Evidence map›Paper›PMID 36515114›Full record

ArticleProceedings. Biological sciences2022

Metapopulation persistence can be inferred from incomplete surveys.

Chuliang Song, Marie-Josée Fortin, Andrew Gonzalez

Abstract read
In one paragraph

Article in Proceedings. Biological sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. A practical guide to characterising ecological coexistence.Biological reviews of the Cambridge Philosophical Society · 2026
    Review
  2. Rapid monitoring of ecological persistence.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  3. Article
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

3 authors.

Chuliang SongDepartment of Biology, Quebec Centre for Biodiversity Science, McGill University, Montreal, Canada H3A 1B1.ORCID 0000-0001-7490-8626
Marie-Josée FortinDepartment of Ecology and Evolutionary Biology, University of Toronto, Toronto, Canada M5S 3B2.ORCID 0000-0002-9935-1366
Andrew GonzalezDepartment of Biology, Quebec Centre for Biodiversity Science, McGill University, Montreal, Canada H3A 1B1.ORCID 0000-0001-6075-8081

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Habitat destruction and fragmentation are principal causes of species loss. While a local population might go extinct, a metapopulation-populations inhabiting habitat patches connected by dispersal-can persist regionally by recolonizing empty patches. To assess metapopulation persistence, two widely adopted indicators in conservation management are metapopulation capacity and patch importance. However, we face a fundamental limitation in that assessing metapopulation persistence requires that we survey or sample all the patches in a landscape: often these surveys are logistically challenging to conduct and repeat, which raises the question whether we can learn enough about the metapopulation persistence from an incomplete survey. Here, we provide a robust statistical approach to infer metapopulation capacity and patch importance by sampling a portion of all patches. We provided analytic arguments on why the metapopulation capacity and patch importance can be well predicted from sub-samples of habitat patches. Full-factorial simulations with more complex models corroborate our analytic predictions. We applied our model to an empirical metapopulation of mangrove hummingbirds (

Indexed as

EcosystemModels, BiologicalAnimalsBirdsPopulation Dynamicsconnectivity matrixincomplete surveylandscape matrixmetapopulation capacitypatch importance

Identifiers

PMID36515114
PMCPMC9748775

What OpenQuestion holds

Textmetadata
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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.