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The phosphate solubilizing properties of Lysinibacillus macroides ST-30, Pseudomonas pelleroniana N-26, and Bacillus cereus ST-6 were tested for the chickpea crop of the Tarai region of Uttarakhand. These microbially inoculated plants have shown significant (p > 0.05) improvement in the plant health and crop health parameters, viz., root length, shoot length, fresh weight, dry weight, nodule number, nodule fresh weight, nodule dry weight, chlorophyll content, and nitrate reductase. The highest shoot length (46.10 cm) and chlorophyll content (0.57 mg g-1 fresh weight) were observed in ST-30 at 75 DAS with 20 kg P2O5/ha. Similarly, for plant P content, an increase of 90.12% over control was recorded in the same treatment. Treatments consisting of Lysinibacillus macroides ST-30 along with 20 kg/ha P2O5 were found to be most suitable as phosphatic fertilizer. Conclusively, sustainable agriculture practices in the Tarai as well as the field region may be developed based on a strategy of exploring microbial inoculants from the pristine region of the Western Himalayas. The presence and abundance of bacterial inoculants were confirmed through qRT-PCT. We conclude that the effective plant growth-promoting bacterium Lysinibacillus macroides ST-30 broadens the spectrum of phosphate solubilizers available for field applications and might be used together with 20 Kg/ha P2O5. [ABSTRACT FROM AUTHOR]

Soil and water loss, as well as nutrient depletion in croplands and grazing areas, are major problems for smallholder farmers in the highlands of Ethiopia. This review aims to synthesize the main constraints, effectiveness, and potential scenarios of sustainable land management (SLM) initiatives. The findings of the review show that the main barriers to the adoption of the SLM initiatives have been the inability to monitor the conserved catchment through the establishment of an enabled institution at the local administration level (Kebele) and labor difficulties related to composting and terrace maintenance. The discontinuity of poorly constructed terracing, the undervaluing of local knowledge and skills, and the insufficient integration of various soil management techniques all impeded the implementation of the SLM initiatives. Terraces do not effectively control total soil loss, maintain soil moisture, stop nutrient depletion, or increase crop yield, despite their considerable contribution to minimizing soil loss caused by rill and sheet erosion. The most efficient way to keep soil, water, and nutrient losses at an acceptable level while simultaneously increasing production sustainably was to combine the use of terraces stabilized by multifunctional vegetation, drainage ditches, and agronomic methods between terraces. Thus, the planning and implementation of any sustainable land management initiative must be based on the idea that structural, vegetative, and agronomic land management practices at a given field and watershed level should be combined with an appreciation of indigenous skills and knowledge. The application of land management strategies to croplands and grazing areas should be complemented by controlled grazing and a cut-and-carry grazing system. [ABSTRACT FROM AUTHOR]

Understanding and estimating the economic value that society places on agricultural soil quality protection and improvement can guide the development of policies aimed at mitigating pollution, promoting conservation, or incentivizing sustainable land management practices. We estimate the general public's willingness to pay (WTP) for agricultural soil quality protection and improvement in Spain (n = 1000) and the UK (n = 984) using data from a cross-sectional survey via Qualtrics panels in March–April 2021. We use a double-bound dichotomous choice contingent valuation approach to elicit the individuals' WTP. We investigate the effect of uncertainty on the success of policies aiming at achieving soil protection. In addition, to understand the heterogeneity in individuals' WTP for agricultural soil quality protection and improvement, we model individuals' WTP through individuals' awareness and attitudes toward agricultural soil quality protection and the environment; trust in institutions; risk and time preferences; pro-social behavior; and socio-demographics in Spain and the UK. We found that there is significant public support for agricultural soil quality protection and improvement in Spain and the UK. We also found that the support does not vary significantly under uncertainty of success of policies aiming at achieving soil protection. However, the individual's reasons for supporting agricultural soil quality protection and improvement are found to depend on the level of uncertainty and country. Hence, promoting public support for soil protection needs to be tailored according to the level of the general public's perceived uncertainty and geographic location. [ABSTRACT FROM AUTHOR]

Bamboo-based agroforestry systems have emerged as a sustainable and promising approach for land management, offering enhanced productivity, sustainability, and resource preservation. Intercrops play a pivotal role in agroforestry systems, significantly contributing to their overall productivity and sustainability. This article explores the potential of bamboo agroforestry in diversifying agroecosystems, generating income streams, and contributing to sustainable rural development. The study evaluates the performance (yield and biomass) of two intercrops, okra and black gram, within Dendrocalamus brandisii-based agroforestry model and assesses their impact on soil nutrient status. Okra cultivation commenced once the bamboo plants had matured to 12 months, while black gram was introduced at the 18-month stage. Results indicate that wider spacing between bamboo plants significantly enhances intercrop yields, emphasizing the economic viability of bamboo agroforestry. The harvest index analysis reveals efficient resource utilization in intercropped systems, harvest indices for vegetables (okra) typically range between 30 and 40 percent, whereas pulses, such as black gram, often exhibit higher harvest indices, falling within the range of 70 to 90 percent. Importantly, the study finds that bamboo growth remains unaffected by intercrops, highlighting the compatibility of bamboo cultivation with diverse agricultural practices. Furthermore, the impact of intercrops on soil physico-chemical properties is examined, with okra cultivation negatively influencing soil moisture, bulk density, pH, and electrical conductivity, while black gram cultivation positively affects soil nitrogen, calcium, magnesium, and sulphur. These findings contribute valuable insights for optimizing bamboo agroforestry systems, promoting sustainable land use, and ensuring food security in diverse agroecological contexts. [ABSTRACT FROM AUTHOR]

