Improving the predictability and interpretability of co‐occurrence modelling through feature‐based joint species distribution ensembles-Reference-Cited by-同舟云学术

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Improving the predictability and interpretability of co‐occurrence modelling through feature‐based joint species distribution ensembles

Published:2022-06-25 Issue:1 Volume:14 Page:146-161
ISSN:2041-210X
Container-title:Methods in Ecology and Evolution
language:en
Short-container-title:Methods Ecol Evol

Author:

Powell‐Romero Francisca¹^ORCID,Fountain‐Jones Nicholas M.²^ORCID,Norberg Anna³^ORCID,Clark Nicholas J.¹^ORCID

Affiliation:

1. School of Veterinary Science The University of Queensland Gatton Qld Australia

2. School of Natural Sciences University of Tasmania Hobart TAS Australia

3. Centre for Biodiversity Dynamics, Department of Biology Norwegian University of Science and Technology Trondheim Norway

Publisher

Wiley

Subject

Ecological Modeling,Ecology, Evolution, Behavior and Systematics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/2041-210X.13915

Reference78 articles.

1. Trees as islands: canopy ant species richness increases with the size of liana‐free trees in a Neotropical forest

2. Predicting the future of species diversity: macroecological theory, climate change, and direct tests of alternative forecasting methods

3. The importance of biotic interactions for modelling species distributions under climate change

4. Ensemble forecasting of species distributions

5. Why does forecast combination work so well?

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