Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1111/gcb.16041 |
Detecting climate signals in populations across life histories | |
Sté; phanie Jenouvrier; Matthew C. Long; Christophe F. D. Coste; Marika Holland; Marlè; ne Gamelon; Nigel G. Yoccoz; Bernt-Erik Sæ; ther | |
2022-01-14 | |
发表期刊 | Global Change Biology |
出版年 | 2022 |
英文摘要 | Climate impacts are not always easily discerned in wild populations as detecting climate change signals in populations is challenged by stochastic noise associated with natural climate variability, variability in biotic and abiotic processes, and observation error in demographic rates. Detection of the impact of climate change on populations requires making a formal distinction between signals in the population associated with long-term climate trends from those generated by stochastic noise. The time of emergence (ToE) identifies when the signal of anthropogenic climate change can be quantitatively distinguished from natural climate variability. This concept has been applied extensively in the climate sciences, but has not been explored in the context of population dynamics. Here, we outline an approach to detecting climate-driven signals in populations based on an assessment of when climate change drives population dynamics beyond the envelope characteristic of stochastic variations in an unperturbed state. Specifically, we present a theoretical assessment of the time of emergence of climate-driven signals in population dynamics (). We identify the dependence of on the magnitude of both trends and variability in climate and also explore the effect of intrinsic demographic controls on . We demonstrate that different life histories (fast species vs. slow species), demographic processes (survival, reproduction), and the relationships between climate and demographic rates yield population dynamics that filter climate trends and variability differently. We illustrate empirically how to detect the point in time when anthropogenic signals in populations emerge from stochastic noise for a species threatened by climate change: the emperor penguin. Finally, we propose six testable hypotheses and a road map for future research. |
领域 | 气候变化 ; 资源环境 |
URL | 查看原文 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/345060 |
专题 | 气候变化 资源环境科学 |
推荐引用方式 GB/T 7714 | Sté,phanie Jenouvrier,Matthew C. Long,et al. Detecting climate signals in populations across life histories[J]. Global Change Biology,2022. |
APA | Sté.,phanie Jenouvrier.,Matthew C. Long.,Christophe F. D. Coste.,Marika Holland.,...&ther.(2022).Detecting climate signals in populations across life histories.Global Change Biology. |
MLA | Sté,et al."Detecting climate signals in populations across life histories".Global Change Biology (2022). |
条目包含的文件 | 条目无相关文件。 |
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