Search

The Ebinur Lake Basin is an ecologically sensitive area in an arid region. Investigating its land use and land cover (LULC) change and assessing and predicting its ecosystem service value (ESV) are of great importance for the stability of the basin's socioeconomic development and sustainable development of its ecological environment. Based on LULC data from 1990, 2000, 2010, and 2020, we assessed the ESV of the Ebinur Lake Basin and coupled the grey multi-objective optimization model with the patch generation land use simulation model to predict ESV changes in 2035 under four scenarios: business-as-usual (BAU) development, rapid economic development (RED), ecological protection (ELP), and ecological–economic balance (EEB). The results show that from 1990 to 2020, the basin was dominated by grassland (51.23%) and unused land (27.6%), with a continuous decrease in unused land and an increase in cultivated land. In thirty years, the total ESV of the study area increased from 18.62 billion to 67.28 billion yuan, with regulation and support services being the dominant functions. By 2035, cultivated land increased while unused land decreased in all four scenarios compared with that in 2020. The total ESV in 2035 under the BAU, RED, ELP, and EEB scenarios was 68.83 billion, 64.47 billion, 67.99 billion, and 66.79 billion yuan, respectively. In the RED and EEB scenarios, ESV decreased by 2.81 billion and 0.49 billion yuan, respectively. In the BAU scenario, provisioning and regulation services increased by 6.05% and 2.93%, respectively. The ELP scenario, focusing on ecological and environmental protection, saw an increase in ESV for all services. This paper can assist policymakers in optimizing land use allocation and provide scientific support for the formulation of land use strategies and sustainable ecological and environmental development in the inland river basins of arid regions. [ABSTRACT FROM AUTHOR]

The land in the South Tasikmalaya Regency is dominated by dry land with a steep and hilly land contour. In addition, the area has a shallow soil solum, so it has a high potential for erosion and landslides. Therefore, it is necessary to innovate an integrated cultivation system that is economically feasible, but still maintains environmental sustainability. In this research, the aim is to formulate a model for the development of integrated plantation polyculture farming (IPPF) for the welfare of farmers. The method in this study uses a mixed method design. The location of the research carried out is in the Tasikmalaya Regency. The data used are the results of interviews and questionnaires to 250 IPPF farmers. The data used were obtained by multistage cluster random sampling. The sustainable IPPF development model was analysed using Structural Equation Modelling (SEM). This analysis is used to determine the various potential capital factors for agricultural development on the sustainable development of the IPPF and farmers' welfare. The results of the study show that the potential development capital [natural resources (SDA) capital, economic capital, socio-cultural capital, physical capital, and multifunctional IPPF], jointly or partially affect the IPPF sustainability. Human resource capital has no effect on the sustainable IPPF development, while the sustainable IPPF development affects the farmers' welfare levels, and the potential agricultural development capital and its multifunctionality affect the sustainable IPPF development and farmers' welfare. The IPPF development model that improves the welfare of farmers is carried out through the development of specific local superior commodities, increasing the added value and cooperation, developing access to credit, regenerating farmers, sustainable assistance and infrastructure improvements. The results of this study are expected to be a reference for the government in improving IPPF sustainability to achieve the welfare of its farmers. Apart from that, the model that has been developed can make a contribution to science in the form of a comprehensive analysis of the factors that influence the sustainability of IPPF. [ABSTRACT FROM AUTHOR]

