期刊名称：Proceedings of the National Academy of Sciences
印刷版ISSN：0027-8424
电子版ISSN：1091-6490
出版年度：2020
卷号：117
期号：38
页码：23208-23210
DOI：10.1073/pnas.2016537117
出版社：The National Academy of Sciences of the United States of America
摘要：To detect biodiversity changes, biologists can rely on time series of historical observations and resurveys (1⇓–3). As global climate is warming, there is a staggering number of studies detecting population losses (i.e., local extinction or extirpation events), species range shifts (e.g., leading-edge expansion), and community reshuffling (e.g., biotic homogenization) (4⇓–6). However, to attribute these detections to specific factors, with the aim to hone our predictive tools, is a more challenging task and still a nascent research area. Recent work suggests that not only the magnitude of climate change matters to explain the observed variation in biodiversity changes but also the ambient climate context from historical surveys (i.e., baseline climatic conditions) (7) as well as the interaction between the two (4, 5) (Fig. 1). For instance, under similar velocities of climate change, marine species coming from initially warm waters are shifting their geographical range poleward much faster than those coming from initially cold waters (5). These complex interactions generate climate context dependencies (Fig. 1) and thus complicate our understanding of biodiversity responses to anthropogenic climate change. Yet, the total contribution of climate context dependencies, like the one example mentioned above to explain the observed variation in biodiversity redistribution under climate change, remains relatively low (5), thus bringing into question the relevance of complicating models that rely on climatic predictors only. In a study in PNAS, Vandvik et al. (8) propose to simplify the use of complex interaction terms between climatic variables in models to explain, and potentially predict, biodiversity responses to anthropogenic climate change by rethinking climate context dependencies in biological terms.
