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Rapid uptake of greenhouse gas (GHG) mitigation measures is central to reducing agricultural and land use emissions and meeting the UK Net Zero policy. The socioeconomic challenges and barriers to uptake are poorly understood, with yet unclear structural pathways to the uptake of GHG mitigation measures. Using an online survey of 201 agricultural land managers across the UK, and applying multiple linear regression and stepwise regression analysis, this research established farm and farmers' factors influencing perceptions and willingness to adopt GHG mitigation measures. The results consistently show that farm sector, farmers' business perception, and labour availability influence willingness to adopt GHG mitigation measures. Based on the farmers' qualitative feedback, other barriers to adoption include costs and concerns for profitability, lack of flexibility in land tenancy contracts, poor awareness and knowledge of the application of some GHG mitigation measures, perception about market demand e.g bioenergy crops, and scepticism about the future impacts of adopting varying GHG mitigation measures. In the midst of the ongoing net zero transition, this study identifies existing barriers to the uptake of GHG mitigation measures, and specifically, a substantial gap between farmers and the science of GHG mitigation measures and the need to incentivise a farm and farming community-led policy interventions to promote adoption of GHG mitigation measures. [ABSTRACT FROM AUTHOR]

The soil environment plays an important role in urban ecosystems. To study the heavy metal contamination of soil in Beilun District, Ningbo, we collected soil samples from 60 points in urban and peri-urban areas of Beilun District and analyzed the spatiotemporal variation and sources of heavy metal pollution in various land-use types. The results shown that the heavy metal contents in 2015 and 2022 were higher than the background soil values of Ningbo city, and there was an accumulation of heavy metals over these 7 years. The contents of heavy metals in green belts and woodland in 2022 were higher than those in 2015, while there was no significant change in agricultural land. The heavy metal contents in both years were mainly in the order green belts > agricultural land > woodland. The spatiotemporal distribution of heavy metal content showed that heavy metal pollution in Beilun District was concentrated in five industrial areas, and there was a trend toward the disappearance of highly polluted points. But the single-factor pollution index, pollution load index (PLI), and geoaccumulation index (Igeo) indicated that there was no significant heavy metal pollution in Beilun District, and individual elements at specific points showed slight pollution. The source analysis results showed that the main source of Hg is chemical, As is mainly derived from agricultural, Cr, Ni and Cu are mainly derived from natural, the main sources of Zn and Cd are electroplating and machinery activities, and the main source of Pb is traffic. These results specify a reference for future investigation on urban soil heavy metals, and the source apportionment results provide a scientific foundation for subsequent soil heavy metal pollution treatment. [ABSTRACT FROM AUTHOR]

This article examines Ghana's land development and planning laws from a historical perspective. The methodology involves a documentary study of historical records to explore the evolution of these laws, spanning from the colonial period to the present. Through this approach it sheds light on significant milestones such as the 1988 local government changes, the land use decree's implementation by military juntas, and the identified deficiencies in the decree pertaining to physical planning. The expositions from this study show that Ghana has over the years adopted many land development and planning laws, that there is a visible demand for land among people and a desire by developers to use their land. The topic of planning is thus a significant area for stakeholders in Ghana. The study, therefore, recommends that, given the fact that land development and planning laws are here to stay, and that people are the primary drivers of social change, these laws should respect the culture and norms of the people, and should as well always incorporate active public engagement for stakeholders to feel a sense of ownership and belongingness in the entire process. [ABSTRACT FROM AUTHOR]

The first Earth Day on April 22, 1970, celebrated the grassroots environmental movement that began in the '60s and early '70s and ushered in the creation of a new legal framework for controlling pollution and addressing environmental concerns in the United States. However, more than fifty years later, some experts fear that the environmental progress achieved during the '70s and '80s has begun to stall as the United States and other nations experience broad economic hardship and must shift their focus to more immediate concerns. Therefore, even as the damaging effects of climate change threaten communities across the globe, the next major environmental movement is unlikely to happen at the federal or global level. Instead, state and local citizens and governments must address the increasing impacts of climate change by exploring short- and long-term approaches to land use planning and environmental regulation to prepare communities to be resilient to coming changes. This Article attempts to consolidate the various land use tools, such as planning, zoning, sustainable and green development, eminent domain, inverse condemnation, nuisance law, renewable energy incentives, and smart cities, which can help communities and individuals deal with past, current, and future impacts from climate change. These more localized tools present greater opportunities to prepare for climate change and continuing disasters, address systemic inequalities and disruptive histories, and build or rebuild resilient communities through mitigation and adaptation. This Article suggests that the principle of social ecological resilience is an effective concept to deal with climate change when our ecosystems are prone to disruption, promoting a land use system that manages risk through mitigation and adaptation. By incorporating principles of social-ecological resilience, sustainability, and adaptation into the circle of disaster risk management and other regulatory responses, communities can better prepare for the future while also establishing equitable laws and policies. The Article continues by assessing local land use concepts that are available to mitigate and adapt to climate change at the community level. While local governments have a vital role in establishing mitigation and adaptation strategies through a variety of land use regulations and policymaking, the participation of all citizens who live and work in the community----particularly the vulnerable ones----is also essential for creating planning and governance strategies that further a community's resilience goals. This inclusive, community-wide approach provides a framework for assessing emergency response strategies at the local level, analyzing various compensation models to spread risks following a disaster, and facilitating cohesive and effective rebuilding efforts. Bearing all these tools in mind, this Article concludes that adaptive governance informed by resilience thinking at the local level will help build (and rebuild) communities capable of withstanding whatever the future holds. [ABSTRACT FROM AUTHOR]

Societal Impact Statement: Global climate models that incorporate carbon sources and sinks usually consider that forest uptake of carbon is in a state of equilibrium. Both historical and paleoecological records suggest that this is commonly not the case for Amazonia. Here, the impacts of colonial practices on Amazonian Indigenous peoples and forests are reviewed. Human activities affect forests' successional stages, trajectories, and species composition. By increasing the spatial coverage of paleoecological records that focus on pre‐ and post‐Columbian periods, the long‐term interactions between humans and Amazonian forests and their role in affecting Earth's climate may be better understood. Summary: Legacy effects left by the activities of Indigenous people in Amazonia are well known. Although severe, widespread, and recently occurring, the impacts left post‐1492 CE have been less investigated. We review the impact of colonial practices on Indigenous peoples and Amazonian forests. We suggest that forests comprise the sum of their past events, in a mosaic of different cumulative successional trajectories depending on the type, frequency, intensity, and timing of human influence. In regions with a history of minimal human influence, old‐growth species sensitive to fire would be the dominant landscape. In regions with high pre‐Columbian and low colonial influence, old‐growth forests carrying pre‐Columbian ecological legacies would be prevalent. Regions occupied by Indigenous groups post‐1492 CE would also carry similar ecological legacies. In regions influenced by the Jesuits, mid‐successional forests are expected to be enriched with cacao trees. In regions of latex extraction during the rubber boom, mid‐growth forests would present high abundances of early and mid‐successional species and depletion of some species. In deforested areas, we expect early successional forests with influence of exotic useful species. This patchwork of history probably plays a large role in shaping today's forests, and the biodiversity and carbon dynamics documented within them. Paleoecological work focusing on the last millennium, although scarce, has the potential to detect these mosaics of past human influence, and they should be considered when estimating forest ages and successional stages across the basin. [ABSTRACT FROM AUTHOR]

The article focuses on critiquing the disparity between the rigorous public review procedures required under New York City's Uniform Land Use Review Procedure (ULURP). It highlights how state powers, facilitated by Empire State Development (ESD) through General Project Plans (GPP), often sidestep meaningful community engagement and oversight, thereby potentially infringing on property rights without sufficient public scrutiny.

