EFFECTS OF LIVESTOCK GRAZING ON AQUATIC MACROINVERTEBRATES IN SOUTHERN INTERIOR WETLANDS OF BRITISH COLUMBIA, CANADA by DENISE LYNN CLARK B.Sc. Thompson Rivers University, 2003 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE IN ENVIRONMENTAL SCIENCES in the Department of Natural Resource Sciences Thesis examining committee: Brian Heise (Ph.D.), Thesis Supervisor and Associate Professor, Natural Resource Sciences, Thompson Rivers University Lauchlan Fraser (Ph.D.), Professor, Natural Resource Sciences, Thompson Rivers University Tom Dickinson (Ph.D.), Dean of Science and Associate Professor, Biological Sciences, Thompson Rivers University Darryl Carlyle-Moses (Ph.D.), Associate Professor, Geography and Environmental Studies, Thompson Rivers University Robert Cannings (Ph.D.), External Examiner, Curator Entomology (Emeritus), Royal British Columbia Museum April 2015 Thompson Rivers University © Denise Lynn Clark 2015 ii Thesis Supervisor: Associate Professor Brian Heise (Ph.D.) ABSTRACT Grasslands in the southern interior of British Columbia are extensively grazed by free ranging livestock. Water sources are limited in these grassland landscapes and wetlands are commonly used by livestock for drinking water and forage. My study examined the impacts of livestock disturbance on the abundance, biomass and community composition of aquatic macroinvertebrates residing in these wetlands. Aquatic macroinvertebrates were collected in the spring and summer of 2008 from 17 wetlands with a range of grazing disturbance. Three sweep and core samples were collected from each wetland and grazing intensity was determined by the amount of bare ground at each site. Spring sweep total abundance (r2=0.464, p=0.003) and biomass (r2=0.728, p<0.001) were negatively correlated with livestock disturbance as were spring abundance and biomass of zygopterans (r2=0.593, p<0.001; adj. r2=0.513, p=0.001). Spring sweep family richness (r2=0.462, p=0.003), Shannon’s family diversity (r2=0.569, p<0.001) and Simpson’s family diversity (r2=0.385, p=0.008) also decreased as livestock disturbance increased. Resource managers should consider Zygoptera (damselflies) as a potential indicator of wetland water quality and livestock impact. Range plans should adopt only light grazing in wetland areas and limit livestock access to sustain the biodiversity and productivity of these valuable aquatic ecosystems. Keywords: aquatic macroinvertebrates, grassland wetlands, livestock grazing, British Columbia, Zygoptera iii TABLE OF CONTENTS ABSTRACT.............................................................................................................................. ii TABLE OF CONTENTS......................................................................................................... iii ACKNOWLEDGEMENTS..................................................................................................... vi LIST OF FIGURES ................................................................................................................ vii LIST OF TABLES ................................................................................................................... ix GLOSSARY OF TERMS ........................................................................................................ xi CHAPTER 1. INTRODUCTION ............................................................................................. 1 Grassland Ecosystems ........................................................................................................... 1 Wetland Ecosystems ............................................................................................................. 2 Livestock Grazing ................................................................................................................. 3 Aquatic Invertebrates ............................................................................................................ 3 Thesis Objectives and Format............................................................................................... 5 Literature Cited ..................................................................................................................... 6 CHAPTER 2. EFFECTS OF LIVESTOCK GRAZING ON AQUATIC MACROINVERTEBRATES IN SOUTHERN INTERIOR WETLANDS OF BRITISH COLUMBIA, CANADA ........................................................................................................ 11 Introduction ......................................................................................................................... 11 Methods .............................................................................................................................. 13 Study Area ...................................................................................................................... 13 Estimates of Livestock Disturbance ............................................................................... 15 Aquatic Invertebrate Sampling and Processing .............................................................. 15 Statistical Analysis .......................................................................................................... 17 Results ................................................................................................................................. 18 iv Aquatic Invertebrate Community Structure .................................................................... 18 Community Response to Disturbance............................................................................. 25 Individual Taxa Response to Livestock Disturbance ..................................................... 31 Discussion ........................................................................................................................... 36 Aquatic Invertebrate Community Response ................................................................... 36 Zygoptera Response ........................................................................................................ 37 Other Taxa Response to Disturbance.............................................................................. 38 Study limitations ............................................................................................................. 39 Management Recommendations ..................................................................................... 40 Conclusion ...................................................................................................................... 40 Literature Cited ................................................................................................................... 42 CHAPTER 3. CONCLUSION ............................................................................................... 49 Research Summary ............................................................................................................. 49 Challenges of Wetland Invertebrate Research and Future Research Directions ................ 49 Management Implications................................................................................................... 50 Recommendations ............................................................................................................... 52 Literature Cited ................................................................................................................... 53 APPENDIX A. Physical Data ................................................................................................ 54 APPENDIX B. Photos of livestock disturbance at study wetlands. ...................................... 55 APPENDIX C. Aquatic macroinvertebrate taxa list .............................................................. 56 APPENDIX D. Length-mass regression equations ............................................................... 58 APPENDIX E. Relative abundance and biomass (%) of spring and summer aquatic macroinvertebrates. ................................................................................................................. 59 APPENDIX F. Nonmetric multidimensional scaling (NMDS) ordinations of dominant taxa community structure and environmental variables. ................................................................ 63 v APPENDIX G. Environmental variable correlation values from nonmetric multidimensional scaling (NMDS) ordinations. ..................................................................... 66 APPENDIX H. Significant linear regressions with macroinvertebrates and environmental variables other than livestock disturbance. ............................................................................. 67 vi ACKNOWLEDGEMENTS I wish to thank all those who have supported me in this research endeavor. I would like to sincerely thank my thesis supervisor Dr. Brian Heise. His guidance, encouragement and unending patience through my research and personal challenges have been greatly appreciated. To my other committee members Dr. Lauchlan Fraser, Dr. Tom Dickinson and Dr. Darryl Carlyle-Moses, I thank you for your time, input and feedback in helping to generate this thesis. I am grateful for the many thought-provoking conversations and guidance from Dr. Nancy Flood, Dr. Louis Gosselin, Dr. Karl Larsen, Dr. Wendy Gardner and Dr. Don Noakes. I also thank Dr. Rob Cannings for his assistance with the identification of immature dragonflies and for his time as my external examiner. Special thanks to Bruce Harrison for his assistance with wetland selection and for sharing his wealth of waterfowl knowledge and to Marc Jones for his livestock disturbance data and statistical advice. Many thanks to Becky Weafer, who was a valued research assistant in the lab and field and who, because of me, will forever cringe at the mention of the word “recce”. I also wish to acknowledge Jacqueline Dennette, Hartland Molson, Tanya Fedorick, Kay Linley, Adam Bruno, Patsy Parr, and Eleanor Bassett who put in many long hot and rainy days in the field slogging through stinky, mucky ponds and/or in the lab staring endlessly through a microscope. Thank you to Cameron Carlyle for his time spent assisting me with the use of R for my analyses. Thank you to the private landowners (Froleks, Deleeuws, Haughtons, and Gowans) who granted access to wetlands on their properties. My deepest gratitude goes to my husband who picked up the slack at home so I could focus on my project and whose never-ending support and encouragement got me to the finish line. Lastly, I thank Jacque Sorensen whose friendship and support has been invaluable throughout my project. This work was generously supported by Thompson Rivers University, the Forest Science Program, Ducks Unlimited Canada, and the Institute for Wetland and Waterfowl Research. vii LIST OF FIGURES Figure 2.1. Location of the four study areas (stars) near Kamloops, BC. (Map sources: Natural Resource Canada 2004; Google Maps 2014). ........................................................... 14 Figure 2.2. Linear relationship between livestock disturbance and a) spring sweep total abundance and b) spring sweep total biomass. Livestock disturbance represents the mean # of quadrat corners that intersected bare ground at each wetland (Jones et al. 2011). Dotted lines represent 95% confidence intervals................................................................................ 26 Figure 2.3. Linear relationship between livestock disturbance and spring sweep a) family richness, b) Shannon’s family-level diversity (H’) and c) Simpson’s family-level diversity (D). Livestock disturbance represents the mean # of quadrat corners that intersected bare ground at each wetland (Jones et al. 2011). Dotted lines represent 95% confidence intervals. .................................................................................................................................. 27 Figure 2.4. Nonmetric multidimensional scaling (NMDS) ordination (stress=13.3%) of summer sweep abundance dominant taxa community structure with overlay of fitted vector representing the significant (r2=0.714, p=0.006) environmental variable livestock disturbance (Disturb). Wetland site (in red) disturbance level is represented by a continuum with large circles being most disturbed and dots representing least disturbed sites. Taxa (in black) are as follows: Aes=Aeshnidae, Bol=Collembola, Cer=Ceratopogonidae, Chi=Chironomidae, Cor=Corixidae, Dyt=Dytiscidae, Gas=Gastropoda, Les=Lestidae, Oli=Oligochaeta, and Ost=Ostracoda. .................................................................................... 