Modeling net primary productivity of terrestrial ecosystems in the semi-arid climate of the Mongolian Plateau using LSWI-based CASA ecosystem model

Bao, Gang; Qin, Zhihao; Xin, Xiaoping; Bao, Yuhai; Bayarsaikan, Sainbuyin; Zhou, Yi; Chuntai, Bilegtmandakh

doi:10.1016/j.jag.2015.12.001

Cited by 81 publications

(43 citation statements)

References 55 publications

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“…Of the models that estimate NPP globally, the CASA ecosystem model is one of the most widely used models. It adequately addresses NPP spatial and temporal dynamics at regional to global scales [31]. NPP estimates are determined using two variables: (1) vegetation photosynthetic active radiation (APAR); (2) actual light use efficiency ( ε ).…”

Section: Methodsmentioning

confidence: 99%

Ecosystem Services Insights into Water Resources Management in China: A Case of Xi’an City

Liu

Jing

Gao

et al. 2016

IJERPH

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Global climate and environmental changes are endangering global water resources; and several approaches have been tested to manage and reduce the pressure on these decreasing resources. This study uses the case study of Xi’an City in China to test reasonable and effective methods to address water resource shortages. The study generated a framework combining ecosystem services and water resource management. Seven ecosystem indicators were classified as supply services, regulating services, or cultural services. Index values for each indicator were calculated, and based on questionnaire results, each index’s weight was calculated. Using the Likert method, we calculated ecosystem service supplies in every region of the city. We found that the ecosystem’s service capability is closely related to water resources, providing a method for managing water resources. Using Xi’an City as an example, we apply the ecosystem services concept to water resources management, providing a method for decision makers.

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Section: Methodsmentioning

confidence: 99%

Ecosystem Services Insights into Water Resources Management in China: A Case of Xi’an City

Liu

Jing

Gao

et al. 2016

IJERPH

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“…Throughout the EASR, natural vegetation mainly includes meadows, meadow steppes, typical steppes, desert steppes, alpine steppes, and alpine meadows (Appendix , Olson et al., ; Editorial Committee of Vegetation Map of China Chinese Academy of Sciences, ; Woodward, ; Bao et al., ). The dominant grasses include perennial bunchgrasses, and constructive species belong to the Stipa genus, which refers to species controlling the structure and function of the ecosystem while their amount being not always maximum in the ecosystem (Woodward, ; Zhou, ).…”

Section: Methodsmentioning

confidence: 99%

“…Evaluations of ANPP in grasslands at a regional or global scale have suggested that the ANPP of grasslands exhibits obvious spatial variations (Bao et al., ; Eisfelder, Klein, Niklaus, & Kuenzer, ; Irisarri, Oesterheld, Paruelo, & Texeira, ; Sala, Parton, Joyce, & Lauenroth, ; Xia et al., ; Zhang et al., ). Estimates of total aboveground net primary productivity (TANPP) in global grasslands vary from 1423 Tg C yr −1 to 4635 Tg C yr −1 (Bazilevich, Rodin, & Rozov, ; Parton et al., ; Whittaker & Likens, ; Xia et al., ).…”

Section: Introductionmentioning

confidence: 99%

“…Studies on the spatiotemporal dynamics of the ANPP of the EASR mainly focus on typical geographical units within it, such as on the Inner Mongolian temperate grasslands (Ma, Fang, Yang, & Mohammat, ; Ma, Liu et al., ; Ma, Yang, He, Hui, & Fang, ) and the Tibetan Plateau alpine grasslands (Zhang et al., ). In recent years, some studies have also analyzed the spatiotemporal dynamics of the ANPP in the grassland areas of Mongolia and Kazakhstan at a national scale (Bao et al., ; Eisfelder et al., ). However, studies on the spatiotemporal dynamics of ANPP have not yet been specifically reported for the entire EASR.…”

Section: Introductionmentioning

confidence: 99%

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Analysis of spatial and temporal patterns of aboveground net primary productivity in the Eurasian steppe region from 1982 to 2013

