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Short-term effects of clear-cut harvesting on the export of fish food subsidies in high elevation headwater… Sorensen, Jacqueline Jody 2012

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Short-Term Effects of Clear-cut Harvesting on the Export of Fish Food Subsidies in High Elevation Headwater Streams of Interior British Columbia by Jacqueline Jody Sorensen B.N.R.S., Thompson Rivers University, 1998  A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF ENVIRONMENTAL SCIENCE in The College of Graduate Studies (Environmental Sciences)  THE UNIVERSITY OF BRITISH COLUMBIA (Okanagan)  April 2012 ©Jacqueline Jody Sorensen, 2012  Abstract I investigated the immediate effects of clear-cut logging on the export of invertebrates and organic matter from headwater streams by using a Before, After, Control, Impact, Paired series approach (BACIP). Seventeen high elevation streams within two study areas (Horsefly River and Eagle Lake) in the southern interior of British Columbia, Canada were sampled for drifting macro-invertebrates, fine particulate organic matter (FPOM), and dissolved organic carbon (DOC). Invertebrate drift was collected by diverting the entire stream flow through a 250 µm mesh drift net over a 24 hour period (in triplicate for a total of 72 hours), directly before and one year after logging. I compared differences between 10 clear-cut treatment and 7 control streams in terms of invertebrate drift biomass/abundance flux (mg 24 hrs -1 and invertebrates 24 hrs-1 ), invertebrate drift biomass/abundance density (mg m-3 and invertebrates m-3 ), and FPOM and DOC concentration and flux (mg L-1 and mg 24 hrs-1 ). In addition to total invertebrate export, biotic metrics in the form of composition measures, taxa richness and diversity were calculated to determine changes in the invertebrate drift community. In the pre-impact phase of this study, I found that headwater streams were productive exporters of invertebrates (18-5382 invertebrates 24hrs-1 ) and organic matter (FPOM: 3-516 g 24hrs-1 , DOC: 1051579 g 24hrs-1 ). In the post-impact analysis, significant increases in total drifting invertebrate biomass and abundance flux were detected in clear-cut streams at Horsefly River. Additionally, community analysis of the drift composition showed significant changes in flux and density of Ephemeroptera (E), Plecoptera (P), Trichoptera (T) and Diptera (D). %EPT (ratio of EPT/total invertebrate abundance) was the only measure to indicate reduced abundance of sensitive taxa as a result of logging at both study areas. Significant changes in diversity were also observed at Eagle Lake. Overall, no significant responses in total flux or concentrations of FPOM and DOC were revealed. It is possible that seasonal and longer term annual monitoring may further define trends that were observed in the short term.  ii  Table of Contents Abstract .......................................................................................................................................ii Table of Contents ........................................................................................................................iii List of Tables ............................................................................................................................... v List of Figures ............................................................................................................................. vi Acknowledgements .................................................................................................................... vii 1  2  Introduction .......................................................................................................................... 1 1.1  Organic matter in streams...............................................................................................1  1.2  Flow of organic matter in streams ...................................................................................2  1.3  Invertebrate drift ............................................................................................................4  1.4  Ecological connectivity ..................................................................................................5  1.5  Effects of forest harvesting .............................................................................................7  1.6  Riparian management in British Columbia.......................................................................8  1.7  Thesis objectives & format .............................................................................................8  Short-Term Effects of Clear-cut Harvesting on the Export of Invertebrates and Organic Matter from Headwater Streams in Interior British Columbia; A Multi-Site Before-After-ControlImpact (BACI) Approach .................................................................................................... 10 2.1  Overview .................................................................................................................... 10  2.2  Methods ...................................................................................................................... 12  2.2.1  Study areas........................................................................................................... 12  2.2.2  Site description..................................................................................................... 13  2.2.3  Study design......................................................................................................... 14  2.2.4  Physical/chemical characteristics ........................................................................... 15  2.2.5  Macroinvertebrate drift ......................................................................................... 15  2.2.6  Fine particulate and dissolved organic matter.......................................................... 17  2.2.7  Statistical analyses ................................................................................................ 18  2.3  Results ........................................................................................................................ 18  2.3.1  Physical/chemical ................................................................................................. 18  2.3.2  Pre-impact export ................................................................................................. 19  2.3.3  Post-impact export ................................................................................................ 20  2.4  Discussion ................................................................................................................... 26 iii  2.4.1  Pre-impact export ................................................................................................. 26  2.4.2  Post-impact export ................................................................................................ 27  2.5 3  Effects of Clear-cut Logging on Invertebrate Drift Community Composition in Headwater Streams of Interior British Columbia .................................................................................... 31 3.1  Overview .................................................................................................................... 31  3.2  Methods ...................................................................................................................... 33  3.2.1  Study areas........................................................................................................... 33  3.2.2  Site descriptions ................................................................................................... 34  3.2.3  Study design......................................................................................................... 35  3.2.4  Physical/chemical characteristics ........................................................................... 36  3.2.5  Macroinvertebrate drift ......................................................................................... 36  3.2.6  Statistical analyses ................................................................................................ 39  3.3  4  Summary..................................................................................................................... 29  Results ........................................................................................................................ 39  3.3.1  Physical/chemical ................................................................................................. 39  3.3.2  Drift-benthos comparison ...................................................................................... 40  3.3.3  Drift composition ................................................................................................. 42  3.3.4  Taxa richness and diversity ................................................................................... 50  3.4  Discussion ................................................................................................................... 50  3.5  Summary..................................................................................................................... 53  Conclusion.......................................................................................................................... 55 4.1  Summary of research.................................................................................................... 55  4.2  Strengths and limitations .............................................................................................. 56  4.3  Applications and future directions ................................................................................. 58  References ................................................................................................................................. 61 Appendices ................................................................................................................................ 67 Appendix A – Sampling dates.................................................................................................. 67 Appendix B – Photos of drift sampling ..................................................................................... 68 Appendix C – Physical/chemical information ........................................................................... 69 Appendix D – List of identified invertebrate taxa ...................................................................... 70 Appendix E – Analysis & discussion of the drift-discharge relationship...................................... 72  iv  List of Tables Table 2.1 Total mean flux and densities of drifting invertebrates and organic matter...................... 20 Table 2.2 Results of paired comparisons for control–treatment differences for drift flux and drift densities of biomass and abundance............................................................................. 21 Table 2.3 Mean daily flux and concentrations of FPOM and DOC.. ............................................. 25 Table 3.1 Summary of taxa for benthic kick and drift samples...................................................... 41 Table A.1 Sampling dates for variables within the Horsefly River and Eagle Lake study areas........ 67 Table C.1 Physical and chemical information for study streams.........................................................69 Table D.1 List of taxa identified in invertebrate drift samples............................................................70  v  List of Figures Figure 1.1 A simplified model of a detrital food web in a forested stream.................................. 3 Figure 2.1 Map of study stream locations .............................................................................. 13 Figure 2.2 Daily flux and biomass/abundance densities of drifting aquatic invertebrates in treatments and controls pre- (2005) and post-impact (2006) in the Horsefly River study area........................................................................................................... 22 Figure 2.3 Daily flux and biomass/abundance densities of drifting invertebrates in treatments and controls pre- (2005) and post-impact (2006) in the Eagle Lake study area ........ 23 Figure 3.1 Map of study stream locations .............................................................................. 34 Figure 3.2 Relative biomass/abundance flux and densities of dominant invertebrate groups in the Horsefly River study area .............................................................................. 45 Figure 3.3 Relative biomass/ abundance flux and densities of dominant invertebrate groups in the Eagle Lake study area ................................................................................ 46 Figure 3.4 Mean difference values for Control – Treatment for biomass and abundance flux and densities of drifting aquatic and terrestrial invertebrate groups in treatments and controls pre- and post-impact in the Horsefly River study area ........................ 47 Figure 3.5 Mean difference values for Control – Treatment for biomass and abundance flux and densities of drifting aquatic and terrestrial invertebrate groups in treatments and controls pre- and post-impact in the Eagle Lake study area.............................. 48 Figure B.1 Photos of temporary flume installation, measurement of discharge, and drift net set-up…………………………………………………………………………… 68 Figure E.1 The relationship between discharge and daily invertebrate abundance and biomass for the Horsefly River and Eagle Lake study areas………………………. 72  vi  Acknowledgements I offer my deepest gratitude to my supervisors, Dr. Jeff Curtis and Dr. Brian Heise for their mentorship and guidance through my journey on this project. They extended considerable understanding and patience as I juggled a full time job and the birth of my two children during the course of this research. To the rest of my committee, Dr. Bob Lalonde and Dr. Adam Wei, thank-you for seeing me through to the finish line. This project could not have been done without the financial support from our granting agency, The Forest Science Program of British Columbia and the support of the host institution (and my employer), Thompson Rivers University. In-kind contributions were also received in the form of sample analysis, provided by Dr. Curtis’s lab at the University of British Columbia Okanagan. I would also like to acknowledge the many people who have helped out along the way. Our research assistants, Denise Clark and Dana Taylor, thank you for your tireless efforts in the field and in front of the microscope. Trent Hammer, thank you for answering my never-ending technical questions about dissolved organic carbon analysis. And lastly, special thanks to my husband who has provided unwavering support during my graduate work.  vii  1  Introduction  The effects of forest harvesting on the export of aquatic invertebrates and organic matter from high elevation, first order streams has not been well documented in British Columbia (BC). Recent research has focused more specifically on the effects of logging on benthic aquatic invertebrates (e.g., Price et al. 2003, Hernandez et al. 2005, and Moldenke & Ver Linden 2007), but few have investigated the potential impacts of logging on the export of invertebrates to downstream reaches, particularly fish-bearing reaches. Additionally, organic matter dynamics and stream energetics have been well studied (e.g., Meyer et al. 1998, Webster et al. 1999, Kiffney et al. 2000, Richardson et al. 2005), but more empirical evidence is required to assess the effects of logging on organic matter export in temperate streams. As organic matter and aquatic invertebrates are vital subsidies to downstream food webs (Vannote et al. 1980), the potential to indirectly affect adjacent fish populations could be significant. Concern was expressed by many government agencies that existing guidelines under BC’s Forest and Range Practices Act (FRPA) may not be adequate to protect fish communities lower down in the watershed. In this chapter, the role of organic matter in headwater streams, the ecological connectivity of stream ecosystems, invertebrate drift, and an overview of current research on the effects of clear-cut harvesting on organic matter will be discussed.  1.1 Organic matter in streams Organic matter may arrive in a stream in many different forms and through various pathways. Allochthonous materials are those that originate outside of the stream such as leaf litter, coarse woody debris, and leachate from soils (Cummins 1974). Climate, topography, soils, surrounding vegetation, and disturbance regimes can all influence the contributions of allochthonous materials to streams (Minshall 1988, Hartman & Bilby 2004). Autochthonous organic matter is produced within the stream and includes the autotrophic (primarily algae) and heterotrophic organisms (including aquatic invertebrates) that form the detrital food web (Cummins 1974). For functional purposes, organic materials are classified based on particle size and solubility. Particulate organic matter (POM) is generally broken down into coarse particulate organic matter (CPOM) and fine particulate matter (FPOM) (Cummins 1974). CPOM comprises needles, leaves, twigs, fruits and wood materials that are greater than 1 mm in size, while FPOM is essentially all other materials in the range of 0.5 µm – 1 mm, made up of degraded CPOM, 1  animal parts, feces, and micro-organisms (Cummins 1974). The size fraction less than 0.5 µm is referred to as dissolved organic matter (DOM) and is the dominant form of organic matter in aquatic ecosystems (Steinberg 2003). The chemical composition of DOM is extremely complex; however, DOM is often operationally defined as all organic carbon that passes through a 0.45 µm membrane filter (Leenher & Croué 2003). Generally, it consists of low molecular weight compounds such as carbohydrates and amino acids, and high molecular weight compounds (collectively called humic substances) that are considered to be relatively refractory (Leenher & Croué 2003). Humic substances absorb light at the blue end of the spectrum and can cause water high in DOM to appear brown in color (Evans et al. 2005). Due to this absorbance potential, DOM is also known to protect stream organisms from ultraviolet radiation (Kelly et al. 2003).  1.2 Flow of organic matter in streams FPOM and DOM are both highly mobile components of stream organic matter that are transported downstream and play an important role in the detrital food web. Although CPOM normally dominates organic matter inputs (in the form of leaf litter) into headwater streams, it is the smaller size fractions of FPOM and DOM that are more readily transported (Cushing et al. 1993, Kiffney et al. 2000). In areas of south-western British Columbia, DOM has been quantified as the most important source of organic matter, making up close to 80% of total export, while POM makes up approximately 15% (Kiffney et al. 2000, Karlsson et al. 2005). Allochthonous inputs of CPOM and DOM dominate in headwater stream environments due to the close association with riparian vegetation and soils and high degree of canopy closure (as originally described by Vannote et al. 1980 in the River Continuum Concept). These terrestrial sources of organic matter provide the base of fixed carbon energy in headwater streams and are processed to carbon dioxide and nutrients by heterotrophic organisms (Suberkropp 1998). Figure 1.1 illustrates a simplified detrital food web of a forested stream. It is important to note that autochthonous production by primary producers is shown as a minor contributor to organic matter in this type of stream ecosystem. Although levels of primary production will vary in headwater streams depending on light availability, it is relatively minimal compared to larger higher order streams (Vannote et al. 1980).  2  Forming the base of the food web, DOM enters the stream primarily through groundwater, leachates from soil runoff, precipitation (Aitkenhead-Peterson et al. 2003), and through the breakdown of CPOM within the stream (Meyer et al. 1998, Yoshimura et al. 2010). Variables such as soil properties, flow path, and slope (which would determine the amount of time water would remain in contact with substrates) are all found to be important regulators of DOM export in streams (Webster & Meyer 1997, Palmer et al. 2005). Biologically available DOM (normally low molecular weight compounds) is then broken down by bacteria and contributes to the formation of biofilm, which is a biologically active layer of embedded algae, bacteria, and fungi that forms over the stream substrate (McArthur & Richardson 2002, Frost et al. 2008). This biofilm becomes an important food source for grazing invertebrates and also contributes to the pool of FPOM through consumption (production of feces) and sloughing (McArthur & Richardson 2002). Many studies investigating the dynamics of organic matter in the hyporheic zone (the saturated sediments below and lateral to the stream channel) have demonstrated the importance of DOM in maintaining microbial communities on sub-surface sediments as well (e.g., Pusch 1996, Sobczak & Findlay 2002). The hyporheic biofilm can therefore function in storing and releasing substantial quantities of DOM into the stream food web (Pusch 1996).  