Overgrazing leads to soil cracking that later triggers the severe degradation of alpine meadows on the Tibetan Plateau

Niu, Yujie; Zhu, Huimin; Yang, Siwei; Ma, Shaolin; Zhou, Jianwei; Chu, Bin; Hua, Rui; Hua, Limin

doi:10.1002/ldr.3312

Cited by 59 publications

(31 citation statements)

References 27 publications

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“…Livestock traffic along roadsides has destroyed much of these rangeland areas. Increased grazing intensity and greater rangeland pressure reduce the quality of vegetation quality, causing the more palatable species to decrease and possibly disappear (Beygi Heidarlou et al, 2019; Niu et al, 2019). Greater movement and more grazing can reduce water infiltration, thus increasing runoff during rainfall events, which leads to increased soil erosion (Geerken & Ilaiwi, 2004; Kumar et al, 2019; Manzano, Návar, Pando‐Moreno, & Martínez, 2000; Shaoliang et al, 2007; Vargas‐Pineda, Trujillo‐González, & Torres‐Mora, 2020; Wilcox, Rawls, Brakensiek, & Wight, 1990).…”

Section: Discussionmentioning

confidence: 99%

“…Consequently, the number of inedible plants increases as range quality decreases. Overgrazing has other negative effects on environmental ecosystems (Mohammad & Adam, 2010; van Oudenhoven, Veerkamp, Alkemade, & Leemans, 2015) like soil degradation (Manzano et al, 2000; Papanastasis, Kyriakakis, Kazakis, Abid, & Doulis, 2003), and rising runoff rates (Mohammad & Adam, 2010; Niu et al, 2019). Overgrazing is one of the most important causes of rangeland degradation.…”

Section: Discussionmentioning

confidence: 99%

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Assessment of land degradation using machine‐learning techniques: A case of declining rangelands

et al. 2020

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Increased use and increasing demands pose serious threats to rangelands. In this study, we document a pronounced downward trend in rangeland quality in the Alborz Mountains in Firozkuh County, Iran using analysis of three machine‐learning models (MLMs). A total of 1,147 transects were established to evaluate the rangeland quality trends from field data collected over a 7‐year period. Twelve independent conditional factors were analyzed for their relationships to range quality through three MLMs—Random Forest (RF), classification and regression tree (CART), and support vector machine (SVM). Based on assessments of the trained and validated models, RF, with a ROC‐AUC = 0.96, was determined to be the most robust. The results show that about 20% of the rangeland in the study area is in a critically degraded condition. Distances from roads and livestock density are the two factors most strongly linked to degradation. These results, in combination with field observations, indicate that the rangelands of the study area face two major challenges (overgrazing and early grazing) that require new strategies to mitigate and prevent damages. This study may provide important guidance for evaluating rangeland conditions in other regions of the world.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Assessment of land degradation using machine‐learning techniques: A case of declining rangelands

et al. 2020

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“…According to their data, they hypothesized a degradation trajectory of an alpine rangeland based on the cracking phenomenon induced by overgrazing. The first three stages and the last two were isolated in their hypothesis, and can be found in the figure legend in Figure 9 of their paper (Niu et al, 2019). The main result of this paper is that cracks were found in grassland under the conditions of overgrazing (Niu et al, 2019).…”

mentioning

confidence: 73%

“…The first three stages and the last two were isolated in their hypothesis, and can be found in the figure legend in Figure 9 of their paper (Niu et al, 2019). The main result of this paper is that cracks were found in grassland under the conditions of overgrazing (Niu et al, 2019). The cracks became larger in cold season, became smaller in the plant growth season, and were a process of circulation of bigger and smaller (Niu et al, 2019).…”

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confidence: 79%

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The hypothetical degradation trajectory in ‘Overgrazing leads to soil cracking that later triggers the severe degradation of alpine meadows on the Tibetan Plateau’ was not precisely right

Li¹

2020

Preprint

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Characterization of the spatial distribution of plateau pika burrows along an alpine grassland degradation gradient on the Qinghai–Tibet Plateau

Qian

Fan

et al. 2021

Ecology and Evolution

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Plateau pika burrows are common feature of degraded grassland in the Qinghai–Tibet Plateau (QTP) and serve as an important indicator of pika activity and grassland degradation. However, the current understanding of the spatial pattern changes of pika burrows and their critical thresholds across a degradation gradient in alpine grassland is deficient. In this study, we investigated and quantified changes in the spatial pattern of plateau pika burrows under typical degraded alpine shrub meadows in the northeastern QTP using an unmanned aerial vehicle and landscape pattern metrics. The degradation of the alpine shrub meadow leads to a change in landscape pattern from a two‐layered structure of alpine shrub and alpine meadow to a mosaic of alpine meadow and bare soil, with plateau pika burrows scattered throughout. Moderate degradation is the tipping point for changes in surface landscape patterns, followed by the disappearance of alpine shrub, the retreat of alpine meadows and the encroachment of bare soil, and the increasing density and size of pika burrows. The area characteristics of alpine meadows have influenced changes in the spatial pattern of pika burrow, and maintaining its proportional area is a vital measure to control the threat of pika burrows to pastures. The results of this paper provide a methodological reference and guidance for the sustainable utilization of grassland on the QTP.

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Overgrazing leads to soil cracking that later triggers the severe degradation of alpine meadows on the Tibetan Plateau

Cited by 59 publications

References 27 publications

Assessment of land degradation using machine‐learning techniques: A case of declining rangelands

Assessment of land degradation using machine‐learning techniques: A case of declining rangelands

The hypothetical degradation trajectory in ‘Overgrazing leads to soil cracking that later triggers the severe degradation of alpine meadows on the Tibetan Plateau’ was not precisely right

Characterization of the spatial distribution of plateau pika burrows along an alpine grassland degradation gradient on the Qinghai–Tibet Plateau

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