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

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.

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

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.

Spatial Analysis on the Fluctuation of Regional NPP in the Typical Steppe, in China

2012 ◽  
Vol 518-523 ◽  
pp. 5126-5129 ◽  
Author(s):  
Su Ying Li ◽  
Xiu Mei Wang ◽  
Ying Chang ◽  
Xiao Xia Wu ◽  
Qiang Fan
Keyword(s):  
Energy Efficiency ◽  
Primary Productivity ◽  
Inner Mongolia ◽  
Annual Variation ◽  
Net Primary Productivity ◽  
Average Rate ◽  
Landscape Scale ◽  
Typical Steppe ◽  
Casa Model ◽  
Grassland Productivity

Assessing the inter-annual variation of regional grassland productivity is imperative to meet the local requirements of grassland adaptive management at regional- or landscape- scale. For the semiarid grassland of Inner Mongolia, the improved CASA model, a kind of light-energy-efficiency model, was used to simulate the Net Primary Productivity (NPP) of the regional grassland. And this study further calculated the Standard Deviation (SD) and Coefficient of Variation (CV) of the regional NPP. Both of SD and CV were used to reflect the fluctuations of regional NPP in the study area among years. Approximately 1/3 of the regional NPP over the years were dramatically changed, frequently up to large amplitude by an average rate of 1 times or more.

scholarly journals Quantifying the Impacts of Anthropogenic Activities and Climate Variations on Vegetation Productivity Changes in China from 1985 to 2015

2020 ◽  
Vol 12 (7) ◽  
pp. 1113
Author(s):  
Shahid Naeem ◽  
Yongqiang Zhang ◽  
Jing Tian ◽  
Faisal Mueen Qamer ◽  
Aamir Latif ◽  
...  
Keyword(s):  
Climate Change ◽  
Primary Productivity ◽  
Human Activities ◽  
Vegetation Cover ◽  
Net Primary Productivity ◽  
Anthropogenic Activities ◽  
Climate Factors ◽  
Climate Variations ◽  
Base Period ◽  
Increasing Trends

Accurate assessment of vegetation dynamics provides important information for ecosystem management. Anthropogenic activities and climate variations are the major factors that primarily influence vegetation ecosystems. This study investigates the spatiotemporal impacts of climate factors and human activities on vegetation productivity changes in China from 1985 to 2015. Actual net primary productivity (ANPP) is used to reflect vegetation dynamics quantitatively. Climate-induced potential net primary productivity (PNPP) is used as an indicator of climate change, whereas the difference between PNPP and ANPP is considered as an indicator of human activities (HNPP). Overall, 91% of the total vegetation cover area shows declining trends for net primary productivity (NPP), while only 9% shows increasing trends before 2000 (base period). However, after 2000 (restoration period), 78.7% of the total vegetation cover area shows increasing trends, whereas 21.3% of the area shows decreasing trends. Moreover, during the base period, the quantitative contribution of climate change to NPP restoration is 0.21 grams carbon per meter square per year (gC m−2 yr−1) and to degradation is 2.41 gC m−2 yr−1, while during the restoration period, climate change contributes 0.56 and 0.29 gC m−2 yr−1 to NPP restoration and degradation, respectively. Human activities contribute 0.36 and 0.72 gC m−2 yr−1 during the base period, and 0.63 and 0.31 gC m−2 yr−1 during the restoration period to NPP restoration and degradation, respectively. The combined effects of climate and human activities restore 0.65 and 1.11 gC m−2 yr−1, and degrade 2.01 and 0.67 gC m−2 yr−1 during the base and restoration periods, respectively. Climate factors affect vegetation cover more than human activities, while precipitation is found to be more sensitive to NPP change than temperature. Unlike the base period, NPP per unit area increases with an increase in the human footprint pressure during the restoration period. Grassland has more variability than other vegetation classes, and the grassland changes are mainly observed in Tibet, Xinjiang, and Inner Mongolia regions. The results may help policy-makers by providing necessary guidelines for the management of forest, grassland, and agricultural activities.

