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Over the past decades, the drylands of the Yellow River Basin (YRBD) have undergone profound changes in landscape patterns and ecological dynamics, significantly impacting regional sustainable development. To assess the spatio-temporal variations of ecological risk in the YRBD and provide guidance for sustainable regional development, we constructed a coupled Land Use-Landscape Ecological Risk Model-Geographical Detector-PLUS framework for the assessment, analysis, and simulation of dryland landscape ecological risk (LER). The main findings are as follows: (1) Between 2000 and 2020, the area of built-up land, forest, grassland, and water in the YRBD increased, while the area of unused land and cropland decreased. (2) LER exhibited significant spatial heterogeneity, dominated by Sub-low and Low risks. High risk areas were primarily located in the western Inner Mongolia Plateau, whereas Low risk areas were prevalent in the Loess Plateau, with an overall decline in risk levels over the 20 years. (3) Water resources, ecological status, and human activities are the main driving factors affecting LER, with the impact of human activities becoming increasingly significant over the past 20 years. (4) Under three development scenarios in 2030, the LER is projected to further decrease, although the impact of these scenarios varies across different research sub-regions. Notably, the Ecological Priority Scenario emerges as more effective in mitigating regional LER. (5) Developing precise land use policies tailored to regional characteristics, continuously implementing ecological restoration projects, strengthening water resource management, and enhancing monitoring capabilities are effective ways to reduce LER in the YRBD. This study systematically quantified the impact of different development scenarios on LER in the YRBD, revealing its spatio-temporal characteristics, and emphasized the importance of planning guidance, ecological restoration, and risk monitoring to align regional development with ecological protection. The findings provide scientific evidence for ecological protection and sustainable development in the YRBD and other drylands, offering valuable insights for global dryland ecological risk management. [ABSTRACT FROM AUTHOR]

The carbon storage capacity of terrestrial ecosystems serves as a crucial metric for assessing ecosystem health and their resilience to climate change. By evaluating the effects of land use alterations on this storage, carbon management strategies can be improved, thereby promoting carbon reduction and sequestration. While county-level cities are pivotal to ecological conservation and high-quality development, they often face developmental challenges. Striking a balance between economic growth and meeting peak carbon emissions and carbon neutrality objectives is particularly challenging. Consequently, there is an urgent need to bolster research into carbon storage management. The study focuses on Jianli City, employing the InVEST model and land use data to examine the response patterns of land use changes and terrestrial system carbon storage from 2000 to 2020. Using the PLUS model, the study simulated the land use and carbon storage in Jianli City for the year 2035 under three scenarios: Natural Development scenario, Urban Expansion scenario, and Ecology and food security scenario. Our findings indicate the following: (1) Between 2000 and 2020, significant shifts in land use were observed in Jianli City. These changes predominantly manifested as the interchange between Cropland and Water areas and the enlargement of impervious surfaces, leading to a decrease of 691,790.27 Mg in carbon storage. (2) Under the proposed scenarios—Natural Development scenario, Urban Expansion scenario, and Ecology and food security scenario—the estimated carbon storage capacities in Jianli City were 39.95 Tg, 39.90 Tg, and 40.14 Tg, respectively. When compared with the 2020 data, all these estimates showed an increase. In essence, our study offers insights into optimizing land use structures from a carbon storage standpoint to ensure stability in Jianli's carbon storage levels while mitigating the risks associated with carbon fixation. This has profound implications for the harmonious evolution of regional eco-economies. [ABSTRACT FROM AUTHOR]

In recent years, the "dual carbon" issue has become a major focus of the international community. Changes in land use driven by anthropogenic activities have a profound impact on ecosystem structure and carbon cycling. This study quantitatively assesses the spatiotemporal changes in cropland occupation and supplementation in the Pearl River Delta from 2000 to 2020 using the InVEST model, analyzing the spatial clustering of carbon storage changes caused by variations in cropland area. The PLUS model was employed to simulate land-use patterns and the spatial distribution of carbon storage in four future development scenarios. The results indicate the following: (1) From 2000 to 2020, the net change rate of cropland area in the Pearl River Delta was −0.81%, with a decrease of 16.49 km2 in cropland area, primarily converted to built-up land and forest land. (2) Carbon storage in the Pearl River Delta exhibited a pattern of lower values in the center and higher values in the periphery. The terrestrial ecosystem carbon storage in the Pearl River Delta was 534.62 × 106 t in 2000, 518.60 × 106 t in 2010, and 512.57 × 106 t in 2020, showing an overall decreasing trend. The conversion of cropland and forest land was the main reason for the decline in total regional carbon storage. (3) The area of carbon sequestration lost due to cropland occupation was significantly greater than the area of carbon loss compensated by new cropland, indicating an imbalance in the quality of cropland occupation and supplementation as a crucial factor contributing to regional carbon loss. (4) Under the ecological priority scenario, the expansion of built-up land and the reduction in ecological land such as cropland and forest land were effectively controlled, resulting in the minimal loss of carbon storage. The soil organic carbon pool of cropland is the most active carbon pool in terrestrial ecosystems and has a significant impact on carbon storage. Clarifying the relationship between "cropland protection measures–land use changes–ecosystem carbon storage" will improve cropland protection policies, provide references for regional carbon sequestration enhancement, and support sustainable socio-economic development. [ABSTRACT FROM AUTHOR]

Abstract Over the past decades, the drylands of the Yellow River Basin (YRBD) have undergone profound changes in landscape patterns and ecological dynamics, significantly impacting regional sustainable development. To assess the spatio-temporal variations of ecological risk in the YRBD and provide guidance for sustainable regional development, we constructed a coupled Land Use-Landscape Ecological Risk Model-Geographical Detector-PLUS framework for the assessment, analysis, and simulation of dryland landscape ecological risk (LER). The main findings are as follows: (1) Between 2000 and 2020, the area of built-up land, forest, grassland, and water in the YRBD increased, while the area of unused land and cropland decreased. (2) LER exhibited significant spatial heterogeneity, dominated by Sub-low and Low risks. High risk areas were primarily located in the western Inner Mongolia Plateau, whereas Low risk areas were prevalent in the Loess Plateau, with an overall decline in risk levels over the 20 years. (3) Water resources, ecological status, and human activities are the main driving factors affecting LER, with the impact of human activities becoming increasingly significant over the past 20 years. (4) Under three development scenarios in 2030, the LER is projected to further decrease, although the impact of these scenarios varies across different research sub-regions. Notably, the Ecological Priority Scenario emerges as more effective in mitigating regional LER. (5) Developing precise land use policies tailored to regional characteristics, continuously implementing ecological restoration projects, strengthening water resource management, and enhancing monitoring capabilities are effective ways to reduce LER in the YRBD. This study systematically quantified the impact of different development scenarios on LER in the YRBD, revealing its spatio-temporal characteristics, and emphasized the importance of planning guidance, ecological restoration, and risk monitoring to align regional development with ecological protection. The findings provide scientific evidence for ecological protection and sustainable development in the YRBD and other drylands, offering valuable insights for global dryland ecological risk management.

The present investigation examines the modelling and prediction of Land Use and Land Cover (LULC) changes in Thailand's Samut Songkhram province using three LULC prediction models: Markov Chain (LCM), Cellular Automata with Artificial Neural Network (CA-ANN), and Patch-Generating Land Use Simulation (PLUS) and using Sentinel-2 data and the proposed technique. By comparing models, this study identifies land conversion patterns effectively in each land use character. This study is a helpful strategy for acquiring land use information quickly. The proposed approach is practical in two significant aspects: first, it accurately identifies land use variations, and second, it simulates future land use change distributions. The analysis demonstrates that land use patterns have changed in a balanced manner between 2019 and 2021. The results reveal that patterns' quality in types of artificial surfaces and water bodies are efficient classifications, with more than 80% with LCM and CA-ANN. Furthermore, researchers performed a comparative analysis of the proposed approaches against well-known models such as Markov Chain, CA-ANN, and PLUS in the research area for 2023. The comparison disclosed that the proposed approaches are predictable, and LULC change identification in the dynamics area is more realistic, especially when using initial variable inputs. Classified LULC for 2023 confirmed the recent trends, with increased artificial surfaces, tree-covered regions, water bodies, and other land covers, while herbaceous crops, woody crops, mangroves, and salt fields decreased. Even though the study focuses primarily on short-term LULC changes, it highlights the significance of expanding the analysis to include long-term forecasts for a more straightforward overview. These long-term predictions provide essential information for policymakers and planners, assisting them in developing long-term management strategies to navigate the study area's transfer environment. [ABSTRACT FROM AUTHOR]

