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 Response of net primary productivity to grassland phenological changes in Xinjiang, China

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e10650
Author(s):  
Renping Zhang ◽  
Jing Guo ◽  
Gang Yin
Keyword(s):  
Primary Productivity ◽  
Net Primary Productivity ◽  
Growing Season ◽  
Casa Model ◽  
Phenological Changes ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Phenological Metrics ◽  
The Impact

Determining the relationship between net primary productivity (NPP) and grassland phenology is important for an in-depth understanding of the impact of climate change on ecosystems. In this study, the NPP of grassland in Xinjiang, China, was simulated using the Carnegie-Ames-Stanford approach (CASA) model with Moderate Resolution Imaging Spectroradiometer (MODIS) grassland phenological (MCD12Q2) data to study trends in phenological metrics, grassland NPP, and the relations between these factors from 2001–2014. The results revealed advancement of the start of the growing season (SOS) for grassland in most regions (55.2%) in Xinjiang. The percentage of grassland area in which the end of the growing season (EOS) was delayed (50.9%) was generally the same as that in which the EOS was advanced (49.1%). The percentage of grassland area with an increase in the length of the growing season (LOS) for the grassland area (54.6%) was greater than that with a decrease in the LOS (45.4%). The percentage of grassland area with an increase in NPP (61.6%) was greater than that with a decrease in NPP (38.4%). Warmer regions featured an earlier SOS and a later EOS and thus a longer LOS. Regions with higher precipitation exhibited a later SOS and an earlier EOS and thus a shorter LOS. In most regions, the SOS was earlier, and spring NPP was higher. A linear statistical analysis showed that at various humidity (K) levels, grassland NPP in all regions initially increased but then decreased with increasing LOS. At higher levels of K, when NPP gradually increased, the LOS gradually decreased.

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 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%.

scholarly journals Dynamics of Vegetation Net Primary Productivity and Its Response to Drought in the Mongolian Plateau

Atmosphere ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1587
Author(s):  
Xiaomeng Guo ◽  
Siqin Tong ◽  
Jinyuan Ren ◽  
Hong Ying ◽  
Yuhai Bao
Keyword(s):  
Primary Productivity ◽  
Net Primary Productivity ◽  
Growing Season ◽  
Mongolian Plateau ◽  
Casa Model ◽  
Lag Effect ◽  
Increasing Trend ◽  
Different Seasons ◽  
The Impact ◽  
Global Carbon

Vegetation net primary productivity (NPP) is an important aspect of the global carbon cycle, and its change is closely related to climate change. This study analyzed the spatial-temporal variation of the standardized precipitation evapotranspiration index (SPEI) and NPP in the Mongolian Plateau, and investigated the effect of drought on NPP. To this end, NPP was simulated using the Carnegie-Ames-Stanford Approach (CASA) model. The results showed that from 1982 to 2014, NPP exhibited an upward trend in different seasons, and a significant increasing trend in most areas in the growing season and spring. The degree of drought also showed an increasing trend in each season. Moreover, the decrease in NPP and SPEI in Mongolia was larger than that in Inner Mongolia. Vegetation showed a positive correlation with SPEI in the growing season and summer, but a negative correlation in the other seasons. Moreover, the impact of drought on vegetation in the growing season showed a lag effect, whereas the lag response was inconspicuous during the early stages of the growing season. Different vegetation NPP responded strongly to the SPEI of the current month and the previous month.

Impacts of climate change on net primary productivity of grasslands in Inner Mongolia

2014 ◽  
Vol 36 (5) ◽  
pp. 493 ◽  
Author(s):  
Qiuyue Li ◽  
Debao Tuo ◽  
Lizhen Zhang ◽  
Xiaoyu Wei ◽  
Yurong Wei ◽  
...  
Keyword(s):  
Climate Change ◽  
Primary Productivity ◽  
Inner Mongolia ◽  
Net Primary Productivity ◽  
Emission Scenario ◽  
Future Climate ◽  
Future Climate Change ◽  
Emission Scenarios ◽  
The Impact ◽  
A1b Scenario

Net primary productivity (NPP) of grasslands is a key variable for characterising carbon cycles in grassland ecosystems. The prediction of NPP in Inner Mongolia is important for adaptation to future climate change, food security and sustainable use of the grassland resources. The output from two models, potentially suitable for simulating NPP in response to climate change, was tested against observed aboveground forage mass of dry matter at eight sites in Inner Mongolia from 1995 to 2005. The Classification Indices-Based Model (CIBM) showed an acceptable agreement with field measurements. The impact of climate change on the NPP of grasslands was subsequently analysed by CIBM using future climate projections from a Global Circulation Model based on three greenhouse gas emission scenarios: A2 (medium-high emission), A1B (medium emission) and B2 (medium-low emission) differing in assumptions about patterns of global social and economic development. Generally, significant increases in NPP, compared with the baseline NPP of 3.6 tonnes ha–1 for 1961–90, were predicted. The magnitude of the increase in NPP depended on the emission scenario, as well as on the time frame and region considered. Overall the predicted NPP stimulation increased with the level of emissions assumed, being 4.8 tonnes ha–1 in the A2 scenario, 4.3 tonnes ha–1 in the B2 scenario and 4.5 tonnes ha–1 in the A1B scenario in the 2080s (2071–2100). The increase in NPP in response to climate change differed between regions and there was an interaction with emission scenario. For the A2 and the B2 emission scenarios, the western region of Inner Mongolia was predicted to exhibit the strongest NPP increases, but, under the A1B scenario for the 2050s, the south-eastern region exhibited the greatest increase in NPP. It is concluded that the productivity of grassland in Inner Mongolia is likely to increase in response to climate change but these predicted effects are sensitive to emission scenarios and differ regionally. This will provide opportunities but also challenges for herders and policy makers in adapting to this change.

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.

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