Spatial-temporal distribution of net primary productivity and its relationship with climate factors in Inner Mongolia from 2001 to 2010

2013 ◽  
Vol 33 (12) ◽  
pp. 3752-3764 ◽  
Author(s):  
穆少杰 MU Shaojie ◽  
李建龙 LI Jianlong ◽  
周伟 ZHOU Wei ◽  
杨红飞 YANG Hongfei ◽  
章超斌 ZHANG Chaobin ◽  
...  
Keyword(s):  
Primary Productivity ◽  
Inner Mongolia ◽  
Net Primary Productivity ◽  
Temporal Distribution ◽  
Climate Factors

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

2019 ◽  
Vol 11 (15) ◽  
pp. 4176 ◽  
Author(s):  
Qing Huang ◽  
Weimin Ju ◽  
Fangyi Zhang ◽  
Qian Zhang
Keyword(s):  
Climate Change ◽  
Interannual Variability ◽  
Primary Productivity ◽  
Southwest China ◽  
Net Primary Productivity ◽  
Terrestrial Ecosystem ◽  
Co2 Concentration ◽  
Series Data ◽  
Geographical Regions ◽  
The Future

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.

scholarly journals Biomass Production Assessment in a Protected Area of Dry Tropical forest Ecosystem of India: A Field to Satellite Observation Approach

2021 ◽  
Vol 9 ◽  
Author(s):  
Tarun K. Thakur ◽  
Digvesh K. Patel ◽  
Anita Thakur ◽  
Anirudh Kumar ◽  
Arvind Bijalwan ◽  
...  
Keyword(s):  
Climate Change ◽  
Carbon Sequestration ◽  
Tropical Forest ◽  
Primary Productivity ◽  
Forest Ecosystem ◽  
Net Primary Productivity ◽  
Mixed Forest ◽  
Vegetation Types ◽  
C Storage ◽  
Tropical Forest Ecosystem

In recent decades, degradation and loss of the world’s forest ecosystems have been key contributors to biodiversity loss and future climate change. This article analyzes plant diversity, biomass, carbon sequestration potential (CSP), and the net primary productivity (NPP) of four vegetation types viz., Dense mixed forest (DMF); Open mixed forest (OMF); Teak plantation (TP), and Sal mixed forest (SMF) in the dry tropical forest ecosystem of central India through remote sensing techniques together with physical ground observations during 2013–2018. The total C storage in trees varied from 16.02 to 47.15 Mg ha−1 in studied vegetation types with the highest in DMF and lowest in OMF. The total C storage in stem wood, branches, and foliage falls in the range of 52.93–78.30%, 9.49–22.99%, and 3.31–12.89% respectively. The total standing biomass varied from 83.77 to 111.21 Mg ha−1 and these variations are due to different vegetation types, with the highest in DMF followed by TP, SMF while the lowest was estimated in OMF. The net primary productivity (NPP) [aboveground (AG) + belowground (BG)] varied from 7.61 to 9.94 Mg ha−1 yr−1 with mean values of 8.74 Mg ha−1 yr−1 where AG shares a maximum contribution of 77.66%. The total biomass production was distributed from 64.09 to 82.91% in AG and 17.08–35.91% in BG components. The present study outlines that the studied forest ecosystem has the substantial potential of carbon sequestration and a great possibility of mitigating local and global climate change.

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

2014 ◽  
Vol 121 (1-2) ◽  
pp. 319-335 ◽  
Author(s):  
Suosuo Li ◽  
Shihua Lü ◽  
Yongjun Zhang ◽  
Yuanpu Liu ◽  
Yanhong Gao ◽  
...  
Keyword(s):  
Climate Change ◽  
Primary Productivity ◽  
Net Primary Productivity ◽  
Terrestrial Ecosystem

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.

scholarly journals Research Advances in Net Primary Productivity of Terrestrial Ecosystem

2020 ◽  
Vol 08 (08) ◽  
pp. 48-54
Author(s):  
Yixin Xu ◽  
Xiaoling Hu ◽  
Zhao Liu ◽  
Huayong Zhang
Keyword(s):  
Primary Productivity ◽  
Net Primary Productivity ◽  
Terrestrial Ecosystem
Sign in / Sign up

Export Citation Format

Share Document