Spatially explicit species distribution models: A missed opportunity in conservation planning?

Species distribution Environmental niche modelling Grid cell
DOI: 10.1111/ddi.12891 Publication Date: 2019-01-30T08:42:36Z
ABSTRACT
Abstract Aim Systematic conservation planning is vital for allocating protected areas given the spatial distribution of features, such as species. Due to incomplete species inventories, models (SDMs) are often used predicting species’ habitat suitability and probability occurrence. Currently, SDMs mostly ignore dependencies in predictor data. Here, we provide a comparative evaluation how accounting dependencies, that is, autocorrelation, affects delineation optimized areas. Location Southeast Australia, U.S. Continental Shelf, Danube River Basin. Methods We employ Bayesian spatially explicit non‐spatial terrestrial, marine freshwater species, using realm‐specific unit shapes (grid, hexagon subcatchment, respectively). then apply software gurobi optimize plans based on targets derived from (10%–50% each analyse sensitivity), compare plans. Results Across realms irrespective shape, (a) produce average more accurate predictions terms AUC, TSS, sensitivity specificity, along with higher detection probability. All optimizations meet targets. Spatial use (b) substantially different compared those SDM predictions, but (c) encompass similar amount units. The overlap selection units smallest lowest vice versa. Main conclusions Species core tools planning. Not surprisingly, characteristics has drastic impacts therefore encourage practitioners consider features improve representation future
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