Resolving misaligned spatial data with integrated species distribution models.

ABSTRACT: Advances in species distribution modeling continue to be driven by a need to predict species responses to environmental change coupled with increasing data availability. Recent work has focused on development of methods that integrate multiple streams of data to model species distributions. Combining sources of information increases spatial coverage and can improve accuracy in estimates of species distributions. However, when fusing multiple streams of data, the temporal and spatial resolutions of data sources may be mismatched. This occurs when data sources have fluctuating geographic coverage, varying spatial scales and resolutions, and differing sources of bias and sparsity. It is well documented in the spatial statistics literature that ignoring the misalignment of different data sourc

SUBMITTER: Pacifici K 

PROVIDER: S-EPMC6851831 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature