Objective
Feedbacks between plants and soil under environmental change are likely to have a significant impact on ecosystem carbon cycling. Recent work has shown that increased atmospheric carbon dioxide concentrations have enhanced tree growth in forests. However these increases in growth can also cause ‘priming effects’ whereby microbial degradation of soil organic matter is stimulated by fresh carbon inputs, such as plant litter, releasing additional carbon from the soil. Given that forest soils represent the largest terrestrial carbon pool, priming effects could cause a major release of carbon dioxide to the atmosphere. Despite their potential importance in ecosystem carbon dynamics under environmental change, the processes and mechanisms underlying priming effects are still poorly understood. This is in part due to the enormous disparities in the experimental scales and methods required to study microbial processes vs. ecosystem carbon dynamics and the difficulties in extrapolating the results of laboratory studies to the ecosystem level. This project will significantly advance our understanding of the role of priming effects in forest carbon dynamics in different forest types and reconcile the experimental problems of scale using multidisciplinary nested studies across multiple scales. The nested design will explicitly test the validity of extrapolations made at one scale to predict effects at another. The ultimate aim is to allow the extrapolation of results from small-scale studies of priming to the ecosystem level for a wide range of forests. The results will establish this fundamentally new approach as a widely applicable method in the study of plant-soil feedbacks. This research will provide the first comprehensive comparative dataset on priming effects across forests worldwide and form the solid basis for their inclusion in model predictions of forest carbon cycling under future global change.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- agricultural sciencesagriculture, forestry, and fisheriesagriculturehorticulturearboriculture
- natural sciencesbiological sciencesecologyecosystems
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Call for proposal
ERC-2012-StG_20111012
See other projects for this call
Funding Scheme
ERC-SG - ERC Starting GrantHost institution
LA1 4YW Lancaster
United Kingdom