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The thin soil layer with uneven distribution in karst areas facilitates the migration of phosphorus (P) to groundwater, threatening the safety of water sources seriously. To offer a scientific guidance for water pollution control and land use planning in karst areas, this study examined the relationships between land use and P in groundwater and surface water, and quantified the phosphate sources in Gaoping river basin, a small typical watershed in karst areas. Spatial distribution analysis revealed that the highest mean P concentrations in groundwater and surface water were in farmland and construction-farmland zones, respectively. Land use impact analysis showed that the concentration of P in groundwater was influenced positively by farmland but negatively by forest land. In contrast, the concentration of P in surface water was influenced positively by both farmland and construction land. The mixed end-element and Bayesian-based Stable Isotope Analysis in R (SIAR) model results showed that agricultural fertilizers were the main phosphate source for groundwater in farmland and forest-farmland zones, while urban sewage was the main source in the construction-farmland zone. For surface water, the main phosphate source was agricultural fertilizers in both farmland and construction-farmland zones. This study indicates that controlling P pollution in local water bodies should pay close attention to the management of land use related to human activities, including regulating sewage discharge from construction land and agricultural fertilizer usage. [Display omitted] • Groundwater phosphorus concentration is positively correlated with the proportion of farmland. • Fertilizers and urban sewage were the main sources of groundwater phosphate. • The sources of ground and surface waters phosphate in the karst region were quantified using multiple models. [ABSTRACT FROM AUTHOR]

Northwest China has abundant solar energy resources and extensive land, making it a pivotal site for solar energy development. However, restrictions on site selection and severe weather conditions have hindered the establishment and operation of photovoltaic (PV) power stations. Previous studies have not considered meteorological factors when evaluating site suitability, leading to research gaps in identifying suitable areas and establishing indicator systems. We aimed to address these gaps by considering seven factors constraining the construction of centralized PV power stations (CPPS) and developing an indicator system based on terrain, climate, soil, and economic factors. Furthermore, we conducted analyses to quantify the solar energy generation potential (SEGP), carbon emissions reduction benefits, and land utilization potential at different sites. The findings indicate that areas rated as very suitable and extremely suitable comprised the largest proportion (62.35%) of site suitability. The correlation between site suitability and electricity consumption was largely non-significant, highlighting the need for enhanced coordination. Additionally, we forecast the electricity consumption in Xinjiang, Gansu, Inner Mongolia, Qinghai, Ningxia, and Shaanxi for 2030 to be 56.62, 19.86, 54.54, 13.59, 15.96, and 33.34 (× 1011 kWh), respectively, with corresponding carbon emissions reduction potentials of 20.2, 7.1, 19.4, 4.8, 5.7, and 11.9 (× 109 kg). Consequently, PV carbon reduction and land utilization potential are substantial. • Assessment of site suitability and carbon emissions reduction potential. • Development of improved site suitability map using comprehensive indicator system. • Gobi Desert shows high suitability for construction of photovoltaic power stations. • Solar energy generation can meet projected demand and reduce carbon emissions. [ABSTRACT FROM AUTHOR]

Biosphere Reserves (BR) manage large territories with diverse natural covers and land uses to preserve biodiversity, promote local development and preserve ecosystems. This study evaluated how their zoning (buffer and core) and policy timeframes (decree period, management plan period, and land planning period) influence four landscape management outcomes: deforestation, natural cover recovery, and anthropic and natural permanence. For three Mexican BR case studies, land use and cover transitions were calculated and compared to contrafactual sites. Observed rates of land cover change were marginal within all three BR zoning and across their policy timeframe (<0.02 % change rate), suggesting that BR effectively promote the permanence of both natural and anthropic covers. Nevertheless, the predicted probability of uncommon deforestation and recovery outcomes at local levels showed that the effect of a BR over its regulated landscape is not spatiotemporally static, contrasting the effect of individual allocation vs a group or network. Poverty, land tenure, agriculture aptitude and distance to markets adds to this dynamic and is modelled and discussed. This study shows that BR zoning schemes and its regulatory sequence influence the rates of land cover change and the predicted probability of landscape management outcomes across space and time. • Protected area effectiveness analyses is usually measured by curving deforestation. • It usually disregards other landscape management outcomes, regulatory periods and zoning. • Rates of land use and cover change and predicted probabilities on landscape management outcomes are complementary. • Poverty, land tenure, agriculture aptitude and distance to markets have heterogenous effects on coastal Biosphere Reserves. • The effect of Biosphere Reserves on the coastal landscape is not spatiotemporally static, but dynamic. [ABSTRACT FROM AUTHOR]

Rapid urbanization and industrialization have greatly contributed to boosting regional economic growth and mitigating the problem of poverty, but blind expansion of cities and towns has not only caused the inefficient use of urban land resources but also caused the deterioration in the urban ecological environment. Within the current context of emphasizing high-quality development, achieving synergy between the efficient use of urban land and ecological environmental protection is an urgent task for promoting new urbanization construction. In this study, cities in the upper reaches of the Yangtze River (URYR) were adopted as the research object, a theoretical analysis framework for the urban land use efficiency (ULUE) and ecological environment quality (EEQ) was established, the ULUE was measured by using the Slacks-Based Measure (SBM) model, the coupling coordination and interactive corresponding response relationship between the ULUE and EEQ were analyzed, and the influencing factors of the coupling coordination between these two systems were explored by using the random forest model. The following conclusions can be obtained: in 2020, compared with those in 2006, both the ULUE and EEQ were improved, and the two systems exhibited interactions and significant spatiotemporal heterogeneity. The coupling coordination degree (CCD) between the ULUE and EEQ could facilitate maintaining the original state, and the transfer of the CCD exhibited a significant spatial correlation with the state of neighbouring cities. The effect of the ULUE on the EEQ indicated nonlinear characteristics, while the effect of the EEQ on the ULUE was manifested as inhibition initially and then promotion. The random forest regression results showed that the population density, landscape agglomeration and connectivity, market conditions, government intervention, and industrial institutions are the key influencing factors of the CCD. Finally, this study provides policy implications for innovative urban land use modelling, environmental regulation, and industrial transformation and upgrading. • Put forward the framework of coupling coordination and interactive response between urban land use efficiency (ULUE) and ecological environment quality (EEQ) firstly. • Socio-economic and natural data were used to assess the ULUE. • The influencing factors of the coupling coordination between ULUE and EEQ were explored by using the random forest model. • Results can guide the implementation of land utilization and ecological protection. [ABSTRACT FROM AUTHOR]

Understanding particle size distribution (PSD) of total suspended sediments in urban runoff is essential for pollutant fate and designing effective stormwater treatment measures. However, the PSDs from different land uses under different weather conditions have yet to be sufficiently studied. This research conducted a six-year water sampling program in 15 study sites to analyze the PSD of total suspended sediments in runoff. The results revealed that the median particle size decreased in the order: paved residential, commercial, gravel lane residential, mixed land use, industrial, and roads. Fine particles less than 125 μm are the dominant particles (over 75%) of total suspended sediments in runoff in Calgary, Alberta, Canada. Roads have the largest percentage of particles finer than 32 μm (49%). Gravel lane residential areas have finer particle sizes than paved residential areas. The results of PSD were compared with previous literature to provide more comprehensive information about PSD from different land uses. The impact of rainfall event types can vary depending on land use types. A long antecedent dry period tends to result in the accumulation of fine particles on urban surfaces. High rainfall intensity and long duration can wash off more coarse particles. The PSD in spring exhibits the finest particles, while fall has the largest percentage of coarse particles. Snowmelt particles are finer for the same land use than that during rainfall events because the rainfall-runoff flows are usually larger than the snowmelt flows. • A six-year water sampling program was conducted to analyze particle size distribution. • Particle size distributions in runoff from six urban land uses were analyzed. • Fine particles are the dominant particles of suspended sediments in runoff. • Effects of rainfall types on particle size distributions vary with land use types. • Snowmelt particles are finer for the same land use than that of rainfall events. [ABSTRACT FROM AUTHOR]

Rural areas are the main source of ecosystem services in arid and semi-arid areas, and ecosystem services are the background conditions for rural revitalization. In this study, the spatial pattern of key ecosystem services in the countryside was assessed, and the trade-offs and synergistic relationships among ecosystem services were investigated, using the Tacheng-Emin Basin in China as the study area. Finally, the types of ecological function zoning and development strategies for the countryside are proposed. The results showed that: (1) the area of ecological land was large, and the average land use intensity was 2.48, which belonged to the medium intensity. (2) The mean values of the six ecosystem services are all in the middle and lower classes, and the spatial distribution of the five ecosystem services is similar, except for food production. (3) Except for grain production, the other five ecosystem services showed positive feedback to elevation. The other five ecosystem services are synergistic, and there are trade-offs between grain production and other ecosystem services. In the nonlinear interaction mechanism of ecosystem services, the fluctuation constraint occupies the largest proportion. (4) At smaller spatial scales, there are more types of ecosystem service clusters. Combining the results of the study, the villages in the study area can be categorized into five types. This study formulates five priority levels of rural ecological revitalization and proposes different development recommendations for the sustainable development of each type of village. This study is helpful for the fine management of land resources and the revitalization of rural ecology and provides a reference for the sustainable development of ecosystem services in arid and semi-arid areas. • A 10-m resolution land use map was created based on the Random Forest. • Mountains have high ecosystem service values in arid and semi-arid areas. • There are trade-offs between grain production and other services in the study area. • Multiple non-linear relationships exist between ecosystem services. • Ecosystem service clusters are most diverse at the rural scale. [ABSTRACT FROM AUTHOR]

Managing landscape change is increasingly challenging due to rapid anthropogenic shifts. A delicate balance must be struck between the environment and change to ensure landscapes can withstand these impacts. This study conducted in the Tunca River sub-basin of Edirne province, aims to assess landscape sensitivity by examining the influence of land use/land cover (LULC) and climate change on landscape function processes. For this purpose, a methodology was developed based on ecosystem services to determine landscape sensitivity. The results revealed a LULC transformation that could lead to a 60% reduction in forest areas and a 5% and 20% increase in urban and irrigated agricultural areas, respectively. Water and erosion emerged as the most affected landscape function processes. Future scenarios from 2050 to 2070 indicate noteworthy changes in landscape sensitivity, showing an increase in sensitivity in the upper regions of the basin. The study identified high sensitivity in forested areas, moderate sensitivity in agricultural zones, and low sensitivity in micro-basins near residential areas. Protection and improvement strategies are recommended for areas with high and moderate sensitivity, while use-oriented strategies are suggested for those with low sensitivity. This study also establishes a scientific foundation for guiding the protection and management of ecologically sensitive basin areas, offering insights into the effects of landscape change processes at the micro-basin level in connection with climate change models. • The landscape sensitivity framework provides the basis for landscape protection and use decisions. • Landscape sensitivity helps to identify ecologically problematic areas. • Increased urbanization reduces infiltration capacity. • In the 2070 scenario, low and moderate sensitivity micro-basins increase. • Sensitivity is projected to increase in the northern parts of the basin in the future. [ABSTRACT FROM AUTHOR]

