Sustainable Land Research Articles

Understanding Japan's Land-use Dynamics between 1987 and 2050 using Land Accounting and Scenario Analysis

Amidst global concerns about land use change and its far-reaching impact on biodiversity and human well-being, there is a growing need to understand how land use stock and flow changes over time through land use accounting. While existing studies on land accounting have focused on historical land changes, little attention has been paid to future transitions. This study assessed historical patterns and projected future shifts in land use dynamics from 1987 to 2050 across Japan by combining high-resolution land use and land cover datasets, land change simulations, and land accounting. In the analyses, particular attention was paid to the historical and future trends of farmland abandonment by leveraging data at 100-m resolution built on national vegetation surveys. High-resolution analysis of farmland abandonment issue with national scale in Japan is a novelty. From 1987 to 1998, the land stock analysis results showed a pronounced marked increase in residential land (10.4%) and grassland (16.9%); the flow analysis results showed that urban residential sprawl expansion was mainly formed by secondary (32.6%) and plantation (21.1%) forest areas, coinciding with increasing population and economic growth. Projections from 2010 to 2050 indicate a marked increase in abandoned farmland (67.2% per decade), a trend influenced by rapid population decline and presumably agricultural policies, especially significant in regions such as Hokkaido and Kyushu. The findings of this study are crucial for shaping policy and decision-making, underlining the need for sustainable land management strategies that effectively balance urban growth, agricultural productivity, and environmental preservation in Japan.

Quantifying and spatializing the island landsenses ecological condition using a two-dimensional model

Achieving the harmonious development of the “social-ecological” system is a crucial aspect of the global sustainable development goals. Landsenses ecology is an emerging concept that emphasizes sustainable land use planning and comprehensive management. Islands serve as ideal study areas setting for studying the landsenses ecology due to their vulnerability as ecosystems exposed to significant human activities. To assess the condition and spatial distribution of landsenses ecology, we established a quantitative evaluation framework that encompassed eight factors across two perceptions - physical and psychological. Our study focused on two islands situated in southeast China, which, despite their proximity, demonstrate remarkable differences in terms of natural and economic characteristics. The results revealed a significant spatial heterogeneity in the landsenses ecological condition on both islands. Nan'ao island (NAI) exhibited higher values for physical (0.5) and psychological (0.243) perceptions compared to Dongshan island (DSI), which was primarily attributed to varying natural environments and topographic factors. Notably, elevation and slope demonstrated strong correlations with landsenses ecological condition, acting as critical determinants of island development. Finally, using beaches as an example, we examined the impact of landsenses ecological conditions about the tourist resources of the islands. This study contributes to the development of scientifically informed urban and tourism planning processes by providing decision-makers with valuable insights.

The use of living labs to advance agro-ecological theory in the transition towards sustainable land use: A tale of two polders

Agricultural ecosystems worldwide are on life support. A key challenge is the translation of global sustainability goals to local contexts, particularly those related to sustainable land use, climate and biodiversity at the landscape scale. Living labs, place-based, focal areas as pilots of change, have the potential to be instrumental in driving the development of local solutions. When used to their full potential, they can both enable the advancement of agro-ecological theory and aid the transition to sustainable agricultural land use. In this viewpoint paper we present two conceptual advancements culminating in their high potential: (1) a methodological approach with replicated modes of transition and reference sites, while proposed agricultural modes are co-created through stakeholder encounters, (2) a framework that enables long-term monitoring of the relation between ecosystem functioning (expressed as leakiness) and biodiversity (expressed as ecological interaction networks), taking into account the full scale of ecological interactions within the agro-ecosystem. We illustrate how these conceptual advances can be implemented in a living lab in the Netherlands. Here, we discuss how these advances can generate impact and accelerate the transition to planetary-scale sustainability in agricultural ecosystems.

