Data for: The meta-analysis of the effects of spatial sampling bias correction on presence only species distribution models

This dataset contains information extracted from 70 studies identified through a systematic review of the peer-reviewed literature (Web of Science and SCOPUS databases both searched on the 13/02/2023) to evaluate the effect of spatial sampling bias correction methods in presence-only species distribution models.

Methods
Web of Science and SCOPUS databases were searched on the 13/02/2023 using the following search string:

ALL=(("species distribution*" OR SDM OR "environmental niche" OR ENM OR "resource selection" OR "habitat selection" OR suitability OR occurrence) AND ("presence-only" OR “presence data” OR "presence-background" OR “pseudo absence” OR opportunistic OR “citizen science” OR preferential OR maxent OR biomod))

After removing duplicates, the search returned 8564 unique studies, and these were further filtered to remove studies that fell outside of the review subject area based on the title and abstract and then the remaining studies were filtered by content based on the criteria that they involved the building of SDMs using PO data (i.e. no absence information, including inferred absences from complete species lists) and that the study included a direct comparison between SDMs that attempted to correct models for SSB and models without this correction. To avoid ambiguity, studies were required to mention explicitly that a particular analytical approach was designed to account for SSB (e.g., not “filtering to reduce spatial autocorrelation”, which is ambiguous as to the cause of the spatial autocorrelation). This identified 70 studies from which information on the effect of SSB correction on model performance was extracted, along with metadata on species taxonomy, sample sizes of occurrence data, and details of the SDM methods and SSB correction approach used.