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Optimising the Value of By-Catch from Lynx Lynx Camera Trap Surveys in the Swiss Jura Region

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Optimising the Value of By-Catch from Lynx Lynx Camera Trap Surveys in the Swiss Jura Region ©KORA ©KORA Optimising the Value of By-catch from Lynx lynx Camera Trap Surveys in the Swiss Jura Region. Fiona Anne Pamplin 6th August 2013 ©KORA A dissertation submitted to the University of East Anglia, Norwich for the Master of Science degree in Applied Ecology and Conservation 2012-2013. ©This copy of the dissertation has been supplied on the condition that copyright rests with the author and that no information derived therefrom may be published without the author’s written consent. Copyright for all wildlife camera trap photographs used in this document rests with KORA and may not be reproduced in any media without prior permission from KORA, Switzerland. ©KORA Contents 1. Abstract ………………………………………………………………………………………. 4 2. Introduction………………………………………………………………………………… 5 3. Methods …………………………………………………………………………………….. 10 4. Results………………………………………………………………………………………… 18 5. Conclusion & Discussion……………….................................................. 29 6. Recommendations……………………………………………………………………... 34 7. References…………………………………………………………………………………. 37 8. Appendix …………………………………………………………...……………………... 42 2 Acknowledgements I am extremely grateful to Dr. Urs Breitenmoser (KORA) for providing me with the wonderful opportunity to work at KORA Switzerland and for allowing me to use the camera trap data for the purpose of this study. Many thanks also to Dr. Fridolin Zimmermann for granting me access to his treasure trove of camera trap photos, providing lots of helpful ideas, editing suggestions and supporting references. I am indebted to Danilo Foresti (KORA) without whom I would not even have cleared the first analytical hurdles! For his patience and guidance in helping me to master the basics of the Presence program and for his continued and most generous support throughout the project. Thank You! Very special thanks to Dr. Jenny Gill (UEA supervisor) for her encouragement, sound advice and down-to-earth perspective – and for always being there to guide me back to safe waters when I was clearly out of depth! I would also like to mention three other people who have gallantly come to my rescue in addressing various tricky issues concerning ‘Presence’ modelling – UEA PhD student Maira de Souza, Dr. James Hines (USGS Wildlife Research Center) and Dr. Darryl MacKenzie (Proteus Wildlife Research Consultants, New Zealand). A very BIG thank you to you all! 3 Optimising the Value of By-catch from Lynx lynx Camera Trap Surveys in the Swiss Jura. 1. Abstract In order to effectively manage wildlife populations and to evaluate the results of conservation interventions, wildlife managers must first identify ways of measuring population size and geographic distribution of target species. However, the expense and logistics of running surveillance programs for multiple species can be prohibitive. The aim of this study was to explore the potential of camera trap data that had been collected as part of an ongoing monitoring program for Lynx lynx in the Swiss Jura mountains, as a source of information about other wildlife species. Using a photographic data bank from the 60 day 2012-2103 winter survey, images were analysed to assess species richness, distribution and the feasibility of conducting occupancy modelling using PRESENCE software. Unlike camera trap surveys designed to estimate abundance within a capture-recapture framework, occupancy modelling does not rely on recognition of individual animals and may provide a reasonable alternative for assessing population status and trends. The findings of this study demonstrate the value of camera trap by-catch as a source of quantifiable information for species sympatric to lynx. Of a total 2902 wildlife images from 61 camera trap locations, 97.4% photos were of species not specifically targeted within the sampling protocol. The data set of photographs collected for secondary species; roe deer, boar, chamois, badger, fox and hare were sufficiently large to provide robust indicators of species distribution and richness for the study area. Considerably less data were captured for the smaller species, wildcat, beech marten and pine marten. Occupancy modelling was possible for those species with adequate sample size. However lack of model fit was a problem across all of the species, suggesting that the environmental covariates that had been selected for modelling purposes are not strong predictors of occupancy. This study demonstrates the value of camera traps as a tool for 4 multi-species monitoring programs, even when the original sampling protocol is designed around one target species. 