scholarly journals Reducing Vulnerability to Desertification by Using the Spatial Measures in a Degraded Area in Thailand

Land ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 49 ◽  
Author(s):  
Saowanee Wijitkosum

The process of desertification is complex, involving interaction between many factors, both environmental and anthropogenic. However, human activities, especially from land-use change and inappropriate land use, are the most influential factors associated with the desertification risk. This study was conducted in Huay Sai, a degraded land in Thailand. The Environmentally Sensitive Area Index (ESAI) model incorporating Geogracphic Information System (GIS) was applied to investigate and map the desertification sensitivity area. The study aimed to analyze and assess measures to reduce the desertification risk. This study emphasized three group factors with nine subcriteria influencing desertification risk: soil (texture, fertility, drainage, slope gradient, and depth), climatic (precipitation and aridity index), and vegetation factors (land use and soil erosion). In terms of the required spatial measures to reduce the desertification vulnerability, policy and defensive measures that were closely related to drought and desertification of the area were considered. Three main measures covering soil and water conservation, soil improvement, and reforestation were implemented. The area development and restoration plans have been implemented continuously. The study found that 47.29% of the Huay Sai area was at a high risk, with a further 41.16% at a moderate risk. Implementation of three measures indicated that desertification risk was significantly decreased. Addressing the causes of the highest risk areas could help reduce the overall desertification risk at Huay Sai, where most areas would then be at either a moderate (61.04%) or low (32.43%) desertification risk with no severe- or high-risk areas. The success of the area restoration is from the formulation of a restoration and development plan that understands the local conditions. Moreover, the plan integrated the restoration of the soil, forests, and water together in order to restore the ecosystem so that the implementation was able to solve problems directly.

2021 ◽  
Vol 13 (10) ◽  
pp. 5366
Author(s):  
Wei Shi ◽  
Fuwei Qiao ◽  
Liang Zhou

With the interaction of global change and human activities, the contradistinction between supply and demand of ecosystem services in the Qinghai-Tibet Plateau is becoming increasingly tense, which will have a profound impact on the ecological security of China and even Asia. Based on land cover data on the Qinghai-Tibet Plateau in 1990, 2005, and 2015, this paper estimated the supply capacity of ecosystem services using the value equivalent method, calculated the demand for ecosystem services using population density and economic density, established an ecosystem risk index based on the idea of an ecosystem service matrix to reveal the spatio-temporal pattern of the supply and demand of ecosystem services in the Qinghai-Tibet Plateau, and identified the potential ecological risk areas arising from the imbalance between supply and demand. The results showed that: (1) In terms of the spatio-temporal pattern of land use change, the desert area of the Qinghai-Tibet Plateau decreased the most with 26,238.9 km2, and other types of land use increased, of which construction land increased by 131.7%; (2) In terms of the supply and demand of ecosystem services, the Qinghai-Tibet Plateau was mainly dominated by low-level surplus areas, accounting for 64.0%, and the deficit in some areas has worsened significantly; and (3) In terms of division pattern of ecological risk areas, the Qinghai-Tibet Plateau presented characteristics of high risk in the east and low risk in the west. The high-risk area accounted for 1.1%, mainly distributed in the Huangshui Valley and the “One River and Two Tributaries” (Yarlung Zangbo River, Lhasa River, Nianchu River). The research results can provide reference for ecosystem management and policy formulation of the Qinghai-Tibet Plateau and have important significance for realizing the coupling and coordinated development of human–land relationship in Qinghai-Tibet Plateau.


2021 ◽  
Author(s):  
Feifei Zhang ◽  
Margo Chase-Topping ◽  
Chuan-Guo Guo ◽  
Mark Woolhouse

Background: The variation in the pathogen type as well as the spatial heterogeneity of predictors make the generality of any associations with pathogen discovery debatable. Our previous work confirmed that the association of a group of predictors differed across different types of RNA viruses, yet there have been no previous comparisons of the specific predictors for RNA virus discovery in different regions. The aim of the current study was to close the gap by investigating whether predictors of discovery rates within three regions—the United States, China and Africa—differ from one another and from those at the global level. Methods: Based on a comprehensive list of human-infective RNA viruses, we collated published data on first discovery of each species in each region. We used a Poisson boosted regression tree (BRT) model to examine the relationship between virus discovery and 33 predictors representing climate, socio-economics, land use, and biodiversity across each region separately. The discovery probability in three regions in 2010–2019 was mapped using the fitted models and historical predictors. Results: The numbers of human-infective virus species discovered in the United States, China and Africa up to 2019 were 95, 80 and 107 respectively, with China lagging behind the other two regions. In each region, discoveries were clustered in hotspots. BRT modelling suggested that in all three regions RNA virus discovery was best predicted by land use and socio-economic variables, followed by climatic variables and biodiversity, though the relative importance of these predictors varied by region. Map of virus discovery probability in 2010–2019 indicated several new hotspots outside historical high-risk areas. Most new virus species since 2010 in each region (6/6 in the United States, 19/19 in China, 12/19 in Africa) were discovered in high risk areas as predicted by our model. Conclusions: The drivers of spatiotemporal variation in virus discovery rates vary in different regions of the world. Within regions virus discovery is driven mainly by land-use and socio-economic variables; climate and biodiversity variables are consistently less important predictors than at a global scale. Potential new discovery hotspots in 2010–2019 are identified. Results from the study could guide active surveillance for new human-infective viruses in local high risk areas.


