Evidence map›Paper›PMID 24134332›Full record

ArticleEcology letters2013

Predicting species distributions for conservation decisions.

Antoine Guisan, Reid Tingley, John B Baumgartner, Ilona Naujokaitis-Lewis, Patricia R Sutcliffe, Ayesha I T Tulloch, Tracey J Regan, Lluis Brotons, Eve McDonald-Madden, Chrystal Mantyka-Pringle and 13 more

Abstract read
In one paragraph

Article in Ecology letters, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 327 papers.

0numbers the graph read from it
0cells of the map it votes in
327citing 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

327 citing papers in PubMed.

  1. Article
  2. Article
  3. Environmental Drivers of Habitat Suitability for Shortbill Spearfish (Animals : an open access journal from MDPI · 2026
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  7. Distribution Shifts ofEcology and evolution · 2026
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  8. Article
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  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Prediction of the Potential Distribution ofEcology and evolution · 2026
    Article
  16. Article
  17. Article
  18. Climate-driven invasion ofOne health (Amsterdam, Netherlands) · 2026
    Article
  19. Article
  20. Article

267 more citing papers are in PubMed but not listed here.

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

23 authors.

Antoine GuisanDepartment of Ecology and Evolution, University of Lausanne, 1015, Lausanne, Switzerland; Institute of Earth Surface Dynamics, University of Lausanne, 1015, Lausanne, Switzerland; ARC Centre of Excellence for Environmental Decisions (CEED), School of Biological Sciences, The University of Queensland, St Lucia, Brisbane, Qld, 4072, Australia; CSIRO Ecosystem Sciences, Ecosciences Precinct, Dutton Park, Brisbane, Qld, 4102, Australia.
Reid Tingley
John B Baumgartner
Ilona Naujokaitis-Lewis
Patricia R Sutcliffe
Ayesha I T Tulloch
Tracey J Regan
Lluis Brotons
Eve McDonald-Madden
Chrystal Mantyka-Pringle
Tara G Martin
Jonathan R Rhodes
Ramona Maggini
Samantha A Setterfield
Jane Elith
Mark W Schwartz
Brendan A Wintle
Olivier Broennimann
Mike Austin
Simon Ferrier
Michael R Kearney
Hugh P Possingham
Yvonne M Buckley

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Species distribution models (SDMs) are increasingly proposed to support conservation decision making. However, evidence of SDMs supporting solutions for on-ground conservation problems is still scarce in the scientific literature. Here, we show that successful examples exist but are still largely hidden in the grey literature, and thus less accessible for analysis and learning. Furthermore, the decision framework within which SDMs are used is rarely made explicit. Using case studies from biological invasions, identification of critical habitats, reserve selection and translocation of endangered species, we propose that SDMs may be tailored to suit a range of decision-making contexts when used within a structured and transparent decision-making process. To construct appropriate SDMs to more effectively guide conservation actions, modellers need to better understand the decision process, and decision makers need to provide feedback to modellers regarding the actual use of SDMs to support conservation decisions. This could be facilitated by individuals or institutions playing the role of 'translators' between modellers and decision makers. We encourage species distribution modellers to get involved in real decision-making processes that will benefit from their technical input; this strategy has the potential to better bridge theory and practice, and contribute to improve both scientific knowledge and conservation outcomes.

Indexed as

Conservation of Natural ResourcesDecision Support TechniquesModels, TheoreticalDecision MakingEcologyEndangered SpeciesResearch DesignBiological invasionsconservation planningcritical habitatsenvironmental suitabilityreserve selectionspecies distribution modelstructured decision makingtranslocation

Identifiers

PMID24134332
PMCPMC4280402

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.