2. Introduction As camera technology has increased, at the same time becoming more affordable, camera traps have become an integral component of many ecology and conservation programs. ‘Camera trapping’ involves the use of fixed cameras, which are usually triggered by either heat and motion or infra-red remote sensors, to take photographs of passing animals. Camera trap protocols were originally developed for estimating tiger abundance (Karanth & Nichols 1998) using a capture- recapture statistical framework and this application has since been extended to a number of species where the identification of individual animals is possible (Dillon & Kelly 2007, Silver et al. 2004). As a research tool, camera traps are now used in a variety of applications: to inventory elusive and rare animals (Tobler et al. 2008, Watts et al. 2007), to explore species habitat use and distribution (Bowkett et al. 2007, Goulart et al. 2009), to collect data on population demographics (Lopez-Parra et al. 2012) and to explore intra-guild competition (Davis et al. 2010). In all of these projects, it is inevitable that photographs are captured of animals other than the target species, resulting in very large wildlife data sets that frequently remain unanalysed (Linkie et al. 2013). Given the investment required (both in terms of effort and materials) to conduct camera surveys and the paucity of information available for many wildlife species, this represents a significant opportunity cost. Lynx lynx was reintroduced to the Jura Mountains in the early 1970’s and is fully protected in Switzerland under the Bern Convention on the Conservation of European Wildlife and Habitats (1979, Appendix III). It is also listed in Appendix II of CITES (1975). Since the late 1980’s, the progress of the lynx population in the Swiss Jura has been monitored by the non-profit 5 organisation KORA (Coordinated Research Projects for the Conservation and Management of Carnivores in Switzerland). KORA is affiliated to the University of Berne and undertakes applied research on behalf of the Swiss government on the monitoring, ecology and conservation of carnivores in a human dominated landscape. KORA has conducted deterministic camera trapping surveys targeting lynx in the Jura every year since 2008. The result of the latest 2012 -2013 winter survey in the northern part of this region reveals the presence of 14 individual lynx within the 882 km2 reference area (Zimmermann et al., in preparation) (Appendix: Figure A). Most large carnivore monitoring projects of this kind are established either because of the funding available for such charismatic animals or because of issues of human-carnivore conflict and the need to identify and track problem animals. However, in addition to lynx, a large number of other mammal species (‘by-catch’) are captured on camera – including European wildcat, meso- carnivores and various ungulate species. These animals all have an important role to play in natural ecological processes, such as predator-prey interactions, interspecies competition and in the case of herbivores, grazing pressure and competition for pasture with domestic livestock. Equally relevant in terms of conservation management at the landscape level, they rarely attract the interest or funding for independent field studies to monitor population size, trends and distribution. In Switzerland, as in many other similar projects around the world, a vast bank of camera trap data has been accumulated that has yet to be fully exploited. To date, the only studies that have been undertaken by KORA for camera trap data collected in the Jura, concern the felid species (Eichholzer, 2010, Hercé, 2011, Zimmermann et al. 2007, 2010). So how could we use all this data? With the exception of Felis sylvestris, identification of individuals is virtually impossible and we cannot therefore attempt to estimate absolute abundance of each species. However there are other indicators that are commonly used to 6 quantify the status of a wildlife population or community: these include species richness and occupancy. Species richness refers to the number of species in a location or its species ‘diversity’. Species richness indicators are often used for measuring the impact of anthropogenic pressures on biodiversity and for assessing the results of management interventions (O’Brien et al. 2011). Occupancy in single species population studies is defined as the “proportion of area, patches or sample units that is occupied” (MacKenzie et al. 2006). It is viewed as a surrogate for abundance, such that changes in the proportion of area occupied by a species (ψ) infer changes in its population size (MacKenzie & Nichols 2004). Furthermore, the problem of imperfect detection (when a species is present but not detected during a survey) can be overcome by incorporating a function of detection probability into the occupancy model ( MacKenzie et al. 2002). Research Objectives The aim of this study is to conduct an
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