Modifying the maximal light-use efficiency for enhancing predictions of vegetation net primary productivity on the Mongolian Plateau

Jin, Hugejiletu; Bao, Gang; Chen, Jiquan; Chopping, Mark; Jin, Eerdemutu; Mandakh, Urtnasan; Jiang, Kang; Huang, Xiao‐Jun; Bao, Yuhai; Vandansambuu, Battsengel

doi:10.1080/01431161.2019.1707902

Cited by 22 publications

(22 citation statements)

References 61 publications

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“…Since the value of LUE max has a great influence on the estimated NPP, its value is controversial [31,87]. Some research tried to modify the value of LUE max based on field sampling data [10,88]. In future research, LUE max should be modified using more flux measurement sites.…”

Section: Uncertainty Analysismentioning

confidence: 99%

“…China is a country with rich grassland resources, which account for about 40% of the total land area in China [8,9]. Inner Mongolia has the second largest area of grassland and the largest area of pasture in China, in which approximately 66% of the total area is coved by grassland [8,10,11]. The Inner Mongolia grassland is acknowledged as an important barrier for the ecological environment in northern China [12].…”

Section: Introductionmentioning

confidence: 99%

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Spatiotemporal Monitoring of a Grassland Ecosystem and Its Net Primary Production Using Google Earth Engine: A Case Study of Inner Mongolia from 2000 to 2020

Tan

Wang

et al. 2021

Remote Sensing

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Grassland ecosystems are a significant part of the global ecosystem and support the livelihoods of millions of people. The Inner Mongolia grassland is the largest temperate grassland in the world, and an important ecological barrier for China, but due to human activities and climate change it has been faced with an ecological crisis in recent years. In this study, a modified Carnegie-Ames-Stanford approach (CASA) model based on the Google Earth Engine platform was used to determine the net primary production (NPP) in the Inner Mongolia grassland from 2000 to 2020. The results show that the average annual NPP of the Inner Mongolia grassland is 278.63 g C/m2, and 83.22% of the total area has shown an increasing trend during the study period. We also analyzed the impact of land-use/cover change (LUCC) and climatic factors on NPP. We found that: (1) the total area of grassland increased from 2000 to 2010 and then decreased from 2010 to 2020. During the whole study period, although the grassland area increased slightly by 4728.69 km2 because of LUCC, the overall effect of LUCC on grassland NPP was negative, with a loss of 17.63 Tg C compared to an increase of 16.38 Tg C. (2) The main meteorological factor affecting the NPP of the Inner Mongolia grassland is precipitation, followed by sunshine duration and temperature. About 97.06% of the grassland shows a positive correlation between NPP and precipitation. (3) The results for NPP and its changing trends are not completely consistent in the long- and short-term study periods. Considering the instability of grassland growth, it is necessary to take the periodic variation of precipitation into account when studying NPP. These results could provide basic information for policy formulation and scientific research into the ecological environment management of grassland areas in the future.

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Section: Uncertainty Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Monitoring of a Grassland Ecosystem and Its Net Primary Production Using Google Earth Engine: A Case Study of Inner Mongolia from 2000 to 2020

Tan

Wang

et al. 2021

Remote Sensing

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“…Due to China's Belt and Road Initiative (also known as One Belt, One Road), an increasing number of studies have been conducted within the Mongolian Plateau. This includes various statistical methods to distinguish vegetation change and responses to climate change or anthropogenic activity [22][23][24][25]. However, the BFAST algorithm was not adopted to analyse vegetation dynamics in the Mongolian Plateau.…”

Section: Introductionmentioning

confidence: 99%

NDVI Indicates Long-Term Dynamics of Vegetation and Its Driving Forces from Climatic and Anthropogenic Factors in Mongolian Plateau

Guo

Wang

et al. 2021

Remote Sensing

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In recent years, global warming and intense human activity have been responsible for significantly altering vegetation dynamics on the Mongolian Plateau. Understanding the long-term vegetation dynamics in this region is important to assess the impact of these changes on the local ecosystem. Long-term (1982–2015), satellite-derived normalized difference vegetation index (NDVI) datasets were used to analyse the spatio-temporal patterns of vegetation activities using linear regression and the breaks for additive season and trend methods. The links between these patterns and changes in temperature, precipitation (PRE), soil moisture (SM), and anthropogenic activity were determined using partial correlation analysis, the residual trends method, and a stepwise multiple regression model. The most significant results indicated that air temperature and potential evapotranspiration increased significantly, while the SM and PRE had markedly decreased over the past 34 years. The NDVI dataset included 71.16% of pixels showing an increase in temperature and evaporation during the growing season, particularly in eastern Mongolia and the southern border of the Inner Mongolia Autonomous region, China. The proportion indicating the breakpoint of vegetation dynamics was 71.34% of pixels, and the trend breakpoints mainly occurred in 1993, 2003, and 2010. The cumulative effects of PRE and SM in the middle period, coupled with the short-term effects of temperature and potential evapotranspiration, have had positive effects on vegetation greening. Anthropogenic factors appear to have positively impacted vegetation dynamics, as shown in 81.21% of pixels. We consider rapid economic growth, PRE, and SM to be the main driving factors in Inner Mongolia. PRE was the main climatic factor, and combined human and livestock populations were the primary anthropogenic factors influencing vegetation dynamics in Mongolia. This study is important in promoting the continued use of green projects to address environmental change in the Mongolian Plateau.

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“…The CASA model has been widely applied because it can well evaluate the evolution trend and spatio-temporal variability of NPP on global and regional scales [30,31]. It should be noted that the application of the original maximum LUE rate (0.389 gC • MJ −1 ) in the CASA model to different vegetation types at the regional scale will bring large deviations [32]. Therefore, we localized the maximum LUE for different vegetation types to better describe the temporal and spatial characteristics of regional NPP.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2021

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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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Modifying the maximal light-use efficiency for enhancing predictions of vegetation net primary productivity on the Mongolian Plateau

Cited by 22 publications

References 61 publications

Spatiotemporal Monitoring of a Grassland Ecosystem and Its Net Primary Production Using Google Earth Engine: A Case Study of Inner Mongolia from 2000 to 2020

Spatiotemporal Monitoring of a Grassland Ecosystem and Its Net Primary Production Using Google Earth Engine: A Case Study of Inner Mongolia from 2000 to 2020

NDVI Indicates Long-Term Dynamics of Vegetation and Its Driving Forces from Climatic and Anthropogenic Factors in Mongolian Plateau

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

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