Terrestrial Vegetation  CPOM  Groundwater, Runoff  Leaching  DOM  Light  Producers  Groundwater, Runoff  Fragmentation  Flocculation  Fungi Microbes  FPOM  bacteria, protozoa  Shredders  Scrapers  Collectors Predators  Figure 1.1 A simplified model of a detrital food web in a forested stream, illustrating the organisms responsible for processing the dominant forms of organic matter. Invertebrate functional feeding groups are indicated by grey shaded ovals. (Adapted from Cummins 1974, and Suberkropp 1998)  3  The production of FPOM results from flocculation or aggregation of DOM, and through the breakdown of CPOM via fungal decomposition and invertebrate detritivores (primarily shredders) (Cummins 1974). CPOM is initially colonized by fungi and bacteria which greatly increases the palatability and nutrition to shredders (Webster et al. 1999). Studies have shown complex relationships between fungal colonization and feeding preferences (e.g., Arsuffi & Suberkropp 1985) and overall most invertebrates will not consume CPOM before microbial colonization has occurred (Suberkropp 1998). The consumption of CPOM by shredders results in fragmentation and the production of feces, which in turn also contributes to the pool of FPOM. This relationship has been measured in a number of studies where aquatic invertebrates were removed by treatment with pesticides (Wallace et al. 1982, Cuffney and Wallace 1989, Cuffney et al. 1990) or where leaf litter was prevented from entering a stream (Hall et al. 2000, England & Rosemond 2004). Overall, the removal of invertebrates resulted in up to 74% reduction in leaf litter processing which significantly decreased the export of FPOM, while leaf litter exclusion resulted in dramatic reductions of invertebrate abundance and diversity and the standing crop of POM. It is evident that invertebrates, particularly shredders, play an important role in the processing of organic matter in headwater streams. Thus, they are the intermediate link between stream detritus and predators higher up in the trophic hierarchy (Malmqvist 2002).  1.3 Invertebrate drift Aquatic invertebrates are another important component of organic matter in streams. The movement of invertebrates downstream, termed drift, is an ecologically important phenomenon within stream ecosystems. Although highly variable, a significant proportion of the local population of invertebrates in a stream can be carried downstream every day, with drift distances varying between two and several hundred meters (reviewed by Brittain & Eikeland 1988). This movement provides both a source of colonization and direct food subsidies for fish in downstream reaches (Wipfli et al. 2007). Invertebrate drift is not entirely passive and dependent upon stream flow, and the mechanisms surrounding drift are complex. Although counterintuitive, many studies have shown weak relationships or negative correlations between drift and discharge (Matzinger & Bass 1995, Faulkner & Copp 2001, Wipfli & Gregovich 2002, Leung et al. 2009). The factors that cause invertebrates to drift are not well described but several types of drift have been identified in the literature; catastrophic drift, which is in response to large-scale disturbances such as flood, pesticide, sedimentation events, or even drought; behavioural or active drift 4  includes invertebrates entering the water column as a result of their activity, such as dispersal, escape from predation or poor habitat conditions; and constant or passive drift which is the background movement of invertebrates that are accidently dislodged from the substrate (Brittain & Eikeland 1988). Invertebrate drift is highly variable and is known to exhibit diel and seasonal fluctuations (Resh & Rosenberg 1989, Romaniszyn et al. 2007). Diel drift patterns are often a result of behavioural drifters entering the flow in response to environmental cues. For example, many studies have shown that drift tends to increase at night, possibly to avoid predation under the cover of darkness (Brittain & Eikeland 1988). Seasonally, drift varies dramatically across different ecosystems (Brittain & Eikeland 1988); however, in temperate streams invertebrate drift abundance is often highest in spring and early summer (Benke et al. 1991, Wipfli & Gregovich 2002). Average densities reported in the literature range from 1-22 individuals m-3 in Alaska (Wipfli & Gregovich 2002), less than 2 individuals m-3 in north-central British Columbia (Hoover et al. 2007), and 0.55.0 individuals m-3 in tropical streams (Benke et al. 1991). Terrestrial invertebrates (also termed allochthonous drift because it originates outside of the stream) can form an important part of the drift, especially during summer (Baxter et al. 2005). Terrestrial invertebrates are also considered a high quality resource for fish and have been shown to make up a large portion of the annual diet for drift feeding salmonids (Baxter et al. 2005). For example, in small northern streams in Japan, nearly half of the annual prey ingested by salmonids was terrestrial in origin (Kawaguchi & Nakano 2001). Similarly, terrestrial prey dominated the gut contents of fish during summer and fall in Oregon streams but was secondary to aquatic insects at other times of the year (Romero et al. 2005). These results suggest that during the growing season, typically June to September in temperate streams, allochthonous drift plays a very important role in the diet of drift feeding fish. Furthermore, the presence of terrestrial invertebrates in stream drift has been shown to directly influence the biomass and distribution of resident fish (Kawaguchi et al. 2003).  1.4 Ecological connectivity Headwater streams have been undervalued in their importance to downstream fish production (Wipfli & Baxter 2010). Literature now suggests that headwaters are ecologically connected to downstream reaches through numerous pathways and may contribute important prey subsidies for 5  fish (Gomi et al. 2002, Wipfli et al. 2007, Wipfli & Baxter 2010). The potential for drift contributions from headwater streams was demonstrated most notably by Wipfli and Gregovich (2002) in southeastern Alaska. This large scale study of Pacific coastal streams suggested that forested headwaters can provide a year-round source of organic matter and invertebrates to downstream habitats. Considering the sheer density of headwater streams on the landscape, the cumulative contributions would be considerable. To quantify this potential, they estimated through a simple watershed model that given the export of 0.44 g invertebrate dry mass m-2 year-1, every kilometer of fish-bearing stream could receive enough energy from headwater streams to support 100-2000 juvenile salmonids. Although it is generally accepted by the scientific community that a strong trophic linkage is certain between headwater streams and downstream reaches, information gaps still exist (Richardson et al. 2005, Wipfli et al. 2007). The degree of continuity, particularly for the transport of invertebrates, between headwater streams and downstream reaches remains poorly understood. Much research has been focused on organic matter transport and nutrient cycling but few have studied the transport or fate of invertebrate prey to downstream networks (Wipfli & Baxter 2010). If invertebrates could travel 50 m per day as originally reported by Waters (1965), or longer during high discharge events, how far could they potentially go to become food for fish? Are drifting invertebrates in fish-bearing reaches only locally derived? The transport of organic and inorganic materials through watersheds can vary both spatially and temporally (Gomi et al. 2002, MacDonald & Coe 2007). With so many variables to consider (season, discharge, slope, topography etc.) it is apparent drift distances would vary tremendously across the landscape and would be difficult to predict (Brittain & Eikeland 1988, MacDonald & Coe 2007). Attempts to quantify the degree of continuity between headwater streams and downstream reaches are beginning to emerge from the literature. Recent evidence from Oregon suggests that invertebrate drift originates locally within a stream (Danehy et al. 2011). This study attempted to quantify the distance travelled by drifting invertebrates by blocking the flow of invertebrates to downstream reaches during summer base flow. No changes in invertebrate drift were found between blocked and unblocked streams. Although the authors recognize that these results may not be consistent during higher flow conditions, low flow during summer is the most metabolically demanding period for fish (Harvey et al. 2006, Rosenfeld & Taylor 2009). At this time, water levels are low and temperatures are high, and fish are most sensitive to changes in prey abundance (Rosenfeld & Taylor 2009). The idea that drift is generated within the immediate  6  vicinity of a stream reach contradicts the general assumption that invertebrates are transported to downstream reaches as food for fish. Further investigation in this area is required.  1.5 Effects of forest harvesting In recognition of the connectivity between headwater streams and downstream reaches, much attention has been given to the impacts of land use activities on these ecosystems. Clear-cut harvesting removes the forest canopy and has the potential to significantly affect the biotic and abiotic characteristics of streams. Since headwater streams can make up the majority of total stream area in a watershed (Gomi et al. 2002), then the cumulative effects of landscape disturbance on higher order streams may become very large. Over the past few decades, considerable research has focused on the effects of forestry activities on small streams. It has been well documented that logging can bring about changes in stream temperature (Gravelle & Link 2007), organic matter dynamics (Bilby & Bisson 1992), channel structure (Jackson et al. 2001) and the structure and function of macroinvertebrate communities (Stone & Wallace 1998, Hernandez et al. 2005, Nislow & Lowe 2006). Results from organic matter modeling experiments in BC streams, predicting the effects of forest harvesting, suggest up to 80% reduction in the stock of POM (Karlsson et al. 2005). Benthic invertebrate communities have shown various responses to logging. Commonly, biomass and abundance will often increase after clear-cut harvesting (e.g., Stone & Wallace 1998, Hernandez et al. 2005, Nislow & Lowe 2006, Jackson et al. 2007) or show little to no change (e.g., Gravelle et al. 2009). Taxonomic richness of invertebrate communities has been shown to decline in harvested watersheds of Quebec (Martel et al. 2007) and increase in forests of central United States (Brown et al. 1997). It is clear that our ability to generalize about the effects of logging on invertebrate communities is limited, and may depend largely on underlying environmental conditions of the region (Richardson 2008). Information regarding the effects of harvesting on invertebrate drift in headwater streams remains scant. In central British Columbia, forest harvesting decreased the density and flux of drifting aquatic invertebrates but increased the relative density of allochthonous drift (terrestrial invertebrates) (Hoover et al. 2007). The higher density of terrestrial invertebrates was thought to be a result of increased levels of herbaceous vegetation and warmer temperatures observed in harvested streams. Similarly, in North Carolina streams, litter exclusion studies have resulted in a 7  reduction of benthic and drifting invertebrates (Siler et al. 2001). Conversely, increased export of invertebrates and detritus were found to occur in logged streams of southeastern Alaska (Piccolo & Wipfli 2002) and Washington (Binckley et al. 2010). These contradictory results may be indicative of site-specific responses to forest harvesting. The variation of invertebrates and detritus in stream drift has been shown to be a function of both harvesting and eco-region (Binckley et al. 2010). For example, headwater streams in the Cascade Mountains of Washington exported more invertebrates and detritus in logged catchments, but significant differences among wet and dry ecosystems were observed (Binckley et al. 2010). Moreover, it is evident that ecosystem-specific information may be required to fully assess the impacts of logging on organic matter in headwater streams.  1.6 Riparian management in British Columbia In British Columbia, streams receive riparian management protection under the Forest and Range Practices Act of BC (FRPA) to preserve water quality for stream organisms and human consumption. Streams are classified based on their size, presence of fish and their proximity to community watersheds (BC MOFLNRO 2004). Most headwater or first order streams fall within the S5 or S6 classification, which are defined as streams that do not contain fish nor reside within a community watershed. An S5 stream is greater than 3 m wide, and an S6 encompasses any stream less than 3 m wide. Harvesting regulations do not require the establishment of a riparian reserve zone for S5 or S6 streams, but rather a riparian management zone in which harvesting activity is only restricted. For S6 streams, 100% of stems can be removed from the management zone (BC MOFLNRO 2004). The only exception to this is if the stream drains directly into a fishbearing reach, then enough stems to maintain channel and bank stability must be maintained around the stream (BC MOFLNRO 2004). Due to this lack of protection and the potential connectivity to downstream reaches, it is essential that we understand the changes that could be imposed on ecosystem functioning.  1.7 Thesis objectives & format The primary objective of this research was to assess the short-term effects, if any, of clear-cut harvesting on the export of aquatic invertebrates, FPOM and DOM in high elevation, headwater streams of interior British Columbia. A secondary objective was to quantify the total organic 8  matter export from these streams to estimate the potential contribution to downstream reaches and as food for fish. The anticipated outcome of this research is to incorporate the results of the study into current riparian management guidelines for small, non-fish-bearing streams in British Columbia. By examining streams in two different ecosystems (the Engelmann Spruce Sub-alpine fir and Sub-boreal Spruce biogeoclimatic zones), information derived from this project may be extrapolated to a large number of high elevation forested streams within the interior of BC, and may assist resource managers in obtaining sustainable forest management practices by developing optimal riparian guidelines. The results of the research are presented in two chapters within this thesis. Chapter 2 describes the results of the effects of clear-cut harvesting on the overall export of organic matter from headwater streams. This chapter focuses on the total abundance and biomass flux and densities of drifting aquatic invertebrates, FPOM and DOM export before and after logging. Chapter 3 is a more detailed analysis of the drifting invertebrate community as a result of logging treatment. In this chapter, potential changes to community structure and diversity are explored. To conclude the thesis, Chapter 4 summarizes the research conclusions and discusses the strengths and limitations of the project. As well, potential applications and possible future directions for research are addressed.  9  2  Short-Term Effects of Clear-cut Harvesting on the Export of Invertebrates and Organic Matter from Headwater Streams in Interior British Columbia; A Multi-Site Before-After-ControlImpact (BACI) Approach  2.1 Overview Forestry is the most influential industry on the landscape of boreal forests and its potential to affect stream water quality and biological communities is substantial (Richardson et al. 2005). Currently, non-fish-bearing headwater streams in British Columbia (BC), Canada receive very little protection under provincial legislation, and rely on the application of practical, cost-effective measures (best management practices (BMP)) to maintain proper functioning condition (BC MOFLNRO 2004). BMP allow 100% removal of merchantable timber from non-fish-bearing streams less than 3 m wide while retaining non-merchantable deciduous trees and shrubs within 5 m of the stream edge (BC MOFLNRO 2004). Because headwater streams can make up the majority of total stream area in a watershed (Gomi et al. 2002), and are relatively unprotected from the physical effects of logging, the cumulative effects on higher order streams may become very large. The export of invertebrates and organic matter is known to support trophic linkages in stream food webs (Gomi et al. 2002, Wipfli et al. 2007, Wipfli & Baxter 2010), and changes to this transport as a result of landscape disturbance may have consequences to higher trophic levels further down in the watershed. Therefore, in order to protect the integrity of downstream reaches, we must understand the potential consequences that forest practices can have on stream food webs, in order to develop effective riparian management strategies for headwater streams. Aquatic invertebrates, fine particulate organic matter (FPOM) and dissolved organic matter (commonly measured as dissolved organic carbon or DOC) all play very important roles in stream food webs. The movement, or drift, of aquatic invertebrates provides a source of colonization and potential food subsidies for fish in downstream reaches (Wipfli et al. 2007). Although coarse particulate organic matter (CPOM) normally dominates terrestrial inputs (in the form of leaf litter) into headwater streams, it is the smaller size fractions of FPOM and DOM that are more readily transported through watersheds (Cushing et al. 1993, Kiffney et al. 2000). In areas of south-western British Columbia, DOM has been quantified as the dominant source of organic matter, making up close to 80% of total export, while POM makes up approximately 15% (Kiffney et al. 2000, Karlsson et al. 2005). Aside from being an important source of energy for 10  microbial communities, DOM can also provide indirect benefits to stream organisms by attenuating UV radiation (Kelly et al. 2003). There is a large body of literature documenting the physical and biological changes that can occur in streams as a result of logging. Removing the forest canopy can bring about changes in aquatic invertebrate communities (e.g., Stone & Wallace 1998, Price et al. 2003, Hernandez et al. 2005, Jackson et al. 2007, Moldenke & Ver Linden 2007), water temperature (e.g., Gravelle & Link 2007), organic matter dynamics (e.g., Bilby & Bisson 1992, Meyer et al. 1998, Webster et al. 1999, Kiffney et al. 2000, Richardson et al. 2005), and even channel physical structure (e.g., Jackson et al. 2001). The responses of aquatic invertebrates to clear-cut logging are highly variable and often contradictory (Melody & Richardson 2007). Increased invertebrate production has been commonly demonstrated (e.g., Stone & Wallace 1998, Hernandez et al. 2005, Nislow & Lowe 2006, Jackson et al. 2007) largely due to increases in autochthonous (within stream) production, while others have shown little to no changes (eg., Gravelle et al. 2009). It is evident from the literature that the response of macroinvertebrate communities to logging is often unpredictable, and may depend on many local factors, especially climate (Binckley et al. 2010). The response of invertebrate drift to the effects of clear-cut harvesting is relatively unknown. Although invertebrate drift can be correlated to benthic invertebrate communities (James et al. 2008), empirical evidence is required to estimate the effects of harvesting on invertebrate drift. Simulation of deforestation, which involves reducing the inputs of terrestrial detritus to streams, has demonstrated reductions of benthic and drifting invertebrates (Siler et al. 2001). The effects of various types of riparian reserve strips on invertebrate drift have been studied in central BC (Hoover et al. 2007). In treatments where 100% of the riparian vegetation was removed, significant