Climate reconstruction analysis using coexistence likelihood estimation (CRACLE): A method for the estimation of climate using vegetation

PREMISE OF THE STUDY: Plant distributions have long been understood to be correlated with the environmental conditions to which species are adapted. Climate is one of the major components driving species distributions. Therefore, it is expected that the plants coexisting in a community are reflectiv...

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Bibliographic Details
Published in:American journal of botany 2015-08, Vol.102 (8), p.1277-1289
Main Authors: Harbert, Robert S., Nixon, Kevin C.
Format: Article
Language:English
Subjects:
Climate
climate change
climate niches
ecological filtering
Estimating techniques
Flowers & plants
GBIF
Likelihood Functions
Meteorology - methods
Models, Biological
paleoclimate
plant community
Plant Dispersal
Precipitation
species coexistence
Vegetation
WorldClim
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Summary:PREMISE OF THE STUDY: Plant distributions have long been understood to be correlated with the environmental conditions to which species are adapted. Climate is one of the major components driving species distributions. Therefore, it is expected that the plants coexisting in a community are reflective of the local environment, particularly climate. METHODS: Presented here is a method for the estimation of climate from local plant species coexistence data. The method, Climate Reconstruction Analysis using Coexistence Likelihood Estimation (CRACLE), is a likelihood-based method that employs specimen collection data at a global scale for the inference of species climate tolerance. CRACLE calculates the maximum joint likelihood of coexistence given individual species climate tolerance characterization to estimate the expected climate. KEY RESULTS: Plant distribution data for more than 4000 species were used to show that this method accurately infers expected climate profiles for 165 sites with diverse climatic conditions. Estimates differ from the WorldClim global climate model by less than 1.5°C on average for mean annual temperature and less than ~250 mm for mean annual precipitation. This is a significant improvement upon other plant-based climate-proxy methods. CONCLUSIONS: CRACLE validates long hypothesized interactions between climate and local associations of plant species. Furthermore, CRACLE successfully estimates climate that is consistent with the widely used WorldClim model and therefore may be applied to the quantitative estimation of paleoclimate in future studies.
ISSN:0002-9122
1537-2197
DOI:10.3732/ajb.1400500