Distance sampling with camera traps

Reliable estimates of animal density and abundance are essential for effective wildlife conservation and management. Camera trapping has proven efficient for sampling multiple species, but statistical estimators of density from camera trapping data for species that cannot be individually identified are still in development. We extend point‐transect methods for estimating animal density to accommodate data from camera traps, allowing researchers to exploit existing distance sampling theory and software for designing studies and analysing data. We tested it by simulation, and used it to estimate densities of Maxwell's duikers (Philantomba maxwellii) in Taï National Park, Côte d'Ivoire. Densities estimated from simulated data were unbiased when we assumed animals were not available for detection during long periods of rest. Estimated duiker densities were higher than recent estimates from line transect surveys, which are believed to underestimate densities of forest ungulates. We expect these methods to provide an effective means to estimate animal density from camera trapping data and to be applicable in a variety of settings.

[1]  Stephen T. Buckland,et al.  Monte Carlo confidence intervals , 1984 .

[2]  J. Hart,et al.  Methods of estimating ungulate populations in tropical forests , 1988 .

[3]  H. Newing.  Behavioural ecology of duikers (Cephalophus spp.) in forest and secondary growth, Tai, Cote d'Ivoire , 1994 .

[4]  Andrew J. Plumptre,et al.  Monitoring mammal populations with line transect techniques in African forests , 2000 .

[5]  S. Buckland.  Introduction to distance sampling : estimating abundance of biological populations , 2001 .

[6]  K. U. Karanth,et al.  Estimation of large herbivore densities in the tropical forests of southern India using distance sampling , 2003 .

[7]  P. Brussard,et al.  Wariness of coyotes to camera traps relative to social status and territory boundaries , 2003 .

[8]  H. Newing.  Bushmeat hunting and management: implications of duiker ecology and interspecific competition , 2004, Biodiversity & Conservation.

[9]  F. Rovero,et al.  Estimating the abundance of forest antelopes by line transect techniques: a case from the Udzungwa Mountains of Tanzania , 2004 .

[10]  Darryl I. MacKenzie,et al.  Designing occupancy studies: general advice and allocating survey effort , 2005 .

[11]  Christophe Boesch,et al.  Manipulating decay time for efficient large-mammal density estimation: gorillas and dung height. , 2007, Ecological applications : a publication of the Ecological Society of America.

[12]  Len Thomas,et al.  IMPROVING ESTIMATES OF BIRD DENSITY USING MULTIPLE- COVARIATE DISTANCE SAMPLING , 2007 .

[13]  T. Schweder.  Advanced Distance Sampling: Estimating Abundance of Biological Populations , 2007 .

[14]  Piran C. L. White,et al.  Selection of line‐transect methods for estimating the density of group‐living animals: lessons from the primates , 2008, American journal of primatology.

[15]  A. Bowkett,et al.  Genetic testing of dung identification for antelope surveys in the Udzungwa Mountains, Tanzania , 2009, Conservation Genetics.

[16]  S. Focardi,et al.  Response to human presence during nocturnal line transect surveys in fallow deer (Dama dama) and wild boar (Sus scrofa) , 2009, European Journal of Wildlife Research.

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

[18]  A. Todd,et al.  Using Dung to Estimate Gorilla Density: Modeling Dung Production Rate , 2008, International Journal of Primatology.

[19]  David L. Borchers,et al.  Density Estimation by Spatially Explicit Capture–Recapture: Likelihood-Based Methods , 2009 .

[20]  Len Thomas,et al.  Estimating the Encounter Rate Variance in Distance Sampling , 2009, Biometrics.

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

[22]  S. T. Buckland,et al.  Point Transect Sampling Along Linear Features , 2010, Biometrics.

[23]  Len Thomas,et al.  Distance software: design and analysis of distance sampling surveys for estimating population size , 2009, The Journal of applied ecology.

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

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

[26]  M. Morrison,et al.  Point-Based Mark-Recapture Distance Sampling , 2011 .

[27]  Antony J. Lynam,et al.  TERRESTRIAL ACTIVITY PATTERNS OF WILD CATS FROM CAMERA-TRAPPING , 2013 .

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

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

[30]  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.

[31]  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 .

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

[33]  A. Paviolo,et al.  Daily activity patterns and habitat use of the lowland tapir (Tapirus terrestris) in the Atlantic Forest , 2014 .

[34]  K. Parker,et al.  Understanding the paradox of deer persisting at high abundance in heavily browsed habitats , 2014 .

[35]  Margaret Kosmala,et al.  Applying a random encounter model to estimate lion density from camera traps in Serengeti National Park, Tanzania , 2015, The Journal of wildlife management.

[36]  David W. Macdonald,et al.  Random versus Game Trail-Based Camera Trap Placement Strategy for Monitoring Terrestrial Mammal Communities , 2015, PloS one.

[37]  Steven R. Beissinger,et al.  Estimating abundance of unmarked animal populations: accounting for imperfect detection and other sources of zero inflation , 2015 .

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

[39]  Stephen T. Buckland,et al.  Distance Sampling: Methods and Applications , 2015 .

[40]  Fridolin Zimmermann,et al.  Camera Trapping for Wildlife Research , 2016 .

[41]  Neil Reid,et al.  An invasive‐native mammalian species replacement process captured by camera trap survey random encounter models , 2016 .

[42]  Bart Kranstauber,et al.  Wildlife speed cameras: measuring animal travel speed and day range using camera traps , 2016 .

[43]  C. Prigioni,et al.  Pine marten density in lowland riparian woods: A test of the Random Encounter Model based on genetic data , 2016 .

[44]  E. Howe,et al.  An empirical evaluation of camera trapping and spatially explicit capture‐recapture models for estimating chimpanzee density , 2017, American journal of primatology.