Evidence map›Paper›PMID 34465240›Full record

ArticleProceedings. Biological sciences2021

Spatial ecology of conflicts: unravelling patterns of wildlife damage at multiple scales.

Carlos Bautista, Eloy Revilla, Teresa Berezowska-Cnota, Néstor Fernández, Javier Naves, Nuria Selva

Abstract read
In one paragraph

Article in Proceedings. Biological sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Identifying the Risk Regions of Wild Boar (Animals : an open access journal from MDPI · 2023
    Article
  9. 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

6 authors.

Carlos BautistaInstitute of Nature Conservation of the Polish Academy of Sciences (IOP PAN), Adama Mickiewicza 33, 31-120 Kraków, Poland.ORCID 0000-0003-3979-797X
Eloy RevillaEstación Biológica de Doñana CSIC (EBD-CSIC), Americo Vespucio 26, 41092 Sevilla, Spain.ORCID 0000-0001-5534-5581
Teresa Berezowska-CnotaInstitute of Nature Conservation of the Polish Academy of Sciences (IOP PAN), Adama Mickiewicza 33, 31-120 Kraków, Poland.ORCID 0000-0002-2566-6672
Néstor FernándezGerman Centre for Integrative Biodiversity Research (iDiv), Halle-Jena-Leipzig, Puschstraße 4, 04103 Leipzig, Germany.ORCID 0000-0002-9645-8571
Javier NavesEstación Biológica de Doñana CSIC (EBD-CSIC), Americo Vespucio 26, 41092 Sevilla, Spain.ORCID 0000-0003-3773-0288
Nuria SelvaInstitute of Nature Conservation of the Polish Academy of Sciences (IOP PAN), Adama Mickiewicza 33, 31-120 Kraków, Poland.ORCID 0000-0003-3389-201X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Human encroachment into natural habitats is typically followed by conflicts derived from wildlife damage to agriculture and livestock. Spatial risk modelling is a useful tool to gain the understanding of wildlife damage and mitigate conflicts. Although resource selection is a hierarchical process operating at multiple scales, risk models usually fail to address more than one scale, which can result in the misidentification of the underlying processes. Here, we addressed the multi-scale nature of wildlife damage occurrence by considering ecological and management correlates interacting from household to landscape scales. We studied brown bear (

Indexed as

Animals, WildUrsidaeAgricultureAnimalsEcosystemHumansbeehiveshuman–wildlife coexistencemulti-scale analysisspatial risk modellingUrsus arctoswildlife damage

Identifiers

PMID34465240
PMCPMC8437235

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.