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The role of microhabitat associations in producing cross-taxa congruence Turvey, Shannon Lee 2007

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T H E R O L E OF M I C R O H A B I T A T A S S O C I A T I O N S IN P R O D U C I N G C R O S S - T A X A C O N G R U E N C E by Shannon Lee Turvey B . S c , Simon Fraser University, 2005 A THESIS S U B M I T T E D IN P A R T I A L F U L F I L L M E N T OF T H E R E Q U I R E M E N T S F O R T H E D E G R E E OF M A S T E R OF S C I E N C E in T H E F A C U L T Y OF G R A D U A T E STUDIES (Forestry) T H E U N I V E R S I T Y OF BRIT ISH C O L U M B I A June 2007 © Shannon Lee Turvey, 2007 ABSTRACT Ecological interactions between taxa and environmental factors influencing the distribution of multiple taxa are both thought to generate spatial concordance, or congruence, in diversity. Observational studies have generally failed to find evidence for strong cross-taxa congruence across sites, and examples o f experimental studies testing for congruence as a result o f an underlying ecological mechanism are largely lacking. Here I present the results of an experimental study employing downed wood additions in a B A C I design to test for an association of small mammals, carabid beetles, plants and amphibians with volume of downed wood as a possible mechanism for congruence. In addition, I tested for congruence in species richness and community similarity across these four groups. After one field season, there was no significant effect of treatment on within-group abundance, species richness or diversity. Species richness was not significantly correlated across taxa for any taxa pair. Small mammals, carabids and plants showed weak but significant congruence in community similarity, while the amphibian assemblage was not congruent with any other taxon. These results suggest that use of downed wood by these four groups does not generate congruence in diversity at fine scales, and that other ecological processes and sources of environmental variation may be more important in generating congruence in assemblage similarity. Furthermore, the potential of one taxon to act as an indicator of species-level diversity within another taxon may be limited. TABLE OF CONTENTS ABSTRACT i i TABLE OF CONTENTS i i i LIST OF TABLES •. iv LIST OF FIGURES v ACKNOWLEDGEMENTS v i i THE ROLE OF MICROHABITAT ASSOCIATIONS IN PRODUCING CROSS-TAXA CONGRUENCE 1 1 Introduction 1 2 Methods 6 2.1 Study area and site description 6 2.2 Field methods 7 2.3 Statistical analysis 12 3 Results 15 3.1 Within-taxon treatment effects 15 3.2 Cross-taxa congruence in species richness and community similarity 17 4 Discussion 18 4.1 Lack of effect of wood addition treatment 18 4.2 Cross-taxa congruence in species richness and community similarity 22 4.3 Implications 27 5 References 45 i i i LIST OF TABLES Table 1: Abundance and frequency of occurrence of each species pre-treatment and post-treatment for each of the four taxonomic groups studied 29 Table 2: Within-taxon abundance at each site by taxon. Data from multiple pre-treatment or multiple post-treatment sample periods have been pooled. Catch per unit effort (CPUE) values reflect the number of individuals encountered per 100 trap nights or sample locations 31 Table 3: Within-taxon diversity at each site by taxon. Data from multiple pre-treatment or multiple post-treatment sample periods have been pooled. Rarified species richness (SR) values were rarified to the smallest abundance at any site for that taxon during that time period (pre or post) 33 iv LIST OF FIGURES Figure 1: Schematic showing dimensions and layout of one site pair with respect to the stream. Each site is 1-ha in size, with one 0.5-ha plot on either side of the stream channel. Each site extends for 100 m along the stream reach and extends 50 m away from the stream on either side. The control and treatment sites are separated by a buffer of at least 50 m 35 Figure 2: Schematic showing dimensions and layout of traps and plant transects within one half of a site (0.5 ha). The mammal traps (M) are separated from one another by 14.3 m and begin at 7.15 m away from the stream. The invertebrate traps (I) are 10 m apart and the first trap is 2 m away from the stream. The amphibian trap (A) is 10 m away from the site midline and is set back 5 m from the stream. Each 15m plant transect (P) is initiated at a random location within a plant stratum and extends from that point in a random direction. There are two plant transects within one stratum and two strata on one side of the stream within a site 36 Figure 3: Response of all four taxa to treatment. Response measure for each taxon is untransformed catch per unit effort (CPUE), which reflects the number of individuals encountered per 100 trap nights or sample locations. Each panel shows CPUE of one taxon for control and treatment sites before and after treatment application. Bars represent means of the sites within each treatment and the error bars represent + 1 standard error. Black bars indicate control sites and grey bars indicate treatment sites, a. Mammal CPUE. b. Carabid CPUE. c. Plant CPUE. d. Amphibian CPUE 37 Figure 4: Response of all four taxa to treatment. Response measure for each taxon is untransformed species richness (SR), rarified to the smallest total abundance at any site. Each panel shows SR of one taxon for control and treatment sites before and after treatment application. Bars represent means of the sites within each treatment and the error bars represent + 1 standard error. Black bars indicate control sites and grey bars indicate treatment sites, a. Mammal SR. b. Carabid SR. c. Plant SR. d. Amphibian SR 38 Figure 5: Response of all four taxa to treatment. Response measure for each taxon is diversity calculated using the untransformed Shannon index (FT), which emphasizes species richness. Each panel shows diversity of one taxon for control and treatment sites before and after treatment application. Bars represent means of the sites within each treatment and the error bars represent + 1 standard error. Black bars indicate control sites and grey bars indicate treatment sites, a. Mammal diversity, b. Carabid diversity, c. Plant diversity, d. Amphibian diversity 39 v Figure 6: Response of all four taxa to treatment. Response measure for each taxon is diversity calculated using the untransformed Simpson's index (1 - D), which emphasizes species dominance. Each panel shows diversity of one taxon for control and treatment sites before and after treatment application. Bars represent means of the sites within each treatment and the error bars represent + 1 standard error. Black bars indicate control sites and grey bars indicate treatment sites, a. Mammal diversity, b. Carabid diversity, c. Plant diversity, d. Amphibian diversity 40 Figure 7: Pre-treatment cross-taxa congruence in species richness (SR). Values on each axis represent within-taxon SR. SR values are rarified to the smallest abundance at any site for that taxon. Each data point represents one site. A positive relationship across taxa indicates congruence 41 Figure 8: Post-treatment cross-taxa congruence in species richness (SR). Values on each axis represent within-taxon SR. SR values are rarified to the smallest abundance at any site for that taxon. Each data point represents one site. A positive relationship across taxa indicates congruence 42 Figure 9: Pre-treatment cross-taxa congruence in community similarity. Values on each axis represent between-site Bray-Curtis similarity in community composition. The Bray-Curtis index ranges from 0 to 1. A value of 0 means that two sites have no species in common, and a value of 1 means that two sites have the same species and that their proportional abundances are equivalent. Each data point represents one pair-wise, between-site comparison. A positive relationship across taxa indicates congruence 43 Figure 10: Post-treatment cross-taxa congruence in community similarity. Values on each axis represent between-site Bray-Curtis similarity in community composition. The Bray-Curtis index ranges from 0 to 1. A value of 0 means that two sites have no species in common, and a value of 1 means that two sites have the same species and that their proportional abundances are equivalent. Each data point represents one pair-wise, between-site comparison. A positive relationship across taxa indicates congruence 44 vi ACKNOWLEDGEMENTS This project was made possible with the help of many people. Many thanks to my