Quantifying Grazing Intensity Using Remote Sensing in Alpine Meadows on Qinghai-Tibetan Plateau

Ma, Qian; Chai, Linrong; Hou, Fujiang; Chang, Shenghua; Yong, Ma; Tsunekawa, Atsushi; Cheng, Yanjun

doi:10.3390/su11020417

Cited by 33 publications

(40 citation statements)

References 35 publications

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“…Both plant productivity and species diversity will increase under appropriate grazing intensity [5]. However, overgrazing is considered to be the main cause of natural grassland degradation [6]. Parts of grassland ecosystems have degenerated and largely disappeared [7], and the most effective method to improve the ecological conditions in grasslands is to restore the natural vegetation [8].…”

Section: Introductionmentioning

confidence: 99%

Effects of Grazing Exclusion on Biomass Growth and Species Diversity among Various Grassland Types of the Tibetan Plateau

Wang

Fan

et al. 2019

Sustainability

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Livestock grazing is an important determinant of species diversity and plant growth. Overgrazing is identified as one of the most important disturbances resulting in grassland degradation. Although many restoration practices have been implemented, grazing exclusion is one of the most effective methods to restore degraded grasslands. We explored the impact of five years of grazing exclusion on plant growth and species diversity in four types of grasslands: temperate steppe (TS), swamp meadow (SM), alpine steppe (AS), and alpine meadow (AM). Our results showed that grazing exclusion increased plant height, coverage, biomass, and species diversity in all four grasslands. The aboveground biomass in AM (180.8%), TS (117.3%), and SW (105.9%) increased significantly more than AS (10.1%). Grazing exclusion in AM had the greatest effect on proportion of palatable species, and the increase in palatable species in AM was higher than that of the other grassland types significantly. Species diversity increased significantly within the enclosure in SM (23.9%) and AM (20.8%). Our results indicate that grazing exclusion is an effective management strategy to restore degraded grasslands and it works best in alpine meadow. This study contributes to the growing theoretical basis for grassland management strategies and has a significant effect on sustainable development for grassland resources and pastoral areas.

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Section: Introductionmentioning

confidence: 99%

Effects of Grazing Exclusion on Biomass Growth and Species Diversity among Various Grassland Types of the Tibetan Plateau

Wang

Fan

et al. 2019

Sustainability

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“…Moreover, while using GI of three to five dominant species and major accompanying species to predict community AGB, the accuracy and PA of predictive equations were lower than prediction of six representative species ( Table 6 ). Normally, toxic species were dominant in the degraded grassland, which seldomly were ingested by grazing livestock, and overgrazing altered the environmental factors of grassland far severely than proper grazing [ 41 ]. Thereby, predictive equations might need to be modified by the degradation degree of grassland especially under overgrazing, which had took place in about 70% of global grassland in varying degrees [ 42 ].…”

Section: Discussionmentioning

confidence: 99%

Growth Indicators of Main Species Predict Aboveground Biomass of Population and Community on a Typical Steppe

Huang

Liu

Wang

et al. 2020

Plants

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The objective was to explore a fast, accurate, non-destructive, and less disturbance method for predicting the aboveground biomass (AGB) of the typical steppe, by using plant height and canopy diameter of the dominant species, Stipa bungeana, Artemisia capillaris, and Lespedeza davurica, data were observed from 165 quadrats during the peak plant growing season, and the product of plant height (PH) and canopy diameter (PC) were calculated for each species. AGB of population were predicted for the same species and other species through using 2/3 of the measured data, and the optimal predictive equation was linear in terms of determination coefficient. The other 1/3 of the data, which was measured from no grazing paddocks or rotational grazing paddocks, was substituted into the predictive equations for validation. Results showed that PC of one dominant species could be used to predict aboveground biomass (AGB) of the same species or other species well. The predicted and measured values were significantly correlative, and most of the predictive accuracy was above 80%, and not affected by the managements of grassland, grazing or no grazing. A combination of 3 to 6 representative species was used to predict AGB of the community, and the predictive equations with PC of six species as an independent variable were the most optimal because explaining 83.5% variation of AGB. The predictive methods cost 1/15, 1/9, and 1/51 of time, labor, and capital as much as the destructive sample method (quadrat sampling method), respectively, and thus improved the efficiency of field study and protecting the fragile study areas, especially the long-term study sites in grassland.

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“…Studies focusing on grazing intensity patterns used vegetation index time series to conduct trend analyses and extract regional patterns [64,85,166,167]. The grazing intensity was either defined as a proxy, e.g., a vegetation index [64], estimated from biomass information [85,168], approached statistically from livestock census data [147] or was based on field experiments [167,169].…”

Section: Analysis Of Grazing Intensitymentioning

confidence: 99%

“…When grazing intensity was based on livestock data it was usually defined as animal per area [167,169]. In some studies, land allocation algorithms were applied to generate spatial information on livestock densities from lower resolution census data, e.g., [170].…”

Section: Analysis Of Grazing Intensitymentioning

confidence: 99%

Remote Sensing of Grassland Production and Management—A Review

2020

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Grasslands cover one third of the earth’s terrestrial surface and are mainly used for livestock production. The usage type, use intensity and condition of grasslands are often unclear. Remote sensing enables the analysis of grassland production and management on large spatial scales and with high temporal resolution. Despite growing numbers of studies in the field, remote sensing applications in grassland biomes are underrepresented in literature and less streamlined compared to other vegetation types. By reviewing articles within research on satellite-based remote sensing of grassland production traits and management, we describe and evaluate methods and results and reveal spatial and temporal patterns of existing work. In addition, we highlight research gaps and suggest research opportunities. The focus is on managed grasslands and pastures and special emphasize is given to the assessment of studies on grazing intensity and mowing detection based on earth observation data. Grazing and mowing highly influence the production and ecology of grassland and are major grassland management types. In total, 253 research articles were reviewed. The majority of these studies focused on grassland production traits and only 80 articles were about grassland management and use intensity. While the remote sensing-based analysis of grassland production heavily relied on empirical relationships between ground-truth and satellite data or radiation transfer models, the used methods to detect and investigate grassland management differed. In addition, this review identified that studies on grassland production traits with satellite data often lacked including spatial management information into the analyses. Studies focusing on grassland management and use intensity mostly investigated rather small study areas with homogeneous intensity levels among the grassland parcels. Combining grassland production estimations with management information, while accounting for the variability among grasslands, is recommended to facilitate the development of large-scale continuous monitoring and remote sensing grassland products, which have been rare thus far.

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Quantifying Grazing Intensity Using Remote Sensing in Alpine Meadows on Qinghai-Tibetan Plateau

Cited by 33 publications

References 35 publications

Effects of Grazing Exclusion on Biomass Growth and Species Diversity among Various Grassland Types of the Tibetan Plateau

Effects of Grazing Exclusion on Biomass Growth and Species Diversity among Various Grassland Types of the Tibetan Plateau

Growth Indicators of Main Species Predict Aboveground Biomass of Population and Community on a Typical Steppe

Remote Sensing of Grassland Production and Management—A Review

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