decreases in the density and flux of drifting aquatic invertebrates were observed. Contradictory to these findings, increased export of invertebrates and detritus have been found to occur in logged streams in regions of the Pacific Northwest (Piccolo & Wipfli 2002, Binckley et al. 2010). Moreover, significant differences among streams within differing eco-regions suggest that the response of invertebrate drift to forest harvesting may be dependent on region-specific conditions (Binckley et al. 2010). The effects of clear-cut logging on organic matter have been reasonably well documented and are also known to vary considerably with climate and vegetation. Overall, research has demonstrated a sharp reduction in litter contributions to streams upon the removal of the forest canopy up to the 11  streambank (Bilby & Bisson 1992, Webster et al. 1999, Kiffney & Richardson 2010). Total export of DOC is generally known to increase for several years after clear-cut logging (reviewed by Kreutzweiser 2008). Estimates from studies in the boreal forests of Sweden have reported increases in DOC export of up to 70% in clear-cut streams (Laudon et al. 2009). Results from an experimental forest in northwestern Ontario show peak DOC export 2 years after logging but then drop off to at or below pre-harvest levels (Morris 2009). In interior British Columbia, unpublished data from Mackay and Heise (2005) have shown initial increases in FPOM concentrations in newer clear-cuts but recovery within 5 years, and no effects on total export of DOC. The purpose of this study was to assess the immediate effects of clear-cut harvesting on the export of invertebrates, FPOM, and DOC from high elevation headwater streams in the interior of BC. I applied a spatially (multiple locations) and temporally replicated Before-After-ControlImpact (BACI) design across multiple streams in two watersheds. By examining potential impact trajectories within ecologically different watersheds, my goal was to be able to extrapolate results to similar ecosystems. Drifting invertebrates and organic matter were collected from 22 streams 1 year prior to logging and from 17 streams 1 year after logging (2 years after for DOC). Preimpact data were used to estimate export contributions from headwaters streams of the BC interior. As a result of clear-cut harvesting, I hypothesized that increases in invertebrate abundance and biomass in the drift would be observed, as well as increases in the export of FPOM and DOC.  2.2 Methods 2.2.1  Study areas  This study was conducted in two watersheds approximately 60 km apart within the Cariboo Forest Region in the southern interior of British Columbia, Canada (Figure 2.1). With the assistance of local forest licensees, Tolko Industries for the Horsefly region and West Fraser Mills for the Eagle Lake region, eligible streams were selected that were proposed for clear-cut logging treatment in 2005/2006. Streams selected for this study shared similar physical characteristics within their catchment areas such as width (<3 m), slope, aspect, discharge and substrate. Streams were also confirmed fishless by referring to consultant reports prepared for the licensee’s harvest plan (either by electrofishing or identification of fish barrier). Undisturbed control streams were selected in close proximity to each treatment stream. Originally, 12 cut12  block treatment and 10 control streams were sampled across the two watersheds in the pre-impact condition in 2005. Due to changes in the logging schedule, only 10 treatment and 7 control streams were sampled post-impact. Two of the anticipated treatment streams were only partially logged and 3 controls were omitted because they were compromised by harvesting activity. The presence of Mountain pine beetle in the Eagle lake watershed and Spruce beetle in the Horsefly River watershed created challenging conditions to adhere to a strict logging plan, as licensees were forced to move to areas of intensive beetle activity. Data from omitted streams were still used to increase replication for estimates of total export before impact occurred but were removed from the post-impact analysis.  Horsefly River Study Area  Legend Clear-cut treatment Omitted treatment Control Omitted control Road (un-paved) Park  Eagle Lake Study Area  Figure 2.1 Map of study stream locations. The Horsefly River and Eagle Lake watersheds are located in the Cariboo Forest Region in south-central British Columbia. All streams sampled in preimpact condition in 2005 are shown, with hollow symbols indicating streams omitted in 2006. (Map source: Natural Resource Canada 2004)  2.2.2  Site description  The Horsefly River study area is situated within the Engelmann-spruce Sub-alpine fir (ESSF) biogeoclimatic zone (Steen & Coupé 1997) and the location of study streams ranged from 1300 to 1600 m in elevation. Located in the foothills of the Cariboo Mountains, the mean annual precipitation is greater than 1000 mm with snow-free periods typically lasting from mid-June to September (Steen & Coupé 1997). The topography is mountainous with relatively steep slopes (range of 17 – 54%), with discharges of study streams varying from 0.4 to 6 Ls-1 in early summer. 13  The surrounding vegetation of the Horsefly study sites was typical of an ESSF Wet Cool subzone, characterized by mature coniferous stands of sub-alpine fir (Abies lasiocarpa) and Engelmann spruce (Picea engelmannii), with the understory dominated by various components of alder (Alnus sp.), thimbleberry (Rubus parviflorus), devils club (Oplopanax horridus), white flowered rhododendron (Rhododendron albiflorum), lady fern (Athyrium filix-femina), sitka valerian (Valeriana sitchensis), foamflower (Tiarella trifoliata), and five-leaved bramble (Rubus pedatus). Spruce beetle (Dendroctonus rufipennis) was also present in the watershed and had begun to infect Engelmann spruce trees around study streams in 2005. The Eagle Lake study area, ranging from 1100 to 1400 m in elevation, is located in the Sub-boreal Spruce (SBS) zone (Steen & Coupé 1997). This ecosystem type is drier than the ESSF, with the mean annual precipitation ranging from 480 to 720 mm (Steen & Coupé 1997). The rolling topography consisted of less steep terrain than the Horsefly River study area (range of 4 – 28% slope), with study stream discharges ranging from 0.2 to 3 L s-1 . The dominant forest cover surrounding the Eagle Lake study sites was lodgepole pine (Pinus contorta) with minor components of Engelmann spruce and sub-alpine fir. Understory vegetation comprised alder, thimbleberry, devils club, lady fern, horsetail (Equisetum sp.), bunchberry (Cornus canadensis), and five-leaved bramble. 2.2.3  Study design  This study followed a BACI (Before – After – Control - Impact) paired design with both spatial and temporal replication (Stewart-Oaten et al. 1986, Underwood 1994). This approach is designed to focus on changes due to impact relative to a reference (control) area. Treatment streams were paired with a proximal control stream and sampled simultaneously before and after clear-cut logging impact. Two alternative models of analyses were applied to this design: 1) the differences between control-treatment stream pairs were compared before and after logging, and 2) The means of pooled treatment and pooled control streams were compared before and after logging. This second approach was included to identify differences in analyses that may have resulted from artificially creating control-treatment pairs. Control locations were not randomly selected but were chosen to share similar physical characteristics such as width, slope, aspect and discharge with treatment streams (as recommended by Underwood 1994). In most cases control streams were located within 1 km of treatment streams, and were at minimum 50 m away from the associated cut-block boundary. 14  Control stream sampling locations were established at the same elevation if possible and were sampled during the same time period as treatment streams. Sampling locations for treatment streams were 200 m downstream of the upper cut-block boundary to equalize the length of stream exposed to harvest treatment (road intersections were avoided to prevent confounding effects). Clear-cut logging treatment consisted of complete removal of riparian vegetation in both study areas. In all but 2 streams, trees were yarded away from the stream channel but most streams experienced considerable deposition of branches and needles. Drifting invertebrate and organic matter response variables were measured in ten treatment and seven control streams during stable flow conditions prior to logging (pre-impact) in summer 2005, and again the following year after logging took place (post-impact) in 2006. Exceptionally, one replicate and control pair in the Eagle lake study area was sampled in the post-impact condition in 2007 because of logging postponement. Due to the labor intensive nature of sample sorting and identification, drifting invertebrates were sampled once before and once after logging treatment. To monitor potential seasonal variation in dissolved organic carbon concentrations, water samples were collected in spring and fall in addition to summer sampling (see Appendix I for specific sampling dates). 2.2.4  Physical/chemical characteristics  Physical and chemical site characteristics were recorded at each study stream, including discharge, wetted channel width, slope, aspect, and substrate composition. Precipitation was also monitored during the sampling period (to prevent sampling during a spate event) as well as pH, conductivity and temperature. To determine stream discharge, a section of metal stove pipe was installed at a natural drop in the stream channel to funnel nearly 100% of the stream flow through a makeshift flume (see Appendix II for photos). Discharge was then measured volumetrically by recording the time it took to fill a container of known volume (Gore 1996). Discharge (L s-1 ) was measured at the beginning and end of a 24 hour period to estimate a daily average. 2.2.5  Macroinvertebrate drift  Drifting invertebrates were sampled over a 24 hour period in triplicate (72 hours in total) to achieve an accurate estimate of daily export (flux). Taxon-specific behaviour and diel patterns can cause fluctuations in the drift composition during the course of a day (Brittain & Eikeland 1988). Sampling over 72 hours was undertaken to reduce this variability and include both diurnal 15  and nocturnal drifters. To collect drifting invertebrates, a 250 µm drift net was installed under the stovepipe flume so that the entire stream flow was directed into the net. Backflow or escapes at the net entrance were minimized by allowing the stream flow to fall into the net (see Appendix II for photos of drift sampling set-up). Collected organisms and debris were transferred to Whirl-pak bags and preserved in the field with 70% ethanol for later enumeration, identification and measurement. In the lab, invertebrates were removed from sample debris by sorting under 4 x magnification. As the objective of this project was to focus on macroinvertebrates as fish food subsidies, the micro-invertebrate component (e.g., copepods) that was not easily visible at 4 x magnification was ignored. This micro-component, although not identified, would be included in the estimate of fine particulate organic matter (described below). If the estimated sorting time of each drift sample appeared to be greater than 12 hours, samples were separated into coarse (> 2 mm) and fine fractions (250 µm – 2 mm) by rinsing through wire mesh sieves. Coarse fractions were sorted entirely while the fine fractions were sub-sampled prior to sorting. Due to the minute particle size of the fine fraction, we used a volumetric sub-sampling approach using a Folsom plankton splitter based on methods proposed by Glozier et al. (2002). After sorting, the remaining debris from all samples was returned to bags and every tenth sample was re-sorted for quality control purposes (as per recommendations from Glozier et al. 2002). Sorted invertebrates were enumerated and identified to family or genus using taxonomic keys (Merritt & Cummins 1996, Stewart & Oswood 2006). Mayflies (Ephemeroptera), stoneflies (Plecoptera), and caddisflies (Trichoptera) were identified to genus while the true flies (Diptera) were identified to family level only. Total body lengths of Ephemeroptera, Plecoptera, Diptera and Trichoptera were measured to calculate dry-mass based on length-weight regressions from the literature (Sample et al. 1993, Burgherr & Meyer 1997, Benke et al. 1999). All other insect and non-insect invertebrates (less dominant groups) were identified to class or order only to determine aquatic or terrestrial origins. Dry-mass of these groups were determined by desiccating and weighing. Although results for total biomass and densities of all invertebrates combined will be presented in this chapter, a full taxonomic analysis is presented in Chapter 3. Invertebrate drift was expressed as both daily flux and density variables. Once the samples were enumerated and measured, the total number of invertebrates in the 24 hour drift sample was used as the estimate of drift flux and expressed as invertebrates 24 hrs -1 . The daily average stream discharge was then used to standardize the 24 hour drift to biomass and abundance density 16  measurements (mg of dry mass m-3 and invertebrates m-3 respectively). Because of the large spectrum of factors that can influence drift (Brittain & Eikeland 1988), it was important to establish a relationship with the amount of individuals in the drift and stream discharge. Therefore, before proceeding with standardization, the relationship between stream discharge and total flux of invertebrates was examined for each study area. 2.2.6  Fine particulate and dissolved organic matter  Fine particulate organic matter (FPOM) and dissolved organic matter (DOC) were sampled in triplicate at each study stream once during the 72 hour sampling period. Three 10 litre carboys were filled with stream water using a 1 mm screen to eliminate larger organic debris. Sample water was filtered on site through a 0.45 µm glass fibre filter (pre-ashed and weighed) using a field vacuum filter apparatus. The volume of sample filtered was adjusted accordingly to produce a visible film on the filter (minimum 1 L). Filters were then folded and placed in a pre-ashed tinfoil envelope, sealed in a plastic bag and stored in a freezer upon returning from the field. The ash-free dry weight of the filter residue was determined in the lab using the gravimetric approach (Wallace and Grubaugh 1996) and the filter volume used to calculate the concentration of FPOM in mg L-1 . The remaining filtrates from the FPOM procedure were collected for analysis of DOM (organic matter < 0.45 µm). DOM concentration was estimated by determining total organic carbon content (TOC) of the filtered sample and reported as dissolved organic carbon or DOC. Filtered water was stored in 60 ml amber glass bottles and kept cold with ice packs in a portable cooler. Samples were transported back to the lab and analyzed for DOC concentration (mg L-1 ) using the non-purgible organic carbon method with a Shimadzu total carbon analyzer. Samples were analyzed in duplicate to allow crosschecking, and blanks and reference solutions were used accordingly for quality control and assurance measures. Flux or the rate of FPOM and DOM output were calculated by multiplying concentrations by the mean 24 hour discharge. In cases where less than 100% of the stream flow was captured by the artificial flume (i.e., subsurface or peripheral flow that could not be measured), estimates of total stream flow were applied to the data to avoid underestimating total flux of both FPOM and DOM.  17  2.2.7  Statistical analyses  The null hypothesis that invertebrate drift, FPOM, and DOM dependent variables did not differ before and after clear-cut harvesting (at α = 0.05) was examined. As the study design was based on repeated measures at the exact location before and one year after harvesting, I used paired ttests (or non-parametric equivalent) and repeated measures ANOVA (RM-ANOVA) to compare response variable means before and after impact. Both the mean differences between controltreatment pairs, as well as pooled controls and pooled treatments were compared. To avoid inflation of error estimates, Horsefly River and Eagle Lake study areas were analyzed separately due to biological/physical differences and inconsistency in sampling times. Non-synchronized sampling was required due to difficult access and time required to complete 72 hour drifts at each location. All data were analyzed using SPSS (version 17.0); Shapiro-Wilks and Levene’s test were used to test assumptions of normality and homoscedasticity respectively. If assumptions were not met, transformations were applied as necessary. Typically, ln x or log10 (x + c) for difference data were applied with the constant c chosen to anchor the minimum value at 1.0 (Osborne 2002). For ease of graphical interpretation, non-transformed data is presented in bar graphs illustrating the change in means before and after clear-cut harvesting. Paired t-tests were used to analyze drifting invertebrate and FPOM concentration and flux variables before and after logging (except for Horsefly River FPOM flux for which the non-parametric Wilcoxon sign-rank test was used). RM-ANOVA was used to compare DOM concentration and flux over a 3 year period (1 year before and 2 years after). In order to express and compare invertebrate drift in terms of density (individuals m-3 or biomass m-3 ), simple linear regression with ANOVA was used to examine the relationship between invertebrate drift flux and stream discharge.  2.3 Results 2.3.1  Physical/chemical  At the Horsefly River study area, the temperature of study streams ranged from 7 to 9 °C at the time of sampling and all streams had a neutral pH (mean = 7.2) and consistently low specific conductance (mean = 70 µS cm-1 ). Stream temperatures at the Eagle Lake study area ranged from 8-12 °C and mean conductance was approximately 112 µS cm-1 , also with a neutral pH. Although discharges varied among study streams, differences between treatments and controls 18  within each study area were not significant (Horsefly River; t = -0.007, p = 0.995, Eagle Lake; t = -2.117, p = 0.088). Lower discharges were observed in 2006 (post-impact) compared to 2005 (pre-impact) in all study streams except for Horsefly River streams 507 and 508. Because chemical variables were solitary measurements, statistical comparisons over the years were not performed; however, these variables remained relatively constant over time and showed no major fluctuations in response to logging (see Appendix III for detailed physical and chemical information). 2.3.2  Pre-impact export  Headwater streams at both Horsefly River and Eagle lake study areas contributed an average of 370 mg of invertebrate dry mass per day to the drift, but this varied considerably among study streams (range of 5-1223 mg 24 hrs-1 ). The daily flux of individual drifting invertebrates ranged from 18-5862 individuals 24 hrs-1 (Table 2.1 displays mean export of invertebrates and organic matter variables over a 24 hour period (flux) as well as the mean abundance and biomass densities of invertebrates). Eagle Lake study streams appeared to contribute twice as many individuals to the drift as Horsefly River which was likely due to the types of invertebrate taxa that dominated the drift within these watersheds. Larger bodied Trichoptera (caddisflies) made up to 50% of the total biomass in Horsefly streams but were represented by very few individuals, while streams in Eagle Lake were dominated by smaller bodied Diptera (mostly chironomids) and Ephemeroptera (mayflies) (see Chapter 3 for a detailed taxonomic analysis of the drift and Appendix IV for a complete list of identified taxa). Before proceeding with conversion of flux variables to density measures, the relationships between total invertebrate flux and stream discharge were tested using simple linear regression analysis (see Appendix V for more details about this analysis). The linear relationships between invertebrate drift flux and discharge were significant at Horsefly River (biomass; R2 = 0.642, ANOVA p = 0.002, abundance; R2 = 0.729, ANOVA p < 0.001), but appeared weak at Eagle Lake (biomass; R2 = 0.048, ANOVA p = 0.599, abundance; R 2 = 0.531, ANOVA p <0.040). Due to the weak relationship between drift flux and discharge at the Eagle Lake study area, density measures were used with caution for purposes of comparison. When flux estimates were standardized to discharge and expressed as densities, biomass was 7 times higher and abundance was over 16 times higher at Eagle Lake compared to Horsefly River (largely due to lower stream flows in this study area). Variability in abundance density was also quite high at Eagle Lake, ranging from 7-186 invertebrates m-3 , while Horsefly varied only from 1-8 invertebrates m-3 . 