Summary
This study validates species distribution modelling approaches by comparing MaxEnt predictions against spatial abundance models derived from a large Amazonian forest plot dataset. The authors found weak but significant positive relationships between natural history collection distributions and both abundance and distribution models, and propose a data quality pipeline that conservatively estimates species area of occupancy whilst removing spatial biases in museum specimen occurrence records. The findings suggest that presence-only SDMs should be applied cautiously in large biodiversity assessments without manual verification, particularly where automatic processing is used.
Regional applicability
This study focuses on Amazonian tropical forest species and methodologies for validating species occurrence data. Whilst the specific taxonomic and ecological context is tropical, the methodological framework for reconciling museum specimen bias with field plot data could inform UK biodiversity assessment practices, particularly for national conservation and IUCN assessments where distribution model accuracy is critical.
Key measures
Spatial correlation between natural history collection distributions and inverse distance weighting abundance models; sensitivity; area of occupancy estimates; data consistency metrics
Outcomes reported
The study compared presence-only species distribution models (MaxEnt) with spatial abundance models based on plot data for Amazonian tree species, and proposed a pipeline to improve occurrence data quality and estimate area of occupancy.
Topic tags
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