supervisor, John Richardson, for his advice, support, and encouragement. Thanks also to my committee members, Jonathan Shurin and Suzanne Simard, for their advice and comments. This project was supported financially by an N S E R C grant to John Richardson and by a Forest Sciences Program (British Columbia) project-specific grant. Tom Sull ivan, Steve Mitchel l , and Peter Marshall graciously gave of their time and experience, and the mammal traps were generously loaned by Walt Klenner. Paul Lawson, Ionut Aron, and Cheryl Power at the Malcolm Knapp Research Forest provided assistance and support wherever possible, and the research forest kindly donated the trees for this project. I would like to recognize field and lab assistance from Ashlee Albright, Isabelle Deguise, Nancy Hofer, Mel issa Hogg, Jeffrey Jarrett, A y a Reiss, Pina V io la , and Karen Tso. The members of the Richardson lab group helped with many aspects of this project and gave unparalleled support and encouragement. Special thanks go out to the rest of the fab five. It has been a privilege to spend the past two years in your company. M y family and friends have provided essential moral and practical support throughout this process. Thanks especially to my dad, Lyndon, for stepping up to the plate whenever assistance was in short supply. Y o u made it possible both to get started and to keep going. To my husband, Ryan: thanks for being beside me through everything. Mel issa: you've been a rock throughout this whole process - thanks for sticking with me for a second run. Final thanks go out to Jason Smith, who got me excited about quantifying biodiversity in the first place. THE ROLE OF MICROHABITAT ASSOCIATIONS IN PRODUCING CROSS-TAXA CONGRUENCE 1 Introduction Biodiversity, or the diversity of life, is declining rapidly worldwide (Bellwood and Hughes 2001, Boisvert and V iv ien 2005). Landscape modification and habitat degradation are considered major contributors to biodiversity declines and are fuelling concerns about biodiversity loss (Lindenmayer et al. 2002, Simila et al. 2006). Diminishing biodiversity is currently a pressing environmental issue, and is of special concern to conservationists, resource managers, policy makers, and members of the public (Brown 1998, Baumgartner et al. 2006). As a consequence of concerns about broad-scale biodiversity loss and habitat modification, diversity maintenance is a primary goal of conservation efforts and sustainable resource management (Lemelin and Darveau 2006, Sanchez-Fernandez et al. 2006, Leyequien et al. 2007). Biodiversity has intrinsic importance (Giliomee 2006, Larrere and Larrere 2007), and global biodiversity loss is thought to be irreversible (Soule and Sanjayan 1998). Furthermore, species extinction can affect ecological processes and species-level relationships (Cardinale et al. 2006, Gil iomee 2006, Chan et al. 2007). In order to maintain biodiversity, effective and consistent means of assessment are necessary. Monitoring diversity in managed and unmanaged systems over multiple spatial and temporal scales is essential to determine the consequences of anthropogenic activities, such as logging, for system biodiversity. Furthermore, quantification of biodiversity across habitats and land patches is crucial i f conservation planning and reserve prioritization are to be effective. 1 Biodiversity assessment ideally entails a complete survey of the biodiversity within a defined area (Sarkar et al. 2006). However, such an inventory is generally impractical since availability of time, money, and taxonomists is limited (Heino et al. 2005, Sanchez-Fernandez et al. 2006). To reduce the resources required to monitor biodiversity, surrogates are frequently employed as diversity indicators (Fleishman et al. 2005, Favreau et al. 2006). A number of different types of taxonomic surrogates have been proposed and evaluated. These include flagship species, umbrella species, and indicators (Andelman and Fagan 2000). Flagship species are charismatic species used to garner public support for conservation (Carignan and Vi l lard 2002, Favreau et al. 2006). While protection of flagship species may help to protect other biodiversity, they are chosen based on mass appeal rather than biological criteria. Umbrel la species are wide-ranging species whose habitat needs are supposed to incorporate the habitat requirements of many other species (Ozaki et al. 2006). The use of umbrella species as a conservation tool doesn't allow quantitative prediction of presence or abundance of other species. Indicators, by way of contrast, are individual species or groups of species that can be utilized to predict overall biodiversity (Chiarucci et al. 2005, Hess et al. 2006). Indicators use diversity within one group to estimate diversity of other groups within the same geographic area (Chiarucci et al. 2005, Sanchez-Fernandez et al. 2006). This approach depends on the existence of cross-taxa co-variation in spatial diversity patterns across multiple taxa, also known as congruence (Chiarucci et al. 2005). Congruence can arise due to similar responses of multiple taxa to a single environmental gradient, covariance of environmental factors which independently determine diversity patterns in different taxa, and ecological cross-taxa interactions (Heino et al. 2003). In the case where several taxa depend on the same structural 2 habitat feature, the taxa may demonstrate cross-taxa congruence. The utility of strong congruence is that management and conservation decisions based on assessment of a surrogate group wi l l be similar to decisions based on assessment of the group the surrogate represents (Lindenmayer et al. 2002). Downed wood (DW) is a habitat element that is utilized by many different species and may be important for the persistence of those species in an ecosystem (Bunnell et al. 1999). In unmanaged systems, D W is recruited to the forest floor through processes such as windthrow, diseases, and insect infestation, which can all result in tree mortality (Harmon et al. 1986, Jonsson et al. 2005). Species that utilize D W include invertebrates, macrofungi, and vertebrates (Bunnell et al. 1999). The utility of D W to terrestrial species varies with size of individual wood pieces, and many wood-associated species prefer larger pieces of D W (Jonsson et al. 2005). D W volume and other characteristics such as average size and decay class are affected by intensity and type of land management (Craig et al. 2006). Several studies have shown that small mammal abundance is positively correlated with D W density (Carey and Johnson 1995, Loeb 1999, Manning and Edge 2004). D W is an important type of terrestrial cover and may be utilized by small mammals as travel routes to avoid detection by auditory predators (Barnum et al. 1992), for nesting, and for foraging (Bowman et al. 2000). Small mammals, particularly voles, tend to be associated with D W in later stages of decay rather than util izing D W uniformly with respect to decay class (Tallmon and Mi l l s 1994). It has been hypothesized that the moist microclimates associated with decaying logs increase the abundance of mycorrhizal fungi near the logs (Tallmon and M i l l s 1994), which are a major food 3 resource for mycophagous small mammals such as red-backed voles and flying squirrels (Carey 1995, Bowman et al. 2000). Some small mammals are insectivorous, and the association of certain invertebrates with D W (Hagan and Grove 1999) may partially explain the correlation between D W volume and small mammal abundance. Terrestrial amphibians use the moist microclimate provided by D W for reproduction (Bunnell et al. 1999, Hagan and Grove 1999, Herbeck and Larsen 1999, Welsh and Droege 2001), and many insectivorous amphibians may forage on the invertebrates associated with D W (Evans et al. 2003, Jabin et al. 2004, Moseley et al. 2005). Diversity of carabids and other ground-dwelling beetles has shown positive correlations with increased D W volume (Lassau et al. 2005). The l ikely mechanism for this is the provision of physical refuges and sites for reproduction, and the direct and indirect facilitation of foraging (Pearce et al. 2003, Lassau et al. 2005). Decaying D W is also an important source of nutrients for terrestrial vascular plants and provides a favourable microclimate for establishment and growth (Baier et al 2007). Because a number of small mammal, carabid, terrestrial plant, and amphibian species utilize D W , it seems plausible that the volume of D W at a site may partly determine within-taxon abundance and diversity. Cross-taxa diversity patterns may show congruence, since all four taxa interact with a common structural resource. This study tested the hypothesis that an increase in D W volume within riparian zones would lead to an increase in abundance and diversity of small mammals, carabid beetles, plants, and amphibians. Furthermore, I hypothesized that these taxa (small mammals, carabid beetles, 4 plants, and amphibians) would show congruence in species richness and community similarity at a stand scale within riparian zones due to their common use of D W . Riparian zones were selected for this study because they are a unique habitat type utilized by many taxa (Richardson et al. 2005, Sabo et al. 2005). Because of their importance to streams through the provision of shade and large woody debris, they are frequently incorporated into management plans. There is some controversy about whether D W within riparian zones should be salvaged or retained for its contribution to the maintenance of terrestrial diversity. As a result, clarifying the relationship between D W volume and terrestrial species within riparian zones is of great interest to managers. 