ReviewEcology letters2026
Variability, Drivers, and Utility of Genetic Diversity-Area Relationships in Terrestrial Vertebrates.
Review in Ecology letters, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Variability, Drivers, and Utility of Genetic Diversity-Area Relationships in Terrestrial Vertebrates.Ecology letters · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Maintaining genetic diversity within and among populations is critical for conservation and a prominent goal of the Kunming-Montreal Global Biodiversity Framework. However, direct estimates of genetic diversity are unavailable for most species, and time and resources are insufficient to fill these substantial data gaps and meet conservation target timelines. We evaluated a proxy-based prediction of genetic diversity loss, the Genetic Diversity Area Relationship (GDAR), which describes relationships between genetic diversity and the geographic area occupied by a species. We estimated differences in three metrics of genetic diversity relative to sample area using 55 previously published datasets from 51 species. GDARs were highly variable across species and strongly dependent on population structure, with no clear differences across vertebrate classes. Traits correlated with population structure and study area explained 35%-45% of the variation in GDARs. Across genetic diversity metrics, prediction accuracy was highest for GDARs estimated from allele count compared to allelic richness and gene diversity. Our findings suggest there are opportunities for refining taxon-specific GDARs to predict genetic diversity loss following area loss in the absence of genetic data.
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.