28 Figure 2.5. Nonmetric multidimensional scaling (NMDS) ordination (stress=13.3%) of summer sweep abundance dominant taxa community structure with overlay of fitted vector representing the significant (r2=0.714, p=0.006) environmental variable livestock disturbance (Disturb). Wetland site (in red) disturbance level is represented by a continuum with large circles being most disturbed and dots representing least disturbed sites. Taxa (in black) are as follows: Cer=Ceratopogonidae, Chi=Chironomidae, Dyt=Dytiscidae, Les=Lestidae, Lym=Lymnaeidae, Oli=Oligochaeta, and Ost=Ostracoda. ............................. 29 Figure 2.6. Nonmetric multidimensional scaling (NMDS) ordination (stress=1.74%) of summer core abundance dominant taxa community structure with overlay of fitted vector representing the significant (r2=0.534, p=0.034) environmental variable livestock disturbance (Disturb). Wetland site (in red) disturbance level is represented by a continuum with large circles being most disturbed and dots representing least disturbed sites. Taxa (in black) are as follows: Cer=Ceratopogonidae, Chi=Chironomidae, Oli=Oligochaeta. ........... 30 viii Figure 2.7. Linear relationship between livestock disturbance and spring sweep a) Zygoptera abundance b) Zygoptera biomass c) Lestidae abundance and d) Lestidae biomass. Livestock disturbance represents the mean # of quadrat corners that intersected bare ground at each wetland (Jones et al. 2011). Dotted lines represent 95% confidence intervals. .................................................................................................................................. 32 ix LIST OF TABLES Table 2.1. Dominant taxa for sweep and core abundance during spring and summer sampling sessions. Taxa were selected based on their presence in >50% of all wetlands and having >5% relative abundance in at least one wetland site................................................... 19 Table 2.2. Dominant taxa for sweep and core biomass during spring and summer sampling sessions. Taxa were selected based on their presence in >50% of all wetlands and having >5% relative biomass in at least one wetland site. ................................................................. 20 Table 2.3. Summary of mean spring sweep abundance, biomass and diversity measures. Column heading abbreviations are defined as Disturb=livestock disturbance gradient (low values are least disturbed), Abu=abundance (organisms/m3), Bio=biomass (mg/m3), S=family richness, H’=Shannon’s Diversity Index, and D=Simpson’s Diversity Index. Values in parenthesis represent ± 1 S.E.. ................................................................................ 21 Table 2.4. Summary of mean summer sweep abundance, biomass and diversity measures. Column heading abbreviations are defined as Disturb=livestock disturbance gradient (low values are least disturbed), Abu=abundance (organisms/m3), Bio=biomass (mg/m3), S=family richness, H`=Shannon’s Diversity Index, and D=Simpson`s Diversity Index. Values in parentheses represent ± 1 S.E.. ............................................................................... 22 Table 2.5. Summary of mean spring core abundance, biomass and diversity measures. Column heading abbreviations are defined as Disturb=livestock disturbance gradient (low values are least disturbed), Abu=abundance (organisms/m3), Bio=biomass (mg/m3), S=family richness, H`=Shannon’s Diversity Index, D=Simpson`s Diversity Index. Values in parentheses represent ± 1 S.E.. ........................................................................................... 23 Table 2.6. Summary of mean summer core abundance, biomass and diversity measures. Column heading abbreviations are defined as Disturb=livestock disturbance gradient (low values are least disturbed), Abu=abundance (organisms/m3), Bio=biomass (mg/m3), S=family richness, H`=Shannon’s Diversity Index, D=Simpson`s Diversity Index. Values in parentheses represent ± 1 S.E.. ........................................................................................... 24 Table 2.7. Significant spring and summer sweep abundance regressions with livestock disturbance as the independent variable alone or in combination with other environmental variables. Regression slopes are described as either positive (+) or negative (-). Only relationships with p <0.05 are shown. .................................................................................... 33 x Table 2.8. Significant spring sweep biomass regressions with livestock disturbance as the independent variable alone or in combination with other environmental variables. Regression slopes are described as either positive (+) or negative (-). Only relationships with p <0.05 are shown. .......................................................................................................... 34 Table 2.9. Significant spring and summer core abundance and summer core biomass regressions with livestock disturbance as the independent variable alone or in combination with other environmental variables. Regression slopes are described as either positive (+) or negative (-). Only relationships with p <0.05 are shown. ................................................. 35 xi GLOSSARY OF TERMS Benthic invertebrates: Aquatic invertebrates living on, or in, the bottom substrates of an aquatic habitat. Bioturbation: The restructuring of sedimentary deposits, as in a lake bottom or seabed, by living organisms (e.g., worms, clams) by activities such as burrowing, or ingestion or defecation of sediment grains. Depressional wetlands: Wetlands that occur in topographical depressions which allow the accumulation of surface waters. Diversity: A quantitative measure that reflects how many different types (e.g., invertebrate families) there are in a dataset and simultaneously takes into account the proportions of individuals or how evenly the individuals are distributed among those types. Endophytic ovipositor: An organism (e.g., damselfly) that uses a specialized abdominal organ (ovipositor) to insert its eggs into plant tissue. Lentic systems: Aquatic habitats situated in still fresh water. Lotic systems: Aquatic habitats situated in flowing fresh water. Nektonic invertebrates: Aquatic invertebrates living in the water column of an aquatic habitat, including those mobile organisms along the nekton/benthic (epibenthic) boundary and those found on aquatic plants (epi-phytic). Richness: A quantitative measure that reflects how many different types (e.g., invertebrate families) there are in a dataset. Latin and common names for the aquatic invertebrates examined in this study are listed in Appendix C. 1 CHAPTER 1. INTRODUCTION Wetlands throughout the world are being lost at an alarming rate (Zedler and Kercher 2005; Mitsch and Gosselink 2007). As wetland function and productivity are extremely valuable to society, conservation of these ecosystems is of utmost importance. In British Columbia’s (BC) southern interior, ranching operations use grassland and wetland areas to provide abundant forage and drinking water for domestic livestock. Impacts of livestock disturbance on wetland aquatic invertebrate communities have not been thoroughly examined in Canada (Hornung and Rice 2003; Foote and Rice Hornung 2005; Silver and Vamosi 2012), and research in BC is lacking from the primary literature. Concern has been expressed by government agencies, Ducks Unlimited Canada, local researchers and ranching operators over the effectiveness of best management practices and sustainable levels of livestock use (Bruce Harrison, pers. comm. 2007). Southern interior wetland biodiversity and productivity can be conserved by developing a better understanding of this complex relationship between wetlands and ranching practices. This chapter will discuss southern interior grassland and wetland ecosystems, livestock disturbance impacts on wetlands, aquatic invertebrates and how aquatic invertebrates can be used to assess wetland health. I will finish with an outline of my thesis objectives. Grassland Ecosystems British Columbia grasslands are rare on the landscape and occupy less than one percent of the land base (Wikeem and Wikeem 2004). Located in areas of the province where summers are hot and dry with little precipitation, provincial grasslands are in the northern reaches of the Great Basin shrub-steppe grasslands found in the western United States and Mexico (GCCBC 2011). Almost 90% of BC grasslands lie within the hot semi-arid southern interior region. Grasslands provide many recreational opportunities and are economically important to the beef cattle industry, which relies on them for forage. Water is limiting in BC grasslands (Tisdale 1947), and wetland habitats are often primary sources of water for both domestic and wild animals. 2 Wetland Ecosystems Wetlands are integral components of grassland ecosystems and critical to the survival of many organisms (Mitsch and Gosselink 2007). Generally defined as areas with hydric soils and hydrophytic vegetation, wetlands are highly variable in size, hydrology, water chemistry and geographic area (Rader 2001; MacKenzie and Moran 2004). Wetland ecosystems provide many important functional contributions to the environment and, thus, to society. Wetlands mitigate water quality by filtering sediments, nutrients and pollutants flowing from surface water, streams, rivers, lakes and ground water. They recharge ground water, provide relief from flood waters, reduce soil erosion, sequester carbon from the atmosphere, and provide habitat and forage for many wildlife species (Delesalle 1998, MOE 2004). Economically, wetlands provide many recreation opportunities such as fishing, hunting, and bird watching. They supply irrigation for agriculture operations, and water, shade and forage for livestock. Wetlands are under increasing pressures from development and, it is more important now than ever that we understand how to manage them for multiple users while maintaining the integrity of the resource for those wildlife dependent upon them. The depressional wetlands of BC’s southern interior occur as a mosaic throughout the grassland landscape and are similar to prairie pothole wetlands in terms of their ecology, climate and hydrology. They rely on rainwater or snow melt, have cycles of wet and dry years, exist in semi-arid climates with warm summers and cold winters and are usually fishless (Wikeem and Wikeem 2004). These shallow open water wetlands are dynamic productive ecosystems and can be further classified based on duration of flooding (Stewart and Kantrud 1971). Different durations of flooding create different vegetation communities, which in turn provide a variety of habitats and food resources for aquatic invertebrates and both terrestrial and aquatic vertebrates (Murkin and Ross 2000). In BC, 32 species at risk are among the 30% of wildlife dependent upon southern interior wetlands for survival (Delesalle 1998; Wikeem and Wikeem 2004). Many studies have examined the physical and chemical attributes and aquatic invertebrate communities in BC interior wetlands (e.g., Topping and Scudder 1977; Cannings and Scudder 1978; Cannings et al. 1980; Cannings and Cannings 1987); however, the effects of livestock grazing on these 3 ecosystems has yet to be explored. Poor management of livestock could potentially decrease habitat quality and quantity for all wetland users. Livestock Grazing Livestock ranching is a widespread land use within BC grasslands, and if poorly managed can be detrimental to wetland structure and function (Collins et al. 1998; Steinman et al. 2003). Livestock spend a disproportional amount of time in wetlands versus upland areas grazing submergent, emergent and shoreline vegetation, drinking, loitering and cooling off (Adams and Fitch 1998; Nader et al. 1998; Ganskopp 2001). Effects of livestock disturbance in wetland ecosystems can be both direct and indirect. Direct impacts include vegetation trampling and removal, and fecal and urine inputs which decrease water quality and reduce habitat availability (Coffin and Lauenroth 1988; Collins et al. 1998; Steinman et al. 2003). Cattle feces and urine decrease dissolved oxygen, vascular plant richness and percent cover and increase algal productivity in vernal pool mesocosm experiments (Croel and Kneitel 2011). Indirect effects result from shifts in vegetation communities which induce changes throughout higher trophic levels and affect wetland productivity (Rader and Richardson 1994; Dodson et al. 2005). Livestock-induced changes to wetlands have caused reductions in available cover and nesting habitat and food resources for waterfowl (Ryan et al. 2006). Aquatic Invertebrates As an important ecological link between primary production and higher trophic levels, aquatic invertebrates are a critical component of wetland food webs. In wetland ecosystems invertebrates are primary consumers affecting primary production through consumption of living vegetation as herbivores or consumption of plant and animal litter as detritivores (van der Valk 2012). They also are secondary consumers or predators, feeding on zooplankton, other aquatic invertebrates and small vertebrates (Hershey and Lamberti 2001; White and Roughley 2008). Aquatic invertebrates provide abundant food for secondary consumers and many vertebrates such as waterfowl are dependent on them. Several studies have demonstrated that waterfowl select wetland habitats based on 4 invertebrate densities (e.g., Murkin et al. 1982; Murkin and Kadlec 1986). Wetland invertebrates provide waterfowl with a crucial source of dietary protein (Krapu 1974) and inadequate invertebrate densities during the breeding season are known to reduce clutch size, egg viability and brood survivorship (Krapu 1981; Cox et al. 1998). Changes in abundance and diversity of aquatic macroinvertebrate communities can be useful in determining livestock impacts on wetland productivity and function due to their important contributions to wetland food webs. Our knowledge of livestock grazing impacts on aquatic invertebrates in wetland ecosystems in Canada is limited. Examinations of aquatic invertebrate communities are a well-documented method of assessing and monitoring aquatic resources. Biomonitoring studies have traditionally used aquatic invertebrates to examine the effects of anthropogenic activities on water and habitat quality in rivers and streams in North America (e.g., Hilsenhoff 1988; Rosenberg and Resh 1993; Barbour et al. 1999). The use of biomonitoring practices are wide ranging, examining the before and after effects of projects, activities or release of toxicants (e.g., Mackay and Heise 2007; Thomson et al. 2005; Johnson et al. 2015), compliance monitoring for release of pollutants into aquatic systems (e.g., Lowell and Culp 2002), and larger-scale studies to compare impacts of land use practices against unstressed reference condition sites (e.g., Bailey et al. 1998). Aquatic invertebrates have also been used to examine agricultural impacts on lotic systems including those of cattle grazing (e.g., Moore and Palmer 2005; Carlisle et al. 2008). More recently, biological assemblages have been employed to assess wetland function; however, relatively few studies have applied this technique to determine the impacts of livestock grazing (e.g., Steinman et al. 2003; Davis and Bidwell 2008). Canadian studies on wetland invertebrate assemblage response to grazing disturbance are rare. Alberta research has revealed that odonates (damselflies and dragonflies) could potentially be used as indicators of wetland health due to their close association with and dependence on wetland vegetation and the relative ease of their collection and identification (Hornung and Rice 2003, Foote and Rice Hornung 2005). 5 Thesis Objectives and Format The primary objective of this research was to examine the effects of livestock disturbance on BC’s southern interior wetland invertebrate communities. Wetland aquatic invertebrate community density and structure were analyzed in response to a gradient of livestock disturbance levels and environmental parameters. Overall predictions were that because of habitat loss and degradation 1) heavy livestock disturbance would decrease the richness and diversity of wetland aquatic macroinvertebrate communities and 2) zygopteran (damselfly) abundance and biomass would decrease with heavy levels of livestock grazing because these taxa have been described in Alberta studies as particularly sensitive to grazing-induced reductions in wetland vegetation. A secondary project objective was to characterize and provide baseline data on aquatic invertebrate densities and community composition in wetlands near Kamloops, BC. By examining a range of grazing intensities within four different areas on private and public lands, I expected to provide regionallyspecific recommendations for sustainable wetland use to local land managers. Chapter 2 describes the study design and the results of livestock grazing on wetland aquatic invertebrate communities. 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F. Charles, T. L. Nightengale, and D. M. Winter. 2005. Effects of removal of a small dam on downstream macroinvertebrate and algal assemblages in a Pennsylvania stream. Journal of North American Benthological Society 24:192-207. Tisdale, E. W. 1947. The grasslands of the Southern Interior of British Columbia. Ecology 28:346-382. Topping, M. S., and G. G. E. Scudder. 1977. Some physical and chemical features of saline lakes in central British Columbia. Syesis 10:145-149. van der Valk, A. G. 2012. The biology of freshwater wetlands. 2nd edition. Oxford University Press Inc., New York, NY. White, D. S. and R. E. Roughley. 2008. Aquatic Coleoptera. Pages 571-671 in Merritt, R. W., K. W. Cummins, and M. B. Berg (editors). An Introduction to the Aquatic Insects of North America. 4th edition. Kendall/Hunt Publishing Co., Dubuque, IA. 10 Wikeem B. and S. Wikeem. 2004. The Grasslands of British Columbia. Grassland Conservation Council of British Columbia. Kamloops, BC. Zedler, J. B. and S. Kercher. 2005. Wetland resources: status, trends, ecosystem services and restorability. Annual Review of Environment and Resources 30:39-74. 11 CHAPTER 2. EFFECTS OF LIVESTOCK GRAZING ON AQUATIC MACROINVERTEBRATES IN SOUTHERN INTERIOR WETLANDS OF BRITISH COLUMBIA, CANADA Introduction Depressional wetlands are common in the grasslands of British Columbia’s (BC) southern interior and are often used by free ranging livestock for forage and fresh water. Livestock spend a disproportional amount of time in wetlands versus upland areas grazing submergent, emergent and shoreline vegetation and drinking, loitering and cooling off (Adams and Fitch 1998; Nader et al. 1998). These livestock activities can decrease water quality with fecal and urine inputs, increase turbidity and decrease biodiversity by altering habitats and food resources for insects, amphibians, reptiles, waterfowl and other wildlife (Coffin and Lauenroth 1988; Collins et al. 1998; Steinman et al. 2003). Heavy livestock use may have negative consequences on the ecological condition and sustainability of these important ecosystems. Aquatic invertebrates play an important role in the trophic dynamics of aquatic systems. In wetlands they function as primary consumers, acting as detritivores on litter and herbivores on algae, as well as secondary consumers preying on zooplankton, other aquatic invertebrates, and small vertebrates (Pip 1978; Caldwell et al. 1980; Travis et al. 1985; Nelson et al. 1990; Wen 1992). Many benthic taxa also contribute to mixing of sediment particles and nutrient flux through bioturbation (Brönmark and Hansson 2002). Many vertebrates are drawn to wetlands for the abundant invertebrate food resources there. Aquatic invertebrates account for a large proportion of waterfowl diets (Krapu 1974), particularly during the breeding season (Swanson et al. 1985), and are crucial for waterfowl brood survival (Cox et al. 1998). Aquatic invertebrate communities are important contributors to the productivity and functioning of wetland ecosystems and compositional and density changes in them can be indicative of wetland impairment. 12 The use of aquatic invertebrates as bioindicators of water and habitat quality in lotic systems has long been in practice (e.g., Hilsenhoff 1988; Rosenberg and Resh 1993; Barbour et al. 1999) with many studies examining cattle impacts (e.g., Moore and Palmer 2005; Carlisle et al. 2008). The application of this technique in lentic wetlands has been a more recent development with relatively few studies focusing on livestock grazing as the disturbance (e.g. Steinman et al. 2003; Ausden et al. 2005; Davis and Bidwell 2008). Canadian studies examining invertebrate response to livestock disturbance in wetlands are rare and have been conducted only in Alberta and Manitoba. Manitoba studies examined the effects of cattail mowing (Neckles et al. 1990) and hydrologic changes to wetland aquatic invertebrates (Murkin and Ross 1999; Murkin and Ross 2000; Wrubleski 2005). Alberta studies have either focused on the effects of timing of grazing or specific taxon responses to cattle grazing and the disturbance it causes. Effects of rotational wetland grazing were examined by Silver and Vamosi (2012), who found that early grazed wetlands had lower abundance and diversity of invertebrates, as well as different common taxa than late grazed pastures. Cattle grazing caused a significant decrease in odonate abundance and reproductive effort by reducing vegetation height both within and adjacent to wetlands and a reduction in odonate species richness and diversity with complete vegetation removal (Hornung and Rice 2003; Foote and Rice Hornung 2005). To my knowledge, no published studies have examined livestock effects on BC’s southern interior depressional wetland invertebrate communities. The primary objective of this research was to clarify the ecological links between livestock disturbance and aquatic macroinvertebrate abundance, biomass and community composition in grassland wetlands of the southern interior of BC. I predicted that 1) heavy livestock disturbance would decrease the richness and diversity of wetland aquatic macroinvertebrate communities and 2) zygopteran abundance and biomass would decrease with heavy levels of livestock grazing. The results of my study will contribute to the primary literature, provide crucial regionally specific data and promote the implementation of effective management of these wetland resources. 13 Methods Study Area Seventeen wetlands were examined in four grassland areas near Kamloops (50˚40’N, 120˚20’W) in the southern interior of British Columbia, Canada: Campbell Range, Rose Hill, Hamilton Commonage and Lac Du Bois (Figure 2.1). These southern interior wetlands are situated in the Thompson Very Dry Warm Bunchgrass Variant (BGxw2) biogeoclimatic zone (Meidinger and Pojar 1991), and have an average annual precipitation of 270 mm (MOFR 2007). Wetlands ranged in area (0.35 to 2.30 ha), perimeter length (0.22 to 0.86 km), elevation (764 to 1227 m) and pH (7.66 to 10.64) across study areas (Appendix A). Conductivity values were highly variable across sites (950 to 11820 µS/cm) due to the seasonality and semi-permanence of these waterbodies. Study wetlands were selected based on: 1) an absence of salt tolerant plants; 2) their inclusion in the Ducks Unlimited Canada annual waterfowl survey routes (Bruce Harrison pers. comm. 2007); 3) that the wetlands examined provided a full range of grazing intensities. To control and limit effects not due to livestock grazing, efforts were made to avoid high salinity wetlands as the invertebrate communities are known to be different than those in wetlands with lower salinity (e.g., Cannings and Scudder 1978; Cannings et al. 1980). My highest conductivity value was below the 15000 - 45000 µS/cm range at which wetlands are considered subsaline or saline in the Alberta Wetland Classification System (AESRD 2014). High disturbance wetlands coincided with the high elevation wetlands. To account for elevational differences in emergency timing (i.e., temperature difference), sampling sessions began with low elevation sites and concluded with those wetlands found at higher elevations. Two of the study areas, Campbell Range and Rose Hill, are privately owned while the other two areas, Hamilton Commonage and Lac du Bois (2 sub-areas: Lac du Bois Bachelor and Lac du Bois Long Lake), are grazed under a Crown land lease agreement. Cattle are rotated from pasture to pasture in all study areas depending on the season, range Figure 2.1. Location of the four study areas (stars) near Kamloops, BC. (Map sources: Natural Resource Canada 2004; Google Maps 2014). 