REVIEW: Wildlife camera trapping: a review and recommendations for linking surveys to ecological processes

Summary Reliable assessment of animal populations is a long-standing challenge in wildlife ecology. Technological advances have led to widespread adoption of camera traps (CTs) to survey wildlife distribution, abundance and behaviour. As for any wildlife survey method, camera trapping must contend with sources of sampling error such as imperfect detection. Early applications focused on density estimation of naturally marked species, but there is growing interest in broad-scale CT surveys of unmarked populations and communities. Nevertheless, inferences based on detection indices are controversial, and the suitability of alternatives such as occupancy estimation is debatable. We reviewed 266 CT studies published between 2008 and 2013. We recorded study objectives and methodologies, evaluating the consistency of CT protocols and sampling designs, the extent to which CT surveys considered sampling error, and the linkages between analytical assumptions and species ecology. Nearly two-thirds of studies surveyed more than one species, and a majority used response variables that ignored imperfect detection (e.g. presence–absence, relative abundance). Many studies used opportunistic sampling and did not explicitly report details of sampling design and camera deployment that could affect conclusions. Most studies estimating density used capture–recapture methods on marked species, with spatially explicit methods becoming more prominent. Few studies estimated density for unmarked species, focusing instead on occupancy modelling or measures of relative abundance. While occupancy studies estimated detectability, most did not explicitly define key components of the modelling framework (e.g. a site) or discuss potential violations of model assumptions (e.g. site closure). Studies using relative abundance relied on assumptions of equal detectability, and most did not explicitly define expected relationships between measured responses and underlying ecological processes (e.g. animal abundance and movement). Synthesis and applications. The rapid adoption of camera traps represents an exciting transition in wildlife survey methodology. We remain optimistic about the technology's promise, but call for more explicit consideration of underlying processes of animal abundance, movement and detection by cameras, including more thorough reporting of methodological details and assumptions. Such transparency will facilitate efforts to evaluate and improve the reliability of camera trap surveys, ultimately leading to stronger inferences and helping to meet modern needs for effective ecological inquiry and biodiversity monitoring.

[1]  Roel R. Lopez,et al.  Distribution and Abundance of Endangered Florida Key Deer on Outer Islands , 2008 .

[2]  Samuel T. Turvey,et al.  Estimating animal density using camera traps without the need for individual recognition , 2008 .

[3]  Anthony J. Giordano,et al.  Lack of trophic release with large mammal predators and prey in Borneo , 2013 .

[4]  Erin K. Kuprewicz Mammal Abundances and Seed Traits Control the Seed Dispersal and Predation Roles of Terrestrial Mammals in a Costa Rican Forest , 2013 .

[5]  Darryl I. MacKenzie,et al.  The use of photographic rates to estimate densities of tigers and other cryptic mammals: a comment on misleading conclusions , 2002 .

[6]  Rebecca J. Foster,et al.  Differential Use of Trails by Forest Mammals and the Implications for Camera‐Trap Studies: A Case Study from Belize , 2010 .

[7]  Margaret F. Kinnaird,et al.  Cryptic mammals caught on camera: assessing the utility of range wide camera trap data for conserving the endangered Asian tapir , 2013 .

[8]  Robert M. Dorazio,et al.  Occupancy estimation and the closure assumption , 2009 .

[9]  David L. Smith,et al.  The use of photographic rates to estimate densities of tigers and other cryptic mammals , 2001, Animal Conservation.

[10]  John A. Litvaitis,et al.  Identifying performance differences among trail cameras used to monitor forest mammals , 2014 .

[11]  M. Hebblewhite,et al.  Distinguishing technology from biology: a critical review of the use of GPS telemetry data in ecology , 2010, Philosophical Transactions of the Royal Society B: Biological Sciences.

[12]  D. Macdonald,et al.  To bait or not to bait: A comparison of camera-trapping methods for estimating leopard Panthera pardus density , 2014 .

[13]  D. Fisher,et al.  Dingoes affect activity of feral cats, but do not exclude them from the habitat of an endangered macropod , 2012, Wildlife Research.

[14]  M. Conroy,et al.  Analysis and Management of Animal Populations , 2002 .

[15]  J. Andrew Royle,et al.  Spatially-explicit models for inference about density in unmarked populations , 2011 .

[16]  Darryl I MacKenzie,et al.  Sampling design trade-offs in occupancy studies with imperfect detection: examples and software. , 2007, Ecological applications : a publication of the Ecological Society of America.

[17]  J. Andrew Royle,et al.  Spatial Capture-Recapture , 2013 .

[18]  J. Andrew Royle,et al.  ESTIMATING SITE OCCUPANCY RATES WHEN DETECTION PROBABILITIES ARE LESS THAN ONE , 2002, Ecology.

[19]  J. Andrew Royle,et al.  Using multiple data sources provides density estimates for endangered Florida panther , 2013 .

[20]  D. Dawson,et al.  Occupancy in continuous habitat , 2012 .

[21]  Paul D. Meek,et al.  "Which camera trap type and how many do I need?" A review of camera features and study designs for a range of wildlife research applications , 2013 .

