scholarly journals Impacts of land-use change and elevated CO<sub>2</sub> on the interannual variations and seasonal cycles of gross primary productivity in China

2019 ◽  
Author(s):  
Binghao Jia ◽  
Xin Luo ◽  
Ximing Cai ◽  
Atul Jain ◽  
Deborah N. Huntzinger ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Primary Productivity ◽  
Driving Forces ◽  
Southern China ◽  
Co2 Concentration ◽  
Mean Value ◽  
Temporal Changes ◽  
Gross Primary Productivity ◽  
Control Factor

Abstract. Climate change, rising CO2 concentration, and land use and land cover change (LULCC) are primary driving forces for terrestrial gross primary productivity (GPP), but their impacts on the temporal changes in GPP are confounded. In this study, the effects of the three main factors on the interannual variation (IAV) and seasonal cycle amplitude (SCA) of GPP in China were investigated using 12 terrestrial biosphere models from the Multi-scale Synthesis and Terrestrial Model Intercomparison Project. The simulated ensemble mean value of China's GPP, driven by common climate forcing, LULCC, and CO2 data, was found to be 7.4 ± 1.8 Pg C yr−1, which was in close agreement with the independent upscaling GPP estimate (7.1 Pg C yr−1). In general, climate was the dominant control factor of the annual trends, IAV, and seasonality of China's GPP. The overall rising CO2 led to enhanced plant photosynthesis, thus increasing annual mean and IAV of China's total GPP, especially in northeastern and southern China where vegetation is dense. LULCC decreased the IAV of China's total GPP by ~ 7 %, whereas rising CO2 induced an increase of 8 %. Compared to climate change and elevated CO2, LULCC showed less contributions to GPP's temporal variation and its impact acted locally, mainly in southwestern China. Furthermore, this study also examined subregional contributions to the temporal changes in China's total GPP. Southern and southeastern China showed higher contributions to China's annual GPP, whereas southwestern and central parts of China explained larger fractions of the IAV in China's GPP.

scholarly journals Impacts of land use change and elevated CO<sub>2</sub> on the interannual variations and seasonal cycles of gross primary productivity in China

2020 ◽  
Vol 11 (1) ◽  
pp. 235-249 ◽  
Author(s):  
Binghao Jia ◽  
Xin Luo ◽  
Ximing Cai ◽  
Atul Jain ◽  
Deborah N. Huntzinger ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Primary Productivity ◽  
Driving Forces ◽  
Southern China ◽  
Co2 Concentration ◽  
Mean Value ◽  
Temporal Changes ◽  
Gross Primary Productivity ◽  
Control Factor

Abstract. Climate change, rising CO2 concentration, and land use and land cover change (LULCC) are primary driving forces for terrestrial gross primary productivity (GPP), but their impacts on the temporal changes in GPP are uncertain. In this study, the effects of the three main factors on the interannual variation (IAV) and seasonal cycle amplitude (SCA) of GPP in China were investigated using 12 terrestrial biosphere models from the Multi-scale Synthesis and Terrestrial Model Intercomparison Project. The simulated ensemble mean value of China's GPP between 1981 and 2010, driven by common climate forcing, LULCC and CO2 data, was found to be 7.4±1.8 Pg C yr−1. In general, climate was the dominant control factor of the annual trends, IAV and seasonality of China's GPP. The overall rising CO2 led to enhanced plant photosynthesis, thus increasing annual mean and IAV of China's total GPP, especially in northeastern and southern China, where vegetation is dense. LULCC decreased the IAV of China's total GPP by ∼7 %, whereas rising CO2 induced an increase of 8 %. Compared to climate change and elevated CO2, LULCC showed less contributions to GPP's temporal variation, and its impact acted locally, mainly in southwestern China. Furthermore, this study also examined subregional contributions to the temporal changes in China's total GPP. Southern and southeastern China showed higher contributions to China's annual GPP, whereas southwestern and central parts of China explained larger fractions of the IAV in China's GPP.

scholarly journals Modelling the response of net primary productivity of the Zambezi teak forests to climate change along a rainfall gradient in Zambia

