Hydrological Effects of Vegetation Cover Degradation and Environmental Implications in a Semiarid Temperate Steppe, China

Sun, Lei; Yang, Li-Zhe; Hao, Lu; Fang, Di; Jin, Kailun; Huang, Xiaolin

doi:10.3390/su9020281

Cited by 20 publications

(10 citation statements)

References 35 publications

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“…Previous studies also indicated that overgrazing has been present in the Xilin river basin for a long time, triggering a series of ecological problems, including serious grassland degradation [23,48,55]. This was also confirmed in the BLR model, which presented a significant and positive coefficient in the fit BLR function, suggesting that higher grazing intensity led to a greater likeliness of vegetation degradation.…”

Section: Discussionsupporting

confidence: 57%

Comparison of Modeling Grassland Degradation with and without Considering Localized Spatial Associations in Vegetation Changing Patterns

Wang

Li³

et al. 2018

Sustainability

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Abstract:Grassland ecosystems worldwide are confronted with degradation. It is of great importance to understand long-term trajectory patterns of grassland vegetation by advanced analytical models. This study proposes a new approach called a binary logistic regression model with neighborhood interactions, or BLR-NIs, which is based on binary logistic regression (BLR), but fully considers the spatio-temporally localized spatial associations or characterization of neighborhood interactions (NIs) in the patterns of grassland vegetation. The BLR-NIs model was applied to a modeled vegetation degradation of grasslands in the Xilin river basin, Inner Mongolia, China. Residual trend analysis on the normalized difference vegetation index (RESTREND-NDVI), which excluded the climatic impact on vegetation dynamics, was adopted as a preprocessing step to derive three human-induced trajectory patterns (vegetation degradation, vegetation recovery, and no significant change in vegetation) during two consecutive periods, T 1 (2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008) and T 2 (2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015). Human activities, including livestock grazing intensity and transportation accessibility measured by road network density, were included as explanatory variables for vegetation degradation, which was defined for locations if vegetation recovery or no significant change in vegetation in T 1 and vegetation degradation in T 2 were observed. Our work compared the results of BLR-NIs and the traditional BLR model that did not consider NIs. The study showed that: (1) both grazing intensity and road density had a positive correlation to vegetation degradation based on the traditional BLR model; (2) only road density was found to positively correlate to vegetation degradation by the BLR-NIs model; NIs appeared to be critical factors to predict vegetation degradation; and (3) including NIs in the BLR model improved the model performance substantially. The study provided evidence for the importance of including localized spatial associations between the trajectory patterns for mapping vegetation degradation, which has practical implications for designing management policies to counterpart grassland degradation in arid and semi-arid areas.

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Section: Discussionsupporting

confidence: 57%

Comparison of Modeling Grassland Degradation with and without Considering Localized Spatial Associations in Vegetation Changing Patterns

Wang

Li³

et al. 2018

Sustainability

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“…The area is semi-arid and falls under Agro-Ecological Region 5; hence it has low agriculture potential (Chikodzi et al, 2013). However, the study area is of ecological importance, with vital wildlife corridors (Tchakatumba et al, 2019). Figure 1 shows the study area, highlighting the key settlements, rivers and ward boundaries in the southern part of Beitbridge District, Zimbabwe.…”

Section: Description Of the Study Areamentioning

confidence: 99%

“…This is confirmed by the participatory land-use plan regarding the Shashe study area prepared by Murwira et al (2006). Land cover such as vegetation, permanent grasslands and plantations restrains the surface runoff, hence reducing the chance of flooding (Sun et al, 2017). However, land-cover types such as buildings, roads, and informal settlements decrease the penetration capacity of the soil and increase the water runoff, which enhances flooding (Ouma and Tateishi, 2014).…”

Section: Land Use and Land Covermentioning

confidence: 99%

Modelling flood hazard in dry climates of southern Africa: a case of Beitbridge, Limpopo Basin, Zimbabwe

Chikwiramakomo

Gumindoga

Shekede

et al. 2021

WSA

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Floods are among the natural hazards that have adverse effects on human lives, livelihoods, economies and infrastructure. Dry climates of southern Africa have, over the years, experienced an increase in the frequency of tropical cyclone induced floods. However, understanding the key factors that influence susceptibility to floods has remained largely unexplored in these dry climates. Therefore, this study sought to model flood hazards and determine key factors that significantly explain the probability of flood occurrence in the southern parts of Beitbridge District, Zimbabwe. To achieve these objectives, logistic regression was used to predict spatial variations in flood hazards following cyclone Dineo in 2017. Before spatial prediction of flood hazard, environmental variables were tested for multicollinearity using the Pearson correlation coefficient. Only two environmental variables, i.e., elevation and rainfall, were not significantly correlated and were thus used in the subsequent flood hazard modelling. Results demonstrate that two variables significantly (p < 0.05) predicted spatial variations in flood hazard in the southern parts of the Beitbridge District with relatively high accuracy defined by the area under the curve (AUC = 0.98). In addition, results indicate that ~56 % of the study area is regarded as highly susceptible to floods. Given the projected increase in extreme events such as intense rainfall as a result of climate change, floods will be expected to correspondingly increase in these semi-arid regions. Results presented in this study underscore the importance of geospatial techniques in flood-hazard modelling, which is the key input in sustainable land-use planning. It can thus be concluded that spatial analytical techniques play a key role in flood early warning systems aimed at supporting and building resilient communities in the face of climate change–induced floods.

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“…The degradation of grasslands increases evaporation rates [85,86] and surface runoff [83,87], reducing soil-water infiltration capacity [67,83,84]. This in turn reduces the effective soil water content [43] and increases soil loss due to erosion [88], leading to greater risks of degradation [89]. This process is highly relevant in semiarid regions, where plant and litter cover are scare per se.…”

Section: Water Cyclementioning

confidence: 99%

Drivers, Process, and Consequences of Native Grassland Degradation: Insights from a Literature Review and a Survey in Río de la Plata Grasslands

2019

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Natural grasslands are being progressively degraded around the world due to human-induced action (e.g., overgrazing), but there is neither a widely accepted conceptual framework to approach degradation studies nor a clear definition of what “grassland degradation” is. Most of the drivers, processes, and consequences related to grassland degradation are widespread and are usually separately quoted in the literature. In this paper, we propose a comprehensive framework with different conceptual categories, for monitoring grassland degradation, and a new definition based on current ones. We provide a conceptual update of grassland degradation based on a literature review and an expert survey, focused on the Río de la Plata grasslands (RPG). We identified “drivers” as external forces or changes that cause degradation; “processes” as measurable changes in grasslands conditions that can be evaluated using indicators; and “consequences” as the impacts or results of the process of grassland degradation. We expect that this conceptual framework will contribute to monitoring programs, to support management decisions, to design conservation measures, and to communicate the importance of grasslands conservation and the different concepts involved. Particularly for RPG, we expect that this paper will contribute to promote sustainable management practices in this important and often neglected ecosystem.

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Hydrological Effects of Vegetation Cover Degradation and Environmental Implications in a Semiarid Temperate Steppe, China

Cited by 20 publications

References 35 publications

Comparison of Modeling Grassland Degradation with and without Considering Localized Spatial Associations in Vegetation Changing Patterns

Comparison of Modeling Grassland Degradation with and without Considering Localized Spatial Associations in Vegetation Changing Patterns

Modelling flood hazard in dry climates of southern Africa: a case of Beitbridge, Limpopo Basin, Zimbabwe

Drivers, Process, and Consequences of Native Grassland Degradation: Insights from a Literature Review and a Survey in Río de la Plata Grasslands

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