Using Remote Sensing and GIS Technologies to Estimate Grass Yield and Livestock Carrying Capacity of Alpine Grasslands in Golog Prefecture, China

Yu, Liang; Li, Zhou; Liu, Wei; Zhou, Huakun

doi:10.1016/s1002-0160(10)60023-9

Cited by 73 publications

(40 citation statements)

References 17 publications

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“…MOD13Q1 data are provided every 16 days at 250-meter spatial resolution as a gridded level-three product (available at [40]). Since providing consistent spatial and temporal comparisons of global vegetation conditions, such MODIS NDVI products can be used to monitor the vegetation conditions and simulate above-ground productivity [26,41]. However, these NDVI products might be affected by cloud, atmosphere, and ice-snow cover.…”

Section: Ndvi Datamentioning

confidence: 99%

Simulation of the Grazing Effects on Grassland Aboveground Net Primary Production Using DNDC Model Combined with Time-Series Remote Sensing Data—A Case Study in Zoige Plateau, China

Wang

Bian

2016

Remote Sensing

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Abstract:Measuring the impact of livestock grazing on grassland above-ground net primary production (ANPP) is essential for grass yield estimation and pasture management. However, since there is a lack of accurate and repeatable techniques to obtain the details of grazing locations and stocking rates at the regional scale, it is an extremely challenging task to study the influence of regional grazing on the grassland ANPP. Taking Zoige County as a case, this paper proposes an approach to quantify the spatial and temporal variation of grazing intensity and grazing period through time-series remote sensing data, simulated grassland ANPP through the denitrification and decomposition (DNDC) model, and then explores the impact of grazing on grassland ANPP. The result showed that the model-estimated ANPP while considering grazing had a significant relationship with the field-observed ANPP, with the coefficient of determination (R 2 ) of 0.75, root mean square error (RMSE) of 122.86 kgC/ha, and average relative error (RE) of 8.77%. On the contrary, if grazing activity was not considered in simulation, a large uncertainty was found when the model-estimated ANPP was compared with the field observation, showing R 2 of 0.4, RMSE of 211.51 kgC/ha, and average RE of 32.5%. For the whole area of Zoige County in 2012, the statistics of the estimation showed that the total regional ANPP was up to 3.815ˆ10 5 tC, while the total regional ANPP, without considering grazing, would be overestimated by 44.4%, up to 5.51ˆ10 5 tC. This indicates that the grazing parameters derived in this study could effectively improve the accuracy of ANPP simulation results. Therefore, it is feasible to combine time-series remote sensing data with the process model to simulate the grazing effects on grassland ANPP. However, some issues, such as selecting proper remote sensing data, improving the quality of model input parameters, collecting more field data, and exploring the data assimilation approaches, still should be considered in the future work.

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Section: Ndvi Datamentioning

confidence: 99%

Simulation of the Grazing Effects on Grassland Aboveground Net Primary Production Using DNDC Model Combined with Time-Series Remote Sensing Data—A Case Study in Zoige Plateau, China

Wang

Bian

2016

Remote Sensing

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“…Currently, about one half million km 2 of alpine grasslands in the QTP is degraded, and grassland degradation has reduced the productivity of alpine grasslands by approximately 30% over the last 20 yr in the QTP (Cui and Garf , Yu et al. , Dong et al. ).…”

Section: Introductionmentioning

confidence: 99%

Effects of grazing on ecosystem structure and function of alpine grasslands in Qinghai–Tibetan Plateau: a synthesis

