The popularity of machine learning (ML), deep learning (DL) and artificial intelligence (AI)
has risen sharply in recent years. Despite this spike in popularity, the inner workings of ML …

A lot of hype has recently been generated around deep learning, a novel group of artificial
intelligence approaches able to break accuracy records in pattern recognition. Over the …

Species distribution modeling (SDM) is widely used in ecology and conservation. Currently,
the most available data for SDM are species presence‐only records (available through …

Abstract Protected Areas (PAs) are the cornerstone of biodiversity conservation. Here, we
collated distributional data for> 14,000 (~ 70% of) species of amphibians and reptiles …

This book introduces the key stages of niche-based habitat suitability model building,
evaluation and prediction required for understanding and predicting future patterns of …

This article reviews the current research and applications of various digital soil map**
(DSM) techniques used to map Soil Organic Carbon (SOC) concentration and stocks …

Presence‐only data present challenges for selecting thresholds to transform species
distribution modeling results into binary outputs. In this article, we compare two recently …

Soil organic carbon (SOC) is a key indicator of ecosystem health, with a great potential to
affect climate change. This study aimed to develop, evaluate, and compare the performance …

Hutchinson's n‐dimensional hypervolume concept underlies many applications in
contemporary ecology and evolutionary biology. Estimating hypervolumes from sampled …

Provisioning a sufficient stable source of food requires sound knowledge about current and
upcoming threats to agricultural production. To that end machine learning approaches were …