32  4 2 3 0  0 1* 1 0  20 23 28 32  11 0 2 29  * alive as pupa  146  Table 4.3  Temperature 5 5 9 12  Duration of pupation at the individual level  SPECIES  N=  trivittatus americanus americanus americanus  20 23 28 32  P U P A T I O N (in days) (median time as pupa) 28 28 19 12  Pupation Pupation M i n . time Max. time 21 35 3.5 32.2 10 23.1 10 13  147  Figure 4.1  Comparison of survival rates for Chaoborus americanus larvae raised at 5,9, and 12 ° C .  Time (degree-days)  148  that the die-off at 5°C took place later on the degree-day scale. These two curves are statistically different (Cox's calculation for two sample test: p=0.0001).  The shape of the 12°C curve was different than that of the 5°C and 9°C curves described above (Figure 4.1).The curve ended at approx. 1200 degree-days due to metamorphosis, and only a small proportion of the population died before metamorphosis took place. The decline i n survival i n both the 9°C and the 12°C curves started at 600 degree-days. However, at 800 degree-days, the two groups bifurcated from one another: 12°C pupae emerged, while the 9°C i n d i v i d u a l s died. By 1100 degree-days, all s u r v i v i n g 12°C pupae emerged while most 9°C individuals died. Chaoborus americanus death rate at 9°C was constant over the 800-1100 degree-day interval.  149  4.4 DISCUSSION Water temperature can influence aquatic invertebrates directly by affecting rates of i n d i v i d u a l development, and indirectly, by changing the timing and the strength of interactions i n relation to their predators, competitors and prey.  In laboratory experiments, I determined that water temperature d i d not have a significant effect on the number of larvae that reached pupation. The most direct influence of temperature on Chaoborus individuals was i n determining the number of pupae w h i c h could emerge. A t the colder temperature, the n u m b e r s w h i c h could emerge declined. This effect was different for the two species of Chaoborus. In C. trivittatus, 53% of pupae were able to metamorphose at 5°C, while no C. americanus  completed ecdysis (Table 4.2). Development i n C.  americanus seems to be limited b y a temperature threshold, that is C. americanus needs a temperature cue to metamorphose and finish its life cycle. B y the t i m e i n d i v i d u a l pupae reached an accumulation of 800 D D , the level at w h i c h 12°C individuals started pupating, the proportion of 9°C i n d i v i d u a l had declined to 70%. By 1100 D D , when 12°C i n d i v i d u a l finished pupating, 9°C i n d i v i d u a l survival had declined to below 20%. Moreover, C. americanus pupae held at 5°C, lived as long (28 days) as those of C. trivittatus, but the former died rather t h a n emerge like the latter. Thus, the accumulation of a certain number of degree-days is not sufficient as a threshold to allow metamorphosis i n C. americanus:  a  minimal temperature threshold is needed. Such a temperature threshold, rather than a degree-day threshold, could explain the  difference i n geographical 150  distribution between C. americanus and C. trivittatus. The latter is found i n lakes in higher latitude (Borkent 1981) and higher altitude (Borkent 1981; Lamontagne et al. 1994) than C. americanus.  In relation to its more southerly distribution,  Lamontagne et al. (1994) showed that C. americanus was not found i n lakes w i t h a mid-summer surface temperature below 16°C.  Delays i n  individual  development  or  increased  mortality  due  to  cold  temperature lead to delayed onset of pupation and emergence, and can affect population and community dynamics. C o l d water temperature delays the onset of pupation and emergence by lengthening the time spent i n the different l a r v a l instars. Temperature induced developmental delays can indirectly affect the interactions of Chaoborus w i t h their prey and predator populations. Luecke (1988) showed that i n Lake Lenore, pupae were captured by trout i n greater proportion than the larvae although the latter had relatively larger density. I n his study, pupae of C. flavicans  emerged i n two days at 19.2°C, while they  required 8 days at 16°C. H e modeled the emergence i n relation to temperature and predation by trout, and he calculated that trout could remove 23% of the population of Chaoborus pupae day" at the peak of the pupation period. T h e 1  colder was the water the longer was the p u p a l stage, w h i c h increased  the  probability for pupae of being eaten before emergence. H e suggested that this could explain w h y the summer cohort i n Lake Lenore had better recruitment than the spring cohort. In the presence of a pupa predator, Chaoborus greater losses i n cold water. By the same principle, but i n regards to  suffers  Chaoborus 151  predation on Daphnia, as cold water lengthens the pupation period, Daphnia population is released from predation by Chaoborus for a longer period of t i m e . A s Daphnia population increases, rotifers are outcompeted and their populations decrease [Neill, 1984 #250; see Chapter 3]. U n d e r prolonged pupation and delayed emergence, predator recruitment could be drastically reduced due to a scarcity of rotifers u p o n which to feed. This effect is compounded i n C. americanus  because  emergence is prevented until temperature reaches 9 °C or more. In the event of a cold spring, the Daphnia population has a longer w i n d o w of time to increase its density, if it is little affected itself, by cold temperature.  In the laboratory, I showed that C. americanus  needs a water temperature above  9°C to produce substantial emergence. In the field, this threshold could be lower. In lakes, C. americanus  larvae undergo diel vertical migration (Teraguchi and  Northcote 1966; Fedorenko and Swift 1972). Pupae have also been observed to migrate vertically (Luecke, 1988; pers. observ.). (Luecke 1988) By migrating to the upper water layers, pupae take advantage of warmer temperatures faster.  