ArticleEvolutionary applications2015
Anthropogenic ecosystem fragmentation drives shared and unique patterns of sexual signal divergence among three species of Bahamian mosquitofish.
Article in Evolutionary applications, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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.
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.
Who cites it
6 citing papers in PubMed.
- Anthropogenic Change and the Process of Speciation.Cold Spring Harbor perspectives in biology · 2023Review
- Resource competition explains rare cannibalism in the wild in livebearing fishes.Ecology and evolution · 2022Article
- Strong spatial population structure shapes the temporal coevolutionary dynamics of costly female preference and male display.Evolution; international journal of organic evolution · 2022Article
- The evolutionary consequences of habitat fragmentation: Body morphology and coloration differentiation among brook trout populations of varying size.Ecology and evolution · 2017Article
- Sexual selection reinforces a higher flight endurance in urban damselflies.Evolutionary applications · 2017Article
- Dissolved organic carbon and unimodal variation in sexual signal coloration in mosquitofish: a role for light limitation?Proceedings. Biological sciences · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
When confronted with similar environmental challenges, different organisms can exhibit dissimilar phenotypic responses. Therefore, understanding patterns of phenotypic divergence for closely related species requires considering distinct evolutionary histories. Here, we investigated how a common form of human-induced environmental alteration, habitat fragmentation, may drive phenotypic divergence among three closely related species of Bahamian mosquitofish (Gambusia spp.). Focusing on one phenotypic trait (male coloration), having a priori predictions of divergence, we tested whether populations persisting in fragmented habitats differed from those inhabiting unfragmented habitats and examined the consistency of the pattern across species. Species exhibited both shared and unique patterns of phenotypic divergence between the two types of habitats, with shared patterns representing the stronger effect. For all species, populations in fragmented habitats had fewer dorsal-fin spots. In contrast, the magnitude and trajectory of divergence in dorsal-fin color, a sexually selected trait, differed among species. We identified fragmentation-mediated increased turbidity as a possible driver of these trait shifts. These results suggest that even closely related species can exhibit diverse phenotypic responses when encountering similar human-mediated selection regimes. This element of unpredictability complicates forecasting the phenotypic responses of wild organisms faced with anthropogenic change - an important component of biological conservation and ecosystem management.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.