Despite concerted efforts in emission control, air pollution control remains challenging. Urban planning has emerged as a crucial strategy for mitigating PM 2.5 pollution. What remains unclear is the impact of urban form and their interactions with seasonal changes. In this study, base on the air quality monitoring stations in the Yangtze River Delta urban agglomeration, the relationship between urban spatial indicators (building morphology and land use) and PM 2.5 concentrations was investigated using full subset regression and variance partitioning analysis, and seasonal differences were further analysed. Our findings reveal that PM 2.5 pollution exhibits different sensitivities to spatial scales, with higher sensitivity to the local microclimate formed by the three-dimensional structure of buildings at the local scale, while land use exerts greater influence at larger scales. Specifically, land use indicators contributed sustantially more to the PM 2.5 prediction model as buffer zone expand (from an average of 2.41% at 100 m range to 47.30% at 5000 m range), whereas building morphology indicators display an inverse trend (from an average of 13.84% at 100 m range to 1.88% at 5000 m range). These results enderscore the importance of considering building morphology in local-scale urban planning, where the increasing building height can significantly enhance the disperion of PM 2.5 pollution. Conversely, large-scale urban planning should prioritize the mixed use of green spaces and construction lands to mitigate PM 2.5 pollution. Moreover, the significant seasonal differences in the ralationship between urban spatical indicatiors and PM 2.5 pollution were observed. Particularly moteworthy is the heightened association between forest, water indicators and PM 2.5 concentrations in summer, indicating the urban forests may facilitate the formation of volatile compunds, exacerbating the PM 2.5 pollution. Our study provides a theoretical basis for addressing scale-related challenges in urban spatial planning, thereby forstering the sustainable development of cities. • Building structures significantly influence PM 2.5 locally, emphasizing the role of microclimates in pollution dynamics. • Land use's role in PM 2.5 pollution grows with buffer zone expansion, while building morphology's impact lessens over distance. • Urban forests, water indicators have a stronger link to PM 2.5 in summer, urging tailored planning for different seasons. [ABSTRACT FROM AUTHOR]

Future changes in land use/land cover (LULC) and climate (CC) affect watershed hydrology. Despite past research on estimating such changes, studies on the impacts of both these nonstationary stressors on urban watersheds have been limited. Urban watersheds have several important details such as hydraulic infrastructure that call for fine-scale models to predict the impacts of LULC and CC on watershed hydrology. In this paper, a fine-scale hydrologic model—Personal Computer Storm Water Management Model (PCSWMM)—was applied to predict the individual and joint impacts of LULC changes and CC on surface runoff attributes (peak and volume) in 3800 urban subwatersheds in Midwest Florida. The subwatersheds a range of characteristics in terms of drainage area, surface imperviousness, ground slope and LULC distribution. The PCSWMM also represented several hydraulic structures (e.g., ponds and pipes) across the subwatersheds. We analyzed changes in the runoff attributes to determine which stressor is most responsible for the changes and what subwatersheds are mostly sensitive to such changes. Six 24-h design rainfall events (5- to 200-year recurrence intervals) were studied under historical (2010) and future (year 2070) climate and LULC. We evaluated the response of the subwatersheds in terms of runoff peak and volume to the design rainfall events using the PCSWMM. The results indicated that, overall, CC has a greater impact on the runoff attributes than LULC change. We also found that LULC and climate induced changes in runoff are generally more pronounced in greater recurrence intervals and subwatersheds with smaller drainage areas and milder slopes. However, no relationship was found between the changes in runoff and original subwatershed imperviousness; this can be due to the small increase in urban land cover projected for the study area. This research helps urban planners and floodplain managers identify the required strategies to protect urban watersheds against future LULC change and CC. [Display omitted] • Changes in runoff attributes due to CC and LULC change in 3800 urban watersheds. • Greater changes for runoff peak than volume. • Greater changes in both runoff attributes for milder slope and smaller watersheds. • Dominant impacts of CC over LULC change for both runoff attribute. [ABSTRACT FROM AUTHOR]

Land use/land cover (LULC) can have significant impacts on water quality and the health of aquatic ecosystems. Consequently, understanding and quantifying the nature of these impacts is essential for the development of effective catchment management strategies. This article provides a critical review of the literature in which the use of statistical methods to model the impacts of LULC on water quality is demonstrated. A survey of these publications, which included hundreds of original research and review articles, revealed several common themes and findings. However, there are also several persistent knowledge gaps, areas of methodological uncertainty, and questions of application that require further study and clarification. These relate primarily to appropriate analytical scales, the significance of landscape configuration, the estimation and application of thresholds, as well as the potentially confounding influence of extraneous variables. Moreover, geographical bias in the published literature means that there is a need for further research in ecologically and climatically disparate regions, including in less developed countries of the Global South. The focus of this article is not to provide a technical review of statistical techniques themselves, but to examine important practical and methodological considerations in their application in modelling the impacts of LULC on water quality. [Display omitted] • Statistical methods are effective in modelling relationships between land use and water quality. • The results of reviewed studies have been remarkably consistent in several respects. • However, there remain several persistent knowledge gaps which require further research. • These relate to scale, landscape configuration, land use thresholds, and confounding variables. • There is a need for additional context-specific research, especially in developing countries. [ABSTRACT FROM AUTHOR]

Soil microbial biomass and activity strongly depend on land use, vegetation cover, climate, and soil physicochemical properties. In most cases, this dependence was assessed by one-to-one correlations while by employing network analysis, information about network robustness and the balance between stochasticity and determinism controlling connectivity, was revealed. In this study, we further elaborated on the hypothesis of Smith et al. (2021) that cropland soils depended more on climate variables and therefore are more vulnerable to climate change. We used the same dataset with that of Smith et al. (2021) that contains seasonal microbial, climate and soil variables collected from 881 soil points representing the main land uses in Europe: forests, grassland, cropland. We examined complete (both direct and indirect relationships) and incomplete networks (only direct relationships) and recorded higher robustness in the former. Partial Least Square results showed that on average more than 45% of microbial attributes' variability was predicted by climate and habitat drivers denoting medium to strong effect of habitat filtering. Network architecture slightly affected by season or land use type; it followed the core/periphery structure with positive and negative interactions and no hub nodes. Microbial attributes (biomass, activity and their ratio) mostly belong to core block together with Soil Organic Carbon (SOC), while climate and soil variables to periphery block with the exception of cropland networks, denoting the higher dependence between microbial and climate variables in these latter. All complete networks appeared robust except for cropland and forest in summer, a finding that disagrees with our initial hypothesis about cropland. Networks' connectivity was controlled stronger by stochasticity in forest than in croplands. The lack of human interventions in forest soils increase habitat homogeneity enhancing the influence of stochastic agents such as microbial unlimited dispersal and/or stochastic extinction. The increased stochasticity implies the necessity for proactive management actions. • Complete networks exhibited higher robustness than incomplete ones. • Cropland in summer and forest in autumn and summer exhibited the lowest robustness. • Connectivity of complete networks was controlled mostly by stochasticity than determinism. • Stochasticity was higher in forest (natural soil) than cropland (man-affected soils). • Stochasticity implies the necessity for more proactive management practices and less remedial actions. [ABSTRACT FROM AUTHOR]

Reducing soil erosion (SE) is crucial for achieving harmony between human society and the ecological environment. The cultivated land fragmentation (CLF), directly or indirectly, alters soil structure, diminishes its water-holding capacity, and escalates the risk of SE. Scientific assessment of the effect of CLF on SE can provide new insights into controlling of SE across watersheds in China. However, few studies have quantified the effect of CLF on SE. Therefore, we utilized land use change data in the Yangtze River basin from 2000 to 2020, measuring the levels of CLF and SE using Fragstats and InVEST models. The bivariate spatial autocorrelation model was employed to reveal the spatial relationship between CLF and SE. Additionally, we constructed a spatial Durbin model and introduced the geographically and temporally weighted regression model to analyze the role of CLF on SE. The south bank of the upper and middle reaches of the Yangtze River basin exhibited high CLF and SE. The bivariate spatial autocorrelation results showed a significant positive spatial correlation between CLF and SE. The spatial Durbin model results showed that CLF had a spatial spillover effect and time lag on SE, and the effect of CLF on SE had an inverted "N" curve. The study also confirmed that last SE and neighboring SE areas influenced local SE. Currently, CLF had a negative effect on SE in the Sichuan Basin, Yunnan-Guizhou Plateau, and the middle and lower Yangtze River Plain, and positively in Qinghai, Hunan, and Jiangxi provinces. These findings suggest that the government should enhance cross-regional and cross-sectoral cooperation and monitoring of cultivated land changes to prevent and control SE effectively. • Cultivated land fragmentation and soil erosion are increasing. • Cultivated land fragmentation has a dual spatio-temporal effect on soil erosion. • A nonlinear relationship between cultivated land fragmentation and soil erosion. • Cultivated land fragmentation inhibits soil erosion in a specific period. [ABSTRACT FROM AUTHOR]

Bisphenol analogues (BPs) have gained increasing attention in recent years due to their ubiquitousness and potential endocrine disrupting properties in environments. However, little information is available on their spatiotemporal distribution, source apportionment and ecological risk in river sediments, especially the case in river basins with a high population density and those typical regions with agricultural-urban gradient, where land use patterns and intensity of human activity are varying. In this study, field investigations of BPs in the sediment of the entire Qinhuai River Basin, a typical agricultural-suburban agricultural-urban gradient area, were conducted before and after the flood period. Thirty-two sites were sampled for six types of BPs, resulted in no significant difference in the concentration of ΣBPs between the two periods, with ΣBPs ranging from 3.92 to 151 ng/g and 2.16–59.0 ng/g, respectively. Bisphenol A (BPA) was the main contributor. Whereas a multivariate analysis of variance (MANOVA) suggested that the composition structure of BPs had been influenced by water periods. The land use patterns had an impact on the distribution of ΣBPs in river sediments, which was more significant in after the flood period, with ΣBPs in urban rivers was 1.85 times, 3.44 times, and 3.08 times higher than the suburban rivers, agricultural rivers, and reservoirs, respectively. Yet land use types did not significantly alter the composition structure of BPs. The correlation analysis between BPs and the physicochemical properties of sediments showed a significant positive correlation between BPA and total organic carbon (TOC). The positive matrix factorization model (PMF) suggested that BPs in sediments of the basin might be influenced by industrial coatings, textiles, electronics and biopharmaceuticals, as well as urban wastewater or solid waste generated from daily life. The ecological risk assessment posed by BPA, based on the risk quotient, indicated that the ecological risk of BPA in sediments was low for three indicator benthic organisms: crustaceans, worms, and mollusks. However, the risk of BPA in river sediments varied among different land use patterns, with the risk ranking as follows: reservoirs < agricultural rivers < suburban rivers < urban rivers. [Display omitted] • ΣBPs was no significantly between the two periods, BPA was the main contributor. • The land use patterns had an impact on the distribution of BPs in river sediments. • ΣBPs, BPA, and total organic carbon observed a significant positive correlation. • Three key sources of BPs were identified in the QRB based on the PMF model. • BPA posed low risk for benthic animals but varied across land use patterns. [ABSTRACT FROM AUTHOR]