Moreover, under  fluctuating  temperature,  temperature  for development  temperature  range (Ratte 1985). Even under temperature  daily mean temperature  can be  expanded,  the  to develop  favorable  especially i n  range the  of  lower  regimes showing a  below the lower constant temperature  limit,  some  insects are able to complete their development, while they fail to develop u n d e r the mean comparable constant temperature  (Lin et al. 1954; Messenger and  Flitters 1958: i n Ratte, 1985). Figure 4.2 schematically describes the relationship  152  Figure 4.2 Schematic representing the effect of developmental rate acceleration due to fluctuating temperature i n the low part of the range of developmental temperature of an insect. A s temperature increases, so does d e v e l o p m e n t a l rate. However, i n the lower part of the range, developmental rates under fluctuating temperature are faster than expected b y extrapolating to d e v e l o p m e n t a l temperature zero (T ) indicated by the dashed line intercepting the temperature axis (based on Messenger and Flitters, 1958: cited i n Ratte, 1985). 0  I  L  T  0  Low  High M e a n temperature  153  between mean temperature and developmental rate. The dashed line represents the relationship expected under a constant temperature regime. The relationship is extrapolated d o w n to the developmental zero temperature, where no growth takes place. The bold  line  represents  the  relationship  for  a  fluctuating  temperature regime, w i t h the same mean as the constant regime. Over a certain temperature range, both the constant and the fluctuating regime, produce similar developmental rates. In the higher part of the temperature range, the constant temperature regime produces higher developmental rates, than the fluctuating temperature regime. However, i n the lower part of the temperature range, the fluctuating temperature regime produces the higher developmental rates (Ratte 1985).  If C. americanus  can overcome the fixed 9°C threshold, under  fluctuating  temperature I w o u l d expect that more pupae w o u l d be able to emerge than the number observed i n m y fixed temperature experiments i n the laboratory. Ratte (1979; 1985: cited i n Buns (1991)) showed that for larvae of C. crystallinus laboratory, fluctuating temperature allowed faster development.  i n the  But i n field  enclosures, larvae raised under both homogeneous (within the epilimnion) and fluctuating temperatures (where larvae were allowed to migrate between e p i l i m n i o n and cooler h y p o l i m n i o n ) , had nearly equal developmental This result might be confounded, because food levels i n the enclosures  the  times. were  lower than i n the laboratory experiments, and larvae might have been limited by food, rather than by temperature. H e d i d not investigate the effect of fluctuating  154  temperature on pupa developmental rates. However, as food level is irrelevant during pupation, I w o u l d expect that pupa developmental rates w o u l d be affected by temperature fluctuation, as i n Ratte's laboratory experiments.  However,  different species can develop at different rates under the same temperature regime. Fluctuating temperature experiments i n the laboratory or i n the field are needed to determine  the impact of such a temperature regime on p u p a l  development. Moreover, physiological and biochemical experiments are needed to pinpoint w h y C. americanus  pupae can develop and darken as if to emerge,  but cannot complete pupal ecdysis i n cold water. Perhaps  certain  essential  chemicals are not synthesized or active below the threshold temperature.  4.5 CONCLUSION Water temperature below 9°C prevents Chaoborus  americanus  emergence i n the  laboratory. This partly explains this species' more southerly and lower a l t i t u d i n a l distribution, compared to C. trivittatus.  In the field, pupae w o u l d  encounter  fluctuating temperature through diel vertical migration, and could potentially avoid the limitation imposed on their development by the fixed temperature threshold  observed i n the laboratory. The m i n i m u m  temperature  on  Chaoborus  pupal  development  is to  effect of cold lengthen  water  pupation  duration, and to delay emergence. This prolongs the period of time available to Daphnia  to bloom under l o w predation pressure. This could have a negative  impact on the resilience, and the persistence of the predation state.  155  CHAPTER 5  GENERAL DISCUSSION A N D CONCLUSION  5.1 The makings of an extended transient state  Shirley Lake does not  have  two functional  domains  of attraction  zooplankton community i n relation to predation by Chaoborus. Chaoborus  of its  In theory, the  domain could still be present, but it is apparently very small. I n  practice, considering the variability i n environmental factors, the c o m m u n i t y w o u l d not stay w i t h i n such a small domain long enough for this domain to be detectable. The community w o u l d barely have time to settle into the  Chaoborus  domain before being pushed out of it again by a new disturbance. Delays i n predator development induced by high predator densities i n the spring support the idea that no, or at most, a small Chaoborus  d o m a i n exists i n oligotrophic  lakes such as Shirley Lake.  