Document Detail


How close are we to a predictive science of the biosphere?
MedLine Citation:
PMID:  16815439     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
In just 20 years, the field of biosphere-atmosphere interactions has gone from a nascent discipline to a central area of modern climate change research. The development of terrestrial biosphere models that predict the responses of ecosystems to climate and increasing CO2 levels has highlighted several mechanisms by which changes in ecosystem composition and function might alter regional and global climate. However, results from empirical studies suggest that ecosystem responses can differ markedly from the predictions of terrestrial biosphere models. As I discuss here, the challenge now is to connect terrestrial biosphere models to empirical ecosystem measurements. Only by systematically evaluating the predictions of terrestrial biosphere models against suites of ecosystem observations and experiments measurements will a true predictive science of the biosphere be achieved.
Authors:
Paul R Moorcroft
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Publication Detail:
Type:  Journal Article; Research Support, U.S. Gov't, Non-P.H.S.; Review     Date:  2006-05-12
Journal Detail:
Title:  Trends in ecology & evolution     Volume:  21     ISSN:  0169-5347     ISO Abbreviation:  Trends Ecol. Evol. (Amst.)     Publication Date:  2006 Jul 
Date Detail:
Created Date:  2006-07-03     Completed Date:  2006-12-07     Revised Date:  2011-05-03    
Medline Journal Info:
Nlm Unique ID:  8805125     Medline TA:  Trends Ecol Evol     Country:  England    
Other Details:
Languages:  eng     Pagination:  400-7     Citation Subset:  IM    
Affiliation:
Department of Organismic and Evolutionary Biology, Harvard University, 22 Divinity Avenue, Cambridge, MA 02138, USA. paul.moorcroft@harvard.edu
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MeSH Terms
Descriptor/Qualifier:
Acclimatization / physiology
Atmosphere / analysis*
Biodiversity
Climate*
Ecosystem*
Forecasting*
Geology / methods
Models, Theoretical
Plant Physiological Phenomena

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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