This study offers a first-of-its-kind investigation into the spatial and temporal transformation of agricultural land use and expansion in crops and livestock at national scale during the middle and latter half of the 19th century. We introduce an innovative methodological framework that combines historical data with advanced spatial analysis to trace and map the evolution of frontiers of agricultural land use changes, illustrating Denmark's agricultural evolution towards the modern era. Our research uncovers critical shifts in cropland, grazing land, and livestock density offering unprecedented insights into the mechanisms driving agricultural expansion and intensification. The mechanisms driving this expansion and their potential impact on contemporary agroecological challenges linked to land use intensification are explored. Our results point to a significant broadening and shifting of land use frontiers offering a historical perspective on agricultural land use. This sets the stage for promoting the analysis of drivers of change and gaining insights into how landscape development could be steered into an environmentally and societally more desirable and sustainable direction tackling present-day agroecological challenges. • We studied spatial and temporal patterns of agricultural frontiers. • Significant trends shed light on the evolving landscape of agricultural production. • Two distinct frontiers of agricultural land use are identified. • Over time, land use categories shift towards higher homogeneity. [ABSTRACT FROM AUTHOR]

With the extensive industrialization and urbanization taking place in China during the recent decades, land use throughout the country has experienced profound changes influenced not only by the demand for population growth and living standard improvement but also by the constraints of series of land use policies. However, whether the conflict between the expansion of settlement land (SL) and the loss of cultivated land (CL) have been resolved at the national scale or transferred between the local regions remains unclear. Based on yearly ESA CCI land use and land cover products from 1992 to 2020, the long-term trends of quantity and spatial pattern of SL expansion and CL change in China from national and local views were investigated using trend statistic methods, and finally a comprehensive zoning framework was proposed to recognize the trade-off and synergies relationships between SL expansion and CL change. There are a continuous expansion of SL with global linear trends showing three breakpoints in 2000, 2005, and 2012, and a fluctuation decline of CL presented with four breakpoints in 1997, 2002, 2006, and 2013. Aggregation and dispersion tendencies with linear characteristics of SL expansion and CL change were found with breakpoints in 2001, 2008, 2012, and 2016 and breakpoints in 2001 and 2010, respectively. A spotty spatial pattern of SL was shown spatially coincident with urban agglomerations in China while the planar continuous characteristic was found for CL. Local counties were classified into five tradeoff and synergies zones (TSZs), where general synergies (G-S) and decoupling (D) of SL expansion and CL change were rare cases and the different change in quantity and trend of SL expansion and CL change in local counties was concealed by the national trend. A few scattered counties were belonging to G-S and D TSZs, while most of the counties in the central-east and western China were in General-Tradeoff (G-T) and Superior-Tradeoff (S-T) TSZs. Counties in south and north China with higher percentages of CL were more prevalent in Superior-Synergy (S–S) TSZ. Our findings explicated the complex relationships between SL expansion and CL change of China at the national scale and in local counties, which pointed out the differences of unified land use management activities across scales and could provide insights for future policy-making and management measures of land use to both ensure the national food security and promote regional sustainable development more synchronously. [Display omitted] • A nearly 3.2 times settlements expansion presented linear trends in global China. • Cultivated land change witnessed fluctuations with a total decrease by ∼0.83%. • Local settlements expansion and cultivated land change are spatially diverse. • Aggregation and dispersion were found in settlements and cultivated land change. • Counties in China were classified into five tradeoff and synergies zones (TSZs). [ABSTRACT FROM AUTHOR]

The application of life cycle assessment (LCA) to biorefineries is a necessary step to estimate their environmental sustainability. This review explores contemporary LCA biorefinery studies, across different feedstock categories, to understand approaches in dealing with key methodological decisions which arise, including system boundaries, consequential or attributional approach, allocation, inventory data, land use changes, product end-of-life (EOL), biogenic carbon storage, impact assessment and use of uncertainty analysis. From an initial collection of 81 studies, 59 were included within the final analysis, comprising 22 studies which involved dedicated feedstocks, 34 which involved residue feedstocks (including by-products and wastes), and a further 3 studies which involved multiple feedstocks derived from both dedicated and secondary sources. Many studies do not provide a comprehensive LCA assessment, often lacking detail on decisions taken, omitting key parts of the value chain, using generic data without uncertainty analyses, or omitting important impact categories. Only 28% of studies included some level of primary data, while 39% of studies did not undertake an uncertainty or sensitivity analysis. Just 8% of studies included data related to dLUC with a further 8% including iLUC, and only 14% of studies considering product end of life within their scope. The authors recommend more transparency in biorefinery LCA, with justification of key methodological decisions. A full value-chain approach should be adopted, to fully assess burdens and opportunities for biogenic carbon storage. We also propose a more prospective approach, taking into account future use of renewable energy sources, and opportunities for increasing circularity within bio-based value chains. [Display omitted] • 59 studies were included in the analysis of biorefinery LCA's. • Review compared biorefinery LCA's as applied to dedicated and residue feedstocks. • Many studies lack detail on decisions taken, omit key parts of the value chain, use generic data without uncertainty analyses, or exclude important impact categories.. • Factors like biogenic carbon storage and iLUC typically not fully evaluated. • Circularity, future renewable energy, and carbon capture and utilisation lacking. [ABSTRACT FROM AUTHOR]

Increasing soil organic carbon (SOC) content is crucial for soil fertility, conservation, and combating climate-related issues by sequestering CO 2. While existing studies explore the total content of SOC, few of them investigate the factors that favor its sequestration and the impact of land use type and management. This research aims to study the spatial variation of the total content and the quality or maturity (in terms of aromaticity) of the humic acid (HA) fraction, along with the factors that enhance its formation and conservation for a longer time in the soil. In addition, the study tries to evaluate the performance of the Regression Kriging (RK) method in producing interpolation maps that describe the natural variation of the SOC and its quality with the aim of defining and preventing soil degradation. Finally, the study aims to evaluate the impact of the land use type and the importance of dense vegetation in the sequestration of the organic carbon (OC) in the soil. The analysis of the SOC was performed in northeast Algeria's semi-arid climate, examining content, quality, and chemical composition. Using geostatistical methods (RK), SOC is correlated with most related factors, producing detailed interpolation maps. The results showed that the SOC and its HA fraction (both its total content and its degree of transformation or maturity (measured in terms of aromaticity and structural condensation) are highly correlated to the topography of the area (P < 0.05). Results reveal variations in HAs' composition across land covers. Notably, areas subjected to burning exhibited a 21% increase in HA aromaticity compared to forested regions and a 29% increase relative to cultivated areas. The study highlights that soil cover has a substantial influence on the performance of SOC sequestration, the forested areas have a positive impact on the storage of SOC in the form of HA with a more complex chemical composition that suggests increased aromaticity and resilience. As a whole, the results indicate the potential of geostatistical methods to provide valuable information about the factors that influence the current status and evolution of SOC in the study area. [Display omitted] • Humic acids are used as an indicator of soil organic carbon quality. • The chemical composition of soil organic carbon controls its sequestration. • Soil organic carbon sequestration is considerably affected by land cover. • Soil organic matter rich in aromatic structures is promoted by wildfires and erosion. • The interpolation of soil organic carbon stocks can be improved through regression kriging. [ABSTRACT FROM AUTHOR]

Urbanization changes land cover through the expansion of impermeable surfaces, leading to a significant rise in runoff, sediment, and nutrient loading. The quality of stormwater is related to land use and is highly variable. Currently, stormwater is predominantly described through watershed models that rely minimally, if at all, on field monitoring data. The simple event mean concentration (EMC) wash-off approach by land use is a common method for estimating urban runoff loads. However, a major drawback of the EMC approach is it assumes concentration remains constant across events for a specific land use. Build-up/wash-off equations have been formulated to consider variations in concentration between events. However, several equation parameters are challenging to estimate, making them difficult to use. We conducted a monitoring and modeling study and investigated the impact of land use on stormwater quantity and quality and optimized and investigated the build-up/wash-off parameters for three homogenous urban land uses to estimate nutrients (nitrogen and phosphorus) and sediment loads. Stormwater from commercial, medium-density residential, and transportation land uses was sampled using automatic samplers during storm events, and water quality was characterized for a variety of them for 14 months. Analysis of stormwater samples included assessments for total nitrogen, total phosphorus, and total suspended solids. Results showed that medium-density residential land use had the highest median total nitrogen and total phosphorus event mean concentrations and commercial had the highest median total suspended solids EMCs. Water quality parameters (or build-up/wash-off parameters) exhibited significant variation between land uses, confirming that land use is a key determinant of stormwater quality. The median particle size for each land use was less than 150 μm, indicating that the most common particle size in stormwater was a very fine sand or smaller. This small size should be considered by stakeholders in the design of stormwater treatment systems. [Display omitted] • A monitoring and modeling program was conducted for three urban land uses. • The medium-density residential subcatchment had greater TN and TP EMCs. • An equation relating EMC to build-up wash-off parameters was developed. • Observed EMCs varied across events, reflecting the impact of rainfall characteristics. • The build-up/wash-off relationship considers event-specific variation. [ABSTRACT FROM AUTHOR]