[22]  A. Glen,et al.  Optimising Camera Traps for Monitoring Small Mammals , 2013, PloS one.

[23]  R. Barrett,et al.  A History of Camera Trapping , 2011 .

[24]  Timothy G. O'Brien,et al.  The Wildlife Picture Index: monitoring top trophic levels , 2010 .

[25]  Eric Marboutin,et al.  Abundance of rare and elusive species: Empirical investigation of closed versus spatially explicit capture–recapture models with lynx as a case study† , 2013 .

[26]  Rebecca J. Foster,et al.  A critique of density estimation from camera-trap data† , 2012 .

[27]  J. Nichols,et al.  Advances and applications of occupancy models , 2014 .

[28]  O. Liberg,et al.  Experimental evidence for density-dependence of home-range size in roe deer (Capreolus capreolus L.): a comparison of two long-term studies , 2004, Oecologia.

[29]  Francesco Rovero,et al.  Camera trapping photographic rate as an index of density in forest ungulates , 2009 .

[30]  J. Brashares,et al.  Hierarchical Multi-Species Modeling of Carnivore Responses to Hunting, Habitat and Prey in a West African Protected Area , 2012, PloS one.

[31]  M. Tobler,et al.  An evaluation of camera traps for inventorying large‐ and medium‐sized terrestrial rainforest mammals , 2008 .

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

[33]  Cara R. Nelson,et al.  Efficacy of road removal for restoring wildlife habitat: Black bear in the Northern Rocky Mountains, USA , 2011 .

[34]  Andreas Wilting,et al.  Risky business or simple solution – Relative abundance indices from camera-trapping , 2013 .

[35]  Douglas H. Johnson In Defense of Indices: The Case of Bird Surveys , 2008 .

[36]  J. Andrew Royle,et al.  Spatially explicit models for inference about density in unmarked or partially marked populations , 2011, 1112.3250.

[37]  Matthew Wheatley,et al.  Spatial Patterns of Breeding Success of Grizzly Bears Derived from Hierarchical Multistate Models , 2014, Conservation biology : the journal of the Society for Conservation Biology.

[38]  Karl Vernes,et al.  The history of wildlife camera trapping as a survey tool in Australia , 2015 .

[39]  Margaret F. Kinnaird,et al.  Monitoring an Endangered savannah ungulate, Grevy's zebra Equus grevyi: choosing a method for estimating population densities , 2013, Oryx.

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

[41]  R. Kays,et al.  Recommended guiding principles for reporting on camera trapping research , 2014, Biodiversity and Conservation.

[42]  Wanlop Chutipong,et al.  Tigers, leopards, and dholes in a half-empty forest: Assessing species interactions in a guild of threatened carnivores , 2013 .

[43]  D. MacKenzie Occupancy Estimation and Modeling: Inferring Patterns and Dynamics of Species Occurrence , 2005 .

[44]  Jorge A. Ahumada,et al.  Monitoring the Status and Trends of Tropical Forest Terrestrial Vertebrate Communities from Camera Trap Data: A Tool for Conservation , 2013, PloS one.

[45]  A. F. O'connell,et al.  Camera traps in animal ecology : methods and analyses , 2011 .

[46]  Margaret F. Kinnaird,et al.  Crouching tigers, hidden prey: Sumatran tiger and prey populations in a tropical forest landscape , 2003 .

[47]  Michael K. Schwartz,et al.  Integrating Motion-Detection Cameras and Hair Snags for Wolverine Identification , 2011 .

[48]  J. Nichols,et al.  ESTIMATION OF TIGER DENSITIES IN INDIA USING PHOTOGRAPHIC CAPTURES AND RECAPTURES , 1998 .

[49]  I. Gordon,et al.  Using a General Index Approach to Analyze Camera-Trap Abundance Indices , 2011 .

[50]  Peter B. Banks,et al.  Camera Trapping: Wildlife Management and Research , 2014 .

[51]  S. S. Stevens,et al.  Noninvasive Survey Methods for Carnivores , 2010 .

[52]  J. Marcus Rowcliffe,et al.  Assessing the Status of Wild Felids in a Highly-Disturbed Commercial Forest Reserve in Borneo and the Implications for Camera Trap Survey Design , 2013, PloS one.

[53]  Graeme Caughley,et al.  Analysis of vertebrate populations , 1977 .

[54]  C. Fonseca,et al.  Evaluation of Camera Trapping for Estimating Red Fox Abundance , 2009 .

[55]  A. F. O'connell,et al.  Estimating Site Occupancy and Detection Probability Parameters for Meso- And Large Mammals in a Coastal Ecosystem , 2006 .

[56]  Timothy G. O'Brien,et al.  Abundance, Density and Relative Abundance: A Conceptual Framework , 2011 .

[57]  Ana Carolina Srbek-Araujo,et al.  Influence of camera-trap sampling design on mammal species capture rates and community structures in southeastern Brazil , 2013 .

[58]  M. Chhowalla Synthesis and Applications , 2016 .

[59]  Darryl I. MacKenzie,et al.  Assessing the fit of site-occupancy models , 2004 .