• The runoff, sediment load and runoff erosion power decreased significantly. • Compared with runoff, runoff erosion power-sediment relationship is better. • The power function of runoff erosion power and sediment is better than linear. • Erosion in particular geographic locations responds strongly to runoff erosion power. In recent years, the acceleration of urbanization in the Yangtze River Economic Belt (YREB) has brought about problems such as soil erosion, ecosystem degradation and decline in ecological service functions. Therefore, this paper selects the Fujiang River Basin (FRB) in Upper Yangtze River (UYR), and analyzes the relationship between runoff erosion power (REP) and sediment transport (ST) on the basis of analyzing the variation characteristics of hydrological elements. Based on SWAT model, a variety of scenarios are set up to quantitatively analyze the impact of different land use changes on runoff and ST and REP in the basin. The results indicated that: (1) The annual precipitation in FRB from 1960 to 2018 did not change significantly, while the annual runoff, annual ST and annual REP decreased significantly. Compared with runoff and runoff depth, the relationship between sediment transport modulus (STM) and REP is the best, especially the power function between them is better than the linear function. (2) The results of the evaluation indexes of the simulation results of the SWAT model based on the measured runoff and sediment data from 2008 to 2018 are pass and above, that is, the simulation results are considered reliable. (3) Under the five scenarios of conversion of sloping farmland to forest, conversion of dry land to paddy field and conversion of grassland to bushland and forest land, the runoff and ST in the basin decreased but the overall range was small. The simulation results of SWAT model show that the erosion of specific areas in the basin shows the greatest degree of weakening with the decrease of REP. [ABSTRACT FROM AUTHOR]

This study aims to integrate driver variables with a land use change model (LCM) to explore their impact on the natural environment within the context of land-use changes in the Republic of Djibouti, considering possible Business-as-usual scenarios. Secondary data from 1990 and 2012 on land use land cover (LULC) were analyzed, with a 2022 map generated by adopting the same method of secondary data used (random forest classification in Google Earth Engine (GEE)) for validation. Eight key driver variables were utilized to model plausible future land cover (2035) for Djibouti. Statistical outputs and change maps from the LCM were compared to gauge historical change estimates and simulated scenarios. Analysis from 1990 to 2022 highlights significant land use and cover changes spurred by urbanization, environmental factors, and economic development. Barren land and bushland dominated, while built-up areas and water bodies expanded notably. Urbanization, agriculture, and climate change contributed to vegetation degradation, with declines in mangroves and increases in built-up areas. Water bodies also expanded during this period. Projections from the 2035 LULC map anticipate further urban expansion, underscoring the need for sustainable land management practices. In conclusion, comprehensive land-use planning, interdisciplinary approaches, and stakeholder engagement are deemed critical for addressing Djibouti's socio-economic and environmental challenges and steering towards a sustainable future. These simulated results offer valuable insights for regional governments to frame strategic policies and assess management actions for resource utilization amidst urbanization and population growth trends. [ABSTRACT FROM AUTHOR]

The effects of global climate change and human activities are anticipated to significantly impact ecosystem services (ESs), particularly in urban agglomerations of arid regions. This paper proposes a framework integrating the dynamic Bayesian network (DBN), system dynamics (SD) model, patch generation land use simulation (PLUS) model, and the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model for predicting land use change and optimizing ESs spatial patterns that is built upon the SSP-RCP scenarios from CMIP6. This framework is applied to the oasis urban agglomeration on the northern slope of the Tianshan Mountains in Xinjiang (UANSTM), China. The findings indicate that both the SD model and PLUS model can accurately forecast the distribution of future land use. The SD model shows a relative error of less than 2.32%, while the PLUS model demonstrates a Kappa coefficient of 0.89. The land use pattern displays obvious spatial heterogeneity under different climate scenarios. The expansion of cultivated land and construction land is the main form of land use change in UANSTM in the future. The DBN model proficiently simulates the interactive relationships between ESs and diverse factors. The classification error rates for net primary productivity (NPP), habitat quality (HQ), water yield (WY), and soil retention (SR) are 20.04%, 3.47%, 4.45%, and 13.42%, respectively. The prediction and diagnosis of DBN determine the optimal ESs development scenario and the optimal ESs region in the study area. It is found that the majority of ESs in UANSTM are predominantly influenced by natural factors with the exception of HQ. The socio-economic development plays a minor role in such urban agglomerations. This study offers significant insights that can contribute to the fields of ecological protection and land use planning in arid urban agglomerations worldwide. • An integrated framework combining DBN, SD, PLUS and InVEST models was proposed. • Impact of natural and socioeconomic factors on ESs was determined under climate scenarios. • The spatial pattern of ESs was optimized and partitioned using DBNs. • ESs in arid oasis urban agglomerations are mainly affected by natural factors. [ABSTRACT FROM AUTHOR]