Data from: Using partial aggregation in Spatial Capture Recapture ...

• Main Authors: Milleret, Cyril, Dupont, Pierre, Brøseth, Henrik, Kindberg, Jonas, Royle, J. Andrew, Bischof, Richard
• Format: Dataset
• Language: English
• Published: Dryad 2019
• Subjects: Gulo gulo; Wolverines
• Online Access: https://dx.doi.org/10.5061/dryad.pd612qp; https://datadryad.org/stash/dataset/doi:10.5061/dryad.pd612qp

1. Spatial capture-recapture (SCR) models are commonly used for analyzing data collected using non-invasive genetic sampling (NGS). Opportunistic NGS often leads to detections that do not occur at discrete detector locations. Therefore, spatial aggregation of individual detections into fixed detectors (e.g. center of grid cells) is an option to increase computing speed of SCR analyses. However, it may reduce precision and accuracy of parameter estimations. 2. Using simulations, we explored the impact that spatial aggregation of detections has on a trade-off between computing time and parameter precision and bias, under a range of biological conditions. We used three different observation models: the commonly used Poisson and Bernoulli models, as well as a novel way to partially aggregate detections (Partially Aggregated Binary model (PAB)) to reduce the loss of information after aggregating binary detections. The PAB model divides detectors into K subdetectors and models the frequency of subdetectors with ... : WOLVERINE DATAThe "WOLVERINE.Rdata" file contains the Rdata necessary to run the wolverines males and females empirical example at the original grid cell size (2*2kms) with a Bernoulli model. The README.R file contains the R script and data description necessary to run the JAGS models.WOLVERINE.RdataSCR.BERNOULLI.PAB.WOLVERINEJAGS model file to run the wolverine analysis associated with the WOLVERINE.Rdata file. ...