14 15 conditions and land parcel size. Ranches in the southern interior are mostly cow-calf operations; however, some yearling cattle and horse operations exist in some areas. Cattle are generally Herefords although other breeds occur in smaller numbers. Estimates of Livestock Disturbance A concurrent study examining impacts of livestock on wetland vegetation provided a grazing intensity or livestock disturbance gradient. The mean number of quadrat corners that intersected bare ground was measured at each wetland site and used as a surrogate for grazing intensity (Jones et al. 2011). Bare ground measurements were negatively correlated with vegetation biomass and positively correlated with soil bulk density and were an efficient way to quantify livestock disturbance. Photographs of wetlands with low and high disturbance levels are shown in Appendix B. Aquatic Invertebrate Sampling and Processing Aquatic invertebrates were sampled in 2008 over a two-week period in both early and midsummer to correspond with waterfowl nesting and brood rearing periods. All wetlands sampled were class 4 (Stewart and Kantrud 1971) based on the duration of flooding; this allowed the examination of wetlands with similar attributes and varying grazing pressures. Seventeen wetlands were sampled in spring (May/June) and 12 in the summer (July). Five dried up before the second sampling session in July. Conductivity and pH were recorded concurrently with invertebrate sampling at three locations on each wetland using an YSI multi-probe (YSI Inc., Yellow Springs, Ohio). Wetland invertebrate sampling sites were chosen by measuring perimeter of each wetland on a provincial online map provider (BCGov 2008) and then selecting random sampling points along the perimeter using a random number generator. Sample locations were plotted on the online map and GPS coordinates were obtained for each site. Three sweep and core samples were collected from each wetland during each sampling session. Sweep net samples of the nektonic community (including mobile epi-benthic and epi-phytic 16 organisms) were collected 2 metres from the wetted edge of the wetland using a 500 μm sweep net lowered to just above the substrate surface and rapidly pulled vertically to the water surface (Rader 2001; Merritt et al. 2008b). Water depth was measured at sweep sites and used in conjunction with the net area to determine the volume of water sampled; the number of organisms per cubic metre was then calculated. Core samples (5.1 cm diameter by 10.2 cm deep) were collected 2 metres from the wetland edge using a benthic hand corer (Swanson 1983; Rader 2001). Samples were placed in Whirlpak® bags filled with 70% ethanol for later processing. Invertebrates were sorted using a 3X power magnifying lamp. Microinvertebrates (e.g., cladocerans) were ignored in samples as the primary focus of this study was on the macroinvertebrate community. Aquatic invertebrates were identified using keys and descriptions from Merritt et al. (2008a) and Thorp and Covich (2001). Taxa collected and their common names are listed in Appendix C. Aquatic invertebrates were identified to the family level for insects (Orders Ephemeroptera, Trichoptera, Diptera, Coleoptera, Hemiptera, and Odonata), molluscs (Classes Gastropoda and Bivalvia) and macro-crustaceans (Order Amphipoda), while other aquatic groups were only identified to order or higher taxonomic levels. The large number of immature insect specimens prevented identification to genus or species. Identification keys usually require mature larvae for identification beyond the family level. Biomass was determined using taxon body length and length-mass regressions (Appendix D) from the literature where available, or specimens were dried and weighed. Dry mass was determined using M = a Lb, where M = mass, L = body length and a and b are constants (Smock 1980; Benke et al. 1999; Johnston and Cunjak 1999). When chironomid larval densities exceeded 100 individuals they were volumetrically subsampled in 500 ml of water using a Folsom plankton splitter (McEwen et al. 1954; Glozier et al. 2002). The subsampled chironomids were measured and multiplied by the proportion of the sample examined to obtain total chironomid biomass. Those taxa to be dried and weighed were separated into one of three categories: Gastropoda, Aquatic Others and Terrestrial Others. The Aquatic Others category consisted of aquatic Hydrachnidiae, Oligochaeta, Nematoda, Hirudinea, Bivalvia, Ostracoda, Collembola and pupae of various insect taxa. Terrestrial Others included Lepidoptera, Homoptera, terrestrial and semi-terrestrial Hemiptera, 17 Araneae, terrestrial Coleoptera, Hymenoptera, Thysanoptera, and adult Diptera, Ephemeroptera and Trichoptera. Taxa grouped into these three categories were transferred to pre-weighed aluminum pans and placed in a drying oven at 60°C for 24 h (Johnston and Cunjak 1999). The pans were removed from the oven and placed in a desiccator to cool (minimum of 1 hour) and then weighed to a constant mass (± 0.0001 g) on a microbalance. Dry weights were conservative estimates as the ethanol preservative results in some loss of body mass (Howmiller 1972; Johnston and Cunjak 1999). Richness and diversity indices were calculated at the family level for insects, molluscs, and macro-crustaceans and at higher taxonomic levels for all other aquatic invertebrate groups. Therefore, calculations were conservative and should be considered an underestimate of actual richness and diversity in the study wetlands. Shannon’s diversity index was used to determine the proportional diversity of wetland taxa (Shannon and Weaver 1949), and Simpson’s index was used as a measurement of equitability or evenness (Simpson 1949). Statistical Analysis All statistical analyses were conducted using the R statistical software program (R Development Core Team 2011). Only dominant and widespread taxa were used in analyses. Taxa that had >5% relative abundance/biomass (Steinman et al. 2003; Corcoran et al. 2009) in at least one wetland site and occurred in >50% of wetlands were used in analyses (Batzer et al. 2004). Dominant taxa were determined for abundance and biomass separately; they were also selected separately for the two different sampling methods (sweeps and cores). The inclusion of uncommon taxa in these analyses proved statistically problematic because of the presence of many zero values. Nonmetric multidimensional scaling (NMDS), an indirect ordination technique, was used to summarize associations among wetland invertebrate community composition and environmental variables. NMDS analysis groups similar sites based on dissimilarities in community composition and is robust enough to handle numerous zero values and non- 18 normal multivariate data (Clarke 1993). Ordinations were performed using a Bray-Curtis dissimilarity matrix using the metaMDS function in the vegan community ecology package for the R statistical software (Oksanen et al. 2011; R Development Core Team 2011). Analyses used random starting configurations and the number of dimensions used was determined by stress reduction using a scree plot (McCune and Grace 2002). Significant environmental variables were plotted on the ordinations as vectors so that their relationship with the invertebrate communities could be readily visualized. Stepwise linear regressions were explored in the examination of the relationship between the response variables (total abundance, total biomass, richness, diversity, and abundance and biomass of the most common taxa) and the explanatory variables (disturbance, wetland perimeter length, pH and conductivity). Data were transformed where required to meet the test assumptions of normal errors and homoscedasticity. Results Aquatic Invertebrate Community Structure The study documented 37 higher taxa of aquatic macroinvertebrates from nine classes, eleven orders and thirty-one families (Appendix C). This estimate is conservative as identification of insects was to order or family level and non-insect groups to order, class or phylum. Both spring sweep abundance and biomass had ten dominant taxa (>50% occurrence in all wetlands and >5% relative abundance in at least one wetland) (Table 2.1 and Table 2.2). Summer core abundance taxa contained fewer widespread taxa with only Oligochaeta, Ceratopogonidae and Chironomidae meeting the above criteria. Across all wetlands, sweep abundance was primarily dominated by dipterans and ostracods in the spring and dipterans in the summer (Appendix E, Figure E.1). Core abundance followed a similar pattern, with spring samples consisting primarily of dipterans and ostracods while summer core abundance had a large dipteran presence (Appendix E, Figure E.2). Spring sweep biomass had high proportions of zygopterans, whereas zygopterans, dipterans and gastropods were most prominent in summer sweeps (Appendix E, Figure E.3). Both spring 19 and summer core biomass was primarily composed of dipterans; however, when present, gastropods, trichopterans and zygopterans greatly contributed to the total biomass (Appendix E, Figure E.4). Abundance, biomass, richness and diversity were inconsistent among wetlands and seasons and variance amongst samples was often high (Tables 2.3-2.6). No consistent pattern of abundance, biomass, richness or diversity was found with livestock disturbance at a wetland site level. Summer sweeps had the greatest overall mean abundance (7.98 ± 5.09 organisms/m3) and biomass (3.13 ± 1.66 mg/m3) densities whereas spring sweeps had the lowest mean abundance (5.61 ± 2.75 organisms/m3) and spring cores the lowest mean biomass (1.40 ± 0.80 mg/m3) densities. Mean family richness (9.35 ± 1.59) and diversity (Shannon’s 1.27 ± 0.23; Simpson’s 0.58 ± 0.09) was greatest in spring sweep samples. Summer cores had the lowest family richness (3.56 ± 0.84) and diversity (Shannon’s 0.68 ± 0.17; Simpson’s 0.37 ± 0.09). Table 2.1. Dominant taxa for sweep and core abundance during spring and summer sampling sessions. Taxa were selected based on their presence in >50% of all wetlands and having >5% relative abundance in at least one wetland site. Sweep Abundance Spring Summer Ostracoda Ostracoda Oligochaeta Oligochaeta Gastropoda Ceratopogonidae Collembola Chironomidae Ceratopogonidae Dytiscidae Chironomidae Lestidae Dytiscidae Lymnaeidae Aeshnidae Lestidae Corixidae Core Abundance Spring Summer Ostracoda Oligochaeta Oligochaeta Ceratopogonidae Nematoda Chironomidae Ceratopogonidae Chironomidae Lestidae 20 Table 2.2. Dominant taxa for sweep and core biomass during spring and summer sampling sessions. Taxa were selected based on their presence in >50% of all wetlands and having >5% relative biomass in at least one wetland site. Sweep Biomass Spring Summer Gastropoda Hemiptera Ceratopogonidae Gastropoda Chironomidae Ceratopogonidae Dytiscidae Chironomidae Hydrophilidae Dytiscidae Libellulidae Aeshnidae Aeshnidae Coenagrionidae Coenagrionidae Lestidae Lestidae Limnephilidae Core Biomass Spring Summer Coleoptera Coleoptera Ceratopogonidae Ceratopogonidae Chironomidae Chironomidae Lestidae Ephydridae Table 2.3. Summary of mean spring sweep abundance, biomass and diversity measures. Column heading abbreviations are defined as Disturb=livestock disturbance gradient (low values are least disturbed), Abu=abundance (organisms/m3), Bio=biomass (mg/m3), S=family richness, H’=Shannon’s Diversity Index, and D=Simpson’s Diversity Index. Values in parenthesis represent ± 1 S.E.. Study Area Campbell Range Hamilton Commonage Lac Du Bois Batchelor Lac Du Bois Long Lake Rose Hill Mean Across All Sites Site Disturb Abu Bio S H' D 7 8 Mean 1.62 0.98 1.30 3.79 (1.44) 9.65 (3.69) 6.72 (2.57) 0.69 (0.17) 0.86 (0.18) 0.78 (0.17) 13.33 (2.33) 12.67 (0.88) 13.00 (1.61) 1.50 (0.46) 1.24 (0.26) 1.37 (0.36) 0.60 (0.18) 0.51 (0.11) 0.55 (0.14) 4.3 5 7.1 9 Mean 0.14 1.21 1.88 2.22 1.36 6.25 (2.81) 0.71 (0.44) 0.83 (0.16) 2.36 (0.85) 2.54 (1.07) 9.17 (5.60) 0.65 (0.63) 0.17 (0.05) 0.23 (0.12) 2.56 (1.60) 11.67 (1.86) 5.33 (2.60) 5.33 (0.88) 6.00 (1.53) 7.08 (1.72) 1.69 (0.19) 0.95 (0.50) 1.05 (0.03) 0.72 (0.27) 1.10 (0.25) 0.73 ( 0.05) 0.45 (0.23) 0.58 (0.01) 0.39 (0.16) 0.54 (0.11) 4 4.1 5 6.1 10 Mean 0.25 0.46 0.27 0.33 0.09 0.28 4.05 (1.62) 6.27 (4.32) 19.98 (12.25) 4.58 (2.65) 3.29 (1.76) 7.63 (4.52) 1.36 (0.57) 2.38 (0.22) 9.69 (4.10) 1.49 (1.13) 1.69 (0.86) 3.32 (1.37) 13.00 (1.00) 9.00 (1.53) 11.33 (1.20) 9.67 (1.20) 11.00 (1.00) 10.80 (1.19) 1.38 (0.13) 1.11 (0.13) 1.23 (0.15) 1.40 (0.22) 1.90 (0.12) 1.40 (0.15) 0.61 (0.04) 0.55 (0.07) 0.61 (0.08) 0.64 (0.09) 0.79 (0.04) 0.64 (0.07) 4.1 6.1 7 Mean 13.1 14 19 Mean 0.23 1.32 0.06 0.54 2.84 1.50 1.05 1.79 0.97 9.53 (4.05) 3.84 (1.70) 14.20 (6.89) 9.19 (4.21) 0.53 (0.32) 4.43 (1.30) 1.17 (0.50) 2.05 (0.70) 5.61 (2.75) 2.71 (1.16) 0.80 (0.25) 1.35 (0.33) 1.62 (0.58) 0.20 (0.13) 0.71 (0.29) 1.45 (1.06) 0.79 (0.49) 2.09 (0.99) 13.00 (3.51) 9.00 (2.08) 10.33 (1.20) 10.78 (2.27) 3.33 (0.88) 9.67 (2.19) 5.33 (1.20) 6.11 (1.42) 9.35 (1.59) 1.80 (0.04) 1.20 (0.17) 1.51 (0.21) 1.50 (0.14) 0.94 (0.13) 0.72 (0.36) 1.18 (0.45) 0.94 (0.31) 1.27 (0.23) 0.80 (0.01) 0.56 (0.07) 0.71 (0.06) 0.69 (0.04) 0.57 (0.03) 0.30 (0.18) 0.55 (0.20) 0.47 (0.14) 0.58 (0.09) 21 Table 2.4. Summary of mean summer sweep abundance, biomass and diversity measures. Column heading abbreviations are defined as Disturb=livestock disturbance gradient (low values are least disturbed), Abu=abundance (organisms/m3), Bio=biomass (mg/m3), S=family richness, H`=Shannon’s Diversity Index, and D=Simpson`s Diversity Index. Values in parentheses represent ± 1 S.E.. Study Area Site Disturb Abu