Global Change Biology

Cover image for Vol. 21 Issue 1

Edited by: Steve Long

Impact Factor: 8.224

ISI Journal Citation Reports © Ranking: 2013: 1/42 (Biodiversity Conservation); 4/216 (Environmental Sciences); 6/141 (Ecology)

Online ISSN: 1365-2486

Associated Title(s): GCB Bioenergy

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Global Change Biology exists to promote understanding of the interface between all aspects of current environmental change that affects a substantial part of the globe and biological systems.

The journal publishes primary research articles, technical advances, research reviews, commentaries and letters.

Global Change Biology defines global change as any consistent trend in the environment - past, present or projected - that affects a substantial part of the globe. Examples include:

GCB Highlight 1Connecting carbon and nitrogen storage in rural wetland soil to groundwater abstraction for urban water supply

Most people worldwide are packed into cities, where they no longer obtain water, food, and other natural resources from their local environment. Cities instead meet their needs by obtaining resources from outlying rural ecosystems, perhaps changing those places. This study investigated how rural wetland ecosystems are affected when water is appropriated to meet the demands of the Tampa Bay metropolis (USA). The study discovered that the pumping of groundwater beneath wetlands resulted in drier wetlands with less storage of organic matter and biologically important nutrients in wetland soil. These findings demonstrate that the impacts of urbanization reach into rural ecosystems.


GCB Highlight 2Predictability of the terrestrial carbon cycle

Terrestrial ecosystems sequester roughly 30% of anthropogenic CO2. However, this estimate is not directly deduced from studies of terrestrial ecosystems themselves, but inferred from atmospheric and oceanic data. This raises a question: to what extent is the terrestrial carbon cycle intrinsically predictable? This paper investigated the fundamental properties of terrestrial carbon cycle and examined its intrinsic predictability. It categorizes the carbon cycle components into five groups of high, medium, low, less known, and unknown predictability. Future empirical research should be focused on those less predictive components. Modeling needs to improve model predictive ability for those highly predictive components.


GCB Highlight 3Multimodel ensembles of wheat growth

Crop models are increasingly used to quantify the impact of global changes on crop performance. All predictions are uncertain to some extent, but how uncertain? The authors compared 27 wheat models, which differed markedly in assumptions about processes affecting growth and development, with measured crop performance. All models had substantial errors, for at least some variables, and no model was best at simulating all variables. The average or median of several model simulations gave more robust and consistent results than any single model. Simulations of crop performance using ensembles can reduce uncertainties and thereby increase the potential applications of ecophysiological models.


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