Cultivated land resources are crucial for food security and economic and social development. However, with the acceleration of urbanization and shifts in land use, cultivated land fragmentation (CLF) has emerged as a significant factor constraining the sustainable development of agriculture in China. As the most urbanized region, optimizing cultivated land resources and coordinating urban and rural development has become an urgent issue for rural sustainable development in Guangdong Province. This study analyzes the spatiotemporal characteristics of CLF in Guangdong Province from 2000 to 2020 using landscape pattern indices, CRITIC empowerment, and a multiscale geographically weighted regression (MGWR) model. The cultivated land fragmentation index (CLFI) for Guangdong Province reveals a fluctuating trend from 2000 to 2012, increasing from 0.453 in 2012 to 0.641 in 2020. The CLFI is notably high in the Pearl River Delta region, as well as in Meizhou and Maoming. The results show the dynamic changes of the driving factors of CLF at the county scale in 2000, 2010, and 2020. Slope and grain output consistently emerge as key driving factors of CLF. Furthermore, agricultural benefits played a significant role in 2000 and 2020, whereas the coefficient for social economic development was more pronounced in 2010. By identifying the heterogeneity of the driving factors, this study suggests that strategies to address CLF should comprehensively consider aspects such as the optimization of cultivated land resources, farmers' interests, industrial restructuring, and the multifunctional development of farmland. The study findings can assist government policy-making for rural sustainable development, addressing CLF and food insecurity, and alleviating the regional development imbalance and urban–rural income gap, with the ultimate aim of achieving common prosperity. [ABSTRACT FROM AUTHOR]

Social-ecological systems (SESs) possess a great diversity of land use and land cover (LULC) types with unique assemblages of biodiversity and ecosystem services. However, LULC changes due to landscape fragmentation are emerging as major threats to the system productivity of SESs around the world. This study examined changes to LULC extent and landscape patterns in the Village Tank Cascade Systems (VTCSs) of Sri Lanka using satellite imagery and GIS techniques between 1994 and 2021. Multispectral Landsat images (5 TM and 8 OLI/TIRS) obtained from Google Earth Engine were classified using machine learning algorithms. Overall accuracies obtained were 85.9% (1994) and 88.6% (2021). The LULC change matrix and spatial pattern metrics were used to examine LULC and landscape pattern change dynamics over the VTCS landscapes. LULC change matrix results revealed that forest, which is the dominant LULC class covering 73.7% of the total land area was reduced by 206,725 ha due to transformation into agricultural (70.43%) and scrub (24.33%) lands between 1994 and 2021. Over this time landscape pattern of the VTCS has gradually changed from forest to agricultural land-dominated landscape, with forest and agricultural land types showing a significant negative correlation (p < 0.001; R2 > 0.868), particularly in the southeastern region. Landscape patterns were analysed based on eight spatial metrics calculated at both the landscape and class levels using FRAGSTATS spatial pattern analysis software. At the landscape level, the structure became more dispersed and complex in shape. Heterogeneity was noted to have gradually increased with weakening connectivity, whereas the fragmentation process had gradually accelerated. At the class level, the dominance of forest patches decreased, fragmentation and isolation increased, and connectivity and shape complexity reduced leading to the loss of fragmented forest habitats. The number of patches within the agricultural class increased and became more aggregated and complex in shape. Landscape performance indicators show that VTCSs have experienced a gradual loss of environmental sustainability. Assessment of LULC along with fragmentation can help to monitor the spatial pattern impacts that determine ecological integrity. Thus, the study provides scientific guidance for ecological restoration in degraded VTCSs to effectively improve ecological productivity. [ABSTRACT FROM AUTHOR]

A third of the world's ecosystems are considered degraded, and there is an urgent need for protection and restoration to make the planet healthier. The Sustainable Development Goals (SDGs) target 15.3 aims at protecting and restoring the terrestrial ecosystem to achieve a land degradation-neutral world by 2030. Land restoration through inclusive and productive growth is indispensable to promote sustainable development by fostering climate change-resistant, poverty-alleviating, and environmentally protective economic growth. The SDG Indicator 15.3.1 is used to measure progress towards a land degradation-neutral world. Earth observation datasets are the primary data sources for deriving the three sub-indicators of indicator 15.3.1. It requires selecting, querying, and processing a substantial historical archive of data. To reduce the complexities, make the calculation user-friendly, and adapt it to in-country applications, a module on the FAO's SEPAL platform has been developed in compliance with the UNCCD Good Practice Guidance (GPG v2) to derive the necessary statistics and maps for monitoring and reporting land degradation. The module uses satellite data from Landsat, Sentinel 2, and MODIS sensors for primary productivity assessment, along with other datasets enabling high-resolution to large-scale assessment of land degradation. The use of an in-country land cover transition matrix along with in-country land cover data enables a more accurate assessment of land cover changes over time. Four different case studies from Bangladesh, Nigeria, Uruguay, and Angola are presented to highlight the prospect and challenges of monitoring land degradation using various datasets, including LCML-based national land cover legend and land cover data. [ABSTRACT FROM AUTHOR]

This study presents an in-depth analysis of land use and land cover change on the Kerch Peninsula over a period spanning three decades. Convolutional neural networks were employed in conjunction with satellite imagery analysis to map and quantify the changes in land use and cover. This revealed significant trends and transformations within the peninsula's landscape. The analysis revealed a notable increase in urban expansion, particularly at the expense of natural ecosystems. Furthermore, there was a notable reversion of agricultural lands to grasslands, driven by economic downturns and reduced agricultural activity. These land cover changes underscore the urgency of implementing sustainable land management policies. The study recommends the establishment of conservation easements to protect remaining natural ecosystems, the initiation of reforestation programs to restore degraded lands, and the development of comprehensive water management strategies to address the peninsula's hydrological challenges. Furthermore, the study underscores the pivotal importance of integrating change analysis and predictive modeling to anticipate future land cover scenarios and inform effective land management strategies. The model developed through this research, which employs advanced remote sensing and GIS technologies, provides a robust framework for understanding and managing land use and land cover change. This model can serve as a reference for similar regions globally, offering insights that can inform sustainable land use practices and policy decisions. The findings of this study have implications that extend beyond the Kerch Peninsula. They provide insights that can inform the management of land use changes and the conservation of natural landscapes in regions facing comparable socio-economic and environmental challenges. [ABSTRACT FROM AUTHOR]

This study uses logistic and Poisson regression models to examine the factors influencing the adoption of sustainable land management (SLM) practices in Mali using two rounds of the nationally representative survey Enquête Agricole de Conjoncture Intégrée aux Conditions de Vie des Ménages. The SLMs considered include the application of organic fertilizers, the application of inorganic fertilizers, the use of improved seeds, and the practice of intercropping. On average the application of organic fertilizers (39.2%), and inorganic fertilizers (28.7%) are the most frequent SLM practices among Malian farmers, and between 2014 and 2017, we observe a decline in the practice of intercropping. The regression results show that farmers’ adoption of different SLMs is significantly associated with biophysical factors (average temperature, climate type, plot size, plot shape, and location), demographic factors (age, gender, education, household size), and socioeconomic factors (number of cultivated plots, livelihood diversification, type of crop grown, market access, credit access, economic shocks, and social capital). Our findings suggest that policymakers and agricultural development agencies in Mali need to adopt a multidimensional policy framework to unlock the untapped potential of SLM practices in promoting sustainable agriculture and food security.