Bio S H' D Hamilton Commonage 9 2.22 2.89 ( 1.95) 1.78 (1.10) 9.33 (2.33) 1.41 (0.16) 0.65 (0.08) 4 4.1 5 6.1 10 mean 0.25 0.46 0.27 0.33 0.09 0.28 2.79 (0.77) 22.27 (11.64) 20.94 (18.35) 1.20 (0.27) 2.80 (1.36) 10.00 (6.48) 3.44 (1.49) 8.80 (2.63) 5.53 (4.72) 1.06 (0.66) 2.51 (1.03) 4.27 (2.11) 6.67 (2.19) 8.33 (2.03) 8.33 (2.40) 7.33 (1.76) 6.33 (0.67) 7.40 (1.81) 0.72 (0.23) 0.63 (0.28) 0.52 (0.03) 1.25 (0.08) 1.04 (0.18) 0.83 (0.16) 0.34 (0.12) 0.29 (0.15) 0.23 (0.03) 0.61 (0.01) 0.52 (0.11) 0.40 (0.08) 4.1 6.1 7 mean 0.23 1.32 0.06 0.54 6.78 (1.89) 2.02 (0.65) 4.03 (1.46) 4.28 (1.33) 1.93 (0.86) 2.09 (0.90) 0.94 (0.17) 1.66 (0.64) 12.33 (0.67) 10.33 (1.45) 7.67 (1.20) 10.11 (1.11) 1.58 (0.13) 1.38 (0.28) 1.22 (0.27) 1.39 (0.23) 0.68 (0.05) 0.61 (0.11) 0.58 (0.12) 0.62 (0.09) 13.1 14 19 mean 2.84 1.50 1.05 1.79 26.28 (21.91) 1.59 (0.16) 2.20 (0.63) 10.02 (7.57) 8.12 (5.78) 0.54 (0.24) 0.85 (0.38) 3.17 (2.13) 7.67 (2.85) 10.00 (1.53) 8.33 (1.86) 8.67 (2.08) 0.83 (0.36) 1.42 (0.17) 1.13 (0.06) 1.12 (0.20) 0.38 (0.15) 0.65 (0.06) 0.55 (0.05) 0.53 (0.08) 0.89 7.98 (5.09) 3.13 (1.66) 8.56 (1.74) 1.09 (0.19) 0.51 (0.09) Lac Du Bois Batchelor Lac Du Bois Long Lake Rose Hill Mean Across All Sites 22 Table 2.5. Summary of mean spring core abundance, biomass and diversity measures. Column heading abbreviations are defined as Disturb=livestock disturbance gradient (low values are least disturbed), Abu=abundance (organisms/m3), Bio=biomass (mg/m3), S=family richness, H`=Shannon’s Diversity Index, D=Simpson`s Diversity Index. Values in parentheses represent ± 1 S.E.. Study Area Campbell Range Hamilton Commonage Lac Du Bois Batchelor Lac Du Bois Long Lake Rose Hill Mean Across All Sites Site Disturb Abu Bio S H' D 7 8 Mean 1.62 0.98 1.30 4.39 (1.46) 8.90 (4.00) 6.64 (2.73) 3.52 (3.22) 0.52 (0.29) 2.02 (1.76) 4.67 (0.33) 6.00 (0.00) 5.33 (0.17) 1.04 (0.03) 1.48 (0.02) 1.26 (0.03) 0.53 (0.04) 0.74 (0.01) 0.64 (0.03) 4.3 5 7.1 9 Mean 0.14 1.21 1.88 2.22 1.36 4.59 (2.13) 3.69 (1.28) 4.55 (1.05) 5.33 (2.70) 4.54 (1.79) 0.38 (0.13) 1.19 (0.90) 0.20 (0.05) 4.52 (4.25) 1.57 (1.33) 5.00 (2.31) 5.00 (0.58) 5.33 (0.88) 5.00 (1.15) 5.08 (1.23) 0.91 (0.49) 1.37 (0.08) 1.21 (0.11) 1.31 (0.14) 1.20 (0.21) 0.46 (0.24) 0.72 (0.02) 0.63 (0.04) 0.68 (0.03) 0.62 (0.08) 4 4.1 5 6.1 10 Mean 0.25 0.46 0.27 0.33 0.09 0.54 1.60 (0.43) 8.61 (4.73) 10.70 (0.62) 6.11 (0.42) 8.32 (5.43) 7.07 (2.33) 0.11 (0.03) 0.23 (0.16) 1.72 (0.56) 0.30 (0.12) 0.93 (0.35) 0.66 (0.25) 4.33 (0.33) 3.33 (0.88) 7.67 (1.20) 4.33 (0.88) 6.00 (0.58) 5.13 (0.78) 1.21 (0.04) 0.57 (0.34) 1.17 (0.02) 1.00 (0.19) 1.30 (0.31) 1.05 (0.18) 0.64 (0.04) 0.29 (0.19) 0.57 (0.04) 0.54 (0.10) 0.61 (0.15) 0.53 (0.10) 4.1 6.1 7 Mean 13.1 14 19 Mean 0.23 1.32 0.06 1.79 2.84 1.50 1.05 1.79 0.97 19.39 (8.53) 7.17 (1.21) 5.33 (2.02) 10.63 (3.92) 5.53 (0.93) 2.66 (0.29) 7.05 (0.64) 5.08 (0.62) 6.70 (2.23) 1.93 (0.93) 0.44 (0.22) 0.56 (0.22) 0.98 (0.46) 5.44 (0.86) 0.57 (0.34) 1.24 (0.94) 2.42 (0.72) 1.40 (0.80) 6.33 (1.20) 4.33 (0.88) 4.67 (0.33) 5.11 (0.81) 3.33 (0.33) 3.33 (0.33) 4.67 (0.88) 3.78 (0.52) 4.90 (0.77) 0.99 (0.31) 0.92 (0.11) 0.88 (0.23) 0.93 (0.22) 0.82 (0.09) 0.76 (0.19) 0.95 (0.09) 0.85 (0.13) 1.05 (0.17) 0.47 (0.16) 0.52 (0.07) 0.45 (0.14) 0.48 (0.12) 0.48 (0.08) 0.42 (0.12) 0.53 (0.00) 0.48 (0.07) 0.55 (0.09) 23 Table 2.6. Summary of mean summer core abundance, biomass and diversity measures. Column heading abbreviations are defined as Disturb=livestock disturbance gradient (low values are least disturbed), Abu=abundance (organisms/m3), Bio=biomass (mg/m3), S=family richness, H`=Shannon’s Diversity Index, D=Simpson`s Diversity Index. Values in parentheses represent ± 1 S.E.. Study Area Site Disturb Abu Bio S H' D Hamilton Commonage 9 2.22 3.61 (0.98) 8.70 (1.80) 5.00 (1.00) 1.13 (0.24) 0.56 (0.10) 4 4.1 5 6.1 10 mean 0.25 0.46 0.27 0.33 0.09 0.28 2.99 (1.05) 7.83 (2.24) 4.39 (1.17) 14.84 (6.00) 5.41 (3.20) 7.09 (2.73) 1.07 (0.89) 2.38 (1.00) 1.94 (0.50) 5.58 (3.86) 0.62 (0.23) 2.32 (1.30) 2.33 (0.33) 2.33 (0.88) 3.00 (0.58) 3.00 (0.58) 3.33 (0.33) 2.80 (0.54) 0.69 (0.05) 0.37 (0.21) 0.69 (0.11) 0.18 (0.04) 0.90 (0.06) 0.57 (0.10) 0.47 (0.02) 0.21 (0.11) 0.39 (0.04) 0.07 (0.02) 0.54 (0.04) 0.33 (0.05) 4.1 6.1 7 mean 0.23 1.32 0.06 0.54 13.57 (6.75) 2.75 (0.95) 5.74 (1.61) 7.35 (3.10) 2.81 (1.72) 1.20 (0.56) 2.24 (1.00) 2.08 (1.10) 6.00 (2.00) 3.33 (1.20) 3.67 (0.88) 4.33 (1.36) 0.86 (0.19) 0.68 (0.35) 0.67 (0.25) 0.74 (0.26) 0.43 (0.10) 0.36 (0.18) 0.35 (0.13) 0.38 (0.14) 13.1 14 19 mean 2.84 1.50 1.05 1.79 7.34 (2.17) 1.43 (0.23) 9.55 (3.46) 6.11 (1.95) 2.25 (0.92) 0.20 (0.10) 2.45 (1.26) 1.63 (0.76) 4.00 (1.00) 3.00 (0.58) 3.67 (0.67) 3.56 (0.75) 0.61 (0.09) 0.92 (0.26) 0.40 (0.20) 0.64 (0.18) 0.34 (0.06) 0.53 (0.14) 0.20 (0.12) 0.36 (0.11) 0.89 6.62 (2.48) 2.62 (1.15) 3.56 (0.84) 0.68 (0.17) 0.37 (0.09) Lac Du Bois Batchelor Lac Du Bois Long Lake Rose Hill Mean Across All Sites 24 25 Community Response to Disturbance The main impacts of livestock disturbance on wetland macroinvertebrate communities occurred primarily in the spring and affected those taxa found within the nektonic community. Livestock disturbance was significantly negatively correlated with spring sweep total abundance and total biomass (Figure 2.2). Significant negative associations were also found between livestock disturbance and spring sweep richness, Shannon’s diversity and Simpson’s diversity (Figure 2.3). The only significant benthic community response to livestock disturbance also included conductivity; both were negatively correlated with spring core richness (Table 2.9). In a few instances, regression models including both disturbance and conductivity were significantly correlated with wetland taxa (Tables 2.7-2.9). As most of these taxa also had significant relationships with disturbance alone, the models that included both environmental parameters were not confounded by the effects of conductivity but rather improved the model by explaining more of the variation. NMDS ordinations demonstrated distinct groupings of higher disturbance ponds versus lower disturbance ponds in cases where livestock disturbance was significantly correlated to the community composition. See Appendix F for NMDS ordination plots that include all environmental variables and Appendix G for NMDS correlation values for the environmental variables. The NMDS plot of spring sweep abundance (2 dimensional solution, stress of 10.3%) included disturbance (r2=0.486, p=0.008) as an environmental feature related to abundance of macroinvertebrates (Figure 2.4). The influence of livestock disturbance was evident as indicated by site separation within the plot. However, the effect of conductivity on the community composition, although not significant (r2=0.322, p=0.063), was apparent as disturbed site groupings were not always grouped according to disturbance alone. The ordination of summer sweep abundance (2 dimensional solution, stress of 13.3%; Figure 2.5) and summer core abundance communities (2 dimensional 26 solution, stress of 1.7%; Figure 2.6) showed a clear site separation based on livestock disturbance (r2=0.714, p=0.006; r2=0.534, p=0.035 respectively). Total abundance (log(x)+1) 3 (organisms/m ) a) 3.5 3.0 r2 = 0.464 p = 0.003 2.5 2.0 1.5 1.0 0.5 0.0 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Livestock disturbance b) Total biomass (boxcox) (mg/m3) 3 2 r2 = 0.728 p<0.001 1 0 -1 -2 -3 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 Livestock disturbance (log(x)+1) Figure 2.2. Linear relationship between livestock disturbance and a) spring sweep total abundance and b) spring sweep total biomass. Livestock disturbance represents the mean # of quadrat corners that intersected bare ground at each wetland (Jones et al. 2011). Dotted lines represent 95% confidence intervals. 27 b) a) 2.0 r2=0.462 p=0.003 1.2 r2=0.569 p<0.001 1.8 1.6 1.1 Family H' Family richness (log(x)+1) 1.3 1.0 0.9 1.4 1.2 1.0 0.8 0.8 0.7 0.6 0.4 0.6 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 Livestock disturbance (log(x)+1) Livestock disturbance (log(x)+1) c) 0.9 r2=0.385 p=0.008 0.8 Family D 0.7 0.6 0.5 0.4 0.3 0.2 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Livestock disturbance Figure 2.3. Linear relationship between livestock disturbance and spring sweep a) family richness, b) Shannon’s family-level diversity (H’) and c) Simpson’s family-level diversity (D). Livestock disturbance represents the mean # of quadrat corners that intersected bare ground at each wetland (Jones et al. 2011). Dotted lines represent 95% confidence intervals. 1.0 28 Les Chi Aes B5 0.0 NMDS2 0.5 B4 L7 Cer H9 B10 L4.1 B4.1 Oli R19 B6.1 L6.1 H5 Ost -0.5 Dyt Cor C8 H7.1 H4.3 -1.0 R13.1 R14C7 Gas Bol -1.5 -1.0 -0.5 0.0 Disturb 0.5 1.0 1.5 NMDS1 Figure 2.4. Nonmetric multidimensional scaling (NMDS) ordination (stress=10.3%) of spring sweep abundance dominant taxa community structure with overlay of fitted vector representing the significant (r2=0.486, p=0.008) environmental variable livestock disturbance (Disturb). Wetland site (in red) disturbance level is represented by a continuum with large circles being most disturbed and dots representing least disturbed sites. Taxa (in black) are as follows: Aes=Aeshnidae, Bol=Collembola, Cer=Ceratopogonidae, Chi=Chironomidae, Cor=Corixidae, Dyt=Dytiscidae, Gas=Gastropoda, Les=Lestidae, Oli=Oligochaeta, and Ost=Ostracoda. 29 Lym Disturb B5 0.5 R13.1 H9 L6.1 Chi 0.0 NMDS2 Dyt Cer B4.1 Ost -0.5 L4.1 B6.1 B10 B4 Les R19 R14 L7 Oli -1.0 -0.5 0.0 0.5 NMDS1 Figure 2.5. Nonmetric multidimensional scaling (NMDS) ordination (stress=13.3%) of summer sweep abundance dominant taxa community structure with overlay of fitted vector representing the significant (r2=0.714, p=0.006) environmental variable livestock disturbance (Disturb). Wetland site (in red) disturbance level is represented by a continuum with large circles being most disturbed and dots representing least disturbed sites. Taxa (in black) are as follows: Cer=Ceratopogonidae, Chi=Chironomidae, Dyt=Dytiscidae, Les=Lestidae, Lym=Lymnaeidae, Oli=Oligochaeta, and Ost=Ostracoda. 1.0 30 Chi R19 L7B4.1 B5 L4.1 0.0 NMDS2 0.5 B6.1 L6.1 R13.1 H9 Cer -0.5 R14 Oli B10 B4 0.5 1.0 Disturb -1.5 -1.0 -0.5 0.0 NMDS1 Figure 2.6. Nonmetric multidimensional scaling (NMDS) ordination (stress=1.74%) of summer core abundance dominant taxa community structure with overlay of fitted vector representing the significant (r2=0.534, p=0.034) environmental variable livestock disturbance (Disturb). Wetland site (in red) disturbance level is represented by a continuum with large circles being most disturbed and dots representing least disturbed sites. Taxa (in black) are as follows: Cer=Ceratopogonidae, Chi=Chironomidae, Oli=Oligochaeta. 31 Individual Taxa Response to Livestock Disturbance Livestock disturbance was an important factor influencing Odonata at the suborder and family levels. Zygoptera (damselfly) spring sweep abundance and biomass were both significantly negatively correlated with livestock disturbance (Figure 2.7). One of the two zygopteran families found in spring sweeps, the Lestidae, followed a similar trend with a significant decrease in abundance and biomass as disturbance levels increased (Figure 2.7). Both spring sweep Lestidae abundance and biomass had significant negative associations with a combination of livestock disturbance and perimeter length (Table 2.7-2.8). Both Zygoptera and Lestidae spring core abundance were negatively correlated with livestock disturbance (Table 2.9). In spring sweeps, Aeshnidae (a dragonfly family) abundance was the only positive association with livestock disturbance. Sweep samples containing the families Dytiscidae (Coleoptera), Chironomidae (Diptera), and Ceratopogonidae (Diptera) were negatively affected by heavy levels of livestock disturbance (Table 2.7-2.8). Dytiscid abundance was negatively correlated with livestock disturbance in spring but positively associated in summer (Table 2.7). Spring sweep chironomid abundance decreased as livestock disturbance increased (Table 2.7). Ceratopogonid summer abundance was negatively correlated with livestock use (Table 2.7). Spring biomass of both Chironomidae and Ceratopogonidae had negative relationships with livestock disturbance (Table 2.8). Core samples had few significant relationships with livestock disturbance (Table 2.9). Summer core Ceratopogonidae abundance and biomass were negatively associated with high levels of grazing. In summer, livestock disturbance significantly increased Oligochaeta core abundance. Significant linear relationships with environmental variables other than livestock disturbance can be found in Appendix H. 32 b) 0.6 0.5 Zygoptera biomass (boxcox) 3 (mg/m ) Zygoptera abundance (boxcox) 3 (organisms/m ) a) r2=0.593 