Empirical evaluation of several population size estimates applied to the grey squirrel

Don, B. A. C.

doi:10.4098/at.arch.84-20

Cited by 9 publications

(3 citation statements)

References 25 publications

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“…The relative good performance of the jackknife estimator corroborates the conclusions of previous simulations that were based on virtually created distributions of capture probability [4], [11], [34], [52], [53], [54]. It was very close to the reference population size for the later primary periods in which heterogeneity was lower than for the first primary periods and capture rates were high, despite its tendency to overestimate for theoretically constructed datasets if heterogeneity is low [33] or capture rate very high [30].…”

Section: Discussionsupporting

confidence: 84%

“…The relative poor performance of the latter confirms that the model selection procedure of CAPTURE does not work satisfactorily [4], [9], [11], [53]; Stanley & Burnham (1998) even stated that this procedure in CAPTURE selects an inappropriate model [55].…”

Section: Discussionmentioning

confidence: 99%

“…The poorest relative performance was exhibited by the Finite mixtures model of Pledger (2000), followed by GSRUN [25] , Chapman's Lincoln-Petersen estimate [LP] [3] , [4] , the second sample coverage of Lee and Chao (1994), and the model selected as appropriate by CAPTURE. The relative poor performance of the latter confirms that the model selection procedure of CAPTURE does not work satisfactorily [4] , [9] , [11] , [53] ; Stanley & Burnham (1998) even stated that this procedure in CAPTURE selects an inappropriate model [55] .…”

Section: Discussionmentioning

confidence: 99%

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Reliability of Different Mark-Recapture Methods for Population Size Estimation Tested against Reference Population Sizes Constructed from Field Data

2014

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Reliable estimates of population size are fundamental in many ecological studies and biodiversity conservation. Selecting appropriate methods to estimate abundance is often very difficult, especially if data are scarce. Most studies concerning the reliability of different estimators used simulation data based on assumptions about capture variability that do not necessarily reflect conditions in natural populations. Here, we used data from an intensively studied closed population of the arboreal gecko Gehyra variegata to construct reference population sizes for assessing twelve different population size estimators in terms of bias, precision, accuracy, and their 95%-confidence intervals. Two of the reference populations reflect natural biological entities, whereas the other reference populations reflect artificial subsets of the population. Since individual heterogeneity was assumed, we tested modifications of the Lincoln-Petersen estimator, a set of models in programs MARK and CARE-2, and a truncated geometric distribution. Ranking of methods was similar across criteria. Models accounting for individual heterogeneity performed best in all assessment criteria. For populations from heterogeneous habitats without obvious covariates explaining individual heterogeneity, we recommend using the moment estimator or the interpolated jackknife estimator (both implemented in CAPTURE/MARK). If data for capture frequencies are substantial, we recommend the sample coverage or the estimating equation (both models implemented in CARE-2). Depending on the distribution of catchabilities, our proposed multiple Lincoln-Petersen and a truncated geometric distribution obtained comparably good results. The former usually resulted in a minimum population size and the latter can be recommended when there is a long tail of low capture probabilities. Models with covariates and mixture models performed poorly. Our approach identified suitable methods and extended options to evaluate the performance of mark-recapture population size estimators under field conditions, which is essential for selecting an appropriate method and obtaining reliable results in ecology and conservation biology, and thus for sound management.

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