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Functional traits predict relationship between plant abundance dynamic and long-term climate warming.
Proc Natl Acad Sci U S A. 2013 Nov 05; 110(45):18180-4.PN

Abstract

Predicting climate change impact on ecosystem structure and services is one of the most important challenges in ecology. Until now, plant species response to climate change has been described at the level of fixed plant functional types, an approach limited by its inflexibility as there is much interspecific functional variation within plant functional types. Considering a plant species as a set of functional traits greatly increases our possibilities for analysis of ecosystem functioning and carbon and nutrient fluxes associated therewith. Moreover, recently assembled large-scale databases hold comprehensive per-species data on plant functional traits, allowing a detailed functional description of many plant communities on Earth. Here, we show that plant functional traits can be used as predictors of vegetation response to climate warming, accounting in our test ecosystem (the species-rich alpine belt of Caucasus mountains, Russia) for 59% of variability in the per-species abundance relation to temperature. In this mountain belt, traits that promote conservative leaf water economy (higher leaf mass per area, thicker leaves) and large investments in belowground reserves to support next year's shoot buds (root carbon content) were the best predictors of the species increase in abundance along with temperature increase. This finding demonstrates that plant functional traits constitute a highly useful concept for forecasting changes in plant communities, and their associated ecosystem services, in response to climate change.

Authors+Show Affiliations

Systems Ecology Department, Vrije Universiteit Amsterdam, 1081 HV, Amsterdam, The Netherlands.No affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info available

Pub Type(s)

Journal Article
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

24145400

Citation

Soudzilovskaia, Nadejda A., et al. "Functional Traits Predict Relationship Between Plant Abundance Dynamic and Long-term Climate Warming." Proceedings of the National Academy of Sciences of the United States of America, vol. 110, no. 45, 2013, pp. 18180-4.
Soudzilovskaia NA, Elumeeva TG, Onipchenko VG, et al. Functional traits predict relationship between plant abundance dynamic and long-term climate warming. Proc Natl Acad Sci USA. 2013;110(45):18180-4.
Soudzilovskaia, N. A., Elumeeva, T. G., Onipchenko, V. G., Shidakov, I. I., Salpagarova, F. S., Khubiev, A. B., Tekeev, D. K., & Cornelissen, J. H. (2013). Functional traits predict relationship between plant abundance dynamic and long-term climate warming. Proceedings of the National Academy of Sciences of the United States of America, 110(45), 18180-4. https://doi.org/10.1073/pnas.1310700110
Soudzilovskaia NA, et al. Functional Traits Predict Relationship Between Plant Abundance Dynamic and Long-term Climate Warming. Proc Natl Acad Sci USA. 2013 Nov 5;110(45):18180-4. PubMed PMID: 24145400.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Functional traits predict relationship between plant abundance dynamic and long-term climate warming. AU - Soudzilovskaia,Nadejda A, AU - Elumeeva,Tatiana G, AU - Onipchenko,Vladimir G, AU - Shidakov,Islam I, AU - Salpagarova,Fatima S, AU - Khubiev,Anzor B, AU - Tekeev,Dzhamal K, AU - Cornelissen,Johannes H C, Y1 - 2013/10/21/ PY - 2013/10/23/entrez PY - 2013/10/23/pubmed PY - 2014/1/1/medline KW - alpine plant community KW - plant traits KW - root traits KW - seed mass KW - specific leaf area SP - 18180 EP - 4 JF - Proceedings of the National Academy of Sciences of the United States of America JO - Proc. Natl. Acad. Sci. U.S.A. VL - 110 IS - 45 N2 - Predicting climate change impact on ecosystem structure and services is one of the most important challenges in ecology. Until now, plant species response to climate change has been described at the level of fixed plant functional types, an approach limited by its inflexibility as there is much interspecific functional variation within plant functional types. Considering a plant species as a set of functional traits greatly increases our possibilities for analysis of ecosystem functioning and carbon and nutrient fluxes associated therewith. Moreover, recently assembled large-scale databases hold comprehensive per-species data on plant functional traits, allowing a detailed functional description of many plant communities on Earth. Here, we show that plant functional traits can be used as predictors of vegetation response to climate warming, accounting in our test ecosystem (the species-rich alpine belt of Caucasus mountains, Russia) for 59% of variability in the per-species abundance relation to temperature. In this mountain belt, traits that promote conservative leaf water economy (higher leaf mass per area, thicker leaves) and large investments in belowground reserves to support next year's shoot buds (root carbon content) were the best predictors of the species increase in abundance along with temperature increase. This finding demonstrates that plant functional traits constitute a highly useful concept for forecasting changes in plant communities, and their associated ecosystem services, in response to climate change. SN - 1091-6490 UR - https://www.unboundmedicine.com/medline/citation/24145400/Functional_traits_predict_relationship_between_plant_abundance_dynamic_and_long_term_climate_warming_ L2 - http://www.pnas.org/cgi/pmidlookup?view=long&pmid=24145400 DB - PRIME DP - Unbound Medicine ER -