Evidence map›Paper›PMID 29145486›Full record

ArticlePloS one2017

Geography of current and future global mammal extinction risk.

Ana D Davidson, Kevin T Shoemaker, Ben Weinstein, Gabriel C Costa, Thomas M Brooks, Gerardo Ceballos, Volker C Radeloff, Carlo Rondinini, Catherine H Graham

Abstract read
In one paragraph

Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. The ghost of hosts past: impacts of host extinction on parasite specificity.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2021
    Article
  7. 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

9 authors.

Ana D DavidsonDepartment of Ecology and Evolution, Stony Brook University, Stony Brook, New York, United States of America.ORCID http://orcid.org/0000-0003-4701-5923
Kevin T ShoemakerDepartment of Natural Resources & Environmental Science, University of Nevada, Reno, Nevada, United States of America.
Ben WeinsteinDepartment of Ecology and Evolution, Stony Brook University, Stony Brook, New York, United States of America.
Gabriel C CostaDepartment of Biology, Auburn University at Montgomery, Montgomery, Alabama, United States of America.
Thomas M BrooksInternational Union for Conservation of Nature, Gland, Switzerland.
Gerardo CeballosInstituto de Ecologia, Universidad Nacional Autonoma de Mexico, México D.F., México.
Volker C RadeloffDepartment of Forest and Wildlife Ecology, University of Wisconsin-Madison, Wisconsin, United States of America.
Carlo RondininiGlobal Mammal Assessment program, Department of Biology and Biotechnologies, Sapienza University of Rome, Roma, Italy.
Catherine H GrahamDepartment of Ecology and Evolution, Stony Brook University, Stony Brook, New York, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Identifying which species are at greatest risk, what makes them vulnerable, and where they are distributed are central goals for conservation science. While knowledge of which factors influence extinction risk is increasingly available for some taxonomic groups, a deeper understanding of extinction correlates and the geography of risk remains lacking. Here, we develop a predictive random forest model using both geospatial and mammalian species' trait data to uncover the statistical and geographic distributions of extinction correlates. We also explore how this geography of risk may change under a rapidly warming climate. We found distinctive macroecological relationships between species-level risk and extinction correlates, including the intrinsic biological traits of geographic range size, body size and taxonomy, and extrinsic geographic settings such as seasonality, habitat type, land use and human population density. Each extinction correlate exhibited ranges of values that were especially associated with risk, and the importance of different risk factors was not geographically uniform across the globe. We also found that about 10% of mammals not currently recognized as at-risk have biological traits and occur in environments that predispose them towards extinction. Southeast Asia had the most actually and potentially threatened species, underscoring the urgent need for conservation in this region. Additionally, nearly 40% of currently threatened species were predicted to experience rapid climate change at 0.5 km/year or more. Biological and environmental correlates of mammalian extinction risk exhibit distinct statistical and geographic distributions. These results provide insight into species-level patterns and processes underlying geographic variation in extinction risk. They also offer guidance for future conservation research focused on specific geographic regions, or evaluating the degree to which species-level patterns mirror spatial variation in the pressures faced by populations within the ranges of individual species. The added impacts from climate change may increase the susceptibility of at-risk species to extinction and expand the regions where mammals are most vulnerable globally.

Indexed as

Extinction, BiologicalGeographyMammalsAnimalsClimate Change

Identifiers

PMID29145486
PMCPMC5690607

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.