Habitat quality is an important basis for human well-being and the achievement of sustainable development. Based on land-use data for the Bosten Lake Basin in 2000, 2005, 2010, 2015, and 2022, the PLUS and InVEST models are applied in this study to predict and analyze land-use changes and explore the spatial and temporal evolution characteristics of the region's habitat quality. Additionally, we use a geographic detector model to reveal the drivers of spatial variation in habitat quality. The results show that: (1) Land use in Bosten Lake Basin is dominated by grassland and bare land, with an area share of 93.21%. Habitat quality shows a trend of degradation followed by improvement, with a spatial pattern of high in the northwest and low in the southeast. (2) Habitat quality in 2030 increased from 2022 in all cases, with a mean of 0.354 for the natural development scenario, a maximum of 0.355 for the ecological development scenario, and a minimum of 0.353 for the economic development scenario. (3) The main drivers affecting habitat quality in the Bosten Lake watershed are DEM, mean annual precipitation (MAP), and GDP per capita. X1∩X4 (0.50) and X4∩X10 (0.51) are the interaction factors with the largest dominant effect in 2000, 2010 and 2020, respectively. [ABSTRACT FROM AUTHOR]

Area identification is an important prerequisite for land consolidation and ecological restoration (LCER); the realization of an optimized land use pattern is the key link of land use optimization. This study meets the dual requirements by establishing an identification framework for potential LCER areas. The framework is applied to the Yellow River Basin with the help of the multi-objective linear programming (MOLP) model and patch-generating land use simulating (PLUS) model, which effectively connects the "ideal" land use pattern with the "practical" LCER. The main conclusions are as follows. (1) The land development probability of the basin shows a significant spatial differentiation. Precipitation significantly restricts the development of agricultural and ecological lands, and the population is the key factor affecting the construction land. (2) The construction land sprawl, cropland loss, and grassland reduction would be effectively controlled in the optimized land use pattern, with the forestland and water increasing and the unused land area decreasing. (3) The framework of "land expansion analysis-land use optimization-potential area identification" is established and used to identify LCER areas, including four conversion areas of cropland development, cropland retirement, ecological reconstruction, ecological readjustment, and four non-conversion areas of cropland improvement, ecological conservation, and reserve resource area (I,II). Conversion areas require more LCER interventions than non-conversion areas. The spread of construction land could lead to severe losses of grassland and cropland under the natural development scenario. Land use optimization effectively protects cropland and ecological land, based on which identifying LCER areas and adapting differentiated measures contribute to implementing such conservation while improving the basin's economic and ecological benefits. The identification framework provides flexible method guidance for determining the LCER areas, and offers a reference path for realizing optimized land use structure and pattern. [ABSTRACT FROM AUTHOR]

Studying rice water requirements (ETc) and area is crucial for developing irrigation schedules and adjusting crop structures. The cold rice cultivation region is China’s main high-quality rice production base and has the lowest temperature, highest latitude, and greatest sensitivity to climate. However, little research has focused on its past rice distributions and ETc, and its future variations are not yet clear. Past ETc was calculated by the Penman–Monteith and crop-corrected coefficient method, and past rice distribution patterns were analyzed based on the annual paddy rice planting area datasets. Future reference crop evapotranspiration (ET0) was projected by the statistical downscaling model (SDSM) based on the CMIP6 ensemble of daily predictor variables. The food and agriculture projections to 2050 datasets were used to project future rice areas, and the patch-generating land use simulation (PLUS) model simulated rice distribution. Finally, we projected future rice water supply demand. The results showed that ETc showed a decreasing trend, and the total rice area and production increased by 4.52 and 5.49 times from 1990 to 2020. Both in the past and future, rice was densely distributed in and expanded into the Sanjiang and Songnen Plains, and the spatial characteristic of ETc was as follows: the west was larger than the east, the north was larger than the south, and the central was in between. In the four future periods, the total ETc demonstrated an upward trend, increasing by 7.44–21.04, 15.64–34.74, 24.74–45.84, and 16.14–41.14 mm under the SSP126, SSP245, SSP370, and SSP585 scenarios, respectively, compared to the historical period. And it is generally ranked as SSP370 > SSP245 > SSP126. Finally, we projected future rice water supply meet the demand caused by rice area expansion.

In recent years, the “dual carbon” issue has become a major focus of the international community. Changes in land use driven by anthropogenic activities have a profound impact on ecosystem structure and carbon cycling. This study quantitatively assesses the spatiotemporal changes in cropland occupation and supplementation in the Pearl River Delta from 2000 to 2020 using the InVEST model, analyzing the spatial clustering of carbon storage changes caused by variations in cropland area. The PLUS model was employed to simulate land-use patterns and the spatial distribution of carbon storage in four future development scenarios. The results indicate the following: (1) From 2000 to 2020, the net change rate of cropland area in the Pearl River Delta was −0.81%, with a decrease of 16.49 km2 in cropland area, primarily converted to built-up land and forest land. (2) Carbon storage in the Pearl River Delta exhibited a pattern of lower values in the center and higher values in the periphery. The terrestrial ecosystem carbon storage in the Pearl River Delta was 534.62 × 106 t in 2000, 518.60 × 106 t in 2010, and 512.57 × 106 t in 2020, showing an overall decreasing trend. The conversion of cropland and forest land was the main reason for the decline in total regional carbon storage. (3) The area of carbon sequestration lost due to cropland occupation was significantly greater than the area of carbon loss compensated by new cropland, indicating an imbalance in the quality of cropland occupation and supplementation as a crucial factor contributing to regional carbon loss. (4) Under the ecological priority scenario, the expansion of built-up land and the reduction in ecological land such as cropland and forest land were effectively controlled, resulting in the minimal loss of carbon storage. The soil organic carbon pool of cropland is the most active carbon pool in terrestrial ecosystems and has a significant impact on carbon storage. Clarifying the relationship between “cropland protection measures–land use changes–ecosystem carbon storage” will improve cropland protection policies, provide references for regional carbon sequestration enhancement, and support sustainable socio-economic development.

In the context of the global decline in the capacity of ecosystem services (ESs) to meet increasing human demands, assessing and quantifying ESs is crucial for ecological policy formulation. To address this, our study employs an adjusted land-use matrix method and the patch-generating land-use simulation (PLUS) model for a quantitative analysis of the ES balance in the Beijing–Tianjin–Hebei–Inner Mongolia (JJJM) region from 2000 to 2020, projecting to 2040. Focusing on the JJJM region, a focal area for ecological policy exhibits significant socioeconomic disparities, revealing a synergistic interplay in the ESs balance. Areas with high vegetation cover, like forests and grasslands, demonstrate an elevated ESs balance, with Inner Mongolia having the highest total ESs balance at 71.40. Conversely, highly urbanized areas, such as Beijing and Tianjin, face deficits in the ESs balance, with Tianjin recording the lowest at 17.83. Our results show an upward trend in total ESs balance in the JJJM region (slope: 0.08 year−1). In particular, regulating services are declining (slope: −0.04 year−1), cultural services are increasing (slope: 0.08 year−1), and provisioning services remain relatively stable. Projecting to 2040, our analysis indicates a slight decline in ESs balance, attributed to Inner Mongolia's urban expansion. This emphasizes the need for industrial transfers and proactive urbanization promotion to enhance ESs balance and support sustainable management and ecological civilization development in the JJJM region. [ABSTRACT FROM AUTHOR]

Continuously global warming and landscape change have aggravated the damage of flood disasters to ecological safety and sustainable development. If the risk of flood disasters under climate and land-use changes can be predicted and evaluated, it will be conducive to flood control, disaster reduction, and global sustainable development. This study uses bias correction and spatial downscaling (BCSD), patch-generating land-use simulation (PLUS) coupled with multi-objective optimization (MOP), and entropy weighting to construct a 1 km resolution flood risk assessment framework for the Guanzhong Plain under multiple future scenarios. The results of this study show that BCSD can process the 6th Climate Model Intercomparison Project (CMIP6) data well, with a correlation coefficient of up to 0.98, and that the Kappa coefficient is 0.85. Under the SSP126 scenario, the change in land use from cultivated land to forest land, urban land, and water bodies remained unchanged. In 2030, the proportion of high-risk and medium-risk flood disasters in Guanzhong Plain will be 41.5% and 43.5% respectively. From 2030 to 2040, the largest changes in risk areas were in medium- and high-risk areas. The medium-risk area decreased by 1256.448 km2 (6.4%), and the high-risk area increased by 1197.552 km2 (6.1%). The increase mainly came from the transition from the medium-risk area to the high-risk area. The most significant change in the risk area from 2040 to 2050 is the higher-risk area, which increased by 337 km2 (5.7%), while the medium- and high-risk areas decreased by 726.384 km2 (3.7%) and 667.488 km2 (3.4%), respectively. Under the SSP245 scenario, land use changes from other land use to urban land use; the spatial distribution of the overall flood risk and the overall flood risk of the SSP126 and SSP245 scenarios are similar. The central and western regions of the Guanzhong Plain are prone to future floods, and the high-wind areas are mainly distributed along the Weihe River. In general, the flood risk in the Guanzhong Plain increases, and the research results have guiding significance for flood control in Guanzhong and global plain areas. [ABSTRACT FROM AUTHOR]