• LULC changes of three decades from 1991 to 2021 were examined and predicted. • Multi-spectral remote sensing data and RFT were utilized to generate LULC maps. • ACR were considered to analyze the categorical land use change detection. • Impervious land has expanded 10 times within 30 years and will increase in the future. The integration of multi-spectral remote sensing and GIS-based analysis is significant for studying land cover changes, providing valuable insights for informed land management and sustainable development. The present study aims to examine land use land cover (LULC) changes of three decades from 1991 to 2021 and predict the future LULC change in Binh Duong province, Vietnam to explore a future research direction on land use change and associated challenges in the study region. Multi-spectral remote sensing data and random forest tree (RFT) were utilized to generate LULC maps. Areal statistics and annual change rate were considered to analyze the categorical land use change detection. Statistical measures such as user's accuracy, producer's accuracy, kappa coefficient, and confusion matrix were employed to assess the accuracy of LULC classification. To predict future LULC and simulate the spatio-temporal change, we considered previous year LULC maps, independent spatial variables and a combined artificial neural network (ANN) multi-layer perceptron approach. The analysis revealed that there was a huge transition from agricultural lands to residential land with industry and commerce which resulting an expansion of impervious lands and a rapid decline of agricultural land as well as of scrub land and barren lands, and a changeability of forest and plantation, croplands, and waterbodies. Our study revealed that the impervious land has expanded 10 times within 30 years and will increase in the future. [ABSTRACT FROM AUTHOR]

Different mechanisms act to structure metacommunities. Among them, the most studied are those related to environmental and spatial drivers. Also, most studies on metacommunities are based on data obtained in snapshot surveys, hindering the test of other potential mechanisms, including historical effects. Here, we quantified the relative importance of different sets of variables that could potentially structure zooplankton communities in 39 small reservoirs in Midwest Brazil. In addition to local environmental, spatial, and land use variables, as a proxy for potential priority effects, we tested the effect of earlier zooplankton composition on (later) zooplankton metacommunity structure. The relative importance of these sets of explanatory variables varied over time. However, earlier zooplankton community data were, in general, the most consistent predictors (especially for microcrustaceans) of zooplankton community structure. This result may indicate the role of historical effects on later zooplankton metacommunity structure. Our results highlight the importance of considering multiple surveys and past community data in spatiotemporal studies aiming to unveil the determinants of zooplankton metacommunity structure. [ABSTRACT FROM AUTHOR]

Mounting evidence shows overall insect abundances are in decline globally. Habitat loss, climate change, and pesticides have all been implicated, but their relative effects have never been evaluated in a comprehensive large-scale study. We harmonized 17 years of land use, climate, multiple classes of pesticides, and butterfly survey data across 81 counties in five states in the US Midwest. We find community-wide declines in total butterfly abundance and species richness to be most strongly associated with insecticides in general, and for butterfly species richness the use of neonicotinoid-treated seeds in particular. This included the abundance of the migratory monarch (Danaus plexippus), whose decline is the focus of intensive debate and public concern. Insect declines cannot be understood without comprehensive data on all putative drivers, and the 2015 cessation of neonicotinoid data releases in the US will impede future research. [ABSTRACT FROM AUTHOR]

Generating high-resolution land cover maps using relatively lower-resolution remote sensing images is of great importance for subtle analysis. However, the domain gap between real lower-resolution and synthetic images has not been permanently resolved. Furthermore, super-resolution information is not fully exploited in semantic segmentation models. By solving the aforementioned issues, a deeply fused super resolution guided semantic segmentation network using 30 m Landsat images is proposed. A large-scale dataset comprising 10 m Sentinel-2, 30 m Landsat-8 images, and 10 m European Space Agency (ESA) Land Cover Product is introduced, facilitating model training and evaluation across diverse real-world scenarios. The proposed Deeply Fused Super Resolution Guided Semantic Segmentation Network (DFSRSSN) combines a Super Resolution Module (SRResNet) and a Semantic Segmentation Module (CRFFNet). SRResNet enhances spatial resolution, while CRFFNet leverages super-resolution information for finer-grained land cover classification. Experimental results demonstrate the superior performance of the proposed method in five different testing datasets, achieving 68.17–83.29% and 39.55–75.92% for overall accuracy and kappa, respectively. When compared to ResUnet with up-sampling block, increases of 2.16–34.27% and 8.32–43.97% were observed for overall accuracy and kappa, respectively. Moreover, we proposed a relative drop rate of accuracy metrics to evaluate the transferability. The model exhibits improved spatial transferability, demonstrating its effectiveness in generating accurate land cover maps for different cities. Multi-temporal analysis reveals the potential of the proposed method for studying land cover and land use changes over time. In addition, a comparison of the state-of-the-art full semantic segmentation models indicates that spatial details are fully exploited and presented in semantic segmentation results by the proposed method. [ABSTRACT FROM AUTHOR]

The Land Use Change Alert (LUCA) dataset was developed for effective and timely monitoring of global forest changes that are mostly associated with human activities. Near- real-time changes of forest land use are mapped at 0.05 ha minimum mapping unit for all forest types across the Earth's ecoregions, every two weeks. LUCA is based on Sentinel-1 cloud penetrating synthetic aperture radar (SAR) observations to circumvent limitations of optical imagery from pervasive cloud cover over forested areas globally, and especially in the tropics. The methodology is based on a combination of time-series change detection and machine learning analytics to achieve high accuracy of alerts across all ecoregions and landscapes globally with an average area-adjusted users and producers accuracy of 83% and 63%, respectively. The bi-weekly global alert maps capture forest clearing associated with deforestation and industrial timber harvesting, along with forest degradation associated with selective logging, fragmentation, fire, and roads. The product was developed and released publicly through Google Earth Engine to allow for the rapid assessment of land use change activities, quantifying patterns and processes driving forest change and dynamics across forest ecoregions. LUCA is designed to help monitor a variety of emission reduction programs at the local to regional scales and play a key role in implementing regulations on deforestation-free products. [ABSTRACT FROM AUTHOR]

Most studies in the field of land use and land cover (LULC) classification in remote sensing rely on supervised classification, which requires a substantial amount of accurate label data. However, reliable data are often not immediately available, and are obtained through time-consuming manual labor. One potential solution to this problem is the use of already available classification maps, which may not be the true ground truth and may contain noise from multiple possible sources. This is also true for the classification maps of the MapBiomas project, which provides land use and land cover (LULC) maps on a yearly basis, classifying the Amazon basin into more than 24 classes based on the Landsat data. In this study, we utilize the Sentinel-2 data with a higher spatial resolution in conjunction with the MapBiomas maps to evaluate a proposed noise removal method and to improve classification results. We introduce a novel noise detection method that relies on identifying anchor points in feature space through clustering with self-organizing maps (SOM). The pixel label is relabeled using nearest neighbor rules, or can be removed if it is unknown. A challenge in this approach is the quantification of noise in such a real-world dataset. To overcome this problem, highly reliable validation sets were manually created for quantitative performance assessment. The results demonstrate a significant increase in overall accuracy compared to MapBiomas labels, from 79.85% to 89.65%. Additionally, we trained the L2HNet using both MapBiomas labels and the filtered labels from our approach. The overall accuracy for this model reached 93.75% with the filtered labels, compared to the baseline of 74.31%. This highlights the significance of noise detection and filtering in remote sensing, and emphasizes the need for further research in this area. [ABSTRACT FROM AUTHOR]

To fully comprehend the patterns of land and ecological damage caused by coal mining subsidence, and to scientifically carry out ecological mine restoration and management, it is urgent to accurately grasp the information of coal mining, particularly in complex coaling areas, such as North Anhui, China. In this paper, a space–air–ground collaborative monitoring system was constructed for coal mining areas based on multi-source remote sensing data and subsidence characteristics of coaling areas were investigated in North Anhui. It was found that from 2019 to 2022, 16 new coal mining subsidence areas were found in northern Anhui, with the total area increasing by 8.1%. In terms of land use, water areas were increased by 101.9 km2 from 2012 to 2022, cultivated land was decreased by 99.3 km2, and residence land was decreased by 11.8 km2. The depth of land subsidence in the subsidence areas is divided into 307.9 km2 of light subsidence areas with a subsidence depth of less than 500 mm; 161.8 km2 of medium subsidence areas with a subsidence depth between 500 mm and 1500 mm; and 281.2 km2 of heavy subsidence areas with a subsidence depth greater than 1500 mm. The total subsidence governance area is 191.2 km2, accounting for 26.5% of the total subsidence area. From the perspective of prefecture-level cities, the governance rate reaches 51.3% in Huaibei, 10.1% in Huainan, and 13.6% in Fuyang. The total reclamation area is 68.8 km2, accounting for 34.5% of the subsidence governance area. At present, 276.1 km2 within the subsidence area has reached stable subsidence conditions, mainly distributed in the Huaibei mining area, which accounts for about 60% of the total stable subsidence area. [ABSTRACT FROM AUTHOR]

