Wildlife Conservation Research Unit, The Recanati-Kaplan Centre, University of Oxford, Department of Zoology, Tubney, Abingdon OX13 SQL, UK.
Ecology. 2012 Jul;93(7):1741-51. doi: 10.1890/11-2110.1.
A productive way forward in studies of animal populations is to efficiently make use of all the information available, either as raw data or as published sources, on critical parameters of interest. In this study, we demonstrate two approaches to the use of multiple sources of information on a parameter of fundamental interest to ecologists: animal density. The first approach produces estimates simultaneously from two different sources of data. The second approach was developed for situations in which initial data collection and analysis are followed up by subsequent data collection and prior knowledge is updated with new data using a stepwise process. Both approaches are used to estimate density of a rare and elusive predator, the tiger, by combining photographic and fecal DNA spatial capture-recapture data. The model, which combined information, provided the most precise estimate of density (8.5 +/- 1.95 tigers/100 km2 [posterior mean +/- SD]) relative to a model that utilized only one data source (photographic, 12.02 +/- 3.02 tigers/100 km2 and fecal DNA, 6.65 +/- 2.37 tigers/100 km2). Our study demonstrates that, by accounting for multiple sources of available information, estimates of animal density can be significantly improved.
在动物种群研究中，向前推进的一个富有成效的方法是有效地利用所有可用的信息，无论是作为原始数据还是作为有价值的已发表来源，来获取关键参数。在这项研究中，我们展示了两种利用对生态学家基本感兴趣的参数的多种信息来源的方法：动物密度。第一种方法可以同时从两种不同的数据来源生成估计值。第二种方法是为以下情况开发的：在初始数据收集和分析之后，会进行后续的数据收集，并使用逐步过程用新数据更新先验知识。这两种方法都用于通过结合照片和粪便 DNA 空间捕获-再捕获数据来估计稀有而难以捉摸的捕食者——老虎的密度。与仅利用一种数据源（照片，12.02 +/- 3.02 只老虎/100 平方公里和粪便 DNA，6.65 +/- 2.37 只老虎/100 平方公里）的模型相比，结合信息的模型提供了最精确的密度估计值（8.5 +/- 1.95 只老虎/100 平方公里）。我们的研究表明，通过考虑多种可用信息来源，可以显著提高动物密度的估计值。