Quantitatively revealing the response of carbon stocks to land use change (LUCC) and analyzing the vulnerability of ecosystem carbon stock (ECS) services are of great significance for maintaining the carbon cycle and ecological security. For this study, China's Guizhou Province was the study area. Land use data in 2000, 2010, and 2020 were selected to explore the impacts of LUCC on carbon stocks in multiple scenarios by combining the PLUS and InVEST models and then analyzing the vulnerability of ECS services. The results show that forest land plays an important role in improving ECS services in karst plateau mountainous areas. In 2000–2020, forest land expansion offset the carbon stock reduced by the expansion of built-up land, greatly improving the regional ECS function. Following the natural trend (NT), the total carbon stock in Guizhou Province will decrease by 1.86 Tg; however, under ecological protection (EP) measures, the ECS service performs a positive function for LUCC. Focusing on socioeconomic development (ED) will increase the vulnerability of the regional ECS service. In the future, the forest land area size should be increased, and built-up land should be restricted to better improve the service function of ECS in karst plateau mountainous areas. [ABSTRACT FROM AUTHOR]

The Loess Plateau is one of the most fragile ecological regions in China due to its shortage of water resources and severe soil erosion. The rapid development of urbanization and the implementation of the project of returning farmland to forest (grass) have caused the ecological environment of the region to be strongly impacted by human activities. It is necessary to investigate the spatial and temporal evolution characteristics of ecosystem services and trade-off/synergy relationships on the Loess Plateau, to achieve scientific management of ecological services and sustainable development of the region. This study quantitatively assesses three ecosystem services of water yield (WY), carbon storage (CS), and soil conservation (SC) on the Loess Plateau under different scenarios from 2000 to 2030 by using the InVEST and PLUS models. Further, the trade-off and synergistic relationships among the ecosystem services have been investigated by Spearman correlation analysis. The results showed that the land-use differences are more obvious under different policy scenarios, with a sharp expansion of constructed land, a gradual increase of forest land, and a continuous decrease of arable land in the Loess Plateau from 2000 to 2020; the water yield and soil conservation increase from 2000 to 2020, and the carbon storage shows an opposite trend. The soil conservation and carbon storage scenarios are the best under the ecological conservation scenario in 2030, while the water yield service is the best under the economic development scenario. There is a synergistic relationship between CS and SC, while there is a trade-off relationship between CS and WY. In addition, there are significant trade-off effects between SC and WY. These results can support guiding land-use management and ecological restoration. [ABSTRACT FROM AUTHOR]

Rapid economic growth and urbanization have significantly changed the land use distribution and landscape ecological structure, which has a profound impact on the natural environment. A scientific grasp of the characteristics of land use distribution and its impact on landscape ecological risk is a prerequisite for sustainable urban development. This study aimed to calibrate GlobalLand30 data using the normalized difference impervious surface index (NDISI) obtained from Landsat images, thereby providing a more precise foundation for land simulation. Additionally, it sought to improve the accuracy of the patch-generating land use simulation (PLUS) through parameter sensitivity analysis. Building upon this, the research also simulates future land use in Beijing. Lastly, this study introduced an LER index to assess ecological risk in the current and future urban landscapes. The results showed that the GlobalLand30 data were calibrated and PLUS model accuracy was improved to more than 86%. The accuracy of the modified PLUS model based on a Morris sensitivity analysis was increased, and the kappa coefficients were increased by approximately 3%. The results of the multi-scenario simulation showed that under the SSP126-EP scenario, future land use in Beijing could balance urban development and ecological protection, and thus would be more suitable for sustainable development. In the other two scenarios, ecological land will be encroached by urban development. From 2000 to 2020, the degree of LER was generally lower, moderate, or higher, and the overall level of LER showed a downward trend continuing until 2100 in the SSP126-EG scenario. Future land use simulations and LER assessment under multi-scenarios could help decision makers develop multi-scale landscape protection strategies. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) is the most common cause of dementia with advancing age as its strongest risk factor. AD neuropathologic change (ADNC) is known to be associated with numerous DNA methylation changes in the human brain, but the oldest old (> 90 years) have so far been underrepresented in epigenetic studies of ADNC. Our study participants were individuals aged over 90 years (n = 47) from The 90+ Study. We analyzed DNA methylation from bulk samples in eight precisely dissected regions of the human brain: middle frontal gyrus, cingulate gyrus, entorhinal cortex, dentate gyrus, CA1, substantia nigra, locus coeruleus and cerebellar cortex. We deconvolved our bulk data into cell-type-specific (CTS) signals using computational methods. CTS methylation differences were analyzed across different levels of ADNC. The highest amount of ADNC related methylation differences was found in the dentate gyrus, a region that has so far been underrepresented in large scale multi-omic studies. In neurons of the dentate gyrus, DNA methylation significantly differed with increased burden of amyloid beta (Aβ) plaques at 5897 promoter regions of protein-coding genes. Amongst these, higher Aβ plaque burden was associated with promoter hypomethylation of the Presenilin enhancer 2 (PEN-2) gene, one of the rate limiting genes in the formation of gamma-secretase, a multicomponent complex that is responsible in part for the endoproteolytic cleavage of amyloid precursor protein into Aβ peptides. In addition to novel ADNC related DNA methylation changes, we present the most detailed array-based methylation survey of the old aged human brain to date. Our open-sourced dataset can serve as a brain region reference panel for future studies and help advance research in aging and neurodegenerative diseases.

Carbon storage in terrestrial ecosystems is crucial to advance carbon neutrality and support sustainable development. Extensive studies have explored the effect of land use change on carbon storage, especially urban expansion. As one of the world’s top urban agglomerations, the Pearl River Delta Urban Agglomeration (PRDUA) is facing a dramatic loss of carbon storage along with urbanization. Coordinating economic development and ecological protection and achieving low-carbon green development are urgently needed to alleviate the decline in urban carbon storage. Here, we quantified land use change in the historical period (2000, 2010, 2020) and in 2030 and then estimated carbon storage dynamics at different scales by combining the PLUS model and the InVEST model. We found that: (1) Construction land significantly increased simultaneously with considerable losses of farmland (2273.29 km2) and forestland (949.98 km2) from 2010–2020. In 2030, construction land will expand by 997.83 km2 (12.51%), 1419.97 km2 (17.79%), and 238.60 km2 (2.99%) under the natural growth (NG), urban expansion (UE), and low carbon development (LCD) scenarios, respectively. (2) Compared to 2020, carbon storage under the LCD will reach 6.51×108 Mg, with the lowest decline rate (0.35%). (3) At the city level, Shenzhen had the highest decline rate under various scenarios, followed by Zhuhai and Guangzhou. At the county scale, carbon storage followed the order NG > UE > LCD in 2000–2030. At the grid scale, carbon storage showed a declining trend from the central PRDUA region to marginal areas. Thus, comprehensive considering the multiscale effects of land use change on carbon storage was beneficial to formulate reasonable measures for specific areas. Differentiated development categories at different scales and low-carbon industrial upgrading should be implemented to maintain ecosystem services and achieve sustainable development.