Most species-rich communities consist of a limited number of common species and many rare species. This widespread ecological pattern can arise due to the predominance of either niche-based or neutral-based processes in community structuring. We tested two hypotheses related to this pattern for an anuran metacommunity composed of 35 species distributed in 187 ponds in the South Brazilian grasslands: (1) for common species, niche processes should prevail over neutral ones because common species evolved under a wider range of ecological filters than rare species; (2) for rare species, neutral processes should prevail because rare species are more prone to ecological drift and dispersion limitation. We found that the densities of both common (i.e., the 25% higher density ones) and rare (i.e., the 75% lower density ones) species depended mostly on pond structure and land use, indicating a similar response to niche-based processes in both groups of species. The importance of pond descriptors and type of land use, however, differed between the two groups, confirming that common and rare species represent ecologically distinct groups within the metacommunity. In addition, neutral processes—related to dispersion limitation or not—influenced both species groups, but the spatial filters selected explained a smaller portion of the variation in species densities compared to environmental descriptors. Our findings showcase the prevalence of niche processes in structuring communities of common and rare species of anurans in subtropical grasslands and indicate the variables of pond structure and land use that are relevant to guide conservation practices for the metacommunity of anurans in the South Brazilian grasslands. [ABSTRACT FROM AUTHOR]

This study examined land use land cover change and its determinants in Tigray, Ethiopia and its livelihood zones. We used socioeconomic panel, and satellite data, and applied a mixed-effects model to analyse the factors influencing land allocation among different uses, and transition matrix to analyse land cover dynamics. The results revealed that; land use choices were influenced by plot level factors (such as plot elevation, distance, soil type and quality, and land tenure), household characteristics (such as education, dependency ratio, plot size and number owned, income, livestock and asset, perception of climate change, and access to market and main road), and community level factors (precipitation, product price, population density and livelihood zone variations). Transition matrix analysis showed that between 1986 and 2016, 12.8% of forest was converted to bare land, 6.26% bare land was converted to pasture, and 5.84% of cropland was converted to forest. However, net deforestation occurred in most of the livelihood zones. Therefore, local communities faced environmental and socio-economic challenges from capital constraints induced land fallowing, land fragmentation, and unmanaged land cover change. The study recommended sustainable land use planning and management, market linkages, improved access to roads, forestry subsidies, land tenure security, and land consolidation programs. [ABSTRACT FROM AUTHOR]

Forest–grassland ecotone (FGE) has essential ecological and economic value. Unfortunately, it is impacted greatly by environmental changes and anthropogenic disturbance, and is considered one of the most severely threatened biomes in China. To protect Chinese FGE, identifying its exact boundary and exploring its landscape structure dynamic are badly needed, especially on nationwide scale at one‐year temporal resolution. Here, we mapped the annual FGE distribution of China from 1990 to 2020, investigated its changing trends of area, location and landscape patterns, and revealed the underlying driving factors. Our results showed that FGE area over the 31 years totaled 1 011 870 km2, covering about 10.54% of China's land. The FGE area first increased from 1990 and peaked in 1999, and then kept decreasing until 2020. The FGE gravity center has moved accumulatively 590.15 km over the 31 years, with the net moving distance of 228.76 km southwestward. From 1990 to 2020, forest area increased continuously while grassland and cropland area decreased, but these three landscape types had been dominating the FGE. The increase in forest area was largely converted from grassland. The decline in grassland mainly resulted from its conversion into cropland and forest. Meanwhile, the conversion of cropland to grassland supplemented grassland loss to a certain extent. At landscape level, the total area with decreased fragmentation is larger than that with increased fragmentation. Returning Farmland to Grassland Project and land reclamation were primary drivers for changes of fragmentation in the northern and middle part of the FGE, while temperature and precipitation were primary drivers in southern part. Our results will improve the understanding into the dynamic trends of distribution and pattern of FGE at nationwide scale, and thus help to optimize the designing of ecological projects and protective schemes for FGE as a unique and integral biome. [ABSTRACT FROM AUTHOR]

This study delves into the factors influencing the willingness of rural land transfers in different terrain areas, aiming to promote the improvement of land transfer institutions and accelerate the process of scale farming. Based on rural survey data from Anhui and Qinghai provinces in China, this research uses geographical detector and Binary Logistic Model to explore the differential factors affecting the willingness of farmers to participate in land contract transfer in the first and third terrain areas of China. The study examines four dimensions, including individual characteristics, family endowments, social support strategies, and geographical environment. The findings reveal the following: (1) By comparing the mean values, standard deviations, and coefficients of variation of the data from both provinces, it is evident that the indicators of individual characteristics, family endowments, social support strategies, and geographical environment differ significantly between the two provinces. This indicates substantial disparities in the basic attributes of farmers and their living environments. (2) The single-factor explanatory power significantly influencing farmers' willingness to engage in land transfer varies considerably and is statistically significant at the 1% level. The types of interaction between two factors mainly include dual-factor enhancement, nonlinear enhancement, single-factor nonlinear attenuation, and nonlinear attenuation. (3) There are commonalities and differences in the factors that significantly influence farmers' willingness to participate in land transfer in the two provinces. Common factors influencing farmers' land transfer willingness in both provinces include: the educational level of household heads, the health status of household heads, the number of family laborers, the arable land area, the differentiation of agricultural management objectives, the proportion of agricultural operating income, labor service economy, and relocation policies. Factors showing different influences include: the age of household heads, school-age children, the number of family members engaged in different occupations, the proportion of income from off-farm employment, minimum guarantee policies credit support, location distance, and terrain undulation. Therefore, in formulating land transfer policies, the government should prioritize significant driving factors influencing farmers' decision-making behavior in different regions. It is essential to develop and implement land transfer policies tailored to local conditions with the primary goal of safeguarding the rights and interests of the principal stakeholders, thus achieving sustainable land utilization. [ABSTRACT FROM AUTHOR]

Land use changes significantly impact the structure and functioning of ecosystems. The current research focus lies in how to utilize economic and policy instruments to regulate conflicts among stakeholders effectively. The objective is to facilitate rational planning and sustainable development of land utilization resources. The PLUS model integrates a rule-based mining method for land expansion analysis and a CA model based on multi-type stochastic seeding mechanism, which can be used to mine the driving factors of land expansion and predict the patch-level evolution of land use landscapes. Using the PLUS model, a simulation was conducted to study the future land use distribution in the research area over the next 30 years. Based on land use data from Guizhou Province in 2000, 2010, and 2020, a total of 16 driving factors were selected from three aspects: geographical environment, transportation network, and socio-economic conditions. Four scenarios, namely natural development, urban development, ecological conservation, and farmland rotection, were established. Comparative analysis of the simulated differences among the various scenarios was performed. (1) The overall accuracy of the land use simulation using the PLUS model in the study area was 0.983, with a Kappa coefficient of 0.972 and a FoM coefficient of 0.509. The research accuracy meets the simulation requirements. (2) Through the simulation of four different scenarios, the study investigated the land use changes in Guizhou Province over the next 30 years. Each scenario exhibited distinct impacts on land utilization. Comprehensive comparison of the different simulation results revealed that the farmland protection scenario aligns with the sustainable development goals of the research area. Currently, there is a relative scarcity of research on land use simulation, particularly in model application, for Guizhou Province. This study aims to provide a reference for the rational planning of land resources and high-quality urban construction in Guizhou, promoting the high-quality economic development in tandem with advanced ecological and environmental protection. [ABSTRACT FROM AUTHOR]

When nutrient level in the soil surpasses vegetation demand, nutrient losses due to surface runoff and subsurface leaching are the major reasons for the deterioration of water quality. The Lower Mississippi river basin (LMRB) is one of the sub-basins that deliver the highest nitrogen loads to the Gulf of Mexico. Potential changes in episodic events induced by hurricanes may exacerbate water quality issue in the future. However, uncertainties in modeling the hydrologic response to hurricanes may limit the modeling of nutrient losses during such events. Using a machine learning approach, we calibrated the land component of the Energy Exascale Earth System model (E3SM), or ELM, version 2.1, based on the water table depth (WTD) of a calibrated 3D subsurface hydrology model. While the overall performance of the calibrated ELM is satisfactory, some discrepancies in WTD remain in slope areas with low precipitation due to the missing lateral flow process in ELM. Simulations including biogeochemistry performed using ELM with and without model calibration showed important influences of soil hydrology, precipitation intensity, and runoff parameterization on the magnitude of nitrogen runoff loss and leaching pathway. Despite such sensitivities, both ELM simulations produced reduced WTD and increased runoff and accelerated nitrate-nitrogen runoff loading during Hurricane Ida in August 2021, consistent with the observations. With observations suggesting more pronounced effects of Hurricane Ida on nitrogen runoff than the simulations, we identified factors for model improvement to provide a useful tool for studying hurricane-induced nutrient losses in the LMRB region. [ABSTRACT FROM AUTHOR]

The reasonable spatial planning of primary and secondary schools is an important factor in education development. In spatial planning, there are many models for the locations of primary and secondary schools; however, few quantitative evaluation models are available. Therefore, based on the many factors affecting the layout planning of primary and secondary schools, a knowledge graph of territorial spatial planning that considers the topological relationship, direction relationship and metric relationship in spatial planning is designed and constructed. A school location evaluation model based on the knowledge graph of territorial spatial planning is proposed. The model combines many factors of the locations of schools, such as the service population, the impact of factories on schools, the adjacency and centrality of school plots, terrain and existing schools in the region, to quantitatively evaluate whether schools are reasonably located within a region. This study focuses on the Guangyang Island area in Chongqing, China, exploring the superiority and rationality of the planned land use for primary and secondary schools within the region. By analyzing the top three and bottom three ranked schools in conjunction with the actual conditions of the site, and comparing them with AHP hierarchical analysis and ArcGIS modelling research, the study concludes that the results of this model are highly reasonable within the scope of China's territorial spatial planning. [ABSTRACT FROM AUTHOR]

Other effective area-based conservation measures (OECMs) have been a feature of global biodiversity targets since 2010 (Aichi Targets, Kunming-Montreal Global Biodiversity Framework), although the concept has only relatively recently been formally defined. Although uptake has been limited to date, there is much interest in identifying OECMs to contribute to the target of protecting at least 30% of terrestrial, freshwater and ocean areas by 2030, in conjunction with protected areas. Australia has a long history of protected area development across public, private and Indigenous lands, but consideration of OECMs in policy has recently begun in that country. We review principles proposed by the Australian Government for OECMs in Australia and highlight where these deviate from global guidance or established Australian area-based policy. We examined various land use categories and conservation mechanisms to determine the likelihood of these categories/mechanisms meeting the OECM definition, with a particular focus on longevity of the mechanism to sustain biodiversity. We identified that the number of categories/mechanisms that would meet the OECM definition is relatively small. A number of potentially perverse outcomes in classifying an area as an OECM are highlighted in order to guide proactive policy and program design to prevent such outcomes occurring. [ABSTRACT FROM AUTHOR]

Simple Summary: The utilization of reclaimed land and enhancement of its productivity are crucial for alleviating China's food production shortage. Previous research has indicated that co-cultivating rice with frogs can enhance soil fertility. However, there is limited research on the use of integrated rice–frog farming techniques to improve soil fertility on reclaimed barren land for enhanced food production efficiency. Therefore, this study evaluated the impact of rice–frog co-cultivation on soil fertility and microbial diversity of reclaimed land. Experimental plots were established for rice monoculture, low-density rice–frog co-cultivation, and high-density rice–frog co-cultivation. The study found that during the rice maturity period, the soil fertility in the plots with high-density rice–frog co-cultivation was significantly higher compared to the rice monoculture plots. Additionally, rice–frog co-cultivation increased the soil microbial diversity and altered the structure of the microbial community compared to the rice monoculture. This research indicates that compared with rice monoculture, rice–frog co-cultivation can enhance the soil fertility and microbial diversity of reclaimed land. This study provides a theoretical basis for the construction of integrated farming models on reclaimed land, offering new perspectives and opportunities for the efficient utilization of such land. Utilizing and improving the productivity of reclaimed land are highly significant for alleviating the problem of food production shortage in China, and the integrated rice–frog farming model can improve soil fertility. However, there are few studies on the use of integrated rice–frog farming technology to improve the fertility of reclaimed land and increase its efficiency in food production. Therefore, this study was conducted to evaluate the effects of the rice–frog co-cropping mode on the soil fertility and microbial diversity of reclaimed land. A rice monoculture group (SF), low-density rice–frog co-cropping group (SD, 5000 frogs/mu, corresponds to 8 frogs/m2), and high-density rice–frog co-cropping group (SG, 10,000 frogs/mu, corresponds to 15 frogs/m2) were established and tested. The contents of total nitrogen, soil organic matter, available potassium, and available phosphorus of the soil in the SG group were significantly higher than those in the SF group (p < 0.05) in the mature stage of rice. Compared with the SF group, the SD and SG groups improved the soil microbial diversity and changed the structure of the microbial community. This study indicates that compared with the rice monoculture mode, the rice–frog co-cropping pattern can improve the soil fertility, as well as microbial diversity, of reclaimed land. [ABSTRACT FROM AUTHOR]

Important metapopulation dynamics are disrupted by factors such as habitat loss, climate change, and human-induced mortality, culminating in isolated wildlife populations and threatening species survival. Source populations, where birth rates exceed mortality and connectivity facilitates dispersal, contrast with sink populations, where mortality outstrips births, risking localised extinction. Recolonisation by individuals from source populations is pivotal for species survival. The leopard is the last free-roaming apex predator in South Africa and plays an important ecological role. In the Eastern and Western Cape provinces in South Africa, leopard populations have low densities and fragmented population structures. We identified a leopard population that, after being locally extinct for a century, appeared to recolonise an 'island' of mountainous habitat. We aimed to understand potential factors driving this recolonisation using recent camera trapping surveys and historical statutory destruction permits. We employed spatially explicit capture–recapture (SECR) methods to estimate the leopard density and explore potential factors which best explain density. We found that the recently recolonised Piketberg population now exhibits some of the highest densities reported in the region (~1.8 leopards/100 km2; CI 1.4–2.5). Livestock, human presence, elevation, and the camera trap grid appeared to explain leopard detection rates. When considering the historic data, the re-emergence of leopards in the Piketberg coincided with the cessation of the extensive state-sponsored and state-enabled culling of the species, and the change in land use from livestock production to crop agriculture, which likely contributed to the recolonisation. Elucidating these factors deepens our understanding of leopard metapopulation dynamics in relation to land use and species management and highlights the crucial role of private land and state agencies and associated policies in species persistence. [ABSTRACT FROM AUTHOR]

Given the effect of urbanization on land use and the allocation and implementation of urban green spaces, this paper attempts to analyze the distribution and accessibility of public parks in India's Bengaluru city (previously known as Bangalore). Availability, accessibility, and utilization—the key measures of Urban Green Spaces (UGS)—are mostly used in health research and policy and are important components of Planetary Health Equity in the context of studying UGSs and health. A geo-spatial method was used for mapping the park's distribution and measuring its accessibility, using road network data. To understand equitable access to the parks, four socio-economic parameters—population density, the percentage of the population below 6 years of age, the proxy wealth index, and scheduled caste population—were correlated with the parks' accessibility. This spatial distribution revealed that 19 of 198 wards did not have a single park and that 36 wards only had one park. About 25–29% of wards did not have accessibility to neighborhood-level and community-level parks within a 400–800 m distance. These parks must be accessible within a walking distance of 400–800 m but were found to most likely be inaccessible on the periphery of the city where the population density is low and the children population is high, in comparison to the central part of the city. Similarly, parks were found to be inaccessible in the eastern part of the city where the scheduled caste population is high and also found to be inaccessible for the low-income neighborhoods residing in the western part and southern periphery of the city, indicating the uneven distribution of and inequitable access to public parks. Our study proposes a reshaping of both neighborhood parks and community parks in an attempt to look beyond biodiversity, through the planetary health equity approach, by noting that, while biodiversity indirectly has a positive effect on health, public parks should not only be considered as advancing environmental sustainability and climate resilience, but also as improving the health and wellbeing of the population. Affirmative action in terms of the availability of public parks with adequate area requirements and essential services at a neighborhood scale is required to redress the inequity of access; in addition, the accessibility of parks must be considered important during urban planning. [ABSTRACT FROM AUTHOR]

Understanding the spatial–temporal patterns of air pollution is crucial for mitigation strategies, a task fostered nowadays by the generation of continuous concentration maps by remote sensing technologies. We applied spatial modelling to analyze such spatial–temporal patterns in Lombardy, Italy, one of the most polluted regions in Europe. We conducted monthly spatial autocorrelation (global and local) of the daily average concentrations of PM2.5, PM10, O3, NO2, SO2, and CO from 2016 to 2020, using 10 × 10 km satellite data from the Copernicus Atmosphere Monitoring Service (CAMS), aggregated on districts of approximately 100,000 population. Land-use classes were computed on identified clusters, and the significance of the differences was evaluated through the Wilcoxon rank-sum test with Bonferroni correction. The global Moran's I autocorrelation was overall high (>0.6), indicating a strong clustering. The local autocorrelation revealed high–high clusters of PM2.5 and PM10 in the central urbanized zones in winter (January–December), and in the agrarian southern districts in summer and autumn (May–October). The temporal decomposition showed that values of PMs are particularly high in winter. Low–low clusters emerged in the northern districts for all the pollutants except O3. Seasonal peaks for O3 occurred in the summer months, with high–high clusters mostly in the hilly and mildly urban districts in the northwest. These findings elaborate the spatial patterns of air pollution concentration, providing insights for effective land-use-based pollution management strategies. [ABSTRACT FROM AUTHOR]

