采用 INLA 的时空占用模型

IF 6.3 2区 环境科学与生态学 Q1 ECOLOGY
Jafet Belmont, Sara Martino, Janine Illian, Håvard Rue
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引用次数: 0

摘要

量化、预测和绘制物种分布图的现代方法在生物多样性保护方面发挥了至关重要的作用。由于占据模型能够区分因物种探测不完全而导致的观测误差以及影响占据过程的偏差来源,因此成为分析物种出现数据的热门选择。然而,由于拟合显式时空模型的计算成本过高,环境协变量无法解释的占据率的时空变化往往被忽视或通过简单的空间结构来模拟。在这项工作中,我们展示了如何利用集成嵌套拉普拉斯近似法(INLA)来拟合复杂的时空占用模型,以及 R-INLA 软件包如何提供用户友好界面,使用户可以使用这些复杂模型。我们展示了在对检测过程进行一定简化的前提下,如何将占用模型构建为潜在高斯模型,并从强大的 INLA 框架中获益。R-INLA 中已经实现了大量的复杂建模特征选择和随机效应模型,包括时空模型。这些模型也可用于占位模型,为用户提供了一个高效、可靠和灵活的工具箱。我们将通过两个复杂的案例研究,说明 INLA 如何为开发和拟合复杂的占用模型提供一个灵活且计算效率高的框架。通过这些案例,我们展示了如何将包含空间变化趋势、平滑项和时空随机效应的不同时空模型拟合到检测/非检测汇总数据中。以限制探测模型结构的复杂性为代价,INLA 可以在感兴趣的生态过程中纳入一系列相当复杂的结构,从而扩展占位模型的功能。占用模型在大型时空数据集的可扩展性方面的局限性仍然是一个挑战,也是一个活跃的研究领域。基于 INLA 的占用模型提供了另一种推理和计算框架,以适应复杂的时空占用模型。由于需要新的、更灵活、计算效率更高的方法来拟合这类模型,因此 INLA 成为解决复杂生态问题的一个有吸引力的选择,也是一个前景广阔的研究领域。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Spatio-temporal occupancy models with INLA

Spatio-temporal occupancy models with INLA

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来源期刊
CiteScore
11.60
自引率
3.00%
发文量
236
审稿时长
4-8 weeks
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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