5 2 Methods 2.1 S t u d y a r e a a n d site d e s c r i p t i o n This research was conducted between May and November 2006 in the University of British Columbia's Malco lm Knapp Research Forest ( U B C M K R F ) , located in south-western British Columbia, Canada (49°16'N, 122°34' W). The forest is in the Coastal Western Hemlock (CWH) biogeoclimatic zone (dm subzone). Dominant canopy tree species are Western hemlock (Tsuga heterophylla), Douglas-fir (Pseudotsuga menziesii), and Western redcedar (Thuja plicata) (Cockle and Richardson 2003). A l l study sites were located in 75-year-old, second-growth forest that was initiated following a large forest fire in 1931. This study employed a B A C I (before-after, control-impact) design and included eight sites, each 1 ha in size and divided into two 0.5 ha plots with one plot on each side of the stream channel (Figure 1). Each treatment site was paired with a nearby control site on the same stream, and the four site pairs were placed on four separate streams (Spring Creek, Griffiths Creek, G / H Creek, and an unnamed stream just west of road A41). Subject to the constraints imposed by other research projects, the allocation of treatment within each control-manipulation pair was random with respect to the direction of stream flow. Site pairs were separated by a minimum distance of 50 m to reduce the probability of between-site migration and microclimatic influence. 6 2.2 Field methods D W additions At each manipulated site, 26 Western hemlock trees with diameter at breast height (dbh) > 34 cm were cut down in a dispersed fashion in early June 2006. This was initially estimated to represent a 5% decrease in density of standing trees and a 25-30% increase in the quantity of D W at each treatment site ( M . Feller, pers. comm.). Hemlock was selected over the other two prevalent conifer species because it decays more rapidly than redcedar and is less valuable per unit volume than Douglas-fir. The falling was directionally random, but trees were not felled into or across the stream so that aquatic disturbance was minimized and terrestrial impact was maximized. Any trees left suspended after falling were segmented to lie along the ground, thereby reducing safety risk and increasing the usefulness of the trees as terrestrial habitat structures. The trees were left unaltered where they fell throughout the rest of the study. Small mammal trapping and processing Small mammal species composition and relative abundance at each site was assessed using live trapping. Time-series data were collected over seven trapping sessions, with three sessions before the manipulation and four afterwards. During each trapping period, traps were set in the evening and checked the following two mornings. Prior to treatment application, traps were set for two nights every two weeks. Post-manipulation, the trapping interval was extended to three weeks for three trapping periods and then to four weeks for the final trapping period. A t each 1-ha site, 36 Longworth live traps (B. N . Bolton Inc., Vernon, B C , Canada) were placed at 14.3 m intervals in a 6 x 6 grid (T. Sullivan, pers. comm.). Within a trap line intersecting the 7 stream, three traps were placed on each side of the stream (Figure 2). A l l distances were measured from the stream edge. Traps were baited with whole oats, sunflower seeds, and a slice of apple for moisture (Cockle and Richardson 2003). Coarse brown cotton (B Felt, Upholstery Felt, Burnaby, B C , Canada) was supplied as insulation and bedding material. Each trap was covered with a 10 cm x 20 cm piece of tar roofing to provide shelter and reduce overnight mortality (Cockle and Richardson 2003). Between trapping periods, traps were locked open and baited to reduce the likelihood of trap avoidance (Manning and Edge 2004). A pre-baiting period of two weeks, when traps were baited but locked open, preceded the first trapping period at each site. A l l captured mammals (except shrews) were identified to species in the field (Eder and Pattie 2001, Nagorsen 2002), weighed to the nearest 1 g using a Pesola 100 g spring balance, sexed, and checked for reproductive status (Krebs et al. 1969). Mice and voles were marked using a uniquely numbered ear tag and released at the point of capture (Sullivan et al. 2000). Ear tags were 0.9 cm long and weighed 0.22 g each (Model 1005-1, National Band and Tag Co. , Newport, K A , U S A ) . Due to their small size, live shrews could not be marked using ear tags and were instead weighed, marked with a unique pattern on their dorsal surface using black hair dye (L 'Oreal , Montreal, Q C , Canada), and released (V. Craig, pers. comm.). Live shrews could not be identified to species. They were recorded as Sorex sp. and excluded from further analytical consideration. Shrews and moles that were found dead in the trap or euthanized due to morbidity were taken back to the lab and identified to species using a dissecting light microscope according to Nagorsen (1996). 8 Invertebrate trapping and processing Terrestrial invertebrates were sampled using 30 pitfall traps at each site, arranged in two 5 x 3 grids. Grids were located on opposite sides of the stream and in opposite halves of the site with respect to the mid-line running perpendicular to the stream. Within each trapping grid, three trap lines were installed perpendicular to the stream and spaced 10 m apart, beginning 10 m away from the mid-line of the site (Figure 2). Each line consisted of five pitfall traps at 10 m intervals (Magura et al. 2004), with the first trap located 2 m away from the stream edge to protect it from rising water levels during heavy rains. Traps were comprised of two nested plastic cups with an inner diameter of 6.5 cm and a capacity of 250 m L (Magura et al. 2004). The cups were dug into a flat section of ground so that the rims were level with the surface. To keep out rainwater and detritus, a 30 x 30 cm plywood coverboard was placed over each trap (Rainio and Niemela 2006). The board was elevated to a height of 2 cm above the ground using three cedar sticks so that carabid movement along the forest floor was not impeded (S. Lavallee, pers. comm.). Pitfall traps were opened for one week every two months (7 trap nights) from May through September (Rainio and Niemela 2006). During trapping, approximately 3 cm of 100% propylene glycol was poured into each trap to act as a preservative (Apigian et al. 2006). After field collection, pitfall trap samples were drained through a 75 um sieve in the laboratory. Samples were rinsed wel l with distilled water and transferred to 80% ethanol for long-term preservation. A l l carabids were extracted and identified to species (Lindroth 1961, 1963, 1966, 1968, 1969a, 1969b) using a dissecting light microscope. Within a sample, the number of individuals of each species was recorded. 