An intuitive approach for measuring the resilience of biological communities to environmental change [Research highlights]

Bowler, Diana. 2024 An intuitive approach for measuring the resilience of biological communities to environmental change [Research highlights]. Journal of Animal Ecology, 93 (1). 4-7.

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Research Highlight: Sæther, B. E., Engen, S., & Solbu, E. B. (2023a). Assessing the sensitivity and resistance of communities in a changing environment. Journal of Animal Ecology. In the face of global change, conservation strategies can be informed by understanding which biological communities are most at risk. Metrics that reflect the ‘resilience’ of communities to change could have great utility, but there is still no consensus on the most useful way to measure it. Sæther et al. introduce an intuitive approach to thinking about and measuring resilience based on how variation in the total number of individuals within a community affects the number of species. By using dynamic species abundance distribution models, they also quantify the different sources of population-level variation that contribute to community resilience. Evenness emerges as an important predictor of resilience, with more even communities predicted to be more sensitive to abundance loss. An attractive feature of their approach is the ability to estimate the key parameters using commonly used generalized linear mixed effects models, which they illustrate with a case study on forest bird communities. The approach is ripe for comparison across different systems to explore how these proposed metrics complement existing biodiversity metrics and how they help understand the risk of communities from environmental change.

Item Type: Publication - Article
Digital Object Identifier (DOI):
UKCEH and CEH Sections/Science Areas: Biodiversity (Science Area 2017-)
ISSN: 0021-8790
Additional Keywords: biodiversity indicators, biodiversity loss, compositional change, environmental change, stability
NORA Subject Terms: Ecology and Environment
Date made live: 11 Dec 2023 13:27 +0 (UTC)

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