Evidence map›Paper›PMID 25469163›Full record

ArticleEvolutionary applications2014

Applying evolutionary concepts to wildlife disease ecology and management.

Eric Vander Wal, Dany Garant, Sophie Calmé, Colin A Chapman, Marco Festa-Bianchet, Virginie Millien, Sébastien Rioux-Paquette, Fanie Pelletier

Abstract read
In one paragraph

Article in Evolutionary applications, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Contrasting Patterns of Raccoon (Evolutionary applications · 2025
    Article
  5. Are rabid raccoons (Evolutionary applications · 2023
    Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Lessons from sea louse and salmon epidemiology.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2016
    Review
  16. Article
  17. Article
  18. Article
  19. 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

8 authors.

Eric Vander WalDépartement de biologie, Université de Sherbrooke Sherbrooke, QC, Canada.
Dany GarantDépartement de biologie, Université de Sherbrooke Sherbrooke, QC, Canada.
Sophie CalméDépartement de biologie, Université de Sherbrooke Sherbrooke, QC, Canada ; El Colegio de la Frontera Sur Chetumal, Quintana Roo, Mexico.
Colin A ChapmanDepartment of Anthropology and McGill School of Environment, McGill University Montreal, QC, Canada ; Wildlife Conservation Society Bronx, New York, NY, USA.
Marco Festa-BianchetDépartement de biologie, Université de Sherbrooke Sherbrooke, QC, Canada.
Virginie MillienRedpath Museum, McGill University Montreal, QC, Canada.
Sébastien Rioux-PaquetteDépartement de biologie, Université de Sherbrooke Sherbrooke, QC, Canada.
Fanie PelletierDépartement de biologie, Université de Sherbrooke Sherbrooke, QC, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Existing and emerging infectious diseases are among the most pressing global threats to biodiversity, food safety and human health. The complex interplay between host, pathogen and environment creates a challenge for conserving species, communities and ecosystem functions, while mediating the many known ecological and socio-economic negative effects of disease. Despite the clear ecological and evolutionary contexts of host-pathogen dynamics, approaches to managing wildlife disease remain predominantly reactionary, focusing on surveillance and some attempts at eradication. A few exceptional studies have heeded recent calls for better integration of ecological concepts in the study and management of wildlife disease; however, evolutionary concepts remain underused. Applied evolution consists of four principles: evolutionary history, genetic and phenotypic variation, selection and eco-evolutionary dynamics. In this article, we first update a classical framework for understanding wildlife disease to integrate better these principles. Within this framework, we explore the evolutionary implications of environment-disease interactions. Subsequently, we synthesize areas where applied evolution can be employed in wildlife disease management. Finally, we discuss some future directions and challenges. Here, we underscore that despite some evolutionary principles currently playing an important role in our understanding of disease in wild animals, considerable opportunities remain for fostering the practice of evolutionarily enlightened wildlife disease management.

Indexed as

conservationeco-evolutionary dynamicsenvironmental changeepidemiologyhost–pathogen interactionszoonosis

Identifiers

PMID25469163
PMCPMC4227862

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.