P<0.001 0.4 0.3 0.2 0.1 0.0 0.0 0.1 0.2 0.3 0.4 0.5 0.6 1.0 r2=0.513 p=0.001 0.8 0.6 0.4 0.2 0.0 0.7 0.0 Livestock disturbance (log(x)+1) 1.0 1.5 2.0 2.5 3.0 Livestock disturbance c) d) 0.5 Lestidae biomass (boxcox) 3 (mg/m ) Lestidae abundance (boxcox) 3 (organisms/m ) 0.5 r2=0.457 p=0.003 0.4 0.3 0.2 0.1 0.8 r2=0.379 p=0.008 0.6 0.4 0.2 0.0 0.0 0.0 0.1 0.2 0.3 0.4 0.5 0.6 Livestock disturbance (log(x)+1) 0.7 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 Livestock disturbance (log(x)+1) Figure 2.7. Linear relationship between livestock disturbance and spring sweep a) Zygoptera abundance b) Zygoptera biomass c) Lestidae abundance and d) Lestidae biomass. Livestock disturbance represents the mean # of quadrat corners that intersected bare ground at each wetland (Jones et al. 2011). Dotted lines represent 95% confidence intervals. Table 2.7. Significant spring and summer sweep abundance regressions with livestock disturbance as the independent variable alone or in combination with other environmental variables. Regression slopes are described as either positive (+) or negative (-). Only relationships with p <0.05 are shown. Sampling Period Dependent Variable Independent Variable(s) Spring Coleoptera Dytiscidae Summer F df p r2 Adj. r2 Disturbance Slope - 8.60 15 0.010 0.364 0.322 Disturbance - 9.13 15 0.009 0.378 0.337 Lestidae Disturbance + Perimeter -&- 10.29 14 0.002 0.595 0.537 Aeshnidae Disturbance + 12.51 15 0.003 0.455 0.418 Hemiptera Disturbance + Conductivity -&- 10.17 14 0.002 0.592 0.534 Hemiptera Disturbance - 5.56 15 0.032 0.271 0.222 Corixidae Disturbance + Conductivity -&- 10.17 14 0.002 0.592 0.534 Diptera Disturbance - 9.99 15 0.006 0.400 0.360 Chironomidae Disturbance - 6.77 15 0.020 0.311 0.265 Dytiscidae Disturbance + 10.20 10 0.010 0.505 0.456 Ceratopogonidae Disturbance - 8.49 10 0.015 0.459 0.405 33 Table 2.8. Significant spring sweep biomass regressions with livestock disturbance as the independent variable alone or in combination with other environmental variables. Regression slopes are described as either positive (+) or negative (-). Only relationships with p <0.05 are shown. Sampling Period Spring Dependent Variable Independent Variable(s) F df p r2 Adj. r2 Diptera Disturbance Slope - 17.50 15 <0.001 0.538 0.508 Ceratopogonidae Disturbance+Conductivity -&- 9.79 14 0.002 0.583 0.524 Ceratopogonidae Disturbance - 10.08 15 0.006 0.402 0.362 Chironomidae Disturbance - 15.49 15 0.001 0.508 0.475 Aeshnidae Disturbance+Conductivity -&+ 7.27 14 0.007 0.510 0.440 Lestidae Disturbance+Perimeter -&- 7.89 14 0.005 0.530 0.463 34 Table 2.9. Significant spring and summer core abundance and summer core biomass regressions with livestock disturbance as the independent variable alone or in combination with other environmental variables. Regression slopes are described as either positive (+) or negative (-). Only relationships with p <0.05 are shown. Sampling Period Dependent Variable Independent Variable(s) Slope F df p r2 Adj. r2 Zygoptera Disturbance - 18.86 15 <0.001 0.557 0.528 Lestidae Disturbance - 6.13 15 0.026 0.290 0.243 Richness Disturbance + Conductivity -&- 3.79 14 0.048 0.351 0.259 Ceratopogonidae Disturbance - 8.62 10 0.015 0.463 0.409 Oligochaeta Disturbance + 10.92 10 0.008 0.522 0.474 Oligochaeta Disturbance + Conductivity +&- 7.97 9 0.010 0.639 0.559 Disturbance - 8.65 10 0.015 0.464 0.410 CORE ABUNDANCE Spring Summer CORE BIOMASS Summer Ceratopogonidae 35 36 Discussion Aquatic Invertebrate Community Response The results of this study indicate that high levels of livestock grazing negatively affects the aquatic macroinvertebrate assemblages in local wetlands by reducing the total abundance, total biomass, taxa richness and diversity of these communities. Strongest relationships were observed within nektonic communities during the spring, although benthic and summer patterns also emerged. NMDS ordinations showed significant associations amongst macroinvertebrate community composition and livestock disturbance while regression analyses indicated heavy disturbance to be an important factor in reducing both total abundance and biomass, and family richness and diversity. The literature both supports and refutes these findings and shows the spatial and temporal variability of aquatic invertebrate response to livestock disturbance. Wetland richness and diversity were anticipated to decrease with increasing livestock disturbance because of the reduction of submerged and emergent vegetation and the elevation of nutrients resulting in increased primary production. Higher productivity is often associated with decreased diversity (Jeppesen et al. 2000). My results are corroborated by Ausden et al. (2005), who found species richness was significantly reduced by cattle grazing in United Kingdom fens. Furthermore, a Kansas study found family richness was greater in control than in grazed treatments although no difference in diversity was detected (Kostecke et al. 2005). In sharp contrast to my study, Marty (2005) reported higher aquatic invertebrate richness in grazed versus ungrazed Californian vernal pools. Similarly, Davis and Bidwell (2008) found both benthic and nektonic richness and benthic diversity were greatest in grazed treatments in Nebraska. Steinman et al. (2003) discovered that although invertebrate richness and diversity varied in the two vegetation types present in their south-central Florida wetlands, cattle grazing did not have any effect on the aquatic invertebrate community. Similar patterns of geographic heterogeneous response to 37 livestock disturbance were also evident with total abundance and biomass of macroinvertebrates. Total macroinvertebrate abundance and biomass decreased in the presence of high livestock disturbance. I had expected a compositional shift in wetland taxa under heavy grazing pressure but had surmised this would not necessarily reduce the number or biomass of wetland macroinvertebrates present. McAbendroth et al. (2005) found high invertebrate biomass was correlated with high vegetation complexity and suggested habitat complexity may control invertebrate biomass in wetlands. In my study, decreased wetland vegetation complexity and structure resulting from heavy grazing is supported by a concurrent study examining grazing impacts on wetland vegetation (Jones et al. 2011). Other projects have recorded varying abundance and biomass response to livestock disturbance. In Florida, simulated grazing in depressional freshwater marshes decreased macroinvertebrate abundance (Morrison and Bohlen 2010). In contrast, Davis and Bidwell (2008), found total biomass was greater in grazed than in reference wetlands; however, the opposite was true the following year, with reference wetlands having greater biomass of macroinvertebrates than the grazed treatments. The high degree of disagreement across, and even within, studies suggests that regional differences, such as local climate, geology and elevation may prevent detailed comparison of wetland communities (Batzer et al. 2005). Zygoptera Response Spring sweep biomass was dominated by zygopterans and heavy levels of livestock grazing reduced Zygoptera biomass and abundance at the suborder and family (Lestidae) level. These results were no surprise due to the connection between wetland vegetation and Zygoptera habitat requirements (Hornung and Rice 2003). Lestes is the only genus of Lestidae found in British Columbia and many species of Lestes are specialists of temporary wetlands (Cannings 2002). Most Zygoptera are obligate endophytic ovipositors that lay their eggs in emergent as in the case of Lestes, and submergent vegetation within wetlands (Duffy 1994; Cannings 2002). Macrophytes are utilized by larval stages for foraging, refugia and emergence. This reliance on vegetation makes them susceptible to livestock 38 grazing within, and adjacent to, aquatic habitats. Also, Lestes eggs laid in emergent stems may be eaten along with the plants in spring and summer. Vegetation in heavily grazed sites was completely lacking or, if present, was sparse and/or reduced in height and did not have the visual habitat features adult zygopterans prefer and require (Corbet 1999; Bernath et al. 2002). Foote & Hornung (2005) proposed that vegetation height is also important for wind protection, as zygopterans are not strong flyers and wind refugia may be a critical structural habitat requirement. My study supports this as plant communities within my study wetlands shifted from tall and rhizomatous species to shorter-lived, smaller species in the presence of increased grazing (Jones et al. 2011). Other Taxa Response to Disturbance Not surprisingly, Diptera, because of their rapid reproductive rate, a terrestrial adult stage, and the ability of the larvae of many species to extract oxygen from the atmosphere, are a common and often a dominant taxon present in wetlands (King and Richardson 2002). Within the Diptera, the family Chironomidae usually makes the highest contribution to invertebrate abundance in wetlands (Wrubleski 1987; Batzer et al. 2001). This is supported in my study by both the benthic and nektonic communities. Diptera, primarily family Chironomidae, and Ostracoda were the most abundant macroinvertebrate orders in spring; in summer, the Diptera were the most abundant. Morrison and Bohlen (2010) found that Diptera abundance increased when vegetation was clipped and removed to simulate grazing. Contrary to their results, I found that spring nekton Diptera and chironomid abundance and biomass decreased with heavy grazing. However, chironomids in the spring benthic community responded positively to higher levels of grazing. Given that my taxonomic resolution was to family only, I suggest that different genera or species residing in the benthos versus in the nekton were responsible for this difference. Benthic taxa are more tolerant of anoxic conditions resulting from eutrophication and increased turbidity (Campbell et al. 2009), and would be expected to be less affected by livestock presence. The absence of relationships between summer sweep and core dipteran abundance and richness might be due to the absence of chironomid collected because of emergence timing. 39 The relationship between Dytiscidae abundance and livestock disturbance was negative in the spring but positive in the summer. Dytiscid beetles collected in spring were primarily larvae which depend upon wetland vegetation for hunting prey and require contact with the surface to obtain atmospheric oxygen (Resh et al. 2008). During this time, larval dytiscids would be more vulnerable to vegetation removal and trampling, and agitation of the water surface by livestock. In the absence of fish and birds, Odonata (Suborders Anisoptera and Zygoptera), Dytiscidae and Hemiptera are the top predators of macroinvertebrates in semipermanent wetlands, and are usually speciose and numerous in these wetland ecosystems (Batzer and Wissinger 1996). I speculate that as livestock disturbance increases and zygopterans declined as a result, dytiscid abundance may have increased due to reduced competition for prey and resources. Study limitations As invertebrate communities are highly variable in time and space, my study, because of low sampling frequency and intensity, may have failed to find some potential relationships caused by livestock disturbance. Miller et al. (2008) suggest that within-year temporal shifts in the community dynamics may result in misconstrued and unreliable data. Two sampling sessions may have been insufficient to accurately portray all effects of livestock on macroinvertebrates. Within-wetland abundance and biomass variability was often high. Downing (1991) noted that the structural heterogeneity of wetland habitats causes patchy aggregations of macroinvertebrates. To alleviate this sampling problem, King and Richardson (2002) suggest that aggregate samples from more than one habitat are most accurate in quantifying the community and recording rare taxa. More intensive sampling of each wetland would give a better picture of the invertebrate community and help to determine whether taxa collected were in fact rare or only captured in low numbers due to low sampling effort. More intensive sampling would also potentially allow for genera or species analyses, which probably would provide more insight into livestock effects. Family level analyses may not be sufficient to detect most responses to livestock impacts (King and Richardson 2002). I was unable to conduct statistical analyses using genera or 40 species because of the many immature specimens (difficult or impossible to identify past family level) and the many zero observations in my data set. Management Recommendations Sweep sampling appears to give clearer results than core sampling. For resource managers, this collection method is usually a more efficient technique, requiring less sample processing time than core samples. Although more expensive, the analysis of the biomass of aquatic macroinvertebrates, and not just abundance alone, should be explored in these wetland systems. Biomass characterizes food web energy flow of these important prey items more accurately than abundance alone, thus providing better insight into wetland trophic dynamics and the effects of disturbance. Resource managers should recommend range use plans that include only light grazing regimes and limit livestock access to wetlands. My data indicate that aquatic macroinvertebrates could potentially be used to indicate heavy levels of livestock disturbance; such information would assist resource managers in monitoring for wetland impairment. Specifically, damselflies (Odonata: Zygoptera) at the suborder level or family level (Zygoptera: Lestidae) show promise as a bioindicator of heavy levels of livestock use in British Columbia`s southern interior wetlands. Resource managers would be prudent to include zygopterans in any index developed to assess wetland condition. Conclusion High intensity livestock grazing in southern interior wetlands is reducing total abundance, biomass, richness and diversity of aquatic macroinvertebrates. My study is the first to examine the impact of free-range livestock practices on macroinvertebrates in BC southern interior wetlands, but further study is required to fully understand the consequences of this wide spread disturbance. Future work should examine annual patterns of abundance, biomass, richness and diversity to produce a better understanding of the temporal variability of these systems. 