Impacts of Integrated Watershed Management Interventions on Land Use/Land Cover of Yesir Watershed in Northwestern Ethiopia

Since 2002, numerous sustainable land management (SLM) interventions have been implemented in Ethiopia, such as agroforestry, area closure, forage development, gully rehabilitation, and conservation agriculture. In addition, watershed-based developments contributed comprehensively to a better use of existing natural resources. This study determined the impact of Integrated Watershed Management (IWM) on land use/land cover for the Yesir watershed in Northern Ethiopia. Supervised image classification algorithms were applied to a time series of Landsat 5 (2002) and Landsat 8 (2013 and 2022) images to produce land use/land cover maps. A Geographic Information System was applied to analyze and map changes in land use/land cover for settlements, agricultural land, grazing land, and land covered with other vegetation. In focus group discussions, the time series maps were analyzed and compared with the integrated watershed management practices to analyze their impacts. The results document that integrated watershed management practices have contributed to a significant change in land use/land cover in the study area over the past 20 years. The quantitative analysis of land use/land cover between the years 2002 and 2022 only revealed a downward trend in agricultural land. Considering the value of the Normalized Difference Vegetation Index (NDVI) as a biophysical feature for the increase of green mass, this indicator also documents an improvement in land use/land cover with regard to sustainable land management and consequently poverty alleviation.

Preparation of technosol based on coal gangue and its impact on plant growth in coal mining area

Coal gangue, a byproduct of coal mining, is traditionally considered a nuisance. Recent research has begun to explore its potential for soil improvement and land reclamation through controlled pot experiments. However, its usage in soil matrices remains below 50% in most studies. To address these issues, this study investigates the preparation and utilization of coal gangue in technosols, with a focus on its impact on plant growth under natural conditions. The study was conducted at the Suntuan coal mine, located in the Huaibei mining area of eastern China. Results showed that technosols prepared with a high coal gangue dosage ranging from 60% to 100% could support optimal growth of maize (Zea mays L.) with low pollution risk. The impacts of the amount of coal gangue and organic fertilizer on the improvement of technosol quality and the promotion of vegetation growth were significant. The preferred preparation method involved a combination of coal gangue, soil, biochar, microbial agent, water-retaining agent, and organic fertilizer at 60:40:1:0.0025:0.01:5. Overall, our study emphasizes the potential of coal gangue for sustainable land reclamation and environmental benefit. Through optimized technosol preparation and effective utilization of functional materials, our research contributes to eco-friendly practices in coal mining areas.

Assessing the Impact of Climate Change on Global Crop Yields and Farming Practices

Climate change is recognized as one of the most pressing challenges of our time, with profound implications for global food security. This review article delves into the multifaceted impacts of climate change on crop yields and farming practices on a global scale. By synthesizing recent research findings, identifying key challenges and opportunities, and exploring adaptation strategies, this review provides a comprehensive analysis of the complex interplay between climate change and agriculture. The effects of climate change on agriculture are diverse and far reaching. Alterations in weather patterns, including shifts in temperature, precipitation, and frequency of extreme events, pose significant challenges to agricultural productivity and food security. These changes disrupt traditional farming practices, exacerbate water stress, soil erosion, and crop loss, and threaten the livelihoods of millions of farmers worldwide. Additionally, changes in pest and disease dynamics have further compounded the challenges faced by agricultural systems under pressure from climate variability. These challenges, there are opportunities for innovation and adaptation in the agricultural systems. This review highlights the potential of climate-smart agricultural practices such as crop diversification, conservation agriculture, and precision farming to enhance resilience and mitigate the impacts of climate change on crop yields. investments in climate-resilient crop varieties, improved water management techniques, and sustainable land management practices offer pathways for building adaptive capacities and ensuring food security in a changing climate. addressing the complex challenges of climate change adaptation in agriculture requires concerted action at multiple levels. This review emphasizes the importance of coordinated efforts among policymakers, researchers, farmers, and other stakeholders in developing and implementing effective adaptation strategies. Such strategies should be context-specific, socially equitable, and environmentally sustainable, considering the diverse needs and priorities of different regions and communities. This review underscores the urgent need for coordinated action to build resilient and sustainable food systems in the face of a changing climate. By synthesizing the latest research findings, identifying key challenges and opportunities, and exploring adaptation strategies, this review aims to inform policymakers, researchers, and practitioners about the imperative of addressing climate change’s impacts on agriculture. Only through collaborative and transformative action can we ensure food security for the present and future generations in a rapidly changing world.

Past and future land use change dynamics: assessing the impact of urban development on agricultural land in the Pantura Jabar region, Indonesia.

