Modelling and spatial prediction of earthworms ecological-categories distribution reveal their habitat and environmental preferences

作者：Gabriel Salako, Andrey S. Zaitsev, Bibiana Betancur‐Corredor, David J. Russell · 发表于：Ecological Indicators · 年份：2024 · DOI：10.1016/j.ecolind.2024.112832 · 被引用次数：8 · 研究领域：Invertebrate Taxonomy and Ecology、Species Distribution and Climate Change、Ecology and biodiversity studies

• Earthworms play a vital role in soil system dynamics and processes. • This soil animal shows preferences for certain habitat and environmental condition. • Determination of these environmental thresholds is important as baseline for soil biodiversity Earthworms are one of the important soil animals and have been generally described as soil engineers. Knowledge on environmental conditions driving the distribution and population of this soil animal and the habitat which support these conditions especially at the ecological level is required to understand their responses to these environmental conditions at different habitats so as to guide its usage as bio indicator of soil quality and health. In this study we use RandomForest (RF), a machine learning algorithm to model species distribution, density/abundance based (SDM/SAM) and predict the biodiversity distribution (richness and density, ind.m −2 ) of three basic earthworms ecological categories: epigeic, endogeic and anecic (including the epi-anecic subcategory) across soil and climate variables at multiple habitat type/land uses in Germany. Our study shows there are spatial/ geographic variation in the distribution of the species richness and density among the three earthworms’ ecological categories. Also their environmental and habitat preferences are equally different, while epigeic species are predicted to be climate driven mostly in forests, endogeics are predicted to be the most diverse (in richness and density), but ...