Spatial sampling bias and model complexity in stream-based species distribution models: a case study of Paddlefish (Polyodon spathula) in the Arkansas River basin, U.S.A.

Andrew Taylor, Thomas Hafen, Colt Holley, Alin González & James Long
Leveraging existing presence records and geospatial datasets, species distribution modeling has been widely applied to informing species conservation and restoration efforts. Maxent is one of the most popular modeling algorithms, yet recent research has demonstrated Maxent models are vulnerable to prediction errors related to spatial sampling bias and model complexity. Despite elevated rates of biodiversity imperilment in stream systems, the application of Maxent models to stream networks has lagged, as has the availability of tools...
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These counts follow the COUNTER Code of Practice, meaning that Internet robots and repeats within a certain time frame are excluded.
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