Climate change has become a global issue and is predicted to impact less-developed regions, such as sub-Saharan Africa, severely. Innovative, sustainable renewable energy systems are essential to mitigate climate change's effects and unlock the region's potential, especially with the increasing energy demands and population growth. The region relies heavily on fossil fuels, which calls for urgent action towards energy security and expansion. Hybrid floating solar photovoltaic-hydropower (FPV-HEP) technology has emerged as a cost-effective and transformative solution to accelerate the low-carbon energy transition in sub-Saharan Africa. The technology combines solar panels with existing hydropower infrastructure, ensuring energy security while reducing carbon emissions. This technology offers several benefits over conventional ground-mounted solar systems, including efficient land utilization, energy generation, and water conservation. However, its adoption remains challenging due to technical complexities and evolving regulatory frameworks. Despite these challenges, Nigerian energy professionals have preferred renewable alternatives, mainly distributed solar PV and FPV-HEP plants. This collective embrace of FPV and renewables reflects a growing understanding of their critical role in mitigating climate change through sustainable energy practices. This research aims to contribute to the existing body of knowledge and assist policymakers in making informed decisions on adopting this technology. It also stimulates further research on this topic, offering a new potential solution to the ever-increasing demand for green energy in the region to meet their sustainable development needs. [ABSTRACT FROM AUTHOR]

We analyzed the two main drivers (climate and land uses) shaping the composition of small mammal communities at 16 localities situated in the confluence of the Mediterranean and Eurosiberian regions (Barcelona, Spain). The study area represents a land use and land cover gradient showing urbanization and crop intensification in the lowlands and forest encroachment in mountain areas. We identified 2458 small mammal individuals of 12 different species from barn owl (Tyto alba) pellets. Three open-land species (Microtus duodecimcostatus, Crocidura russula, and Mus spretus) and one forest/generalist species (Apodemus sylvaticus) were dominant in the diet, accounting for 93% of prey. In order to disentangle the effects of both main drivers on the small mammal community, we used partial constrained ordination techniques, which allowed us to determine the pure effects (and shared effects) of the environmental factors. Land use predictors explained 33.4% of the variance (mostly crops), followed by 23.4% of the variance explained by the geo-climatic variables (mostly rainfall), and an additional 24.8% of the variance was shared by both groups of predictors, totaling 81.6% of environmental variance. The remaining 18.4% of variance was unexplained by environmental matrices. This pattern was consistent with expected associations of species and biotic influences at small spatial scales and highlighted that the number of species increased from the crops in the lowlands towards the highlands covered by deciduous and coniferous forests. [ABSTRACT FROM AUTHOR]

Recent international agreements have strengthened and expanded commitments to protect and restore native habitats for biodiversity protection ("area‐based biodiversity conservation"). Nevertheless, biodiversity conservation is hindered because how such commitments should be implemented has been strongly debated, which can lead to suboptimal habitat protection decisions. We argue that, despite the debates, there are three essential principles for area‐based biodiversity conservation. These principles are related to habitat geographic coverage, amount, and connectivity. They emerge from evidence that, while large areas of nature are important and must be protected, conservation or restoration of multiple small habitat patches is also critical for global conservation, particularly in regions with high land use. We contend that the many area‐based conservation initiatives expected in the coming decades should follow the principles we identify, regardless of ongoing debates. Considering the importance of biodiversity for maintenance of ecosystem services, we suggest that this would bring widespread societal benefits. [ABSTRACT FROM AUTHOR]

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

Ethiopia, marked by diverse geography and rapid land use/land cover (LULC) changes, grapples with formidable water resource management challenges. Understanding the hydrological response to these changes is paramount for sustainability. This review paper provides an overview of studies that investigated the hydrological impacts of LULC changes in Ethiopian basins. The review discusses methodologies, key findings, implications for sustainable land and water resource management, research gaps, and future directions. Emphasizing results from diverse studies that utilized hydrological and geospatial modelling, LULC significantly affects surface runoff, streamflow patterns, and groundwater recharge. The observed consequences are increased surface runoff, modified streamflow timing, and reduced groundwater recharge. The review underscores the urgency for integrated land and water management strategies to alleviate adverse effects. Future research priorities include basin-specific studies, long-term monitoring, integrated modelling, consideration of socio-economic factors, and incorporating climate change scenarios to enhance understanding and guide sustainable water resource management in Ethiopian basins. [ABSTRACT FROM AUTHOR]

Land‐use and climate change are major pressures on terrestrial biodiversity. Species' extinction risk and responses to human pressures relate to ecological traits and other characteristics in some clades. However, large‐scale comparative assessments of the associations between traits and responses to multiple human pressures across multiple clades are needed. We investigated whether a set of ecological characteristics that are commonly measured across terrestrial vertebrates (ecological traits and geographic range area) are associated with species' responses to different land‐use types and species' likely sensitivity to climate change. We aimed to test whether generalizable patterns in response to these pressures arise across both pressures and across vertebrate clades, which could inform assessments of the global signature of human pressures on vertebrate biodiversity and guide conservation efforts. At the species level, we investigated associations between land‐use responses and ecological characteristics with a space‐for‐time substitution approach, making use of the PREDICTS database. We investigated associations between ecological characteristics and expected climate‐change sensitivity, estimated from properties of species realized climatic niches. Among the characteristics we considered, 3 were consistently associated with strong land‐use responses and high climate‐change sensitivity across terrestrial vertebrate classes: narrow geographic range, narrow habitat breadth, and specialization on natural habitats (which described whether a species occurs in artificial habitats or not). The associations of other traits with species' land‐use responses and climate‐change sensitivity often depended on species' class and land‐use type, highlighting an important degree of context dependency. In all classes, invertebrate eaters and fruit and nectar eaters tended to be negatively affected in disturbed land‐use types, whereas invertebrate‐eating and plant‐ and seed‐eating birds were estimated to be more sensitive to climate change, raising concerns about the continuation of ecological processes sustained by these species under global changes. Our results highlight a consistently higher sensitivity of narrowly distributed species and habitat specialists to land‐use and climate change, which provides support for capturing such characteristics in large‐scale vulnerability assessments. [ABSTRACT FROM AUTHOR]

Ecosystem state transitions can be ecologically devastating or be a restoration success. State transitions are common within aquatic systems worldwide, especially considering human‐mediated changes to land use and water use. We created a transferable conceptual framework to enable multiscale assessments of state resilience and early warnings of state transitions that can inform strategic restorations and avoid ecosystem collapse. The conceptual framework integrated machine learning predictions with ecosystem state concepts (e.g., state classification, gradients of vulnerability, and recovery potential leading to state transitions) and was devised to investigate possible environmental drivers. As an application of the framework, we generated prediction probabilities of submersed aquatic vegetation (SAV) presence at nearly 10,000 sites in the Upper Mississippi River (United States). Then, we used an interpretability method to explain model predictions to gain insights into possible environmental drivers and thresholds or linear responses of SAV presence and absence. Model accuracy was 89% without spatial bias. Average water depth, suspended solids, substrate, and distance to nearest SAV were the best predictors and likely environmental drivers of SAV habitat suitability. These environmental drivers exhibited nonlinear, threshold‐type responses for SAV. All the results are also presented in an online dashboard to explore results at many spatial scales. The habitat suitability model outputs and prediction explanations from many spatial scales (4 m to 400 km of river reach) can inform research and restoration planning. [ABSTRACT FROM AUTHOR]

The Yellow River Delta (YRD), known for its vast and diverse wetland ecosystem, is the largest estuarine delta in China. However, human activities and climate change have significantly degraded the wetland ecosystem in recent decades in the YRD. Therefore, an understanding of the land use modifications is essential for the efficient management and preservation of ecosystems in this region. This study utilized time series of remote sensing data and the extreme gradient boosting method to generate land use maps of the YRD from 2000 to 2020. Several methods, including transition matrix, land use dynamic degree, and standard deviation ellipse, were employed to explore the characteristics of land use transitions. The results underscore significant spatial variations in land use over the past two decades. The most rapid increase was observed in built-up area, followed by terrestrial water and tidal flats, while unutilized land experienced the fastest decrease, followed by forest–grassland. The spatial distribution patterns of agricultural land, built-up area, terrestrial water, and forest–grassland demonstrated stronger directionality compared to other land use types. The wetlands have expanded in size and improved in structure. Unutilized land has been converted into artificial wetlands comprising ponds, reservoirs, salt ponds, shrimp and crab ponds, and natural wetlands featuring mudflats and forest–grassland. The wetland conservation efforts after 2008 have proven very effective, playing a positive role in ecological and environmental preservation, as well as in regional sustainable development. [ABSTRACT FROM AUTHOR]