9 Plant sampling The vascular plant community was surveyed at six week intervals using a point intercept method (Jonasson 1983). Plant sampling was conducted once before the trees were felled and three times after the treatment. A t each site, eight 15 m transects were established and sampled repeatedly in a stratified random design (S. Simard, pers. comm.). Each side of the stream was partitioned into two strata, with the partition running parallel to the stream edge. The first stratum began at the stream edge and continued to 25 m from the stream. The second stratum began 25 m from the stream and extended a further 25 m into the forest. Within each stratum, two transects were initiated at random points and ran for a horizontal distance of 15 m in a random direction (Figure 2). A l l transects were measured along the ground and then corrected to 15 m horizontal distance using a clinometer (Brunton Cl ino Master, Forestry Suppliers Inc., Jackson, M S , U S A ) . Sampling points were set at intervals of 1 m along each 15 m transect (Kala and Mathur 2002). A l l plants intersecting a vertical pin placed at each sampling point were identified to species according to Pojar and Mackinnon (1994). The number of times every plant contacted a sample pin and the height of each contact was recorded (S. Mitchell , pers. comm.). The number of pin contacts made by a plant species at a site was used as an index of biomass of that plant species at that site (Jonasson 1988). Amphibian trapping Two amphibian pitfall traps were installed at each 1 ha site, with one trap on either side of the stream 5 m away from the stream edge. Traps were approximately 10 m away from the mid-line of the site and were located in opposite halves of the site with respect to the mid-line (Figure 2). Each trap consisted of a P V C pipe, 16 cm in diameter and 40 cm in depth (Matsuda and 10 Richardson 2005). Pipes were installed level with the ground surface. A plastic margarine tub (No. 2 size, Granpac, Wetaskiwin, A B , Canada) was placed at the bottom of the pipe to catch and retain amphibians. A collar was clipped onto the top of the pipe (consisting of a plastic margarine tub with the central portion removed) to prevent amphibian escape. Four drift fences were installed perpendicular to one another around the central pitfall trap to lead amphibians into the trap (Matsuda and Richardson 2005). Drift fences were 25 cm high and 5 m long. They consisted of polyethylene sheeting trenched approximately 10 cm into the ground and supported by wooden survey stakes at 1 m intervals. Seven post-treatment trapping sessions were conducted, with traps opened weekly from October 2 until November 13. Traps were opened one day and then checked on each of the following two days. In the field, all captured amphibians were enumerated, identified to species (Corkran and Thorns 2006) and weighed to the nearest 0.5 g using a field scale (SC 2020, Ohaus, Pine Brook, New Jersey, U S A ) . Total length and snout-to-vent length (SVL) were measured to the nearest mm. Previously unmarked amphibians were marked by injecting them beneath the skin with one or more fluorescent elastomer tags (Northwest Marine Technology, Inc., Olympia, W A , U S A ) on the ventral surface of their limbs (Matsuda and Richardson 2005). Three colours of elastomer were used. Unique colour-limb combinations were used to identify individual amphibians. 11 2.3 Statistical analysis Data from multiple trapping periods were pooled to yield one pre-treatment measure (for small mammals, carabids, and plants) and one post-treatment measure (for all four groups). For use in A N O V A s , abundance data were transformed into a metric of catch per unit effort (CPUE) , measured in units of individuals captured per 100 trap nights. This index of relative abundance controls for unplanned differences in trapping effort across sites (Hopkins and Kennedy 2004). Species richness data were rarified to the smallest abundance at any site during the relevant time period (pre-treatment or post-treatment) prior to analysis. Rarefaction standardizes for the effect of the number of individuals captured on the number of species observed (Gotelli and Colwel l 2001). Rarefaction was performed according to Krebs (1999) using the program Rarefact (Brzustowski 1998). Two measures of biodiversity, the Shannon index of species evenness and the Simpson's diversity index, were computed separately for each taxon in both pre-treatment and post-treatment periods. The Shannon index H ' is a measure of heterogeneity that emphasizes species richness, in that it is weighted towards rare species (Magurran 2004). It is computed according to the function H ' = - L pi ln pi where pi is the relative abundance of species i at a given site. Increasing values of H ' indicate increasing diversity. The Simpson's index emphasizes species dominance and is weighted towards abundant species (Magurran 2004). It is computed according to the function D = L (ni(n i - l ) /N(N - l ) ) 12 where rij is the number of individuals of species i and N is the total number of individuals. Increasing values of D indicate decreasing diversity, thus for analysis and interpretation purposes Simpson's index has been expressed as 1 - D wherever used. Where pre-treatment data were available (small mammals, carabids, and plants), the data were analysed according to a completely randomized two-way factorial design (treatment by time). Where pre-treatment data were not available (amphibians), the data were analysed using a one-way A N O V A to assess the effect of treatment. To conserve error degrees of freedom, stream was not included as a blocking factor. Within-taxon catch per unit effort (CPUE) , rarified species richness (SR), Shannon diversity index (FT) and Simpson's diversity index (1 - D) were each considered as separate response variables. Response variables were successfully transformed where necessary to meet assumptions of normality and homogeneity of variance. A significance level of a = 0.05 was used. A N O V A s were performed using S A S version 9.1.3 (SAS Institute, Cary, N C ) . When the null hypothesis was not rejected (i.e. the treatment by time interaction was not significant for small mammals, carabids, and plants or the treatments did not differ for amphibians), a post hoc power analysis was conducted. This determines the power of the F tests to detect a true significant effect. Effect size f was calculated according to the function f = <rm/o where o is the pooled standard deviation of the variable being measured and a m is the standard deviation of the population means (Cohen 1988). o m is computed as follows: <Tm = V( Kms - m)2/k) 13 where mj is the mean for a single treatment, m is the mean over all treatments, and k is the number of treatments. Effect sizes were interpreted according to the convention that f = 0.10 is small, f = 0.25 is medium, and f = 0.40 is large (Cohen 1988). Power analyses were performed using G * P O W E R 3 (Faul and Erdfelder in press). The strength and significance of congruence was assessed pre-treatment for mammals, carabids, and plants and post-treatment for mammals, carabids, plants, and amphibians. Spearman rank correlation coefficients (rs) were computed for each possible pair-wise cross-taxa combination to test for congruence in species richness at the site level (SAS version 9.1.3, S A S Institute, Cary, N C ) . When the correlation was not significant, a post hoc power analysis was conducted in order to determine the power to detect a significant correlation. Power analyses were performed using G * P O W E R 3 (Faul and Erdfelder in press). To test for congruence in community similarity, one-tailed Mantel tests (Mantel 1967) were computed for every possible pair-wise cross-taxa combination using the program C A D M (Legendre 2001). A Monte Carlo randomization test with 9999 permutations was performed to test congruence significance, and a Mantel test statistic TM was obtained to represent congruence strength. For use in the Mantel tests, pre-treatment and post-treatment similarity matrices were constructed for each taxon using the Bray-Curtis index of similarity (Bray and Curtis 1957, Krebs 1999). Each symmetric similarity matrix consisted of all possible pair-wise comparisons between sites for a given taxon. The Bray-Curtis index incorporates both species presence and relative abundances. It ranges from 0 to 1, with a value of 0 indicating a site pair with no species in common and a value of 1 meaning that the two sites are identical. 