Roles of Climate Change and Increasing CO2 in Driving Changes of Net Primary Productivity in China Simulated Using a Dynamic Global Vegetation Model

Net primary productivity (NPP) is the key component of the terrestrial carbon cycle, and terrestrial NPP trends under increasing CO2 and climate change in the past and future are of great significance in the study of the global carbon budget. Here, the LPJ-DGVM was employed to simulate the magnitude and pattern of China’s terrestrial NPP using long-term series data to understand the response of terrestrial NPP to increasing CO2 concentration and climate change. The results showed that total NPP of China’s terrestrial ecosystem increased from 2.8 to 3.6 Pg C yr−1 over the period of 1961–2016, with an annual average of 3.1 Pg C yr−1. The average NPP showed a gradient decrease from the southeast to northwest. Southwest China and Northwest China, comprising mostly arid and semi-arid regions, exhibited the largest increase rate in total NPP among the six geographical regions of China. Additionally, large interannual variability around the NPP trends was presented, and NPP anomalies in China’s terrestrial ecosystem are strongly associated with the El Niño-Southern Oscillation (ENSO). Southwest China made the largest contribution to the interannual variability of national total NPP. The total NPP of China’s terrestrial ecosystem continuously increased with the concurrent increase in the CO2 concentration and climate change under different scenarios in the future. During the period from 2091 to 2100, the average total NPP under the A2 and RCP85 scenarios would reach 4.9 and 5.1 Pg C yr−1 respectively, higher than 4.2 and 3.9 Pg C yr−1 under the B1 and RCP45 scenarios. Forests, especially temperate forests, make the largest contribution to the future increase in NPP. The increase in CO2 concentration would play a dominant role in driving further NPP increase in China’s terrestrial ecosystems, and climate change may slightly attenuate the fertilization effect of CO2 on NPP.

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Quantitatively assessing the effects of climate change and human activities on ecosystem degradation and restoration in southwest China

The Rangeland Journal ◽

10.1071/rj18111 ◽

2019 ◽

Vol 41 (4) ◽

pp. 335

Author(s):

Z. G. Sun ◽

J. S. Wu ◽

F. Liu ◽

T. Y. Shao ◽

X. B. Liu ◽

...

Keyword(s):

Climate Change ◽

Primary Productivity ◽

Human Activities ◽

Southwest China ◽

Net Primary Productivity ◽

Terrestrial Ecosystems ◽

Ecosystem Degradation ◽

Relative Contribution ◽

Degraded Ecosystem ◽

Annual Means

Identifying the effects of climate change and human activities on the degradation and restoration of terrestrial ecosystems is essential for sustainable management of these ecosystems. However, our knowledge of methodology on this topic is limited. To assess the relative contribution of climate change and human activities, actual and potential net primary productivity (NPPa and NPPp respectively), and human appropriation of net primary productivity (HANPP) were calculated and applied to the monitoring of forest, grassland, and cropland ecosystems in Yunnan–Guizhou–Sichuan Provinces, southwest China. We determined annual means of 476 g C m–2 year–1 for NPPa, 1314 g C m–2 year–1 for NPPp, and 849 g C m–2 year–1 for HANPP during the period between 2007 and 2016. Furthermore, the area with an increasing NPPa accounted for 75.12% of the total area of the three ecosystems. Similarly, the areas with increasing NPPp and HANPP accounted for 77.60 and 57.58% of the study area respectively. Furthermore, we found that ~57.58% of areas with ecosystem restored was due to climate change, 23.39% due to human activities, and 19.03% due to the combined effects of human activities and climate change. In contrast, climate change and human activities contributed to 19.47 and 76.36%, respectively, of the areas of degraded ecosystem. Only 4.17% of degraded ecosystem could be attributed to the combined influences of climate change and human activities. We conclude that human activities were mainly responsible for ecosystem degradation, whereas climate change benefitted ecosystem restoration in southwest China in the past decade.

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

Biogeosciences ◽

10.5194/bg-16-3853-2019 ◽

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.

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

10.5194/bg-2018-421 ◽

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

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Spatiotemporal heterogeneity of net primary productivity and response to climate change in the mountain regions of southwest China

Ecological Indicators ◽

10.1016/j.ecolind.2021.108273 ◽

2021 ◽

Vol 132 ◽

pp. 108273

Author(s):

Yahui Wang ◽

Erfu Dai ◽

Chunsheng Wu

Keyword(s):

Climate Change ◽

Primary Productivity ◽

Southwest China ◽

Net Primary Productivity ◽

Mountain Regions ◽

Spatiotemporal Heterogeneity

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Spatiotemporal Dynamics of Vegetation Net Primary Productivity and Its Response to Climate Change in Inner Mongolia from 2002 to 2019

Sustainability ◽

10.3390/su132313310 ◽

2021 ◽

Vol 13 (23) ◽

pp. 13310

Author(s):

Lei Hao ◽

Shan Wang ◽

Xiuping Cui ◽

Yongguang Zhai

Keyword(s):