19  Biomass density was relatively consistent among most streams but was often strongly influenced by the presence of large-bodied caddisflies in a few of the Horsefly study streams. FPOM and DOM were the dominant forms of organic matter exported from headwater streams in both study areas (Table 2.1). Daily flux of FPOM ranged from 23–500 g 24 hrs-1 at Horsefly River, and 7-134 g 24 hrs-1 at Eagle Lake, while DOM (reported as DOC) ranged from 10 –1442 g 24 hrs-1 . Similarly to invertebrate flux, both study areas showed comparable total fluxes of DOC but were very different in terms of concentration (during base-flow conditions). Eagle Lake showed relatively high concentrations of DOC (mean of 11.8 mg L -1 ) which was almost 4 times that of Horsefly River streams.  Table 2.1 Total mean flux and densities of drifting invertebrates and organic matter at Horsefly and  Eagle Lake study areas. Means are given with standard error in brackets. * Slight underestimates due to abundance data lacking for non-insect groups in 4 of 12 streams. Total Mean Export Invertebrates Daily abundance (individuals 24 hrs -1 ) Daily biomass (mg dry mass 24 hrs -1 ) Abundance density (invertebrates m-3 ) Biomass density (mg dry mass m-3 ) Organic matter Daily DOC (g 24 hrs -1 ) Daily FPOM export (g 24 hrs -1 ) DOC concentration (mg L-1 ) FPOM concentration (mg L-1 )  2.3.3  Horsefly River (n = 12)  Eagle Lake (n = 9)  795* (152) 371 (55) 3.4* (0.8) 1.8 (0.3)  1926 (409) 373 (73) 55.4 (25.4) 12.1 (6.4)  685 (94) 202 (47) 3.2 (0.3) 0.9 (0.1)  671(195) 44 (19) 11.8 (1.6) 0.6 (0.1)  Post-impact export  One year after clear-cut logging, significant increases in drifting invertebrate biomass and abundance flux were observed in the Horsefly River study area relative to controls (Table 2.2). Paired t-tests revealed statistically significant changes in the daily flux of invertebrates when the differences of control –treatment pairs were compared before and after logging (biomass p = 0.039, abundance p = 0.022), while pooled treatment and controls were not significant when compared independently (Figure 2.2 a,b). When the drift was expressed as densities, abundance and biomass more than doubled in treatment streams, although a similar (but less pronounced) effect was also observed in control 20  streams. Paired t-tests of control – treatment differences for 2005 and 2006 showed changes due to logging were not statistically significant; however, when pooled treatment streams for 2005 were compared to 2006, marginally significant changes in abundance density (p = 0.050) and biomass density (p = 0.078) were apparent that were not seen in control streams (p = 0.151 and p = 0.159 respectively). Figure 2.2 illustrates both flux and density drift variables before and after logging. It is important to note that the standard error appears large on the control-treatment differences because this represents the variation among treatment and control pairs. The error associated with the paired t-test is much less due to the nature of the paired comparison but was not suitable for graphical presentation. At Eagle Lake, no significant changes in invertebrate drift flux or density were detected. Although the daily flux of biomass increased in treatment streams, a similar increase was also observed in controls (Figure 2.3). As a result, no significant effects were found when controltreatment differences were compared (Table 2.2). Figure 2.3 illustrates a decreasing trend in the post-impact period for biomass and abundance densities as well as abundance flux. These trends were largely influenced by a few streams that experienced large reductions in small bodied invertebrates (primarily chironomids and baetid mayflies) in the post-impact period (which is revealed by the size of the error bars in Figure 2.3 b,d).  Table 2.2 Results of paired comparisons for control–treatment differences for drift flux (invertebrates day-1 /mg day-1 ) and drift densities of biomass (mg m-3 ) and abundance (invertebrates m-3 ) for Horsefly River and Eagle Lake study areas. Bold values are significant at α=0.05. * Noninsect data were unavailable for 4 Horsefly streams in 2005 therefore total EPTD data were used for this comparison. Study area Horsefly (n = 6 pairs)  Eagle Lk. (n = 4 pairs)  Response variable  Pre-impact difference (SE)  Post-impact difference (SE)  t  p  Biomass flux Biomass density Abundance flux Abundance density*  208(206) -0.2(0.6) 1015(567) 2.0(1.8)  47(175) -1.4(1.2) 194(416) 1.5(3.3)  2.768 0.818 3.298 6.826  0.039 0.451 0.022 0.831  Biomass flux Biomass density Abundance flux Abundance density  -241(131) -3(17) 160(1040) 27(71)  -76(160) 6(6) 524(1553) 34(24)  -0.695 -0.826 -0.375 -0.147  0.537 0.469 0.732 0.893  21  Horsefly River Study Area  2000  600  1500  Invertebrates 24 hrs  -1  mg invertebrate dry mass 24 hrs  -1  800  400  * B P=0.08  200  1000  *  500  B  B P=0.08  P=0.08  B P=0.08  0  0 pre-impact  post-impact  pre-impact  (a)  (b)  *  Treatment Control C-T difference  10  B P=0.08  a  4 -3  8  Invertebrates m  mg invertebrate dry mass m  -3  6  post-impact  2  0  -2  6  4  2  -4  0  pre-impact  pre-impact  post-impact  (c)  post-impact  (d)  Figure 2.2 Means (+1 S.E.) for daily flux (a, b) and biomass and abundance densities (c, d) of drifting  aquatic invertebrates in treatments and controls pre- (2005) and post-impact (2006) in the Horsefly River study area. The hollow bar (C-T difference) shows the mean of the difference values for Control – Treatment. Bars with an asterisk indicate a significant difference (at α = 0.05) when preimpact was compared to post-impact using a paired t-test (some variables required transformation for statistical comparison but raw data is presented here to ease interpretation). Note that the standard error appears large on the control-treatment differences because this represents the variation among treatment and control pairs. The error associated with the paired t-test is much less due to the nature of the paired comparison but was not suitable for graphical presentation.  22  3500  600  3000  400  2500  -1  800  Invertebrates 24 hrs  mg invertebrate dry mass 24 hrs  -1  Eagle Lake Study Area  200  0  -200  -400  2000  1500  1000  500  -600  0  pre-impact  post-impact  pre-impact  (a)  40  (b)  120  Treatment Control C-T difference  100  -3  20  Invertebrates m  mg invertebrate dry mass m  -3  30  post-impact  10  0  80  60  40  -10  20  -20  -30  0 pre-impact  pre-impact  post-impact  (c)  post-impact  (d)  Figure 2.3 Means (+1 S.E.) for biomass and abundance flux (a, b) and densities (c, d) of drifting  invertebrates in treatments and controls pre- (2005) and post-impact (2006) in the Eagle Lake study area. The hollow bar (C-T difference) shows the mean of the difference values for Control – Treatment. No significant difference (at α = 0.05) were detected when pre-impact was compared to post-impact using paired t-tests.  23  FPOM did not respond to clear-cut harvesting at either the Horsefly River or Eagle Lake study area. Paired comparisons of FPOM concentration and flux before and after impact showed no significant changes as a result of logging (Table 2.3). Interestingly, FPOM concentration remained relatively unchanged at the Horsefly River study area, but a 40% increase in mean FPOM concentration was observed at Eagle Lake. Although similar increases were not seen in controls, this did not prove to be statistically significant when control-treatment differences were compared. Similarly to FPOM, DOC concentration and flux did not show statistically significant changes at either study area. When the differences of control-treatment pairs were compared over a 3 year period (1 year before and 2 years after logging), no significant changes were detected with RMANOVA (Table 2.3). DOC concentration remained strikingly constant in Horsefly while fluctuations in total flux were dependent upon discharge during the sampling times. At Eagle Lake, a 30% increase in DOC concentration was observed in the second year after harvesting (2007) compared to pre-impact levels (2005), but this increase was matched by a 20% increase in control streams. Total flux of DOC varied considerably over the 3 year period at Eagle Lake as the mean rate of DOC export dipped to 395 g 24 hrs -1 from 845 g 24 hrs-1 in 2006 and back up to 1211 g 24 hrs-1 in 2007. This was also matched by similar variation in the controls. The paired design of this study controlled for this change and resulted in no significant effects on DOC in study streams due to logging.  24  Table 2.3 Mean daily flux (g 24 hrs -1 ) and concentrations (mg L-1 ) of FPOM and DOC at Horsefly and Eagle Lake study areas pre- and post-impact with results of paired comparisons for Control-Treatment differences. Means are given with 1 SE in brackets; C = Control, T = Treatment, n.d = no data. Study area  Export variable  Pre-impact 2005 C  Horsefly River  Eagle Lake  Post-impact 2006 T  C  Post-impact 2007 T  C  Statistical comparison  Test statistic  p  T  DOC flux [DOC] FPOM flux [FPOM]  663(201) 2.76(0.66) 237(107) 0.76(0.18)  723(152) 3.24(0.46) 242(66) 1.05(0.20)  758(353) 3.53(0.84) 107(30) 0.91(0.31)  572(258) 3.85(0.54) 227(154) 1.05(0.09)  459(206) 3.36(0.73) n.d n.d  596(278) 4.10(0.70) n.d n.d  RMANOVA RMANOVA Wilcoxon signed-rank Paired t-test  F = 0.267 F = 0.257 Z = -1.363 t = -0.265  0.771 0.779 0.173 0.801  DOC flux [DOC] FPOM flux [FPOM]  219(114) 9.83(0.74) 10.59(3.28) 0.46(0.12)  845(333) 9.81(1.33) 85.23(31.06) 0.93(0.13)  63.51(3.66) 8.58(0.28) 4.20(1.48) 0.56(0.19)  395(55) 10.02(0.83) 51.94(12.73) 1.34(0.39)  745(448) 11.98(0.16) n.d n.d  1211(432) 13.67(1.08) n.d n.d  RMANOVA RMANOVA Paired t-test Paired t-test  F = 0.410 F = 1.662 t = -1.188 t = 0.961  0.688 0.298 0.357 0.438  25  2.4 Discussion 2.4.1  Pre-impact export  Although the export of invertebrates varied greatly among streams from two different study areas, our estimates are comparable to other studies of small, headwater streams in north-western North America. Estimates of total mean invertebrate densities in Horsefly River (3.4 invertebrates m-3 ) concur with summer estimates from coastal BC of 1.5-3.3 invertebrates m-3 ( Leung et al. 2009) and appear to be slightly higher than the 2.4 invertebrates m-3 reported from southeastern Alaska (Wipfli and Gregovich 2002) and 1-2 invertebrates m-3 of north-central BC (Hoover et al. 2007). The extremely high abundance density of 55.4 invertebrates m-3 observed in the Eagle Lake study area was likely due to high numbers of baetid mayflies that were present in some study streams, combined with lower flows. This was evident when we examined flux, as the Eagle Lake streams did not export unusually high numbers of invertebrates in a 24 hour period compared to other study streams. Low stream flows at the time of sampling due to hot weather may have resulted in a concentration effect that would prevent an accurate estimation of drift density (Musselwhite and Wipfli 2004). Moreover, regression analysis of the relationship between total flux and discharge indicated a very weak relationship for streams at Eagle Lake, also suggesting that density estimates should be used with caution in this study area. The mean daily export of FPOM from streams at Horsefly and Eagle Lake (202 and 44 g day -1 respectively) is also consistent with the range estimated by Wipfli and Gregovich (2002) of 1-286 g day-1 for streams in southeastern Alaska. Mean DOC concentration for streams in the Horsefly study area (3.2 mg L-1 ) falls within the 1-4 mg L-1 range of estimates for small streams worldwide (Giller and Malmqvist 1998), but exceeds the mean estimate expected for streams within the ESSF of British Columbia produced by Luider et al. (2006) of approximately 1.4 mg L-1 . Eagle Lake mean DOC concentration was very high at 11.8 mg L-1 compared to the expected mean for the SBS zone of approximately 3.0 mgL-1 (Luider et al. 2006). This was most likely due to the high organic composition of stream substrates in this study area, coupled with low discharge and increased contact time of stream water with the substrate (Webster and Meyer 1997).  26  2.4.2  Post-impact export  Positive responses for abundance and biomass flux were evident in treatment streams at the Horsefly River study area when control-treatment differences were compared. Interestingly, pooled comparisons did not detect any change for the same variables. This situation demonstrates the advantage of using control-treatment pairing because it is more likely to detect subtle changes that occur in opposing directions; in this case slight increases in biomass and abundance flux are observed in treatment streams relative to a decrease in controls. For biomass and abundance densities, the opposite is presented where control-treatment differences did not detect a change, while pooled analysis indicated a positive response (although marginal) in both biomass (p = 0.050) and abundance (p = 0.078). The results of these alternate analyses are indicative that different interpretations of the data are possible depending on the statistical approach. It is also noteworthy that differing trends are apparent between flux and density measures at this study area. Dramatic increases in densities are shown in both treatment and control streams that are not reflected in total flux estimates. It is possible that due to lower flows in the post-impact period, standardizing to discharge created a concentration effect, which is problematic for purposes of comparison. Although there are very few studies that have evaluated the effects of clear-cut logging on invertebrate drift, positive responses are common among benthic community studies. For example, benthic invertebrate abundance was up to 3 times higher (biomass 2 times higher) than controls in clear-cut streams of North Carolina (Stone and Wallace 1998). Similarly, increased biomass and abundance have been observed in harvested streams of the Pacific Northwest (e.g., Hernandez et al. 2005, Moldenke and Ver Linden 2007). Unpublished data from high elevation (ESSF) streams of southern British Columbia have also demonstrated increased abundance density of drifting invertebrates in clear-cut streams (Mackay and Heise 2005). In contrast, a significant decrease in drifting aquatic invertebrates in harvested streams has been observed in the SBS zone of interior BC (Hoover et al. 2007). Evidence from the Horsefly River watershed provides further support that clear-cut harvesting can increase the biomass and abundance of drifting invertebrates. The lack of significant responses at the Eagle Lake study area was largely due to immense variation of invertebrate abundance among study streams. Some streams experienced very high numbers of small-bodied baetid mayflies (of the genus Baetis) and/or chironomids (true flies of the family Chironomidae) that fluctuated dramatically between the pre- and post-impact sampling periods (e.g., stream #608 went from 186 individuals m-3 in 2005 to 14 individuals m-3 in 2006). 27  Baetid mayflies are known to be behavioural drifters and can drift en mass in large numbers in response to environmental cues (Waters 1962, Kohler 1985, James et al. 2008). It is possible that due to hot weather conditions in the pre-impact year, we were seeing increased movement of baetid maylies in some study streams. This phenomenon is also partly responsible for increasing the variance among study streams, making it difficult to detect any statistically significant effects if present. Variation of invertebrate communities and their response to harvesting has been observed by other investigators in the SBS zone of the Cariboo Forest Region. Melody and Richardson (2007) compared benthic invertebrate communities between forested and harvested reaches and found more variation among study streams than between the logged and unlogged reaches. They did identify significant differences between logged and unlogged reaches, but these were often in opposing directions. Although no significant differences were found in response to logging at Eagle Lake, negative trends were observed relative to the Horsefly River study area. This may be due to the type of substrate found in the Eagle Lake study area, as these study streams generally consisted of much finer substratum than Horsefly River streams. Substrate composition has been identified as an important factor in determining the direction and magnitude of benthic invertebrate responses to logging. In second order Appalachian streams, total invertebrate densities increased in rock-face and cobble substrates, and decreased in sandy substrates in response to harvest activities (Gurtz and Wallace 1984). Slope and discharge play a role in determining the substratum of stream, which was reflected in the physical characteristics of our two study areas. There are many site specific factors that could affect invertebrate responses to logging. Medhurst et al. (2010) demonstrated that fluctuations in invertebrate richness and density can occur in different directions depending on eco-region. They suggested that the development of an ecoregional classification system may be appropriate for developing guidelines for predicting the response of macroinvertebate communities to logging. Given the variation in results from differing ecosystems of the Horsefly River and Eagle Lake study areas, this study provides support for this recommendation. I suggest further investigation be dedicated to resolving more site-specific responses of invertebrate drift to the effects of forest harvesting. Mean concentrations of FPOM and DOC remained relatively constant before and after logging took place. It was expected, due to the large influx of organic debris into streams as a result of harvesting, that an initial increase in particulate organic matter 1 year after harvesting would be observed. Although this study lacked high frequency sampling and the capture of hydrologic 28  events, capturing samples during base flow conditions was expected to be representative of constant background transport. Because I was evaluating immediate impacts after harvesting (1 year post-impact for FPOM and 2 years post-impact for DOC) we are not able to detect any longer term trends. Although a 40% increase in mean FPOM concentration was observed at Eagle Lake, high variability among treatment and control streams prevented the detection of any significant effects. The presence of Spruce beetle in the Horsefly River study area was identified as an additional source of background variability that may have prevented the detection of clear responses to harvesting. Although a natural phenomenon, it was a rare event that caused large amounts of spruce needles to fall into streams during the scheduled harvest year. Although I was aware the beetle was present in the watershed, it was not expected to move so quickly into the study area. The influx of organic matter may have influenced stream invertebrates, FPOM and DOM in some of the control streams. Unfortunately, the presence of the beetle was very patchy and difficult to quantify in retrospect. Theoretically, this natural phenomenon may actually be mimicking the immediate effects of clear-cut harvesting, as streams are often laden with organic material (namely needles and branches from the de-limbing process) during harvesting. We observed substantial deposition of fine organic debris in all but 2 of the treatment streams in the Horsefly study area. These 2 streams were protected by natural topography that likely prevented crossyarding or de-limbing in close proximity to the stream banks. It is possible that without the confounding effects of the beetle, we may in fact be seeing an increase in biomass and abundance in response to logging that would not be observed in nearby controls in the absence of the beetle.  