14 3 Results 3.1 Wi th in- taxon treatment effects Catch per unit effort (CPUE) Across all sites and trap sessions, a total of 2002 mammals, 1545 carabids, and 97 amphibians were caught and identified to species (Table 1). Plant sampling yielded a total of 2945 individual contact points (Table 1). Across time periods, C P U E (Figure 3) did not differ significantly between treatments for small mammals, carabids, or plants. Amphibian C P U E was significantly higher at control sites than at treatment sites ( F i > 6 = 18.31, p < 0.010). Across treatments, C P U E was not significantly different between times for mammals or plants. Carabid C P U E was significantly greater post-treatment than pre-treatment ( F j ^ = 55.8, p < 0.010) at both the treatment and control sites. The treatment by time interaction was not significant for mammals, carabids, or plants. Species richness (SR) When trapping data were pooled across all sites and trapping sessions, 10 mammal species, 15 carabid species, 19 plant species, and 8 amphibian species were encountered (Table 2). SR (Table 3, Figure 4) did not differ significantly between treatments for small mammals, carabids, plants, or amphibians. Across treatments, post treatment S R was significantly greater than pre-treatment SR for mammals ( F U 2 = 9.46, p < 0.010) and carabids ( F u 2 = 55.8, p = < 0.010). When treatments were pooled, plant SR was significantly greater pre-treatment than post-treatment (F1J2 = 10.13, p < 0.010). The treatment by time interactions were not significant for mammals, carabids, or plants. 15 Diversity indices Diversity, as calculated using the Shannon index (FT, Table 3, Figure 5), did not differ significantly between treatments for carabids, plants, or amphibians. Mammal FT was greater at the control sites than at the manipulated sites ( F i ^ = 11.53, p < 0.010) both before and after the treatment was imposed. Across treatments, there were no significant differences in FT between time periods for small mammals, carabids, or plants, and the interactions between treatment and time were not significant. When the Simpson's index (1 - D) was used to calculate diversity (Table 3, Figure 6), there were no significant differences between treatments for carabids, plants, or amphibians. Mammal diversity was again greater at the control sites than at the manipulated sites (Fi,i2 = 12.39, p < 0.010). When the Simpson's index was pooled across treatments, there were no significant differences between time periods for mammals, carabids, or plants. Mammals, carabids, and plants showed no significant treatment by time interactions. Power analvsis C P U E effect sizes ranged from 0.21 (for plants) to 0.79 (for amphibians). Power to detect a significant treatment by time interaction was 0.5 for carabids, 0.15 for mammals, and 0.12 for plants. The probability of identifying a true post-treatment difference in amphibian C P U E between control and treatment sites was 0.47. For SR, effect sizes ranged from 0.25 (for amphibians) to 0.79 (for carabids and plants). The likelihood of detecting a significant treatment by time interaction was 0.68 for mammals and 0.83 for carabids and plants. Power to detect a post-treatment difference between treatments was 0.092 for amphibian SR. 16 3.2 Cross-taxa congruence in species richness and community similarity Congruence in species richness Pre-treatment correlation analysis (Figure 7) showed no evidence of congruence in species richness between carabids and mammals, plants and mammals, or plants and carabids. Post-treatment (Figure 8), the correlation in species richness between carabids and amphibians was marginally significant (r = - 0.72, p = 0.045). No other pair-wise comparisons of species richness across taxa were significant. Post-hoc power analysis showed that power to detect significant correlations where no congruence was detected ranged from 0.07 to 0.26. Congruence in community similarity Pair-wise Mantel tests for pre-treatment congruence in assemblage similarity (Figure 9) showed evidence of congruence between carabids and mammals (rM = 0.62, p < 0.010), mammals and plants ( r M = 0.66, p = 0.016), and carabids and plants ( r M = 0.40, p = 0.022). Post-treatment (Figure 10), mammal community similarity was congruent with carabids ( r M = 0.48, p = 0.027) and plants ( r M = 0.55, p = 0.028). Similarity in community composition was not congruent for carabids and plants, and amphibians were not congruent with any other taxon. 17 4 Discussion 4.1 Lack of effect of wood addition treatment This study failed to find support for the hypothesis that D W addition increases abundance, species richness and diversity of small mammals, carabid beetles, and plants. This is illustrated by the lack of a significant treatment by time interaction for any response variable within any taxon, which indicates that the post-treatment difference between control and treatment sites did not diverge significantly from the pre-treatment difference. Contrary to my prediction, amphibian abundance was significantly higher at control sites than treatment sites, and no detectable difference in amphibian species richness and diversity was observed between control and treatment sites. There are several possible reasons why the hypothesized treatment effect was not observed: (1) the early decay class of the logs limited their usefulness as functional habitat structures for each of the sampled taxa; (2) species-specific life histories, particularly timing of reproduction, delayed a detectable numerical response; (3) timing of migration and dispersal delayed colonization of treatment sites by new recruits; (4) the wood addition lowered the effectiveness of the sampling methods by causing animals to move less; (5) power to detect a treatment effect was insufficient or (6) D W was not the limiting factor determining species presence and relative abundances of these groups. The first possibility is the most broadly applicable to all taxa in this study. The newly fallen logs were still in a comparatively early stage of decay throughout the field season, and it has been shown that the association between D W and the taxa that utilize it can be highly dependent on the decay class of the wood (Bowman et al. 2000). For example, California red-backed voles (Clethrionomys californicus) utilized logs in later stages of decay significantly more often than 18 expected based on the abundance of logs in each decay class (Tallmon and M i l l s 1994). Bowman et al. (2000) found that although use of individual logs did not depend on their decay stage, abundance of Southern red-backed voles (Clethrionomys gapperi) was positively correlated with volume of wood in the final stages of decay. Log decay class has a significant effect on invertebrate abundance and community composition, with some largely predatory families, such as carabids, associated with logs in advanced stages of decay (Vanderwel et al. 2006). As a result of the decay-dependent relationship between many of these taxa and D W , it may take many years for the full effect of the manipulation on biodiversity to become apparent (Marra and Edmonds 1994, Feller 2003). The second postulated reason for the failure of the treatment to produce detectable changes in abundance and diversity of small mammals, carabids, and plants is a lag between treatment application and the timing of reproduction. For instance, carabid life cycles vary between species, with different species reproducing in spring, in summer, and in autumn (Khobrakova and Sharova 2005). The capacity of a species to respond quickly to elevated resource availability or more favourable environmental conditions could vary depending on the timing of reproduction and the number of reproductive events within a season. A third explanation for the lack of a treatment response is that timing of migration resulted in a lag between treatment application and a population-level response due to colonization of treatment sites through dispersal. Movement would be most l ikely due to migration of adults before or after the breeding season (e.g. Bulger et al. 2003), or dispersal of juveniles from natal patches resulting in colonization of treatment sites (e.g. Vasconcelos and Calhoun 2004). Stage-19 or seasonal dependence of migration and surface activity could delay colonization of a site, despite increased availability of habitat resources. A fourth possible reason for the failure to observe a treatment response is that the wood addition physically obstructed organism movement at manipulated sites post-treatment, thereby lowering the effectiveness of the sampling methods. Increased availability of food or structural refugia at treatment sites would have also reduced the need for surface movement to locate food or physical shelter. This may explain the unexpected result that amphibian abundance was depressed at treatment sites relative to control sites. It is possible that amphibian abundance was greater at control sites than at treatment sites prior to the treatment and that adding D W at