Separation of the Climatic and Land Cover Impacts on the Flow Regime Changes in Two Watersheds of Northeastern Tibetan Plateau

Yang, Linshan; Feng, Qi; Yin, Zhenliang; Deo, Ravinesh C.; Wen, Xin; Si, Jing; Li, Changbin

doi:10.1155/2017/6310401

Cited by 11 publications

(3 citation statements)

References 49 publications

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“…3b). Climate and land cover both influence soil attributes, especially soil moisture and nutrients (Post and Kwon 2000, Teuling et al 2007, Seneviratne et al 2010, Macdonald et al 2012), whereas land cover is intrinsically linked to climate (Thuiller et al 2004, Yang et al 2017). Climate is therefore the main driver responsible for structuring natural habitats and their specific properties such as soil.…”

Section: Discussionmentioning

confidence: 99%

Influence of climate, soil, and land cover on plant species distribution in the European Alps

Chauvier

Thuiller

Brun

et al. 2021

Ecological Monographs

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Although the importance of edaphic factors and habitat structure for plant growth and survival is known, both are often neglected in favor of climatic drivers when investigating the spatial patterns of plant species and diversity. Yet, especially in mountain ecosystems with complex topography, missing edaphic and habitat components may be detrimental for a sound understanding of biodiversity distribution. Here, we compare the relative importance of climate, soil and land cover variables when predicting the distributions of 2,616 vascular plant species in the European Alps, representing approximately two-thirds of all European flora. Using presence-only data, we built point-process models (PPMs) to relate species observations to different combinations of covariates. We evaluated the PPMs through block crossvalidations and assessed the independent contributions of climate, soil, and land cover covariates to predict plant species distributions using an innovative predictive partitioning approach. We found climate to be the most influential driver of spatial patterns in plant species with a relative influence of~58.5% across all species, with decreasing importance from low to high elevations. Soil (~20.1%) and land cover (~21.4%), overall, were less influential than climate, but increased in importance along the elevation gradient. Furthermore, land cover showed strong local effects in lowlands, while the contribution of soil stabilized at mid-elevations. The decreasing influence of climate with elevation is explained by increasing endemism, and the fact that climate becomes more homogeneous as habitat diversity declines at higher altitudes. In contrast, soil predictors were found to follow the opposite trend. Additionally, at low elevations, human-mediated land cover effects appear to reduce the importance of climate predictors. We conclude that soil and land cover are, like climate, principal drivers of plant species distribution in the European Alps. While disentangling their effects remains a challenge, future studies can benefit markedly by including soil and land cover effects when predicting species distributions.

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Section: Discussionmentioning

confidence: 99%

Influence of climate, soil, and land cover on plant species distribution in the European Alps

Chauvier

Thuiller

Brun

et al. 2021

Ecological Monographs

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“…(2019), and Yang et al. (2017). These threshold values could effectively capture the variability of high‐pulse and low‐pulses counts and durations of our flow data.…”

Section: Methodsmentioning

confidence: 98%

Intra‐Annual Variation of High and Low‐Flow Extremes Associated With Land Use and Climate Change in the Upper Tekeze of the Nile River Basin

2022

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In northern Ethiopian highlands, climate variability and land use/land cover (LULC) change has been observed during the past decades. However, it remains unclear that to which extent and how these key drivers contributed to changes in hydrological extremes. As a case study, the respective impacts of LULC change and climate variability on hydrological extremes with respect to magnitude, duration, and frequency metrics were assessed in the Upper Tekeze basin, Ethiopia. A scenario‐based approach using LULC and hydro‐climatological data was developed and five simulation experiments were conducted using Soil and Water Assessment Tool model. Results showed that, during 1986–2015, low‐flow duration has decreased by 5.0 days/yr, and the magnitude and occurrence of high flow has increased by 5.23 m3/s/yr and 5.11 days/yr, respectively. Meanwhile, about 47.42% of the landscape has changed its category while no significant change was detected in annual rainfall during the past 31 yr. Particularly, rocky area increased by 82% which was mostly contributed by losses of bare, sand, and low biomass areas. Significant positive and negative contributions to the changes in high and low‐flow extremes, respectively, were detected from LULC change, while no significant contribution was detected from climate change. The increased rock area tends to be one of the major contributors to the increased high flow while climate change seemed to play a minor role. The potential mechanism is the expansion in rock area increased runoff and high flow, which may lead to significant land deterioration and loss of water storage capacity in the mountainous basin.

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“…Recently, land use and land cover (LULC) change detection and prediction have become popular research topics in the area of remote sensing; thus, these issues have attracted the attention of several researchers and land use planners [1,2]. This is due to the significant effect of LULC changes on altering the hydrological characteristics of basins and watersheds [3,4], climate change [5], and other environmental issues [6]. Globally, different LULC classes of basins and watersheds have undergone considerable changes from one Land 2024, 13, 396 2 of 34 category to another due to increasing anthropogenic activities such as deforestation, agricultural expansion, urbanization, mining, and other related activities [7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Scenario-Based Land Use and Land Cover Change Detection and Prediction Using the Cellular Automata–Markov Model in the Gumara Watershed, Upper Blue Nile Basin, Ethiopia

Belay,

Melesse,

Tegegne

2024

Land

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Land use and land cover (LULC) change detection and prediction studies are crucial for supporting sustainable watershed planning and management. Hence, this study aimed to detect historical LULC changes from 1985 to 2019 and predict future changes for 2035 (near future) and 2065 (far future) in the Gumara watershed, Upper Blue Nile (UBN) Basin, Ethiopia. LULC classification for the years 1985, 2000, 2010, and 2019 was performed using Landsat images along with vegetation indices and topographic factors. The random forest (RF) machine learning algorithm built into the cloud-based platform Google Earth Engine (GEE) was used for classification. The results of the classification accuracy assessment indicated perfect agreement between the classified maps and the validation dataset, with kappa coefficients (K) of 0.92, 0.94, 0.90, and 0.88 for the LULC maps of 1985, 2000, 2010, and 2019, respectively. Based on the classified maps, cultivated land and settlement increased from 58.60 to 83.08% and 0.06 to 0.18%, respectively, from 1985 to 2019 at the expense of decreasing forest, shrubland and grassland. Future LULC prediction was performed using the cellular automata–Markov (CA–Markov) model under (1) the business-as-usual (BAU) scenario, which is based on the current trend of socioeconomic development, and (2) the governance (GOV) scenario, which is based on the Green Legacy Initiative (GLI) program of Ethiopia. Under the BAU scenario, significant expansions of cultivated land and settlement were predicted from 83.08 to 89.01% and 0.18 to 0.83%, respectively, from 2019 to 2065. Conversely, under the GOV scenario, the increase in forest area was predicted to increase from 2.59% (2019) to 4.71% (2065). For this reason, this study recommends following the GOV scenario to prevent flooding and soil degradation in the Gumara watershed. Finally, the results of this study provide information for government policymakers, land use planners, and watershed managers to develop sustainable land use management plans and policies.

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Separation of the Climatic and Land Cover Impacts on the Flow Regime Changes in Two Watersheds of Northeastern Tibetan Plateau

Cited by 11 publications

References 49 publications

Influence of climate, soil, and land cover on plant species distribution in the European Alps

Influence of climate, soil, and land cover on plant species distribution in the European Alps

Intra‐Annual Variation of High and Low‐Flow Extremes Associated With Land Use and Climate Change in the Upper Tekeze of the Nile River Basin

Scenario-Based Land Use and Land Cover Change Detection and Prediction Using the Cellular Automata–Markov Model in the Gumara Watershed, Upper Blue Nile Basin, Ethiopia

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