Accounting for spatial dependence in random forests improves ecological understanding and enhances prediction

Matthew J. Heaton, Michael Dumelle, Kelvyn K. Bladen, Ryan A. Hill, Jake S. Rhodes

Open source

DOI: 10.1002/ecy.70567
Published: 2026-11
Container: Ecology
Publisher: Wiley
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1002/ecy.70567,
  title = {Accounting for spatial dependence in random forests improves ecological understanding and enhances prediction},
  author = {Matthew J. Heaton and Michael Dumelle and Kelvyn K. Bladen and Ryan A. Hill and Jake S. Rhodes},
  year = {2026},
  journal = {Ecology},
  doi = {10.1002/ecy.70567},
  url = {https://doi.org/10.1002/ecy.70567}
}

RIS

TY  - JOUR
TI  - Accounting for spatial dependence in random forests improves ecological understanding and enhances prediction
AU  - Matthew J. Heaton
AU  - Michael Dumelle
AU  - Kelvyn K. Bladen
AU  - Ryan A. Hill
AU  - Jake S. Rhodes
PY  - 2026
JO  - Ecology
DO  - 10.1002/ecy.70567
UR  - https://doi.org/10.1002/ecy.70567
ER  -

APA

Heaton, M. J., Dumelle, M., Bladen, K. K., Hill, R. A., & Rhodes, J. S. (2026). Accounting for spatial dependence in random forests improves ecological understanding and enhances prediction. Ecology. https://doi.org/10.1002/ecy.70567

Source records

crossref · retrieved 2026-11-07T03:47:39.857Z