treatment sites did not effect any change, but pre-treatment amphibian sampling was not conducted. Without prior data for amphibians, it is impossible to say with certainty that the observed post-treatment differences in abundance resulted from the applied manipulation. It is also possible that the limited power of this study to detect a treatment effect led to a failure to reject the null hypothesis. Because there were only four replicates per treatment, power of this study ranged from 0.12 to 0.5 for C P U E and from 0.092 to 0.83 for species richness. Increasing the number of replicates in future work could increase study power. However, a treatment effect was not found even in cases where power was fairly high, which indicates that low power was not solely responsible for the study findings. A final possible explanation for the overall lack of response to the treatment is that the threshold for the positive relationship between D W volume and within-taxon abundance and diversity was 20 exceeded at the manipulated sites before the treatment was applied. In this case, D W volume would not be the limiting factor driving abundance and species richness and other ecological factors such as food availability and predation pressure might be more important in determining community composition. This might also contribute to the lack of strong cross-taxa congruence at these sites. 21 4.2 Cross-taxa congruence in species richness and community similarity Contrary to the prediction of cross-taxa congruence due to strong ecological associations with D W , small mammals, carabid beetles, plants, and amphibians failed to show congruence in species richness. However, weak but significant congruence in assemblage similarity was demonstrated among mammals, carabids, and plants. The amphibian community showed no congruence with any other taxon. Finding congruence in community similarity but not in species richness is consistent with other studies demonstrating that congruence strength depends on the diversity metric used as well as the groups being assessed. A regional study of congruence across four aquatic invertebrate groups found that congruence was weak for species richness but strong for assemblage similarity (Bilton et al. 2006). Howard et al. (1998) found little evidence for cross-taxa congruence in species richness of woody plants, large moths, butterflies, birds, and small mammals. However, when complementarity was compared across sites, taxa were strongly congruent. A study testing four marine taxa for congruence in species richness, assemblage similarity and seven diversity indices found major inconsistencies in strength and significance of congruence between two taxa, depending on which diversity metric was being compared (Karakassis et al. 2006). In other words, the diversity metric employed when testing for congruence can have a substantial impact on the study outcome. This suggests that the potential for congruence to be useful in management and conservation is highly variable and depends strongly on the specific goals of the project in question. If the goal is to maximize species richness at a site, congruence may be of limited use. However, i f the goal is to maximize the total number of species included in a reserve network through maximizing complementarity 22 between reserve sites (Justus and Sarkar 2002), then congruence in community similarity or complementarity across taxa would be highly useful. Scale is crucial to understanding many patterns in ecology, and the field of congruence research is no exception. The scale of study investigation, i.e. the geographical extent of the study and the grain at which data are collected, affects the types of processes which dominate observed diversity patterns. A t local scales within a single habitat type, where a diversity is measured, ecological interactions and variation in microclimate and microhabitat would likely be the major factors influencing biodiversity patterns (Ricketts et al. 2002, Hendrickx et al. 2007). At broader scales, where y diversity is measured, climatic gradients and latitudinal effects are likely to be more important in governing distribution of diversity within and across groups (Flather et al. 1997, Ricketts et al. 2002, Hendrickx et al. 2007). Because scale can dramatically influence study results, caution should be exercised when extrapolating the findings of congruence studies to other spatial scales. Scale also affects the applicability of congruence in a practical sense. Congruence at a local scale is most useful for managers to assess or monitor stand-level biodiversity (Simila et al. 2006), while regional congruence is most relevant to conservation planners, particularly those designing reserve networks (Simila et al. 2006). Conclusive evidence supporting the existence of strong congruence at a local scale, where it would have the most utility to site managers, is largely lacking. Lawton et al. (1998) examined eight taxa in small plots (1 - 3 ha) within a single forest reserve along a gradient of habitat modification. They found no evidence for congruence in species richness for any pair-wise cross-taxon comparison. In a separate study, butterfly diversity and moth diversity were found 23 2 to be uncorrelated across three habitat types at scales of 1-10 km , regardless of the diversity metric used (Ricketts et al. 2002). A Swedish study of 10 stands within a single forest type found limited evidence for congruence in species diversity across vascular plants, bryophytes, epiphytic lichens, and wood-inhabiting fungi (Jonsson and Jonsell 1999). Similarly, Kati et al. (2004) found low congruence in species richness across six vertebrate, invertebrate, and plant taxa within a single 430 k m 2 study area. However, they found some evidence for congruence in cross-site complementarity across the different taxa (Kati et al. 2004). Su et al. (2004) found that species richness of birds, butterflies, and plants was uncorrelated within a single habitat type, but that there was significant congruence in community similarity. One study of eight invertebrate, plant, bryophyte, and fungal taxa in 0.25 ha sites within a 140 ha study area found weak but significant congruence in species richness across sites (Saetersdal et al. 2004). This research was conducted at an extremely fine spatial scale, both in terms of the study grain (1 ha sites) and the extent (a single forest stand). Surveying taxa at only eight sites meant that power to detect significant correlations was extremely low (ranging from 0.07 to 0.26). Consequently, it is difficult to ascertain whether the lack of observed congruence in species richness is due to its absence or due to limited ability to detect it. Furthermore, the study was conducted within a single habitat type (riparian zones), which may have limited the magnitude of environmental variability across sites. Thus the lack of strong congruence across sites may reflect low variability across sites, rather than differences between groups in responses to environmental gradients across sites. However, my study findings are consistent with the results of other fine-scale studies suggesting that congruence in species richness across sites within a single habitat type is weak or nonexistent. This implies that the factors determining within-site 24 diversity at small scales differ between taxa, and that the environmental gradients to which each functional group responds are not identical across groups. Furthermore, ecological relationships among taxa, including trophic interactions, do not appear to be sufficiently strong to generate congruence in species richness at local scales within one habitat type. The evidence for the existence of strong congruence across multiple taxa is more convincing at broader scales. Strong congruence in species richness of mammals, amphibians, birds, and plants has been demonstrated at regional scales (Das et al. 2006). Lamoreux et al. 2006 found correlations in global species richness patterns for amphibians, reptiles, birds, and mammals. Species richness of four invertebrate taxa and fish was highly correlated at a regional scale, and species richness was closely related to temperature gradients (Heino 2002). A s scale of investigation increases, latitudinal gradients and habitat type become more influential in determining species distributions (Flather et al. 1997). Because groups of species are responding to the same environmental gradients at coarse geographic scales, congruence across groups is strong. Whi le