ArticleMarine life science & technology2024
Incorporating physiological knowledge into correlative species distribution models minimizes bias introduced by the choice of calibration area.
Article in Marine life science & technology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Thermal Vulnerability of Reef Fish and Implications for Subsistence Fisheries Throughout the Caribbean.Global change biology · 2026Article
- Species-Specific Responses of Kiwifruit Seed Germination to Climate Change Using Classifier Modeling.Plants (Basel, Switzerland) · 2025Article
- Improving Distribution Prediction by Integrating Expert Range Maps and Opportunistic Occurrences: Evidence From Japanese Sea Cucumber.Ecology and evolution · 2025Article
- Mapping the potential for global offshore finfish mariculture.Marine life science & technology · 2024Article
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10 authors.
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Abstract
Correlative species distribution models (SDMs) are important tools to estimate species' geographic distribution across space and time, but their reliability heavily relies on the availability and quality of occurrence data. Estimations can be biased when occurrences do not fully represent the environmental requirement of a species. We tested to what extent species' physiological knowledge might influence SDM estimations. Focusing on the Japanese sea cucumber Supplementary Information: The online version contains supplementary material available at 10.1007/s42995-024-00226-0.
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