Background: Mangrove ecosystems exhibit significant carbon storage and sequestration. Its capacity to store and sequester significant amounts of carbon makes this ecosystem very important for climate change mitigation. Indonesia, owing to the largest mangrove cover in the world, has approximately 3.14 PgC stored in the mangroves, or about 33% of all carbon stored in coastal ecosystems globally. Unfortunately, our comprehensive understanding of carbon flux is hampered by the incomplete repertoire of field measurement data, especially from mangrove ecosystem-rich regions such as Indonesia and Asia Pacific. This study fills the gap in greenhouse gases (GHGs) flux studies in mangrove ecosystems in Indonesia by quantifying the soil CO2 and CH4 fluxes for different land use types in mangrove ecosystems, i.e., secondary mangrove (SM), restored mangrove (RM), pond embankment (PE) and active aquaculture pond (AP). Environmental parameters such as soil pore salinity, soil pore water pH, soil temperature, air temperature, air humidity and rainfall are also measured. Results: GHG fluxes characteristics varied between land use types and ecological conditions. Secondary mangrove and exposed pond embankment are potential GHG flux sources (68.9 ± 7.0 and 58.5 ± 6.2 MgCO2e ha− 1 yr− 1, respectively). Aquaculture pond exhibits the lowest GHG fluxes among other land use types due to constant inundation that serve as a barrier for the release of GHG fluxes to the atmosphere. We found weak relationships between soil CO2 and CH4 fluxes and environmental parameters. Conclusions: The data and information on GHG fluxes from different land use types in the mangrove ecosystem will be of importance to accurately assess the potential of the mangrove ecosystem to sequester and emit GHGs. This will support the GHG emission reduction target and strategy that had been set up by the Indonesian Government in its Nationally Determined Contributions (NDC) and Indonesia's 2030 Forest and Other Land Use (FOLU) Net Sink. [ABSTRACT FROM AUTHOR]

For decades, the United States Department of the Interior's land acquisition regulations included an "Alaska Exception" that barred acquisition of land into trust in Alaska apart from those acquisitions made for the Metlakatla Indian Community. Although the "Alaska Exception" was initially removed from the regulations in 2014, the fight continues over land-into-trust acquisitions within Alaska. Throughout these debates, the state of Alaska has consistently opposed land-into-trust acquisitions. This Practitioner Guide provides an overview of the recent history of land-into-trust acquisitions in Alaska and analyzes the juxtaposition of the intent behind Alaska's "State Recognition of Tribes" in House Bill 123 and the continuing state opposition to land-into-trust applications. Specifically, this Practitioner Guide argues that, without state collaboration and cooperation with Tribal Nations on landinto-trust issues, House Bill 123, which was meant to signify "the State's desire to foster engagement with Alaska Natives and tribal organizations," ultimately rings hollow. [ABSTRACT FROM AUTHOR]

In landscape ecology, it has become increasingly essential to understand the consequences of past, current, and future human land use patterns for biodiversity and ecosystem function. The most significant factor affecting biodiversity loss is land-use and land-cover change (LULCC). We examine here the impact of long-term changes in LULCC from 2000–2020 on the biodiversity of Marghazar valley in Swat District. Information was also gathered on the perceptions of the surrounding communities based on the flow of ecosystem services (ES), historical changes, and the causes of those changes. Satellite imagery data were used to map LULCC, identify possible causes, and assess the impact of LULCC on the population of partridges. In the last 20 years, forest area has reduced by 23 km2 (33%) and the seasonal water body has declined by 1.015 km2 (2.15%). There was a 38.5 km2 decrease in agricultural land. In contrast, the built-up area increased by 384%, resulting in a total growth of 26.3 km2 and an expansion of 41.1 km2 grassland. Deforestation, agricultural expansions, urbanization, economic considerations and changes in land tenure policy were identified to be the main drivers of LULCC. The primary impact of LULCC on partridges in the studied area are land degradation, population declines, habitat disruption, displacement of partridges by livestock and increasing human-wildlife conflicts. Despite ongoing human pressure, the Marghazar valley still provides extensive habitat for wildlife. Interventions may be needed to maintain biodiversity and ensure long-term ecological services in the area. [ABSTRACT FROM AUTHOR]

Degraded peat has a high potential for use in agricultural production, especially food crops. The water table, which impacts the production of greenhouse gases (GHGs), is the main problem concerning peat utilization. The study aimed to determine the production of greenhouse gases at various peat water levels. The study was conducted in a laboratory setting utilizing the soil column of undisturbed peat soil. The factorial experiment was arranged in randomized block design, with three replicates, with the first factor was peat cropping use: Maize (Zea mays L.), pineapple (Ananas comosus (L.) Merr.), and scrubs. The second factor was water level (0, 10, 20, 30 cm depth). Variables measured were GHG flux (CO2 and CH4), pH, redox potential, total C content, and ash content. The peat cropping use interacted significantly with the peat water level on the potential for CH4 and CO2 production and the value of global warming potential. Water table depth significantly increased CO2 flux and global warming potential (GWP) in all three peat cropping uses. The lowest GWP at a 0 cm peat water level was 944 (pineapple use), 961 (maize use), and 1097 mg CO2e m-2 d-1 (scrub use). Peat for pineapple cultivation produces the lowest CO2 production and GWP compared to maize cultivation and scrubs. The negative relationship between redox potential and GWP is significant in peat for scrub. The relationship between pH and GWP is significant in peat for pineapple and scrub. [ABSTRACT FROM AUTHOR]

Native ecosystem and biodiversity loss from land use conversion into human‐modified landscapes are evident in the United States and globally. In addition to public land conservation, there is an increase in private land conservation through conservation easements (CEs) across exurban landscapes. Not every CE was established strictly for biodiversity protection and permitted land uses can increase human modification. No research of which we are aware has examined the actual tax assessor's land use designations (LUDs) through time. We constructed granular CE datasets (GCED) of CEs and their parcels' tax assessment LUDs for 1997–2008/2009, based on original data from 12 counties in six US states. Using the GCED, we examined patterns in the LUDs, with implications for land uses that could impact CE biological outcomes. We show that LUDs on exurban private conservation lands were predominately residential and agricultural, with increased residential over time. Critically, the LUDs lack a biological conservation exempt designation/category. There is no consistent trend in association between the primary CE reason and its parcel's LUD, suggesting that they coincide in some circumstances but in others, the CE may be a response to contravene the LUD. The majority of the first CE reasons are focused on open space preservation, except in some counties where agricultural land uses and agricultural CEs are associated. The economically and human‐focused LUD is one of many social factors that should be considered in a classification system for private land conservation and CEs more specifically. These results prompt the land conservation, conservation biology, and environmental planning communities to explore assessed land uses' impact on biodiversity conservation objectives. [ABSTRACT FROM AUTHOR]

Internal displacement of populations due to armed conflicts can substantially impact a region's Land Use and Land Cover (LULC) and the efforts towards the achievement of Sustainable Development Goals (SDGs). The objective of this study was to determine the effects of conflict-driven Internally Displaced Persons (IDPs) on vegetation cover and environmental sustainability in the Kas locality of Darfur, Sudan. Supervised classification and change analysis were performed on Sentinel-2 satellite images for the years 2016 and 2022 using QGIS software. The Sentinel-2 Level 2A data were analysed using the Random Forest (RF) Machine Learning (ML) classifier. Five land cover types were successfully classified (agricultural land, vegetation cover, built-up area, sand, and bareland) with overall accuracies of more than 86% and Kappa coefficients greater than 0.74. The results revealed a 35.33% (-10.20 km2) decline in vegetation cover area over the six-year study period, equivalent to an average annual loss rate of -5.89% (-1.70 km2) of vegetation cover. In contrast, agricultural land and built-up areas increased by 17.53% (98.12 km2) and 60.53% (5.29 km2) respectively between the two study years. The trends of the changes among different LULC classes suggest potential influences of human activities especially the IDPs, natural processes, and a combination of both in the study area. This study highlights the impacts of IDPs on natural resources and land cover patterns in a conflict-affected region. It also offers pertinent data that can support decision-makers in restoring the affected areas and preventing further environmental degradation for sustainability. [ABSTRACT FROM AUTHOR]

