scholarly journals Impacts of 1.5 °C and 2 °C Global Warming on Net Primary Productivity and Carbon Balance in China’s Terrestrial Ecosystems

2020 ◽  
Vol 12 (7) ◽  
pp. 2849
Author(s):  
Li Yu ◽  
Fengxue Gu ◽  
Mei Huang ◽  
Bo Tao ◽  
Man Hao ◽  
...  
Keyword(s):  
Global Warming ◽  
Primary Productivity ◽  
Net Primary Productivity ◽  
Climate Adaptation ◽  
Coupled Model ◽  
Terrestrial Ecosystems ◽  
Northern China ◽  
Ecosystem Model ◽  
Intercomparison Project ◽  
Potential Risks

Assessing potential impacts of 1.5 °C and 2 °C global warming and identifying the risks of further 0.5 °C warming are crucial for climate adaptation and disaster risk management. Four earth system models in the Coupled Model Intercomparison Project Phase 5 (CMIP5) and a process-based ecosystem model are used in this study to assess the impacts and potential risks of the two warming targets on the carbon cycle of China’s terrestrial ecosystems. Results show that warming generally stimulates the increase of net primary productivity (NPP) and net ecosystem productivity (NEP) under both representative concentration pathway (RCP) 4.5 and RCP8.5 scenarios. The projected increments of NPP are higher at 2 °C warming than that at 1.5 °C warming for both RCP4.5 and RCP8.5 scenarios; approximately 13% and 19% under RCP4.5, and 12.5% and 20% under RCP8.5 at 1.5 °C and 2 °C warming, respectively. However, the increasing rate of NPP was projected to decline at 2 °C warming under the RCP4.5 scenario, and the further 0.5 °C temperature rising induces the decreased NPP linear slopes in more than 81% areas of China’s ecosystems. The total NEP is projected to be increased by 53% at 1.5 °C, and by 81% at 2 °C warming. NEP was projected to increase approximately by 28% with the additional 0.5 °C warming. Furthermore, the increasing rate of NEP weakens at 2 °C warming, especially under the RCP8.5 scenario. In summary, China’s total NPP and NEP were projected to increase under both 1.5 °C and 2 °C warming scenarios, although adverse effects (i.e., the drop of NPP growth and the reduction of carbon sequestration capacity) would occur in some regions such as northern China in the process of global warming.

scholarly journals Projection of Net Primary Productivity under Global Warming Scenarios of 1.5 °C and 2.0 °C in Northern China Sandy Areas

Atmosphere ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 71 ◽  
Author(s):  
Xiaofei Ma ◽  
Tianci Huo ◽  
Chengyi Zhao ◽  
Wei Yan ◽  
Xun Zhang
Keyword(s):  
Global Warming ◽  
Primary Productivity ◽  
Net Primary Productivity ◽  
Negative Impact ◽  
Northern China ◽  
Inhibitory Effect ◽  
Emission Scenarios ◽  
Casa Model ◽  
Spatio Temporal ◽  
The Impact

Empirical evidence suggests that variations in climate affect the net primary productivity (NPP) across sandy areas over time. However, little is known about the relative impacts of climate change on NPP with global warming of 1.5 and 2.0 °C (GW_1.5 °C_2.0 °C) relative to pre-industrial levels. Here, we used a new set of climate simulations from four Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP 2b) datasets, modified the Carnegie-Ames-Stanford approach (CASA) model and assessed the spatio-temporal variation in NPP in sandy areas of northern China (SAONC). Compared with the reference period (RP, 1986–2005), the NPP variation under four emission scenarios showed clear rising trends and increased most significantly under RCP8.5 with an annual average increase of 2.34 g C/m2. The estimated annual NPP under global warming of 1.5 °C (GW_1.5 °C) increased by 14.17, 10.72, 8.57, and 26.68% in different emission scenarios, and under global warming of 2.0 °C (GW_2.0 °C) it increased by 20.87, 24.01, 29.31, and 39.94%, respectively. In terms of seasonal change, the NPP value under the four emission scenarios changed most significantly in the summer relative to RP, exhibiting a growth of 16.48%. Temperature changes (p > 0.614) had a greater impact on NPP growth than precipitation (p > 0.017), but solar radiation showed a certain negative impact in the middle- and low-latitude regions. NPP showed an increasing trend that changed from the southeast to the central and western regions at GW_1.5 to GW_2.0 °C. NPP was consistent with the spatial change in climate factors and had a promoting role in high latitudes in SAONC, but it was characterized by a certain inhibitory effect at middle and low latitudes in SAONC. The uncertainty of NPP under the four models ranged from 16.29 to 26.52%. Our findings suggest that the impact of GW_1.5 °C is relatively high compared with the current conditions, whereas GW_2.0 °C implies significantly lower projected NPP growth in all areas.

scholarly journals Empirical and model-based estimates of spatial and temporal variations in net primary productivity in semi-arid grasslands of Northern China

2017 ◽  
Author(s):  
Shengwei Zhang ◽  
Rui Zhang ◽  
Tingxi Liu ◽  
Xin Song ◽  
Mark A. Adams
Keyword(s):  
Primary Productivity ◽  
Net Primary Productivity ◽  
Northern China ◽  
Ecosystem Model ◽  
Temporal Variations ◽  
Temperature And Precipitation ◽  
Summer Temperatures ◽  
Arid Grasslands ◽  
Annual Scale ◽  
Pixel Scale