Coastal is the coupling of socio-economic and fragile ecosystems area existing development and protection problems, with lots of reserve land resources (i.e., bottomland and tidal flats). Analyzing and predicting the carbon storage changes caused by land use/land cover (LULC) on the Jiangsu coast were critical for revealing the potential problems of land surface changes and sustainable development. Then, we utilized the single dynamic degree and transfer in/out contribution, exploring the characteristics of LULC change in the study area from 1980 to 2018. Using the InVEST model, PLUS-LEAS model, and PLUS-Markov chain module, we assessed the spatiotemporal of the study area at the county level to reveal the LULC change strategy and driving factor contribution, as well as the composition of LULC and carbon storage in 2036. The results show that the LULC structure in the study area significantly changed from 1980 to 2018, in which the tidal flat and high coverage grassland decreased by 552.84 km2 and 383.71 km2 while the reservoir ponds and urban residential land increased by 1210.69 km2 and 101.70 km2. The major driving factor of LULC change has shifted from a single-factor to multi-factor coupling, and the influence contribution of human activity increased by 6.73%, especially the population. The carbon storage of study areas showed a significant decrease trend during 1980–2010, followed by a slight increase during 2010–2018. High-density carbon storage was mainly distributed in Lianyungang and Nantong and presented a decreasing trend along the coastline extending inland. The dry land and reservoir ponds are the main composition of LULC types in 2036, and the carbon storage increased to 2.39 × 108 t. In addition, more than decades of LULC change will cover part or all of the land use change process and trends, especially high-covered grasslands, so we suggest a 10-year LULC change to analyze coastal areas with lots of tidal flats and bottomlands. Therefore, this study can provide reference and theoretical guidance for ecologically sustainable development and future LULC evolution in coastal cities. [ABSTRACT FROM AUTHOR]

Land degradation under the influence of global warming and ecological environmental destruction due to poor land management is the main challenge facing the Mongolian Plateau, and its future ecological risk change trends and drivers are also unclear. Therefore, to address the context relevant to this challenge, planning based on measured information from land use patterns is required. Based on land use and land cover (LULC), this study evaluates the landscape ecological risk (LER) of the Selenga River Basin by calculating the landscape pattern index. The spatiotemporal pattern and influencing factors of landscape ecological risk in the Selenga River Basin from 1990 to 2040 were analyzed. According to the results of LULC analysis, forest and grassland were the primary land use types in the Selenga River Basin. The built area, forest, and cropland showed an increasing trend, while the grassland area showed a fluctuating decreasing trend. From 1990 to 2010, the comprehensive land use dynamic degree showed a trend of rising first and then falling, specifically from 0.13% in 1990 to 0.29% in 2010, and will drop to 0.06% by 2040, indicating that the range of land use change is becoming more and more stable. The landscape ecological risk assessment shows a distribution pattern of "low at the edge and high in the middle". The landscape ecological risk index (LER) first increases and then decreases, with the peak value in 2010 (0.085). By calculating the spatial aggregation of LER and the partial correlation with climate, we found that the Moran's I index showed an "anti-V"-shaped change trend from 1990 to 2040, and the average landscape ecological risk presents positive spatial correlation, primarily with high-value aggregation, and peaked in 2010. Precipitation had a negative correlation with landscape ecological risk controlling for temperature, while there was a positive relationship between temperature and landscape ecological risk under the influence of controlling precipitation. This study provides a scientific basis for LULC planning in the Selenga River Basin, and is of great significance for maintaining the ecological security of the Mongolian Plateau. [ABSTRACT FROM AUTHOR]

Abstract Background New intraocular lenses (IOLs) have emerged since the originally coined monofocal and multifocal IOLs. The extended depth of focus (EDoF) and enhanced monofocal IOLs (mono-EDoF) that have appeared in the last decade have caused some confusion in their classification. The aim of this review was to summarize the outcomes provided by mono-EDOF IOLs and to determine which of the endpoints, described by the American National Standard (ANSI) for EDoF IOLs, are fulfilled. Methods The MEDLINE, EMBASE, and WEB OF SCIENCE databases were searched. Two independent reviewers screened the studies for inclusion and data extraction. The search strategy was limited to studies published between 2020 and 2022, but not by language. The results are presented as a narrative summary accompanied by tables, in alignment with the objectives of this scoping review. Compliance with the endpoints for clinical outcomes described in the American National Standard Z80.35–2018 (ANSI) for EDoF lenses was checked and additional endpoints were defined. Results Two systematic reviews, 13 laboratory, 21 clinical, and two mixed studies were included. Tecnis Eyhance was the mono-EDOF with the highest volume of evidence to date. Although laboratory studies included other IOLs, clinical evidence for them is still scarce, with only one study of IsoPure compared to a standard monofocal IOL. Evidence in comparison to EDoF lenses is also scarce, even for Tecnis Eyhance, with only three studies including this lens in comparison to an EDoF lens. After evaluation of the ANSI criteria, agreement was found in the failure for the increase in depth of field equal to or greater than 0.5 D for a visual acuity (VA) level of 0.2 logMAR and none of the studies supported that the median monocular VA at intermediate distance was at least 0.2 logMAR. Conclusions Additional clinical evidence is required for other mono-EDOF IOLs beyond Tecnis Eyhance. Until the arrival of a standard classification, mono-EDOF should be better still classified as monofocal because the ANSI standards were not fully met.

Limited attention has been given to improving carbon storage by identifying ecological conservation and restoration areas (ECRAs). In this research, we proposed a new framework for identifying ECRAs by incorporating future carbon storage changes into ecological security patterns (ESPs), including several models of the Patch-generating Land Use Simulation (PLUS), Integrated Valuation of Ecosystem Service and Tradeoffs (InVEST), Minimum Cumulative Resistance (MCR) and circuit theory. This new framework was applied in Jiangsu Yangtze River Economic Belt, East China. To evaluate the effectiveness of this new framework, we compared two scenarios: an ecological priority scenario (EPS) where future carbon storage change was not considered and an ecosystem carbon sequestration scenario (ECSS) where future carbon storage change was explicitly incorporated. Under the EPS, ecological conservation areas and ecological restoration areas were 11169.87 km2 and 221.11 km2, respectively. Under the ECSS, the ecological conservation areas and ecological restoration areas were 14768.76 km2 and 244.89 km2, respectively. Carbon storage will be most likely to increase around lakes and the Yangtze River, and the identified key areas under the ECSS will be more adaptable to future environmental changes than the EPS. This new framework can effectively enhance both ecological function and carbon sequestration, providing effective support for policymakers in landscape management and low-carbon development in other regions facing similar challenges. In the meantime, more caution is needed for the possible limitations, such as without adequate consideration of uncertainties of changes in population, land use, and economy in the future.

Land use is a process that turns a piece of land's natural ecosystem into an artificial one. The mix of plant and man-made covers on the Earth's surface is known as land cover. Land use is the primary external force behind change in land cover, and land cover has an impact on how land use is carried out, resulting in a synergistic interaction between the two at the Earth's surface. In China's Shandong Peninsula city cluster, Dongying is a significant coastal port city. It serves as the administrative hub for the Yellow River Delta and is situated in Shandong Province, China's northeast. The changes in its urban land use and land cover in the future are crucial to understanding. This research suggests a prediction approach that combines a patch-generation land use simulation (PLUS) model and long-term short-term memory (LSTM) deep learning algorithm to increase the accuracy of predictions of future land use and land cover. The effectiveness of the new method is demonstrated by the fact that the average inaccuracy of simulating any sort of land use in 2020 is around 5.34%. From 2020 to 2030, 361.41 km2 of construction land is converted to cropland, and 424.11 km2 of cropland is converted to water. The conversion areas between water and unused land and cropland are 211.47 km2 and 148.42 km2, respectively. The area of construction land and cropland will decrease by 8.38% and 3.64%, respectively, while the area of unused land, water, and grassland will increase by 5.53%, 2.44%, and 0.78%, respectively. [ABSTRACT FROM AUTHOR]

Background: New intraocular lenses (IOLs) have emerged since the originally coined monofocal and multifocal IOLs. The extended depth of focus (EDoF) and enhanced monofocal IOLs (mono-EDoF) that have appeared in the last decade have caused some confusion in their classification. The aim of this review was to summarize the outcomes provided by mono-EDOF IOLs and to determine which of the endpoints, described by the American National Standard (ANSI) for EDoF IOLs, are fulfilled. Methods: The MEDLINE, EMBASE, and WEB OF SCIENCE databases were searched. Two independent reviewers screened the studies for inclusion and data extraction. The search strategy was limited to studies published between 2020 and 2022, but not by language. The results are presented as a narrative summary accompanied by tables, in alignment with the objectives of this scoping review. Compliance with the endpoints for clinical outcomes described in the American National Standard Z80.35–2018 (ANSI) for EDoF lenses was checked and additional endpoints were defined. Results: Two systematic reviews, 13 laboratory, 21 clinical, and two mixed studies were included. Tecnis Eyhance was the mono-EDOF with the highest volume of evidence to date. Although laboratory studies included other IOLs, clinical evidence for them is still scarce, with only one study of IsoPure compared to a standard monofocal IOL. Evidence in comparison to EDoF lenses is also scarce, even for Tecnis Eyhance, with only three studies including this lens in comparison to an EDoF lens. After evaluation of the ANSI criteria, agreement was found in the failure for the increase in depth of field equal to or greater than 0.5 D for a visual acuity (VA) level of 0.2 logMAR and none of the studies supported that the median monocular VA at intermediate distance was at least 0.2 logMAR. Conclusions: Additional clinical evidence is required for other mono-EDOF IOLs beyond Tecnis Eyhance. Until the arrival of a standard classification, mono-EDOF should be better still classified as monofocal because the ANSI standards were not fully met. [ABSTRACT FROM AUTHOR]

