Jeffrey W. Doser, Andrew O. Finley, Marc Kéry, Elise F. Zipkin
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引用次数: 0
摘要
有许多建模技术可用于估算动植物种群的丰度。最准确的方法能考虑生态数据中的多种复杂因素，如观测偏差、空间自相关性和物种相关性。然而，目前缺乏用户友好且计算效率高的软件来实现各种模型，尤其是针对大型数据集。我们开发了 spAbundance R 软件包，用于拟合空间明确的贝叶斯单物种和多物种分层距离采样模型、N 混合物模型和广义线性混合模型。该软件包中的模型可以利用近邻高斯过程（Nearest Neighbour Gaussian Processes）考虑空间自相关性，并利用潜在因子方法在多物种模型中考虑物种相关性，从而可以对具有大量地点和/或物种的数据集进行模型拟合。我们提供了三个小故事和三个案例研究，以突出 spAbundance 的功能。我们使用空间显式多物种距离采样模型估算了美国佛罗里达州 16 种鸟类的密度，使用 N 混合模型估算了美国新罕布什尔州黑喉蓝莺（Setophaga caerulescens）的丰度，并使用空间线性混合模型估算了美国大陆森林地上生物量。该软件包可作为生态学家和保护工作者的有用工具，用于改进对种群和群落丰度空间驱动因素的推断和预测。
期刊介绍：
A British Ecological Society journal, Methods in Ecology and Evolution (MEE) promotes the development of new methods in ecology and evolution, and facilitates their dissemination and uptake by the research community. MEE brings together papers from previously disparate sub-disciplines to provide a single forum for tracking methodological developments in all areas.
MEE publishes methodological papers in any area of ecology and evolution, including:
-Phylogenetic analysis
-Statistical methods
-Conservation & management
-Theoretical methods
-Practical methods, including lab and field
-This list is not exhaustive, and we welcome enquiries about possible submissions. Methods are defined in the widest terms and may be analytical, practical or conceptual.
A primary aim of the journal is to maximise the uptake of techniques by the community. We recognise that a major stumbling block in the uptake and application of new methods is the accessibility of methods. For example, users may need computer code, example applications or demonstrations of methods.
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