Identifying predictable foraging habitats for a wide‐ranging marine predator using ensemble ecological niche models

By K. Scales, Peter I. Miller, S. Ingram, E. Hazen, S. Bograd, R. Phillips. Diversity and Distributions: A journal of biological invasions and biodiversity, 2015

97 citations recorded by the source corpus.

Ecological niche modelling can provide valuable insight into species' environmental preferences and aid the identification of key habitats for populations of conservation concern. Here, we integrate biologging, satellite remote‐sensing and ensemble ecological niche models (EENMs) to identify predictable foraging habitats for a globally important population of the grey‐headed albatross (GHA) Thalassarche chrysostoma.

Subfields: Ecological Modeling, Ecology, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/34f119d524439bf7fdcf5d155d11aecf566c1926

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In Ecological Modeling

In Ecology

In Nature and Landscape Conservation

Citations in the corpus

Dynamic ensemble models to predict distributions and anthropogenic risk exposure for highly mobile species (2019, methodology): “Predictions generated from multi‐model ensembles can also be more accurate than those of single models (Marmion, Parviainen, Luoto, Heikkinen, & Thuiller, 2009; Oppel et al., 2012; Scales et al., 2015).”
A Systematic Review of Marine-Based Species Distribution Models (SDMs) with Recommendations for Best Practice (2017, background): “For instance, studies conducted recently (Jones et al., 2012; Jones and Cheung, 2015; Anderson et al., 2016; Scales et al., 2016) have demonstrated that assembling multiple SDMs provides a framework to incorporate relevant model features such as uncertainty and agreement levels between model…”