Anderson Alexander S, Marques Tiago A, Shoo Luke P, Williams Stephen E
Centre for Tropical Biodiversity and Climate Change, College of Marine & Environmental Sciences, James Cook University, Townsville, Queensland, Australia.
Research Unit for Wildlife Population Assessment, Centre for Research into Ecological and Environmental Modeling, University of St Andrews, The Observatory, Buchanan Gardens, St Andrews, Scotland.
PLoS One. 2015 Jun 25;10(6):e0128464. doi: 10.1371/journal.pone.0128464. eCollection 2015.
Indices of relative abundance do not control for variation in detectability, which can bias density estimates such that ecological processes are difficult to infer. Distance sampling methods can be used to correct for detectability, but in rainforest, where dense vegetation and diverse assemblages complicate sampling, information is lacking about factors affecting their application. Rare species present an additional challenge, as data may be too sparse to fit detection functions. We present analyses of distance sampling data collected for a diverse tropical rainforest bird assemblage across broad elevational and latitudinal gradients in North Queensland, Australia. Using audio and visual detections, we assessed the influence of various factors on Effective Strip Width (ESW), an intuitively useful parameter, since it can be used to calculate an estimate of density from count data. Body size and species exerted the most important influence on ESW, with larger species detectable over greater distances than smaller species. Secondarily, wet weather and high shrub density decreased ESW for most species. ESW for several species also differed between summer and winter, possibly due to seasonal differences in calling behavior. Distance sampling proved logistically intensive in these environments, but large differences in ESW between species confirmed the need to correct for detection probability to obtain accurate density estimates. Our results suggest an evidence-based approach to controlling for factors influencing detectability, and avenues for further work including modeling detectability as a function of species characteristics such as body size and call characteristics. Such models may be useful in developing a calibration for non-distance sampling data and for estimating detectability of rare species.
相对丰度指数并未考虑可探测性的变化，这可能会使密度估计产生偏差，从而难以推断生态过程。距离抽样方法可用于校正可探测性，但在热带雨林中，茂密的植被和多样的群落使抽样变得复杂，目前缺乏关于影响其应用的因素的信息。珍稀物种带来了额外的挑战，因为数据可能过于稀疏，无法拟合探测函数。我们对澳大利亚北昆士兰广泛海拔和纬度梯度上的多种热带雨林鸟类群落收集的距离抽样数据进行了分析。通过音频和视觉探测，我们评估了各种因素对有效条带宽度（ESW）的影响，ESW是一个直观有用的参数，因为它可用于根据计数数据计算密度估计值。体型和物种对ESW的影响最为重要，体型较大的物种比体型较小的物种在更远的距离上可被探测到。其次，潮湿天气和高灌木密度会降低大多数物种的ESW。几种物种的ESW在夏季和冬季也有所不同，这可能是由于鸣叫行为的季节性差异。在这些环境中，距离抽样在后勤方面证明难度较大，但物种之间ESW的巨大差异证实了需要校正探测概率以获得准确的密度估计值。我们的结果提出了一种基于证据的方法来控制影响可探测性的因素，以及进一步工作的途径，包括将可探测性建模为体型和鸣叫特征等物种特征的函数。这样的模型可能有助于为非距离抽样数据制定校准方法，并估计珍稀物种的可探测性。
