Evidence map›Paper›PMID 21516382›Full record

ReviewEcotoxicology (London, England)2011

Quantitative genetics approaches to study evolutionary processes in ecotoxicology; a perspective from research on the evolution of resistance.

Paul L Klerks, Lingtian Xie, Jeffrey S Levinton

Abstract readReview
PubMed Publisher
In one paragraph

Review in Ecotoxicology (London, England), 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 1 pooled it
–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

27 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Evolutionary toxicology in an omics world.Evolutionary applications · 2017
    Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

3 authors.

Paul L KlerksDepartment of Biology, University of Louisiana at Lafayette, Lafayette, LA 70504, USA. klerks@louisiana.edu
Lingtian Xie
Jeffrey S Levinton

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Quantitative genetic approaches are often used to study evolutionary processes in ecotoxicology. This paper focuses on the evolution of resistance to environmental contaminants-an important evolutionary process in ecotoxicology. Three approaches are commonly employed to study the evolution of resistance: (1) Assessing whether a contaminant-exposed population has an increased resistance relative to a control population, using either spatial or temporal comparisons. (2) Estimating a population's heritability of resistance. (3) Investigating responses in a laboratory selection experiment. All three approaches provide valuable information on the potential for contaminants to affect a population's evolutionary trajectory via natural selection. However, all three approaches have inherent limitations, including difficulty in separating the various genetic and environmental variance components, responses being dependent on specific population and testing conditions, and inability to fully capture natural conditions in the laboratory. In order to maximize insights into the long-term consequences of adaptation, it is important to not just look at resistance itself, but also at the fitness consequences and at correlated responses in characteristics other than resistance. The rapid development of molecular genetics has yielded alternatives to the "black box" approach of quantitative genetics, but the presence of different limitations and strengths in the two fields means that they should be viewed as complementary rather than exchangeable. Quantitative genetics is benefiting from the incorporation of molecular tools and remains an important field for studying evolutionary toxicology.

Indexed as

Biological EvolutionAdaptation, PhysiologicalAnimalsEcotoxicologyEnvironmental PollutantsGenetics, PopulationGenetic VariationHeavy Metal PoisoningInvertebratesMetals, HeavyPlantsPoisoningSelection, GeneticEnvironmental PollutantsMetals, Heavy

Identifiers

What OpenQuestion holds

Textmetadata
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.