Enclosure experiments containing high predator densities indicated that prey populations could be depleted. Thus, the prey c o m m u n i t y production rate could be overcome by the Chaoborus  predation rate. One indication of limited prey  production was observed as reductions i n both Daphnia  and rotifer densities i n  m e d i u m and h i g h predator treatments compared to their densities i n the l o w predation experiments and i n the lake. A n o t h e r indication of limitation was  156  delays i n predator development, w h i c h suggested that prey production was not sufficient to feed the enhanced predator populations i n late summer. Resistance mechanisms,  such as flexible predator growth, can usually  counterbalance  variability and limitation i n prey production and prevent  the system from  switching state. For example, i n fish, delays i n i n d i v i d u a l  growth such as  stunting are observed, especially i n older year classes, w h e n food is sufficient for survival but hardly for growth (Scheffer et al. 1995). Chaoborus  also s h o w  developmental delays under l o w food conditions (see Chapter 2, section 2.3.3). I n the Shirley Lake field enclosures, such starvation-resistance mechanisms were overcome by the strength of the disturbance and recruitment of older instars was lower than necessary to sustain predation pressure. A l t h o u g h young instar recruitment had been improved, large prey were not available i n sufficient densities for all the predator larvae that had s u r v i v e d the enlargement of the original  recruitment  bottleneck  of young predators.  In  other  words,  the  bottleneck moved from first and second instars to the third instar (Figure 5.1).  Survival bottlenecks are not an attribute of the predator, Chaoborus, or of the zooplankton community of Shirley Lake exclusively. In general, animals and plants that live i n variable or unpredictable environments hedge their bet and produce large quantities  of young. In adverse  conditions, y o u n g recruits  encounter a limitation, e.g., food, territory or egg laying site availability. Few w i l l survive to reproduce. In more favorable environments, the bottleneck can be overcome and survival is improved. Organisms w i t h complex life histories,  157  Figure 5.1  Schematic representation of the bottlenecks in Chaoborus recruiment.  A n increase in nutrient moves the start of the bottleneck without much enlargement (a, b). Only when nutrients are increased sufficiently to increase substantially zooplankton productivity can the bottleneck be enlarged.  Chaoborus Instar  a) oligotrophic lake (e.g. Shirley Lake, and Gwendoline Lake, Neill, 1988b)  b) enclosures with added nutrients  c) eutrophic lake (e.g. Triangle Lake, Havens, 1990)  158  including those w i t h ontogenetic shifts, face the possibility of a bottleneck at each stage i n their development. G o o d environmental conditions at one stage does not prevent the potential for a bottleneck at another stage i n their life history. I n these organisms, the bottleneck  can only be overcome  if e n v i r o n m e n t a l  conditions are favorable at all stages of their life history.  In m y enclosures, the bottleneck i n Chaoborus s u r v i v a l took place at the t h i r d instar. However, delays i n predator development from third to fourth instar d i d not apparently reduce overwinter s u r v i v a l of fourth instars but could  have  lengthened the time they spent as fourth instar larvae i n the spring and could have desynchronized the timing of pupation and reproduction. Presence of fourth instar larvae over longer periods of time i n the spring delays Daphnia population growth and should improve recruitment  conditions for y o u n g  predator larvae. However, as older larvae can cannibalize the y o u n g recruits (Fedorenko 1975b) there could be an appreciable reduction of young predator recruitment, despite l o w Daphnia densities and h i g h rotifer densities. F o u r t h instar larvae w i t h developmental  delays i n spring can negate the  benefit  provided by delayed Daphnia population increase and prevent persistence of the Chaoborus state.  In m y experimental enclosures, the threshold was initially crossed and the community dynamics m o v e d into the Chaoborus state. This alternative state d i d not persist over several predator generations:  it is thus a transient  state.  159  However, the predation state was maintained for more than a season. The signal generated  by the  experimental  predator  gradient  imposed  in  1992  was  transmitted overwinter, that is from one season to the next. Enhanced fourth instar predator i n spring 1992 resulted, i n spring 1993, i n enhanced fourth instar predator density w h i c h generated  important  delays i n Daphnia  population  growth. Aquatic ecologist often think that winter resets the dynamics to zero for the start of a new growth season. In m y experiments, predator densities were not reset to l o w level as i n the lake after the winter. The predator state persisted for more than one season but less than two predator generations. The predator state is thus an extended transient state.  From an ecological perspective, extended transients can provide an opportunity to maintain high diversity i n an ecosystem by allowing inferior competitors or rare species to take advantage of the change i n conditions. For example, i n Shirley  Lake enclosures,  the  transient  state allowed longer  w i n d o w s of  recruitment for rotifers, Chaoborus, and assumably for phytoplankton. The time duration of an extended transient state depends on the generation time of the longest-lived main player i n the system. For example, i n Lake Mendota, a strong year class (1977) i n Cisco, a long-lived planktivore fish, reduced the population of Daphnia pulicaria, a previously dominant zooplankton prey (Rudstam et al. 1993). The latter was replaced by Daphnia galeata, a smaller species, less sensitive to size-dependent predation by fish. The switch to the smaller and starvation-prone  more  suspension feeder led to shorter clear-water phases i n the  160  spring. Phytoplankton dynamics and Daphnia composition and biomass were affected for 10 years by the success of one year class of a dominant p l a n k t i v o r e (Rudstam et al. 1993).  