Author(s):  
S Vongtanaboon ◽  
W Hancharoen ◽  
S Homya

The objectives of this research were to evaluate risk factors and assess flood risk areas, including analyzing guidelines for flood risk area management in Patong Municipality, Kathu District, Phuket Province. Factors affecting flood were rainfall, slope gradient, soil permeability, land use, and water barrier. Weighting factors and rating factors were indicated and geographic information system for potential surface analysis and overlay analysis were applied. The results revealed that Patong Municipality had high risk area as 2.17 km2 (11.39%). Flood risk area for moderate level accounted for 4.00 km2 (20.99%) and low flood risk area accounted for 12.89 km2 (67.62%). Guidelines for flood risk area management in Patong Municipality should focus on the principles of soil and water conservation, forest restoration and preservation in the upstream area, flow path and stream are management, land use management, ground cover planting to prevent soil erosion and maintain soil moisture.


2019 ◽  
Vol 31 (1) ◽  
Author(s):  
Stefan Nickel ◽  
Winfried Schröder

Abstract Background The aim of the study was a statistical evaluation of the statistical relevance of potentially explanatory variables (atmospheric deposition, meteorology, geology, soil, topography, sampling, vegetation structure, land-use density, population density, potential emission sources) correlated with the content of 12 heavy metals and nitrogen in mosses collected from 400 sites across Germany in 2015. Beyond correlation analysis, regression analysis was performed using two methods: random forest regression and multiple linear regression in connection with commonality analysis. Results The strongest predictor for the content of Cd, Cu, Ni, Pb, Zn and N in mosses was the sampled species. In 2015, the atmospheric deposition showed a lower predictive power compared to earlier campaigns. The mean precipitation (2013–2015) is a significant factor influencing the content of Cd, Pb and Zn in moss samples. Altitude (Cu, Hg and Ni) and slope (Cd) are the strongest topographical predictors. With regard to 14 vegetation structure measures studied, the distance to adjacent tree stands is the strongest predictor (Cd, Cu, Hg, Zn, N), followed by the tree layer height (Cd, Hg, Pb, N), the leaf area index (Cd, N, Zn), and finally the coverage of the tree layer (Ni, Cd, Hg). For forests, the spatial density in radii 100–300 km predominates as significant predictors for Cu, Hg, Ni and N. For the urban areas, there are element-specific different radii between 25 and 300 km (Cd, Cu, Ni, Pb, N) and for agricultural areas usually radii between 50 and 300 km, in which the respective land use is correlated with the element contents. The population density in the 50 and 100 km radius is a variable with high explanatory power for all elements except Hg and N. Conclusions For Europe-wide analyses, the population density and the proportion of different land-use classes up to 300 km around the moss sampling sites are recommended.


2021 ◽  
Vol 13 (2) ◽  
pp. 826
Author(s):  
Meiling Zhou ◽  
Xiuli Feng ◽  
Kaikai Liu ◽  
Chi Zhang ◽  
Lijian Xie ◽  
...  

Influenced by climate change, extreme weather events occur frequently, and bring huge impacts to urban areas, including urban waterlogging. Conducting risk assessments of urban waterlogging is a critical step to diagnose problems, improve infrastructure and achieve sustainable development facing extreme weathers. This study takes Ningbo, a typical coastal city in the Yangtze River Delta, as an example to conduct a risk assessment of urban waterlogging with high-resolution remote sensing images and high-precision digital elevation models to further analyze the spatial distribution characteristics of waterlogging risk. Results indicate that waterlogging risk in the city proper of Ningbo is mainly low risk, accounting for 36.9%. The higher-risk and medium-risk areas have the same proportions, accounting for 18.7%. They are followed by the lower-risk and high-risk areas, accounting for 15.5% and 9.6%, respectively. In terms of space, waterlogging risk in the city proper of Ningbo is high in the south and low in the north. The high-risk area is mainly located to the west of Jiangdong district and the middle of Haishu district. The low-risk area is mainly distributed in the north of Jiangbei district. These results are consistent with the historical situation of waterlogging in Ningbo, which prove the effectiveness of the risk assessment model and provide an important reference for the government to prevent and mitigate waterlogging. The optimized risk assessment model is also of importance for waterlogging risk assessments in coastal cities. Based on this model, the waterlogging risk of coastal cities can be quickly assessed, combining with local characteristics, which will help improve the city’s capability of responding to waterlogging disasters and reduce socio-economic loss.