Based on the PSR model from the perspective of landscape patterns, a spatial conflict measurement model framework based on the pressure-state-response theory was constructed, and spatial statistics, mathematical analysis, and other relevant methods were used to study the intensity level, spatiotemporal differentiation, and evolution law of spatial conflict in the Poyang Lake urban agglomeration. Three different urban development forecasting scenarios of “ecological priority”, “economic priority,” and “planning restriction” were set to simulate the spatial distribution pattern of land use and urban spatial conflict distribution in terms of the patch generation land use simulation model (PLUS). Combined with the research results and status of urban development, optimization strategies and suggestions for alleviating urban spatial conflicts are presented in this study. The results showed that: (1) The intensity of the spatial conflict in the Poyang Lake urban agglomeration significantly increased due to fluctuations in the spatial pressure, spatial structure, and spatial pattern. (2) The lower conflict zones are mainly distributed in the mountains in the west and east of the study area and are mainly located in the border areas of the study area, showing a massive distribution. The higher conflict zones are scattered in the core cities within the entire study area. The proportion of low conflict zones and high conflict zones is the highest, and both are distributed in the transitional regions of low and high conflict zones. (3) Under the ecological priority scenario, the ecological structure had obvious advantages, and the overall spatial conflict intensity was the lowest. In the non-ecological priority scenario, the expansion of the construction land limited the development of ecological land, and the intensity of spatial conflict increased significantly. (4) Increasing forest coverage, improving the area of ecological land, reducing the consumption of urban construction land in surrounding ecology and agricultural structures, and increasing ecological land through basement protection and corridor construction are the optimal strategies to alleviate spatial conflict intensity. [ABSTRACT FROM AUTHOR]

Land use change could affect the carbon sink of terrestrial ecosystems, implying that future carbon storage could be estimated by simulating land use patterns, which is of great significance for the ecological environment. Therefore, the patterns of future land use and carbon storage under the combination scenarios of different Shared Socioeconomic Pathway (SSP) and Representative Concentration Pathway (RCP) of the Yangtze River Delta were simulated by introducing weight matrices into the Markov model and combining the PLUS and InVEST models. The results revealed that the woodland expands greatly during 2020–2060 under the SSP1-RCP2.6 scenario, and the carbon storage of 2060 is at a high level with an estimated value of 5069.31 × 106 t and an average annual increase of 19.13 × 106 t, indicating that the SSP1-RCP2.6 scenario contributes to the improvement of carbon storage. However, the area of built-up land is increasing under the SSP5-RCP8.5 scenario, and the estimated value of carbon storage is 3836.55 × 106 t, with an average annual decrease of 11.69 × 106 t, indicating that the SSP5-RCP8.5 scenario negatively affects carbon sink. Besides, the SSP2-RCP4.5 scenario causes almost no effect on land use change and carbon storage. The above results can help policymakers manage land use patterns and choose the best development scenario. [ABSTRACT FROM AUTHOR]

In the context of the global decline in the capacity of ecosystem services (ESs) to meet increasing human demands, assessing and quantifying ESs is crucial for ecological policy formulation. To address this, our study employs an adjusted land-use matrix method and the patch-generating land-use simulation (PLUS) model for a quantitative analysis of the ES balance in the Beijing–Tianjin–Hebei–Inner Mongolia (JJJM) region from 2000 to 2020, projecting to 2040. Focusing on the JJJM region, a focal area for ecological policy exhibits significant socioeconomic disparities, revealing a synergistic interplay in the ESs balance. Areas with high vegetation cover, like forests and grasslands, demonstrate an elevated ESs balance, with Inner Mongolia having the highest total ESs balance at 71.40. Conversely, highly urbanized areas, such as Beijing and Tianjin, face deficits in the ESs balance, with Tianjin recording the lowest at 17.83. Our results show an upward trend in total ESs balance in the JJJM region (slope: 0.08 year−1). In particular, regulating services are declining (slope: −0.04 year−1), cultural services are increasing (slope: 0.08 year−1), and provisioning services remain relatively stable. Projecting to 2040, our analysis indicates a slight decline in ESs balance, attributed to Inner Mongolia’s urban expansion. This emphasizes the need for industrial transfers and proactive urbanization promotion to enhance ESs balance and support sustainable management and ecological civilization development in the JJJM region.

Continuously global warming and landscape change have aggravated the damage of flood disasters to ecological safety and sustainable development. If the risk of flood disasters under climate and land-use changes can be predicted and evaluated, it will be conducive to flood control, disaster reduction, and global sustainable development. This study uses bias correction and spatial downscaling (BCSD), patch-generating land-use simulation (PLUS) coupled with multi-objective optimization (MOP), and entropy weighting to construct a 1 km resolution flood risk assessment framework for the Guanzhong Plain under multiple future scenarios. The results of this study show that BCSD can process the 6th Climate Model Intercomparison Project (CMIP6) data well, with a correlation coefficient of up to 0.98, and that the Kappa coefficient is 0.85. Under the SSP126 scenario, the change in land use from cultivated land to forest land, urban land, and water bodies remained unchanged. In 2030, the proportion of high-risk and medium-risk flood disasters in Guanzhong Plain will be 41.5% and 43.5% respectively. From 2030 to 2040, the largest changes in risk areas were in medium- and high-risk areas. The medium-risk area decreased by 1256.448 km2 (6.4%), and the high-risk area increased by 1197.552 km2 (6.1%). The increase mainly came from the transition from the medium-risk area to the high-risk area. The most significant change in the risk area from 2040 to 2050 is the higher-risk area, which increased by 337 km2 (5.7%), while the medium- and high-risk areas decreased by 726.384 km2 (3.7%) and 667.488 km2 (3.4%), respectively. Under the SSP245 scenario, land use changes from other land use to urban land use; the spatial distribution of the overall flood risk and the overall flood risk of the SSP126 and SSP245 scenarios are similar. The central and western regions of the Guanzhong Plain are prone to future floods, and the high-wind areas are mainly distributed along the Weihe River. In general, the flood risk in the Guanzhong Plain increases, and the research results have guiding significance for flood control in Guanzhong and global plain areas.

Quantitatively revealing the response of carbon stocks to land use change (LUCC) and analyzing the vulnerability of ecosystem carbon stock (ECS) services are of great significance for maintaining the carbon cycle and ecological security. For this study, China’s Guizhou Province was the study area. Land use data in 2000, 2010, and 2020 were selected to explore the impacts of LUCC on carbon stocks in multiple scenarios by combining the PLUS and InVEST models and then analyzing the vulnerability of ECS services. The results show that forest land plays an important role in improving ECS services in karst plateau mountainous areas. In 2000–2020, forest land expansion offset the carbon stock reduced by the expansion of built-up land, greatly improving the regional ECS function. Following the natural trend (NT), the total carbon stock in Guizhou Province will decrease by 1.86 Tg; however, under ecological protection (EP) measures, the ECS service performs a positive function for LUCC. Focusing on socioeconomic development (ED) will increase the vulnerability of the regional ECS service. In the future, the forest land area size should be increased, and built-up land should be restricted to better improve the service function of ECS in karst plateau mountainous areas.

The Loess Plateau is one of the most fragile ecological regions in China due to its shortage of water resources and severe soil erosion. The rapid development of urbanization and the implementation of the project of returning farmland to forest (grass) have caused the ecological environment of the region to be strongly impacted by human activities. It is necessary to investigate the spatial and temporal evolution characteristics of ecosystem services and trade-off/synergy relationships on the Loess Plateau, to achieve scientific management of ecological services and sustainable development of the region. This study quantitatively assesses three ecosystem services of water yield (WY), carbon storage (CS), and soil conservation (SC) on the Loess Plateau under different scenarios from 2000 to 2030 by using the InVEST and PLUS models. Further, the trade-off and synergistic relationships among the ecosystem services have been investigated by Spearman correlation analysis. The results showed that the land-use differences are more obvious under different policy scenarios, with a sharp expansion of constructed land, a gradual increase of forest land, and a continuous decrease of arable land in the Loess Plateau from 2000 to 2020; the water yield and soil conservation increase from 2000 to 2020, and the carbon storage shows an opposite trend. The soil conservation and carbon storage scenarios are the best under the ecological conservation scenario in 2030, while the water yield service is the best under the economic development scenario. There is a synergistic relationship between CS and SC, while there is a trade-off relationship between CS and WY. In addition, there are significant trade-off effects between SC and WY. These results can support guiding land-use management and ecological restoration.

