Reliable species distributions are obtainable with sparse, patchy and biased data by leveraging over species and data types

Abstract New methods for species distribution models (SDMs) utilise presence–absence (PA) data to correct the sampling bias of presence‐only (PO) data in a spatial point process setting. These have been shown to improve species estimates when both datasets are large and dense. However, is a PA dataset that is smaller and patchier than hitherto examined able to do the same? Furthermore, when both datasets are relatively small, is there enough information contained within them to produce a useful estimate of species' distributions? These attributes are common in many applications. A stochastic s... Mehr ...