Microplastic pollution in the soil environment is of great concern. However, the current research on microplastics (MPs) in Southwest China mainly focuses on their distribution characteristics and sources in soil, making the understanding of the soil properties and land use patterns influencing soil MPs insufficient. In this study, the abundance and distribution characteristics of MPs in the soil of different land use patterns in Guizhou Province were determined. The results revealed that the average abundance of MPs in soils was 2936 items/kg, ranging from 780 to 9420 items/kg. The MPs were mainly small particle size (0–0.5 mm), granular, and black, accounting for 87.5%, 36.6%, and 82.2%, respectively. The most common polymer types of MPs were polypropylene, polyethylene terephthalate, and polyethylene, which accounted for 20.4%, 16.8%, and 16.4%, respectively. As soil bulk density increased, microplastic abundance and small particle size decreased. Soil microplastic abundance slightly decreased with increasing soil porosity. The abundance of MPs increased with the increase in soil pH, but no significant correlation was observed between soil organic matter content and microplastic abundance. pH was the major factor that affected the microplastic distribution, which accounted for 32.5%. This study provides insight into the distribution and influencing factors of soil MPs and also provides a theoretical basis for subsequent research on soil microplastic pollution. [Display omitted] • The abundance of MPs in soil was ranged from 780 to 9420 items/kg. • The major factor affecting microplastic distribution in soils was pH. • pH was positively correlated with the abundance of MPs in soil. • Soil bulk density was negatively associated with the abundance of MPs in soil. • The distribution of MPs was closely related to soil properties. [ABSTRACT FROM AUTHOR]

Global land resources are over-exploited and natural habitats are declining, often driven by expanding livestock production. In Ireland, pastureland for grazing cattle and sheep account for circa 60% of terrestrial land use. The agriculture, forestry and other land use sector (AFOLU) is responsible for 44% of national greenhouse gas (GHG) emissions. A new Grassland Animal response Model (GLAM) was developed to relate livestock-cohort grass and feed requirements to farm-grassland system areas, enhancing environmental assessment of prospective AFOLU configurations. Although land conversion targets are often well-defined, they tend to lack a clear definition of where land sparing can occur. Through analyses of 10 scenarios of milk and beef production and management strategies, we found that displacing beef cows with dairy cows can increase national protein output while sparing up to 0.75 million ha (18%) of grassland (albeit with a minor increase in overseas land requirement for additional concentrate feed). Reducing slaughter age, increasing exports of male dairy calves and increasing grassland use efficiency on beef farms each achieved between 0.19 and 0.32 million ha of land sparing. Sexed semen to achieve more favourable male-female birth ratios had a minor impact. GHG emissions, ammonia emissions and nutrient leaching were only reduced substantially when overall cattle numbers declined, confirming the need for cattle reductions to achieve environmental objectives. Nonetheless, application of GLAM shows potential for improved grass and cattle management to spare good quality land suitable for productive forestry and wetland restoration. This change is urgently needed to generate scalable carbon dioxide removals from the land sector in Ireland, and globally. [Display omitted] • GLAM models land requirements of changing herd dynamics in livestock systems. • Land & environmental impacts of protein output vary in cattle production strategies. • Up to 18% of Irish grassland can be spared without reducing total protein production. • GHG emission reductions across studied scenarios fall far short of climate targets. • Translating bio-physical potential to reality will require careful policy intervention. [ABSTRACT FROM AUTHOR]

The licensed cannabis industry represents one of the top five most economically valued agricultural commodities in California, yet farming largely remains on remote, environmentally sensitive, "marginal" lands. Using mixed methods, this paper examines the determinants of this marginalization, their embedded elaboration, and their relation to historical policy regimes. We used Generalized Additive Models (GAMs) to determine the most important predictors of licensed cannabis industry development since the inception of a statewide licensing program in 2018 and to compare the distribution of licensed cannabis to other forms of rural agriculture, including vineyards and pasture, to understand landscape factors and environmental sensitivity of land uses. We found that a county's median income and the extent of traditional (non-cannabis) agriculture, as measured by the proportion of on-farm (non-cannabis) employment, were both negatively associated with its amount of licensed cannabis agriculture. Ethnographic data suggests that cannabis is often excluded from traditional agricultural areas, through formal local-level bans, restrictive zoning, high "prime" farmland values, and cultural exclusions from other powerful resource users. The resulting relegation to "marginal" lands foments conflicts with amenity land users and environmentalists, even as it partly supports "legacy" cultivators whose farms were established under prior policy regimes. Results suggest that cannabis is more likely to be grown under conditions that introduce regulatory hurdles, including farming on steeper slopes, with natural streams onsite, and without access to large groundwater aquifers for irrigation. Our findings suggest that failure to allow licensed cannabis farming in traditional agriculture regions has led to a self-fulfilling prophecy wherein cannabis cultivation is largely relegated to environmentally sensitive areas where cultivation activity has an elevated tendency for environmental impacts. • Cannabis cultivation occurs outside conventional agricultural areas on "marginal" land. • Counties with higher incomes and more traditional agriculture issue fewer licenses. • Non-cannabis land users drive cannabis licensing restrictions. • Marginalization of cannabis produces environmental conflict and marginalizes farmers. • Marginal land use is socially and geographically produced. [ABSTRACT FROM AUTHOR]

By identifying Earth heritage sites, UNESCO Global Geoparks (UGGps) have promoted geo-tourism and regional economic prosperity. However, commercial and tourism development has altered the natural contexts of these geoparks, diminishing their initial value. Before implementing land use policies, spatial landscape parameters should be monitored in multiple dimensions and in real time. This study aims to develop Bilateral Segmentation Network (BiSeNet) models employing an upgraded U-structured neural network in order to monitor land use/cover changes and landscape indicators in a Vietnamese UGGp. This network has proven effective at preserving input image data and restricting the loss of spatial information in decoding data. To demonstrate the utility of deep learning, eight trained BiSeNet models were evaluated against Maximum Likelihood, Support Vector Machine, and Random Forest. The trained BSN-Nadam model (128x128), with a precision of 94% and an information loss of 0.1, can become a valuable instrument for analyzing and monitoring monthly changes in land uses/covers once tourism activities have been rapidly expanded. Three tourist routes and 41 locations in the Dak Nong UGGp were monitored for 30 years using three landscape indices: Disjunct Core Area Density (DCAD), Total Edge Contrast Index (TECI), Shannon's Diversity Index (SHDI), based on the results of the model. As a result, 18 identified geo-sites in the Daknong Geopark have been influenced significantly by agricultural and tourist activities since 2010, making these sites less uniform and unsustainable management. It promptly alerts UNESCO management to the deterioration of geological sites caused by urbanization and tourist development. • Eight BiSeNet model to classify basalt land uses/covers and landscape assessment were developed. • Performance of BiSeNet using input size of 128x128 with Nadam optimizer is highest. • Three different indices including DCAD, TECI, and SHDI were chosen to assess landscape quality. • Outcomes of BiSeNet models are used effectively to monitor different landscape indices. • Landscape quality in 41 geosites of Dak Nong UGGp was monitored over 30 years. [ABSTRACT FROM AUTHOR]

Modeling the long-term trends of contaminants in topsoil under controlled measures is critical for sustainable agricultural environmental management. Traditional mass balance equations cannot predict spatial variation and exchange flux of regional soil contaminants for it lacks a method of assigning input-output parameters to each simulated cell. To overcome this limitation, we allocate the estimated source contribution flux to the spatial grid cell in the regional chemical mass balance by integrated positive matrix factorization (P-RCMB) with historical trends quantification. Focusing on Cd and As, which are elements with elevated risks of food intake and volatilization/infiltration, the model is applied to 30 ha of agricultural land near the enterprise. Predictions indicate an additional 13.5% of the soil is contaminated, and approximately 2.57 ha may accrue after 100 years at the site, with an uncertainty range of 0.98–5.3 ha. Clean water irrigation (CWI) reduces contamination expansion by approximately 42%, including approximately 4813 g ha−1 yr−1 net As infiltration, playing a dominant role in preventing the formation of severely contaminated soil. Stop straw return, green fertilizers use, and reduced atmospheric deposition control the exchange flux of Cd (114.9 g ha−1 yr−1) in moderate/slight contamination areas. For the different contaminants' cumulative trends in dryland and paddy fields, achieving a net cumulative flux close to zero in marginally contaminated areas presents a viable approach to optimize current emission standards. if trade-off straw removal and additional fertilizer inputs, a straw return rate of approximately 40% in Cd-contaminated soil will yield overall benefits. This model contributes valuable insights and tools for policymaking in contaminated land sustainable utilization and emission standard optimization. [Display omitted] • A regionalized chemical mass balance model based on positive matrix factorization. • Cd and As infiltration led by irrigation causes heavily contaminated areas. • Marginal net flux change can be used as an indicator of optimal emission limits. • Straw removal is not always correct under the trade-off of additional fertilizer. [ABSTRACT FROM AUTHOR]

Soil aggregates are essential functional units involved in soil carbon sequestration, particularly in saline-sodic soils prone to severe carbon loss. In the present study, the distribution of aggregate-associated carbon fractions and their influencing factors were investigated after artificial utilization of saline soil in the Songnen Plain, Northeast China. Physicochemical properties, enzymatic activities, and bacterial communities were measured in various hierarchical aggregates among two natural land-use types (saline wasteland and degraded grassland) and three anthropogenic land-use types (artificial forest, upland field, and paddy field). The results indicated that, compared to saline wasteland, anthropogenic land use was witnessed an increase in macroaggregate proportions, and PF in large macroaggregates increased the most, while UF and FL were mainly increased in small macroaggregates. After transforming from natural land to anthropogenic land, the aggregate-associated carbon fractions (total organic carbon, readily soluble organic carbon, dissolved organic carbon, and microbial biomass carbon) increased, especially in small macroaggregates. All enzyme activities increased after artificial utilization, hydrolase (urease, amylase, and invertase), catalase, and β-glucosidase activities were highest in the small macroaggregates. Bacterial biomass was increased in all three aggregate types compared to natural land. Due to the influence of various factors on soil carbon storage, through partial least squares path modeling revealed that large macroaggregates were conducive to carbon storage. These findings suggested that artificial utilization of saline soil can increase large macroaggregate proportions and the abundance of aggregate-associated carbon, resulting in increased soil carbon stocks, with PF having the greatest carbon sequestration capacity. [Display omitted] • Artificial utilization of saline soil increased macroaggregate proportions. • Artificial utilization also increased the abundance of aggregate-associated carbon. • Land-use alteration changed the soil enzyme activities and microbial biomass. • Anthropogenic use of saline soils enhances the soil carbon stock capacity. [ABSTRACT FROM AUTHOR]