Sub-Saharan Africa (SSA) faces severe land degradation, driven by a combination of human and natural factors. Deforestation, inadequate land management practices, and unsustainable farming methods are the primary causes. The historical trends reveal the impact of soil erosion and nutrient depletion on 70% of the soil and 65% of its total land area. Unchecked degradation poses a critical threat to economic growth and poverty reduction initiatives. The region's food security is intricately linked to the complex interplay between land degradation and a rapidly growing population. Escalating demand for agricultural resources raises concerns about the ability to meet the needs of SSA's population. The adoption of sustainable agricultural intensification practices (SIAP) emerges as a crucial strategy to address land degradation and enhance food security. SIAP involves innovative and ecologically sensitive techniques, such as agroforestry and organic farming, targeting to optimise resource use and minimise negative impacts on soil health. The interconnectedness between factors of land degradation, food security, and the contribution of SIAP underscores the urgency of adopting sustainable practices to ensure a balanced relationship between agricultural productivity and environmental conservation in SSA. While SIAP holds promise, challenges such as socio-economic barriers, low adoption rates, and contextual variations necessitate continuous support and well-designed policies for successful implementation.

Sustaining agricultural production in arid and semi‐arid regions is of paramount importance to food security, geo‐political independence, and social stability. In this context, it is vital to understand the effectiveness of policies. In this article, we aim to answer the question of what role the state and its policies play for soil protection in rainfed agriculture in Tunisia, and why. Beyond evaluating soil protection, this work contributes to explaining the role of the Tunisian state throughout the current phase of democratization for natural resource protection. That way it enhances our understanding of policy implementation in democratizing countries and contribute to theorizing of the policy process. We use qualitative methods and literature to understand the state infrastructural power of the Tunisian state in regard to soil protection. Land degradation in Tunisia remains a large problem. We explain the weak role of the state in effectively protecting soils as a result of subnational variation, and interrelated capabilities and weight of the state. Besides the overarching fiscal crisis that becomes worse over the years, neopatrimonial traits of the Tunisian state facilitate discrimination of rural areas, marginalization of parts of the farming population, and rainfed agriculture. Thereby, willingness and abilities of farmers and administrations to implement sustainable land management are undermined. Together with institutional uncertainty in administrations as a result of the current open‐ended democratization process, neopatrimonialist traits weaken administrative capacities. [ABSTRACT FROM AUTHOR]

Soil erosion poses a significant threat to sustainable land management and agricultural productivity. Addressing this issue requires advanced predictive models that can accurately identify areas at risk and inform soil conservation strategies. This study focuses on the development and interpretation of well-optimized deep learning (DL) models to predict soil erosion probability, aiming to enhance decision-making in land management. Utilizing the Revised Universal Soil Loss Equation (RUSLE) in conjunction with ground-truthing, we identified critical erosion-prone areas. To predict soil erosion probability, we employed Bayesian optimization to fine-tune Deep Neural Network (DNN), Convolutional Neural Network (CNN), Fully Connected Neural Network (FCNN), and DNN-CNN hybrid models. These DL models were verified using a set of metrics. SHAP value analysis as a means of explainable artificial intelligence (XAI) was used to interpret these DL models for better decision-making. RUSLE estimations and ground truthing highlight that Soil erosion rates in the northeastern and northwestern regions are nearing the highest observed at 25 tonnes per hectare annually, largely due to steep slopes and limited vegetation. In contrast, the southern and southeastern areas have lower erosion rates, due to denser vegetation and gentler slopes. Deep learning models, optimized using Bayesian methods, demonstrate high performance in spatially modeling soil erosion probability. The DNN model achieved an accuracy of 0.93, a precision of 0.92, and an F1-score of 0.94, identifying 222.73 sq. km as highly susceptible to erosion, which indicates its strong ability to detect true erosion events. The CNN model identified 49.68% of the study area (503.30 sq. km) as high-risk, with an accuracy of 0.90 and a precision of 0.91. The FCNN model showed a balanced risk distribution, indicating 37.04% of the land (375.25 sq. km) as very low risk and 36.43% (369.11 sq. km) as very high risk, with an accuracy of 0.91. The DNN-CNN hybrid model highlighted 41.58% of the area (421.20 sq. km) as high risk, demonstrating its effectiveness in capturing spatial patterns of erosion susceptibility. SHAP value analysis indicates that land use and soil type (LULC and K-factor) are crucial in erosion predictions, with LULC having a significant predictive influence in the DNN model. These insights facilitate the prioritization of soil conservation measures, enabling decision-makers to focus on the most impactful factors for mitigating soil erosion. [ABSTRACT FROM AUTHOR]

This is the first study on “presumed drylands”; lands with an aridity index higher than or equal to 0.65 and dryland features. It aims to describe the nature and extent of “presumed drylands” and their drivers and pressures of land degradation, current state, ongoing impacts, and land-management responses. We find that “presumed drylands” cover 10.75 million km2 (7% of the globe). Most “presumed drylands” are tropical and subtropical grassland biomes (58%), although the most frequent land use is forest (30%) and half of the area of “presumed drylands” (50%) contains trees. Land degradation in these areas is driven by regionally distinct biophysical and anthropogenic factors, compounded by climate change and extreme weather events. Responses implemented include agroforestry, sustainable land management, fire management, restoration, and protection. The scope and scale of ongoing degradation suggests that “presumed drylands” may become drylands. Hence, urgent investment in sustainable land management is needed. [ABSTRACT FROM AUTHOR]

