
You have already added 0 works in your ORCID record related to the merged Research product.
You have already added 0 works in your ORCID record related to the merged Research product.
<script type="text/javascript">
<!--
document.write('<div id="oa_widget"></div>');
document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=undefined&type=result"></script>');
-->
</script>
Reference carbon cycle dataset for typical Chinese forests via colocated observations and data assimilation

pmid: 33531507
pmc: PMC7854661
AbstractChinese forests cover most of the representative forest types in the Northern Hemisphere and function as a large carbon (C) sink in the global C cycle. The availability of long-term C dynamics observations is key to evaluating and understanding C sequestration of these forests. The Chinese Ecosystem Research Network has conducted normalized and systematic monitoring of the soil-biology-atmosphere-water cycle in Chinese forests since 2000. For the first time, a reference dataset of the decadal C cycle dynamics was produced for 10 typical Chinese forests after strict quality control, including biomass, leaf area index, litterfall, soil organic C, and the corresponding meteorological data. Based on these basic but time-discrete C-cycle elements, an assimilated dataset of key C cycle parameters and time-continuous C sequestration functions was generated via model-data fusion, including C allocation, turnover, and soil, vegetation, and ecosystem C storage. These reference data could be used as a benchmark for model development, evaluation and C cycle research under global climate change for typical forests in the Northern Hemisphere.
- Institute of Applied Ecology China (People's Republic of)
- Chinese Academy of Sciences China (People's Republic of)
- University of Edinburgh United Kingdom
- Institute of Botany China (People's Republic of)
- Chinese Academy of Sciences China (People's Republic of)
Statistics and Probability, Data Descriptor, China, Science, Library and Information Sciences, Forests, Education, Carbon Cycle, Soil, Biomass, Atmosphere, Q, Carbon, Computer Science Applications, Statistics, Probability and Uncertainty, Information Systems, Environmental Monitoring
Statistics and Probability, Data Descriptor, China, Science, Library and Information Sciences, Forests, Education, Carbon Cycle, Soil, Biomass, Atmosphere, Q, Carbon, Computer Science Applications, Statistics, Probability and Uncertainty, Information Systems, Environmental Monitoring
