Evidence map›Paper›PMID 40847557›Full record

ReviewEcology letters2025

Understanding and Predicting Population Response to Anthropogenic Disturbance: Current Approaches and Novel Opportunities.

Cassie N Speakman, Sarah Bull, Sarah Cubaynes, Katrina J Davis, Sébastien Devillard, John M Fryxell, Cara A Gallagher, Elizabeth A McHuron, Kévan Rastello, Isabel M Smallegange and 10 more

Abstract readReview
In one paragraph

Review in Ecology letters, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

20 authors.

Cassie N SpeakmanFRB-CESAB, Montpellier, France.ORCID https://orcid.org/0000-0002-0023-518X
Sarah BullDepartment of Biology, University of Oxford, Oxford, UK.
Sarah CubaynesCEFE, Univ Montpellier, CNRS, EPHE, IRD, Montpellier, France.
Katrina J DavisDepartment of Biology, University of Oxford, Oxford, UK.
Sébastien DevillardUniversite Claude Bernard Lyon 1, LBBE, UMR 5558, CNRS, VAS, Villeurbanne, France.
John M FryxellDepartment of Integrative Biology, University of Guelph, Guelph, Ontario, Canada.ORCID https://orcid.org/0000-0002-5278-8747
Cara A GallagherDepartment of Ecoscience, Aarhus University, Aarhus, Denmark.ORCID https://orcid.org/0000-0001-7094-1752
Elizabeth A McHuronCooperative Institute for Climate, Ocean, and Ecosystem Studies, University of Washington, Seattle, Washington, USA.
Kévan RastelloDepartment of Biology, University of Victoria, Victoria, British Columbia, Canada.
Isabel M SmallegangeSchool of Natural and Environmental Sciences, Newcastle University, Newcastle upon Tyne, UK.
Roberto Salguero-GómezDepartment of Biology, University of Oxford, Oxford, UK.ORCID https://orcid.org/0000-0002-6085-4433
Elsa BonnaudLaboratory Ecology Systematic and Evolution, UMR 8079, Université de Paris-Saclay, Gif-sur-Yvette, France.
Christophe DuchampFrench Biodiversity Agency (OFB), France.
Patrick GiraudouxChrono-Environment Lab, University Marie and Louis Pasteur/CNRS, Besançon, France.
Simon LacombeCEFE, Univ Montpellier, CNRS, EPHE, IRD, Montpellier, France.
Courtney J MarneweckGiraffe Conservation Foundation, Windhoek, Namibia.ORCID https://orcid.org/0000-0002-5064-1979
Louis SchrollCEFE, Univ Montpellier, CNRS, EPHE, IRD, Montpellier, France.
Adrien TableauFrench Biodiversity Agency (OFB), France.
Sandrine RuetteFrench Biodiversity Agency (OFB), France.
Olivier GimenezCEFE, Univ Montpellier, CNRS, EPHE, IRD, Montpellier, France.

Funding

Deutsche Forschungsgemeinschaft DFG-GRK 2118/1Natural Environment Research Council NE/X013766/1
6 · The paper itself

Abstract

Effective conservation of biodiversity depends on the successful management of wildlife populations and their habitats. Successful management, in turn, depends on our ability to understand and accurately forecast how populations and communities respond to human-induced changes in their environments. However, quantifying how these stressors impact population dynamics remains challenging. Another significant hurdle at this interface is determining which quantitative approach(es) are most appropriate given data types, constraints and the intended purpose. Here, we provide a cross-taxa overview of key methodological approaches (e.g., matrix population models) and model elements (e.g., energetics) that are currently used to model the effects of anthropogenic disturbance on wildlife populations. Specifically, we discuss how these modelling approaches differ in their key assumptions, in their structure and complexity, in the questions they are best poised to address and in their data requirements. Our intention is to help overcome some of the methodological biases that might persist across taxonomic specialisations, identify new opportunities to address existing modelling challenges and improve scientific understanding of the direct and indirect impacts of anthropogenic disturbance. We guide users through the identification of appropriate model configurations for different management purposes, while also suggesting key priorities for model development and integration.

Indexed as

Anthropogenic EffectsBiodiversityConservation of Natural ResourcesModels, BiologicalAnimalsEcosystemHumansPopulation Dynamics

Identifiers

PMID40847557
PMCPMC12374093

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.