congruence at regional and global scales is useful for conservation planning, it is not useful for local stand level management and site assessment (Simila et al. 2006). This limits its potential utility for managers, since most land is managed at the stand scale rather than at the landscape scale. In addition to the effect of study extent on diversity patterns, the size of individual study sites affects diversity because total species richness tends to increase with habitat area (Favreau et al. 2006). This can generate apparent congruence in species richness over broad spatial scales as a result of differential sampling effort across habitats rather than ecological cross-taxa 25 relationships (Howard et al. 1998). In a study testing for cross-taxa congruence in woody plants, large moths, butterflies, birds, and small mammals, congruence strength and significance was drastically reduced once the effect of forest size was accounted for (Howard et al. 1998). This is an important consideration in studies testing for congruence. Either sites should be of equivalent size, or the effect of site size on observed species richness should be accounted for before tests of cross-site congruence in species richness are conducted. Site dimensions were uniform across sites in this study, so while study grain likely influenced absolute results, relative differences in species richness across sites were not biased by differences in site size. 26 4.3 Implications This study does not provide any supportive evidence for common use of D W by multiple taxa as an underlying mechanism for cross-taxon congruence at a local scale. Further monitoring wi l l be necessary to determine whether this is due to insufficient time elapsed since treatment or whether D W does not l imit abundance and species diversity at these sites. Furthermore, these data do not support use of a single taxon as a surrogate for diversity within other taxa at local scales. The lack of significant congruence in species richness precludes the use of within-taxon diversity at one site to predict diversity within another taxon at the same site. While some congruence in community similarity was demonstrated, this type of congruence has limited predictive value. This limits its utility to managers, who are frequently concerned with accurately predicting species richness at the site level. Knowledge of compositional similarity between sites may be useful to conservation planners aiming to maximize retention of P diversity by maximizing complementarity between protected sites (Balmford et al. 2000, Steinitz et al. 2005, Hendrickx et al. 2007). However, conservation planning usually occurs over a much larger extent and at a larger grain than the scale of this study. It is also important to note the distinction between statistically significant cross-taxon congruence and congruence that is l ikely to have predictive utility (Gaston 1996). For a species or a group of species to be a reliable indicator, the relationship between the predictor and the predicted must have low variance (Beccaloni and Gaston 1995). In this study, congruence in assemblage similarity ranged in strength from 0.4 to 0.66 when significant. This is interesting 27 from a biological perspective, but less useful from a predictive perspective since these relationships are not strong enough to permit confident decision making. Finding weak congruence in community similarity and no congruence in species richness at is consistent with other fine-scale research conducted within a single habitat type. These results suggest that the potential for indicators to be useful predictors of diversity within other taxa at fine spatial grain and extent is limited. Consequently, managers seeking to assess and monitor biodiversity at fine scales should evaluate target groups independently based on their representation goals rather than relying on surrogate measures of within-taxon diversity. Management decisions based on habitat representation, higher-taxa surrogates or survey-based approaches may be more promising options to ensure that all taxa are adequately represented at a local scale. 28 Table 1 Abundance and frequency of occurrence of each species pre-treatment and post-treatment for each of the four taxonomic groups studied. Smal l mammals # of # of sites Species name Common name individuals encountered encountered (out of 8) Pre Post Pre Post Clethrionomys gapperi Vigors Southern red-backed vole 85 144 5 5 Glaucomys sabrinus Shaw Northern flying squirrel 0 1 0 1 Microtus oregoni Bachman Creeping vole 0 3 0 2 Mustela erminea richardsonii Short-tailed weasel 0 2 0 2 Neurotrichus gibbsii Baird Shrew mole 0 3 0 2 Peromyscus maniculatus Wagner Deer mouse 777 893 8 8 Sorex cinereus Kerr Masked shrew 5 7 3 4 Sorex monticolus Merriam Dusky shrew 28 32 6 8 Sorex vagrans Baird Vagrant shrew 6 15 5 7 Zapus trinotatus Rhoads Pacific jumping mouse 1 0 1 0 Carabids #of # of sites Species name individuals encountered encountered (out of 8) Pre Post Pre Post Bembidion iridescens LeConte 1 0 1 0 Cychrus tuberculatus Harris 2 3 2 2 Leistus ferruginosus Mannerheim 1 3 1 3 Omus dejeani Reiche 1 0 1 0 Promecognathus crassus LeConte 1 0 1 0 Pterostichus algidus LeConte 0 1 0 1 Pterostichus amethystinus Mannerheim 0 25 0 8 Pterostichus crenicollis LeConte 4 25 2 6 Pterostichus herculaneus Mannerheim 27 562 3 8 Pterostichus lama Menetries 1 4 1 1 Pterostichus neobrunneus Lindroth 0 1 0 1 Pterostichus pumilus Casey 2 3 2 3 • Scaphinotus angulatus Harris 3 28 3 8 Scaphinotus angusticollis Fischer von Waldheim 190 652 8 8 Scaphinotus marginatus Fischer von Waldheim 1 4 1 3 Plants Species name C o m m o n name # of contacts # of sites encountered (out o f 8) Pre Post P r e Post Athyrium filix-femina Lady fern 6 8 3 6 Blechnum spicant Deer fern 75 193 7 7 Cornus canadensis Bunchberry 21 26 4 4 Dryopteris expansa Spiny wood fern 30 55 4 5 Gaultheria shallon Salal 165 482 7 7 Ilex aquifolium English holly 4 1 2 1 Lycopodium clavatum Running clubmoss 2 0 1 0 Lysichiton americanum Skunk cabbage 2 5 2 2 Menziesia ferruginea False azalea 21 56 6 5 Pteridium aquilinum Bracken fern 15 24 5 6 Polystichum munitum Sword fern 129 298 8 8 Rubus leucodermis Black raspberry 10 14 4 4 Rubus spectabilis Salmonberry 96 227 3 4 Tiarella trifoliata Foamflower 7 11 4 2 Trillium ovatum Western trillium 0 1 0 1 Vaccinium alaskaense Alaskan blueberry 49 135 6 6 Vaccinium membranaceum Black huckleberry 20 6 4 1 Vaccinium ovalifolium Oval-leaved blueberry 8 5 1 2 Vaccinium parvifolium Red huckleberry 231 507 8 8 Amphib ians Species name C o m m o n name # o f # of sites ind iv idua ls encountered encountered (out of 8) Post Post Ambystoma gracile Baird Northwestern salamander 21 8 Ambystoma macrodactylum Baird Long-toed salamander 1 1 Ascaphus truei Stejneger Coastal tailed frog 21 6 Bufo boreas Baird and Girard Western toad 3 2 Ensatina escholtzii Gray Ensatina 23 6 Plethodon vehiculum Cooper Western red-backed salamander 24 8 Rana aurora Baird and Girard Red-legged frog 1 1 Taricha granulosa Skilton Rough-skinned newt 3 2 30 Table 2 Within-taxon abundance at each site by taxon. Data from multiple pre-treatment or multiple post-treatment sample periods have been pooled. Catch per unit effort (CPUE) values reflect the number of individuals encountered per 100 trap nights or sample locations. Small mammals Treatment Abundance CPUE Pre Post Pre Post A41 Control 89 114 45.88 46.72 GC Control 122 131 70.52 61.5 GH Control 100 132 50.25 59.19 SC Control 131 132 78.92 56.9 A41 Treatment 78 129 39 49.62 GC Treatment 123 138 65.43 63.01 GH Treatment 124 166 62.94 74.77 SC Treatment 135 158 71.43 68.1 Carabids Treatment Abundance CPUE Pre Post Pre Post A41 Control 66 426 31.43 101.43 GC Control 3 55 1.43 13.78 GH Control 51 297 25.12 71.91 SC Control 6 71 2.86 16.9 A41 Treatment 83 222 42.35 56.63 GC Treatment 8 89 3.81 21.55 GH Treatment 10 76 4.93 18.4 SC Treatment 7 75 3.33 18.47 31 Plants Treatment # of CPUE contacts Pre Post Pre Post A41 Control 25 58 19.53 15.10 GC Control 210 502 164.06 130.73 GH Control 134 391 104.69 101.82 SC Control 73 153 57.03 39.84 A41 Treatment 8 4 6.25 1.04 GC Treatment 154 395 120.31 102.86 GH Treatment 174 337 135.94 87.76 SC Treatment 113 214 88.28 55.73 Amphibians Treatment Abundance CPUE Post Post A41 Control 23 82.14 GC Control 23 95.83 GH Control 18 69.23 SC Control 9 40.91 A41 Treatment 5 17.86 GC Treatment 7 36.84 GH Treatment 7 25 SC Treatment 5 17.86 Table 3 Within-taxon diversity at each site by taxon. Data from multiple pre-treatment or multiple