Wind power is one of the fastest growing renewable energy sectors and plays a focal role in the transition to a fossil fuel free society in Europe. Technological developments have enabled the construction of turbines within forested areas, which has raised concerns regarding the audio-visual impact on these landscapes. However, there is a paucity of research with regard to the role that forests may play in mitigating the negative impacts of wind farms. In this study, we created a simplified model for noise attenuation based on the ISO 9613-2 and Nord2000 noise models and a visibility model which both relates the audio-visual effect to forest stand structure and applied them in the GIS environment. Our findings suggest that forests can act as effective noise barriers, with the sound attenuation level dependent on the distance that sound travels through the forest, as well as the size and density of the trees. However, in the case of a high elevation sound source (such as wind turbines), the forest begins to act as a noise shield from a distance of between 500 and 1500 m, depending on the height of the forest and the land topography. While current noise models do not consider the impact of tree species, our visibility model accounts for tree size, density and species, as well as understorey and thinning. Our results indicate that spruce trees provide a better visual constraint whereas visibility distances within mature Calluna -type pine forests tend to be more extensive. Both models include variables that can be adjusted by forest management, thereby allowing integration with forest planning software. Overall, this study presents indicative methods for the evaluation of potential forest landscape shields, a concept that could have broad applications, including Landscape Value Trading. • Forest can potentially provide additional noise attenuation of up to 10 dB. • Forest stands can serve as landscape shields effectively reducing visual disturbances. • Integrating noise and visibility models into forest management planning is feasible. [ABSTRACT FROM AUTHOR]

Urban land is a fundamental but scarce resource that carries intensive human socio-economic activities. The demographic decline and housing vacancy issues that emerged with de-industrialization have raised concerns regarding the sustainable utilization of urban land resources, particularly in the American Rust Belt region. In this context, a comprehensive analysis of industrial land use can offer valuable insights to support the sustainable planning of shrinking cities. However, existing urban land research exhibits insufficient resolution at the sectoral scale and impedes the evaluation of industrial land use efficiency within the urban context. To address this gap, we established an integrated land use estimation framework for economic sectors based on multi-source data, which enables the assessment of land use efficiency at a finer sectoral scale. The method was then applied to the city of Detroit, Cleveland, and Pittsburgh. The results demonstrate that the current industrial land mix in the three cities is dominated by service-providing industries, but the land usage by goods-producing sectors in these cities presents a relatively high level of efficiency. The Moran's I value indicates a clustered tendency for the main economic sectors. The land use area results reveal that Other Services occupies the most land area in Detroit (2.29 million m2) and Cleveland (2.04 million m2). While in Pittsburgh, Professional Scientific and Technical Services (1.44 million m2) is the largest. In terms of the economic output, Management of Companies and Enterprises is the most efficient sector in Detroit (20.28 thousand $/m2) and Cleveland (29.43 thousand $/m2), while Pittsburgh's Public Administration (11.73 thousand $/m2) is the most efficient. As many other cities in the world are about to enter the era of de-industrialization or low growth, the outcomes can also serve as a reference to guide their sustainable revitalization in line with the SDGs. • A block-level model is proposed to estimate economic sector land use. • Service-providing industries dominate current land use in selected rust cities. • Management of Companies and Enterprises has the highest land use efficiency. • The findings can contribute to the sustainable revitalization of shrinking cities. [ABSTRACT FROM AUTHOR]

China's 2060 carbon neutrality goal has significant implications for energy, water, and land systems. However, the multi-sector dynamics among China's energy-water-land system have rarely been examined explicitly. This study adopts an integrated assessment framework to simulate China's energy-water-land system co-evolution under alternative carbon neutrality scenarios and climate impacts. Results show that although the net zero emission target provides the incentive for the energy system to move away from fossil fuels, total water withdrawal will increase due to the deployment of nuclear, bioenergy, and coal power plants with carbon capture and storage. Diversifying the negative emission technologies, by leveraging direct air capture technology, can alleviate the potential water stress and land use conflicts, which would otherwise be exacerbated by large-scale deployment of afforestation and bioenergy with carbon capture and storage. Northwest and northeast regions of China are the hotspots experiencing water withdrawal increases, while Bohai Rim and coastal regions are identified to experience fierce land competition. This study demonstrates the potential for general applicability to carry out resource planning and policy evaluation from the multi-sector coordination perspective. • Water-intensive electricity generation technologies drive up water withdrawal. • Diversifying negative emission technologies can reduce the impacts on water system. • Climate policy imposes more significant impacts than climate change. • Water withdrawal increases concentrate in Northwestern and Northeastern China. • Land competition mostly occurs in China's population-dense area. [ABSTRACT FROM AUTHOR]

Bees are primary pollinators across various terrestrial biomes and rely heavily on floral resources for sustenance. The composition of landscapes can influence bee foraging behavior, while human activities can directly affect both the composition and nutritional value of bee food. We aimed to assess how landscape structure and land use practices can impact the composition and nutritional value of food sources for two generalist social bee species, Apis mellifera and Scaptotrigona postica. Food samples were collected from twenty-five colonies of A. mellifera and thirteen of S. postica to examine how food composition and nutritional value may vary based on the extent of human land use and the composition of landscapes surrounding beekeeping sites. The pollen composition and nutritional value of A. mellifera were influenced by both land use practices and landscape heterogeneity. The number of patches determined total sugar and lipid content. Landscape heterogeneity affected pollen composition in S. postica , primarily due to the number of patches, while total sugar was affected by landscape diversity. Pollen nutritional value in S. postica was linked to land use, mainly meadow and vegetation, which influenced total sugar and dry matter. S. postica showed a higher sensitivity to land use changes compared to A. mellifera , which was more affected by landscape heterogeneity. Assuring landscape heterogeneity by preserving remaining forest patches around apiaries and meliponaries is crucial. Thoughtful land use planning is essential to support beekeeping activities and ensure an adequate quantity and quality of bee food resources. • Land use affects the composition and nutritional value of the food used by bees. • Biodiversity ensures food supply and variety of foraging options for bees. • Native Scaptotrigona postica is more sensitive to land use than exotic Apis mellifera. • In land use, the health of bee populations that promote pollination must be priority. • Beekeepers must ensure that bees have access to enough, diverse and quality food. [ABSTRACT FROM AUTHOR]

Lands and waters administered by governing entities for public use (i.e., "public lands") are subject to changing social and ecological conditions (e.g., overcrowding, drought). Public lands managers are often tasked with addressing these changes while balancing conservation goals and public use mandates, and their decisions can significantly and inequitably impact visitor sensitivities to different types of exposures. To gain insights into visitor sensitivities and their adaptive capacity to mitigate the impacts of exposures, we draw upon a comprehensive monitoring effort conducted in collaboration with the U.S. Fish and Wildlife Service (Service) to understand visitor experiences on national wildlife refuges (refuges). We collected data from 10,556 visitors to 68 refuges during 2018–2019, then segmented respondents into unique visitor types based on their frequency of visiting "this refuge" where they were contacted, their participation across different activities at that refuge, and visits to other public lands for purposes of their primary activity, all during the 12 months prior to being contacted. We then explored differences among the resulting visitor types in their (a) purpose of visit, (b) satisfaction with opportunities during their visit, and (c) demographic characteristics. Finally, we used external data sources to explore the sensitivities and adaptive capacity of visitors' home communities. Our approach identified eight types of visitors with distinct sensitivities and adaptive capacities. For example, the type categorized as "most sensitive" due to activity specialization and site dependency was more likely to engage in activities (e.g., fishing, hunting) that may be subsistence uses of public lands and more often lived in communities with reduced adaptive capacity. Our assessment supports public lands decision-making by helping to understand and address social inequities that may arise or be exacerbated by rapidly changing conditions. • Sensitivities to exposures depend on why , and to and from where people visit. • "Most sensitive" visitors were more likely to engage in potential subsistence uses. • "Most sensitive" visitors also lived in more socially vulnerable home communities. • Visitors who substituted activity and site demonstrated higher adaptive capacity. • Understanding visitor sensitivities can improve planning and decision-making. [ABSTRACT FROM AUTHOR]

Predicting the future distribution of coastal wetlands and characterizing changes in the area of wetlands between historical and future periods are important for the formulation of wetland conservation and management plans. Here, we used a cellular automata–Markov model and satellite images to simulate the future distribution of coastal wetlands under the business-as-usual scenario (BAU) and ecological protection scenario (EP) along the Yellow and Bohai Seas in China; we also explored historical (from 1990 to 2020) and future (from 2020 to 2050) changes in wetlands and the factors driving these changes. We found that the area of tidal flats gradually decreased because of increases in the area of saltpans, and the aquaculture area increased because of land reclamation and the invasion of Spartina alterniflora ; most of the tidal flat area was fragmented into multiple small patches. If the current rate of degradation continues (BAU), the area of tidal flats will decrease by 21.25%, and the area of saltpans and aquaculture will increase by 13.83% and 21.25%, respectively. By contrast, under EP, the area of tidal flats will increase by 13.81%, and this increase will mainly stem from the conversion of areas with S. alterniflora (174.49 km2, 33.22%) to aquaculture areas (155.17 km2, 29.54%). Clear differences between historical and future periods were observed among Liaohe Estuary, Bohai Bay, Laizhou Bay, and the Yancheng–Nantong coasts. Land reclamation is the main factor inducing changes in the area of tidal flats, saltpans, and aquaculture in Liaohe Estuary, Bohai Bay, and Laizhou Bay. Land reclamation and the S. alterniflora invasion both affect the distribution of wetlands along the Yancheng–Nantong coasts. [Display omitted] • Predicted coastal wetlands patterns in 2020–2050 under two scenarios. • Explored historical and future coastal wetlands change from 1990 to 2050. • Tidal flats increase with policy conservation while decrease without any measures. • Coastal wetlands prediction will help planners for better management. [ABSTRACT FROM AUTHOR]

Urbanisation is a key aspect of land use change (LUC), and accurately modelling of urban LUC is crucial for sustainable development. Cellular automata (CA) are widely used in LUC research. However, previous studies have overlooked the significant temporal dependence and spatial heterogeneity associated with LUC. To address these gaps, this study proposes a novel model called KCLP-CA, which integrates k-means, a convolutional neural network (CNN), a long and short-term memory neural network (LSTM), and the popular patch-generation land use model (PLUS). Initially, k-means and CNN are utilised to address spatial heterogeneity, while LSTM tackles temporal dependence. The LSTM and land expansion analysis strategy (LEAS) models of PLUS are employed to obtain land use conversion probability maps. Finally, a simulation of land use dynamic change was conducted using a linear weighted fusion conversion probability map that accounts for random factors. To validate the KCLP-CA model, land use data collected from Hangzhou between 1995 and 2000 were employed. The results showed that the KCLP-CA model outperformed traditional methods, including artificial neural networks and random forest model, with the figure of merit (FoM) index increasing from 2.12% to 4.19%. Random forest analysis of drivers impacting LUC revealed that distance to water and road network density exerted the greatest influence on urban land development in Hangzhou. Incorporation of various policy planning factors affecting urban development yielded simulation results aligning more closely with reality, resulting in a FoM index increase of 1.64–1.76%. In summary, the model developed in this study combines the strengths of two sub models to deliver an accurate and effective simulation of future land use. [Display omitted] • Effects of spatiotemporal dependence on land use change were studied. • A novel KCLP-CA model was proposed in this study. • This model effectively combines the advantages of the KCL-CA and PLUS models. • Improved simulation outcomes were observed when the KCLP-CA model was employed. [ABSTRACT FROM AUTHOR]

