Evidence map›Paper›PMID 38034327›Full record

ArticleEcology and evolution2023

Predicting the spatial expansion of an animal population with presence-only data.

Owain Barton, John R Healey, Line S Cordes, Andrew J Davies, Graeme Shannon

Abstract read
In one paragraph

Article in Ecology and evolution, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

5 authors.

Owain BartonSchool of Natural Sciences Bangor University Bangor UK.ORCID https://orcid.org/0000-0002-6181-8469
John R HealeySchool of Natural Sciences Bangor University Bangor UK.
Line S CordesNorwegian Institute for Nature Research Trondheim Norway.
Andrew J DaviesDepartment of Biological Sciences University of Rhode Island Kingston Rhode Island USA.
Graeme ShannonSchool of Natural Sciences Bangor University Bangor UK.ORCID https://orcid.org/0000-0002-5039-4904

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Predictive models can improve the efficiency of wildlife management by guiding actions at the local, landscape and regional scales. In recent decades, a vast range of modelling techniques have been developed to predict species distributions and patterns of population spread. However, data limitations often constrain the precision and biological realism of models, which make them less useful for supporting decision-making. Complex models can also be challenging to evaluate, and the results are often difficult to interpret for wildlife management practitioners. There is therefore a need to develop techniques that are appropriately robust, but also accessible to a range of end users. We developed a hybrid species distribution model that utilises commonly available presence-only distribution data and minimal demographic information to predict the spread of roe deer (

Indexed as

Capreolus capreolushybrid modelmechanisticpopulation managementpresence‐only datarange expansionspatially explicit spreadwildlife management

Identifiers

PMID38034327
PMCPMC10681852

What OpenQuestion holds

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LicenceCC BY
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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.