Identification and Density Estimation of American Martens (Martes americana) Using a Novel Camera-Trap Method

Camera-traps are increasingly used to estimate wildlife abundance, yet few studies exist for small-sized carnivores or comparing efficacy against traditional methods. We developed a camera-trap to identify the unique ventral patches of American martens (Martes americana). Our method was designed to: (1) determine the optimal trap configuration to photograph ventral patches; (2) evaluate the use of temporally clustered photographs to determine independence and improve identification; and (3) determine factors that influence identification probability. We tested our method by comparing camera- and live-trap density estimates using spatial capture–recapture (SCR) models. The ventral patches of radio-collared martens were most visible when traps were placed 15–20 cm above a feeding platform. Radio-collared martens (n = 14) visited camera-traps for long periods (median = 7 min) with long intervals between visits (median = 419 min), and visits by different martens at the same trap <15 min apart was infrequent (n = 3) during both years. Similarly, there was complete agreement among observers that clustered photos of un-collared martens were always of the same individual. Pairwise agreement was high between observers; eight un-collared martens were identifiable by consensus on 90% (54 of 60) of recorded visits. Factors influencing identification probability were directly related to the time martens spent feeding at traps (β = 0.143, P = 0.01) and inversely proportional to the time that elapsed since traps were baited (β = −0.344, P = 0.006). Density estimates were higher and more precise for camera-trapping (0.60, 0.35–1.01 martens/km2) than live-trapping (0.45, 0.16–1.22 martens/km2), providing evidence that SCR density estimates may be biased when capture heterogeneity is present, yet cannot be accounted for due to small sample size. Our camera-trap method provides a minimally invasive and accurate tool for monitoring marten populations.

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

[2]  T. S. Jung,et al.  Can camera trapping provide accurate estimates of small mammal (Myodes rutilus and Peromyscus maniculatus) density in the boreal forest? , 2016, Journal of Mammalogy.

[3]  Niels da Vitoria Lobo,et al.  Computer-aided photo-identification system with an application to polar bears based on whisker spot patterns , 2010 .

[4]  Kevin Jiang.  Introduction , 2013, Nature Medicine.

[5]  Diego J. Lizcano,et al.  A Camera Trapping and Radio Telemetry Study of Lowland Tapir (Tapirus terrestris) in Bolivian Dry Forests , 2003 .

[6]  R. Jackson,et al.  Estimating Snow Leopard Population Abundance Using Photography and Capture–Recapture Techniques , 2006 .

[7]  Martin Stevens,et al.  Image calibration and analysis toolbox – a free software suite for objectively measuring reflectance, colour and pattern , 2015, Methods in ecology and evolution.

[8]  Donald D. Katnik,et al.  Influence of Landscape Pattern on Habitat Use by American Marten in an Industrial Forest , 1998 .

[9]  P. Colgan,et al.  Numerical responses of martens to a food shortage in Northcentral Ontario , 1987 .

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

[11]  John A. Bissonette,et al.  The influence of forest fragmentation and landscape pattern on American martens , 1999 .

[12]  Jerrold L. Belant,et al.  How Does Spatial Study Design Influence Density Estimates from Spatial Capture-Recapture Models? , 2012, PloS one.

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

[14]  E. Ritchie.  Noninvasive Survey Methods for Carnivores , 2009 .

[15]  Varun R. Goswami,et al.  Optimizing individual identification and survey effort for photographic capture–recapture sampling of species with temporally variable morphological traits , 2012 .

[16]  Brett T. McClintock,et al.  Mark-Recapture and Mark-Resight Methods for Estimating Abundance with Remote Cameras: A Carnivore Case Study , 2015, PloS one.

[17]  J Andrew Royle,et al.  Spatially explicit inference for open populations: estimating demographic parameters from camera-trap studies. , 2010, Ecology.

[18]  Edward C. Soutiere.  Effects of timber harvesting on marten in Maine , 1979 .

[19]  Maurice G. Kendall.  The advanced theory of statistics , 1958 .

