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人口统计学与环境的关系可以提高对气候变化下物种分布动态的机制理解。

Demography-environment relationships improve mechanistic understanding of range dynamics under climate change.

机构信息

Institute for Biochemistry and Biology, University of Potsdam, 14469 Potsdam, Germany.

Theoretical Ecology Lab, Faculty of Biology and Pre-Clinical Medicine, University of Regensburg, 93053 Regensburg, Germany.

出版信息

Philos Trans R Soc Lond B Biol Sci. 2023 Jul 17;378(1881):20220194. doi: 10.1098/rstb.2022.0194. Epub 2023 May 29.

Abstract

Species respond to climate change with range and abundance dynamics. To better explain and predict them, we need a mechanistic understanding of how the underlying demographic processes are shaped by climatic conditions. Here, we aim to infer demography-climate relationships from distribution and abundance data. For this, we developed spatially explicit, process-based models for eight Swiss breeding bird populations. These jointly consider dispersal, population dynamics and the climate-dependence of three demographic processes-juvenile survival, adult survival and fecundity. The models were calibrated to 267 nationwide abundance time series in a Bayesian framework. The fitted models showed moderate to excellent goodness-of-fit and discriminatory power. The most influential climatic predictors for population performance were the mean breeding-season temperature and the total winter precipitation. Contemporary climate change benefitted the population trends of typical mountain birds leading to lower population losses or even slight increases, whereas lowland birds were adversely affected. Our results emphasize that generic process-based models embedded in a robust statistical framework can improve our predictions of range dynamics and may allow disentangling of the underlying processes. For future research, we advocate a stronger integration of experimental and empirical studies in order to gain more precise insights into the mechanisms by which climate affects populations. This article is part of the theme issue 'Detecting and attributing the causes of biodiversity change: needs, gaps and solutions'.

摘要

物种通过分布范围和数量动态来应对气候变化。为了更好地解释和预测这些变化,我们需要深入了解气候条件如何塑造潜在的种群动态过程。在这里,我们旨在从分布和数量数据中推断出种群动态与气候的关系。为此,我们针对 8 种瑞士繁殖鸟类种群开发了具有空间异质性的、基于过程的模型。这些模型综合考虑了扩散、种群动态以及三个种群动态过程(幼体存活率、成体存活率和繁殖力)对气候的依赖性。这些模型是在贝叶斯框架下通过 267 个全国性的数量时间序列进行校准的。拟合模型显示出中等至良好的拟合优度和区分能力。对种群表现影响最大的气候预测因子是繁殖季节的平均温度和整个冬季的降水量。当代气候变化使典型山地鸟类的种群趋势受益,导致种群损失降低,甚至略有增加,而低地鸟类则受到不利影响。我们的研究结果强调,嵌入稳健统计框架中的通用基于过程的模型可以提高我们对分布动态的预测能力,并可能有助于厘清潜在的种群动态过程。在未来的研究中,我们提倡更加强化实验和实证研究的整合,以便更准确地了解气候影响种群的机制。本文是主题为“检测和归因生物多样性变化的原因:需求、差距和解决方案”的一部分。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c15b/10225853/b7ee662cf614/rstb20220194f01.jpg

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