The shift between alternative states, be they domains or transient states, occurs i n systems where one or more of the functionally "important" species w o r k at the edge of their ability. W o r k i n g i n what could be considered an extreme c o n d i t i o n (e.g. limited resource, limited refugia, or physiological stress) for that species, the system w i l l move i n a new direction ( G r i m m and Wissel 1997). The system approaches and crosses a boundary between states. The system dynamic m o v e s from density-dependent to density-vague behavior. For a population w i t h a sufficiently large variance i n numbers, recruitment w i l l seem to be densityvague  at intermediate  levels, and  density-dependent  at  small  and  large  population levels (Carpenter 1988b).  5.2  Dynamical thresholds: the role of nutrient availability, temperature and  species c o m p o s i t i o n In many experiments, increased nutrient availability has been required to obtain the shift i n community dynamics (Neill 1988a; Moss 1990). Furthermore, w h o l e lake studies (Neill 1988b; Moss 1990; Stenson 1990) show that the mechanisms observed i n enclosures also apply at the lake scale. N e i l l (1988b) hypothesized, based on his enclosure and whole lake experiments i n G w e n d o l i n e Lake, that oligotrophic lakes do not produce enough prey to sustain higher  Chaoborus 161  predator densities. In his whole lake study, fertilization of the lake d u r i n g one season modified the zooplankton biomass, however it d i d not result i n a lasting qualitative change, and d i d not increase predator densities i n the subsequent season. Stenson (1990) limed a fishless, acidic, oligotrophic lake and observed a switch to increased Chaoborus (C. flavicans  and C. obscuripes) densities. L i m i n g  i n acidified lakes improved abiotic properties of acid water and freed nutrients.  Small  cell phytoplankton  density, rotifer  density, and  up  predator  recruitment increased. O n the other hand, Bosmina coregoni, a small cladoceran (< 0.5 m m i n length), decreased. The switch to Chaoborus state persisted o v e r two years i n Gardsjon Lake i n Stenson's study.  In Shirley and Gwendoline Lakes, Chaoborus were present i n l o w densities and had little impact on cladocerans. Enclosure experiments (Neill and Peacock 1980; N e i l l 1981b; 1988a) showed that Chaoborus  could reduce Daphnia  and other  crustacean species' population biomass, w h e n the system's nutrient levels were increased. This allowed a greater proportion of the primary production to reach the rotifers, thus yielding an enhanced prey base for young predator recruitment.  Predation impact by Chaoborus  on prey populations i n eutrophic conditions  differs from the predator impact i n oligotrophic conditions. Havens  (1990)  conducted exclosure and enclosure experiments i n fishless, rotifer-dominated and eutrophic Triangle Lake. A l t h o u g h his enclosures harbored h i g h densities of Chaoborus: (200-800 second and third instars m" i n M a y and June), he concluded, 162  w h e n he compared enclosure and exclosure experiments, that Chaoborus  in  temperate eutrophic lakes, such as Triangle Lake, do not have a major top-down effect on rotifers. The rotifers' intense reproductive output may greatly exceed losses due to Chaoborus  predation. O n the other  hand, h i g h densities of  Chaoborus might impact the crustacean zooplankton to a greater extent because crustaceans have longer generation times than rotifers (Gannon and Stemberger 1978 cited in Havens 1990). In comparison, although second and third instars i n Shirley Lake enclosures reached similar levels (200-1000 i n d i v i d u a l s m" ) as i n 3  Triangle Lake enclosures, the former were associated w i t h a reduction i n rotifer densities. This is evidence supporting the limitation of rotifer production by l o w nutrient i n Shirley Lake experiments.  References about mesotrophic lakes showing multiple domains of attraction have not been found. If these lakes often switched, the data w o u l d be very variable, difficult to analyze, and thus might not have been presented i n the literature. O n the other hand, for similar nutrient levels, mesotrophic lakes are sometimes classified as "oligotrophic" or "eutrophic" based on their species assemblage. Re-analysis, w i t h the idea of thresholds i n m i n d , might provide n e w insights on the variability i n dynamics of mesotrophic lakes. N e w experiments in mesotrophic lakes might highlight discontinuous system behaviors.  Other factors, such as water temperature, can also indirectly reroute p r i m a r y production to rotifer populations by affecting rates (e.g. growth, predation,  163  survival)  differentially between species or groups  (e.g. cladocerans  versus  rotifers, predator versus prey). In a cold year, because Daphnia productivity was reduced more than that of the rotifers, Chaoborus even  more  increase the  substantial  (Neill  predation impact could be  1988a). Delayed Daphnia  size of the w i n d o w for young predator  dynamics indirectly recruitment.  Delayed  predator development has a more ambiguous effect. Small delays w o u l d increase the  young  predator  recruitment  window  by  further  delaying  Daphnia  population. O n the other hand, long delays w o u l d decrease that w i n d o w by desynchronizing the predator reproductive period and allowing cannibalism o n the young recruits. Change i n temperature is not essential to obtain a shift i n community structure or dynamic. However, it is an important factor to take i n t o consideration w h e n trying to predict the impact of a disturbance  on  the  community. The same disturbance, applied i n a cold or a w a r m year, can give quite different results (Neill 1988a; Scheffer 1998).  