Abstract. Spatiotemporal variations in net primary productivity (NPP) of vegetation offer insights to surface water and carbon dynamics, and are closely related to temperature and precipitation. We employed the Carnegie-Ames-Stanford Approach ecosystem model to estimate NPP of semiarid grassland in northern China between 2001 and 2013. Model estimates were strongly linearly correlated with observed values (R2 = 0.67, RMSE = 35 g C m−2 year−1). We also quantified inter-annual changes in NPP over the 13-year study period. NPP varied between 141 and 313 g C m−2 year−1, with a mean of 240 g C m−2 year−1. NPP increased from west to east each year, and mean precipitation in each county was significantly positively correlated with NPP in annually, summer and autumn. Mean precipitation was also positively correlated with NPP in spring, but the correlation was not significant. Annual and summer temperatures were mostly negatively correlated with NPP, but temperature was positively correlated with spring and autumn NPP. Spatial correlation and partial correlation analyses at the pixel scale confirmed precipitation as a major driver of NPP. Temperature was negatively correlated with NPP in 99 % of the regions at the annual scale, but after removing the effect of precipitation, temperature was positively correlated with the NPP in 77 % of the regions.

scholarly journals Drought-Induced Reduction in Net Primary Productivity across Mainland China from 1982 to 2015

2018 ◽  
Vol 10 (9) ◽  
pp. 1433 ◽  
Author(s):  
Chengguang Lai ◽  
Jun Li ◽  
Zhaoli Wang ◽  
Xiaoqing Wu ◽  
Zhaoyang Zeng ◽  
...  
Keyword(s):  
Primary Productivity ◽  
Net Primary Productivity ◽  
Mainland China ◽  
Terrestrial Ecosystems ◽  
Northern China ◽  
Tibet Plateau ◽  
Positive Correlation ◽  
Casa Model ◽  
Increasing Trend ◽  
Qinghai Tibet Plateau

Terrestrial net primary productivity (NPP) plays an essential role in the global carbon cycle as well as for climate change. However, in the past three decades, terrestrial ecosystems across mainland China suffered from frequent drought and, to date, the adverse impacts on NPP remain uncertain. This study explored the spatiotemporal features of NPP and discussed the influences of drought on NPP across mainland China from 1982 to 2015 using the Carnegie Ames Stanford Application (CASA) model and the standardized precipitation evapotranspiration index (SPEI). The obtained results indicate that: (1) The total annual NPP across mainland China showed an non-significantly increasing trend from 1982 to 2015, with annual increase of 0.025 Pg C; the spring NPP exhibited a significant increasing trend (0.031 Pg C year−1, p < 0.05) while the summer NPP showed a higher decreasing trend (0.019 Pg C year−1). (2) Most areas of mainland China were spatially dominated by a positive correlation between annual NPP and SPEI and a significant positive correlation was mainly observed for Northern China; specific to the nine sub-regions, annual NPP and SPEI shared similar temporal patterns with a significant positive relation in Northeastern China, Huang-Huai-Hai, Inner Mongolia, and the Gan-Xin Region. (3) During the five typical drought events, more than 23% areas of mainland China experienced drought ravage; the drought events generally caused about 30% of the NPP reduction in most of the sub-regions while the NPP in the Qinghai-Tibet Plateau Region generally decreased by about 10%.

Variability of ecosystem carbon source from microbial respiration is controlled by rainfall dynamics

2021 ◽  
Vol 118 (52) ◽  
pp. e2115283118
Author(s):  
Heng Huang ◽  
Salvatore Calabrese ◽  
Ignacio Rodriguez-Iturbe
Keyword(s):  
Primary Productivity ◽  
Microbial Growth ◽  
Net Primary Productivity ◽  
Carbon Sources ◽  
Terrestrial Ecosystems ◽  
Rainfall Regime ◽  
Physical Factors ◽  
Scale Parameters ◽  
Complex Interactions ◽  
Soil Heterotrophic Respiration

Soil heterotrophic respiration (Rh) represents an important component of the terrestrial carbon cycle that affects whether ecosystems function as carbon sources or sinks. Due to the complex interactions between biological and physical factors controlling microbial growth, Rh is uncertain and difficult to predict, limiting our ability to anticipate future climate trajectories. Here we analyze the global FLUXNET 2015 database aided by a probabilistic model of microbial growth to examine the ecosystem-scale dynamics of Rh and identify primary predictors of its variability. We find that the temporal variability in Rh is consistently distributed according to a Gamma distribution, with shape and scale parameters controlled only by rainfall characteristics and vegetation productivity. This distribution originates from the propagation of fast hydrologic fluctuations on the slower biological dynamics of microbial growth and is independent of biome, soil type, and microbial physiology. This finding allows us to readily provide accurate estimates of the mean Rh and its variance, as confirmed by a comparison with an independent global dataset. Our results suggest that future changes in rainfall regime and net primary productivity will significantly alter the dynamics of Rh and the global carbon budget. In regions that are becoming wetter, Rh may increase faster than net primary productivity, thereby reducing the carbon storage capacity of terrestrial ecosystems.

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

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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