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

[21]  K. Hornik,et al.  Visualizing Categorical Data , 2001 .

[22]  L. Waits,et al.  NONINVASIVE GENETIC SAMPLING TOOLS FOR WILDLIFE BIOLOGISTS: A REVIEW OF APPLICATIONS AND RECOMMENDATIONS FOR ACCURATE DATA COLLECTION , 2005 .

[23]  Brian D. Gerber,et al.  Evaluating the potential biases in carnivore capture–recapture studies associated with the use of lure and varying density estimation techniques using photographic-sampling data of the Malagasy civet , 2011, Population Ecology.

[24]  Christopher J. Kyle,et al.  Empirical comparison of density estimators for large carnivores , 2010 .

[25]  William A Link,et al.  Uncovering a Latent Multinomial: Analysis of Mark–Recapture Data with Misidentification , 2010, Biometrics.

[26]  Mollie E. Brooks,et al.  Generalized linear mixed models: a practical guide for ecology and evolution. , 2009, Trends in ecology & evolution.

[27]  Marcella J. Kelly,et al.  Ocelot Leopardus pardalis in Belize: the impact of trap spacing and distance moved on density estimates , 2007, Oryx.

[28]  Y. Yom-Tov,et al.  Recent increase in body size of the American marten Martes americana in Alaska , 2008 .

[29]  D. M. Phillips,et al.  Seasonal changes in home-range area and fidelity of martens , 1998 .

[30]  Giuliano Galimberti,et al.  Classification Trees for Ordinal Responses in R: The rpartScore Package , 2012 .

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

[32]  D. M. Phillips,et al.  Seasonal Habitat Selection by Marten in an Untrapped Forest Preserve , 1997 .

[33]  J. Andrew Royle,et al.  Density Estimation in a Wolverine Population using Spatial Capture-Recapture Models , 2011 .

[34]  D. Bates,et al.  Linear Mixed-Effects Models using 'Eigen' and S4 , 2015 .

[35]  J. Andrew Royle,et al.  Integrating resource selection information with spatial capture–recapture , 2012, Methods in Ecology and Evolution.

[36]  Marcella J. Kelly,et al.  COMPUTER-AIDED PHOTOGRAPH MATCHING IN STUDIES USING INDIVIDUAL IDENTIFICATION: AN EXAMPLE FROM SERENGETI CHEETAHS , 2001 .

[37]  M. Efford.  Density estimation in live‐trapping studies , 2004 .

[38]  David R. Anderson,et al.  Model selection and multimodel inference : a practical information-theoretic approach , 2003 .

[39]  Per Wegge,et al.  Effects of trapping effort and trap shyness on estimates of tiger abundance from camera trap studies , 2004 .

[40]  C. Carroll.  Interacting Effects of Climate Change, Landscape Conversion, and Harvest on Carnivore Populations at the Range Margin: Marten and Lynx in the Northern Appalachians , 2007, Conservation biology : the journal of the Society for Conservation Biology.

[41]  Luiz Gustavo R. Oliveira-Santos,et al.  Is it possible to individually identify mammals with no natural markings using camera-traps?A controlled case-study with lowland tapirs , 2010 .

[42]  K. Poole,et al.  Suitability of a young deciduous-dominated forest for American marten and the effects of forest removal , 2004 .

[43]  S. Buskirk,et al.  Analysis of variability in home-range size of the American marten , 1989 .

[44]  T. Fuller,et al.  Biology and Conservation of Martens, Sables, and Fishers: A New Synthesis , 2014 .

[45]  Jacob S. Ivan,et al.  Using auxiliary telemetry information to estimate animal density from capture–recapture data , 2013 .

[46]  Innes C. Cuthill,et al.  Why the leopard got its spots: relating pattern development to ecology in felids , 2011, Proceedings of the Royal Society B: Biological Sciences.

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

[48]  G. Mowat,et al.  Estimating marten Martes americana population size using hair capture and genetic tagging , 2002, Wildlife Biology.