Jiao

et al. 2017

Ecology and Evolution

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To explore the importance of the Eurasian steppe region (EASR) in global carbon cycling, we analyzed the spatiotemporal dynamics of the aboveground net primary productivity (ANPP) of the entire EASR from 1982 to 2013. The ANPP in the EASR was estimated from the Integrated ANPPNDVI model, which is an empirical model developed based on field‐observed ANPP and long‐term normalized difference vegetation index (NDVI) data. The optimal composite period of NDVI data was identified by considering spatial heterogeneities across the study area in the Integrated ANPPNDVI model. EASR's ANPP had apparent zonal patterns along hydrothermal gradients, and the mean annual value was 43.78 g C m−2 yr−1, which was lower than the global grasslands average. Compared to other important natural grasslands, EASR's ANPP was lower than the North American, South American, and African grasslands. The total aboveground net primary productivity (TANPP) was found to be 378.97 Tg C yr−1, which accounted for 8.18%–36.03% of the TANPP for all grasslands. In addition, EASR's TANPP was higher than that of the grasslands in North America, South America, and Africa. The EASR's TANPP increased in a fluctuating manner throughout the entire period of 1982–2013. The increasing trend was greater than that for North American and South American and was lower than that for African grasslands over the same period. The years 1995 and 2007 were two turning points at which trends in EASR's TANPP significantly changed. Our analysis demonstrated that the EASR has been playing a substantial and progressively more important role in global carbon sequestration. In addition, in the development of empirical NDVI‐based ANPP models, the early–middle growing season averaged NDVI, the middle–late growing season averaged NDVI and the annual maximum NDVI are recommended for use for semi‐humid regions, semi‐arid regions, and desert vegetation in semi‐arid regions, respectively.

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“…For larger regional scale areas and temporal continuous series data, model calculation is considered to be an effective alternative for estimating the historical NPP. Though a variety of models have been created for NPP estimation and other components of the carbon cycle, the CASA (Canegie-Ames-Stanford Approach) model is an excellent light-use efficiency model, which has been applied and verified in many different areas [32][33][34][35].…”

Section: Npp Estimationmentioning

confidence: 99%

Monitoring Phenology in the Temperate Grasslands of China from 1982 to 2015 and Its Relation to Net Primary Productivity

Zhang

Wang

et al. 2019

Sustainability

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Both vegetation phenology and net primary productivity (NPP) are crucial topics under the background of global change, but the relationships between them are far from clear. In this study, we quantified the spatial-temporal vegetation start (SOS), end (EOS), and length (LOS) of the growing season and NPP for the temperate grasslands of China based on a 34-year time-series (1982–2015) normalized difference vegetation index (NDVI) derived from global inventory modeling and mapping studies (GIMMS) and meteorological data. Then, we demonstrated the relationships between NPP and phenology dynamics. The results showed that more than half of the grasslands experienced significant changes in their phenology and NPP. The rates of their changes exhibited spatial heterogeneity, but their phenological changes could be roughly divided into three different clustered trend regions, while NPP presented a polarized pattern that increased in the south and decreased in the north. Different trend zones’ analyses revealed that phenology trends accelerated after 1997, which was a turning point. Prolonged LOS did not necessarily increase the current year’s NPP. SOS correlated with the NPP most closely during the same year compared to EOS and LOS. Delayed SOS contributed to increasing the summer NPP, and vice versa. Thus, SOS could be a predictor for current year grass growth. In view of this result, we suggest that future studies should further explore the mechanisms of SOS and plant growth.

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Modeling net primary productivity of terrestrial ecosystems in the semi-arid climate of the Mongolian Plateau using LSWI-based CASA ecosystem model

Cited by 81 publications

References 55 publications

Ecosystem Services Insights into Water Resources Management in China: A Case of Xi’an City

Ecosystem Services Insights into Water Resources Management in China: A Case of Xi’an City

Analysis of spatial and temporal patterns of aboveground net primary productivity in the Eurasian steppe region from 1982 to 2013

Monitoring Phenology in the Temperate Grasslands of China from 1982 to 2015 and Its Relation to Net Primary Productivity

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