Declining land productivity and increasing land and food scarcity, amidst high population growth have precipitated the need for intensification of crop production. Sustainable land management technologies (SLMTs) have been suggested as a way to support the intensification process. In Uganda, agricultural advisory services (AAS) geared towards improved adoption of the SLMTs are provided, and farmers can access AAS from diverse sources, with the possibility of accessing from single or multiple sources. This study attempts to identify and prioritize the drivers of farmers’ access to (single/multiple) sources of AAS and determine the impact of access to these sources of AAS on the adoption of SLMT, and crop productivity. The study uses cross-sectional data collected from 435 households in the southwestern highlands of Uganda, in Kisoro and Kabale districts. The multinomial endogenous switching regression model combined with an endogenous switching regression model was used to analyse the data. Results indicate that both single and multiple sources of AAS have a positive effect on adoption of SLMTs and crop productivity, with the latter having a positive effect on the adoption of more SLMTs, while it seems to reduce the adoption of some other SLMTs. Similarly, accessing AAS from multiple sources has a higher positive impact on crop productivity, when compared to no access, but a lower impact when compared to access to a single source of AAS. These results suggest that access to multiple sources of AAS has positive impacts, but there are possible inherent challenges in the way it is implemented; lack of synchronisation of the messages given to the farmers, and the top-down approaches used to disseminate knowledge on SLMTs by some of the AAS providers may confound the possibly higher benefits of access to multiple sources of AAS. This study points out the need for policy to consider the advantages of having a streamlined agricultural extension system, with coordinated efforts from all agricultural advisory service providers and stakeholders. [ABSTRACT FROM AUTHOR]

Land use planning (LUP) to achieve Land Degradation Neutrality (LDN) needs methods and tools that support the identification of best LUP solutions in terms of transitions from current degradative land use (LU) and land management (LM) practices to better LU and LM options. A crucial need is the identification of context specific sustainable land management (SLM) options. Addressing this need must aim at not only reversing/recovering past degradation (e.g., via restoration or rehabilitation in land degradation hotspots), but also avoiding "new" degradation possibly caused by unsuitable LU and LM. This requires SLM planning based on anticipated impact assessment of the LU‐LM transition scenarios set to achieve LDN, which can be achieved through a participatory planning process that integrates interests/needs and knowledge of stakeholders with science‐based supportive tools to identify rational, plausible, and socially relevant options. The geoinformatics Land Use Planning for LDN (LUP4LDN) conceptual procedure and tool have been designed for this purpose. Their aim is to support national and subnational planners by (i) mapping geographic patterns of past land degradation (LD) utilizing the LDN indicators adopted by the UNCCD (SDG 15.3.1 indicator) for user‐defined regions of interest (RoI); (ii) helping users anticipate future LD by identifying land that is unsustainably managed and that will likely become degraded during the planning period; (iii) partitioning the LD areas into spatial domains of socio‐ecological contextual similarity (i.e., contextual similarity units) to which the LU‐LM transitional options will be fitted; and (iv) providing an interactive procedure for participatory LU‐LM transitional scenario development over selected contextual similarity units and timeframes. LUP4LDN uses the Global Database of the World Overview of Conservation Approaches and Technologies (WOCAT), ICARDA's Geoinformatics Options by Context (GeOC) tool, and ELD (Economics of Land Degradation) indicators to identify context‐relevant SLM that are available in the RoI, suggests candidate SLM options, and visualizes related expected levels of impacts on ecosystem services via maps and graphs. The generated maps inform users about trade‐offs upon which users can discuss or negotiate transitional pathways. LUP4LDN has been codeveloped with national stakeholders in Tunisia and Burkina Faso. The piloting implementation in the two countries assessed how LUP4LDN fits with existing LUP processes and the benefits achieved by using the tool to support LUP for LDN. [ABSTRACT FROM AUTHOR]

Interactions among multiple stakeholders in coffee production have grown in importance in recent decades, as connections between individuals and groups have been established. The objective of the study is to examine the roles and connections of stakeholders in quality coffee production and the implications for sustainable land management in Yirgacheffe, Ethiopia. The stakeholders analysis—Process Net-Map and Participatory Analysis Matrix—was used to examine stakeholders' attributes, particularly their power and interest, as well as their interactions in quality coffee production. The data were gathered through key informant interviews and village focus group discussions. To investigate the perceived responsibilities of other stakeholders in sustainable land management, a household survey was undertaken with 352 randomly selected coffee farmers. The findings highlighted that stakeholders have varying degrees of power and interest in quality coffee production, and that the relationships and flows that exist among stakeholders for sustainable land management represent efforts from stakeholders along the coffee sector. The measures of the centrality and power-interest matrix of stakeholders demonstrated that government agencies have a greater outbound degree centrality and greater power than coffee producers do in coffee production. The study has revealed that there is asymmetrical power distribution among stakeholders for decisions and actions in quality coffee production and then sustainable land management. To make the coffee livelihood more sustainable, the study suggests policy intervention that strengthens strong partnerships among the stakeholders in quality coffee production in a way that sustainable land management would be enhanced. [ABSTRACT FROM AUTHOR]

The combination of extension approaches is encouraged, but information on their impact on farmers' innovativeness is still not fully documented. This study aimed to analyze the impact of combining extension approaches on smallholder farmers' innovativeness in Sustainable Land Management practices adoption in Benin. Thus, we collected data through two focus group discussions with 20 farmers, and semi-structured interviews with 10 extension agents and 111 farmers. A seven-point Likert scale with 18 items was used to measure farmers' innovativeness composed of three dimensions (propensity to innovate, capacity to innovate, and innovation practice) drawn from current literature. The results show that a combination of extension approaches based on technical capacity building, awareness raising, knowledge sharing, farmer-to-farmer, and the provision of inputs strengthen farmers' innovation propensity, capacity, and practice. When farmers' innovativeness increases, they adopt the least resource-demanding innovations and adapt the resource-demanding ones. Therefore, combining extension approaches that strengthen farmers' innovativeness is a better way to increase innovation adoption. It improves farmers' capacity to overcome farming difficulties on their own. A key implication of this finding is that interventions that aim to enhance the adoption and appropriation of agricultural innovations should integrate the three components of innovativeness into their framework. [ABSTRACT FROM AUTHOR]

