A quixotic view of spatial bias in modelling the distribution of species and their diversity.

ABSTRACT: Ecological processes are often spatially and temporally structured, potentially leading to autocorrelation either in environmental variables or species distribution data. Because of that, spatially-biased in-situ samples or predictors might affect the outcomes of ecological models used to infer the geographic distribution of species and diversity. There is a vast heterogeneity of methods and approaches to assess and measure spatial bias; this paper aims at addressing the spatial component of data-driven biases in species distribution modelling, and to propose potential solutions to explicitly test and account for them. Our major goal is not to propose methods to remove spatial bias from the modelling procedure, which would be impossible without proper knowledge of all the processes generat

SUBMITTER: Rocchini D 

PROVIDER: S-EPMC11332097 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature