Year: 2023
Type: article
Abstract: PREMISE: Researchers often use ecological niche models to predict where species might establish and persist under future or novel climate conditions. However, these predictive methods assume species have stable niches across time and space. Furthermore, ignoring the time of occurrence data can obscure important information about species reproduction and ultimately fitness. Here, we assess compare ecological niche models generated from full-year averages to seasonal models. METHODS: In this study, we generate full-year and monthly ecological niche models for Capsella bursa-pastoris in Europe and North America to see if we can detect changes in the seasonal niche of the species after long-distance dispersal. RESULTS: We find full-year ecological niche models have low transferability across continents and there are continental differences in the climate conditions that influence the distribution of C. bursa-pastoris. Monthly models have greater predictive accuracy than full-year models in cooler seasons, but no monthly models can predict North American summer occurrences very well. CONCLUSIONS: The relative predictive ability of European monthly models compared to North American monthly models suggests a change in the seasonal timing between the native range to the non-native range. These results highlight the utility of ecological niche models at finer temporal scales in predicting species distributions and unmasking subtle patterns of evolution.
Source: American Journal of Botany
DOI: 10.1002/ajb2.16140
Authors: Maya K. Wilson Brown, Emily B. Josephs
Institution: Michigan State University
Language: English
Subfield: Ecological Modeling
Field: Environmental Science
Domain: Physical Sciences
SDG: Life on land
Open Access status: hybrid
Estimated APC paid: $2,000
OpenAlex ID: W4319662274