ABSTRACT
This chapter offers a synthesis of concepts relevant to the large-scale deployment of correlative niche models, marrying many useful concepts from ecology and machine learning in the development and application of these models. It highlights several of the focal challenges that arise when using correlative niches models and relate them to the broader context of machine learning. The chapter discusses the domain-specific challenges that must be considered when deploying these models. It provides a review of commonly used correlative niche models, highlighting their theoretical and practical similarities and differences. The chapter also provides a summary of platforms used to deploy these models and the technologies that enable their large-scale use. It outlines the latest trends and future directions to hold particular promise. The chapter elaborates on a variety of factors that introduce challenges into the modeling of species distributions and ecological niches.