et al. 2017

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1656Abstract. Humans have grazed on the Qinghai-Tibetan Plateau (QTP) for many thousands of years. In recent decades, the intensity of grazing has increased and several new management strategies have been put into place to address the resulting changes in rangeland condition. Effective management of grazing activities in this region requires understanding the impact of livestock grazing across the diverse array of alpine grassland ecosystems present in the QTP, but recent studies have identified a number of critical uncertainties in the ecological science that underlies these management principles. To address these uncertainties, we carried out a synthesis analysis of the effect of livestock grazing on 26 indicators of ecosystem structure and function based on 61 studies from 88 independent research sites within the QTP. Our synthesis results indicate that livestock grazing exerts complex controls on ecosystem structure and function, which vary according to local landscape characteristics. We found that grazing contributes to greater plant species diversity (Shannon-Wiener index, Simpson dominance index, and Pielou evenness index significantly increased 0.18, 0.05, and 0.03, respectively, due to grazing), but decreased aboveground biomass (47.15%), soil organic carbon (12.41%), soil total nitrogen (12.75%), and microbial biomass carbon (9.42%). Further, ecosystem function is controlled by interactions between grazing and other landscape characteristics such as elevation and mean annual temperature. The management regime currently in place in the QTP, which involves complete exclusion of grazing in some areas, can have variable effects on grassland health. Therefore, the complexity of these responses is an indication that livestock and grassland management may benefit from a more nuanced management regime than is currently utilized in the QTP.

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“…Three main grassland types exist, namely desert steppe, alpine steppe, and alpine meadow, with coverage from open to dense. Alpine grassland AGB on the Tibetan Plateau was studied by quantifying spatial or temporal distribution from in situ measurements, model simulations, or remote sensing approaches (Luo et al, 2002;Shen et al, 2008;Tan et al, 2010;Yang et al, 2009;Yu, Wang, & Wang, 2010b;Yu, Zhou, Liu, & Zhou, 2010a). Vegetation cover in the large spatial extent of the plateau with various grassland types revealed distinct patterns and temporal changes by remote sensing detection (Meyer et al, 2017;Xu, Chen, & Levy, 2008).…”

Section: Introductionmentioning

confidence: 99%

Relationships between aboveground biomass and plant cover at two spatial scales and their determinants in northern Tibetan grasslands

Jiang

Zhang

et al. 2017

Ecology and Evolution

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The relationships between cover and AGB for the dominant and widely distributed alpine grasslands on the northern Tibetan Plateau is still not fully examined. The objectives of this study are to answer the following question: (1) How does aboveground biomass (AGB) of alpine grassland relate to plant cover at different spatial scales? (2) What are the major biotic and abiotic factors influencing on AGB–cover relationship? A community survey (species, cover, height, and abundance) was conducted within 1 m × 1 m plots in 70 sites along a precipitation gradient of 50–600 m. Ordinary linear regression was employed to examine AGB–cover relationships of both community and species levels at regional scale of entire grassland and landscape scale of alpine meadow, alpine steppe, and desert steppe. Hierarchical partitioning was employed to estimate independent contributions of biotic and abiotic factors to AGB and cover at both scales. Partial correlation analyses were used to discriminate the effects of biotic and abiotic factors on AGB–cover relationships at two spatial scales. AGB and community cover both exponentially increased along the precipitation gradient. At community level, AGB was positively and linearly correlated with cover for all grasslands except for alpine meadow. AGB was also linearly correlated with cover of species level at both regional and landscape scales. Contributions of biotic and abiotic factors to the relationship between AGB and cover significantly depended on spatial scales. Cover of cushions, forbs, legumes and sedges, species richness, MAP, and soil bulk density were important factors that influenced the AGB–cover relationship at either regional or landscape scale. This study indicated generally positive and linear relationships between AGB and cover are at both regional and landscape scales. Spatial scale may affect ranges of cover and modify the contribution of cover to AGB. AGB–cover relationships were influenced mainly by species composition of different functional groups. Therefore, in deriving AGB patterns at different spatial scales, community composition should be considered to obtain acceptable accuracy.

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Using Remote Sensing and GIS Technologies to Estimate Grass Yield and Livestock Carrying Capacity of Alpine Grasslands in Golog Prefecture, China

Cited by 73 publications

References 17 publications

Simulation of the Grazing Effects on Grassland Aboveground Net Primary Production Using DNDC Model Combined with Time-Series Remote Sensing Data—A Case Study in Zoige Plateau, China

Simulation of the Grazing Effects on Grassland Aboveground Net Primary Production Using DNDC Model Combined with Time-Series Remote Sensing Data—A Case Study in Zoige Plateau, China

Effects of grazing on ecosystem structure and function of alpine grasslands in Qinghai–Tibetan Plateau: a synthesis

Relationships between aboveground biomass and plant cover at two spatial scales and their determinants in northern Tibetan grasslands

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