Based on the PLUS model, research proposed a method to adjust the probability of land use transition to reduce the calculation error of the number of pixels. The refined algorithm is applied to simulate Shenzhen land use situation in 2030 under a progressive scenario using three periods of Shenzhen land use data in 2000, 2010 and 2020. Then, InVEST model was employed to evaluate the distribution situation and future trends of habitat quality in Shenzhen during the study period. Following are the conclusions: 1) The construction land in Shenzhen expanded rapidly and the ecological land gradually shrank during the research period. The proportion of artificial surface area increased by about 45.4% (304.98 km2) within 20 years. 2) By simulating the land use situation of Shenzhen in 2030, the results revealed that the land use change of Shenzhen in the future is mainly concentrated in the central and western regions. 3) The overall average habitat quality of Shenzhen was at a medium level, but the habitat quality showed a continuous degradation trend in each year throughout the study period. Spatially, the habitat quality degradation are mainly concentrated in Shenzhen’s central and western region. 4) Under the natural development scenario, Shenzhen’s habitat quality would experience a sharp decline by 2030. The habitat quality of the conservation area is guaranteed to a certain degree, but the artificial surface expansion outside the area will still affect the habitat quality in the boundary constraint scenario; Only in scenario of ecological priority, the habitat quality of Shenzhen has been restored and improved to a large extent. 5) In order to slow down the degradation trend and improve the regional ecological environment. It is necessary not only to strictly implement various protection boundaries delineated in the context of Territorial Spatial Planning, but also to implement the policy of “Clear waters and green mountains are as good as mountains of gold and silver” in the process of urban development. Government should reasonably control the scale of cities, optimize the ecological compensation mechanism, and implement ecological restoration policies such as returning farmland to forests and returning farmland to grassland.

Predicting trends in land use/cover change (LUCC) and assessing future ecological security (ES) can help effectively balance regional ecological conservation and economic development. In this study, a land use simulation model was used to predict the spatial-temporal variation in land use in Kashgar in 2030 under three scenarios (inertial development, agricultural land protection, and forest and rangeland conservation). Subsequently, by combining the pressure–state–response model and predicted land use, the ES of the Kashgar region in 2000, 2010, and 2020 were evaluated. We found that (1) only agricultural land and built-up land in the Kashgar region increased from 2000–2020 by 4174.79 and 434.44 km2, respectively. (2) The area of the region belonging to a generally safe level or above decreased from 38.36% in 2000 to 36.89% in 2010 and then increased to 37.71% in 2020. (3) In 2030, the ES status under the three scenarios will be improved, among which the agricultural land protection scenario corresponds to the best ES status. This research is valuable for deeply understanding the interaction mechanism between LUCC and ES in typical artificial oases in arid areas of the Kashgar region and sustaining relatively stable internal structures and socioeconomic activities in the arid oasis of the Kashgar region. [ABSTRACT FROM AUTHOR]

Under the urbanization context, land use/land cover (LULC) changes rapidly which affects both the probability of urban flood disaster and its consequence. In order to explore the impact of LULC changes on rainstorm flood disaster risk in the future, a framework of rainstorm flood disaster risk assessment is constructed from natural‐social perspective through LULC simulation based on the patch‐generating land use simulation (PLUS) model in this study. Specifically, the spatial LULC under three future development scenarios (inertia development scenario, economic priority scenario and sustainable development scenario) for the year 2030 is simulated, and then assessment model of rainstorm flood disaster risk is constructed through obtaining inundation depth and social vulnerability based on simulated LULC. Jingdezhen City in China is selected as an example. The results show that proposed risk assessment framework based on PLUS model can be used to detect the risk changes in different development scenarios. The risk of urban rainstorm flood disaster under economic priority scenario is most severe and risk under the sustainable development scenario is the lowest under the same return period rainstorm. Under the sustainable development scenario, green land including forest land, grassland and open water increases, which reduces the surface runoff and decrease the risk of rainstorm flood disaster effectively, however the reduction is limited with the greater rainstorm return period. Therefore, adaptive measures should be implemented together with land use planning to prevent and control urban flood risk. This study provides a framework to predict the future risk of urban rainstorm flood under different development scenarios, which can support for flood disaster risk prevention and urban sustainable development. [ABSTRACT FROM AUTHOR]

Rapid economic growth and urbanization have significantly changed the land use distribution and landscape ecological structure, which has a profound impact on the natural environment. A scientific grasp of the characteristics of land use distribution and its impact on landscape ecological risk is a prerequisite for sustainable urban development. This study aimed to calibrate GlobalLand30 data using the normalized difference impervious surface index (NDISI) obtained from Landsat images, thereby providing a more precise foundation for land simulation. Additionally, it sought to improve the accuracy of the patch-generating land use simulation (PLUS) through parameter sensitivity analysis. Building upon this, the research also simulates future land use in Beijing. Lastly, this study introduced an LER index to assess ecological risk in the current and future urban landscapes. The results showed that the GlobalLand30 data were calibrated and PLUS model accuracy was improved to more than 86%. The accuracy of the modified PLUS model based on a Morris sensitivity analysis was increased, and the kappa coefficients were increased by approximately 3%. The results of the multi-scenario simulation showed that under the SSP126-EP scenario, future land use in Beijing could balance urban development and ecological protection, and thus would be more suitable for sustainable development. In the other two scenarios, ecological land will be encroached by urban development. From 2000 to 2020, the degree of LER was generally lower, moderate, or higher, and the overall level of LER showed a downward trend continuing until 2100 in the SSP126-EG scenario. Future land use simulations and LER assessment under multi-scenarios could help decision makers develop multi-scale landscape protection strategies.

Coastal is the coupling of socio-economic and fragile ecosystems area existing development and protection problems, with lots of reserve land resources (i.e., bottomland and tidal flats). Analyzing and predicting the carbon storage changes caused by land use/land cover (LULC) on the Jiangsu coast were critical for revealing the potential problems of land surface changes and sustainable development. Then, we utilized the single dynamic degree and transfer in/out contribution, exploring the characteristics of LULC change in the study area from 1980 to 2018. Using the InVEST model, PLUS-LEAS model, and PLUS-Markov chain module, we assessed the spatiotemporal of the study area at the county level to reveal the LULC change strategy and driving factor contribution, as well as the composition of LULC and carbon storage in 2036. The results show that the LULC structure in the study area significantly changed from 1980 to 2018, in which the tidal flat and high coverage grassland decreased by 552.84 km2 and 383.71 km2 while the reservoir ponds and urban residential land increased by 1210.69 km2 and 101.70 km2. The major driving factor of LULC change has shifted from a single-factor to multi-factor coupling, and the influence contribution of human activity increased by 6.73%, especially the population. The carbon storage of study areas showed a significant decrease trend during 1980–2010, followed by a slight increase during 2010–2018. High-density carbon storage was mainly distributed in Lianyungang and Nantong and presented a decreasing trend along the coastline extending inland. The dry land and reservoir ponds are the main composition of LULC types in 2036, and the carbon storage increased to 2.39 × 108 t. In addition, more than decades of LULC change will cover part or all of the land use change process and trends, especially high-covered grasslands, so we suggest a 10-year LULC change to analyze coastal areas with lots of tidal flats and bottomlands. Therefore, this study can provide reference and theoretical guidance for ecologically sustainable development and future LULC evolution in coastal cities.

Land degradation under the influence of global warming and ecological environmental destruction due to poor land management is the main challenge facing the Mongolian Plateau, and its future ecological risk change trends and drivers are also unclear. Therefore, to address the context relevant to this challenge, planning based on measured information from land use patterns is required. Based on land use and land cover (LULC), this study evaluates the landscape ecological risk (LER) of the Selenga River Basin by calculating the landscape pattern index. The spatiotemporal pattern and influencing factors of landscape ecological risk in the Selenga River Basin from 1990 to 2040 were analyzed. According to the results of LULC analysis, forest and grassland were the primary land use types in the Selenga River Basin. The built area, forest, and cropland showed an increasing trend, while the grassland area showed a fluctuating decreasing trend. From 1990 to 2010, the comprehensive land use dynamic degree showed a trend of rising first and then falling, specifically from 0.13% in 1990 to 0.29% in 2010, and will drop to 0.06% by 2040, indicating that the range of land use change is becoming more and more stable. The landscape ecological risk assessment shows a distribution pattern of “low at the edge and high in the middle”. The landscape ecological risk index (LER) first increases and then decreases, with the peak value in 2010 (0.085). By calculating the spatial aggregation of LER and the partial correlation with climate, we found that the Moran’s I index showed an “anti-V”-shaped change trend from 1990 to 2040, and the average landscape ecological risk presents positive spatial correlation, primarily with high-value aggregation, and peaked in 2010. Precipitation had a negative correlation with landscape ecological risk controlling for temperature, while there was a positive relationship between temperature and landscape ecological risk under the influence of controlling precipitation. This study provides a scientific basis for LULC planning in the Selenga River Basin, and is of great significance for maintaining the ecological security of the Mongolian Plateau.