2.5 Summary It is evident that high elevation streams in interior British Columbia can be highly productive in terms of providing a potential source of invertebrates and organic matter to downstream food webs. In response to clear-cut harvesting, significant increases in the daily flux of biomass and abundance of drifting invertebrates were observed in 1 of 2 study areas (Horsefly River). No significant changes in invertebrate drift variables were detected in the Eagle Lake study area, likely due to the large natural variability revealed in this ecosystem type. Differences in responses between wet and dry ecosystems further suggest that potential effects due to harvesting on streams may be ecosystem dependent. Fluctuations in FPOM and DOM did not appear to be  29  outside the natural variation inherent in these headwater systems, as no significant changes were evident over the monitoring period. Overall, no negative impacts were observed in the short-term as a result of clear-cut harvesting. Due to potentially confounding effects of spruce beetle in the Horsefly River study area, clear responses to logging were difficult to establish, but likely hindered detection of stronger positive responses of invertebrate and organic matter variables. It is important to note this study examined short-term effects of logging on streams, therefore further research is required to investigate both seasonal and long-term trends. I anticipate these data will assist riparian managers in assessing the effectiveness of best management practices in British Columbia, and provide useful information for developing effective management guidelines in the future.  30  3  Effects of Clear-cut Logging on Invertebrate Drift Community Composition in Headwater Streams of Interior British Columbia  3.1 Overview Forestry is the most influential industry on the landscape of boreal forests and its potential to affect stream water quality and biological communities is substantial (Richardson et al. 2005). Currently, non-fish-bearing headwater streams in British Columbia (BC), Canada receive very little protection under provincial legislation, and rely on the application of practical, cost-effective measures (best management practices (BMP)) to maintain proper functioning condition (FRPA 2004). BMP allow 100% removal of merchantable timber from non-fish-bearing streams less than 3 m wide while retaining non-merchantable deciduous trees and shrubs within 5 m of the stream edge (FRPA 2004). Because headwater streams can make up the majority of total stream area in a watershed (Gomi et al. 2002), and are relatively unprotected from the physical effects of logging, the cumulative effects on higher order streams may become very large. The export of invertebrates and organic matter is known to support trophic linkages in stream food webs (Gomi et al. 2002, Wipfli et al. 2007, Wipfli & Baxter 2010), and changes to this transport as a result of landscape disturbance may have consequences to higher trophic levels further down in the watershed. Therefore, in order to protect the integrity of downstream reaches, we must understand the potential consequences that forest practices can have on stream food webs, in order to develop effective riparian management strategies for headwater streams. There is a large body of literature documenting the physical and biological changes that can occur in streams as a result of logging. Removing the forest canopy can bring about changes in aquatic invertebrate communities (e.g., Stone & Wallace 1998, Price et al. 2003, Hernandez et al. 2005, Jackson et al. 2007, Moldenke & Ver Linden 2007), water temperature (e.g., Gravelle & Link 2007), organic matter dynamics (e.g., Bilby & Bisson 1992, Meyer et al. 1998, Webster et al. 1999, Kiffney et al. 2000, Richardson et al. 2005), and even channel physical structure (e.g., Jackson et al. 2001). The responses of aquatic invertebrates to clear-cut logging are highly variable and often contradictory (Melody & Richardson 2007). Increased productivity has been commonly demonstrated (eg., Stone & Wallace 1998, Hernandez et al. 2005, Nislow & Lowe 2006, Jackson et al. 2007) largely due to increases in autochthonous (within stream) production, while others have shown little to no change (eg., Gravelle et al. 2009). It is evident from the literature that the response of macroinvertebrate communities to logging is often unpredictable, and may depend on many local factors, especially climate (Binckley et al. 2010). 31  The effects of clear-cut harvesting on invertebrate drift composition are relatively unknown. Although invertebrate drift can be correlated to benthic invertebrate communities (James et al. 2008), empirical evidence is required to estimate the effects of harvesting on invertebrate drift. Simulation of deforestation, which involves reducing the inputs of terrestrial detritus to streams, has demonstrated reductions of benthic and drifting invertebrates (Siler et al. 2001). The effects of various types of riparian reserve strips on invertebrate drift have been studied in central BC (Hoover et al. 2007). In treatments where 100% of the riparian vegetation was removed, significant decreases in the density and flux of drifting aquatic invertebrates were observed, while the relative density of terrestrial invertebrates in the drift increased (Hoover et al. 2007). Due to the intimate association with riparian vegetation that is typical of headwaters, terrestrial invertebrates (or allochthonous drift) can form an important part of the drift, especially during summer (Baxter et al. 2005). It is important to quantify the impacts that logging may have on these subsidies because terrestrial invertebrates are considered a high quality resource, and have been shown to make up a large portion of the annual diet for drift feeding salmonids (Kawaguchi and Nakano 2001, Baxter et al. 2005). Similarly, litter exclusion studies in headwater streams have demonstrated reductions of benthic and drifting invertebrates by mimicking the effects of deforestation (Siler et al. 2001). Alternatively, increased export of invertebrates and detritus have been found to occur in logged streams in regions of the Pacific Northwest (Piccolo & Wipfli 2002, Binckley et al. 2010). Moreover, identified differences among streams within differing eco-regions suggest that the response of invertebrate drift to forest harvesting may be dependent on region or even site-specific conditions (Binckley et al. 2010). The purpose of this study was to assess the immediate effects of clear-cut harvesting on invertebrate drift composition from high elevation headwater streams in the interior of BC. This study was part of a larger investigation on the effects of harvesting on total organic matter export (results for which were presented in Chapter 2). Since changes to invertebrate drift composition could ultimately influence higher trophic levels downstream (Davies and Nelson, 1994, Baxter et.al. 2005), the intent was to identify any changes in the drifting community that may have occurred as a result of clear-cut harvesting. Although community analysis of drift is not conventional, it has been demonstrated in the literature that drift can be a good, but perhaps broad, representation of benthic communities (e.g., Siler et al. 2001, James et al. 2008). If a good correlation between benthic and drift communities could be shown, then we could assess potential impacts of harvesting using assessment metrics typically used for the benthos.  32  To address the research questions, I applied a spatially (multiple locations) and temporally replicated Before-After-Control-Impact (BACI) design across two watersheds. By examining potential impact trajectories within ecologically different watersheds, my goal was to be able to extrapolate results to similar ecosystems. Drifting invertebrates were collected from 22 streams 1 year prior to, and from 17 streams 1 year after logging took place. After sorting and identifying drift samples to genus level, a variety of invertebrate metrics were applied to measure the response of drift composition to clear-cut logging.  3.2 Methods 3.2.1  Study areas  This study was conducted in two watersheds approximately 60 km apart within the Cariboo Forest Region in the southern interior of British Columbia, Canada (Figure 3.1). With the assistance of local forest licensees, Tolko Industries for the Horsefly region and West Fraser Mills for the Eagle Lake region, eligible streams were selected that were proposed for clear-cut logging treatment in 2005/2006. Streams selected for this study shared similar physical characteristics within their catchment areas such as width (<3 m), slope, aspect, discharge and substrate, and were confirmed fishless. Undisturbed control streams were also selected in close proximity to each treatment stream. Originally, 12 cut-block treatment and 10 control streams were sampled across the two watersheds in the pre-impact condition in 2005. Due to changes in the logging schedule, only 10 treatment and 7 control streams were sampled post-impact. Two of the anticipated treatment streams were only partially logged and 3 controls were omitted because they were compromised by harvesting activity. The presence of Mountain pine beetle in the Eagle lake watershed and Spruce beetle in the Horsefly River watershed created challenging conditions to adhere to a strict logging plan, as licensees were forced to move to areas of intensive beetle activity.  33  Horsefly River Study Area  Legend Clear-cut treatment Omitted treatment Control Omitted control Road (un-paved) Park  Eagle Lake Study Area  Figure 3.1 Map of study stream locations. The Horsefly River and Eagle Lake watersheds are located in the Cariboo Forest Region in south-central British Columbia. All streams sampled in preimpact condition in 2005 are shown, with hollow symbols indicating streams omitted in 2006. (Map source: Natural Resource Canada 2004)  3.2.2  Site descriptions  The Horsefly River study area is situated within the Engelmann-spruce Sub-alpine fir (ESSF) biogeoclimatic zone, and the location of study streams ranged from 1300 to 1600 m in elevation. Located in the foothills of the Cariboo Mountains, the mean annual precipitation for this area is greater than 1000 mm with snow-free periods typically lasting from mid-June to September (Steen & Coupé 1997). The topography is mountainous with relatively steep slopes (range of 17 – 54%), with discharges of study streams varying from 0.4 to 6 Ls-1 in early summer. The surrounding vegetation of the Horsefly study sites was typical of an ESSF Wet Cool subzone (Steen & Coupé 1997), characterized by mature coniferous stands of sub-alpine fir (Abies lasiocarpa) and Engelmann spruce (Picea engelmannii), with the understory dominated by various components of alder (Alnus sp.), thimbleberry (Rubus parviflorus), devils club (Oplopanax horridus), white flowered rhododendron (Rhododendron albiflorum), lady fern (Athyrium filix-femina), sitka valerian (Valeriana sitchensis), foamflower (Tiarella trifoliata), and five-leaved bramble (Rubus pedatus). Spruce beetle (Dendroctonus rufipennis) was also present in the watershed and had begun to infect Engelmann spruce trees around study streams in 2005.  34  The Eagle Lake study area is located in the Sub-boreal Spruce (SBS) zone, with study sites ranging from 1100 to 1400 m in elevation. This ecosystem type is drier than the ESSF with the mean annual precipitation ranging from 480 to 720 mm (Steen & Coupé 1997). The rolling topography consisted of less steep terrain than the Horsefly River study area (range of 4 – 28% slope), with study stream discharges ranging from 0.2 to 3 L s -1 . The dominant forest cover surrounding the Eagle Lake study sites was lodgepole pine (Pinus contorta) with minor components of Engelmann spruce and sub-alpine fir. Understory vegetation comprised alder, thimbleberry, devils club, lady fern, horsetail (Equisetum sp.) bunchberry (Cornus canadensis) and five-leaved bramble. 3.2.3  Study design  This study followed a BACI (Before – After – Control - Impact) paired design with both spatial and temporal replication (Stewart-Oaten et al. 1986, Underwood 1994). This approach is designed to focus on changes due to impact relative to a reference (control) area. Treatment streams were paired with a proximal control stream and sampled simultaneously before and after clear-cut logging impact. Data analyzed are the differences between control-treatment stream pairs, compared before and after logging. Control locations were not randomly selected but were chosen to share similar physical characteristics such as width, slope, aspect and discharge with treatment streams (as recommended by Underwood 1994). In most cases control streams were located within 1 km of treatment streams, and were at minimum 50 m away from the associated cut-block boundary. Control stream sampling locations were established at the same elevation if possible and were sampled during the same time period as treatment streams. Sampling locations for treatment streams were 200 m downstream of the upper cut-block boundary to equalize the length of stream exposed to harvest treatment (road intersections were avoided to prevent confounding effects). Clear-cut logging treatment consisted of complete removal of riparian vegetation in both study areas. In all but two streams, trees were yarded away from the stream channel but most streams experienced considerable deposition of branches and needles. Drifting invertebrates were measured in ten treatment and seven control streams during stable flow conditions prior to logging (pre-impact) in summer 2005, and again the following year after logging took place (post-impact) in 2006. Exceptionally, one replicate and control pair in the Eagle lake study area was sampled in the post-impact condition in 2007 because of logging postponement. Due to the labour intensive nature of sample sorting and identification, drifting 35  invertebrates were sampled once before and once after logging treatment (see Appendix I for specific sampling dates). 3.2.4  Physical/chemical characteristics  Physical and chemical site characteristics were recorded at each study stream, including discharge, wetted channel width, slope, aspect, and substrate composition. Precipitation was also monitored during the sampling period (to prevent sampling during a spate event) as well as pH, conductivity and temperature. To determine stream discharge, a section of stove pipe was installed at a natural drop in the stream channel to funnel nearly 100% of the stream flow through a makeshift flume (see Appendix II for photos). Discharge was then measured volumetrically by recording the time it took to fill a container of known volume (Gore 1996). Discharge (L s -1 ) was measured at the beginning and end of a 24 hour period to estimate a daily average. 3.2.5  Macroinvertebrate drift  Drifting invertebrates were sampled over a 24 hour period in triplicate (72 hours in total) to achieve an estimate of daily export (flux). Taxon-specific behaviour and diel patterns can cause fluctuations in the drift composition during the course of a day (Brittain & Eikeland 1988). Sampling over 72 hours was undertaken to reduce this variability and include both diurnal and nocturnal drifters. To collect drifting invertebrates, a 250 µm mesh drift net was installed under the stovepipe flume so that the entire stream flow was directed into the net. Backflow or escapes at the net entrance were minimized by allowing the stream flow to fall into the net (see Appendix II for photos of drift sampling set-up). Benthic kick samples (from riffle locations) were also collected at the end of each drift sampling period to provide a qualitative comparison between the drifting and benthic invertebrate communities (~0.25 m2 kick sample per study stream). The presence/absence of invertebrate taxa in drift and benthic kick samples were determined in a subset of 7 study streams from both Eagle Lake and Horsefly River study areas. The subset was made up of treatment and control streams that represented the range of discharges found among study streams. Collected organisms and debris were transferred to Whirl-pak bags and preserved in the field with 70% ethanol for later enumeration, identification and measurement. In the lab, invertebrates were removed from sample debris by sorting under 4 x magnification. As the objective of this 36  project was to focus on macroinvertebrates as fish food subsidies, the micro-invertebrate component (e.g., copepods) that was not easily visible at 4 x magnification was ignored. This micro-component, although not identified, was included in the estimate of fine particulate organic matter that was summarized in Chapter 2. If the estimated sorting time of each drift sample appeared to be greater than 12 hours, samples were separated into coarse (> 2 mm) and fine fractions (250 µm – 2 mm) by rinsing through wire mesh sieves. Coarse fractions were sorted entirely while the fine fractions were sub-sampled prior to sorting. Due to the minute particle size of the fine fraction, we used a volumetric subsampling approach using a Folsom plankton splitter based on methods proposed by Glozier et al. (2002). After sorting, the remaining debris from all samples was returned to bags and every tenth sample was re-sorted for quality control purposes (as per recommendations from Glozier et al. 2002). Sorted invertebrates were enumerated and identified to family or genus using taxonomic keys (Merritt and Cummins 1996, Stewart and Oswood 2006). Mayflies (Ephemeroptera), stoneflies (Plecoptera), and caddisflies (Trichoptera) were identified to genus while the true flies (Diptera) were identified to family level only. Total body lengths of Ephemeroptera, Plecoptera, Trichoptera and Diptera (herein referred to as E,P,T, and D respectively) were measured to calculate dry-mass based on length-weight regressions from the literature (Sample et al. 1993, Burgherr and Meyer 1997, Benke et al. 1999). All other insect and non-insect invertebrates (less dominant groups) were identified to class or order only to determine aquatic or terrestrial origins. Emergent, winged adults of aquatic insect taxa were classified as terrestrial in origin. Dry-mass of these groups was determined by desiccating and weighing. Invertebrate drift was expressed as both daily flux and density variables . Once the samples were enumerated and measured, the total number of invertebrates in the 24 hour drift sample was used as the estimate of drift flux and expressed as invertebrates 24 hrs -1 . The daily average stream discharge was then used to standardize the 24 hour drift to biomass and abundance density measurements (mg of dry mass m-3 and invertebrates m-3 respectively). Because of the large spectrum of factors that can influence drift (Brittain and Eikeland 1988), it was important to establish a relationship with the amount of individuals in the drift and stream discharge. Therefore, before proceeding with standardization, the relationship between stream discharge and total flux of invertebrates was examined for each study area (see Appendix V).  37  Biotic metrics used to evaluate community composition of the drift included abundance/biomass flux and abundance/biomass density of the orders E, P, T, D, and terrestrial invertebrates (a combination of orders such as Hymenoptera, Orthoptera, Coleoptera (refer to Appendix IV for classification of terrestrial invertebrates), EPT abundance flux (E+P+T), %EPT (ratio of EPT abundance flux/total aquatic invertebrate abundance flux) and EPT/D (ratio of EPT abundance flux/D abundance flux). Richness and diversity metrics were applied in the form of EPTD genera richness, Shannon’s index as a measure of proportional diversity (Shannon and Weaver 1949) and Simpson’s index as a measure of equitability or evenness (Simpson 1949). Other non-insect taxa were excluded from the richness and diversity metrics due to their minor presence in the drift and also due to missing abundance data from four Horsefly streams in 2005. Additionally, dipterans were only identified to the family level so one genus was accounted for in each family, likely resulting in an overall underestimate of total taxa. Immature taxa, that were not identifiable to genus because of their small size, were common in the drift especially for heptageniid and baetid mayflies, and nemourid stoneflies. In order to prevent underestimation of abundance for these taxa for evenness and proportional abundance calculations within the diversity metrics, family level counts for Family Heptageniidae, Baetidae and Nemouridae were used. In most cases, there was only one genus representative for each family, but in streams that had two genera within Nemouridae or Heptageniidae, this would have resulted in a slight underestimation of genera richness. This was considered an acceptable tradeoff to include the large amount of immature larvae. Although infrequent taxa are sometimes removed from benthic diversity measures (e.g., Richards & Minshall 1992) I felt this would not accurately represent the many infrequent taxa that were present in the drift. Richardson (2008) also expressed concern regarding the exclusion of infrequent taxa from analyses, and that it may result in gross underestimation of biodiversity. As a compromise to eliminating all infrequent taxa, I excluded any taxon that was ˂ 1 individual 24 hrs-1 within a stream. Due to the difficulty in assigning functional feeding groups at the genus level (Merritt et al. 2008), a full functional feeding group analysis was not attempted. Instead, I looked at specific genera that could be classified as purely shredders and looked for changes in the ratio of these shredders to total abundance flux (% shredders). This functional composition metric was preferred as it known to be sensitive to changes in the riparian zone as well as to additions of organic matter in streams (Resh & Jackson 1993, Stone & Wallace 1998).  