Climate Change ◽

Solar Radiation ◽

Primary Productivity ◽

Inner Mongolia ◽

Net Primary Productivity ◽

Terrestrial Ecosystem ◽

Climate Factors ◽

Vegetation Types ◽

Casa Model ◽

Close Relationship

Understanding vegetation dynamics and their responses to climate change are essential to enhance the carbon sequestration of the terrestrial ecosystem under global warming. Although some studies have identified that there is a close relationship between vegetation net primary productivity and climate change, it is unclear whether this response exists in ecologically fragile areas, especially in Inner Mongolia, in which multiple ecological ecotones are related to vegetation types. This study uses the Carnegie–Ames–Stanford Approach (CASA) model to estimate vegetation NPP in Inner Mongolia from 2002 to 2019 and focuses on the spatial and temporal changes of NPP of different vegetation types and their responses to three typical climate factors: precipitation, temperature, and solar radiation. The results show that the NPP estimated by the CASA model agrees well with the observed NPP (R2 = 0.66, p < 0.001). The vegetation NPP in Inner Mongolia decreases gradually from northeast to southwest, and the average NPP is 223.50 gC ∙ m−2. From 2002 to 2019, the NPP of all vegetation types trended upward, but exhibiting different rates. The vegetation types, ranked in order of decreasing NPP, are forest, cropland, grassland, and desert. The NPP response of different vegetation types to climate factors possesses significant differences. The cropland NPP and grassland NPP are mainly affected by precipitation, the desert NPP is controlled by both precipitation and solar radiation, and the forest NPP is determined by all three climate factors.

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The change of global terrestrial ecosystem net primary productivity (NPP) and its response to climate change in CMIP5

Theoretical and Applied Climatology ◽

10.1007/s00704-014-1242-8 ◽

2014 ◽

Vol 121 (1-2) ◽

pp. 319-335 ◽

Cited By ~ 8

Author(s):

Suosuo Li ◽

Shihua Lü ◽

Yongjun Zhang ◽

Yuanpu Liu ◽

Yanhong Gao ◽

...

Keyword(s):

Climate Change ◽

Primary Productivity ◽

Net Primary Productivity ◽

Terrestrial Ecosystem

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Effects of climatic factors on the net primary productivity in the source region of Yangtze River, China

Scientific Reports ◽

10.1038/s41598-020-80494-9 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Zhe Yuan ◽

Yongqiang Wang ◽

Jijun Xu ◽

Zhiguang Wu

Keyword(s):

Climate Change ◽

Primary Productivity ◽

Yangtze River ◽

Net Primary Productivity ◽

Climatic Factors ◽

Source Region ◽

Primary Reason ◽

Vegetation Types ◽

Temperature And Precipitation ◽

Increasing Trend

AbstractThe ecosystem of the Source Region of Yangtze River (SRYR) is highly susceptible to climate change. In this study, the spatial–temporal variation of NPP from 2000 to 2014 was analyzed, using outputs of Carnegie–Ames–Stanford Approach model. Then the correlation characteristics of NPP and climatic factors were evaluated. The results indicate that: (1) The average NPP in the SRYR is 100.0 gC/m2 from 2000 to 2014, and it shows an increasing trend from northwest to southeast. The responses of NPP to altitude varied among the regions with the altitude below 3500 m, between 3500 to 4500 m and above 4500 m, which could be attributed to the altitude associated variations of climatic factors and vegetation types; (2) The total NPP of SRYR increased by 0.18 TgC per year in the context of the warmer and wetter climate during 2000–2014. The NPP was significantly and positively correlated with annual temperature and precipitation at interannual time scales. Temperature in February, March, May and September make greater contribution to NPP than that in other months. And precipitation in July played a more crucial role in influencing NPP than that in other months; (3) Climatic factors caused the NPP to increase in most of the SRYR. Impacts of human activities were concentrated mainly in downstream region and is the primary reason for declines in NPP.

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Spatial-temporal changes in river runoff and terrestrial ecosystem water retention under 1.5 °C and 2 °C warming scenarios across China

10.5194/esd-2017-96 ◽

2017 ◽

Author(s):

Ran Zhai ◽

Fulu Tao ◽

Zhihui Xu

Keyword(s):

Climate Change ◽

Interannual Variability ◽

River Runoff ◽

Water Retention ◽

Terrestrial Ecosystem ◽

Maximum Temperature ◽

Climate Scenarios ◽

Warming Scenario ◽

Basin Scale ◽

The Impact

Abstract. The Paris Agreement set a long-term temperature goal of holding the global average temperature increase to below 2.0 ℃ above pre-industrial levels, and pursuing efforts to limit this to 1.5 ℃, it is therefore important to understand the impacts of climate change under 1.5 ℃ and 2.0 ℃ warming scenarios for climate adaptation and mitigation. Here, climate scenarios by four Global Circulation Models (GCMs) for the baseline (2006–2015), 1.5 ℃ and 2.0 ℃ warming scenarios (2106–2115) were used to drive the validated Variable Infiltration Capacity (VIC) hydrological model to investigate the impacts of global warming on river runoff and Terrestrial Ecosystem Water Retention (TEWR) in China. The trends in annual mean temperature, precipitation, river runoff and TEWR were analysed at the grid and basin scale. Results showed that there were large uncertainties in climate scenarios from the different GCMs, which led to large uncertainties in the impact assessment. The differences among the four GCMs were larger than differences between the two warming scenarios. The interannual variability of river runoff increased notably in areas where it was projected to increase, and the interannual variability increased notably from 1.5 ℃ warming scenario to 2.0 ℃ warming scenario. By contrast, TEWR would remain relatively stable. Both extreme low and high river runoff would increase under the two warming scenarios in most areas in China, with high river runoff increasing more. And the risk of extreme river runoff events would be higher under 2.0 ℃ warming scenario than under 1.5 ℃ warming scenario in term of both extent and intensity. River runoff was significantly positively correlated to precipitation, while increase in maximum temperature would generally cause river runoff to decrease through increasing evapotranspiration. Likewise, precipitation also played a dominant role in affecting TEWR. Our findings highlight climate change mitigation and adaptation should be taken to reduce the risks of hydrological extreme events.

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