This document is an editorial from the journal Frontiers in Environmental Science, discussing the importance of scaling up sustainable land management (SLM) in the drylands of Sub-Saharan Africa. It emphasizes the role of SLM in soil and water conservation, climate change mitigation and adaptation. The editorial calls for policy interventions and economic understanding of the impacts of land degradation and the benefits of SLM. It introduces five research articles that cover various aspects of SLM, including land degradation, soil fertility management, land access, reforestation, and agroecological practices. The goal is to provide evidence-based strategies and policy recommendations for scaling up SLM in Sub-Saharan Africa. The document also references additional sources that provide information on land degradation neutrality and sustainable land management. [Extracted from the article]

Studying land use and land cover (LULC) patterns, identifying driving forces, and simulating future scenarios are vital for grasping the complex connection between human actions and the environment. This helps in shaping sustainable land management strategies and preparing for the impacts of climate change. However, there is a necessity for a comprehensive system modeling framework that can accurately capture spatial and temporal changes in LULC, analyze driving mechanisms, and provide an integrated analysis of future simulations. In this paper, a comprehensive IM-RF-Markov-PLUS analysis framework is developed, focusing on the Fuxian Lake Basin (FLB) as a study area. The study aims to achieve accurate prediction of LULC by combining the microscopic LULC change trend and the contribution of macroscopic driving forces. The results show that: (1) The IM-RF-Markov-PLUS framework can explore the change patterns and driving mechanisms of LULC in the FLB, and accurately predict the LULC in the FLB. Compared with the PLUS model, its accuracy is improved by 2 %. (2) IM analysis reveals that LULC transformation in the FLB is both general and specific. Although the area of grassland, buildings, roads and structures converted to desert and bare land is minimal, it shows relatively tendentious and specific change characteristics. (3) Different land types are significantly affected by driving factors, with the expansion of LULCs is constrained by major factors. The distance to the lake has the most significant impact on the distribution of garden land, while the primary road has the greatest impact on the distribution of forestland. (4) Under different scenarios, the spatial heterogeneity of LULC patterns is obvious. In 2035, under baseline and economic development scenarios, cultivated land will decrease, while other LULC types will increase. Under the cultivated land protection scenario, cultivated land is protected, with an increase of 5.85 %. Under the ecological protection scenario, there is an increase in ecological land. The largest increase is in forestland, which increases by a total of 3.46 %. The ecological protection scenario presents a viable approach for ensuring the sustainable development of the FLB. The results of this paper may serve as a reliable foundation for implementing LULC strategies in the FLB and offer guidance for crafting sustainable development regulations at the regional level.

In an era of dynamic urbanization, especially in densely populated regions such as the Greater Istanbul Metropolitan Area, land degradation (LD) is a widespread and multifaceted phenomenon. Hence, there is a need for monitoring LD to track the direction of urban sprawl and respond rationally. In this context, the purpose of this study was to investigate the magnitude and directions of LD in Istanbul from 1984 to 2022. The originality of the study lies in the development of the CAI_A index, which is a quantitative measure of the degree of anthropogenic impact. This study utilized Landsat 5 and Landsat 8 satellite imagery from 1984, 2002, and 2022, employing a maximum likelihood classification method to determine land cover and land use changes. The results show that the area of LD by anthropogenic activity has increased by an average of nearly 40 percentage points in each district of Istanbul over the past four decades, significantly impacting both natural and semi‐natural areas. Furthermore, a noteworthy observation was made regarding forests in the northern part of the study area, which demonstrated stability and resilience to LD. The results of the study are important for the urban environment because they facilitate a better understanding of the impact of human activities on mitigating LD in the context of climate change, among other things. Moreover, the results identify specific areas in need of targeted monitoring and remedial actions regarding LD. Research Highlights: Istanbul's urbanization has been consistent since 1984.Urban expansion primarily contributes to agricultural land degradation.Land degradation clusters near settlements and on the southern coast.State forests are crucial for preserving natural areas and resisting degradation.Forest services are threatened by fragmented urban expansion. [ABSTRACT FROM AUTHOR]

The increasing incidence of droughts and heavy rainfall events is exacerbating conflicts between human and environmental demands for water. However, through providing multiple water-related ecosystem services and benefits simultaneously, Natural/Small Water Retention Measures (NSWRM) can mitigate such competing claims. Thus, they also contribute to the achievement of various Sustainable Development Goals and environmental targets set out in water- and agriculture-related policies of the European Union. In particular, NSWRM provide for the sound management of watersheds, which can significantly contribute to improved water quality and availability—as well as improving the resilience of agriculture and society. This paper demonstrates how NSWRM fit into the framework of ecosystem-based concepts, including Natural Water Retention Measures (NWRM), Green Infrastructure (GI), Sustainable Land Management (SLM), Ecosystem-based Adaptation (EbA), and Nature-based Solutions (NbS). NSWRM, as a distinct concept, bring added value to the other concepts by focussing on easy-to-implement, modestly sized, localised technical solutions to problems associated with water management, sediment, and nutrient loss. Through experience under the EU Horizon 2020 project OPTAIN ("OPtimal strategies to retAIN and re-use water and nutrients in small agricultural catchments across different soil-climatic regions in Europe"), we show what NSWRM are, how they are linked to each of the ecosystem-based concepts, and how they can help add value to these concepts. Fourteen case studies are drawn upon from diverse countries across Europe. As a result of this analysis, we present the potential for the application of NSWRM in the context of these concepts, while helping to identify planning tools, the expertise required, and potential funding mechanisms. [ABSTRACT FROM AUTHOR]

