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A method for estimating abundance of mobile populations using telemetry and counts of unmarked animals

机译:一种使用遥测和未标记动物计数估算流动人口数量的方法

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While numerous methods exist for estimating abundance when detection is imperfect, these methods may not be appropriate due to logistical difficulties or unrealistic assumptions. In particular, if highly mobile taxa are frequently absent from survey locations, methods that estimate a probability of detection conditional on presence will generate biased abundance estimates. Here, we propose a new estimator for estimating abundance of mobile populations using telemetry and counts of unmarked animals. The estimator assumes that the target population conforms to a fission‐fusion grouping pattern, in which the population is divided into groups that frequently change in size and composition. If assumptions are met, it is not necessary to locate all groups in the population to estimate abundance. We derive an estimator, perform a simulation study, conduct a power analysis, and apply the method to field data. The simulation study confirmed that our estimator is asymptotically unbiased with low bias, narrow confidence intervals, and good coverage, given a modest survey effort. The power analysis provided initial guidance on survey effort. When applied to small data sets obtained by radio‐tracking Indiana bats, abundance estimates were reasonable, although imprecise. The proposed method has the potential to improve abundance estimates for mobile species that have a fission‐fusion social structure, such as Indiana bats, because it does not condition detection on presence at survey locations and because it avoids certain restrictive assumptions.
机译:当检测不完善时,虽然存在许多估算丰度的方法,但是由于后勤方面的困难或不切实际的假设,这些方法可能不合适。特别是,如果调查地点经常缺少高度移动的分类单元,则根据存在的条件来估计检测概率的方法将产生偏差的丰度估计。在这里,我们提出了一种新的估算器,用于使用遥测技术和未标记动物的数量估算流动人口的数量。估算者假设目标人群符合裂变融合分组模式,在该模式中,人群被划分为大小和组成经常变化的组。如果满足假设,则无需定位总体中的所有群体来估计丰度。我们推导一个估算器,进行仿真研究,进行功率分析,并将该方法应用于现场数据。仿真研究证实,在进行了适度的调查工作的情况下,我们的估计器在低偏差,窄置信区间和良好覆盖范围上渐近无偏。功率分析为调查工作提供了初步指导。当将其应用于通过无线电跟踪印第安纳蝙蝠获得的小数据集时,尽管不精确,但丰度估计是合理的。所提出的方法有可能改善具有裂变融合社会结构的流动物种(例如印第安那蝙蝠)的丰度估计,因为它不以在调查地点的存在为条件进行检测,并且可以避免某些限制性假设。

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