Grimm Annegret, Gruber Bernd, Henle Klaus
Department of Conservation Biology, UFZ - Helmholtz Centre for Environmental Research, Leipzig, Germany; Institute for Biology, Faculty of Biosciences, Pharmacy and Psychology, University of Leipzig, Leipzig, Germany.
Department of Conservation Biology, UFZ - Helmholtz Centre for Environmental Research, Leipzig, Germany; Institute for Applied Ecology, Faculty of Applied Sciences, University of Canberra, Australian Capital Territory, Canberra, Australia.
PLoS One. 2014 Jun 4;9(6):e98840. doi: 10.1371/journal.pone.0098840. eCollection 2014.
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.
在许多生态研究和生物多样性保护中,可靠的种群规模估计至关重要。选择合适的方法来估计丰度往往非常困难,尤其是在数据稀缺的情况下。大多数关于不同估计器可靠性的研究使用基于捕获变异性假设的模拟数据,而这些假设不一定反映自然种群的实际情况。在此,我们利用对树栖壁虎(Gehyra variegata)进行深入研究的封闭种群数据,构建参考种群规模,以评估十二种不同的种群规模估计器在偏差、精度、准确性及其95%置信区间方面的表现。其中两个参考种群反映自然生物实体,而其他参考种群反映种群的人工子集。由于假定存在个体异质性,我们测试了林肯 - 彼得森估计器的改进方法、程序MARK和CARE - 2中的一组模型以及截断几何分布。不同标准下方法的排名相似。考虑个体异质性的模型在所有评估标准中表现最佳。对于来自异质栖息地且没有明显协变量来解释个体异质性的种群,我们建议使用矩估计器或内插刀切法估计器(均在CAPTURE/MARK中实现)。如果捕获频率的数据充足,我们建议使用样本覆盖率或估计方程(均在CARE - 2中实现的模型)。根据捕获能力的分布,我们提出的多重林肯 - 彼得森法和截断几何分布取得了相当不错的结果。前者通常得出最小种群规模,而后者在低捕获概率存在长尾时可被推荐。具有协变量的模型和混合模型表现不佳。我们的方法确定了合适的方法并扩展了选项,以评估野外条件下标重捕种群规模估计器的性能,这对于在生态学和保护生物学中选择合适的方法并获得可靠结果至关重要,从而对于合理管理也至关重要。