Landscapes are social-ecological systems (SESs) that produce ecosystem services, which change over time in response to environmental, biotic, and social drivers. Failure to consider this variability, and the feedbacks that can stabilize or destabilize systems, can have consequences for sustainable ecosystem services provision. This study applies a conceptual metaframework, past-present-future lens, to interpret changes in land cover and ecosystem services within the Cape Floristic Region (CFR) of South Africa. Paleoecology (fossil pollen, spores, and charcoal) and participatory system dynamics modeling were used to explore long-term variability in provisioning ecosystem services (plant biodiversity) and the drivers of this variability (fire and herbivory) at Elandsberg Private Nature Reserve (Elandsberg PNR). From ca. 1800s, the paleoecological record suggests that environmental changes, particularly a transition to unpalatable Elytropappus-dominated vegetation, were driven by grazing and that an ecological threshold was crossed in ca. 1950s due to agricultural intensification. Participatory system dynamics was used to identify feedbacks in the dynamic SES structure. The ecological model replicates the paleoecological results and, furthermore, suggests that in the future, returning the system to within historical ranges variability may require sustained reductions in both grazing and fire over decades. This innovative approach blends paleoecology and participatory system dynamics to provide an evidence-based understanding of temporal variability and feedbacks for policymakers and land-use managers to inform sustainable land management. [ABSTRACT FROM AUTHOR]

Sustainable land planning and successful land use change methods are essential as the world faces rising environmental challenges. This study examines the transformative potential of biomimicry and biophilia in addressing these challenges and the potential of bio-collaboration, bio-utilization, bio-inspiration, biophilic design, and biomimicry in creating a sustainable environment. The argument is that such integration can potentially create creative ways to lessen the effects of human activity on the environment by utilizing the knowledge of nature and combining biological system concepts. This study argues that by incorporating the above environmental factors into land planning practices, a holistic and sustainable approach can be achieved, fostering peaceful coexistence between human activities and the natural environment. This will also improve the resilience of urban and rural environments while offering practical solutions for a climate change-conscious world. As the main theoretical contribution, this study synthesizes a theoretical framework in the form of a conceptual structure for understanding, analyzing, and interpreting sustainability by adopting an ecosystem theoretical framework for achieving sustainable land management. [ABSTRACT FROM AUTHOR]

Social-ecological systems (SESs) possess a great diversity of land use and land cover (LULC) types with unique assemblages of biodiversity and ecosystem services. However, LULC changes due to landscape fragmentation are emerging as major threats to the system productivity of SESs around the world. This study examined changes to LULC extent and landscape patterns in the Village Tank Cascade Systems (VTCSs) of Sri Lanka using satellite imagery and GIS techniques between 1994 and 2021. Multispectral Landsat images (5 TM and 8 OLI/TIRS) obtained from Google Earth Engine were classified using machine learning algorithms. Overall accuracies obtained were 85.9% (1994) and 88.6% (2021). The LULC change matrix and spatial pattern metrics were used to examine LULC and landscape pattern change dynamics over the VTCS landscapes. LULC change matrix results revealed that forest, which is the dominant LULC class covering 73.7% of the total land area was reduced by 206,725 ha due to transformation into agricultural (70.43%) and scrub (24.33%) lands between 1994 and 2021. Over this time landscape pattern of the VTCS has gradually changed from forest to agricultural land-dominated landscape, with forest and agricultural land types showing a significant negative correlation (p < 0.001; R2 > 0.868), particularly in the southeastern region. Landscape patterns were analysed based on eight spatial metrics calculated at both the landscape and class levels using FRAGSTATS spatial pattern analysis software. At the landscape level, the structure became more dispersed and complex in shape. Heterogeneity was noted to have gradually increased with weakening connectivity, whereas the fragmentation process had gradually accelerated. At the class level, the dominance of forest patches decreased, fragmentation and isolation increased, and connectivity and shape complexity reduced leading to the loss of fragmented forest habitats. The number of patches within the agricultural class increased and became more aggregated and complex in shape. Landscape performance indicators show that VTCSs have experienced a gradual loss of environmental sustainability. Assessment of LULC along with fragmentation can help to monitor the spatial pattern impacts that determine ecological integrity. Thus, the study provides scientific guidance for ecological restoration in degraded VTCSs to effectively improve ecological productivity.

Agroforestry, as a sustainable land management practice, has garnered attention worldwide for its potential to mitigate climate change impacts and address water scarcity issues. In Tunisia, where climate change-induced stresses are increasingly affecting agriculture and water resources, agroforestry presents a promising solution. This review paper examines the importance of agroforestry in Tunisia within the context of climate change, water shortage, and treated wastewater utilization. By analyzing existing literature and case studies, the paper elucidates the ecological, economic, and social benefits of agroforestry practices in Tunisia. Additionally, it discusses the role of agroforestry in enhancing resilience to climate change, conserving water resources, and utilizing treated wastewater sustainably. Furthermore, the paper evaluates policy support and identifies challenges hindering the widespread adoption of agroforestry in Tunisia. Overall, this review underscores the significance of agroforestry as a multifaceted approach to sustainable land management in Tunisia, offering recommendations for policymakers, practitioners, and researchers to promote its implementation and integration into national strategies.

This research investigates the dynamic interplay between land use changes and landscape ecological risks in China’s Jiangsu Province, specifically focusing on the Huai River-Gaoyou Lake region. Leveraging multi-temporal remote sensing data from 2000 to 2020, we conducted a comprehensive analysis of shifting land cover patterns and their implications. Employing geostatistical techniques, we developed a landscape ecological risk assessment model to quantify ecological vulnerabilities. Additionally, we conducted a resident satisfaction survey aligned with the “Production–Living–Ecological” framework to gain insights into societal perceptions of land use dynamics. Our findings reveal significant land use shifts driven by urbanization, industrialization, and agricultural modernization. While farmland areas have decreased, water bodies and artificial surfaces have expanded, reflecting societal demands and economic growth. The landscape ecological risk assessment model highlights localized vulnerabilities, emphasizing the intricate relationship between land use changes and ecological risks. The resident satisfaction survey indicates overall contentment with various aspects of land use, especially in terms of residential comfort and transportation convenience. However, ecological concerns underscore the need for a balanced approach to land management that prioritizes ecological sustainability alongside economic development.