Identifying and characterizing semi-natural habitats (SNHs) are important to the ecological conservation of cultivated land systems and implementing China's ecological civilization strategy. This study revealed the concept and characteristics of SNHs in Chinese cultivated land systems regarding human activities, resource types, and spatial landscape patterns. The resource quantity, landscape quality, and spatial distribution of SNHs in Southern Jiangsu's cultivated land system were analyzed by constructing the identification model of "land use/land cover type-cultivated land use intensity-spatial landscape pattern". The results showed that the area of SNHs in Southern Jiangsu's cultivated land system was 25.35%, significantly influenced by cultivated land intensification and expansion. The higher the cultivated land use intensity, the lower the quantity of SNHs, and the proportion of SNHs in the intensive-use pattern was only 2.97%. 68.18% of the SNHs in Southern Jiangsu were water, and habitats for important species, such as woodland, grassland, wetlands, and bare land, were scarce. A small patch area, high landscape fragmentation, poor landscape richness and diversity, and low connectivity accompanied increased cultivated land use intensity. From the extensive to intensive utilization, the spatial spread of SNHs from low-value aggregation to high-value scatter areas, with hotspot areas of cultivated land use intensity and SNHs existing only in a small part of Nanjing and Changzhou. This study provides a scientific reference for the rehabilitation and restoration of SNHs in the context of the ecological transformation of land use. It promotes the sustainable intensification of cultivated land systems. It also provides new ideas for linking ecological and urban spaces to form a stable and systematic national ecological safety network. [Display omitted] • SNHs are important to the ecological conservation of cultivated land systems in China. • SNHs are influenced by cultivated land intensification and expansion. • The proportion of SNHs decreases with increased cultivated land use intensity. • Analyzing SNHs promotes the ecological transformation of cultivated land use. [ABSTRACT FROM AUTHOR]

With climate change and urbanization, flood disasters have significantly affected urban development worldwide. In this study, we developed a paradigm to assess flood economic vulnerability and risk at the urban mesoscale, focusing on urban land use. A hydrological simulation was used to evaluate flood hazards through inundation analyses, and a hazard-vulnerability matrix was applied to assess flood risk, enhancing the economic vulnerability assessment by quantifying the differing economic value and flood losses associated with different land types. The case study of Wangchengpo, Changsha, China, found average total economic losses of 126.94 USD/m2, with the highest risk in the settlement core. Residential areas had the highest flood hazard, vulnerability, and losses (61.10% of the total loss); transportation areas accounted for 27.87% of the total economic losses due to their high flooding depth. Despite low inundation, industrial land showed greater economic vulnerability due to higher overall economic value (10.52% of the total). Our findings highlight the influence of land types and industry differences on flood vulnerability and the effectiveness of land-use inclusion in urban-mesoscale analyses of spatial flood characteristics. We identify critical areas with hazard and economic vulnerability for urban land and disaster prevention management and planning, helping to offer targeted flood control strategies to enhance urban resilience. • We established the flood vulnerability curve of Changsha City. • Urban mesoscale's flood vulnerability evaluation is optimized based on land use. • Both land type and industry nature can affect flood economic vulnerability. • The land unit as the hazard-bearing body reflects flood spatial characteristics. • The Hazard-Economic Vulnerability dual risk land is the key to flood control. [ABSTRACT FROM AUTHOR]

Spatial conflicts of land use (SCLU) arise during land-use change, which causes an imbalance of land-use spatial patterns and negatively affects society, the economy, and ecology. Previous research has focused on identifying and measuring SCLU, with less attention on the negative effects. The incorporation of risk assessment methods to evaluate potential conflict risks has been limited. The current study presents methods for measuring SCLU and assessing potential conflict risks from the ecological environment perspective. The spatial comprehensive conflicts index and potential conflict risk index were used to identify and measure the SCLU and to assess and warn against potential conflict risks, respectively, based on a case study in the Ili River Valley in China. The impacts of terrain restriction and land-use change on the SCLU were explored. Results indicate that (1) the SCLU area in the Ili River Valley decreased by 2,608 km2 from 2010 to 2020, compared to the previous decade, the degree of conflict weakened, and the main body of the SCLU gradually shifted northwest. (2) The potential risk areas cover 20,268 km2 in 2020–2030 and are mainly distributed in the "Khorgas City–Huocheng County–Yining City–Yining County" group of towns, as well as along the Ili–Kunes rivers and in the ecological protection zone in the south of the Ili River Valley, which shows the clustering along the city and distribution along the river in the spatial pattern. (3) Topography had a significant impact on the SCLU, and the main types of land-use change in the severe-conflict zone were the reduction of grassland and the expansion of arable and built-up land. For future conflict mitigation in the Ili River Valley, cautioning against urban sprawl and safeguarding land ecological security is critical. This study systematically investigates and analyzes SCLU across three dimensions: theory, methodology, and application to produce a theoretical and practical framework to identify SCLU and assess potential conflict risks. • Spatial conflicts of oasis is studied from the perspective of ecological environment. • Spatial conflicts of land use is identified by risk index and Eco-environmental value. • The warning areas of potential conflict risks are evaluated by Risk Matrix Approach. • Topography and land use type change have significant impacts on spatial conflicts. [ABSTRACT FROM AUTHOR]

Multi-hazards are a great concern in the present world. Likewise, the coastal part of Bangladesh is highly vulnerable to multi-hazards, including waterlogging, surface water salinity, land use change, prolonged dry seasons, and groundwater salinity. Multi-hazards and associated risks make local adaptations more difficult over time. Thus, the purpose of this study is to explore the connection between multi-hazards and their associated socio-ecological risks in the southwestern coastal part of Bangladesh. Mixed-methods approaches were used to collect all the data, and statistical analyses were performed to analyze the data. Results revealed that waterlogging significantly influenced local food access, poverty, child marriage, and divorce problems. Surface water salinity and land use change showed significant differences with the widening of salinity-affected areas. Waterlogging, land use change, and a prolonged dry season all showed significant differences in freshwater access. Prolonged dry seasons and groundwater salinity both have a significant impact on human health. Waterlogging and groundwater salinity significantly influence human migrations. These findings may strengthen local adaptation policies for salinity hazards, land use planning, household poverty, food access, livelihoods, water access, health effects, child marriage, and human migration. In addition, our findings indicate the potential to address the existing knowledge gaps pertaining to coastal hazards, risks, and adaptation issues. • Links between multi-hazards and socio-ecological risks have been identified. • Waterlogging increases multiple risks in coastal communities. • The findings could guide the formulation or strengthening of a multi-hazard adaptation policy. [ABSTRACT FROM AUTHOR]

The continuous increase of urbanization and industrialization brought various climatic changes, leading to global warming. The unavailability of meteorological data makes remotely sensed data important for understanding climate change. Therefore, the land surface temperature (LST) is critical in understanding global climate changes and related hydrological processes. The main objective of this work is to explore the dominant drivers of land use and hydrologic indices for LST in drainage and non-drainage areas. Specifically, the relationship between LST changes, land use, and hydrologic indices in Northeast Qena, Egypt, was investigated. The Landsat 5 and 8 imagery, Geographic Information System (GIS), and R-package were applied to identify the change detection during 2000–2021. The normalized difference between vegetation index (NDVI), bare soil index (BSI), normalized difference built-up, built-up index (BUI), modified normalized difference water index (MNDWI), and soil-adjusted vegetation index (SAVI) were employed. The non-drainage or mountain areas were found to be more susceptible to high LST values. The comprehensive analysis and assessment of the spatiotemporal changes of LST indicated that land use and hydrologic indices were driving factors for LST changes. Considerably, LST retrieved from the Landsat imaginary showed significant variation between the maximum LST during 2000 (44.82°C) and 2021 (50.74°C). However, NDBI has got less spread during the past (2000) with 10–13%. A high negative correlation was observed between the LST and NDVI, while the SAVI and LST positively correlated. The results of this study provide relevant information for environmental planning to local management authorities. [Display omitted] • Significant temporal variation in LST (2000–2021) was extensively investigated. • Increasing LST trend from 2000 (44.82 °C) to 2021 (50.74 °C) was detected. • Climate change impact was strongly proved in the studied area. • LST analysis and indices support UN-SDGs and climate action. [ABSTRACT FROM AUTHOR]

The combined effects of changes in climate and land use and land cover can lead to a decrease in soil organic carbon, potentially affecting soil fertility and agricultural output. The study aimed to evaluate the dynamics of soil organic carbon under various extreme climate and land use and land cover scenarios. The data on land use types and extreme climate indices between 2015 and 2070 were, respectively, sourced from the IPCC and the European Copernicus Climate Change Service webpages. The 2015 baseline data for soil organic carbon was obtained from the African Soil Information Service's website. Data quality control and model validation were conducted to ensure the reliability of the collected data and the predictive model. A generalized regression model was chosen for its accuracy and reliability in predicting soil organic carbon dynamics under different shared socio-economic pathways such as SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios. The study revealed that variations in extreme climate and land use patterns significantly influenced the organic carbon content of the soil. Increased dry days and the conversion of forest and grassland into farmland resulted in a drop in soil organic carbon, while increased wet days and warming temperatures significantly increase it under each scenario. The soil organic carbon content increased by 5.82 and 2.8 g/kg for the SSP1-2.6 and SSP2-4.5 scenarios, respectively, but decreased by 6.90 g/kg under the SSP5-8.5 scenario. Overall, the higher emission scenarios had a significant negative impact on soil organic carbon levels, while the low emission scenarios had a positive impact. Sustainable land management practices are crucial for preserving and managing soil organic carbon levels. [Display omitted] • Low-emission methods are crucial for reducing greenhouse gas emissions, promoting carbon sequestration, and enhancing SOC. • The rising frequency of dry days and colder temperatures underscores the need for sustainable land management practices. • Sustainable land management is crucial as natural areas are converted into farmland. • Prioritizing sustainable development is critical to preserve soil health. [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]