2019 ◽  
Vol 16 (19) ◽  
pp. 3853-3867
Author(s):  
Justine Ngoma ◽  
Maarten C. Braakhekke ◽  
Bart Kruijt ◽  
Eddy Moors ◽  
Iwan Supit ◽  
...  
Keyword(s):  
Climate Change ◽  
21St Century ◽  
Primary Productivity ◽  
General Circulation ◽  
Net Primary Productivity ◽  
Co2 Concentration ◽  
Annual Rainfall ◽  
Rainfall Gradient ◽  
Local Soil ◽  
Parameter Values

Abstract. Understanding climate change effects on forests is important considering the role forests play in mitigating climate change. We studied the effects of changes in temperature, rainfall, atmospheric carbon dioxide (CO2) concentration, solar radiation, and number of wet days (as a measure of rainfall intensity) on net primary productivity (NPP) of the Zambian Zambezi teak forests along a rainfall gradient. Using 1960–1989 as a baseline, we projected changes in NPP for the end of the 21st century (2070–2099). We adapted the parameters of the dynamic vegetation model, LPJ-GUESS, to simulate the growth of Zambian forests at three sites along a moisture gradient receiving annual rainfall of between 700 and more than 1000 mm. The adjusted plant functional type was tested against measured data. We forced the model with contemporary climate data (1960–2005) and with climatic forecasts of an ensemble of five general circulation models (GCMs) following Representative Concentration Pathways (RCPs) RCP4.5 and RCP8.5. We used local soil parameter values to characterize texture and measured local tree parameter values for maximum crown area, wood density, leaf longevity, and allometry. The results simulated with the LPJ-GUESS model improved when we used these newly generated local parameters, indicating that using local parameter values is essential to obtaining reliable simulations at site level. The adapted model setup provided a baseline for assessing the potential effects of climate change on NPP in the studied Zambezi teak forests. Using this adapted model version, NPP was projected to increase by 1.77 % and 0.69 % at the wetter Kabompo and by 0.44 % and 0.10 % at the intermediate Namwala sites under RCP8.5 and RCP4.5 respectively, especially caused by the increased CO2 concentration by the end of the 21st century. However, at the drier Sesheke site, NPP would respectively decrease by 0.01 % and 0.04 % by the end of the 21st century under RCP8.5 and RCP4.5. The projected decreased NPP under RCP8.5 at the Sesheke site results from the reduced rainfall coupled with increasing temperature. We thus demonstrated that differences in the amount of rainfall received in a site per year influence the way in which climate change will affect forest resources. The projected increase in CO2 concentration would thus have more effects on NPP in high rainfall receiving areas, while in arid regions, NPP would be affected more by the changes in rainfall and temperature. CO2 concentrations would therefore be more important in forests that are generally not temperature- or precipitation-limited; however, precipitation will continue to be the limiting factor in the drier sites.

Grassland dynamics in response to climate change and human activities in Inner Mongolia, China between 1985 and 2009

2013 ◽  
Vol 35 (3) ◽  
pp. 315 ◽  
Author(s):  
S. J. Mu ◽  
Y. Z. Chen ◽  
J. L. Li ◽  
W. M. Ju ◽  
I. O. A. Odeh ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Ecological Restoration ◽  
Human Activities ◽  
Inner Mongolia ◽  
Management Practices ◽  
Net Primary Productivity ◽  
Temporal Dynamics ◽  
Driving Forces ◽  
Landscape Patterns

China’s grassland has been undergoing rapid changes in the recent past owing to increased climate variability and a shift in grassland management strategy driven by a series of ecological restoration projects. This study investigated the spatio-temporal dynamics of Inner Mongolia grassland, the main grassland region in China and part of the Eurasia Steppe, to detect the interactive nature of climate, ecosystems and society. Land-use and landscape patterns for the period from 1985 to 2009 were analysed based on TM- and MODIS-derived land-use data. Net Primary Productivity (NPP) estimated by using the Carnegie-Ames-Stanford Approach model was used to assess the growth status of grassland. Furthermore, the factors related to the dynamics of grassland were analysed from the perspectives of two driving factors, climate change and human activities. The results indicated that higher temperatures and lower precipitation may generally have contributed to grassland desertification, particularly in arid regions. During the period from 1985 to 2000, a higher human population and an increase in livestock numbers were the major driving forces responsible for the consistent decrease in NPP and a relatively fragmented landscape. From 2000 to 2009, the implementation of effective ecological restoration projects has arrested the grassland deterioration in some ecologically fragile regions. However, a rapid growth of livestock numbers has sparked new degradation onnon-degraded or lightly degraded grassland, which was initially neglected by these projects. In spite of some achievement in grassland restoration, China should take further steps to develop sustainable management practices for climate adaptation and economic development to bring lasting benefits.