Understanding and estimating the economic value that society places on agricultural soil quality protection and improvement can guide the development of policies aimed at mitigating pollution, promoting conservation, or incentivizing sustainable land management practices. We estimate the general public’s willingness to pay (WTP) for agricultural soil quality protection and improvement in Spain (n = 1000) and the UK (n = 984) using data from a cross-sectional survey via Qualtrics panels in March–April 2021. We use a double-bound dichotomous choice contingent valuation approach to elicit the individuals’ WTP. We investigate the effect of uncertainty on the success of policies aiming at achieving soil protection. In addition, to understand the heterogeneity in individuals’ WTP for agricultural soil quality protection and improvement, we model individuals’ WTP through individuals’ awareness and attitudes toward agricultural soil quality protection and the environment; trust in institutions; risk and time preferences; pro-social behavior; and socio-demographics in Spain and the UK. We found that there is significant public support for agricultural soil quality protection and improvement in Spain and the UK. We also found that the support does not vary significantly under uncertainty of success of policies aiming at achieving soil protection. However, the individual’s reasons for supporting agricultural soil quality protection and improvement are found to depend on the level of uncertainty and country. Hence, promoting public support for soil protection needs to be tailored according to the level of the general public’s perceived uncertainty and geographic location.

Cultivated land resources are crucial for food security and economic and social development. However, with the acceleration of urbanization and shifts in land use, cultivated land fragmentation (CLF) has emerged as a significant factor constraining the sustainable development of agriculture in China. As the most urbanized region, optimizing cultivated land resources and coordinating urban and rural development has become an urgent issue for rural sustainable development in Guangdong Province. This study analyzes the spatiotemporal characteristics of CLF in Guangdong Province from 2000 to 2020 using landscape pattern indices, CRITIC empowerment, and a multiscale geographically weighted regression (MGWR) model. The cultivated land fragmentation index (CLFI) for Guangdong Province reveals a fluctuating trend from 2000 to 2012, increasing from 0.453 in 2012 to 0.641 in 2020. The CLFI is notably high in the Pearl River Delta region, as well as in Meizhou and Maoming. The results show the dynamic changes of the driving factors of CLF at the county scale in 2000, 2010, and 2020. Slope and grain output consistently emerge as key driving factors of CLF. Furthermore, agricultural benefits played a significant role in 2000 and 2020, whereas the coefficient for social economic development was more pronounced in 2010. By identifying the heterogeneity of the driving factors, this study suggests that strategies to address CLF should comprehensively consider aspects such as the optimization of cultivated land resources, farmers’ interests, industrial restructuring, and the multifunctional development of farmland. The study findings can assist government policy-making for rural sustainable development, addressing CLF and food insecurity, and alleviating the regional development imbalance and urban–rural income gap, with the ultimate aim of achieving common prosperity.

A third of the world’s ecosystems are considered degraded, and there is an urgent need for protection and restoration to make the planet healthier. The Sustainable Development Goals (SDGs) target 15.3 aims at protecting and restoring the terrestrial ecosystem to achieve a land degradation-neutral world by 2030. Land restoration through inclusive and productive growth is indispensable to promote sustainable development by fostering climate change-resistant, poverty-alleviating, and environmentally protective economic growth. The SDG Indicator 15.3.1 is used to measure progress towards a land degradation-neutral world. Earth observation datasets are the primary data sources for deriving the three sub-indicators of indicator 15.3.1. It requires selecting, querying, and processing a substantial historical archive of data. To reduce the complexities, make the calculation user-friendly, and adapt it to in-country applications, a module on the FAO’s SEPAL platform has been developed in compliance with the UNCCD Good Practice Guidance (GPG v2) to derive the necessary statistics and maps for monitoring and reporting land degradation. The module uses satellite data from Landsat, Sentinel 2, and MODIS sensors for primary productivity assessment, along with other datasets enabling high-resolution to large-scale assessment of land degradation. The use of an in-country land cover transition matrix along with in-country land cover data enables a more accurate assessment of land cover changes over time. Four different case studies from Bangladesh, Nigeria, Uruguay, and Angola are presented to highlight the prospect and challenges of monitoring land degradation using various datasets, including LCML-based national land cover legend and land cover data.

Repeated applications of straw and wood chips were recently proposed as a conservation strategy for preserving cultivated peatland carbon (C) stock. However, the variability in the amendment biostability and the possible divergent responses of contrasting peat soils need to be assessed. This study investigated the effect of amendment with different plant materials on carbon dioxide (CO2) emissions from two contrasting peat soils (sapric and hemic) in two laboratory experiments. The sapric soil received one application of plant materials and was incubated for 3190 degree-days (145 days at 22°C), while the hemic soil received three successive applications of plant materials and was incubated for three successive periods of 3150 degree-days (126 days at 25°C). CO2 emissions were measured at time intervals ranging from 2 to 14 days and the apparent proportion of the plant material's C remaining in the soil was modeled using an exponential decay function. CO2 emissions from the 0-25 cm horizon of the unamended peats represented 0.7 t C-CO2 ha-1 yr-1 in the sapric soil and 7.3, 1.1, and 0.5 t C-CO2 ha-1 yr-1 in the hemic soil for the first, second, and third amendment periods, respectively. The apparent remaining C of the plant material varied from 52% to 81% in the two experiments, resulting in biomass requirements ranging from 2 to 32 t ha-1. The apparent remaining C was from 26% to 36% higher in the sapric soil than in the hemic soil. The apparent remaining C was also 9% to 38% higher for the treated softwoods than the untreated materials (straws: miscanthus, switchgrass, sorghum; wood chips: willow, birch). The repeated application of straw and wood chips increased CO2 emissions in the first 35 days following each application, resulting in an increased decomposition rate for the tested model. However, no change was detected for the final apparent remaining C across the three applications. These findings highlight the importance of considering soil properties, material types, and the impact of repeated applications for designing effective amendment programs and accurate C projection models for cultivated peatlands. [ABSTRACT FROM AUTHOR]

