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Net primary production of major plant functional types in China: Vegetation classification and ecosystem simulation
- Pan, Shufen, Tian, Hanqin, Lu, Chaoqun, Dangal, Shree R.S., Liu, Mingliang
- Acta ecologica Sinica 2015 v.35 no.2 pp. 28-36
- carbon dioxide, case studies, climate, climate models, cropland, cropping systems, crops, data collection, environmental factors, highlands, hydrology, irrigation, nitrogen, nitrogen fertilizers, paddies, primary productivity, surveys, terrestrial ecosystems, vegetation types, China
- The characteristics and distribution of vegetation are essential information for understanding the structure and functioning of terrestrial ecosystems across a large region. In this study, we developed the contemporary and potential vegetation maps of China with a spatial resolution of 1 km × 1 km. The vegetation classification scheme includes 17 types of vegetation and 3 non-vegetated land cover types. For cropland, we further provide spatial information on three major cropping systems across China, i.e., single, double and triple cropping system. In addition, we further evaluate the accuracy of this classification against field survey. As a case study, we used this vegetation data set combined with other environmental factors (climate, atmospheric CO2 and nitrogen deposition) to drive the Dynamic Land Ecosystem Model (DLEM) for estimating terrestrial net primary production at both plant functional type and national levels. DLEM simulations indicate that net primary productivity (NPP) in China's terrestrial ecosystem has substantially increased by 51%, from 2.50 Pg C y−1 in the 1900s to 3.79 Pg C y−1 during the first decade of the 21st century. Among major plant functional types across China, cropland shows the largest NPP increase by nearly 3–4 fold during 1901–2010 primarily due to cropland expansion as well as increased nitrogen fertilizer use and irrigation. The NPP increase is estimated to be 480 and 692 gC m−2 y−1 for upland crops and rice fields, respectively. This vegetation distribution data set was originally developed for driving the Dynamic Land Ecosystem model (DLEM), but it can be used for other purposes such as driving hydrological and climate models.