Quantitative measurements of the interaction between net primary productivity and livestock production in Qinghai Province based on data fusion technique

Dynamics of land use and land cover changes in China

Understanding the net primary productivity (NPP) of grassland is crucial to evaluate the terrestrial carbon cycle. In this study, we investigated the spatial distribution and the area of global grassland across the globe. Then, we used the Carnegie-Ames-Stanford Approach (CASA) model to estimate global grassland NPP and explore the spatio-temporal variations of grassland NPP in response to climate change from 1982 to 2008. Results showed that the largest area of grassland distribution during the study period was in Asia (1737.23 × 104 km2), while the grassland area in Europe was relatively small (202.83 × 104 km2). Temporally, the total NPP increased with fluctuations from 1982 to 2008, with an annual increase rate of 0.03 Pg C/yr. The total NPP experienced a significant increasing trend from 1982 to 1995, while a decreasing trend was observed from 1996 to 2008. Spatially, the grassland NPP in South America and Africa were higher than the other regions, largely as a result of these regions are under warm and wet climatic conditions. The highest mean NPP was recorded for savannas (560.10 g C/(m2·yr)), whereas the lowest was observed in open shrublands with an average NPP of 162.53 g C/(m2·yr). The relationship between grassland NPP and annual mean temperature and annual precipitation (AMT, AP, respectively) varies with changes in AP, which indicates that, grassland NPP is more sensitive to precipitation than temperature.

http://egeoscien.neigae.ac.cn/CN/article/downloadArticleFile.do?attachType=PDF&id=10072

Assessing the Dynamics of Grassland Net Primary Productivity in Response to Climate Change at the Global Scale

Net primary productivity(NPP) is the core of terrestrial carbon cycle research.Estimating NPP is not accurate in high altitude regions owing to lack of meteorological data.Based on the WRF model meteorological data and SPOT-VEGETATION remote sensing images,the grassland NPP of Qinghai Lake basin was estimated using CASA model from 2000 to 2010.The simulated results were validated by observed data and other simulated data,and then the temporal and spatial variations of NPP were analyzed.The analyses show: 1) WRF meteorological data might be applied well to CASA model,perfectly simulating grassland NPP.2) The annual grassland NPP was 2.71×1012 gC·a-1 and the NPP per unit area was 145.71 gC·m-2·a-1 on average,and spatially,NPP showed an increasing from southeast to northwest with elevation increasing,but NPP per unit area reached a maximum at the altitude of 3 200-3 500 m.3) The inter-annual variation of NPP was obvious and an increasing tendency could be seen from 2000 to 2010.Around Qinghai Lake there was a main NPP increasing area.The NPP changed month by month significantly;most of them(57.36%) took place in summer.4) Correlation analysis between NPP and meteorological data,including solar radiation,air temperature and precipitation,shows that the main factor affecting NPP is air temperature.

Estimating the Grassland NPP in Qinghai Lake Basin Based on WRF Model Data and CASA Model

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Estimating the Grassland NPP in Qinghai Lake Basin Based on WRF Model Data and CASA Model