We conducted a hospital-based case–control study to explore the association between proximity to various land use types and childhood leukemia and lymphoma. This research involved 428 cases of childhood leukemia and lymphoma (2016–2021), along with a control group of 428 children aged 1–15 in Tehran. We analyzed the risk of childhood cancer associated with land use by employing logistic regression adjusted for confounding factors such as parental smoking and family history. The odds ratio (OR) for children with leukemia and lymphoma residing within 100 m of the nearest highway was 1.87 (95% CI = 1.00–3.49) and 1.71 (95% CI = 1.00–2.93), respectively, in comparison to those living at a distance of 1000 m or more from a highway. The OR for leukemia with exposure to petrol stations within 100 m was 2.15 (95% CI = 1.00–4.63), and for lymphoma it was 1.09 (95% CI = 0.47–2.50). A significant association was observed near power lines (OR = 3.05; 95% CI = 0.97–9.55) within < 100 m for leukemia. However, no significant association was observed between power lines and the incidence of childhood lymphoma. There was no association between bus stations, major road class 2, and the incidence of childhood leukemia and lymphoma. In conclusion, our results suggest a possible association between the incidence of childhood leukemia and proximity to different urban land uses (i.e., highways and petrol stations). This study is the first step in understanding how urban land use affects childhood leukemia and lymphoma in Tehran. However, comprehensive studies considering individual-level data and specific pollutants are essential for a more nuanced understanding of these associations. [ABSTRACT FROM AUTHOR]

Shared Autonomous Vehicles (SAVs) are expected to have a transformative role in future transportation systems, by reducing vehicle ownership, helping in alleviating congestion, improving accessibility and traffic safety, and changing travel behavior and urban infrastructure. The potential introduction of SAVs in transportation systems has triggered the need of exploiting suitable tools for designing and planning SAV operations and services and assessing their impacts. An explicit category of such tools are agent-based models (ABMs), whose advantage in efficiently representing transportation systems with a fine level of detail, has allowed them to gain importance in modeling SAVs. This paper systematically reviews and organizes the current state-of-the-art on ABMs dealing with SAVs. The review is two-fold: first, the methodological aspects of exploiting ABMs in the context of SAV services and operations are analyzed and second, ABM-based findings on the anticipated impacts of SAVs to traffic, travel behavior, land uses, the environment and so on, are presented and discussed. The paper concludes with recommendations for future research on SAVs and other, potential ABM applications for that purpose. [ABSTRACT FROM AUTHOR]

Accurately assessing and predicting the impacts of land use changes on ecosystem carbon stocks in the Yellow River Basin (YRB) and exploring the optimization of land use structure to increase ecosystem carbon stocks are of great practical significance for China to achieve the goal of "double carbon". In this study, we used multi-year remote sensing data, meteorological data and statistical data to measure the ecosystem carbon stock in the YRB from 2000 to 2020 based on the InVEST model, and then simulated and measured the ecosystem carbon stock under four different land use scenarios coupled with the FLUS model in 2030. The results show that, from 2000 to 2020, urban expansion in the YRB continued, but woodland and grassland grew more slowly. Carbon stock showed an increasing trend during the first 20 years, with an overall increase of 7.2 megatons, or 0.23%. Simulating the four land use scenarios in 2030, carbon stock will decrease the most under the cropland protection scenario, with a decrease of 17.7 megatons compared with 2020. However, carbon stock increases the most under the ecological protection scenario, with a maximum increase of 9.1 megatons. Furthermore, distinct trends in carbon storage were observed across different regions, with significant increases in the upstream under the natural development scenario, in the midstream under the ecological protection scenario and in the downstream under the cropland protection scenario. We suggest that the upstream should maintain the existing development mode, with ecological protection prioritized in the middle reaches and farmland protection prioritized in the lower reaches. This study provides a scientific basis for the carbon balance, land use structure adjustment and land management decision-making in the YRB. [ABSTRACT FROM AUTHOR]

Wetlands are integral components of agricultural landscapes, providing a wide range of ecological, economic, and social benefits essential for sustainable development and rural livelihoods. Globally, they are vulnerable ecological assets facing several significant threats including water extraction and regulation, land clearing and reclamation, and climate change. Classification and mapping of wetlands in agricultural landscapes is crucial for conserving these ecosystems to maintain their ecological integrity amidst ongoing land-use changes and environmental pressures. This study aims to establish a robust framework for wetland classification and mapping in intensive agricultural landscapes using time series of Sentinel-2 imagery, with a focus on the Gwydir Wetland Complex situated in the northern Murray–Darling Basin—Australia's largest river system. Using the Google Earth Engine (GEE) platform, we extracted two groups of predictors based on six vegetation indices time series calculated from multi-temporal Sentinel-2 surface reflectance (SR) imagery: the first is statistical features summarizing the time series and the second is phenological features based on harmonic analysis of time series data (HANTS). We developed and evaluated random forest (RF) models for each level of classification with combination of different groups of predictors. Our results show that RF models involving both HANTS and statistical features perform strongly with significantly high overall accuracy and class-weighted F1 scores (p < 0.05) when comparing with models with either statistical or HANTS variables. While the models have excellent performance (F-score greater than 0.9) in distinguishing wetlands from other landcovers (croplands, terrestrial uplands, and open waters), the inter-class discriminating power among wetlands is class-specific: wetlands that are frequently inundated (including river red gum forests and wetlands dominated by common reed, water couch, and marsh club-rush) are generally better identified than the ones that are flooded less frequently, such as sedgelands and woodlands dominated by black box and coolabah. This study demonstrates that HANTS features extracted from time series Sentinel data can significantly improve the accuracy of wetland mapping in highly fragmentated agricultural landscapes. Thus, this framework enables wetland classification and mapping to be updated on a regular basis to better understand the dynamic nature of these complex ecosystems and improve long-term wetland monitoring. [ABSTRACT FROM AUTHOR]

Change detection is crucial for evaluating land use, land cover changes, and sustainable development, constituting a significant component of Earth observation tasks. The difficulty in extracting features from high-resolution images, coupled with the complexity of image content, poses challenges for traditional change detection algorithms in terms of accuracy and applicability. The recent emergence of deep learning methods has led to substantial progress in the field of change detection. However, existing frameworks often involve the simplistic integration of bi-temporal features in specific areas, lacking the fusion of temporal information and semantic details in the images. In this paper, we propose an attention-guided multi-scale fusion network (AMFNet), which effectively integrates bi-temporal image features and diverse semantics at both the encoding and decoding stages. AMFNet utilizes a unique attention-guided mechanism to dynamically adjust feature fusion, enhancing adaptability and accuracy in change detection tasks. Our method intelligently incorporates temporal information into the deep learning model, considering the temporal dependency inherent in these tasks. We decode based on an interactive feature map, which improves the model's understanding of evolving patterns over time. Additionally, we introduce multi-level supervised training to facilitate the learning of fused features across multiple scales. In comparison with different algorithms, our proposed method achieves F1 values of 0.9079, 0.8225, and 0.8809 in the LEVIR-CD, GZ-CD, and SYSU-CD datasets, respectively. Our model outperforms the SOTA model, SAGNet, by 0.69% in terms of F1 and 1.15% in terms of IoU on the LEVIR-CD dataset, by 2.8% in terms of F1 and 1.79% in terms of IoU on the GZ-CD dataset, and by 0.54% in terms of F1 and 0.38% in terms of IoU on the SYSU-CD dataset. The method proposed in this study can be applied to various complex scenarios, establishing a change detection method with strong model generalization capabilities. [ABSTRACT FROM AUTHOR]

The West Sahel is facing significant threats to its vegetation and wildlife due to the land degradation and habitat fragmentation. It is crucial to assess the regional vegetation greenness dynamics in order to comprehensively evaluate the effectiveness of protection in the natural reserves. This study analyzes the vegetation greenness trends and the driving factors in the Dosso Partial Faunal Reserve in Niger and nearby unprotected regions—one of the most important habitats for endemic African fauna—using satellite time series data from 2001 to 2020. An overall vegetation browning trend was observed throughout the entire region with significant spatial variability. Vegetation browning dominated in the Dosso Reserve with 17.7% of the area showing a significant trend, while the area with significant greening was 6.8%. In a comparison, the nearby unprotected regions to the north and the east were found to be dominated by vegetation browning and greening, respectively. These results suggest that the vegetation protection practice was not fully effective throughout the Dosso Reserve. The dominant drivers were also diagnosed using the Random Forest model-based method and the Partial Dependence Plot tool, showing that water availability (expressed as soil moisture) and land use/land cover change were the most critical factors affecting vegetation greenness in the study region. Specifically, soil moisture stress and specific land management practices associated with logging, grazing, and land clearing appeared to dominate vegetation browning in the Dosso Reserve. In contrast, the vegetation greening in the central Dosso Reserve and the nearby unprotected region to the east was probably caused by the increase in shrubland/forest, which was related to the effective implementation of protection. These findings improve our understanding of how regional vegetation greenness dynamics respond to environmental changes in the Dosso Reserve and also highlight the need for more effective conservation planning and implementation to ensure sustainable socio-ecological development in the West Sahel. [ABSTRACT FROM AUTHOR]