Species composition can also influence the state i n w h i c h  the  community  functions. In the Gardsjon Lake study (Stenson 1990) mentioned  previously,  m i n i m u m and m a x i m u m total phosphorus i n the lake (3-9 pig l " P) includes the 1  range observed i n Gwendoline Lake (3-6 | i g l" P) and i n Shirley Lake (4-7 tig l " P). 1  1  A major difference w i t h Gwendoline and Shirley Lakes is that the  dominant  cladocerans i n Gardsjon Lake, studied by Stenson, were small species, such as Bosmina  coregoni  and  Diaphanosoma  brachyurum,  rather  than  large  cladocerans such as Daphnia. The small cladoceran species do not monopolize as  164  m u c h of the phytoplankton resource as w o u l d  larger cladocerans, such as  Daphnia (Bogdan and Gilbert 1982; DeMott 1982). In the presence of a smaller and less efficient cladoceran species, rotifers can harvest a greater portion of the primary production to maintain their populations. This means that the presence of the second domain depends not only on the nutrient level that sets the productivity of the system, but also on h o w this production is divided between the competing prey species. Enclosure experiments using Bosmina  i n conditions  representing Shirley Lake, or using Daphnia i n conditions representing Gardsjon Lake w o u l d give an interesting comparison between oligotrophic systems.  Hence, lake productivity i n itself is not a sufficient indicator to predict i n w h i c h domain  or state the  lake w i l l  be found.  productivity to the rotifer compartment  The  allocation of the  primary  w o u l d be a better indicator of the  domain or state i n w h i c h the community functions.  5.3 Alternative domains and states: importance of the threshold perspective The controversy between Connell and Sousa (1983) and Sutherland (1981; 1990) about the existence of alternative  states i n natural  communities  is better  understood as a question of perspective. C o n n e l l and Sousa d i d not have a threshold perspective i n m i n d . They considered only systems w h i c h responded to the pressure applied to them. Systems w h i c h  resisted change were  not  included i n their analysis of the presence of alternative states (Sutherland 1990). 165  If a system sometimes remained unchanged and sometimes changed under disturbance, Connell  and Sousa only  retained  as data the  system  which  responded. They had eliminated, by definition, and as a matter of perspective, information pertinent to their discussion. F r o m a threshold perspective, the fact that a system does not respond under certain circumstances and responds under others is of major importance.  The work of Connel and Sousa (1983), the criticism of Sutherland (1981; 1990) and the criteria used to choose variables and their range for a study indicate that notions of "stability" (e.g. persistence, resilience, resistance, d o m a i n of attraction) are context related. These notions depend on the variables and their  range  chosen for the study, on the time/spatial scales i n v o l v e d ,  on the level of  description  finally,  chosen  (e.g.  population,  community),  and  on  the  characteristics of the disturbance (Pahl-Wostl 1995; G r i m m and Wissel 1997), elements  which  comparisons  should  between  be included  in  a "stability statement"  systems can be made  more  easily. W i t h  so  that  a better  understanding of what facet(s) of stability is(are) addressed i n a study and w i t h more comparisons between systems, thresholds and alternative states might be observed i n more systems than those currently.  166  5.4 Hysteresis: one threshold when going up, another when going d o w n  Because ecological systems have built-in mechanisms to resist change from one domain to another, it is expected that ecological systems w i t h a threshold crossed w h e n going from domain " A " to d o m a i n " B " might have a second threshold w h e n going from domain " B " to domain "A" (Figure 5.2).  Hysteresis loops are usually present i n models for systems w i t h alternative states (Noy-Meir 1975; L u d w i g et al. 1978; A d a m s and DeAngelis 1987; Scheffer 1990; 1991a; Carpenter and Pace 1997). The presence of a hysteresis indicates that the system possesses resistance, w h i c h prevents or delays a change between d o m a i n s of attraction. It also indicates the range of the variables or parameters at w h i c h both the resilience and the resistance of the system are low: where a system's behavior i n the face of disturbance w i l l be less predictable. In phase space, this is represented by the area between and including the thresholds forming  the  hysteresis loop (Figure 5.2). For a disturbance of a certain size, a c o m m u n i t y outside the hysteresis area remains i n the vicinity, or rebounds to its o r i g i n a l attractor. For the same size disturbance, a community i n the hysteresis area could switch attractor. For example, referring to figure 5.2, apply a two-centimetre disturbance, parallel to the x-axis, to a point sitting on the upper attractor, first under the letter " B " , then i n the m i d d l e of the range where the hysteresis is. I n the first case, the point stays on or close to the attractor and its location can easily be predicted. In the second case, the point is taken over a threshold (indicated by xxx). The system w i l l switch attractors. N o w imagine that the range where  167  Figure 5.2  Schematic representation of a hysteresis loop and the area of dynamic unpredictability i n system w i t h two domains of attraction. The dynamic trajectories of the system are different when the system goes from A to B, and from B to A . The hatched area represents a zone of increased variability and unpredictability in system behavior. In this area, a small disturbance is sufficient to switch the system between the two attractors.  