38  3.2.6  Statistical analyses  The null hypothesis that invertebrate drift response variables did not differ before and after clearcut harvesting (at α = 0.05) was examined. As the study design was based on repeated measures at the exact location before and one year after impact, I used paired t-tests (or non-parametric equivalent) to compare mean differences between clear-cut treatment and control streams before and after impact (Stewart-Oaten 1986). Both the mean differences between control-treatment pairs, as well as pooled controls and pooled treatments were compared. To avoid inflation of error estimates, Horsefly River and Eagle Lake study areas were analyzed separately due to biological/physical differences and inconsistency in sampling times. Non-synchronized sampling was required due to difficult access and time required to complete 72 hour drifts at each location. All data were analyzed using SPSS (version 17.0); Shapiro-Wilks and Levene’s test were used to test assumptions of normality and homoscedasticity respectively. If assumptions were not met, transformations were applied as necessary. Typically, lnx or log10 (x + c) for difference data were applied with the constant c chosen to anchor the minimum value at 1.0 (Osborne 2002). For ease of graphical interpretation, non-transformed data are presented in bar graphs illustrating the change in means before and after clear-cut harvesting. In order to express and compare invertebrate drift in terms of abundance density (individuals m-3 ), simple linear regression with ANOVA was used to examine the relationship between invertebrate drift flux and stream discharge.  3.3 Results 3.3.1  Physical/chemical  At the Horsefly River study area, the temperature of study streams ranged from 7 to 9 °C at the time of sampling and all streams had a neutral pH (mean = 7.2) and consistently low specific conductance (mean = 70 µS cm-1 ). Stream temperatures at the Eagle Lake study area ranged from 8-12 °C and mean conductance was approximately 112 µS cm-1 , also with a neutral pH. Although discharges varied among study streams, differences between treatments and controls within each study area were not significant (Horsefly River; t = -0.007, p = 0.995, Eagle Lake; t = -2.117, p = 0.088). Lower discharges were observed in 2006 (post-impact) compared to 2005 (pre-impact) in all study streams except for Horsefly River streams 507 and 508. Because chemical variables were solitary measurements, statistical comparisons over the years were not 39  performed; however, these variables remained relatively constant over time and showed no major fluctuations in response to logging (see Appendix III for detailed physical and chemical information). 3.3.2  Drift-benthos comparison  In the subset of seven streams that were compared for presence/absence of invertebrate taxa, drift samples accurately represented taxa present in the benthos. In all streams, more taxa were present in the drift than in the benthos (as much as 85% more in Horsefly streams and 50% more in Eagle Lake study streams) (Table 3.1). Surprisingly, non-insect taxa such as worms and gastropods that are more typical of the stream benthos were also present in the drift. This provided qualitative evidence that proceeding with the use of relative abundance measures of taxonomic groups, and applying richness and diversity metrics for evaluating the impacts of forest harvesting was appropriate because the drift appeared to be a good representation of stream community composition.  40  Table 3.1 Summary of taxa for benthic kick and drift samples for a subset of streams within the Horsefly  River and Eagle Lake study areas. (• ) indicates presence in benthos (x) indicates presence in drift. Phylum or Class Oligochaeta Arachnida Insecta Insecta Insecta Insecta Insecta Insecta Insecta Insecta Insecta Insecta Insecta Insecta Insecta Insecta Insecta Insecta Insecta Insecta Insecta Insecta Insecta Insecta Insecta Insecta Insecta Insecta Insecta Insecta Insecta Insecta Insecta Insecta Insecta Insecta Insecta Insecta Insecta Insecta Insecta Insecta Insecta Insecta Insecta Insecta Insecta Insecta Ostracoda Gastropoda Nematoda Nematomorpha Platyhelminthes  O rder  Family  Acarina Coleoptera Diptera Diptera Diptera Diptera Diptera Diptera Diptera Ephemeroptera Ephemeroptera Ephemeroptera Ephemeroptera Ephemeroptera Ephemeroptera Ephemeroptera Ephemeroptera Ephemeroptera Plecoptera Plecoptera Plecoptera Plecoptera Plecoptera Plecoptera Plecoptera Plecoptera Plecoptera Plecoptera Plecoptera Plecoptera T richoptera T richoptera T richoptera T richoptera T richoptera T richoptera T richoptera T richoptera T richoptera T richoptera T richoptera T richoptera T richoptera T richoptera T richoptera T richoptera T richoptera  unidentifed Ceratopogonidae Chironomidae Culicidae Dixidae Psychodidae Simuliidae T ipulidae Ameletidae Baetidae Ephemerellidae Ephemerellidae Heptageniidae Heptageniidae Heptageniidae Heptageniidae Heptageniidae Chloroperlidae Chloroperlidae Leuctridae Leuctridae Nemouridae Nemouridae Nemouridae Peltoperlidae Perlodidae Perlodidae Perlodidae Perlodidae Apataniidae Apataniidae Brachycentridae Glosssomatidae Goeridae Hydropsychidae Lepidostomatidae Limnephilidae Limnephilidae Limnephilidae Limnephilidae Limnephilidae Limnephilidae Limnephilidae Philopotamidae Rhyacophilidae Uenoidae  Genus  Horsefly River ID 502 504 507 508 • x x • x x x x x x • x • x • x • x • x  • • Ameletus Baetis Attenella Drunella immature Cinygma Cinygmula Epeorus Rhithrogena Haploperla Plumiperla Despaxia Paraleuctra Malenka Visoka Zapada Yoraperla Isoperla Megarcys Perlinodes Rickera Allomyia Moselyana Micrasema Glossosoma Lepania Parapsyche Lepidostoma Chyranda Cryptochia Desmona Ecclisomyia Eocosmoecus Homophylax Psychoglypha Wormaldia Rhyacophila Neothremma  •  • • •  x  x x x x  • •  x x x x  • • • •  x x x x  •  • • • •  x x x x x x x  •  •  x x  • •  •  x  •  x  •  •  x  • • •  x x x x  x  •  x  x x x  • •  x x x  x x  •  x x x  •  •  • • •  x  • • •  • x x  •  x x x x  •  x x  •  x  x x  •  x  x x x  • • •  x x x  • • •  x x x  •  x x x  • • •  x x x  •  •  x  x  •  •  x  •  x  • • •  •  x x x x  x  x x • •  •  x  • •  x x  • x x  x x x x x  x x x x  ID 605 • x •  x  x  • •  41  x x x x x x  Eagle Lake 602 603 • • x • x x x x  x x  • • •  x x x x x  x x  • •  x  •  x •  x  x  x  x  x  x  x x  x  x x x  •  x x x  •  •  x x x  x x  •  x  •  x x x x x  •  x x x x  x  •  x x  3.3.3  Drift composition  In 2005 prior to impact, Ephemeroptera, Plecoptera, Trichoptera, and Diptera (EPTD) made up on average 90% of the drift in streams at both Horsefly River and Eagle Lake study areas (invertebrate taxa identified at both study areas are provided in Appendix IV). Aquatic insects dominated the drift in both biomass and abundance density and flux before and after logging impact. Ephemeroptera and Diptera were the most abundant in the drift, together making up 68% of total abundance densities at Horsefly River, and 85% at Eagle Lake. This was due to large numbers of small baetid mayflies (family Baetidae) and chironomids (family Chironomidae) that dominated across all sites (Figures 3.2, 3.3). At Horsefly River, the dominant taxon in terms of total biomass (both flux and density) was Trichoptera. This was due to the presence of many large-bodied cased caddisflies (e.g., Limnephilidae) that contributed greatly to total biomass. This influence on biomass is exemplified when we compare biomass proportions to abundance proportions (for both density and flux measures) as Trichoptera made up a minor component of the drift in terms of abundance (Figure 3.2). Larger caddisflies were generally not as frequent at Eagle Lake which may have been a result of emergence timing; however, it is evident in Figure 3.3 that they were also a minor component in drift abundance but more influential on drift biomass. The smallest portion of the drift in both study areas comprised the non-insect (represented mainly by phyla Nematoda, Nematomorpha, Oligochaeta, and class Ostracoda) and terrestrial invertebrate components. The non-insect proportion was often less than 1% of total biomass and often contained numerous tiny ostracods that could potentially bias total abundance estimates. For this reason, it was excluded from the community analyses. Terrestrial invertebrate composition ranged from 0-9% of total biomass flux and 3-6% of abundance flux at Horsefly River, while Eagle Lake estimates ranged from 0-21% for biomass flux and 0.3 – 12% of abundance flux. In the post-impact condition (2006), statistically significant changes to the drifting community (at the order level) were detected at the Horsefly River study area (Figure 3.4). Paired t-tests of control-treatment differences indicated significant changes in biomass flux for Ephemeroptera (t = -2.59, p = 0.049), Trichoptera (t =-3.74, p = 0.013) and Diptera (t = -3.72, p = 0.014), abundance flux of Diptera (t = -2.70, p = 0.043), and biomass density of Plecoptera (Z = -1.99, p = .046). Interestingly, pooled analysis of flux variables indicated only marginal increases in biomass and abundance of Ephemeroptera in control streams (t = -3.28, p = 0.046; t = -3.14, p = 0.052 respectively) with no changes in treatment streams. Additionally, pooled comparison of 42  density variables in treatment streams show strong increases in biomass density of Trichoptera (t = -4.66, p = 0.006) and Diptera (t = -3.01, p = 0.030) that were not revealed by analysis of control-treatment differences. No significant changes were detected for EPTD with paired comparisons of control-treatment differences at the Eagle Lake study area (Figure 3.5). Pooled analysis did indicate a significant decrease in Diptera abundance flux and density in control streams (flux; t = 5.077, p = 0.037, density; t = 5.03, p = 0.037) but was matched by a similar (although marginal) decrease in Diptera biomass flux in treatment streams (t = 2.88, p = 0.063). It is noteworthy that abundance flux and density of Ephemeroptera dropped dramatically in treatment streams while increases were observed in controls. Immense variation in abundance of baetid mayflies at this study area may have prevented the detection of any significant response. The terrestrial component of the drift showed no response to logging at the Horsefly River study area, but may have increased slightly in Eagle Lake treatment streams. Pooled analysis did reveal significant increase of abundance density of terrestrial invertebrates in treatment streams (t = 3.87, p = 0.031); however, this was matched by a weak increase in control streams (t = -3.25, p = 0.083). Paired difference analysis likely controlled for this change as no significant differences were detected with this approach (Figure 3.5). Total abundance flux of combined EPT (E+P+T) remained remarkably constant at the Horsefly River study area after logging treatment (mean of 317 individuals in 2005 to 325 individuals in 2006). EPT flux at the Eagle Lake study area decreased relative to controls (mean of 1394 in 2005 to 740 individuals in 2006) but was not statistically significant. Proportional composition of EPT (%EPT) was more responsive to the effects of harvesting at both study areas (Table 3.2). At Horsefly River, this metric revealed significant change when control-treatment differences (p = 0.049), as well as pooled treatments (p = 0.007) were compared. Pooled analysis of treatment streams at Horsefly River also revealed a decrease in the proportional metric EPT/D (p = 0.006), which indicated a significant increase in the number of dipterans relative to EPT in the postharvest drift. At Eagle Lake, marginally significant changes were observed with %EPT, which was a result of increased proportions of EPT in control streams that were not seen in treatments streams (control-treatment p = 0.073; pooled control p = 0.058). Given the variability at this study area, this is likely indicative of a meaningful negative response (which would echo the trend observed at Horsefly River).  43  No changes were detected in proportions of shredders relative to total abundance flux (% shredders) at either study area. Surprisingly, this metric remained quite constant both in control and treatment streams over the 2 year study period.  44  Horsefly River Study Area  Invertebrate dry mass (mg 24 hrs )  500  1400  -1  1200  Invertebrates 24 hrs  -1  400  300  200  1000  800  600  400  100 200  0  0  control (05)  control (06)  cut-block (05)  cut-block (06)  control (05)  control (06)  5  7  Terr E P T D  6  -3  5  Invertebrates m  -3  Invertebrate dry mass (mg m )  cut-block (06)  (b)  (a)  4  cut-block (05)  3  2  4  3  2  1 1  0  0  control (05)  control (06)  cut-block (05)  cut-block (06)  control (05)  control (06)  cut-block (05)  cut-block (06)  Treatment (year)  (c)  (d)  Figure 3.2 Relative biomass and abundance flux (a,b) and densities (c,d) of dominant invertebrate groups in the Horsefly River study area. Stacked bars represent category means in control streams (n= 4) and treatment stream (n = 7) in the pre-impact year of 2005 and post-impact year of 2006 (Terr = terrestrial insects of combined orders, E = Ephemeroptera, P = Plecoptera, T = Trichoptera, and D = Diptera).  45  Eagle Lake Study Area  3000  2500 -1  500  Invertebrates 24 hrs  -1  Invertebrate dry mass (mg 24 hrs )  600  400  300  200  2000  1500  1000  500  100  0  0 control (05)  control (06)  cut-block (05)  cut-block (06)  control (05)  control (06)  18  70  Terr E P T D  60  50 -3  12  Invertebrates m  -3  Invertebrate dry mass (mg m )  14  cut-block (06)  (b)  (a)  16  cut-block (05)  10 8 6  40  30  20  4 10  2 0  0  control (05)  control (06)  cut-block (05)  cut-block (06)  (c)  control (05)  control (06)  cut-block (05)  cut-block (06)  (d)  Figure 3.3 Relative biomass and abundance flux (a,b) and densities (c,d) of dominant invertebrate  groups in the Eagle Lake study area. Stacked bars represent category means in control streams (n= 3) and treatment stream (n = 4) in the pre-impact year of 2005 and post-impact year of 2006 (Terr = terrestrial insects of combined orders, E = Ephemeroptera, P = Plecoptera, T = Trichoptera, and D = Diptera).  46  Horsefly River Study Area  *  150  *  1200  *  *  1000 800 -1  100  Invertebrates 24 hrs  -1  Invertebrate dry mass (mg 24 hrs )  200  50 0 -50  600 400 200  -100  0  -150  -200 -400  -200 E  P  T  D  E  Terr  P  Invertebrate category  T  (a)  C-T difference 2005 C-T difference 2006  4  *  -3  Invertebrate dry mass (mg m )  Terr  (b)  2  1  D  Invertebrate category  3  Invertebrates m  -3  0  -1  -2  -3  2  1  0  -1  -4  -2  E  P  T  D  Terr  E  P  T  D  Invertebrate category  Invertebrate category  (c)  (d)  Figure 3.4 Mean difference values for Control – Treatment (+1 S.E.) for biomass and abundance flux  (a, b) and densities (c ,d) of drifting aquatic and terrestrial invertebrate groups in treatments and controls pre- (2005) and post-impact (2006) in the Horsefly River study area (E = Ephemeroptera, P = Plecoptera, T = Trichoptera, D = Diptera, and Terr = combined orders of terrestrial invertebrates). Bars with an asterisk indicate a significant difference (at α = 0.05) when pre-impact differences were compared to post-impact (some variables required transformation for statistical comparison but raw data is presented here to ease interpretation).  47  Terr  Eagle Lake Study Area  300  1500  100 -1  1000  Invertebrates 24 hrs  -1  Invertebrate dry mass (mg 24 hrs )  2000  200  0 -100 -200 -300  500 0 -500 -1000  -400  -1500  -500  -2000  E  P  T  D  Terr  E  P  Invertebrate category  T  D  Terr  Invertebrate category  (a)  (b)  C-T difference 2005 C-T difference 2006  100  20 -3  Invertebrate dry mass (mg m )  80 60  Invertebrates m  -3  10  0  -10  40 20 0 -20 -40  -20  -60  -30  -80  E  P  T  D  Terr  E  P  T  D  Invertebrate category  Invertebrate category  (c)  (d)  Figure 3.5 Bars represent the mean of the difference values for Control – Treatment (+1 S.E.) for  biomass and abundance flux (a, b) and densities (c ,d) of drifting aquatic and terrestrial invertebrate groups in treatments and controls pre- (2005) and post-impact (2006) in the Eagle Lake study area (E = Ephemeroptera, P = Plecoptera, T = Trichoptera, D = Diptera, and Terr = combined orders of terrestrial invertebrates). No significant changes were found (at α = 0.05) when pre-impact C-I differences were compared to post-impact (Some variables required transformation for statistical comparison but raw data is presented here to ease interpretation).  48  Terr  Table 3.2 Mean values of invertebrate metrics measured at Horsefly River and Eagle Lake study areas pre- and post-impact, with results of paired  comparisons for control-treatment differences and pooled comparisons. Means are given with 1 SE in brackets; C = Control, T = Treatment. Significant (and marginally significant) p values are in bold. Study area  Horsefly River  Eagle Lake  Invertebrate metric  Pre-impact 2005  Post-impact 2006  C-T test statistic  C-T p  Pooled C test statistic  Pooled C p  Pooled T test statistic  Pooled T p  C  T  C  T  EPTD richness EPT flux %EPT EPT/D %Shredders Shannon’s index Simpson’s index  17.8(3.90) 292(233) 43.1(6.5) 1.57(0.82) 12.0(3.8) 1.35(0.30) 0.57(0.14)  15.5(1.6) 317(194) 42.4(9.8) 1.88(1.04) 8.6(2.4) 1.28(0.19) 0.54(0.08)  18.0(3.4) 388(201) 46.9(13.3) 5.72(4.23) 10.3(5.9) 1.33(0.12) 0.60(0.05)  14.5(1.9) 325(270) 29.9(9.5) 1.10(0.74) 10.1(3.0) 1.03(0.17) 0.44(0.08)  t = -0.20 t = -0.76 t = -2.59 Z = -1.57 t = 0.39 t = -1.01 t = -1.25  0.853 0.480 0.049 0.116 0.707 0.357 0.268  t = -0.13 Z = -1.46 t = -0.46 t = -1.00 Z = -0.54 t = 0.10 t = -0.27  0.903 0.144 0.679 0.391 0.593 0.930 0.802  t = 0.64 Z = -0.31 t = 4.44 t = 4.54 Z = 0.52 t = 1.43 t = 1.38  0.552 0.753 0.007 0.006 0.600 0.212 0.226  EPTD richness EPT flux %EPT EPT/D %Shredders Shannon’s index Simpson’s index  13.3(2.9) 624(269) 30.1(6.8) 0.58(0.07) 6.0(3.6) 0.87(0.13) 0.40(0.09)  14.3(1.6) 1394(684) 58.0(6.7) 1.72(0.50) 8.5(6.0) 1.39(0.15) 0.65(0.05)  14.7(0.9) 690(497) 44.1(9.5) 1.25(0.61) 6.2(0.4) 1.60(0.11) 0.72(.04)  15.5(1.3) 740(509) 39.9(14.5) 2.19(0.98) 5.7(1.4) 1.60(0.18) 0.70(0.05)  Z = -3.65 t = -1.02 t = -2.72 t = -0.18 t = -0.35 t = -3.50 t = -6.68  0.715 0.385 0.073 0.871 0.750 0.039 0.007  t =-0.46 t = -0.29 t =-3.99 t = -1.71 t = -0.07 Z = -1.60 t = -6.40  0.691 0.801 0.058 0.230 0.952 0.109 0.024  t = -1.21 t = 1.46 t = 1.40 t = -0.41 t = 0.57 t = -1.67 Z = -0.73  0.312 0.242 0.256 0.711 0.611 0.194 0.465  49  3.3.4  Taxa richness and diversity  Taxa richness for EPTD was remarkably constant across both study areas, suggesting no adverse effects due to logging at this level of taxonomic resolution. Although shifts in the number of taxa may have occurred at the species level, none were identified at the genus level (Table 3.2). The number of taxa identified in the drift ranged from 10-19 genera at Eagle Lake and 7-24 genera at Horsefly (a list of taxa is provided in Appendix IV). At Eagle Lake, a significant change in diversity was detected when control-treatment differences were compared. Both Shannon’s (p = 0.039) and Simpson’s indices (p = 0.007) showed only slight increases in the index value relative to controls that almost doubled in value (larger value of both indices indicate improved condition). Pooled analysis confirmed the difference in Simpson’s index was due to a significant increase in control streams (p = 0.024) that was not observed in treatments.  3.4 Discussion By sampling drift over a 72 hour period, a representative community sample was captured that comprised taxa from all phyla and orders observed in benthic kick samples. Using a presence/absence approach to compare benthic composition to drift is certainly limited to qualitative analysis; however, it does demonstrate that drift samples (taken over a substantial period of time in stable flow conditions) in smaller headwater streams may sufficiently represent the taxonomic make-up of a stream community. More importantly, it is unlikely to underestimate the richness of that community. Changes to the drift composition at the order level were observed in the Horsefly River study area as a result of logging. It is important to note that different comparison results were often observed depending on the choice of analysis (pooled vs. paired differences), or whether flux or density measures were compared. For example, Plecoptera showed significant change in terms of biomass density when paired differences were compared, but not with pooled analysis. Controltreatment differences in Ephemeroptera, Trichoptera and Diptera indicated changes in total biomass flux but not when expressed as density. The difficulty in identifying clear changes due to logging effects may be attributed to background fluctuations of biomass and abundance in control streams. What is evident overall, is that order level changes were occurring in treatment streams that were not consistent with fluctuating controls.  