The "Yangtze River Economic Belt Development Strategy" is one of China's three major national development strategies. Enhancing the protection and quality of arable land in the Yangtze River Economic Belt (YEB) is pivotal for fostering regional growth. In this study, land use data spanning the years 1980 to 2020 in the YEB were extracted from the national land use database maintained by the Resource and Environment Data Center of the Chinese Academy of Sciences. Employing Geographic Information System (GIS) spatial analysis techniques and arable land change metrics, the study delineated the spatiotemporal characteristics of arable land alterations across the YEB for the period. Additionally, using grain output data at the prefecture level from 2011 to 2020, the paper calculated provincial grain output to analyze the impact of arable land changes over the last four decades on grain output. The findings revealed that: (1) From 1980 to 2020, the total arable land area in the YEB decreased by approximately 41,775 square kilometers, with the most significant decrease occurring in the downstream region. (2) From 1980 to 1990, the primary factor contributing to the decrease in arable land area was the expansion of water bodies, while from 1990 to 2020, the principal reason for the reduction in arable land area was the expansion of construction land. (3) From 1980 to 2020, the decrease in arable land area resulted in a net reduction of approximately 25.12 million tons in total grain output, with the largest decline observed in the downstream regions and the smallest decline in the upstream regions. (4) Consistent with the trends in arable land area reduction, the main reason for the decline in grain output from 1980 to 1990 was the expansion of water bodies encroaching upon arable land, whereas from 2000 to 2010, the primary cause of arable land reduction was the expansion of construction land areas. In conclusion, the research suggested that over the past four decades, the primary driver behind the reduction in arable land within the YEB has been the expansion of construction land areas. Particularly noteworthy was the period from 2000 to 2010, during which the impact of arable land reduction on grain output was most pronounced. This period coincided with the rapid economic development and accelerated urbanization process within the YEB. [ABSTRACT FROM AUTHOR]

Producers of biofuels for the EU market may use 'low ILUC-risk' certification as evidence that they have not deprived other economic sectors of feedstock material, and hence that indirect land use change (ILUC) emissions have been avoided. At present, the uptake of low ILUC-risk certification is limited to a handful of niche projects, as there is little commercial incentive for obtaining certification. This may be considered a missed opportunity, because low ILUC-risk farming methods offer a range of sustainability co-benefits beyond the mitigation of ILUC emissions. This paper examines the policy foundations of low ILUC-risk and develops policy recommendations that would aim to confer advantages to low ILUC-risk biofuels. Some weaknesses in the low ILUC-risk system's environmental safeguards are also highlighted. [ABSTRACT FROM AUTHOR]

Soil erosion is one of the major environmental concerns, causing a reduction in soil carbon stock and soil fertility. It is generally difficult to estimate soil erosion in hilly terrains. To overcome this, different types of erodibility indices are developed and used to describe the intensity of soil erosion. The present study was conducted in Nagaland state of northeast India, where clay ratio (CR), modified clay ratio (MCR), critical level of organic matter (CLOM) and erodibility factor (K) were used to assess the severity of soil erosion under different land uses. To study these, soil samples from forest, jhum, fallow jhum and tea gardens were collected from 0 to 30 cm soil depth. The results showed that sand and clay content were significantly different under different land uses, while soil organic carbon (SOC) and stocks followed the same trend, with maximum and minimum values under tea (60.55 t C ha–1 ) and jhum lands (40.74 t C ha–1 ) respectively. Among the different erodibility indices, only CR and MCR values were found to be significantly different from each other. Higher values of CR and MCR under jhum and fallow jhum lands indicate that these land uses are more prone to erosion. The present study provides a picture of severity of soil erosion under different land uses in Nagaland and recommends that CR and MCR can be used to evaluate soil erosion in hilly terrain areas. [ABSTRACT FROM AUTHOR]

Simple Summary: Optimal human health requires the adequate provision of all nutrients in the correct proportions, ensuring the provision of energy and essential small molecules. All primates, including humans, are omnivorous but the most striking difference from other primates is the remarkable diversity of the diets we consume. Animal-sourced foods are important for human nutrition and health, but they can have a negative impact on the environment. The aim here is to examine these impacts that can result in land use tensions associated with population growth and the loss of native forests and wetlands during agricultural expansion, increased greenhouse gas emissions, and high water use with poor water quality outcomes. However, several technologies and practices can be used to mitigate against these impacts. These include grazing when feed quality is high, the use of dietary additives, breeding of animals with higher growth rates and increased fecundity, rumen microbial manipulations using vaccines and other additives, soil management to reduce nitrous oxide emission, management systems to improve carbon sequestration, improved nutrient use efficacy, use of cover crops, low-emission composting barns, covered manure storages, and direct injection of animal slurry into soil. Other technologies and systems to provide further solutions continue to be researched. Animal-sourced foods are important for human nutrition and health, but they can have a negative impact on the environment. These impacts can result in land use tensions associated with population growth and the loss of native forests and wetlands during agricultural expansion. Increased greenhouse gas emissions, and high water use but poor water quality outcomes can also be associated. Life cycle analysis from cradle-to-distribution has shown that novel plant-based meat alternatives can have an environmental footprint lower than that of beef finished in feedlots, but higher than for beef raised on well-managed grazed pastures. However, several technologies and practices can be used to mitigate impacts. These include ensuring that grazing occurs when feed quality is high, the use of dietary additives, breeding of animals with higher growth rates and increased fecundity, rumen microbial manipulations through the use of vaccines, soil management to reduce nitrous oxide emission, management systems to improve carbon sequestration, improved nutrient use efficacy throughout the food chain, incorporating maize silage along with grasslands, use of cover crops, low-emission composting barns, covered manure storages, and direct injection of animal slurry into soil. The technologies and systems that help mitigate or actually provide solutions to the environmental impact are under constant refinement to enable ever-more efficient production systems to allow for the provision of animal-sourced foods to an ever-increasing population. [ABSTRACT FROM AUTHOR]

Remote sensing technologies are critical for analyzing the escalating impacts of global climate change and increasing urbanization, providing vital insights into land surface temperature (LST), land use and cover (LULC) changes, and the identification of urban heat island (UHI) and surface urban heat island (SUHI) phenomena. This research focuses on the nexus between LULC alterations and variations in LST and air temperature (Tair), with a specific emphasis on the intensified SUHI effect in Kharkiv, Ukraine. Employing an integrated approach, this study analyzes time-series data from Landsat and MODIS satellites, alongside Tair climate records, utilizing machine learning techniques and linear regression analysis. Key findings indicate a statistically significant upward trend in Tair and LST during the summer months from 1984 to 2023, with a notable positive correlation between Tair and LST across both datasets. MODIS data exhibit a stronger correlation (R2 = 0.879) compared to Landsat (R2 = 0.663). The application of a supervised classification through Random Forest algorithms and vegetation indices on LULC data reveals significant alterations: a 70.3% increase in urban land and a decrement in vegetative cover comprising a 15.5% reduction in dense vegetation and a 62.9% decrease in sparse vegetation. Change detection analysis elucidates a 24.6% conversion of sparse vegetation into urban land, underscoring a pronounced trajectory towards urbanization. Temporal and seasonal LST variations across different LULC classes were analyzed using kernel density estimation (KDE) and boxplot analysis. Urban areas and sparse vegetation had the smallest average LST fluctuations, at 2.09 °C and 2.16 °C, respectively, but recorded the most extreme LST values. Water and dense vegetation classes exhibited slightly larger fluctuations of 2.30 °C and 2.24 °C, with the bare land class showing the highest fluctuation 2.46 °C, but fewer extremes. Quantitative analysis with the application of Kolmogorov-Smirnov tests across various LULC classes substantiated the normality of LST distributions p > 0.05 for both monthly and annual datasets. Conversely, the Shapiro-Wilk test validated the normal distribution hypothesis exclusively for monthly data, indicating deviations from normality in the annual data. Thresholded LST classifies urban and bare lands as the warmest classes at 39.51 °C and 38.20 °C, respectively, and classifies water at 35.96 °C, dense vegetation at 35.52 °C, and sparse vegetation 37.71 °C as the coldest, which is a trend that is consistent annually and monthly. The analysis of SUHI effects demonstrates an increasing trend in UHI intensity, with statistical trends indicating a growth in average SUHI values over time. This comprehensive study underscores the critical role of remote sensing in understanding and addressing the impacts of climate change and urbanization on local and global climates, emphasizing the need for sustainable urban planning and green infrastructure to mitigate UHI effects. [ABSTRACT FROM AUTHOR]