Most knowledge about species and habitats is in-homogeneously distributed, with biases
existing in space, time and taxonomic and functional knowledge. Yet, controversially the …

Malaria importation is one of the hypothetical drivers of malaria transmission dynamics
across the globe. Several studies on malaria importation focused on the effect of the use of …

Spatial neighboring graphs play a crucial role in accounting for global spatial dependency,
particularly in spatial models that utilize the Conditional Autoregressive (CAR) covariance …

Gaussian processes (GPs), implemented through multivariate Gaussian distributions for a
finite collection of data, are the most popular approach in small-area spatial statistical …

As malaria incidence decreases and more countries move towards elimination, maps of
malaria risk in low-prevalence areas are increasingly needed. For low-burden areas …

For species of conservation concern and human–wildlife conflict, it is imperative that spatial
population data be available to design adaptive‐management strategies and be prepared to …

For many survey-based spatial modelling problems, responses are observed as spatially
aggregated over survey regions due to limited resources. Covariates, from weather models …

This paper addresses the challenge of obtaining precise demographic information at a fine-
grained spatial level, a necessity for planning localized public services such as water …

Open data is frequently released spatially aggregated, usually to comply with privacy
policies. However, coarse heterogeneous aggregations complicate learning and integration …

Accurate predictions of the populations and spatial distributions of wild animal species is
critical from a species management and conservation perspective. Culling is a measure …