Evaluation of net primary productivity and its spatial and temporal patterns in southern China’s grasslands

2013 ◽  
Vol 35 (3) ◽  
pp. 331 ◽  
Author(s):  
Z. G. Sun ◽  
X. H. Long ◽  
C. M. Sun ◽  
W. Zhou ◽  
W. M. Ju ◽  
...  
Keyword(s):  
Primary Productivity ◽  
Production Efficiency ◽  
Net Primary Productivity ◽  
Southern China ◽  
Mean Annual Precipitation ◽  
Mean Annual Temperature ◽  
Spatial And Temporal Patterns ◽  
Important Indicator ◽  
Grassland Ecosystems ◽  
The Mean

The net primary productivity (NPP) of grassland ecosystems is an important indicator of the capacity for carbon (C) absorption. The Global Production Efficiency Model was adopted to simulate NPP in southern China’s grasslands and to analyse the temporal and spatial dynamics from 1981 to 2000. There was a high correlation between measured and simulated values (R2 = 0.84). Based on the data from 1981 to 2000, the mean annual NPP was 1082 g C m–2 year–1, and the highest value (1798 g C m–2 year–1) was in Hainan province, and the lowest value (500 g C m–2 year–1) was in south-western Tibet. The highest mean NPP values were in the permanent wetlands (1193 g C m–2 year–1) and savannas (1137 g C m–2 year–1); woody savannas had an intermediate value (1087 g C m–2 year–1), and the lowest NPP occurred in typical grasslands and open shrubs, the mean values were 709 and 689 g C m–2 year–1, respectively. Temporally, the total NPP in southern China’s grasslands slightly increased in the 20-year period, especially from 1981 to 1990. The mean annual total of NPP in the 20 years was 0.758 Pg C. Inter-annual variation in total NPP was driven mainly by mean annual temperature rather than mean annual precipitation. The results suggest that grassland ecosystems in southern China have a large C sink.

scholarly journals Application of a new model using productivity coupled with hydrothermal factors (PCH) for evaluating net primary productivity of grassland in southern China

Solid Earth ◽  
2017 ◽  
Vol 8 (2) ◽  
pp. 545-552
Author(s):  
Zheng-Guo Sun ◽  
Jie Liu ◽  
Hai-Yang Tang
Keyword(s):  
Primary Productivity ◽  
Net Primary Productivity ◽  
Southern China ◽  
Hot Spot ◽  
Terrestrial Ecosystems ◽  
Mean Annual Precipitation ◽  
Mean Annual Temperature ◽  
New Model ◽  
Significant Relationships ◽  
Grassland Ecosystems

Abstract. Grassland ecosystems play important roles in the global carbon cycle. The net primary productivity (NPP) of grassland ecosystems has become the hot spot of terrestrial ecosystems. To simulate grassland NPP in southern China, a new model using productivity coupled with hydrothermal factors (PCH) was built and validated based on data recorded from 2003 to 2014. The results show a logarithmic correlation between grassland NPP and mean annual temperature and a linear positive correlation between grassland NPP and mean annual precipitation in southern China, both highly significant relationships. There was a highly significant correlation between simulated and measured NPP (R2 = 0. 8027). Both RMSE and relative root mean square error (RRMSE) were relatively low, showing that the simulation results of the model were reliable. The NPP values in the study area had a decreasing trend from east to west and south to north. Mean NPP was 471.62 g C m−2 from 2003 to 2014. Additionally, the mean annual NPP of southern grassland presented a rising trend, increasing 3.49 g C m−2 yr−1 during the past 12 years. These results document performance and use of a new method to estimate the grassland NPP in southern China.

scholarly journals Application of a new productivity coupling hydrothermal factors (PCH) model for evaluating net primary productivity of grassland in Southern China

2016 ◽  
Author(s):  
Zheng-Guo Sun ◽  
Jie Liu ◽  
Hai-Yang Tang
Keyword(s):  
Primary Productivity ◽  
Net Primary Productivity ◽  
Southern China ◽  
Hot Spot ◽  
Terrestrial Ecosystems ◽  
Mean Annual Precipitation ◽  
Mean Annual Temperature ◽  
Significant Relationships ◽  
Grassland Ecosystems ◽  
Global Carbon

