Weather, not climate, defines distributions of vagile bird species

Reside, April E., VanDerWal, Jeremy J., Kutt, Alex S. and Perkins, Genevieve C. (2010) Weather, not climate, defines distributions of vagile bird species. PLoS ONE, 5 10: . doi:10.1371/journal.pone.0013569

Author Reside, April E.
VanDerWal, Jeremy J.
Kutt, Alex S.
Perkins, Genevieve C.
Title Weather, not climate, defines distributions of vagile bird species
Journal name PLoS ONE   Check publisher's open access policy
ISSN 1932-6203
Publication date 2010-10-22
Year available 2010
Sub-type Article (original research)
DOI 10.1371/journal.pone.0013569
Open Access Status DOI
Volume 5
Issue 10
Total pages 9
Place of publication San Francisco, CA, United States
Publisher Public Library of Science
Language eng
Formatted abstract
Background: Accurate predictions of species distributions are essential for climate change impact assessments. However the standard practice of using long-term climate averages to train species distribution models might mute important temporal patterns of species distribution. The benefit of using temporally explicit weather and distribution data has not been assessed. We hypothesized that short-term weather associated with the time a species was recorded should be superior to long-term climate measures for predicting distributions of mobile species.

Methodology: We tested our hypothesis by generating distribution models for 157 bird species found in Australian tropical savannas (ATS) using modelling algorithm Maxent. The variable weather of the ATS supports a bird assemblage with variable movement patterns and a high incidence of nomadism. We developed "weather" models by relating climatic variables (mean temperature, rainfall, rainfall seasonality and temperature seasonality) from the three month, six month and one year period preceding each bird record over a 58 year period (1950-2008). These weather models were compared against models built using long-term (30 year) averages of the same climatic variables.

Conclusions: Weather models consistently achieved higher model scores than climate models, particularly for wide-ranging, nomadic and desert species. Climate models predicted larger range areas for species, whereas weather models quantified fluctuations in habitat suitability across months, seasons and years. Models based on long-term climate averages over-estimate availability of suitable habitat and species' climatic tolerances, masking species potential vulnerability to climate change. Our results demonstrate that dynamic approaches to distribution modelling, such as incorporating organismappropriate temporal scales, improves understanding of species distributions.
Keyword Multidisciplinary Sciences
Science & Technology - Other Topics
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Non-UQ

Document type: Journal Article
Sub-type: Article (original research)
Collection: School of Agriculture and Food Sciences
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Citation counts: TR Web of Science Citation Count  Cited 58 times in Thomson Reuters Web of Science Article | Citations
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