[49]  Pedro Sarmento,et al.  Use of Camera-Trapping to Estimate Puma Density and Influencing Factors in Central Brazil , 2010 .

[50]  Alexej P. K. Sirén,et al.  Spatial ecology and resource selection of a high-elevation American marten (Martes americana) population in the northeastern United States , 2016 .

[51]  E. Cuéllar,et al.  A Camera Trapping and Radio Telemetry Study of Lowland Tapir ( Tapirus terrestris ) in Bolivian Dry Forests , 2003 .

[52]  Rodolfo Dirzo,et al.  A Novel Method to Improve Individual Animal Identification Based on Camera-Trapping Data , 2011 .

[53]  R. Flynn,et al.  Temporal Changes in Population Dynamics of American Martens , 2009 .

[54]  J Andrew Royle,et al.  Bayesian inference in camera trapping studies for a class of spatial capture-recapture models. , 2009, Ecology.

[55]  P. Lukacs,et al.  Review of capture–recapture methods applicable to noninvasive genetic sampling , 2005, Molecular ecology.

[56]  D. M. Phillips,et al.  Martes Foot-Loading and Snowfall Patterns in Eastern North America , 2005 .

[57]  M. Mazerolle,et al.  Title Model Selection and Multimodel Inference Based on (q)aic(c) , 2010 .

[58]  J. Fattebert,et al.  Estimating wild boar (Sus scrofa) abundance and density using capture–resights in Canton of Geneva, Switzerland , 2008, European Journal of Wildlife Research.

[59]  Bruce G. Marcot,et al.  DNA-based approach to aging martens (Martes americana and M. caurina) , 2011 .

[60]  M. Kelly,et al.  Estimating Puma Densities from Camera Trapping across Three Study Sites: Bolivia, Argentina, and Belize , 2008 .

[61]  John D. J. Clare,et al.  Predicting bobcat abundance at a landscape scale and evaluating occupancy as a density index in central Wisconsin , 2015 .

[62]  David R. Anderson,et al.  Evaluation of Two Density Estimators of Small Mammal Population Size , 1985 .

[63]  M. Kendall,et al.  The advanced theory of statistics , 1945 .

[64]  James D. Nichols,et al.  Estimating Tiger Abundance from Camera Trap Data: Field Surveys and Analytical Issues , 2011 .

[65]  Allan F. O'Connell,et al.  Comparison of density estimation methods for mammal populations with camera traps in the Kaa‐Iya del Gran Chaco landscape , 2012 .

[66]  David R. Anderson,et al.  Statistical inference from capture data on closed animal populations , 1980 .

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

[68]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[69]  Michael Stevens,et al.  A comparison of the effectiveness of camera trapping and live trapping for sampling terrestrial small-mammal communities , 2010 .

[70]  W. Zielinski,et al.  Determining the Gender of American Martens and Fishers at Track Plate Stations , 2008 .

[71]  William J. Zielinski,et al.  Biology and Conservation of Martens, Sables, and Fishers: A New Synthesis , 2017 .

[72]  Brian D. Gerber,et al.  An assessment of carnivore relative abundance and density in the eastern rainforests of Madagascar using remotely-triggered camera traps , 2010, Oryx.

[73]  G. Seber.  The estimation of animal abundance and related parameters , 1974 .

[74]  Pierre Taberlet,et al.  An evaluation of field and non-invasive genetic methods to estimate brown bear (Ursus arctos) population size , 2006 .

[75]  J. Nichols,et al.  Statistical inference for capture-recapture experiments , 1992 .

[76]  D L Borchers,et al.  Spatially Explicit Maximum Likelihood Methods for Capture–Recapture Studies , 2008, Biometrics.

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

[78]  Y. Jhala,et al.  Home range and habitat preference of female lions (Panthera leo persica) in Gir forests, India , 2009, Biodiversity and Conservation.

[79]  Leo Breiman,et al.  Classification and Regression Trees , 1984 .