post-treatment sample periods have been pooled. Rarified species richness (SR) values were rarified to the smallest abundance at any site for that taxon during that time period (pre or post). Small mammals Treatment SR Rarified SR Shannon index Simpson's index Pre Post Pre Post Pre Post Pre Post A41 Control 4 6 3.87 6 0.86 1.04 0.53 0.58 GC Control 4 5 3.87 4.97 0.6 0.54 0.3 0.26 GH Control 4 4 3.78 3.86 0.93 0.92 0.54 0.56 SC Control 2 5 1.6 4.71 0.33 0.46 0.16 0.2 A41 Treatment 4 5 4 4.97 0.54 0.62 0.25 0.3 GC Treatment 4 3 3.26 2.97 0.04 0.28 0.02 0.1 GH Treatment 3 6 2.63 5.03 0.26 0.28 0.11 0.12 SC Treatment 3 5 2.4 4.36 0.12 0.26 0.04 0.1 Carabids Treatment SR Rarified SR Shannon index Simpson's index Pre Post Pre Post Pre Post Pre Post A41 Control 6 8 1.79 3.84 0.92 0.67 0.5 0.34 GC Control 1 9 1 9 0 1.39 0 0.66 GH Control 5 6 1.4 4.41 0.56 0.93 0.25 0.51 SC Control 2 5 1.5 4.5 0.45 0.53 0.33 0.23 A41 Treatment 3 5 1.24 3.77 0.32 0.88 0.16 0.53 GC Treatment 5 9 2.59 7.54 1.49 1.11 0.86 0.49 GH Treatment 2 5 1.3 4.83 0.33 0.96 0.2 0.53 SC Treatment 2 5 1.43 3.93 0.41 0.28 0.29 0.1 33 Plants Treatment SR Rarified SR Shannon index Simpson's index Pre Post Pre Post Pre Post Pre Post A41 Control 6 5 3.86 2.77 1.04 1.06 0.59 0.66 GC Control 12 12 4.38 2.86 1.37 1.25 0.58 0.58 GH Control 7 10 3.45 2.59 1 0.98 0.6 0.5 SC Control 13 11 5.43 3.27 1.73 1.55 0.48 0.49 A41 Treatment 4 2 4 2 0.87 0.56 0.64 0.62 GC Treatment 13 13 4.93 3.02 1.68 1.53 0.8 0.77 GH Treatment 11 12 3.42 2.5 1.06 1.04 0.79 0.73 SC Treatment 13 14 5.15 3.08 1.82 1.81 0.82 0.83 Amphibians Treatment SR Rarified SR Shannon index Simpson's index A41 Control 6 3.15 1.46 0.75 GC Control 5 3.14 0.8 0.76 GH Control 5 3.01 1.33 0.71 SC Control 4 2.94 1.33 0.69 A41 Treatment 4 4 1.33 0.9 GC Treatment 3 2.43 1.41 0.52 GH Treatment 3 2.9 1.08 0.76 SC Treatment 4 4 1.15 0.9 Figure 1 Schematic showing dimensions and layout of one site pair with respect to the stream. Each site is 1-ha in size, with one 0.5-ha plot on either side of the stream channel. Each site extends for 100 m along the stream reach and extends 50 m away from the stream on either side. The control and treatment sites are separated by a buffer of at least 50 m. 50 m 100m 100 m > 5 0 m control 0.5 ha treatment 0.5 ha 50 hi s t r e a m 50 m 0.5 ha control -100m -> 5 0 m 0.5 ha treatment -100m — 50 m 35 Figure 2 Schematic showing dimensions and layout of traps and plant transects within a single 0.5 ha plot (one half of a site). The mammal traps (M) are separated from one another by 14.3 m and begin at 7.15 m away from the stream. The invertebrate traps (I) are 10 m apart and the first trap is 2 m away from the stream. The amphibian trap (A) is 10 m away from the site midline and is set back 5 m from the stream. Each 15 m plant transect (P) is initiated at a random location within a plant stratum and extends from that point in a random direction. There are two plant transects within one stratum and two strata on one side of the stream within a site. 36 Figure 3 Response of all four taxa to treatment. Response measure for each taxon is untransformed catch per unit effort (CPUE), which reflects the number of individuals encountered per 100 trap nights or sample locations. Each panel shows CPUE of one taxon for control and treatment sites before and after treatment application. Bars represent means of the sites within each treatment and the error bars represent + 1 standard error. Black bars indicate control sites and grey bars indicate treatment sites, a. Mammal CPUE. b. Carabid CPUE. c. Plant CPUE. d. Amphibian CPUE. 80 LU Z) Q_ O 60 40 H B 20 - T n J pre-treatment post-treatment pre-treatment post-treatment 140 -j 120 -100 -LU 80 -Z) Q_ O 60 -40 -20 -0 -100 pre-treatment post-treatment post-treatment 37 Figure 4 Response of all four taxa to treatment. Response measure for each taxon is untransformed species richness (SR), rarified to the smallest total abundance at any site. Each panel shows SR of one taxon for control and treatment sites before and after treatment application. Bars represent means of the sites within each treatment and the error bars represent + 1 standard error. Black bars indicate control sites and grey bars indicate treatment sites, a. Mammal SR. b. Carabid SR. c. Plant SR. d. Amphibian SR. pre-treatment post-treatment pre-treatment post-treatment pre-treatment post-treatment post-treatment 38 Figure 5 Response of all four taxa to treatment. Response measure for each taxon is diversity calculated using the untransformed Shannon index (FT), which emphasizes species richness. Each panel shows diversity of one taxon for control and treatment sites before and after treatment application. Bars represent means of the sites within each treatment and the error bars represent + 1 standard error. Black bars indicate control sites and grey bars indicate treatment sites, a. Mammal diversity, b. Carabid diversity, c. Plant diversity, d. Amphibian diversity. 0.2 H 1.2 1.0 0.8 X 0-6 0.4 0.2 0.0 B :,'Sjt pre-treatment post-treatment pre-treatment post-treatment 1.6 1.4 1.2 1.0 0.8 H 0.6 0.4 H 0.2 0.0 jilt I •^1 oil ism m m pre-treatment post-treatment post-treatment 39 Figure 6 Response of all four taxa to treatment. Response measure for each taxon is diversity calculated using the untransformed Simpson's index (1 - D), which emphasizes species dominance. Each panel shows diversity of one taxon for control and treatment sites before and after treatment application. Bars represent means of the sites within each treatment and the error bars represent + 1 standard error. Black bars indicate control sites and grey bars indicate treatment sites, a. Mammal diversity, b. Carabid diversity, c. Plant diversity, d. Amphibian diversity. 0.6 0.5 0.4 0.3 0.2 A 0.1 0.0 B Hi pre-treatment post-treatment pre-treatment post-treatment 0.8 0.6 A Q i 0.4 A 0.2 0.0 Q i pre-treatment post-treatment post-treatment 40 Figure 7 Pre-treatment cross-taxa congruence in species richness (SR). Values on each axis represent within-taxon SR. SR values are rarified to the smallest abundance at any site for that taxon. Each data point represents one site. A positive relationship across taxa indicates congruence. 3 1 1 2 3 carabid S R 1 2 3 4 5 mammal S R 6 -] • -5 - • • • -on 4 - • • CO -•4—* c 3 -03 Q . 2 -1 -0 -1 2 carabid S R 41 Figure 8 Post-treatment cross-taxa congruence in species richness (SR). Values on each axis represent within-taxon SR. SR values are rarified to the smallest abundance at any site for that taxon. Each data point represents one site. A positive relationship across taxa indicates congruence. 2 4 6 8 10 carabid SR 0 1 2 3 4 5 amphibian SR 0 2 4 6 8 10 carabid SR 0 2 4 6 mammal SR 1 2 3 4 5 amphibian SR 0 1 2 3 4 5 amphibian SR 42 Figure 9 Pre-treatment cross-taxa congruence in community similarity. Values on each axis represent between-site Bray-Curtis similarity in community composition. The Bray-Curtis index ranges from 0 to 1. A value of 0 means that two sites have no species in common, and a value of 1 means that two sites have the same species and that their proportional abundances are equivalent. Each data point represents one pair-wise, between-site comparison. A positive relationship across taxa indicates congruence. 0.0 0.2 0.4 0.6 0.8 1.0 carabids 0.0 0.2 0.4 0.6 0.8 1.0 plants 0.0 0.2 0.4 0.6 0.8 1.0 plants 43 Figure 10 Post-treatment cross-taxa congruence in community similarity. Values on each axis represent between-site Bray-Curtis similarity in community composition. The Bray-Curtis index ranges from 0 to 1. A value of 0 means that two sites have no species in common, and a value of 1 means that two sites have the same species and that their proportional abundances are equivalent. Each data point represents one pair-wise, between-site comparison. A positive relationship across taxa indicates congruence. 0.0 0.2 0.4 0.6 0.8 1.0 carabids 0.0 0.2 0.4 0.6 0.8 1.0 amphibians CO -g CD o 1.0 1.0 -, • • 0.8 - • •• 0.8 • • * • * CO • • 0.6 - • • TD 0.6 - • c • • • JD CD •> • + 0.4 • • • CD 0.4 - : • • • • O 0.2 • 0.2 - • 0.0 0.0 - i i i i 0.0 0.2 0.4 0.6 0.8 1.0 plants 0.0 0.2 0.4 0.6 0.8 1.0 amphibians c CD CL E CD 1.0 - i 0.8 - • • • 0.6 -% • • • _ 0.4 -1 • • • * • • 0.2 -0.0 - 1 1 l 0.0 0.2 0.4 0.6 0.8 1.0 plants 0.0 0.2 0.4 0.6 0.8 1.0 plants 44 5 References Andelman, S. J . , and W. F. Fagan 2000. Umbrellas and flagships: efficient conservation surrogates or expensive mistakes? Proceedings of the National Academy of Sciences 97:5954-5959. Apigian, K. 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