Sparse modeling for climate variable selection across trophic levels
Sparse modeling for climate variable selection across trophic levels is a scholarly work by Eliza M. Grames, published in 2024 in ''Ecology''. The main subjects of the publication include selection (genetic algorithm), environmental niche modelling, conservation biology, global warming, ecology, abiotic component, pollinator decline, glossary of archaeology, trophic level, variable, geography, and population. The authors used a Bayesian sparse modeling approach to select among 80 metrics of climate and applied the approach to 19 datasets of bird, insect, and plant population responses to abiotic conditions as case studies of how the method can be applied for climate variable selection in a time series context.