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CONCLUSION Research Summary My research objectives were to characterize wetland macroinvertebrate communities in the southern interior of British Columbia and to determine their response to a gradient of livestock grazing disturbance. As predicted, 1) macroinvertebrate richness and diversity decreased with higher levels of grazing as did 2) zygopteran, specifically Lestidae, abundance and biomass. In addition, total macroinvertebrate abundance and biomass decreased as grazing intensity increased. As a vital link between producers (algae and macrophytes) and higher trophic links in wetlands (Batzer and Wissinger 1996), invertebrate response to heavy livestock use may have large-scale consequences not only for the aquatic macroinvertebrate assemblages, but the entire ecosystem. Challenges of Wetland Invertebrate Research and Future Research Directions My study provides baseline knowledge of southern interior wetland macroinvertebrate assemblages and contributes to the primary literature on the response of these communities to livestock grazing disturbance. As with most ecological studies, there were limitations to my study due to finite resources and time constraints. Low sampling effort and intensity, and the lack of identifications at genus and species levels, may have prevented the discovery of more detailed associations between livestock grazing and wetland invertebrate communities. Wetland macroinvertebrate distributions vary spatially and temporally. The complexity of wetland habitat structure results in patchy taxon distributions (Downing 1991) and requires intensive sampling to thoroughly sample invertebrate communities. Sampling wetland invertebrates is relatively easy; however, extraction of specimens from sediments and debris can be laborious, time consuming and consequently expensive. Accurate identification of specimens is the most difficult task of all. To adequately compare livestock effects across a range of grazing intensities required examination of a large number of wetlands. Due to the length of time required to process samples, I was able to 50 collect only three samples per sampling device in each wetland. This restricted the statistical analyses of many taxa due to their scarcity in samples. I could not determine whether some taxa were rare in the study wetlands or were simply not captured. Future research should address this problem by collecting aggregate samples from many different habitats within a wetland and subsampling (King and Richardson 2002) to improve the diversity of taxa collected and to determine which taxa are, in fact, rare. Although I sampled during the spring and summer, temporal differences in community assemblages may have been missed. Miller et al. (2008) caution that within-year temporal differences in invertebrate community response to gradients of disturbance may be unreliable if sampling has occurred over periods of greater than 15 days. Budgetary limitations prevented us from sampling more than twice. The inclusion of more sampling sessions would potentially have allowed genus or species level identifications, because larger numbers of mature larvae (more readily identified than immature ones) probably would have been collected. King and Richardson (2002) suggest that family level identification may not be adequate as wide ranging disturbance tolerances of species within families may result in misinterpretation of family level data. Future studies should attempt to sample over many intervals throughout the year to provide a temporal baseline of wetland invertebrate densities and composition. This would help alleviate concerns regarding the interpretation of environmental disturbance impacts on invertebrate communities. Despite some sampling inadequacies and only moderate taxonomic resolution, I was able to show clear effects of livestock disturbance on wetland macroinvertebrates. These differences were detected at both the community level and, in the case of zygopterans, at the family level. Management Implications Range and wildlife managers face challenges in balancing economic feasibility with best management practises for wetland and upland areas. In BC’s grasslands there is no formal 51 legislation for protection of depressional wetlands; however, livestock grazing is managed through the use of best management practices (BMPs) (MFLRNO 2015). Grazing within Crown range is allocated through the province’s Range Program which requires tenure and lease holders to develop prescriptive Range Use Plans (RUP) or Range Stewardship Plans. Livestock grazing on private land relies on landowners to employ BMPs and conduct their operations with consideration for what best suits their livelihood and the environment. This can often be difficult for smaller operators as indicated by the range of grazing disturbance within my study. With one exception, study wetlands located within Crown land in Lac du Bois Provincial Park were all grazed at the low end of the livestock grazing gradient whereas many of the wetlands on private land were in the middle or in the upper end of the gradient. The negative effects of livestock grazing can be avoided by following an adaptive management plan that includes the four principals of range management: distribution, use level, rest and time and duration of grazing (Fraser 2013). Should adverse livestock grazing effects become evident, RUPs can be adapted to effectively mitigate further impacts. Tenure and lease holders are encouraged to assess their land management practices, and are given online brochures and training by the provincial ministry (BCMFR 2006). Overgrazing of riparian areas is often an issue of livestock distribution due to livestock’s affinity for wetland versus upland areas (Ganskopp 2001). In many cases, it is more cost-effective for managers either to completely fence off wetland areas and provide off-site water or use fencing to limit livestock access, rather than reducing stocking densities to compensate for over-usage (Stillings et al. 2003). Aquatic invertebrate research is important to the understanding and management of wetland ecosystems in southern interior grasslands. North America studies show highly variable responses of ecosystems to livestock disturbance, suggesting regionally specific studies are necessary to characterize communities and their response. My study provides regionally specific data on macroinvertebrate community assemblages and shows that aquatic invertebrates respond to high levels of livestock disturbance in wetlands. Managers 52 should consider aquatic macroinvertebrates as an assessment tool for determining sustainable levels of livestock grazing in wetlands. The development of regional indices of biological integrity would allow the establishment of long-term monitoring programs. Zygoptera and perhaps Lestidae should be included as a metric as they respond strongly to the removal of vegetation during heavy grazing. Recommendations Based on the findings of this study, I propose two recommendations that will improve monitoring and management of southern interior wetlands to sustain and conserve them for wildlife and the ranching community. My first recommendation is for provincial ministries to consider developing an index of biological integrity to monitor and prevent impairment of regional wetlands. Nektonic communities showed a stronger response to heavy grazing than benthic communities, and if rapid assessment is the goal of land or wildlife managers, research should focus on sweep sampling as a monitoring method. Due to their clear response to high livestock disturbance, the damselfly suborder Zygoptera should be used as a possible indicator taxon. Secondly, southern interior ranchers should adopt only light grazing in local wetlands. This can be achieved by limiting the time livestock spend at each wetland and associated riparian area with rest rotation grazing cycles. Fencing and/or off-site watering stations should also be implemented to limit livestock access to wetlands. Crown land managers should ensure that ranchers are closely adhering to the principles outlined in their RUPs and should monitor for compliance to ensure plans are effective at preventing or reducing livestock damage to grasslands and wetland areas. Regulatory agencies should establish a working relationship with private ranches and farms to promote stewardship and assist in the development of sustainable livestock grazing management plans that protect wetlands found on private properties. 53 Literature Cited Batzer D. P. and S. A. Wissinger. 1996. Ecology of insect communities in non-tidal wetlands. Annual Review of Entomology 41:75–100. British Columbia Ministry of Forests and Range (BCMFR). 2006. A methodology for monitoring Crown range. Range Branch, Kamloops, BC. Rangeland Health Brochure [10] draft. Downing, J. A. 1991. The effect of habitat structure on the spatial distribution of freshwater invertebrate populations. Pages 87-119 in S. S. Bell, E. D. McCoy, and H.R. Mushinsky (editors). Habitat structure: the physical arrangement of objects in space. Chapman and Hall, New York, NY. Fraser, D. 2013. The four principles of range management. BC Ministry of Forests, Lands and Natural Resource Operations, Range Branch. Rangeland Health Brochure 13. Available from http://www.for.gov.bc.ca/hra. [accessed Jan 2015]. Ganskopp, D. 2001. Manipulating cattle distribution with salt and water in large arid-land pastures: a GPS/GIS assessment. Applied Animal Behaviour Science. 73:251-262. King, R. S. and C. J. Richardson. 2002. Evaluating subsampling approaches and macoinvertebrate taxonomic resolution for wetland bioassessment. Journal of the North American Benthological Society 21(1):150-171. Miller, A. T., M. A. Hanson, J. O. Church, B. Palik, S. E. Bowe and M. G. Butler. 2008. Invertebrate community variation in seasonal forest wetlands: implications for sampling and analyses. Wetlands 28(3):874-881. Ministry of Forests, Lands and Natural Resource Operations (MFLNRO). 2015. Range Branch, BC Government Rangeland Management. Available from http://www.for.gov.bc.ca/hra. [accessed Jan 2015]. Stillings, A. M., J. A. Tanaka, N.R. Rimbey, T. Delcurto, P. A. Momont and M. L. Porath. 