With the expansion in the quantity and types of biodiversity data being collected, there is a
need to find ways to combine these different sources to provide cohesive summaries of …

Presence‐only data are widely used for species distribution modelling, and point process
regression models are a flexible tool that has considerable potential for this problem, when …

Popular frameworks for studying habitat selection include resource‐selection functions
(RSFs) and step‐selection functions (SSFs), estimated using logistic and conditional logistic …

The study of animal movement has always been a key element in ecological science,
because it is inherently linked to critical processes that scale from individuals to populations …

Ecological data often exhibit spatial pattern, which can be modeled as autocorrelation.
Conditional autoregressive (CAR) and simultaneous autoregressive (SAR) models are …

Infectious diseases are strong drivers of wildlife population dynamics, however, empirical
analyses from the early stages of pathogen emergence are rare. Tasmanian devil facial …

Over the last two decades spatial point pattern analysis (SPPA) has become increasingly
popular in ecological research. To direct future work in this area we review studies using …

Electric vehicles (EVs) are increasingly considered as a promising solution to tackle climate
change impacts, improve air quality, and enhance growth sustainability. This paper …

This forecasting approach may be useful for water managers and associated public health
managers to predict near-term future high-risk cyanobacterial harmful algal blooms …

The High Burden High Impact (HBHI) strategy for malaria encourages countries to use
multiple sources of available data to define the sub-national vulnerabilities to malaria risk …