scholarly journals Response of Net Primary Productivity of Zambezi teak forests to climate change along a rainfall gradient in Zambia

2018 ◽  
Author(s):  
Justine Ngoma ◽  
Maarten C. Braakhekke ◽  
Bart Kruijt ◽  
Eddy Moors ◽  
Iwan Supit ◽  
...  
Keyword(s):  
Climate Change ◽  
21St Century ◽  
Primary Productivity ◽  
Net Primary Productivity ◽  
Co2 Concentration ◽  
Annual Rainfall ◽  
Base Line ◽  
Rainfall Gradient ◽  
Local Soil ◽  
Parameter Values

Abstract. Understanding climate change effects on forests is important considering the role forests play in mitigating climate change. We studied the effects of changes in temperature, rainfall, atmospheric carbon dioxide (CO2) concentration, solar radiation, and number of wet days (as a measure of rainfall intensity) on net primary productivity (NPP) of the Zambian Zambezi teak forests along a rainfall gradient. Using 1960–1989 as base-line, we projected changes in NPP for the end of the 21st century (2070–2099). We adapted the parameters of the dynamic vegetation model, LPJ-GUESS, to simulate the growth of Zambian forests at three sites along a moisture gradient receiving annual rainfall of between 700 mm to more than 1000 mm. The thus adjusted plant functional type was tested against measured data. We forced the model with contemporary climate data (1960–2005) and with climatic forecasts of an ensemble of five General Circulation Models (GCMs) following RCP4.5 and RCP8.5. We used local soil parameter values to characterize texture and measured local tree parameter values for maximum crown area, wood density, leaf longevity, and allometry. While increased CO2 concentration enhances NPP at the wetter Kabompo and the intermediate Namwala sites, NPP decreases at the drier Sesheke site under both scenarios by the end of 21st century. The projected decreased NPP under RCP8.5 at the Sesheke site results from the reduced rainfall. We thus demonstrated that differences in rainfall pattern influence the way in which climate change will affect forests resources. We also showed that using local parameter values is essential to obtaining reasonably reliable simulations.

scholarly journals Comprehensive Assessment of the Effect of Urban Built-Up Land Expansion and Climate Change on Net Primary Productivity

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-12 ◽  
Author(s):  
Pengyan Zhang ◽  
Yanyan Li ◽  
Wenlong Jing ◽  
Dan Yang ◽  
Yu Zhang ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Land Use Change ◽  
Primary Productivity ◽  
Net Primary Productivity ◽  
Urban Expansion ◽  
Ecosystem Functions ◽  
Rapid Urbanization ◽  
Important Indicator ◽  
The Impact

Urbanization is causing profound changes in ecosystem functions at local and regional scales. The net primary productivity (NPP) is an important indicator of global change, rapid urbanization and climate change will have a significant impact on NPP, and urban expansion and climate change in different regions have different impacts on NPP, especially in densely populated areas. However, to date, efforts to quantify urban expansion and climate change have been limited, and the impact of long-term continuous changes in NPP has not been well understood. Based on land use data, night light data, NPP data, climate data, and a series of social and economic data, we performed a comprehensive analysis of land use change in terms of type and intensity and explored the pattern of urban expansion and its relationship with NPP and climate change for the period of 2000–2015, taking Zhengzhou, China, as an example. The results show that the major form of land use change was cropland to built-up land during the 2000–2015 period, with a total area of 367.51 km2 converted. The NPP exhibited a generally increasing trend in the study area except for built-up land and water area. The average correlation coefficients between temperature and NPP and precipitation and NPP were 0.267 and 0.020, respectively, indicating that an increase in temperature and precipitation can promote NPP despite significant spatial differences. During the examined period, most expansion areas exhibited an increasing NPP trend, indicating that the influence of urban expansion on NPP is mainly characterized by an evident influence of the expansion area. The study can provide a reference for Zhengzhou and even the world's practical research to improve land use efficiency, increase agricultural productivity and natural carbon sinks, and maintain low-carbon development.

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