Sustainable land management is considered a sustainable way to combat the threat of various forms of land destruction and erosion. However, there is little information on the factors affecting the household's decision to implement sustainable land management practices. In the present study, the factors affecting the implementation of sustainable land management practices by rural households applied in Sib and Souran county have been analyzed. The present study is applied in terms of purpose and in terms of descriptive-analytical method. The statistical population of the research is the Rural Households of the Sib and Soran area, which was selected by 230 sample formulas by random sampling method. Questionnaires and interviews were used to collect data and information. Descriptive statistics were used to identify sustainable management practices. Structural equation modeling (SEM) was used to identify the factors affecting the implementation of sustainable land management practices by rural households. The results of the methods used showed that in this area more basic and simple methods do not require much cost and capital. Using animal/animal fertilizer, use of organic and green fertilizers, plowing the land for the slope of the land, creating an empty and rocky dam at the top of the land, and creating earthy seals and the most important sustainable management methods in the Sib and Souran area. The results of the structural equation model factors affecting the implementation of sustainable land management methods by rural households also showed that the properties of agricultural farms with a coefficient of 0.79 had the most impact on the implementation of sustainable land management practices in the Sib and Soran area. The factor of Agricultural Ecology Properties with an Impact Coincision of 0.73, Organizational Support and Infrastructure Factor with an Impact Coincision of 0.69, Household Properties of 0.68, and Social and Economic Properties Factor with an Impact of 0.65, are subsequent. [ABSTRACT FROM AUTHOR]

Land is a natural resource, and settlement development is central for human activities. The growth of settlements comes at the expense of natural and agricultural land. Understanding urban growth dynamics, defined in this study as new urban development, can lead to an increased awareness of the stresses on land resources and the suitability of current land use policies. It can also reflect how changes in the economic cycles and planning policies can influence these dynamics. This is even more critical in small island states, where land is a scarce resource. This study uses data extracted from development-planning applications between 1993 and 2019 in order to understand urban growth in the island-state of Malta. A methodology was developed to (i) use web-scraping techniques to extract development-planning applications data from a public online database in order to define development descriptors, (ii) establish keywords that imply growth within the urban area, and (iii) analyse growth in view of local planning zones and regulations. The results show that over the years, there has been a decrease in the share of granted development-planning applications that lead to the growth of the urban area when compared to those granted applications permitting other forms of development, such as that linked to minor modifications to existing buildings and restoration works amongst others. Nonetheless, the absolute number of granted development-planning applications resulting in growth has increased, particularly in the last construction boom (post 2013). The share of applications denoting growth granted within the development zone has remained stable throughout the years. The years with the highest numbers of permits granted outside the development zone, where there was a disposition against development, were 2017 and 2018. In conclusion, the trends and patterns resulting from development cycles were analysed and discussed. The outcomes of this work will lead to better measurement of urban growth in Malta and assess the efficacy of current national development-planning policies. This is in line with the UN's Sustainable Development Goal 11, which aims at making "cities and human settlements inclusive, safe, resilient, and sustainable". The research specifically addresses Target 11a, which is focused on supporting "positive economic, social, and environmental links between urban, peri-urban, and rural areas by strengthening national and regional development planning". [ABSTRACT FROM AUTHOR]

Soil erosion poses a significant threat to sustainable land management and agricultural productivity. Addressing this issue requires advanced predictive models that can accurately identify areas at risk and inform soil conservation strategies. This study focuses on the development and interpretation of well-optimized deep learning (DL) models to predict soil erosion probability, aiming to enhance decision-making in land management. Utilizing the Revised Universal Soil Loss Equation (RUSLE) in conjunction with ground-truthing, we identified critical erosion-prone areas. To predict soil erosion probability, we employed Bayesian optimization to fine-tune Deep Neural Network (DNN), Convolutional Neural Network (CNN), Fully Connected Neural Network (FCNN), and DNN-CNN hybrid models. These DL models were verified using a set of metrics. SHAP value analysis as a means of explainable artificial intelligence (XAI) was used to interpret these DL models for better decision-making. RUSLE estimations and ground truthing highlight that Soil erosion rates in the northeastern and northwestern regions are nearing the highest observed at 25 tonnes per hectare annually, largely due to steep slopes and limited vegetation. In contrast, the southern and southeastern areas have lower erosion rates, due to denser vegetation and gentler slopes. Deep learning models, optimized using Bayesian methods, demonstrate high performance in spatially modeling soil erosion probability. The DNN model achieved an accuracy of 0.93, a precision of 0.92, and an F1-score of 0.94, identifying 222.73 sq. km as highly susceptible to erosion, which indicates its strong ability to detect true erosion events. The CNN model identified 49.68% of the study area (503.30 sq. km) as high-risk, with an accuracy of 0.90 and a precision of 0.91. The FCNN model showed a balanced risk distribution, indicating 37.04% of the land (375.25 sq. km) as very low risk and 36.43% (369.11 sq. km) as very high risk, with an accuracy of 0.91. The DNN-CNN hybrid model highlighted 41.58% of the area (421.20 sq. km) as high risk, demonstrating its effectiveness in capturing spatial patterns of erosion susceptibility. SHAP value analysis indicates that land use and soil type (LULC and K-factor) are crucial in erosion predictions, with LULC having a significant predictive influence in the DNN model. These insights facilitate the prioritization of soil conservation measures, enabling decision-makers to focus on the most impactful factors for mitigating soil erosion.

Landscapes are social–ecological systems (SESs) that produce ecosystem services, which change over time in response to environmental, biotic, and social drivers. Failure to consider this variability, and the feedbacks that can stabilize or destabilize systems, can have consequences for sustainable ecosystem services provision. This study applies a conceptual meta-framework, past–present–future lens, to interpret changes in land cover and ecosystem services within the Cape Floristic Region (CFR) of South Africa. Paleoecology (fossil pollen, spores, and charcoal) and participatory system dynamics modeling were used to explore long-term variability in provisioning ecosystem services (plant biodiversity) and the drivers of this variability (fire and herbivory) at Elandsberg Private Nature Reserve (Elandsberg PNR). From ca. 1800s, the paleoecological record suggests that environmental changes, particularly a transition to unpalatable Elytropappus-dominated vegetation, were driven by grazing and that an ecological threshold was crossed in ca. 1950s due to agricultural intensification. Participatory system dynamics was used to identify feedbacks in the dynamic SES structure. The ecological model replicates the paleoecological results and, furthermore, suggests that in the future, returning the system to within historical ranges variability may require sustained reductions in both grazing and fire over decades. This innovative approach blends paleoecology and participatory system dynamics to provide an evidence-based understanding of temporal variability and feedbacks for policymakers and land-use managers to inform sustainable land management.