168  hysteresis occurs is not w e l l defined (lots of variability around the location of the thresholds). Redo the second exercise and try to predict i n what d o m a i n the system w i l l be found. The end result is unpredictable. One can do a s i m i l a r exercise using the frequency of disturbances rather than size. If the size or the frequency of disturbances, or the true location of the thresholds, are not k n o w n or predictable, the resulting domain for a point located away from the hysteresis area w i l l be more easily predicted, than the domain for a point positioned w i t h i n the hysteresis loop.  In the field, separate experiments are required to reveal the two thresholds. F o r example, I passed the threshold from Daphnia d o m a i n to Chaoborus  state by  adding predators and removing Daphnia. To reveal a hysteresis, I w o u l d need to start experiments i n Chaoborus state and reduce predators or increase  Daphnia  densities to see if this threshold is different than the first one.  5.5 Management issues i n a threshold perspective From a management perspective, the range of a variable between, and i n c l u d i n g , the thresholds (see hatched rectangle on variable 1, Figure 5.2) should be avoided entirely to maintain the system w i t h i n a chosen d o m a i n of attraction. In the zone between the thresholds,  unpredicted, and  unpredictable,  events  and  disturbances w i l l be more likely to bring about large changes i n the system t h a n these same events taking place outside the hatched rectangle. F r o m a s a m p l i n g 169  perspective, the hatched rectangle is the range of the variable that, i n the field, w i l l require the use of adaptive sampling designs (Thompson 1992), where the sampling interval changes based on the value of the variable sampled rather than based on the calendar (Ouimet and Legendre 1988).  Thresholds associated w i t h extended transient states can become a useful tool i n management  interventions  when  managers  require  a temporary  system  alteration. The system can be pushed, through a disturbance, into the transient state and it should return on its o w n towards the attractor of the domain. O n the other hand, if a manager requires a "permanent" change i n the system and that system possesses an alternative  extended  transient  state rather  than  an  alternative domain, the intervention w o u l d look successful at first but w o u l d fail over time. W h e n  information on the system is scarce, differentiating  between a system w i t h alternative domains from one w i t h one alternative domain and an extended transient state is practically impossible. Long-term monitoring of management interventions is essential to collect the i n f o r m a t i o n needed to differentiate between the presence of domains and that of extended transient states.  170  CONCLUSION  Nonlinearities i n prey and predator  population  dynamics and i n  predator  functional response can lead to thresholds and multiple domains of attraction. Because of such nonlinearities, a predator can regulate prey populations over a certain range of a variable and cannot over a different range. Factors such as size structure and ontogenetic shifts generate pools of i n d i v i d u a l s w i t h  different  abilities, thus w i t h different potential growth and population dynamics. U n d e r disturbance, the different pools of i n d i v i d u a l s (e.g., small versus large, y o u n g versus  adult)  can respond  differently,  generating  nonlinear  responses  in  population dynamics and increasing the possibility for thresholds  i n system  behavior.  egg/young  In variable  or  unpredictable  environments,  surplus  production can also generate nonlinearities i n dynamics by establishing a h i g h potential for change i n population dynamics. This potential can decay over time, resulting i n no change i n population dynamics, or can be fulfilled, resulting i n a switch between system states.  In m y experiments, enhanced fourth instar Chaoborus expanded the recruitment between the Daphnia  densities i n the spring  w i n d o w for young predator instars. A  domain and the Chaoborus  threshold  state was crossed. In the  literature, the number of systems, aquatic and terrestrial, w h i c h are shown to have thresholds i n community behavior is increasing, and there are n o w a few examples of systems w i t h at least two domains of attraction.  171  Considering the potential for nonlinearities i n population dynamics and species interactions, and considering the complexity of natural communities, the current paucity of systems representative  of multiple domains  might be more  a  reflection of the perspective and tools used to focus research efforts, than a true representation of the functioning of ecological systems. A shift i n perspective from 'stability' to variability, from equilibria to thresholds, w i l l influence the results we can observe, the way we interpret them, and more importantly, w i l l influence  the questions we can answer (Breckling 1992; Pahl-Wostl  1995).  Furthermore, common statistical tools often mask the presence of thresholds. They are w e l l suited for data analysis w i t h i n states, but can often give erroneous interpretations w h e n the data span more than one d o m a i n or state, therefore underestimating the number of ecological systems w i t h thresholds i n their dynamics.  