Preprints

[Final version available] Explainable Artificial Intelligence enhances the ecological interpretability of black-box species distribution models

Masahiro Ryo, Boyan Angelov, Stefano Mammola, et al.

Published: 2020-04-17
Subjects: Artificial Intelligence and Robotics, Biodiversity, Computer Sciences, Ecology and Evolutionary Biology, Life Sciences, Physical Sciences and Mathematics, Research Methods in Life Sciences, Terrestrial and Aquatic Ecology

Species distribution models (SDMs) are widely used in ecology, biogeography and conservation biology to estimate relationships between environmental variables and species occurrence data and make predictions of how their distributions vary in space and time. During the past two decades, the field has increasingly made use of machine learning approaches for constructing and validating SDMs. Model [...]