50  The large variability in drift observed in Horsefly River control streams may be related to the effects of Spruce beetle in this study area. As discussed in Chapter 2, this was a rare event that caused large amounts of needle-fall into streams during the scheduled harvest year. Although I was aware Spruce beetle was present in the watershed, it was not expected to move so quickly into the study area. This influx of organic matter may have influenced invertebrate communities due to an increased supply of organic matter (primarily needles) and perhaps increased light penetration in some of the control streams. Unfortunately, the presence of the beetle was very patchy and was difficult to quantify in retrospect. Theoretically, this natural phenomenon may actually be mimicking the immediate effects of clear-cut harvesting as streams are often laden with organic material (namely needles and branches from the de-limbing process) during harvesting. Without clear measurement of organic matter input into streams as a result of the beetle, it is extremely difficult to partial out the effects this may have had on study streams. In the Eagle lake study area, patterns of drift density composition closely matched those expressed as flux. This was surprising as this study area contained mostly low discharge streams that showed a weak relationship between drift flux and discharge (see Appendix V for this analysis). High variability was evident in the drift in these small streams, largely influenced by baetid mayflies and chironomids. Large pulses of baetid mayflies are known to occur in response to environmental cues as they are behavioural drifters (Waters 1962, Kohler 1985, James et al. 2008). It is possible that due to hot weather, or some other unknown environmental conditions in the pre-impact year, we were seeing increased movement of baetid mayflies in some study streams. Because of their high numbers they have the potential to skew abundance data in certain directions and create problems of increased variation. The terrestrial invertebrate component of the drift showed no clear changes in either study area. Although a weak increase in densities could be argued at the Eagle Lake study area, this was not clear due to marginal increases observed in control streams as well. This was surprising as I expected to see a reduction in allochthonous contributions to the drift as a result of removing much of the riparian vegetation from the stream bank. If the shrubby herbaceous layer was not left intact, as was the case for many of our study streams, then I might expect to see immediate reductions of terrestrials falling into the stream from this habitat. Although no differences were detected immediately after harvesting, longer term monitoring would be required to identify changes to terrestrial drift after riparian vegetation has had time to regenerate. For example, once regrowth has been established, it is possible that terrestrial drift may increase, as was observed by Hoover et al. (2007) in north-central British Columbia. They found the relative terrestrial 51  component of drift increased in relation to the degree of canopy openness when different harvest buffer widths were examined. This, they concluded, was due to increased terrestrial insect habitat created by a well-developed herbaceous layer in the riparian zone, and possible increased insect activity from warmer temperatures in cut-blocks. In the short term, I did not observe any adverse effects to the terrestrial component of drift as a result of harvest treatment. The %EPT metric showed a meaningful decline in treatment streams relative to increasing controls at both study areas. These results indicate that relative to total abundance flux of invertebrates, there has been a decline in the abundance of sensitive taxa (EPT). Although simple to calculate, coarse level EPT metrics have been shown to be surprisingly accurate in detecting disturbance in streams. An EPT index has been successfully used to track changes in ecosystem processes with artificially induced disturbance (Wallace, Grubaugh & Whiles 1996). Maloney and Feminella (2006) re-emphasized this in their study on the effectiveness of single and multimetric measures to detect disturbance. They found that many compositional metrics, including functional feeding groups, were susceptible to high seasonal and annual variation, but EPT richness was relatively robust. Herringshaw et al. (2011) recently identified EPT density, %EPT and taxa richness as valuable indicators of urban land use impacts in streams. Therefore it is possible that the %EPT metric is detecting some effect due to logging that is not reflected in other single metric indicators. The proportion of shredding invertebrates (%shredders) remained relatively constant in treatment and control streams in both study areas. Due to the substantial deposition of coarse organic matter deposited in many treatment streams, I expected to see an increase in shredding invertebrates. Shredders are known to be particularly responsive to changes in coarse organic matter in headwater streams. Some investigators have observed higher densities of shredders in harvested streams due to increased detrital resources (Stone and Wallace 1998, Haggerty et al. 2004, Jackson et al. 2007), but others have also found functional feeding group composition and diversity of invertebrate communities unresponsive to harvest, even over a 10 year period (Gravelle et al. 2009). Hernandez et al. (2005) demonstrated that the addition of more labile allochthonous organic matter such as red alder increased the abundance of shredders as well as overall taxa richness of benthic invertebrates in harvested areas. It is possible that the type of organic matter (in our case, namely needles and twigs of coniferous species) was not as palatable as herbaceous foliage, and did not influence the composition of shredding invertebrates.  52  It is apparent that both the Horsefly River and Eagle Lake study areas experienced large fluctuations in invertebrate drift in both treatment and controls that may have overwhelmed the possibility of detecting subtle changes in communities due to logging. Although Spruce beetle effects may have played a role in influencing control streams in the Horsefly River study area, control streams in Eagle Lake also exhibited considerable change. An alternative explanation would be that fluctuations observed in our study streams are really demonstrative of the natural variation inherent in these small headwater stream ecosystems. Similar studies investigating the effects of timber harvest activities have observed overwhelming variation in benthic invertebrate communities. Melody and Richardson (2007) compared benthic invertebrate communities between forested and harvested reaches in central British Columbia, and found more variation among study streams than between the logged and unlogged reaches. Although they found significant differences between logged and unlogged reaches, some replicates responded positively and others negatively. Additionally, other studies have revealed that differences in invertebrate communities due to elevation can be more substantial than differences due to logging (Moldenke and Ver Linden 2007), and that interannual variability of invertebrate communities may prevent the detection of subtle effects of disturbance from harvest activities (Gravelle et al. 2009). One of the major limitations to this study is the lack of temporal replication. I can only infer immediate responses to impact with only one year of post-harvest observation. Long-term monitoring may be required to tease out potential temporal trends associated with the natural variability observed in study streams; however, recent results by Louhi et al. (2010) demonstrated that climatic variability overwhelmed their ability to detect any changes due to drainage improvement related disturbance, even with a very robust six year BACI study. This suggests that long-term monitoring may not be the answer to clarify trends in natural variability that are already evident in the short term.  3.5 Summary Upon comparison of benthic kick samples and invertebrate drift, I found that 24-hour drift samples represented all taxa found in the benthos and contained from 65-85% more taxa. This demonstrated that in headwater streams, invertebrate drift can provide a good estimate of taxa richness in a stream community. In response to clear-cut harvesting, significant changes in EPTD composition were detected at the Horsefly River study area. This may have been a result of 53  confounding effects from the Spruce bark beetle that was prevalent in this study area. At Eagle Lake, no significant changes in EPTD composition were observed, although the abundance of mayflies appeared to decline sharply in all density and flux measures. %EPT was the only measure to indicate reduced abundance of sensitive taxa as a result of logging at both study areas, and significant changes were detected for measures of diversity in the Eagle Lake study area. Proportional composition of shredders and taxonomic richness were remarkably constant over time in all treatment and control streams in both study areas. Due to the variability of drift composition both in control and treatment streams, clear responses to harvesting were often difficult to infer. It is possible that seasonal and long-term annual monitoring may further define trends observed in the short term.  54  4  Conclusion  4.1 Summary of research I have fulfilled my research objectives to quantify the export of aquatic invertebrates, fine particulate matter (FPOM) and dissolved organic matter (DOM) from headwater streams, and to assess the immediate effects of clear-cut harvesting on these exports. Overall, results from chapters 2 and 3 demonstrated that high elevation streams in interior British Columbia can be highly productive in terms of providing a source of invertebrates and organic matter to downstream reaches, and that clear-cut harvesting, under current management practices, has had no clearly defined adverse effects on the total abundance, biomass and composition of drifting invertebrates and organic matter. My results showed trends of increasing abundance and biomass density and flux of drifting invertebrates in forested headwater streams of the Horsefly River watershed; however, it was difficult to clearly establish logging effects due to large fluctuations observed in control streams. No significant changes in total drift abundance and biomass were detected in the Eagle Lake study area, although a decreasing trend was observed. Differences in responses between wet and dry ecosystems further suggest that potential effects due to harvesting on streams may be ecosystem dependent. Flux and concentration of FPOM and DOM did not appear to be outside the natural variation inherent in these headwater systems as no significant changes were evident over the post-impact monitoring period. Clear-cut harvesting did cause significant changes to the drifting invertebrate community structure in the Horsefly River study area. Changes to the composition of the dominant orders Ephemeroptera (E), Plecoptera (P), Trichoptera (T) and Diptera (D) relative to controls streams were detected. No significant changes in EPTD composition were observed at the Eagle Lake study area. %EPT was the only measure to indicate reduced abundance of sensitive taxa as a result of logging at both study areas. Proportional composition of shredding invertebrates and taxonomic richness were remarkably constant over time in controls and treatments of both study areas. Significant differences were also detected for measures of diversity in the Eagle Lake study area, likely due to large fluctuations in baetid mayflies which affected evenness. Due to the variability of drift composition both in control and treatment streams, clear responses to harvesting were difficult to infer. Although no negative impacts were observed in the short-term  55  in response to clear-cut harvesting, further research is required to investigate both seasonal and long-term trends.  4.2 Strengths and limitations One of the major strengths of this research was the attempt to provide adequate replication of impact treatment. Typically, Before-After-Control-Impact (BACI) experiments are limited to one or few impact areas which are sampled over a period of time (or replicated in time) (Smith 2002). I attempted a multiple, paired BACI design (M-BACIP) which included both spatial and temporal control elements (which is essentially a double control including a before impact reference in addition to a proximal, matching control stream, called a control-treatment pairing). This design is thought to be more robust and would potentially provide more inference on the effects of disturbance (Stewart-Oaten et al. 1986, Underwood 1994, Murtagh 2000). Although temporal replication was limited to 1 year before and 1 year after, I attempted to compensate by increasing the intensity of sampling by conducting 24 hour drift samples (in triplicate to achieve a 72 hour mean estimate) in multiple impact streams. Working in conjunction with Forest Licensees, especially during a time when the province was experiencing a widespread pine beetle epidemic, proved to be one of the more challenging aspects of my research. After a few months of reconnaissance and consultation with Licensees from all over southern BC, 12 treatment and 10 control streams were identified in the Cariboo Forest Region that were scheduled for clear-cut harvesting in 2005/2006. Replicates were inevitably lost for both control and treatment streams due to last minute changes in the logging schedule. Licensees were often forced to abandon 5 year logging plans to follow the beetle infestation as it moved through their operating areas. Overall, I ended up with 10 clear-cut treatment and 7 control streams which was much fewer than anticipated and likely resulted in reduction of statistical power. After examination of the data, it was apparent that I was not able to statistically infer clear responses to harvesting effects due to the variability among replicates, both in control and treatment groups. High variability among replicates is common in ecological field studies and can often result in failure to detect the effects of different stressors (Downes 2010). Perhaps increased replication and longer term monitoring could have helped differentiate between natural background fluctuations and trends due to logging effects. This of course would be expensive and due to funding limitations, was not possible for this project.  56  The analysis of both control-treatment pair differences and pooled treatments and controls provided strength to my statistical analysis. Interestingly, results from the two approaches revealed different results, particularly in the Horsefly River study area. One of the major disadvantages of control-treatment stream pairing is that it assumes the investigators know enough about watershed and invertebrate community processes to choose appropriate pairs. In reality, it is impossible to find identical streams in nature that would respond exactly the same way to perturbation. So if treatment streams do not follow the same trajectory of responses as control streams, the assumption is made that this is an effect due to treatment instead of a different response to natural circumstances. The results from my data suggest that one of the advantages of using control-treatment pairs is that it can often detect more subtle changes in highly variable systems, especially if the response of treatment streams is in opposition to the trajectory of the controls. This was evident with analysis of drifting invertebrate flux at Horsefly River; pooled analysis was unable to detect differences pre- and post-impact because the change was not large, but control-treatment differences detected a significant response because controls and treatment responded in opposite directions. The advantage of comparing pooled treatments and pooled controls independently is that the assumption of pairing is removed and replicates now represent the variability in responses to treatment. The problem with this approach is that high variability among replicates can easily prevent the detection of statistically significant responses, particularly without strong replication. Discussions in the literature have attempted to address problems associated with proper data analysis and interpretation of BACI based designs (e.g., Conquest 2000, Murtagh 2000) and suggestions have been made that caution should be used with hypothesis testing and reliance on p-values in the absence of strong replication. The occurrence of Spruce bark beetle in the Horsefly River study area was a source of limitation for this study. The beetle introduced confounding variables such as increased needle drop into control streams and caused problems with data interpretation. Although I was aware beetle was present in the watershed, I did not anticipate the spread to occur as quickly as it did, nor to cause trees to shed their needles within the year. As I was unable to properly quantify this effect in retrospect, it was difficult to determine whether fluctuations observed in control streams were due to normal levels of background variation or simply due to beetle effects. Overall, I can say that using control-treatment pairing was effective at controlling for natural variability, but because of the rarity and timing of the event, it likely overwhelmed my ability to detect any small changes due to logging (coined “demonic intrusion” by Hurlbert 1984). Having said that, it is evident that large fluctuations are inherent in these headwater forested streams and perhaps stream communities may be resilient to the effects of harvesting. 57  Lastly, the weak linear relationship between drifting invertebrate flux and discharge in my study streams led me to interpret converted density measurements (flux standardized by discharge) with caution. Although it has been well established in the literature that drift can vary due to many biotic and abiotic factors other than discharge (e.g., Matzinger & Bass 1995, Faulkner & Copp 2001), it is surprisingly common for drift studies to report results in density rather than flux without providing good correlations between drift abundance and discharge. As a result of their review on drift, Brittain & Eikeland (1998) recommended using drift rates for comparative purposes because it was less dependent on the dilution and concentration effects that can occur with changing flow regimes. More recently, Downes (2010) recognized the need to address inappropriate standardizations in the literature based on previously existing theory. Invertebrate drift was provided as a good example of how conversion of a sample to density measurement, even though a linear relationship between drift and discharge has not been established, is often inappropriate. A linear relationship is important because standardization to discharge assumes that the number of drifting individuals will increase with increasing discharge. Despite using drift density in specific applications and especially for estimating prey availability for fish (as demonstrated by Leung et al. 2009), the results of this study emphasize that it is important to include both flux and density measures to properly quantify the dynamics of invertebrate export, especially for comparative purposes.  4.3 Applications and future directions The primary goal of this research was to quantify potential impacts to organic matter export in headwater streams under current riparian management practices. Due to the lack of protection for non-fish-bearing headwater streams in British Columbia, there was concern about the loss of food resources to downstream reaches, particularly for higher trophic levels. In light of recent knowledge on the connectivity of stream ecosystems (e.g., Gomi et al. 2002, Wipfli & Baxter 2010) there was legitimate concern that harvesting activities could indirectly affect fish habitat in higher order streams. This study provides evidence that under current riparian management practices in high elevation forests, clear-cut logging has had no clear, detrimental effects on organic matter export in interior British Columbia streams. In particular, in terms of direct food subsidies for fish, harvest practices have significantly increased the total biomass and abundance flux of drifting invertebrates in 1 of 2 study areas.  