Salako, GabrielRussell, David J.Stucke, AndresEberhardt, Einar2023-05-162023-05-162023-04-19Salako, G., Russell, D.J., Stucke, A. et al. Assessment of multiple model algorithms to predict earthworm geographic distribution range and biodiversity in Germany: implications for soil-monitoring and species-conservation needs. Biodivers Conserv (2023). https://doi.org/10.1007/s10531-023-02608-9https://doi.org/10.1007/s10531-023-02608-9https://hdl.handle.net/20.500.14096/362© The Author(s) 2023. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Version of Scholarly Record of this Article is published in Biodiversity and Conservation, 2023, available online at: https://link.springer.com/article/10.1007/s10531-023-02608-9 . Keywords: density; species richness; spatial distribution; modelling; biodiversity.Identifying the potential distribution of soil-biodiversity with its density and richness relationships, including constituent species, is a pre-requisite for the assessment, conservation and protection of soil biodiversity and the soil functions it drives. Although the role of earthworms in improving soil quality has long been established, to quantitatively and spatially assess how this soil-animal group’s distribution changes along environmental gradients and geographic space and the identification of the drivers of such change has not been fully investigated. This comprehensive study aimed at modelling and mapping earthworm spatial distribution and diversity patterns to determine their conservation needs and provide baseline reference data for Germany. The study compared multiple modelling algorithms to map earthworm community parameters and 12 species-specific distribution probabilities, calculate their geographic range sizes and determine responses to environmental predictor variables. Three general patterns of spatial distribution ranges were identified by the model predictions (large-range, mid-range, and restricted-range species) with the corresponding environmental contributions to the predictions. Modelled species responses to environmental predictors confirm observed environmental drivers of earthworm distribution in Germany. The range classes based both on distributional level and geographic space provide the necessary information for identifying conservation and decision-making priorities, especially for restricted-distribution species as well as those with clearly defined habitat preferences.enArticle