The Chinese government has implemented a series of ecological restoration projects in the Loess Plateau (LP), and the surface cover changed dramatically, impacting the ecosystem services (ESs) greatly. In this study, we used K-means clustering to classify the land use structures (LUSs) of the LP from 1990 to 2015 at the small watershed scale, and investigated the effects of LUS on water supply (WS), soil conservation (SC), and carbon sequestration (CS, expressed as NPP) with constraint lines. The values of WS and SC were obtained from the InVEST simulation, validated by the hydrographic station data. The results showed that the LUSs in LP were cropland structure (CLS, distinguished with CS), forest structure (FS), grassland structure (GS), crop-grassland structure (CGS), crop-forest-grassland structure (CFGS) and a very few areas of barren structure (BS). The proportion of dominant land use in those LUSs with a balance of WS, SC, and CS was 0.6–0.7 (cropland in CLS), 0.5 (forest in FS), 0.45/0.4 (cropland/grassland in CGS), 0.75 to 0.85 (grassland in GS), and 0.15/0.4/0.25 to 0.35 (cropland/forest/grassland in CFGS), respectively. The types of constraint curves of ESs for those LUSs involves hump-shaped curve, negative convex, half-concave-waved curve and concave-waved curve. This study proposed a method to objectively delineate LUS and improved the constraint line method to make it suitable for cases with less data, innovatively presenting the variation of ESs inside LUSs, which may provide a reference for optimal land planning and sustainable development of social-ecological systems. • Six types of land use structures (LUSs) were classified by K-means clustering. • Non-linear effects of LUSs on ecosystem services (ESs) were studied at small watershed scale. • Improved constraint lines method showed synergies and trade-offs between ESs due to LUSs. • The coordination of ESs occurs in appropriate proportional interval of LUS. [ABSTRACT FROM AUTHOR]

Subtropical rivers are one of the hotspots of global biodiversity, facing increased risks of fish diversity changes and species extinction. However, until now, human impacts on native and non-native fish communities in subtropical rivers still lack sufficient effort. Here, we used the environmental DNA (eDNA) approach to investigate fish communities in the Dongjiang River of southeast China, a typical subtropical river, and explored the effects of regional land use and local water pollution on fish taxonomic and functional diversity. Our data showed that 90 species or genera of native fish and 15 species or genera of non-native fish were detected by the eDNA approach, and there was over 85% overlap between eDNA datasets and historical records. The taxonomic and functional diversity of all, native and non-native fish communities showed consistent spatial patterns, that is, the upstream of the tributary was significantly higher than that of the mainstream and downstream. Land use and water pollution such as COD and TP were the determinants in shaping the spatial structure of fish communities, and water pollution explained 31.56%, 29.88%, and 27.80% of the structural variation in all, native and non-native fish communities, respectively. The Shannon diversity and functional richness of native fish showed a significant downward trend driven by COD (p Shannon = 0.0374; p functional = 0.0215) and land use (p Shannon = 0.0159; p functional = 0.0441), but they did not have significant impacts on non-native fish communities. Overall, this study emphasizes the inconsistent response of native and non-native fish communities to human impacts in subtropical rivers, and managers need to develop strategies tailored to specific fish species to effectively protect water security and rivers. [Display omitted] • Our data show over 85% overlap between eDNA datasets and historical records. • The taxonomic and functional diversity of fish communities exhibits similar spatial patterns. • The inconsistent responses of native and non-native fish to human impacts are observed. • Water pollution significantly affects the structure of native fish rather than non-native fish. [ABSTRACT FROM AUTHOR]

Unbalanced land use development has resulted in water scarcity, high energy consumption, and a significant increase in carbon emissions. Complex and changing environments make it more difficult to manage land use sustainably. This study constructed a variety of future change scenarios coupling climate and socioeconomic development and developed a multidimensional land use spatial optimization (LUSO) model linked with water-energy-carbon. The model is solved using a nondominated sorting genetic algorithm-III (NSGA-Ⅲ) coupled with the information feedback model (IFM). The advantages of this framework include: (1) LUSO based on the clarification of the interactions between different land use types and water-energy-carbon; (2) trade-offs between dimensions are considered to achieve coordinated multidimensional development of the economy, resources, environment, and spatial conversion; and (3) a spatial optimization pattern of land use in response to climate change and socioeconomic development changes can be obtained. The model framework is applied to the Mid-Yangtze River City Cluster for empirical analysis. The results show that socioeconomic development can lead to rapid changes in land use patterns, especially in cultivated and construction land. By 2030, the optimized land use pattern under the intermediate route model is the most suitable land use scenario for the region to achieve sustainable development. Under this scenario, the area of construction land increased by 22.09%, the area of cultivated land decreased by 2.2%, the economic output increased by 76,678.31 (1012 yuan), and the carbon emissions increased by only 5677.79 (107 kg), with an overall sustainability level of 0.85. This study can provide decision-makers with sustainable land resource management options that can respond to changing environments and achieve multidimensional synergistic development. [Display omitted] • A spatial optimization method for land use based on the land-water-energy-carbon nexus. • Integration of climate change and socioeconomic development. • Synergistic optimization of economy, resources, environment, and spatial conversion. • Improved IFM-NSGA-III for land use decision-making in changing environments. [ABSTRACT FROM AUTHOR]

The escalating impact of land use pressures indicates we've exceeded the proposed safe planetary boundary. Economic shifts and increased trade drive China's demand for agricultural and forestry products, land-use changes, and subsequent biodiversity damage often occur far from where they are consumed. Given many species in China are endemic or endangered, neglecting these interconnected economic trends threatens its biodiversity conservation targets. Here, we first quantify species loss due to six land use types embodied in the life cycle at the Chinese sub-national level. Then, a Chinese high-resolution multi-regional input-output (MRIO) model was used to link threatened species to key industrial sectors in the supply chain, tracking the spatiotemporal patterns of land use species loss embodied in Chinese trade from 2007 to 2017. Our results reveal a 6% increase in aggregated species loss in China during the study period. This subtle change in species loss footprints in recent years is partially due to increases in consumption levels being offset by reductions in species loss intensity, though drivers vary by region. Notably, the Northwest and Southwest, known for their high species richness, suffer the greatest inequalities in species loss. The domestic species loss transfer most apparent in the outsourcing from the Eastern Coast to the Southwest. The Southwest registered the highest territory-based species loss, particularly for amphibians, while the highest impacts in the supply chain are associated with Forestry, logging, and related activities. Our analysis underscores the need for enhanced provincial dialogue to systematically value and monitor biodiversity, a key natural capital, and encourage its conservation. Our study effectively monitors the consumption-based species losses across China, which can further improve knowledge and dialogue on ecological challenges associated with trade. • EEIO-based methods track China's slow land use species loss increase (2007–2017). • The most apparent biodiversity threat outsourcing is from seaboard to Southwest. • "Forestry, logging, and related services" has the highest species loss footprint. • Southwest has highest territory-based species loss, especially for amphibians. • Species loss intensity declines in China, while Industrial structures' role reverses. [ABSTRACT FROM AUTHOR]

Photovoltaic (PV) facility installation occupying large land areas gradually expands into vast grasslands. The construction of PV arrays should be synchronized with the establishment of fences to prevent grazing and human disturbance. However, it is still being determined whether deploying PV arrays in degraded grasslands has better restoration effects than common grassland fencing, achieving a win-win for grassland restoration and resolving land use conflicts. Here, we investigated soil and vegetation characteristics to assess the different impacts of PV arrays, fencing, and free-grazing on restoration in the degraded grassland in the Songnen Plain, Northeast China. The results showed that the PV arrays and fencing significantly improved soil and vegetation parameters, with the PV arrays dramatically increasing carbon and nitrogen storage in plants (including aboveground, underground, and litter) and soil. The mixed linear model analysis showed that the experimental zones had a significant influence on the carbon and nitrogen pools in plants and soil. Compared to single grassland fencing, the PV arrays significantly improved the carbon storage of plants and soil, with increases of 30.19% and 17.93%, respectively. Furthermore, there was an observed increase of 9.44% and 0.75% in the nitrogen storage. Soil pH and bulk density were the main factors influencing soil carbon and nitrogen storage in the fenced zones. Increasing soil moisture in the PV array zones resulted in higher soil carbon and nitrogen storage than in the fenced zones. The PV arrays showed a 78.61% increase in annual mean soil carbon sequestration rates compared to the grassland restoration measures reported in previous studies. Overall, the PV array zone superimposed the dual effects of PV panels and their fences, with the ecological indicators showing a greater positive influence than common grassland fencing. Our results suggested that deploying PV arrays was a win-win strategy for promoting grassland restoration and resolving land use conflicts in degraded grasslands. • PV arrays have better restoration effects than common grassland fencing. • PV arrays increase soil C sequestration by 78.61% compared to previous measures. • PV arrays can restore the degraded grassland and resolve land use conflicts. [ABSTRACT FROM AUTHOR]

Globally, significant societal resources are devoted to mitigating negative effects of eutrophication from excessive phosphorus (P) and nitrogen (N) loading. Potential effectiveness of mitigation measures and possible confounding factors are often assessed using studies conducted in headwater catchments. However, success is often evaluated based on trends in river mouth water chemistry. It is not clear how transferrable insights from headwater catchments are to larger rivers. Here, relationships between P and suspended solids (SS) identified in small agricultural headwater catchments were applied to 30 larger, mixed land use catchments draining into Mälaren, a Swedish great lake. Relationships identified in headwater streams between SS concentration, catchment agricultural land percentage and arable land clay content were corroborated for the larger catchments (R2 = 0.59, p-value<0.001. The same was true for connections between SS and particulate P (R2 = 0.74, p-value<0.001). This study highlights the importance of agricultural land, clay content and SS for P transport, on both smaller headwater as well as larger catchment scales, supporting the use of headwater findings on larger, management relevant scales. Consequently, these relationships should be used to target mitigation measures to reduce SS and P losses. To explore the effectiveness of mitigation measures on water quality, we assessed long-term (20 year) trends in tributary water quality and compared these trends to the amount of mitigation measures implemented in the catchment. Overall improving trends were detected using regional Mann Kendall tests, but few decreasing trends in nutrient concentrations were found for individual sites using Generalized Additive Models (GAM). The lack of significant trends and identifiable connections to amount of mitigation measures implemented could be due to several reasons, e.g. insufficient time for recently implemented measures to have an effect, ongoing release of legacy P as well as low areal coverage and poor spatial placement of implemented measures. In addition, trend detection requires large amounts of data and the results should be carefully interpreted and communicated. [Display omitted] • Analyses of 20 years of environmental monitoring data for 30 streams. • Generalized additive models detected few trends in phosphorus and suspended solids. • Headwater relations for phosphorus and suspended solids scale well to larger rivers. • No clear connection between implemented mitigation measures and water quality trends. • Continuous long-term monitoring is crucial for trend detection. [ABSTRACT FROM AUTHOR]

