Spatial capture–mark–resight estimation of animal population density

Sightings of previously marked animals can extend a capture-recapture dataset without the added cost of capturing new animals for marking. Combined marking and resighting methods are therefore an attractive option in animal population studies, and there exist various likelihood-based non-spatial models, and some spatial versions fitted by Markov chain Monte Carlo sampling. As implemented to date, the focus has been on modeling sightings only, which requires that the spatial distribution of pre-marked animals is known. We develop a suite of likelihood-based spatial mark-resight models that either include the marking phase ("capture-mark-resight" models) or require a known distribution of marked animals (narrow-sense "mark-resight"). The new models sacrifice some information in the covariance structure of the counts of unmarked animals; estimation is by maximizing a pseudolikelihood with a simulation-based adjustment for overdispersion in the sightings of unmarked animals. Simulations suggest that the resulting estimates of population density have low bias and adequate confidence interval coverage under typical sampling conditions. Further work is needed to specify the conditions under which ignoring covariance results in unacceptable loss of precision, or to modify the pseudolikelihood to include that information. The methods are applied to a study of ship rats Rattus rattus using live traps and video cameras in a New Zealand forest, and to previously published data.

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

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

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

[4]  Brett T. McClintock,et al.  From NOREMARK to MARK: software for estimating demographic parameters using mark–resight methodology , 2010, Journal of Ornithology.

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

[6]  David L. Borchers,et al.  Trace-Contrast Models for Capture–Recapture Without Capture Histories , 2016 .

[7]  Murray G Efford,et al.  Population density estimated from locations of individuals on a passive detector array. , 2009, Ecology.

[8]  Murray G Efford,et al.  Estimation of population density by spatially explicit capture-recapture analysis of data from area searches. , 2011, Ecology.

[9]  S. Pledger.  Unified Maximum Likelihood Estimates for Closed Capture–Recapture Models Using Mixtures , 2000, Biometrics.

[10]  Rahel Sollmann,et al.  Comparing capture–recapture, mark–resight, and spatial mark–resight models for estimating puma densities via camera traps , 2014 .

[11]  M. Efford,et al.  Compensatory heterogeneity in spatially explicit capture-recapture data. , 2014, Ecology.

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

[13]  David L. Borchers,et al.  Spatial Capture–Recapture Models , 2016 .

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

[15]  Dietrich Stoyan,et al.  Parameter Estimation and Model Selection for Neyman‐Scott Point Processes , 2008, Biometrical journal. Biometrische Zeitschrift.

[16]  Byron J. T. Morgan,et al.  Integrated Analysis of Capture–Recapture–Resighting Data and Counts of Unmarked Birds at Stop-Over Sites , 2013 .

[17]  Brett T. McClintock,et al.  A Generalized Mixed Effects Model of Abundance for Mark-Resight Data When Sampling is Without Replacement , 2009 .

[18]  N. Reid,et al.  AN OVERVIEW OF COMPOSITE LIKELIHOOD METHODS , 2011 .

[19]  J Andrew Royle,et al.  A hierarchical model for spatial capture-recapture data. , 2008, Ecology.

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

[21]  Brett T McClintock,et al.  Estimating Abundance Using Mark–Resight When Sampling Is with Replacement or the Number of Marked Individuals Is Unknown , 2009, Biometrics.

[22]  Brett T McClintock,et al.  A less field-intensive robust design for estimating demographic parameters with mark-resight data. , 2009, Ecology.

[23]  Brett T McClintock,et al.  A spatial mark--resight model augmented with telemetry data. , 2013, Ecology.

[24]  Murray G. Efford,et al.  Density-dependent home-range size revealed by spatially explicit capture–recapture , 2016 .

[25]  Richard B. Chandler,et al.  Generalized spatial mark–resight models with an application to grizzly bears , 2018 .

[26]  Brett T. McClintock,et al.  Mark-resight abundance estimation under incomplete identification of marked individuals , 2014 .