2020 ◽  
Vol 12 (1) ◽  
pp. 1497-1511
Author(s):  
Alexey Naumov ◽  
Varvara Akimova ◽  
Daria Sidorova ◽  
Mikhail Topnikov

AbstractDespite harsh climate, agriculture on the northern margins of Russia still remains the backbone of food security. Historically, in both regions studied in this article – the Republic of Karelia and the Republic of Sakha (Yakutia) – agricultural activities as dairy farming and even cropping were well adapted to local conditions including traditional activities such as horse breeding typical for Yakutia. Using three different sources of information – official statistics, expert interviews, and field observations – allowed us to draw a conclusion that there are both similarities and differences in agricultural development and land use of these two studied regions. The differences arise from agro-climate conditions, settlement history, specialization, and spatial pattern of economy. In both regions, farming is concentrated within the areas with most suitable natural conditions. Yet, even there, agricultural land use is shrinking, especially in Karelia. Both regions are prone to being affected by seasonality, but vary in the degree of its influence. Geographical location plays special role, and weaknesses caused by remoteness to some extent become advantage as in Yakutia. Proximity effect is controversial. In Karelia, impact of neighboring Finland is insignificant compared with the nearby second Russian city – Saint Petersburg.


Author(s):  
Hui Wei ◽  
Wenwu Zhao ◽  
Han Wang

Large-scale vegetation restoration greatly changed the soil erosion environment in the Loess Plateau since the implementation of the “Grain for Green Project” (GGP) in 1999. Evaluating the effects of vegetation restoration on soil erosion is significant to local soil and water conservation and vegetation construction. Taking the Ansai Watershed as the case area, this study calculated the soil erosion modulus from 2000 to 2015 under the initial and current scenarios of vegetation restoration, using the Chinese Soil Loess Equation (CSLE), based on rainfall and soil data, remote sensing images and socio-economic data. The effect of vegetation restoration on soil erosion was evaluated by comparing the average annual soil erosion modulus under two scenarios among 16 years. The results showed: (1) vegetation restoration significantly changed the local land use, characterized by the conversion of farmland to grassland, arboreal land, and shrub land. From 2000 to 2015, the area of arboreal land, shrub land, and grassland increased from 19.46 km2, 19.43 km2, and 719.49 km2 to 99.26 km2, 75.97 km2, and 1084.24 km2; while the farmland area decreased from 547.90 km2 to 34.35 km2; (2) the average annual soil erosion modulus from 2000 to 2015 under the initial and current scenarios of vegetation restoration was 114.44 t/(hm²·a) and 78.42 t/(hm²·a), respectively, with an average annual reduction of 4.81 × 106 t of soil erosion amount thanks to the vegetation restoration; (3) the dominant soil erosion intensity changed from “severe and light erosion” to “moderate and light erosion”, vegetation restoration greatly improved the soil erosion environment in the study area; (4) areas with increased erosion and decreased erosion were alternately distributed, accounting for 48% and 52% of the total land area, and mainly distributed in the northwest and southeast of the watershed, respectively. Irrational land use changes in local areas (such as the conversion of farmland and grassland into construction land, etc.) and the ineffective implementation of vegetation restoration are the main reasons leading to the existence of areas with increased erosion.


2020 ◽  
Vol 13 (1) ◽  
pp. 22
Author(s):  
Tianshi Pan ◽  
Lijun Zuo ◽  
Zengxiang Zhang ◽  
Xiaoli Zhao ◽  
Feifei Sun ◽  
...  

The implementation of ecological projects can largely change regional land use patterns, in turn altering the local hydrological process. Articulating these changes and their effects on ecosystem services, such as water conservation, is critical to understanding the impacts of land use activities and in directing future land planning toward regional sustainable development. Taking Zhangjiakou City of the Yongding River as the study area—a region with implementation of various ecological projects—the impact of land use changes on various hydrological components and water conservation capacity from 2000 to 2015 was simulated based on a soil and water assessment tool model (SWAT). An empirical regression model based on partial least squares was established to explore the contribution of different land use changes on water conservation. With special focus on the forest having the most complex effects on the hydrological process, the impacts of forest type and age on the water conservation capacity are discussed on different scales. Results show that between 2000 and 2015, the area of forest, grassland and cultivated land decreased by 0.05%, 0.98% and 1.64%, respectively, which reduces the regional evapotranspiration (0.48%) and soil water content (0.72%). The increase in settlement area (42.23%) is the main reason for the increase in water yield (14.52%). Most land use covered by vegetation has strong water conservation capacity, and the water conservation capacity of the forest is particularly outstanding. Farmland and settlements tend to have a negative effect on water conservation. The water conservation capacity of forest at all scales decreased significantly with the growth of forest (p < 0.05), while the water conservation capacity of different tree species had no significant difference. For the study area, increasing the forest area will be an effective way to improve the water conservation function, planting evergreen conifers can rapidly improve the regional water conservation capacity, while planting deciduous conifers is of great benefit to long-term sustainable development.


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