Climate extreme variables generated using monthly time‐series data improve predicted distributions of plant species-Reference-Cited by-同舟云学术

Climate extreme variables generated using monthly time‐series data improve predicted distributions of plant species

Published:2021-02-02 Issue:4 Volume:44 Page:626-639
ISSN:0906-7590
Container-title:Ecography
language:en
Short-container-title:Ecography

Author:

Stewart S. B.¹²^ORCID,Elith J.³,Fedrigo M.²⁴^ORCID,Kasel S.²,Roxburgh S. H.⁵,Bennett L. T.⁶,Chick M.⁷,Fairman T.⁷,Leonard S.⁸,Kohout M.⁹,Cripps J. K.⁹,Durkin L.⁹,Nitschke C. R.²^ORCID

Affiliation:

1. Land and Water Business Unit, CSIRO Sandy Bay TAS Australia

2. School of Ecosystem and Forest Sciences, Univ. of Melbourne Burnley VIC Australia

3. School of Biosciences, Univ. of Melbourne Parkville VIC Australia

4. GeoRubix Solutions Hobart TAS Australia

5. Land and Water Business Unit, CSIRO ACT Australia

6. School of Ecosystem and Forest Sciences, Univ. of Melbourne Creswick VIC Australia

7. Dept of Environment, Land Water and Planning East Melbourne VIC Australia

8. Dept of Primary Industries, Parks, Water and Environment Hobart TAS Australia

9. Arthur Rylah Inst. for Environmental Research, Dept of Environment, Land Water and Planning Heidelberg VIC Australia

Publisher

Wiley

Subject

Ecology, Evolution, Behavior and Systematics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/ecog.05253

Reference85 articles.

1. Temperature sensitivity of drought-induced tree mortality portends increased regional die-off under global-change-type drought

2. Drought-induced shift of a forest-woodland ecotone: Rapid landscape response to climate variation

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4. Structural diversity underpins carbon storage in Australian temperate forests

5. Tackling extremes: challenges for ecological and evolutionary research on extreme climatic events

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