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Data · dataset · 2024

A dataset of carbon and water fluxes observed in Xishuangbanna tropical seasonal rain forest from 2011 to 2015

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The proposal for China's dual-carbon target is based on the foundation of addressing climate change.

Description

It is imperative to enhance carbon sinks and reduce carbon sources to implement climate governance. The terrestrial ecosystem is an important atmospheric carbon sink, while the tropical seasonal rain forest, as a component of the terrestrial ecosystem in China characterized by rich biomass, and strong productivity, plays an essential role in carbon sequestration.

As one of the basic observation and research stations of China Flux Research Network (ChinaFLUX), the Xishuangbanna Tropical Seasonal Rainforest Ecological Station built in 2002 has accumulated 20 years of carbon and water flux observation data. Based on the ChinaFLUX data processing system, this dataset processes and collates the tropical seasonal rain forest flux and conventional meteorological data of Xishuangbanna from January 2011 to December 2015.

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The result is a collection of data products at half-hourly, daily, monthly, and yearly intervals. This dataset can be applied to research fields such as the analysis of the carbon cycle response mechanism of ecosystems and the assessment of carbon sequestration benefits under climate change, and it can also serve as a valuable reference for the optimization of ecosystem model parameters and the verification of results.

Through multi-platform architecture, multi-scale integration, and multi-method coupling, the dataset is expected to further provide basic support for analyzing the mechanisms of regional and even global carbon-water-heat cycles in ecosystems, spatiotemporal dynamics and predicting future carbon sink potential, thus providing the scientific basis for achieving China's carbon neutrality goal.

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Provenance · 1 source records, 12 field assertions
SourceKeyLast seenRaw
ScienceDB10.57760/sciencedb.o00119.0007911 d agoJSON v1
FieldAssertionExtractorEvidence
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