Summary
This review examines statistical approaches for spatial modelling of biodiversity at the community level, contrasting community-level modelling with traditional species-by-species approaches. The authors present three broad modelling strategies and discuss their relative strengths and weaknesses, arguing that community-level modelling offers advantages for applications involving large numbers of species, particularly those recorded infrequently, by synthesising complex multispecies data into forms more readily interpretable by scientists and decision-makers.
Regional applicability
The paper is methodological and geographic-agnostic, presenting modelling frameworks applicable to biodiversity assessment and land-use planning across any region. Its relevance to United Kingdom practice would depend on adoption of these approaches in UK biodiversity surveys and environmental planning, where spatial modelling of community-level biodiversity could inform habitat management and conservation prioritisation.
Key measures
Spatial modelling strategies; community-level biodiversity outputs; species richness; compositional dissimilarity; environmental predictors; species distribution patterns
Outcomes reported
The paper compares three modelling strategies for predicting spatial patterns of biodiversity at community level using environmental predictors: assemble-first-predict-later, predict-first-assemble-later, and assemble-and-predict-together approaches. It evaluates how community-level modelling can synthesise multispecies data into outputs including predictive maps of community types, species groups, compositional gradients, and macroecological properties.
Topic tags
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