Conservation science depends on an accurate understanding of what's happening in a
given ecosystem. How many species live there? What is the makeup of the population? How …

In pursuit of a more robust provenance in the field of species distribution modelling, an
extensive literature search was undertaken to find the typical default values, and the range …

Species distribution models (SDMs) are empirical models relating species occurrence to
environmental variables based on statistical or other response surfaces. Species distribution …

This paper introduces four representative machine learning (ML) methods, ie, random forest,
MaxEnt, support vector machine and artificial neural network and reviews their application in …

Sustainable management efforts are currently hindered by a lack of basic information about
the spatial distribution of species on large landscapes. Based on complex ecological …

SDMs are not new to conservation, but their popularity has increased dramatically in recent
years. This step-by-step review provides an overview of the efficacy of SDMs in guiding …

Over the past decade the number of statistical modelling tools available to ecologists to
model species' distributions has increased at a rapid pace (eg Elith et al. 2006; Austin 2007) …

Joint species distribution models (JSDM s) account for biotic interactions and missing
environmental predictors in correlative species distribution models. Several different JSDM s …

Scientists and decision-makers need tools that can assess which specific pressures lead to
ecosystem deterioration, and which measures could reduce these pressures and/or limit …

Species distribution modeling (SDM) links ecological theory of species-environment
relationships with statistical learning methods and geospatial data to understand and predict …