A new Automated Behavioural Response system to integrate playback experiments into camera trap studies

Summary How animals respond to anthropogenic disturbances is a core component of conservation biology and how they respond to predators and competitors is equally of central importance to wildlife ecology. Camera traps have rapidly become a critical tool in wildlife research by providing a fully automated means of observing animals without needing an observer present, permitting data to be collected on rare or elusive species and infrequent events. Snapshots from camera traps revealing a species’ presence have been the principal data used to date to gauge behaviour; but, lacking experimental controls, such data permit only correlational analyses potentially open to confounding effects. Playback experiments provide a powerful means to directly test the behavioural responses of animals, enabling strong inferences and rigorous conclusions not subject to the potential confounds affecting the interpretation of snapshot data; the principal factor to date limiting the use of playback experiments being the need to have an observer present. We developed an Automated Behavioural Response system (ABR) comprising a custom-built motion-sensitive speaker system that can be paired with any commercially available camera trap, providing the means to conduct playback experiments directly testing the behavioural responses of any species that can be ‘caught’ on a camera trap. We describe field tests in Uganda, Canada and the USA, experimentally testing the effects of anthropogenic disturbances and interactions among large carnivores, in species as diverse as elephants, black bears, chimpanzees and cougars; experiments that would be completely infeasible without the ABR. We evaluate factors affecting the rate of successful data collection in the experiments in Uganda and Canada, and detail how we maximized the system's performance in the USA experiment. By integrating the power playback experiments provide to directly and rigorously test behavioural responses with the capacity camera trapping affords to study virtually any animal anywhere, the ABR can both greatly expand the range of research questions addressed by conservation biologists and wildlife ecologists and qualitatively improve the rigour of the resulting conclusions. We discuss various ways to optimize the ABR's performance in any circumstance, and the many novel research opportunities made available by this new methodology.

[1]  R. Kays,et al.  Quantifying the sensitivity of camera traps: an adapted distance sampling approach , 2011 .

[2]  Oswald J. Schmitz,et al.  Resolving Ecosystem Complexity (MPB-47) , 2010 .

[3]  R. Kays,et al.  Quantifying levels of animal activity using camera trap data , 2014 .

[4]  Ben G. Weinstein,et al.  MotionMeerkat: integrating motion video detection and ecological monitoring , 2015 .

[5]  A. F. O'connell,et al.  Camera Traps in Animal Ecology , 2011 .

[6]  E. Revilla,et al.  The Lion King and the Hyaena Queen: large carnivore interactions and coexistence , 2015, Biological reviews of the Cambridge Philosophical Society.

[7]  Justin P Suraci,et al.  Fear of large carnivores causes a trophic cascade , 2016, Nature Communications.

[8]  Julia Baker,et al.  Profiling unauthorized natural resource users for better targeting of conservation interventions , 2015, Conservation biology : the journal of the Society for Conservation Biology.

[9]  J. Mcnutt,et al.  African Wild Dogs as a Fugitive Species: Playback Experiments Investigate How Wild Dogs Respond to their Major Competitors , 2012 .

[10]  R. Kays,et al.  Emerging Technologies to Conserve Biodiversity. , 2015, Trends in ecology & evolution.

[11]  J. Ahumada,et al.  Community structure and diversity of tropical forest mammals: data from a global camera trap network , 2011, Philosophical Transactions of the Royal Society B: Biological Sciences.

[12]  V. Thuppil,et al.  Playback of felid growls mitigates crop-raiding by elephants Elephas maximus in southern India , 2015, Oryx.

[13]  T. Caro Behavior and conservation: a bridge too far? , 2007, Trends in ecology & evolution.

[14]  Andrew S. Bridges,et al.  Behavior and Activity Patterns , 2011 .

[15]  S. Durant,et al.  Living with the enemy: avoidance of hyenas and lions by cheetahs in the Serengeti , 2000 .

[16]  Graeme Shannon,et al.  Elephants can determine ethnicity, gender, and age from acoustic cues in human voices , 2014, Proceedings of the National Academy of Sciences.

[17]  Larissa L. Bailey,et al.  Inference for Occupancy and Occupancy Dynamics , 2011 .

[18]  D. Macdonald,et al.  Landscapes of Coexistence for terrestrial carnivores: the ecological consequences of being downgraded from ultimate to penultimate predator by humans , 2015 .

[19]  V. Yovovich,et al.  Scale Dependent Behavioral Responses to Human Development by a Large Predator, the Puma , 2013, PloS one.

[20]  C. Packer,et al.  Female lions can identify potentially infanticidal males from their roars , 1993, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[21]  D. Blumstein,et al.  Prey Responses to Predator's Sounds: A Review and Empirical Study , 2014 .

[22]  H. Wittmer,et al.  The Comparative Effects of Large Carnivores on the Acquisition of Carrion by Scavengers , 2015, The American Naturalist.

[23]  A. Frid,et al.  Synthesis Human-caused Disturbance Stimuli as a Form of Predation Risk , 2002 .

[24]  Hjalmar S. Kühl,et al.  Assessing the performance of a semi‐automated acoustic monitoring system for primates , 2015 .

[25]  Clinton D. Francis,et al.  A Framework for Understanding Noise Impacts on Wildlife: An Urgent Conservation Priority , 2013 .

[26]  Bart Kranstauber,et al.  Bias in estimating animal travel distance: the effect of sampling frequency , 2012 .

[27]  John-André Henden,et al.  Towards good practice guidance in using camera‐traps in ecology: influence of sampling design on validity of ecological inferences , 2013 .

[28]  C. Wilmers,et al.  Top carnivores increase their kill rates on prey as a response to human-induced fear , 2015, Proceedings of the Royal Society B: Biological Sciences.

[29]  Patrick O. McGowan,et al.  The Neurological Ecology of Fear: Insights Neuroscientists and Ecologists Have to Offer one Another , 2011, Front. Behav. Neurosci..

[30]  L. Zanette,et al.  Perceived Predation Risk Reduces the Number of Offspring Songbirds Produce per Year , 2011, Science.

[31]  Christopher N. Johnson,et al.  Effects of predator control on behaviour of an apex predator and indirect consequences for mesopredator suppression , 2012 .

[32]  Erin M. Bayne,et al.  REVIEW: Wildlife camera trapping: a review and recommendations for linking surveys to ecological processes , 2015 .

[33]  S. L. Lima,et al.  Behavioral decisions made under the risk of predation: a review and prospectus , 1990 .

[34]  Ádám Z. Lendvai,et al.  Low cost audiovisual playback and recording triggered by radio frequency identification using Raspberry Pi , 2015, PeerJ.

[35]  S. King You talkin’ to me? Interactive playback is a powerful yet underused tool in animal communication research , 2015, Biology Letters.