Once a discontinuity i n dynamics has been observed, a distinction between domain of attraction, transient state or extended transient state must be made. This categorization requires detailed information, as w e l l as experimentation and modeling, to determine the extent of the states and their persistence. T h e distinction between types of states is especially important intervention for ecological management.  w h e n designing  Determining i n w h i c h systems, and  under what conditions thresholds w i l l be reached, or avoided, is of increasing importance as we steadily increase pressure (rate and size of disturbances) o n managed and natural systems.  172  A  Enclosure construction design  - Enclosures were made of white, w o v e n polyurethane plastic - Float was made of extruded plastic foam and inserted i n yellow coated ( U V protection) w o v e n polyurethane plastic - W o o d frame was made of 2X4 rough cedar  173  APPENDIX B  M e t h o d for enclosure f i l l up w i t h pumps  Enclosure were filled using 3-inch diameter diaphragm pumps. Five p u m p s , operated by five volunteers, were used to fill enclosures two at a time, over the same period of time. The pairs were as follows: B-C, D-E, A - F , G - H , I-J. The p u m p output hose was set i n the first enclosure of a pair for about half hour. The hose was then moved to the second enclosure for about one hour. The hose was moved back for another half hour to the first enclosure. In this w a y , migrating or new  blooms of zooplankton could be divided up between enclosures  more  equitably than by filling one enclosure fully at a time. Water was p u m p e d i n until the enclosure was w e l l rounded on the sides.  174  APPENDIX C  Comments o n predator time series 1992-1994.  I present the details of the three year time series for each instar i n A p p e n d i c e s C - l to C-4. Time series patterns are based on a single replicate measurement  series  per station from M a y 1992 to October 1994.  I noted several discrepancies between the life histories of C. americanus  and C.  trivittatus w h i c h can affect the interpretation of the data. C. trivittatus i n Shirley Lake seems to have two reproductive periods w h i c h means that second instars are present most of the time i n the lake. O n the other hand, C. trivittatus d i d not recruit w e l l i n the enclosures. The data I present under the expression "total Chaoborus", i n the Appendices and i n Chapter 2, represent (1) i n the lake, the total of both species for each date over the three year study, (2) i n the enclosures, the total of both species till July 1992 and only C. americanus thereafter.  Several features  from July 1992  of Shirley Lake time series originated from  the  peculiarities i n the life history of C. trivittatus. not previously observed i n neighboring lakes These included extended period of first instar recruitment from M a y to November rather than i n June-July only (Appendix C - l , panel 1), presence of second instars throughout the year, including a second peak i n the fall (Appendix C-2, panel 1). Moreover, I observed i n the lake and i n some enclosures that C. trivittatus and C. americanus  were overwintering i n second  and third instars (Appendices C-2 and C-3), and that larval development took place over the winter. Finally, first and second instars, w h e n present i n the fall (Oct., Nov.),  were observed to migrate vertically. They were found i n greater  density i n the deeper samples and i n lower density or absent from the 0-3 m  175  samples (Appendices C l - and C2, panel 1). Usually, young instars are neither found i n the fall nor found to migrate.  Both the lake and the enclosures experienced not one but  two m a i n seasonal  declines i n fourth instar densities. (Appendix C-4). The first decline, i n June and July (Appendix C-4, panel 1)), is representative of the disappearance of fourth instars larvae from the water c o l u m n as they pupate and emerge to reproduce. The decline i n the lake is less pronounced because a good proportion of predators are Chaoborus trivittatus, a species w h i c h d i d not recruit i n the enclosures and which, i n Shirley Lake, pupate, emerge and reproduce at different times than C. americanus  (Figure 2.2). Thus, i n the lake, fourth instar larvae are always  present, although at l o w levels (generally < 50 larvae m" ). The second decline takes place i n the fall (October-November) and represents not a true decrease i n fourth instar larvae densities, but a v i r t u a l one. Because the fall and subsequent spring densities are generally similar and because reproduction does not take place i n the winter, I attribute the winter decline to a change i n "behavior" o n the part of the predators. In the lake, where two different depths were sampled (Appendix C-4, panel 1)), I found a greater density of the fourth instar larvae i n the deep samples i n late fall than d u r i n g the summer. A s s u m i n g the same relationship for the enclosures, I can conclude that the larvae were present, but below the depth sampled. Fourth instar larvae are k n o w n to move deeper i n late fall and winter (Fedorenko, 1972). Moreover, i n cold temperatures, the a n i m a l s have lower respiration rates (Swift, 1976), and higher food assimilation (Giguere, 1980, 1981). W i t h lower food intake requirement to fulfill i n cold conditions, a greater proportion of the population stays i n deep water instead of undergoing vertical migration each day. 176  M o n t h l y sample time series for total Chaoborus first instar larva density i n Shirley Lake and i n experimental enclosures from 1992 to 1994  APPENDIX C - l  Time is indicated in months and in Julian days over three years  (1) Lake;  (2) Low  (3) Medium (4) H i g h predator treatments  1992  1993  fr e „ Sj> £ tj fc * fr i2 2, Z< £ o 2 J  I  I  I  I  L  I  I  1994  w> "S,  I  I  I  I  H-  >  I  L  I  I  1_J  I  1 0 rH  J 10  3  -i  I L  J  I  I  I  I  I  L  J  1—1  I  I  I  I  L  1 1 1r 0  0  0  0  1—1  CN  ^ O CO C S C S CO CO  I  I  I  I  I  L  ft  |:\ 10  10  2  J  t ***  \  i \  J  io°  1  *  I".  •  :  -  ST e  SP cL — fc  \  —1—r~i—rn—1—1—r  I  6  * fr  -*  fr  0  n, -w >  i l l Z $ 6 I J  ^  I  fn—1 0 0 ID rH  J  0 0 r-4 I  I  0  I  I  L  J  1 1—1—r 0  0  0  O CO CN CO CO  I  I  I  I  L  1 1 1 1 1r fr a - SP O H - fc 2 £ £ < cn O Z  I  I  I  I  1 1 1 1 1 1 1  L  1 1 1—1 1 1—1—r o o o o o o  0  r H ^< CN CN  I  I  J  0 0 rH  rH CN CN  t N O CO CN CO CO  I  I  I  I  I  L  J  cy  t-4  j  3  S T U D  < S £ Z< % O Z  1  1—r  1—r  ^ o.  1 i n 1 r _ SP a- - fc  I  I  I  0  o  p  O  I  I  I  I  L  l—rn—1—r  r  ^ fr ro- <2 c  177  APPENDIX C-2  Monthly sample time series for total Chaoborus second instar larva density in Shirley Lake and in experimental enclosures from 1992 to 1994 Time is indicated i n months and i n Julian days over three years  (2) L o w (3) Medium (4) H i g h predator treatments  (1) Lake;  1992  1993 0*5 5 'S s « " o  2 £ £ < « OZ  j-1  I  l__l I  1994  I L  J  I  I  I  I  I  I  60 "K, H - . 3 V> a' ST « «  a, ,2 a -2-  L  J  I  I  I  I  I  o  I L  10 ^ 10 2  10\ 10°.  i  o oi—i o o i—r o o o in oo r n o ro rH  rH  J  I  CN CN  I  10 -J J  CN  CO  I  I  I  CO  L  i i T—t  i—r  T—I  i—I  CN CN  CN CO  I  I  I  I  _l  I  o  I L_  J  I  o  o  o  CN  CN  (N  O CO CO CO  I  I  I  I L  T-I  CO  I  — .A f—r o  o  "\ I  10' 10  1  10° . i "i i '  _ 10 •'-J  10 i  i—i—r  60 Q,  <=  1V  I—TTT—I—T  >  T3 3  V-  F ^ / G  c  1 ' 1  l  ?  CN CN  3  10  M.OZ  / ' A ' '*  \ \A  10 -J 10  Q, * >  a> « o  CN  1  CO  CO  l  I  o o  (N 1/1 r H r H  1 ' 1  1  1  1  o o o o o o  O O r H ^ t - » CN CN  t x O C CN CO  1  O CO  0 0 CN  /  l l l  m  T—IT—I  l l l l o o o o o o  C O r - l T f t > . O C O CN  T-H  1  1 i i  r , ^. rr . T M Q, *» > •72 3 of H O  >-• m  CN  CN  i ii  CO CO  ii  L-6m  L-3m  2  §  i ji' i —  /'  I I i i i ii o o o o o o o ID 00 r H O CO rH  r*-3 % c3  » "73 3 5, <  .'i i •,  1  rH  O  aj i  A  10 . :  ir  _  :  10°.  i  1  10°  \_ j—i 2  i 41,  u i—i  < Cfl  r  OZ  T^ *3  7  i  TTT  I  I a  T^TT I I M n, * . >  £ < w0 Z  178  Monthly sample time series for total Chaoborus third instar larva density in Shirley Lake and in experimental enclosures from 1992 to 1994  APPENDIX C-3  Time is indicated in months and in Julian days over three years  (2) L o w (3) Medium (4) H i g h predator treatments  (1) Lake;  1992  1993  1994 fc fr d  10  3  10  2  J  I  I  I  I  I  L  J  I  I  I  I  I  I  I  r~TZ1 ' W OH'  I  L  a, ** >  0 0  I  I  I  I  i  i  i  i i r o o o o o  I  I  I  J  I  I  I  I  I  L  I  L  J  10 J 1  F , I  I J I  fc " fr' C '  < £  TTT ' >  £ < $ O Z  1 1 1 1 1 1 11  ^ LI—i—i « S •=  I OH J  I  I  I  i~ i—r—T 3  j  u O  L _ l  I  L  I  1 I T o1 o11o J  10 J 1  I  I  I  I  I  L  1—1—1—1—1—m 0 0 0 0 0  J  I  I  I  I  I  I  L  L-3m  2  10  I  L  1 r o o o  J  10' •£"1 —  I 6  I lV I op r v h r  ~*  L I >  V f r V  II  '.o'l'I / 1  'fc'fr'd' OH «  §  1  ~  WD-'^L '>  1  3 OH  179  Monthly sample time series for total Chaoborus fourth instar larva density i n Shirley Lake and i n experimental enclosures from 1992 to 1994  A P P E N D I X C-4  Time is indicated in months and in Julian days over three years (1) Lake;  (2) L o w (3) M e d i u m (4) H i g h predator treatments  1992  1993 OH  e  «  1994  60  1  HI  I  > I  (4)  T—i—i—r  i r cs ro ro  J  I  I  I  I  I  I  L  m—i—i—i—rn—r O O o o o o o o N  IT)  i-Hr-t  _ l  Q  rH  I  I  O  r  H  -  ^  C  ^  O  C  O  C N C N C N CO  I  I  I  CO  I  L  (3)  M e d i u m Predation  10" 10  -j  V.  1  10°  T T—I—TJT—I—r  « « - =? & w- •  10  J  3  M  a . *  >*  S  4)  O  L  J  1'  T—I £ OH  &«  < 2 L  J  I  "QV  60  I  I  I "l  «-  I  I  I " I H-  I  i  i  i  i  i  i  i  r  J  I  I  I  I  I  I  L  >  I  L  (2)  L o w Predation  10  2  10  1  10° • T—i—i—i—i—i—r  T — I — I — I — I — I I I  o o o o o o  OD r-H  10 10  J  3  I  I  I  I  I  L 6  2  J  I  I  H  ^  K  O  C N  C N  C N  CO  I  I  I  i  r  O O CN in P)  rH  rH  i  i  i  i  r  O O O O O O o o i - H - ^ t ^ o c o  rH  C N  C N  C N  CO  CO  CO  J  L  J  I  I  I  L  Lake  m  (1)  10 10°.  — i — L J ~ i—r~T" 2  £  £ • < cn O Z  OH.2  S  60  ^  >  TTI—T 3  I 3  I I — | — T 60  fx  3  57 t3 o  ^  >  180  APPENDIX D  Monthly sample time series for total Daphnia density in Shirley lake and in experimental predator addition enclosures from 1992 to 1994. Time is indicated in months and in Julian days over three years  - inverted triangles represent appearance of predator first instars in monthly samples - horizontal guidelines at 1000 Daphnia m 3  1992  M J J A S O N  1993  A M J J A S O N  1994  A M J J A S O N  181  APPENDIX E  Monthly sample time series for total solitary rotifer density in Shirley lake and in experimental predator addition enclosures from 1992 to 1994. Time is indicated in months and in Julian days over three years - horizontal guidelines at 10 000 solitary rotifers m"  1992 o  o  CN  o  0 0 rH  rH  I  io . 6  I  o CN  I  I  1993  3  1994  O  in  O CO  I  I  I  I  io . 5  I  I  I  I  I  I  0 0  I  I  I  I  I  I < I  1  '  CT*  Ov 1  I I II  1  E  H  IO . 4  TJ S  -V-  CS  E a  io . 3  TJ  IO . 2  io .  s  » i  1  I I I I I I II M J J AS ON  'rJ-  I I I I I I I I I II AM J J AS ON  I I I I I I I I II AM J J AS ON  Tj  It  -  CO  o  C cy TJ  •3  K -St  a. cs  Q  O CN  O  10 6  10 5  '  '  o  O  CN  I  I  o  O CO  Tjt  0 0 rH  rH  '  '  VO CO  I  '  o 0 0  o  o  o  O  in  VO  vo I  I  vo I  I  o  o  CN  K  I I  o  *  I  I  o  O Ov  T}< 0 0  I  I  vO CJv  I  I  I  I I  L-3m cu  10 . 4  10 3  10 . 2  101  I I I I I I I I f I I I I I I I I I I I I I I I I I I I I II M J J A S O N AMJJASON AMJJASON  182  BIBLIOGRAPHY Adams, S. M . and D . L . DeAngelis (1987). 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