Intermittent rhythmic delta activities are electroencephalographic discharges with uniform morphology, at a frequency of 4 Hz or less, containing at least six cycles, lost by eye opening and stimulation. These are called “plus” if concomitant theta or higher frequency rapid activity or spike, sharp wave activity is present. This group has a stronger relationship with epileptiform abnormality. We aimed to discuss the clinical presentations, and nomenclature of intermittent rhythmic delta activities with three case reports.

The National Coastal Shelterbelt System Construction Project (NCSSCP) was proposed to increase the afforestation area and neutralize the impact of urbanization, especially in the southeast coastal sub-region of China. In this study, we identified the spatio-temporal evolution characteristics and predicted the land use and land cover changes (LUCC) associated with this project by modeling scenarios, seeking to explore the path of sustainable development. The spatial structure was analyzed using the landscape pattern index approach and the land use transfer matrix. By coupling the Markov model and patch-generating a land-use simulation model (PLUS), different scenarios were analyzed to predict the quantity and spatial changes. According to the results, based on the current trends and due to the impact of urbanization, the forest area was predicted to decrease by 633.19 km2, whilst appearing more spatially fragmented and separated. However, with the completion of the NCSSCP target, the forest area was predicted to increase by 1666.12 km2, and the spatial structure would appear more cohesive and concentrated. From an overall perspective, the afforestation target of NCSSCP will not be completed under the present trend. It is difficult for the afforestation speed of the NCSSCP to keep up with the speed of urbanization. Therefore, giving consideration to both the afforestation speed and quality and reducing the speed of urbanization to balance the economy and ecology would be beneficial in terms of the realization of the aims of sustainable development. [ABSTRACT FROM AUTHOR]

The rapid expansion of cities in tropical regions has triggered a series of problems such as the destruction of rare natural resources and decreases in the environmental resource carrying capacity and ecological security, which seriously threaten the sustainable development of tropical cities. In this study, the city of Sanya, Hainan, China, is taken as an example. A bottom-line ecological security pattern is constructed based on the remote sensing ecological index (RSEI) and the patch-generating land use simulation (PLUS) for urban growth boundary (UGB) delineation. The results show that Sanya has a good ecological background, but the overall ecological quality decreased from 2014 to 2018 due to the expansion of construction in hot spot areas. Under the natural growth scenario, the urban built-up area in Sanya in 2030 will be 73.81% greater than in 2018, mainly occupying a large amount of agricultural and ecological space, and urban expansion will not be effectively suppressed. Delineation of the UGBs combined with the ecological constraints can effectively protect the regional ecological security and control the urban sprawl, which is relatively consistent with the current planning. The results of this study demonstrate that the RSEI-PLUS-based UGB delineation perspective has a high scientific and applicability, and they provide a reference for the coordinated ecological–economic sustainable development of ecologically fragile cities in tropical areas. [ABSTRACT FROM AUTHOR]

The ecosystem of inland river basin is of great significance to the socio-economic stability in arid area. Therefore, to evaluate the ecosystem service values (ESVs) is necessary for monitor ecosystem changes. In this paper, the response of land use/land cover (LULC) during 1990 to 2020 in Aksu River Basin (ARB) to ESV was explored. The advanced equivalent factor which modified by biomass factor and socio-economic was used to evaluate the ESVs of the ARB. A patch-generating land use simulation (PLUS) was used to simulate the ESV spatial distribution considering the influences of temperature (TEM), precipitation (PRE), NDVI, DEM, Soil organic matter content (SOMC) and Human Activity Intensity of Land Surface (HAILS) of the ARB in 2030. The results show that the total ESV in the study area showed an increasing trend (1.63 × 1010 yuan to 5.64 × 1010 yuan) from 1990 to 2020. The grassland had the highest ESV, accounting for nearly 50% of the total ESV for the ARB. The factor detection results showed that q value had the following explanatory power to ESV: HAILS (0.332) > NDVI (0.126) > TEM (0.125) > PRE (0.108) > DEM(0.096) > SOMC(0.089)and the interaction between HAILS and PRE had an effect of 0.493 on ESV. The shape index (SI) was negatively correlated with the ESV, and the correlation coefficient was −0.794. The aggregation index (AI) and Shannon's Diversity Index (SHDI) were positively correlated with the ESV, and the correlation coefficients were 0.872 and 0.878, respectively. The simulation results showed a rapid increase in ESVs in 2030, the ESV of grassland would still be the largest, and the per unit ESV of plowland, forestland, unused land and water area would be 20131.07 yuan/km2, 64743.29 yuan/km2, 3054.21 yuan/km2, 41398.54 yuan/km2, respectively. This paper can help decision-makers achieve sustainable ecosystem service management and develop land-use strategies in inland river basins in arid oases.

Studying rice water requirements (ET c) and area is crucial for developing irrigation schedules and adjusting crop structures. The cold rice cultivation region is China's main high-quality rice production base and has the lowest temperature, highest latitude, and greatest sensitivity to climate. However, little research has focused on its past rice distributions and ET c , and its future variations are not yet clear. Past ET c was calculated by the Penman–Monteith and crop-corrected coefficient method, and past rice distribution patterns were analyzed based on the annual paddy rice planting area datasets. Future reference crop evapotranspiration (ET 0) was projected by the statistical downscaling model (SDSM) based on the CMIP6 ensemble of daily predictor variables. The food and agriculture projections to 2050 datasets were used to project future rice areas, and the patch-generating land use simulation (PLUS) model simulated rice distribution. Finally, we projected future rice water supply demand. The results showed that ET c showed a decreasing trend, and the total rice area and production increased by 4.52 and 5.49 times from 1990 to 2020. Both in the past and future, rice was densely distributed in and expanded into the Sanjiang and Songnen Plains, and the spatial characteristic of ET c was as follows: the west was larger than the east, the north was larger than the south, and the central was in between. In the four future periods, the total ET c demonstrated an upward trend, increasing by 7.44–21.04, 15.64–34.74, 24.74–45.84, and 16.14–41.14 mm under the SSP126, SSP245, SSP370, and SSP585 scenarios, respectively, compared to the historical period. And it is generally ranked as SSP370 > SSP245 > SSP126. Finally, we projected future rice water supply meet the demand caused by rice area expansion. • Rice area and production increased by 4.52, and 5.49 times in past, respectively. • Future ETo and precipitation were predicted by SDSM model based on CMIP6 data. • ETc was estimated by the crop corrected-coefficient method. • ETc showed a decreasing trend in past, and an increasing trend in future scenario. • Future agricultural irrigation will meet the demand caused by rice area expansion. [ABSTRACT FROM AUTHOR]

Land use is a process that turns a piece of land’s natural ecosystem into an artificial one. The mix of plant and man-made covers on the Earth’s surface is known as land cover. Land use is the primary external force behind change in land cover, and land cover has an impact on how land use is carried out, resulting in a synergistic interaction between the two at the Earth’s surface. In China’s Shandong Peninsula city cluster, Dongying is a significant coastal port city. It serves as the administrative hub for the Yellow River Delta and is situated in Shandong Province, China’s northeast. The changes in its urban land use and land cover in the future are crucial to understanding. This research suggests a prediction approach that combines a patch-generation land use simulation (PLUS) model and long-term short-term memory (LSTM) deep learning algorithm to increase the accuracy of predictions of future land use and land cover. The effectiveness of the new method is demonstrated by the fact that the average inaccuracy of simulating any sort of land use in 2020 is around 5.34%. From 2020 to 2030, 361.41 km2 of construction land is converted to cropland, and 424.11 km2 of cropland is converted to water. The conversion areas between water and unused land and cropland are 211.47 km2 and 148.42 km2, respectively. The area of construction land and cropland will decrease by 8.38% and 3.64%, respectively, while the area of unused land, water, and grassland will increase by 5.53%, 2.44%, and 0.78%, respectively.