58  The lack of adverse effects on stream drift is important information for fisheries managers on a local and regional scale. Certainly, local application of this knowledge will be very important in the Horsefly River watershed, as this system is an extremely important salmon-bearing river that supports large spawning populations of sockeye salmon (Lilja 2008), as well as smaller runs of chinook and coho salmon (BCMOE 2011). Study streams in the Horsefly River study area drain directly into the headwaters of the Horsefly River; therefore, results of this study bear direct implications to fisheries in this watershed. As managers attempt to identify and mitigate land-use impacts on fish habitat for both resident and migratory species, I anticipate that these data will reduce uncertainty in evaluating the impacts of logging in these watersheds. At the regional scale, this information will assist forest managers in evaluating the effectiveness of current riparian management guidelines in interior British Columbia. Given the variation in results from my two study areas, I recommend further investigation be dedicated to resolving site-specific responses of both benthic and drifting invertebrates to the effects of forest harvesting. Although benthic invertebrate responses have been evaluated based on many physical factors such as substrate composition (e.g., Gurtz & Wallace 1984, Herlihy et al. 2005), many biotic and abiotic factors may work together to create conditions for more sitespecific responses. Regional variation has been investigated recently by Medhurst et al. (2010) in the Pacific Northwest. They demonstrated that fluctuations in invertebrate richness and density in responses to logging is closely related to climatic and regional characteristics. They suggested that the development of an eco-regional classification system may be appropriate for developing guidelines for predicting the response of macroinvertebrate communities to logging. This has already been attempted in other parts of the world. Sandin and Johnson (2000) geographically classified over 400 streams in Sweden using eco-regions in an attempt to partition species variance of benthic assemblages. They found this particularly difficult because invertebrate assemblages also varied with latitude, which may be the case in western North America as well. The Horsefly River study area, which is a wet and very productive ecosystem with moderately steep slopes, showed a significant positive response in drifting invertebrate biomass and abundance in response to logging. Eagle Lake, which is a much drier ecosystem with gentle slopes, was a highly variable study area that did not respond clearly to logging effects but showed negative response trends in a few study streams. Based on these results, and those in the literature, we recommend further logging impact studies focus on defining ecosystem responses in British Columbia, so that riparian management guidelines may be adjusted to reflect beneficial harvest practices by region. 59  Another area that warrants further investigation is defining the degree of ecological connectivity between headwater streams and downstream reaches. The potential influence that headwater streams may have on higher order streams has been discussed repeatedly in the scope of this thesis. What hasn’t been well demonstrated in the literature is the degree of ecological connectivity in terms of invertebrate transport distance. Much research has been focused on organic matter export and nutrient cycling but few have studied the transport or fate of invertebrate prey to downstream networks (Wipfli & Baxter 2010). This research, and the results of other drift studies (e.g. Wipfli & Gregovich 2002), have demonstrated that headwater streams can be important contributors of drifting invertebrates, if in fact they make it downstream to feed fish. A recent study by Danehy et al. (2011) presented interesting data that invertebrate drift originates from local populations only. They sampled drifting invertebrates in a stream before and after blocking off the upstream source of drift, and found that this had no significant effect on invertebrate drift abundance downstream. If supported by other studies, this could have major consequences on how we currently view food web theory and transport dynamics in headwater streams. The last issue I identify that requires further research is the issue of invertebrate prey discrimination by drift-feeding fish. If the composition of the invertebrate community were to change as a result of harvest activities, then what consequences would this have on drift-feeding fish downstream? Does it matter whether or not they eat a chironomid or a mayfly instead of a caddisfly? Certainly, the importance of terrestrial prey in the diet of fish has been well documented in the literature (e.g., Kawaguchi & Nakano 2001, Kawaguchi et al. 2003). Also, size selectivity and drift feeding strategies of fish have been approached (Guensch et al. 2001, Gustafsson et al. 2010). Empirical evidence is required to determine whether or not drift-feeding fish are capable of more specific selection. Only then, can we make inferences that harvest effects on invertebrate communities may have consequences for fish in downstream reaches.  60  References Aitkenhead-Peterson, J.A., M cDowell, W.H., and Neff, J.C. 2003. Sources, production and regulation of allochthonous dissolved organic matter inputs to surface waters. 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Ecological linkages between headwaters and downstream ecosystems: Transport of organic matter, invertebrates, and wood down headwater channel. Journal of the American Water Resources Association 43(1): 1-14. Yoshimura, C., Fujii, M ., Omura, T., and Tockner, K. 2010. Instream release of dissolved organic matter from coarse and fine particulate organic matter of different origins. Biogeochemistry 100: 151–165.  66  Appendices Appendix A – Sampling dates Table A.1 Sampling dates for variables within the Horsefly River and Eagle Lake study areas (n.d. indicates no data collected). S tudy Area  S tream  Treatment  Date Sampled Pre-impact  Date Sampled Post-impact  I.D. Invertebrate  FPOM /DOM  DOM  Drift (3x24hrs) (Summer) Horsefly River  Eagle Lake  Invertebrate  FPOM /DOM  DOM  DOM  (Summer)  (Fall)  (Summer)  Drift (3x24hrs) (Summer)  (Fall)  (Summer)  501  Clear-cut  15-18 Jul-05  18-Jul-05  21-Oct-05  10-13 Jul-06  13-Jul-06  2-Oct-06  8-Jul-07  504  Clear-cut  15-18 Jul-05  18-Jul-05  n.d.  14-17 Jul-06  17-Jul-06  2-Oct-06  8-Jul-07  505  Clear-cut  19-22 Jul-05  22-Jul-05  21-Oct-05  14-17 Jul-06  17-Jul-06  2-Oct-06  8-Jul-07  507  Clear-cut  19-22 Jul-05  22-Jul-05  21-Oct-05  14-17 Jul-06  17-Jul-06  3-Oct-06  8-Jul-07  510  Clear-cut  24-27 Jul-05  27-Jul-05  n.d.  18-21 Jul-06  21-Jul-06  3-Oct-06  7-Jul-07  511  Clear-cut  24-27 Jul-05  27-Jul-05  n.d.  18-21 Jul-06  21-Jul-06  3-Oct-06  7-Jul-07  512  Clear-cut  24-27 Jul-05  27-Jul-05  n.d.  18-21 Jul-06  21-Jul-06  4-Oct-06  7-Jul-07  502  Control  15-18 Jul-05  18-Jul-05  21-Oct-05  10-13 Jul-06  13-Jul-06  2-Oct-06  8-Jul-07  503  Control  15-18 Jul-05  18-Jul-05  n.d.  n.d.  n.d.  n.d.  8-Jul-07  506  Control  19-22 Jul-05  22-Jul-05  21-Oct-05  14-17 Jul-06  17-Jul-06  2-Oct-06  8-Jul-07  508  Control  19-22 Jul-05  22-Jul-05  21-Oct-05  14-17 Jul-06  17-Jul-06  3-Oct-06  8-Jul-07  513  Control  24-27 Jul-05  27-Jul-05  n.d.  21-Jul-06  4-Oct-06  7-Jul-07  601  Clear-cut  4-7 Aug-05  7-Aug-05  28-Oct-05  18-21 Jul-06 28-31 Jul-06  31-Jul-06  19-Oct-06  10-Jul-07  602  Clear-cut  4-7 Aug-05  7-Aug-05  28-Oct-05  28-31 Jul-06  31-Jul-06  19-Oct-06  10-Jul-07  604  Clear-cut  8-11 Aug-05  11-Aug-05  n.d.  1-4 Aug-06  4-Aug-06  19-Oct-06  9-Jul-07  606  Clear-cut  8-11 Aug-05  11-Aug-05  n.d.  1-4 Aug-06  4-Aug-06  n.d.  n.d.  608  Clear-cut  12-15 Aug-05  15-Aug-05  n.d.  9-12 Jul-07  12-Jul-07  n.d.  12-Jul-07  603  Control  4-7 Aug-05  7-Aug-05  n.d.  28-31 Jul-06  31-Jul-06  19-Oct-06  10-Jul-07  605  Control  8-11 Aug-05  11-Aug-05  28-Oct-05  1-4 Aug-06  4-Aug-06  n.d.  9-Jul-07  607  Control  8-11 Aug-05  11-Aug-05  n.d.  1-4 Aug-06  4-Aug-06  n.d.  n.d  609  Control  12-15 Aug-05  15-Aug-05  n.d.  9-12 Jul-07  12-Jul-07  n.d.  12-Jul-07  67  Appendix B – Photos of drift sampling  (a)  (b)  (c) Figure B.1 Photos of temporary flume installation (a), measurement of discharge (b), and drift net set-up (c) at study streams in the Horsefly River study area. (Photo credit; (a) by D. Clark, (b) & (c) by J. Sorensen)  68  Appendix C – Physical/chemical information Table C. 1 Physical and chemical information for study streams over the three year sampling period (2005 = pre-impact, 2006/2007 = post-impact). If data  were not available for that particular stream it is indicated by n.d (no data). Bold streams were omitted from the study in 2006, therefore, only pre-impact data were collected.  Stream I.D. Horsefly 501 504 505 507 510 511 512 502 503 506 508 513 Eagle 601 602 604 606 608 603 605 607 609  Treatment  GPS Location Northing Easting  Elev (m)  Slope (%)  Aspect (°)  width (cm)  Discharge (Ls -1 )  pH  Conductivity (µS/cm)  Temp (°C)  2005  2006  2007  2005  2006  2007  2005  2006  2007  2005  2006  2007  clear-cut clear-cut clear-cut clear-cut clear-cut clear-cut clear-cut control control control control control  668021 668281 668240 667318 626722 625487 624883 667913 667863 668049 666400 631363  5812217 5811928 5810428 5812128 5801199 5800359 5801581 5812366 5812446 5810073 5813134 5801125  1303 1326 1382 1321 1518 1449 1350 1304 1291 1375 1304 1607  28 24 37 30 17 20 17 33 29 54 34 20  240 248 302 43 330 260 53 241 234 298 54 204  49.3 77.0 53.3 103.6 85.0 68.0 51.6 54.6 40.7 38.3 101.6 109.6  1.58 4.83 1.01 7.25 3.32 1.85 1.70 4.72 1.14 0.36 3.20 5.98  1.13 1.78 0.32 9.81 1.78 0.72 0.30 0.87 n.d. 0.45 4.69 4.28  0.44 1.25 0.75 12.50 n.d. 1.29 0.52 0.96 n.d. 0.23 2.08 3.38  7.2 7.3 7.6 6.9 n.d. n.d n.d 7.1 7.1 7.1 6.9 n.d  7.3 7.1 6.9 6.9 n.d. 7.6 7.9 7.1 n.d. 7.0 6.8 7.8  7.5 7.5 7.1 7.0 n.d. 7.8 7.9 7.3 n.d. 7.1 6.9 8.0  40 50 30 10 n.d. n.d n.d 70 70 70 0 n.d  50 30 30 10 n.d. 120 300 40 n.d. 20 0 100  40 30 10 10 n.d. 120 260 30 n.d. 30 0 70  8.0 8.0 7.0 9.0 6.8 7.5 7.8 7.5 8.0 7.2 9.0 8.0  8.5 8.3 8.1 9.3 n.d. 9.8 9.7 7.1 n.d. 7.0 8.2 8.4  8.2 8.1 8.4 8.4 n.d. 10.0 12.4 6.7 n.d. 7.0 8.2 9.0  clear-cut clear-cut clear-cut clear-cut clear-cut control control control control  619414 619421 620871 621586 622830 619393 620530 618214 624817  5774436 5774628 5771779 5756437 5753213 5773411 5771856 5756454 5753123  1256 1258 1137 1325 1288 1158 1119 1280 1193  11 21 5 4 10 18 14 14 28  250 245 189 100 50 240 198 30 30  29.5 49.6 87.6 102.7 123.6 55.0 80.0 62.3 50.0  1.00 1.50 0.48 0.68 0.31 0.14 0.47 0.38 3.28  0.39 0.63 0.38 0.20 n.d. 0.08 0.09 0.04 n.d.  0.56 1.57 0.84 n.d. 0.83 0.28 1.17 n.d. 5.98  7.0 7.1 n.d n.d. n.d n.d 7.4 n.d. n.d  7.1 7.6 7.1 n.d. n.d 6.8 7.0 n.d. n.d  7.1 7.2 7.5 n.d. 7.3 6.9 7.7 n.d. 8.1  40 40 n.d n.d. n.d n.d 40 n.d. n.d  60 120 170 n.d. n.d 100 110 n.d. n.d  40 70 100 n.d. 30 80 60 n.d. 400  9.0 10.0 10.0 11.0 9.5 12.0 10.5 10.0 8.0  9.9 10.0 12.0 n.d. n.d 11.7 10.2 n.d. n.d  10.6 12.8 15.3 n.d. 9.0 10.5 11.4 n.d. 6.4  69  Appendix D – List of identified invertebrate taxa Table D.1 List of taxa identified in invertebrate drift samples at Horsefly River and Eagle Lake study areas. Phylum  Family  Genus  Class  O rder  Arthropoda  Arachnida  Acarina  A  Arthropoda  Entognatha  Collembola  T  Arthropoda  Insecta  Coleoptera  unidentifed adults  T  Arthropoda  Insecta  Coleoptera  unidentifed larvae  A  Arthropoda  Insecta  Diptera  unidentified adults  T  Arthropoda  Insecta  Diptera  Ceratopogonidae  A  Arthropoda  Insecta  Diptera  Chironomidae  A  Arthropoda  Insecta  Diptera  Culicidae  A  Arthropoda  Insecta  Diptera  Dixidae  A  Arthropoda  Insecta  Diptera  Psychodidae  A  Arthropoda  Insecta  Diptera  Simuliidae  A  Arthropoda  Insecta  Diptera  T abanidae  A  Arthropoda  Insecta  Diptera  T ipulidae  A  Arthropoda  Insecta  Ephemeroptera  unidentified adults  Arthropoda  Insecta  Ephemeroptera  Ameletidae  Ameletus  A  Arthropoda  Insecta  Ephemeroptera  Baetidae  Baetis  A  Arthropoda  Insecta  Ephemeroptera  Ephemerellidae  Attenella  A  Arthropoda  Insecta  Ephemeroptera  Ephemerellidae  Drunella  A  Arthropoda  Insecta  Ephemeroptera  Heptageniidae  Cinygma  A  Arthropoda  Insecta  Ephemeroptera  Heptageniidae  Cinygmula  A  Arthropoda  Insecta  Ephemeroptera  Heptageniidae  Epeorus (Iron)  A  Arthropoda  Insecta  Ephemeroptera  Heptageniidae  Epeorus (Ironopsis)  A  Arthropoda  Insecta  Ephemeroptera  Heptageniidae  Rhithrogena  A  Arthropoda  Insecta  Hemiptera  unidentified adults  T  Arthropoda  Insecta  Homoptera  unidentified adults  T  Arthropoda  Insecta  Hymenoptera  unidentified adults  T  Arthropoda  Insecta  Isoptera  unidentified adults  T  Arthropoda  Insecta  Lepidoptera  unidentified larvae  T  Arthropoda  Insecta  Plecoptera  unidentified adults  Arthropoda  Insecta  Plecoptera  Chloroperlidae  Haploperla  A  Arthropoda  Insecta  Plecoptera  Chloroperlidae  Plumiperla  A  Arthropoda  Insecta  Plecoptera  Leuctridae  Despaxia  A  Arthropoda  Insecta  Plecoptera  Leuctridae  Paraleuctra  A  Arthropoda  Insecta  Plecoptera  Leuctridae  Perlomyia  A  Arthropoda  Insecta  Plecoptera  Nemouridae  Malenka  A  Arthropoda  Insecta  Plecoptera  Nemouridae  Visoka  A  Arthropoda  Insecta  Plecoptera  Nemouridae  Zapada  A  Arthropoda  Insecta  Plecoptera  Peltoperlidae  Yoraperla  A  Arthropoda  Insecta  Plecoptera  Perlodidae  Isoperla  A  Arthropoda  Insecta  Plecoptera  Perlodidae  Megarcys  A  Annelida  O rigin Aqu/Terr A  70  T  T  Table D.1 continued Phylum  Class  O rder  Family  Genus  O rigin Aqu/Terr  Arthropoda  Insecta  Plecoptera  Perlodidae  Perlinodes  A  Arthropoda  Insecta  Plecoptera  Perlodidae  Rickera  A  Arthropoda  Insecta  Plecoptera  Perlodidae  Setvena  A  Arthropoda  Insecta  T hysanoptera  unidentified adults  Arthropoda  Insecta  T richoptera  unidentified adults  Arthropoda  Insecta  T richoptera  Apataniidae  Allomyia  A  Arthropoda  Insecta  T richoptera  Apataniidae  Moselyana  A  Arthropoda  Insecta  T richoptera  Brachycentridae  Micrasema  A  Arthropoda  Insecta  T richoptera  Glosssomatidae  Glossosoma  A  Arthropoda  Insecta  T richoptera  Goeridae  Lepania  A  Arthropoda  Insecta  T richoptera  Hydropsychidae  Parapsyche  A  Arthropoda  Insecta  T richoptera  Lepidostomatidae  Lepidostoma  A  Arthropoda  Insecta  T richoptera  Limnephilidae  Chyranda  A  Arthropoda  Insecta  T richoptera  Limnephilidae  Cryptochia  A  Arthropoda  Insecta  T richoptera  Limnephilidae  Desmona  A  Arthropoda  Insecta  T richoptera  Limnephilidae  Ecclisomyia  A  Arthropoda  Insecta  T richoptera  Limnephilidae  Eocosmoecus  A  Arthropoda  Insecta  T richoptera  Limnephilidae  Homophylax  A  Arthropoda  Insecta  T richoptera  Limnephilidae  Psychoglypha  A  Arthropoda  Insecta  T richoptera  Philopotamidae  Wormaldia  A  Arthropoda  Insecta  T richoptera  Rhyacophilidae  Rhyacophila  A  Arthropoda  Insecta  T richoptera  Uenoidae  Neothremma  A  Arthropoda  Ostracoda  A  Mollusca  Gastropoda  A  T T  Nematoda  A  Nematomorpha  A  Platyhelminthes  A  71  Appendix E – Analysis & discussion of the drift-discharge relationship The relationships between stream discharge and daily invertebrate abundance and biomass for the Horsefly River and Eagle Lake study areas are provided in Figure E.1.  3000  1200  -1  Invertebrates 24 hrs  1000  0  -1000  R 2 = 0.642 ANOVA p = 0.002  1000  mg invertebrate dry mass 24 hrs  2000  -1  R 2 = 0.729 ANOVA p < 0.001  800 600 400 200 0 -200 -400  -2000 0  1  2  3  4  0  5  1  2  3  10000  1400  R 2 = 0.531 ANOVA p = 0.040  mg invertebrate dry mass 24 hrs  -1  1200  -1  Invertebrates 24 hrs  5  (b)  (a)  8000  4  Discharge (L s-1)  Discharge (L s-1)  6000  4000  2000  0  R 2 = 0.048 ANOVA p = 0.599  1000 800 600 400 200 0 -200  -2000  -400  0.0  0.5  1.0  1.5  2.0  2.5  3.0  3.5  Discharge (L s-1)  0.0  0.5  1.0  1.5  2.0  2.5  3.0  Discharge (L s-1)  (c)  (d)  Figure E.1 The relationship between discharge and daily invertebrate abundance and biomass for the Horsefly River (a, b) and Eagle Lake (c, d) study areas. Dashed lines represent 95% confidence intervals for the regression.  A positive linear relationship between discharge and the mean daily export of invertebrates (both abundance and biomass) was apparent at Horsefly River, but was very weak at Eagle Lake. Although the regression is marginally significant for daily invertebrate abundance at Eagle Lake, this relationship completely disappeared and became insignificant when the highest discharge stream was removed (R2 = 0.145, ANOVA p = 0.399). 72  3.5  Overall, daily invertebrate abundance and biomass flux estimates at Eagle Lake streams were very comparable to Horsefly River streams; however, the discharges at Eagle Lake were much lower, and the number of individuals in the drift became unpredictable. Although increased replication may further define this relationship it is apparent that it is very weak compared to the higher discharge streams in the Horsefly River study area. This suggests that the relationship between invertebrate drift and discharge may become very unpredictable in small streams, particularly with discharges less than 2 L s -1 . It is often assumed that using density-based measurements should account for differences in stream flow and represent an accurate estimate of invertebrate drift. I identified that this may not be a valid assumption based on the drift-discharge relationships observed in my study streams. Although a positive correlation between drift flux (invertebrates 24 hrs -1 ) and discharge (L s-1 ) was revealed, I found the relationship became very weak in streams with discharges less than 2 L s-1 , suggesting that invertebrate drift may be less dependent on flow at low velocities and more dependent on other mechanisms. This effect has been observed by other investigators as well. Musselwhite and Wipfli (2004) concluded that using drift density measures should be used with caution due to the potential to dilute or concentrate sample results. This was originally suggested by Brittain & Eikeland (1998) as a result of their review on drift, that using drift rates for comparative purposes was preferable because it was less dependent on the dilution and concentration effects that can occur with changing flow regimes. Leung et al. (2009) also demonstrated this phenomenon in a small coastal stream in southern BC. Although this study was conducted in only one stream, they found a weak correlation between drift concentration and velocity at the mesohabitat scale (combining pools, riffle, and runs) and found that the relationship completely disappeared with the removal of high velocity habitats. Faulkner and Copp (2001) also implied that theoretical links between flow hydraulics and drift behaviour are poorly understood. Various approaches and opinions have been expressed in the literature on whether or not to use density or flux in drift estimation. Many recent studies that have focused on drift as available prey for fish have chosen flux as one of the more important metrics (e.g., Bacon et al. 2005, Romero et al. 2005, Hoover et al. 2007). Others have argued that using flux will confound the independent effects of drift concentration and discharge on total prey availability (e.g., Leung et al. 2009). Recently, a contribution by B.J. Downes (2010) re-emphasized the need to address inappropriate standardizations in the literature based on previously existing theory. She used invertebrate drift as a good example of how converting flux to density measurements, even 73  though a linear relationship between drift and discharge has not been established, is inappropriate. In response to this, I have provided empirical evidence that it is possible to misinterpret results based on choice of standardization. Based on the poor relationship between invertebrate drift and discharge that was revealed in my study streams, I suggest that although density estimates of drift are important metrics for estimating prey availability, the calculation of flux variables for comparative studies of invertebrate drift is prudent, especially in small streams with discharges less than 2 L s-1 .  74  

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