Digital tools, particularly specialised decision support systems (DSSs), can be utilized to assist in the complex process of brownfield redevelopment. Existing brownfield DSSs typically focus on site-specific, late-stage applications, and socioeconomic factors are often overlooked. In this paper, we present a novel DSS aimed at providing support for early-stage, city region-scale brownfield land use planning and redevelopment. The proposed DSS is a prototype WebGIS application that enables land use planners and other brownfield regeneration professionals to examine a region and a set of sites during the initial planning phase for brownfield redevelopment. The DSS includes three bespoke modules comprising: (1) Land Use Potential (residential, commercial, and public open space), (2) risks posed by contamination and geotechnical hazards, (3) data pertinent to brownfield economic viability assessments. We outline a use case for this DSS, developed through comprehensive user-requirements gathering, and subsequently describe the techniques employed to construct the DSS modules and user interface. Finally, we present the results of user testing, wherein case-study stakeholders assessed the DSS. The feedback obtained during user testing aided in the identification of areas for improvement with regard to the functionality, usability, and effectiveness of the DSS in supporting decision-makers. The feedback was utilized to implement iterative improvements to the DSS and to plan future developments for the prototype DSS. • A novel DSS for sustainable brownfield planning and development is presented. • Development of the DSS ensured comprehensive stakeholder involvement throughout. • The DSS is modular and assesses land use, ground risk, and economics simultaneously. • User testing indicates that the DSS has a high degree of usability and impact. [ABSTRACT FROM AUTHOR]

China possesses extensive grasslands primarily located in dryland regions, which are highly susceptible and fragile to climate change and human intervention, making them prone to degradation and desertification. In recent decades, China has implemented numerous ecological projects to improve the states of ecosystems. Additionally, recent studies have revealed the critical roles of rising CO 2 on dryland greening. However, it is still limited to understand the contributions of anthropogenic recovery and CO 2 fertilization, as well as other climate factors, to the dynamics of grassland degradation and desertification in China. To address these gaps, we employed a two-step approach to differentiate between grassland degradation and desertification as distinct processes across the grasslands and sparsely vegetated lands in China. This involved assessing degradation within existing grassland areas and identifying the conversion of grasslands into desert regions. The study period of 2000–2020 was examined to determine the occurrence of grassland desertification, which suggested a significant decrease in the desertification area in China. Subsequently, the time series of the Enhanced Vegetation Index (EVI) during the growing season was analyzed to track vegetation dynamics. Since the beginning of the 21st century, a significant greening trend has been observed in approximately 97% of the study area. Furthermore, we quantified the effects of anthropogenic climate change (ACC), climate change, and land use change on grassland degradation and desertification in China. The analyses indicated that 50.7% of the observed vegetation changes in the study area from 2000 to 2020 were primarily driven by land use, followed by the effects of rising CO 2 , accounting for 42.1% of the changes. These findings provided some insights on developing regionally-targeted strategies for grassland conservation in China. • This study separated grassland degradation and desertification as two processes. • Trends and drivers of grassland degradation and desertification were quantified. • We compared the trends and drivers among different state regions of grasslands. • This study provided supports for developing regionally-targeted conservation strategies. [ABSTRACT FROM AUTHOR]

Human activities and global changes have undergone significant transformations in land systems. It is imperative to comprehend the intricacies of land use transitions (LUT), as they serve as indicators of the evolving dynamics within the complex human-environmental relationship. In this study, we adopt the conflict-coordination theoretical framework to delve into the role of land-use conflicts (LUC) in driving LUT. Our investigation involves the quantification of LUT and the assessment of LUC within China, spanning from 1980 to 2020. Subsequently, we scrutinized the interplay between LUT and LUC using Spearman correlation analysis and the Wilcoxon test. Our findings reveal that greater diversity in land-use structure can be attributed to ecological land fragmentation and the restoration of unused land, while the expansion of urban and cropland areas contributes to a less diverse land-use pattern. Furthermore, there is a discernible upward trend in land use function. Although the overall degree of LUC in China is relatively mild, there is a noticeable upward trajectory over the past four decades. More pronounced conflicts within land-use patterns promote a diversified land-use pattern, while conflicts arising from competing land-use functions elevate the level of land-use functionality. Moreover, a dynamic interplay between land-use transitions and conflicts becomes evident, with intense conflicts within land-use patterns weakening land-use functionality, and imbalances in functionality driving greater diversity in land-use patterns. Our research introduces an innovative analytical framework that elucidates LUT through the lens of LUC, with the potential for broader applicability across different regions. This framework not only enhances our understanding of LUT but also provides valuable scientific guidance for the effective management of conflicts to promote the sustainable development of land resources. • Land use transition (LUT) is assessed from aspects of structure and function. • We evaluate land use conflict (LUC) underlying structure and function in China. • The relationships between LUT and LUC are examined from 1980 to 2020. • LUC promotes LUT to achieve more diverse structure and high-level function. • The intense conflict of land use function leads to more diverse structure. [ABSTRACT FROM AUTHOR]

Soil quality indices (SQI) used for assessing soil degradation are often developed using additive scoring functions. However, these SQI may lack reference values for interpreting their outputs and the capacity to differentiate changes in specific variables. To overcome these limitations, this study introduces SQI using Log Response Ratios (LRR) as measures of size effects caused by land use in physical, chemical, and microbiological soil quality indicators. LRR vectors projected 2D polygons with condensed change measures along their perimeters. This method was tested in andosols within the southeastern region of Antioquia, Colombia. These soils were subjected to contrasting stages of degradation determined by the extent of A-horizon removal due to land use practices. This study shows that mining and agriculture have detrimental effects on soil organic carbon and water contents, and that size effects vary significantly between land uses (p < 0.05). Microbiological features also exhibit distinct size effects, such as populations of culturable mesophilic bacteria and fungi, microbial basal respiration, spore density of arbuscular mycorrhizal fungi (AMF), their diversity, and total glomalin-related soil proteins (p < 0.05). The SQI proposed exhibited a negative correlation with SQI computed from scoring additive functions either considering the entire dataset (R2 = 0.87) or a minimum dataset (R2 = 0.90). This approach underscores the utility of using LRR geometrical analysis to assess global soil quality differences among land uses (p < 0.01), offering a visual, quantifiable representation of the effects of each land use over specific soil quality indicators. [Display omitted] • Soil quality indices (SQI) may display size effects on their indicators. • We propose an SQI that distinguishes land use impacts using geometrical analysis. • This SQI can differentiate changes in specific quality indicators with 2D polygons. [ABSTRACT FROM AUTHOR]

Balancing ecology and human development has been a long and wide concern. The upper Yangtze River Basin (UYRB) of China has implemented large important ecological restoration projects since the last century. These restoration practices have changed land use patterns within the UYRB, consequently impacting the local carbon cycle. The most noteworthy project is the Grain for Green Program, which returns cropland to natural vegetation (forest and grassland). Yet the effects of restoration on land use change, carbon sequestration, and associated food production remain unclear. This study utilized remote sensing data and conversion coefficients to analyze the ecological-policy-induced land use changes of the UYRB from 2000 to 2020 and their impacts on terrestrial carbon sequestration. Linear regression, machine learning, and structural equation modeling (SEM) were utilized to evaluate the correlations between environmental and socio-economic factors and the distribution of carbon stocks. The results indicated positive effects of ecological activities on the UYRB, despite decreases in cropland. Over the past 20 years, the UYRB had sequestered carbon by a total amount of 1796 ± 926 Mt C. The spatial distribution of sequestered carbon demonstrated a strong correlation with slopes, followed by temperatures. The SEM results indicated that agricultural production and carbon sequestration were enhanced synergically under land use changes. This further demonstrated the effectiveness of these land policies in achieving a balance between crop productivity and ecology protection. We emphasized the importance of vegetation restoration in achieving carbon neutrality and the necessity to continue these projects. We suggested a more reasonable land management for the future UYRB based on the characteristics of each geographical subregion. This work serves as an example of effective land management to other locations worldwide perusing the harmony of ecological restoration and human development. [Display omitted] • Regreening dominated land use changes in the Upper Yangtze River Basin (UYRB). • 4.3% forest increased in the UYRB but at an expense of 3.3% decreased cropland. • The sequestered carbon of UYRB over 20 years is about 1796 ± 926 Mt C. • Slope impacts sequestered carbon most, occupying 50% of relative influence. • Land policies increased agricultural production and carbon sequestration synergistically. [ABSTRACT FROM AUTHOR]

The necessity for extensive historical data, variables, and weight determination still presents challenges and complexity, notwithstanding the growth in research on socio-ecological vulnerability to climate change. In order to fill in these gaps, this study used China's Fujian Province as a case study to propose a unique strategic approach for studying socio-ecological vulnerability to climate change from 2000 to 2020 by utilizing remote sensing and the framework of the Intergovernmental Panel on Climate Change. In a GIS scenario, this method employs a comprehensive framework with a wide variety of indicators and a data-driven ranking algorithm. The findings of this study revealed a moderate degree of socio-ecological vulnerability throughout the coast, with significant regional heterogeneity in its spatial distribution. Furthermore, throughout the course of the two-decade, the highly vulnerable zones expanded by 6.04%, outpacing the low-risk areas by 1116 km2 (61.41%) and 2066 km2 (123.39%), respectively, with the majority of the increase taking place in Fuzhou and Ningde. These changes in vulnerability were shown to be principally influenced by changes in vegetation, precipitation, GDP, and land use (LULC). The major influence of precipitation was highlighted further in the spatial autocorrelation analysis, which demonstrated a close correlation between growing socio-ecological vulnerability and increased precipitation. To conclude, this study's methodology differs from other socio-ecological vulnerability studies in that it is flexible and self-sufficient, offering users a choice of weight application. It also gives a more useful, accurate, and suggestive model to enable decision-makers or stakeholders build strategies or ideas for constructing more resilient coastal systems. [Display omitted] • A strategic approach for socio-ecological vulnerability assessment is established. • The coast exhibits a moderate level of socio-ecological vulnerability. • In Ningde and Fuzhou, highly vulnerable zones grew by 6.04% between 2000 and 2020. • Variations in vulnerability revealed a high spatial correlation with precipitation. • Data ranking approach is a crucial tool for building resilient coastal system. [ABSTRACT FROM AUTHOR]