Land use change could affect the carbon sink of terrestrial ecosystems, implying that future carbon storage could be estimated by simulating land use patterns, which is of great significance for the ecological environment. Therefore, the patterns of future land use and carbon storage under the combination scenarios of different Shared Socioeconomic Pathway (SSP) and Representative Concentration Pathway (RCP) of the Yangtze River Delta were simulated by introducing weight matrices into the Markov model and combining the PLUS and InVEST models. The results revealed that the woodland expands greatly during 2020–2060 under the SSP1-RCP2.6 scenario, and the carbon storage of 2060 is at a high level with an estimated value of 5069.31 × 106 t and an average annual increase of 19.13 × 106 t, indicating that the SSP1-RCP2.6 scenario contributes to the improvement of carbon storage. However, the area of built-up land is increasing under the SSP5-RCP8.5 scenario, and the estimated value of carbon storage is 3836.55 × 106 t, with an average annual decrease of 11.69 × 106 t, indicating that the SSP5-RCP8.5 scenario negatively affects carbon sink. Besides, the SSP2-RCP4.5 scenario causes almost no effect on land use change and carbon storage. The above results can help policymakers manage land use patterns and choose the best development scenario.

Ecosystem service assessment and prediction play a crucial role in sustainable regional development and resource management. Liaoning Province, as a typical representative of Northeast China, faces rapid development challenges such as urbanization, industrialization, and agricultural modernization. At the same time, there is an urgent need for a deeper understanding of the evolution trends of its ecosystems and their impact on ecosystem services. This study employed the InVEST-Markov-PLUS model to conduct simulated research on the assessment of past and future ecosystem services and multi-scenario predictions in Liaoning Province. Based on the land-use changes in Liaoning Province from 2000 to 2020, the InVEST model was used to evaluate the spatiotemporal variations in carbon storage, soil conservation, and water yield in the ecosystem services from 2000 to 2020. Additionally, the equivalent factor method was employed to calculate the value of ecosystem services in Liaoning Province during the same period. Furthermore, by integrating the PLUS and Markov models with the actual conditions of Liaoning Province, four land-use development scenarios for 2030 were constructed, including natural development, economic priority, ecological protection, and cropland protection. The land-use distribution and the quantities and values of ecosystem services under these scenarios were simulated. The study revealed the following findings： ① From 2000 to 2020, carbon storage and soil retention in Liaoning Province showed an overall increasing trend, whereas water yield exhibited a fluctuating decrease trend initially, followed by an increase and then another decrease. ② Carbon storage and soil retention in Liaoning Province showed higher values in the eastern mountainous areas and western hilly regions, with lower values in the central region. Water yield showed a decreasing trend from east to west. ③ The value of ecosystem services increased from 547.94 billion yuan to 565.53 billion yuan, with a total increase of 17.58 billion yuan during the study period. All four types of services showed an increase, with cultural services experiencing the fastest change. ④ In 2030, carbon storage and soil retention in Liaoning Province decreased in all scenarios except for in the ecological protection scenario. Water yield increased only in the cropland protection scenario, whereas it decreased in the other three scenarios. The value of ecosystem services in the study area increased in all scenarios except for in the economic priority scenario.

Intermittent rhythmic delta activities are electroencephalographic discharges with uniform morphology, at a frequency of 4 Hz or less, containing at least six cycles, lost by eye opening and stimulation. These are called "plus" if concomitant theta or higher frequency rapid activity or spike, sharp wave activity is present. This group has a stronger relationship with epileptiform abnormality. We aimed to discuss the clinical presentations, and nomenclature of intermittent rhythmic delta activities with three case reports. [ABSTRACT FROM AUTHOR]

• Taking wetland city as an example, the prediction accuracy of land use change of FLUS, PLUS and CLUES was compared. • The prediction of all three models in land and fine wetland types has achieved high accuracy. • The prediction accuracy of FLUS and CLUES was higher and more stable, and the prediction results of PLUS were easy to appear unreasonable in space. With the development of social economy and the influence of human activities, land use has undergone great changes. Land use prediction models have gradually emerged for more rational planning and development of the region. This study took Changshu and Haikou, two wetland cities, as examples to explore the prediction effects of land and fine wetland types in PLUS, FLUS and CLUES models, and combined CA-Markov model to make a detailed summary of the composition, use requirements, advantages and disadvantages of each model. The results showed that: (1) From 2015 to 2020, the urban area in Changshu and Haikou showed a significant increase, with growth rates of 16.61% and 21.37%, respectively. However, the total area of wetland remained above 10%, which was not greatly affected; (2) The average overall accuracy of the PLUS, FLUS and CLUES models in the prediction of Changshu and Haikou was 0.85, 0.86, and 0.84, respectively, while Kappa was 0.79, 0.81, and 0.78, respectively. Especially, the prediction in the fine wetland types also achieved high accuracy. (3) FLUS and CLUES had more stable results in the comparison of spatial results, deviation on the prediction of some land use categories was easily born in PLUS. Each model has its own advantages and disadvantages in practical application and operation. The research results of this paper are intended to let more people understand different land use prediction models and provide reference basis for the improvement and application of the models. [ABSTRACT FROM AUTHOR]

Understanding the response of nature's contributions to people (NCP) to change in landscape stability may constrain and guide human modification of nature. However, the effects of landscape stability on NCP, in the context of active human modification, remain unclear. To address this issue, we chose the Wujiang River Basin in the Yangtze River Economic Belt of China as a study area and quantified landscape stability in 2000, 2010, and 2020 under different scenarios. Environmental protection and comprehensive development scenarios were simulated for 2030 using the patch-generating land use simulation (PLUS) model. For current and future scenarios, NCP were assessed in terms of indicators, which included habitat creation and maintenance (NCP1), regulation of freshwater (NCP6), and protection of soils (NCP8). Under the current status quo, urban expansion was 491.547 km2, and landscape stability showed a decreasing trend, with the mean value decreasing from 0.049 in 2000 to 0.015 in 2020. In future scenarios, landscape stability was highest under the comprehensive development scenario. In addition, in terms of changes in NCP, the high-value contributions declined by 16%–48% from 2000 to 2020. Our results clarified how NCP respond to landscape stability. These results can help conservation managers develop more targeted ecological strategies that will constrain human modification activities to enhance well-being. • Quantify the response of NCP under different stability conditions. • An indicator system for evaluating NCP stability was established. • Stability decreased, leading to loss of nature's beneficial contributions to people. [ABSTRACT FROM AUTHOR]

The rapid expansion of cities in tropical regions has triggered a series of problems such as the destruction of rare natural resources and decreases in the environmental resource carrying capacity and ecological security, which seriously threaten the sustainable development of tropical cities. In this study, the city of Sanya, Hainan, China, is taken as an example. A bottom-line ecological security pattern is constructed based on the remote sensing ecological index (RSEI) and the patch-generating land use simulation (PLUS) for urban growth boundary (UGB) delineation. The results show that Sanya has a good ecological background, but the overall ecological quality decreased from 2014 to 2018 due to the expansion of construction in hot spot areas. Under the natural growth scenario, the urban built-up area in Sanya in 2030 will be 73.81% greater than in 2018, mainly occupying a large amount of agricultural and ecological space, and urban expansion will not be effectively suppressed. Delineation of the UGBs combined with the ecological constraints can effectively protect the regional ecological security and control the urban sprawl, which is relatively consistent with the current planning. The results of this study demonstrate that the RSEI-PLUS-based UGB delineation perspective has a high scientific and applicability, and they provide a reference for the coordinated ecological–economic sustainable development of ecologically fragile cities in tropical areas.

Background: Patients with essential tremor were initially considered to have isolated tremor, but additional motor and non-motor features have been increasingly recognized. The term "essential tremor plus" was adopted by the Task Force on Tremor of the International Parkinson and Movement Disorder Society to describe essential tremor patients with additional neurologic signs. Objectives: To characterize essential tremor patients and their phenotypes in a movement disorders clinic population in the context of the new tremor classification. Methods: Demographic, clinical, historical, treatment, and diagnostic data were retrospectively collected on 300 patients diagnosed by movement disorder experts with essential tremor. Patients were classified as having essential tremor, essential tremor plus, or essential tremor-Parkinson's disease combination, and features between these groups were compared. Results: Of the 300 patients, 20.7% were classified as isolated essential tremor, 53.3% as essential tremor plus, and 26.0% as essential tremor-Parkinson's disease. There was no significant difference in the duration of tremor symptoms. Essential tremor plus patients were more likely to have dystonia, tandem gait abnormalities, head tremor and greater tremor severity. Essential tremor-Parkinson's disease patients were more likely to have RBD symptoms. There was no significant difference in cognitive impairment between essential tremor plus and essential tremor-Parkinson's disease patients. Conclusions: Additional motor and non-motor features, including parkinsonism, are common in patients with essential tremor. Further studies are needed to clarify essential tremor phenotypes and to provide insights into possible subtypes. Highlights: 300 patients with essential tremor from a movement disorders clinic were re-classified based on the Movement Disorder Society Consensus Statement on the Classification of Tremors. Additional motor and non-motor features, including parkinsonism, were common, and only 20.7% of patients remained classified as isolated essential tremor. [ABSTRACT FROM AUTHOR]