2003. Economic implications of off-stream water developments to improve riparian grazing. Journal of Range Management 56:418-424. APPENDIX A. Physical Data Table A.1. UTM coordinates, elevation, area, perimeter length, mean pH and mean conductivity values for wetlands in spring (May/June) and summer (July), 2008 (n=3). Study Area Campbell Range Hamilton Commonage Lac Du Bois Bachelor Lac Du Bois Long Lake Rose Hill UTM Coordinates (NAD 83) Elevation (m) Area (ha) Perimeter Length (km) 7 10: 708561, 5604710 1076 1.20 8 10: 707444, 5606570 1099 4.3 10: 683727, 5553621 Wetland pH Conductivity (µS/cm) June July June July 0.43 7.68 wetland dry 2401 wetland dry 1.30 0.47 9.59 wetland dry 1384 wetland dry 1168 0.85 0.42 8.87 wetland dry 2906 wetland dry 5 10: 685113, 5552865 1196 2.30 0.86 9.94 wetland dry 3343 wetland dry 7.1 10: 683129, 5550460 1197 1.40 0.63 10.52 wetland dry 3152 wetland dry 9 10: 683646, 5549430 1227 1.50 0.73 8.65 10.35 1842 2481 4 10: 681244, 5627504 784 0.38 0.34 8.67 9.15 9144 11820 4.1 10: 681094, 5627892 798 0.44 0.38 8.60 8.81 5604 8571 5 10: 681013, 5628073 816 0.35 0.23 8.39 9.40 3098 3686 6.1 10: 680559, 5628828 861 0.43 0.28 8.67 9.70 4044 4705 10 10: 679933, 5632183 936 0.37 0.22 9.00 10.64 1947 1613 4.1 10: 682899, 5631165 764 1.10 0.50 8.63 9.06 1088 952 6.1 10: 683235, 5630800 811 0.31 0.22 8.66 9.15 6581 9538 7 10: 683804, 5630309 855 1.50 0.70 8.13 8.77 3179 3491 13.1 10: 692569, 5611180 1009 0.43 0.25 8.10 9.46 2392 2721 14 10: 694156, 5611476 1029 1.00 0.46 7.66 8.78 2140 2220 19 10: 692334, 5605109 891 0.53 0.32 8.06 7.91 3083 4174 54 55 APPENDIX B. Photos of livestock disturbance at study wetlands. a) b) Figure B.1. July 2008 photos of study wetlands with a) low (LDBL 7) and b) high (RH 13.1) levels of livestock grazing disturbance. APPENDIX C. Aquatic macroinvertebrate taxa list Table C.1. List of aquatic macroinvertebrate taxa found in wetlands sampled May/June (Spring) and July (Summer), 2008 near Kamloops, British Columbia, Canada. An “X” denotes taxon presence in sample type (sweeps or cores) and season. Spring (n = 17) Macroinvertebrate Taxon Common Name EPHEMEROPTERA Baetidae TRICHOPTERA Limnephilidae DIPTERA Chironomidae Ceratopogonidae Tipulidae Chaoboridae Culicidae Dixidae Psychodidae Sciomyzidae Stratiomyidae Tabanidae Ephydridae Empididae Dolichopodidae HEMIPTERA Corixidae Notonectidae Gerridae Mayflies Small Minnow Mayflies Caddisflies Northern Case-maker Caddisflies True Flies Non-biting Midges Biting Midges, No-See-Ums Crane Flies Phantom Midges Mosquitoes Dixid Midges, Meniscus midges Moth and Sand Flies Marsh Flies, Snail-killing Flies Soldier Flies Horse Flies, Deer Flies Shore and Brine Flies Dance Flies Longlegged Flies True Bugs Water Boatmen Backswimmers Water Striders Summer (n = 12) Sweeps Cores Sweeps X X X Cores 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 56 COLEOPTERA Dytiscidae Hydrophilidae Haliplidae ODONATA (ZYGOPTERA) Lestidae Coenagrionidae ODONATA (ANISOPTERA) Aeshnidae Libellulidae COLLEMBOLA AMPHIPODA Hyalellidae Gammaridae GASTROPODA Planorbidae Lymnaeidae Physidae OSTRACODA BIVALVIA Sphaeriidae HIRUDINEA OLIGOCHAETA NEMATODA ACARINA Beetles Predaceous Diving Beetles Water Scavenger Beetles Crawling Water Beetles Damselflies Spreadwings Pond Damsels Dragonflies Darner Dragonflies Skimmer Dragonflies Springtails Scuds, Side-swimmers no common name no common name Snails and Limpets Ram's horn Snails Pond Snails Bladder Snails Seed Shrimps Freshwater Clams and Mussels Fingernail Clams Leeches Aquatic Earthworms Roundworms Water Mites 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 57 58 APPENDIX D. Length-mass regression equations Table D.1. Length-mass regression equations used to determine biomass from taxon body lengths. Dry mass was determined using M = a Lb, where M = mass, L = body length and a and b are constants. Reference sources can be found in the Literature Cited section of Chapter 2. Taxon EPHEMEROPTERA Baetidae TRICHOPTERA Limnephilidae DIPTERA Chironomidae Ceratopogonidae Tipulidae Chaoboridae Culicidae Dixidae Psychodidae Sciomyzidae Stratiomyidae Tabanidae Ephydridae Empididae Dolichopodidae HEMIPTERA Corixidae Notonectidae Gerridae COLEOPTERA Dytiscidae (Adult) Dytiscidae (Larva) Hydrophilidae (Adult) Hydrophilidae (Larva) Haliplidae (Adult) Haliplidae (Larva) ODONATA Zygoptera Lestidae Coenagrionidae Anisoptera Aeshnidae Libellulidae AMPHIPODA Hyalellidae Gammaridae a b Reference 0.0068 2.72 Benke 1993 0.0052 2.832 Smock 1980 0.0051 0.0039 0.0054 0.000453 0.000453 0.0051 0.0051 0.0066 0.0066 0.0050 0.0066 0.0066 0.0066 2.322 2.144 2.463 2.43 2.43 2.322 2.322 2.436 2.436 2.591 2.436 2.436 2.436 Smock 1980 Smock 1980 Smock 1980 Eaton 1983 Eaton 1983 Smock 1980 Smock 1980 Smock 1980 Smock 1980 Smock 1980 Smock 1980 Smock 1980 Smock 1980 0.0031 0.0031 0.0150 2.904 2.904 2.596 Smock 1980 Smock 1980 Smock 1980 0.0618 0.0111 0.0618 0.0111 0.0271 0.0111 2.502 2.490 2.502 2.490 2.744 2.490 Smock 1980 Smock 1980 Smock 1980 Smock 1980 Smock 1980 Smock 1980 0.00745 0.0086 2.97 2.666 Pavlov and Zubina 1990 Smock 1980 0.0082 0.0072 2.813 2.618 Smock 1980 Benke 1993 0.0049 0.0049 3.001 3.001 Marchant and Hynes 1981 Marchant and Hynes 1981 59 APPENDIX E. Relative abundance and biomass (%) of spring and summer aquatic macroinvertebrates. a) Relative Abundance (%) 100 Diptera Ostracoda Oligochaeta Coleoptera Zygoptera Hemiptera Anisoptera Collembola Gastropoda Nematoda Other Taxa 80 60 40 20 B5 B6 .1 B4 .1 C 8 R 19 H 5 L6 .1 R 14 C 7 H 7. 1 H 9 R 13 .1 L7 B1 0 H 4. 3 L4 .1 B4 0 Wetland Sites with Increasing Disturbance b) Relative Abundance (%) 100 80 Diptera Ostracoda Oligochaeta Coleoptera Zygoptera Amphipoda Gastropoda Other Taxa 60 40 20 0 L7 B10 L4.1 B4 B5 B6.1 B4.1 R19 L6.1 R14 H9 R13.1 Wetland Sites with Increasing Disturbance Figure E.1. Relative aquatic macroinvertebrate abundance (%) of a) spring and b) summer nektonic communities. To better illustrate the community composition, taxa that were present in >25% of the wetlands and had >5% relative abundance in at least one wetland are shown. Note that this cut-off protocol is different than the criteria used for statistical analyses (see Chapter 2, Methods Section). 60 a) Relative Abundance (%) 100 80 Diptera Ostracoda Oligochaeta Zygoptera Nematoda Other Taxa 60 40 20 B5 B6 .1 B4 .1 C 8 R 19 H 5 L6 .1 R 14 C 7 H 7. 1 H 9 R 13 .1 L7 B1 0 H 4. 3 L4 .1 B4 0 Wetland Sites With Increasing Disturbance b) Relative Abundance (%) 100 80 60 Diptera Ostracoda Oligochaeta Gastropoda Other Taxa 40 20 0 L7 B10 L4.1 B4 B5 B6.1 B4.1 R19 L6.1 R14 H9 R13.1 Wetland Sites with Increasing Disturbance Figure E.2. Relative aquatic macroinvertebrate abundance (%) of a) spring and b) summer benthic communities. To better illustrate the community composition, taxa that were present in >25% of the wetlands and had >5% relative abundance in at least one wetland are shown. Note that this cut-off protocol is different than the criteria used for statistical analyses (see Chapter 2, Methods Section). 61 a) Relative Biomass (%) 100 80 Diptera Coleoptera Anisoptera Zygoptera Trichoptera Gastropoda Aquatic Others Other Taxa 60 40 20 B5 B6 .1 B4 .1 C 8 R 19 H 5 L6 .1 R 14 C 7 H 7. 1 H R 9 13 .1 L7 B1 0 H 4. 3 L4 .1 B4 0 Wetland Sites with Increasing Disturbance b) Relative Biomass (%) 100 80 Diptera Coleoptera Zygoptera Hemiptera Anisoptera Amphipoda Ephemeroptera Gastropoda Aquatic Others 60 40 20 0 L7 B10 L4.1 B4 B5 B6.1 B4.1 R19 L6.1 R14 H9 R13.1 Wetland Sites with Increasing Disturbance Figure E.3. Relative aquatic macroinvertebrate biomass (%) of a) spring and b) summer nektonic communities. To better illustrate the community composition, taxa that were present in >25% of the wetlands and had >5% relative abundance in at least one wetland are shown. Note that this cut-off protocol is different than the criteria used for statistical analyses (see Chapter 2, Methods Section). 62 a) Relative Biomass (%) 100 80 Diptera Coleoptera Zygoptera Anisoptera Trichoptera Gastropoda Aquatic Others 60 40 20 B5 B6 .1 B4 .1 C 8 R 19 H 5 L6 .1 R 14 C 7 H 7. 1 H 9 R 13 .1 L7 B1 0 H 4. 3 L4 .1 B4 0 Wetland Sites with Increasing Disturbance b) Relative Biomass (%) 100 80 Diptera Coleoptera Zygoptera Amphipoda Gastropoda Aquatic Others Other Taxa 60 40 20 0 L7 B10 L4.1 B4 B5 B6.1 B4.1 R19 L6.1 R14 H9 R13.1 Wetland Sites with Increasing Disturbance Figure E.4. Relative aquatic macroinvertebrate biomass (%) of a) spring and b) summer benthic communities. To better illustrate the community composition, taxa that were present in >25% of the wetlands and had >5% relative abundance in at least one wetland are shown. Note that this cut-off protocol is different than the criteria used for statistical analyses (see Chapter 2, Methods Section). 63 1.0 APPENDIX F. Nonmetric multidimensional scaling (NMDS) ordinations of dominant taxa community structure and environmental variables. Les Chi Aes B5 0.0 NMDS2 0.5 Cond B4 L7 Cer H9 Dyt B10 pH Cor L4.1 B4.1 Oli R19 B6.1 L6.1 H5 -0.5 Ost -1.0 C8 H7.1 H4.3 Perim R14C7 R13.1 Gas Disturb 0.5 1.0 Bol -1.5 -1.0 -0.5 0.0 1.5 NMDS1 Figure F.1. Nonmetric multidimensional scaling (NMDS) ordination (stress=10.3%) of spring sweep abundance dominant taxa community structure. The environmental variables of livestock disturbance (Disturb), conductivity (Cond), perimeter length (Perim) and pH are shown as fitted vectors with the length of the arrow corresponding to the strength of the relationship. Livestock disturbance was significantly correlated with the ordination (r2=0.486, p=0.008). Wetland site (in red) disturbance level is represented by a continuum with large circles being most disturbed and dots representing least disturbed sites. Taxa (in black) are as follows: Aes=Aeshnidae, Bol=Collembola, Cer=Ceratopogonidae, Chi=Chironomidae, Cor=Corixidae, Dyt=Dytiscidae, Gas=Gastropoda, Les=Lestidae, Oli=Oligochaeta, and Ost=Ostracoda. 64 Lym Disturb B5 0.5 R13.1 pH L6.1 H9 Chi Cond 0.0 NMDS2 Dyt Cer B4.1 Ost -0.5 L4.1 B6.1 B10 B4 Les Perim R19 R14 L7 Oli -1.0 -0.5 0.0 0.5 NMDS1 Table F.2. Nonmetric multidimensional scaling (NMDS) ordination (stress=13.3%) of summer sweep abundance dominant taxa community structure. The environmental variables of livestock disturbance (Disturb), conductivity (Cond), perimeter length (Perim) and pH are shown as fitted vectors with the length of the arrow corresponding to the strength of the relationship. Livestock disturbance was significantly correlated with the ordination (r2=0.714, p=0.006). Wetland site (in red) disturbance level is represented by a continuum with large circles being most disturbed and dots representing least disturbed sites. Taxa (in black) are as follows: Cer=Ceratopogonidae, Chi=Chironomidae, Dyt=Dytiscidae, Les=Lestidae, Lym=Lymnaeidae, Oli=Oligochaeta, and Ost=Ostracoda. 1.0 65 Chi R19 L7B4.1 B5 L4.1 0.0 NMDS2 0.5 B6.1 Perim R13.1 H9 Cer -0.5 R14 L6.1 Cond Oli B10 B4 0.5 1.0 pH Disturb -1.5 -1.0 -0.5 0.0 NMDS1 Figure F.3. Nonmetric multidimensional scaling (NMDS) ordination (stress=1.74%) of summer core abundance dominant taxa community structure. The environmental variables of livestock disturbance (Disturb), conductivity (Cond), perimeter length (Perim) and pH are shown as fitted vectors with the length of the arrow corresponding to the strength of the relationship. Livestock disturbance was significantly correlated with the ordination (r2=0.534, p=0.034). Wetland site (in red) disturbance level is represented by a continuum with large circles being most disturbed and dots representing least disturbed sites. Taxa (in black) are as follows: Cer=Ceratopogonidae, Chi=Chironomidae, Oli=Oligochaeta. 66 APPENDIX G. Environmental variable correlation values from nonmetric multidimensional scaling (NMDS) ordinations. Table G.1. Environmental variable correlation values from nonmetric multidimensional scaling (NMDS) ordinations. Only ordinations with at least one significant association with an environmental variable are shown. Significant variables (p≤0.05) are in bold. Sample Environmental Variables r2 p value Spring Sweep Abundance Disturbance 0.486 0.008 Perimeter 0.089 0.529 pH 0.126 0.426 Summer Sweep Abundance Summer Core Abundance Conductivity 0.322 0.063 Disturbance 0.721 0.005 Perimeter 0.229 0.307 pH 0.275 0.238 Conductivity 0.300 0.187 Disturbance 0.534 0.035 Perimeter 0.094 0.627 pH 0.152 0.455 Conductivity 0.357 0.133 APPENDIX H. Significant linear regressions with macroinvertebrates and environmental variables other than livestock disturbance. Table H.1. Significant linear regressions with macroinvertebrate communities and environmental variables other than livestock disturbance. Regression slopes are described as either positive (+) or negative (-). Only relationships with p <0.05 are shown. Sampling Period Dependent Variable Independent Variable(s) Slope F df p r2 Adj. r2 SWEEP ABUNDANCE Spring Lestidae Perimeter - 4.71 15 0.046 0.239 0.188 Summer Oligochaeta pH + Conductivity 21.82 9 0.000 0.829 0.791 Oligochaeta pH -&- 8.65 10 0.015 0.464 0.410 SWEEP BIOMASS Spring Aeshnidae Conductivity + 7.89 15 0.013 0.345 0.301 Summer Hemiptera Conductivity - 4.89 10 0.051 0.328 0.261 CORE ABUNDANCE Spring Summer Shannon Diversity pH + 8.12 15 0.012 0.351 0.308 Simpson's Diversity pH + 6.69 15 0.021 0.308 0.262 Oligochaeta Conductivity 6.62 10 0.028 0.398 0.338 Richness Conductivity - 11.38 10 0.007 0.532 0.486 Coleoptera pH - 5.52 10 0.041 0.356 0.291 CORE BIOMASS Summer 67 68