Abstract. Grassland ecosystems play important roles in the global carbon cycle. The net primary productivity (NPP) of grassland ecosystems has become the hot spot of terrestrial ecosystems. To simulate grassland NPP in Southern China, a new productivity coupling hydrothermal factors (PCH) model was built and validated based on data recorded from 2003 to 2014. The results show a logarithmic correlation between grassland NPP and mean annual temperature and a linear positive correlation between grassland NPP and mean annual precipitation in Southern China, both highly significant relationships. There was a highly significant correlation between simulated and measured NPP (R2 = 0.8027). Both RMSE and RRMSE were relatively low, showing that the simulation results of the model were reliable. The NPP values in the study area had a decreasing trend from east to west and south to north. Mean NPP was 471.62 g C m−2 from 2003 to 2014. Additionally, the mean annual NPP of Southern grassland presented a rising trend increasing 3.49 g C m−2 yr−2 during the past 12 years. These results document performance and use of a new method to estimate the grassland NPP in Southern China.

scholarly journals Discrepancies between Global Forest Net Primary Productivity Estimates Derived from MODIS and Forest Inventory Data and Underlying Factors

2021 ◽  
Vol 13 (8) ◽  
pp. 1441
Author(s):  
Jin Han Park ◽  
Jianbang Gan ◽  
Chan Park
Keyword(s):  
Low Income ◽  
Primary Productivity ◽  
Carbon Stock ◽  
Forest Cover ◽  
Net Primary Productivity ◽  
Estimation Methods ◽  
Future Research ◽  
Important Indicator ◽  
Sequestration Potential ◽  
Carbon Losses

The net primary productivity (NPP) of a forest is an important indicator of its potential for the provision of ecosystem services such as timber, carbon, and biodiversity. However, accurately and consistently quantifying global forest NPP remains a challenge in practice. We converted carbon stock changes using the Global Forest Resources Assessment (FRA) data and carbon losses associated with disturbances and timber removals into an NPP equivalent measurement (FRA NPP*) and compared it with the NPP derived from the MODIS satellite data (MOD17 NPP) for the world’s forests. We found statistically significant differences between the two NPP estimates, with the FRA NPP* being lower than the MOD17 NPP; the differences were correlated with forest cover, normalized difference vegetation index (NDVI), and GDP per capita in countries, and may also stem from the NPP estimation methods and scopes. While the former explicitly accounts for carbon losses associated with timber removals and disturbances, the latter better reflects the principles of photosynthesis. The discrepancies between the two NPP estimates increase in countries with a low income or low forest cover, calling for enhancing their forest resource assessment capacity. By identifying the discrepancies and underlying factors, we also provide new insights into the relationships between the MOD17 NPP and global forest carbon stock estimates, motivating and guiding future research to improve the robustness of quantifying global forest NPP and carbon sequestration potential.

scholarly journals Simulating Spatiotemporal Dynamics of Sichuan Grassland Net Primary Productivity Using the CASA Model and In Situ Observations

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Chuanjiang Tang ◽  
Xinyu Fu ◽  
Dong Jiang ◽  
Jingying Fu ◽  
Xinyue Zhang ◽  
...  
Keyword(s):  
Primary Productivity ◽  
Net Primary Productivity ◽  
Alpine Meadow ◽  
Growth Period ◽  
Temporal Variations ◽  
Light Use Efficiency ◽  
Important Indicator ◽  
Casa Model ◽  
Use Efficiency

Net primary productivity (NPP) is an important indicator for grassland resource management and sustainable development. In this paper, the NPP of Sichuan grasslands was estimated by the Carnegie-Ames-Stanford Approach (CASA) model. The results were validated with in situ data. The overall precision reached 70%; alpine meadow had the highest precision at greater than 75%, among the three types of grasslands validated. The spatial and temporal variations of Sichuan grasslands were analyzed. The absorbed photosynthetic active radiation (APAR), light use efficiency (ε), and NPP of Sichuan grasslands peaked in August, which was a vigorous growth period during 2011. High values of APAR existed in the southwest regions in altitudes from 2000 m to 4000 m. Light use efficiency (ε) varied in the different types of grasslands. The Sichuan grassland NPP was mainly distributed in the region of 3000–5000 m altitude. The NPP of alpine meadow accounted for 50% of the total NPP of Sichuan grasslands.

scholarly journals Net Primary Productivity of Pinus massoniana Dependence on Climate, Soil and Forest Characteristics

Forests ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 404 ◽  
Author(s):  
Xin Huang ◽  
Chunbo Huang ◽  
Mingjun Teng ◽  
Zhixiang Zhou ◽  
Pengcheng Wang
Keyword(s):  
Geographical Distribution ◽  
Soil Nutrients ◽  
Primary Productivity ◽  
Net Primary Productivity ◽  
Southern China ◽  
Regional Scale ◽  
Pinus Massoniana ◽  
Forest Productivity ◽  
Tree Component ◽  
Total Tree

Understanding the spatial variation of forest productivity and its driving factors on a large regional scale can help reveal the response mechanism of tree growth to climate change, and is an important prerequisite for efficient forest management and studying regional and global carbon cycles. Pinus massoniana Lamb. is a major planted tree species in southern China, playing an important role in the development of forestry due to its high economic and ecological benefits. Here, we establish a biomass database for P. massoniana, including stems, branches, leaves, roots, aboveground organs and total tree, by collecting the published literature, to increase our understanding of net primary productivity (NPP) geographical trends for each tree component and their influencing factors across the entire geographical distribution of the species in southern China. P. massoniana NPP ranges from 1.04 to 13.13 Mg·ha−1·year−1, with a mean value of 5.65 Mg·ha−1·year−1. The NPP of both tree components (i.e., stem, branch, leaf, root, aboveground organs, and total tree) show no clear relationships with longitude and elevation, but an inverse relationship with latitude (p < 0.01). Linear mixed-effects models (LMMs) are employed to analyze the effect of environmental factors and stand characteristics on P. massoniana NPP. LMM results reveal that the NPP of different tree components have different sensitivities to environmental and stand variables. Appropriate temperature and soil nutrients (particularly soil available phosphorus) are beneficial to biomass accumulation of this species. It is worth noting that the high temperature in July and August (HTWM) is a significant climate stressor across the species geographical distribution and is not restricted to marginal populations in the low latitude area. Temperature was a key environmental factor behind the inverse latitudinal trends of P. massoniana NPP, because it showed a higher sensitivity than other factors. In the context of climate warming and nitrogen (N) deposition, the inhibition effect caused by high temperatures and the lack or imbalance of soil nutrients, particularly soil phosphorus, should be paid more attention in the future. These findings advance our understanding about the factors influencing the productivity of each P. massoniana tree component across the full geographical distribution of the species, and are therefore valuable for forecasting climate-induced variation in forest productivity.

scholarly journals Net Primary Productivity Loss under different drought levels in different grassland ecosystems

2020 ◽  
Vol 274 ◽  
pp. 111144
Author(s):  
Tianjie Lei ◽  
Jie Feng ◽  
Juan Lv ◽  
Jiabao Wang ◽  
Hongquan Song ◽  
...  
Keyword(s):  
Primary Productivity ◽  
Net Primary Productivity ◽  
Productivity Loss ◽  
Grassland Ecosystems

scholarly journals Dust Storms in Northern China: Long-Term Spatiotemporal Characteristics and Climate Controls

2017 ◽  
Vol 30 (17) ◽  
pp. 6683-6700 ◽  
Author(s):  
Qingyu Guan ◽  
Xiazhong Sun ◽  
Jing Yang ◽  
Baotian Pan ◽  
Shilei Zhao ◽  
...  
Keyword(s):  
Wind Speed ◽  
Dust Storm ◽  
Northern China ◽  
Dust Storms ◽  
Effect Of Temperature ◽  
Mean Annual Precipitation ◽  
Mean Annual Temperature ◽  
Spatiotemporal Characteristics ◽  
Dust Generation ◽  
The Mean

Airborne dust derived from desertification in northern China can be transported to East Asia and other regions, impairing human health and affecting the global climate. This study of northern China dust provides an understanding of the mechanism of dust generation and transportation. The authors used dust storm and climatological data from 129 sites and normalized difference vegetation index (NDVI) datasets in northern China to analyze spatiotemporal characteristics and determine the main factors controlling dust storms occurring during 1960–2007. Dust storm–prone areas are consistent with the spatial distribution of northern China deserts where the average wind speed (AWS) is more than 2 m s−1, the mean annual temperature (MAT) ranges from 5° to 10°C, and the mean annual precipitation (MAP) is less than 450 mm. Dust storms commonly occur on spring afternoons in a 3- to 6-h pattern. The three predominant factors that can affect DSF are the maximum wind speed, AWS, and MAT. During 1960–2007, dust storm frequency (DSF) in most regions of northern China fluctuated but had a decreasing trend; this was mainly caused by a gradual reduction in wind speed. The effect of temperature on DSF is complex, as positive and negative correlations exist simultaneously. Temperatures can affect source material (dust, sand, etc.), cyclone activity, and vegetation growth status, which influence the generation of dust storms. NDVI and precipitation are negatively correlated with DSF, but the effect is weak. Vegetation can protect the topsoil environment and prevent dust storm creation but is affected by the primary decisive influence of precipitation.

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