, Volume 51, Issue 4, pp 471-479
Date: 07 Mar 2009

Subsampling photographic capture-recapture data of tigers (Panthera tigris) to minimize closure violation and improve estimate precision: a case study

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Abstract

Most studies using photographic capture-recapture methodology estimate parameters of interest with ecological and sampling uncertainties. However, the effect of sampling effort on assumption violation and estimate precision has seldom been described using empirical data in studies estimating population size of tigers (Panthera tigris tigris). In this study, we evaluate the influence of trap effort (trap area, mean cell area and trap density) on the assumption of geographic closure and their relationship with estimated capture probability. We do this by subsampling capture histories obtained for tigers from 30 trapping stations within the Chilla range of Rajaji National Park, India. We assessed the importance of trapping effort on geographic closure by estimating fidelity ( \( \overset{\lower0.5em\hbox{\(\smash{\scriptscriptstyle\frown}\)}}{F} \) ) and immigration ( \( \overset{\lower0.5em\hbox{\(\smash{\scriptscriptstyle\frown}\)}}{f} \) ) under the Pradel model. Estimate precision (CV% [ \( \hat{N} \) ]) was evaluated based on estimates of capture probability ( \( \hat{p} \) ). Results of the Pradel analysis suggested that larger trap area (TA) ensured geographic closure, while high trap densities (TD) exhibited sex-specific heterogeneity in recapture probabilities p. Simulation results suggested a significant positive correlation between estimates of ( \( \hat{p} \) ) and TD. With increase in estimated capture probability, estimate precision (CV% [ \( \hat{N} \) ]) also improved sharply. Comparison of prior studies towards optimizing sampling strategies is often compromised due to the difference in scale and methods of sampling. Therefore, we urge that subsampling within a dataset as illustrated in our study may prove to be an advantageous step towards standardizing photographic capture-recapture sampling methodology for management objectives.