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Evaluating multi-season occupancy models with autocorrelation fitted to heterogeneous datasets
Predicting species distributions using occupancy models accounting for imperfect detection is now commonplace in ecology. Recently, modeling spatial and temporal autocorrelation was proposed to alleviate the lack of replication in occupancy data, which often prevents model identifiability. However,
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