The conversion of large-scale agricultural land into urban areas poses a significant challenge to achieving national and global food security targets, as outlined in Sustainable Development Goal number 2, which aims to eradicate hunger. Indonesia has experienced a significant decline in rice field areas, with a reduction of approximately 650 thousand hectares within a year (2017-2018), the largest being in Java. Hence, this study aims to examine the impact of urban expansion on agricultural land in the north coast region of West Java Province from 2013 to 2020 and develop a predictive model for 2030 to support sustainable land use planning. The primary methods employed were random forest (RF) analysis using Google Earth Engine, intensity analysis, multilayer perceptron-neural network (MLP-NN), Markov chains-cellular automata (Markov-CA), and stakeholder interviews. The model also evaluated the influence of "distance to tollgates" as a previously unexplored driving factor in existing land use modeling studies. Landsat image classification results using the RF algorithm showed 87-88% accuracy. Cropland has historically been and is projected to remain the primary target for the expansion of built-up areas. Spatial planning irregularities were found in the growth of these areas that adversely affected farmers' socioeconomic and environmental conditions. Evaluation of land use models using MLP-NN and Markov-CA demonstrated an accuracy rate of 86.29-86.23%. The distance to tollgates factor significantly impacts the models, albeit less than population density. The 2030 intervention scenario, which implements a firm policy for sustainable agricultural land use, offers the potential to maintain the predicted cropland loss compared to business as usual.

Linkages between gully erosion susceptibility and hydrological connectivity in Tropical sub-humid river basin: Application of Machine learning algorithms and Connectivity Index

Hydrological connectivity from upslope to downslope of valley floor and main channel, triggered the gully initiation and associated land degradation continue occurring off-site erosion as considered most effective drivers on potential sediment detachment. Present study attempted to identify the linkage between gullies erosion susceptibility (GES) and hydrological connectivity pathway in sub-tropical humid river basin Kangsabati (KRB) using four machine-learning algorithms (MLALs) such as Random Forest (RF), Support Vector Machine (SVM), Extreme Gradient Boosting (XGB), Artificial Neural Network (ANN) for GES mapping, and connectivity index (IC) for hydrological connectivity mapping. Thirty-five controlling factors were selected using Boruta’s approach to produce GES mapping, while frequency ratio (FR) was applied to determine the significant role in each individual class of controlling factors on degree of gully susceptibility. To achieve the efficiency of using MLALs, AUC of ROC including sensitivity, specificity, accuracy, F, and Kappa index were employed to compare in each model. In testing datasets, AUC values reveals that RF (0.99) and XGB (0.99) were well performed and predicted to GES followed by ANN (0.97) and SVM (0.87). FR depicts the most contributing factors of barren land and laterite followed by rainfall erosivity, degraded forest, single crop, and elevation to GES. IC result showed that values range (−11.52 to 0.49) address the three connectivity categories i.e. not connected (NC), gully connected but not reach (CNR), and gully well connected (WC). Correlation analysis clarified that double crop (R = 0.82), topographical wetted index (R = 0.77) and slope (R = 0.0.44) are prolonged WC for large downslope in north-western sub-basins of upper catchment and western, eastern sub-basins of lower catchment, while dense forest (R = -0.71) and vegetation cover (R = -0.82) forms NC gullies and CNR to channel due to interrupted upslope in central sub-basins of upper and lower catchment. Finally, research findings could provide to take strategy for sustainable land uses policy.

Research on Sustainable Land Use in Alpine Meadow Region Based on Coupled Coordination Degree Model—From Production–Living–Ecology Perspective

Changes in land use types in alpine meadow areas have significant impacts on the ecological environment in alpine areas. Exploring land use change is crucial for land use management and optimization in alpine regions. Thus, it is necessary to analyze land use evolution and its drivers in alpine meadow regions from a production–living–ecology space (PLES) perspective by using remote sensing data. We first constructed the PLES evaluation system for Gannan. Then, we analyzed the spatial and temporal evolution characteristics and coupling degree of PLES in the study area. Finally, the driving factors affecting PLES were explored with geodetector. The conclusions of the study reveal that the distribution of productive and ecological spaces is large and concentrated, while the distribution of living spaces is more decentralized. The PLES was mainly concentrated in the area above 2500 m but below 4000 m and with a slope of 40° or less. During the study period, the area of production space showed a decreasing trend, while the areas of living and ecological space both showed increasing trends, primarily occurring at the expense of production space. DEM and GDP were the main factors affecting the distribution of PLES. The coupling level and the degree of coupling coordination were relatively stable in general, showing a pattern of “high in the east and low in the west”. The study provides technical support and a theoretical basis for the future planning of land space and ecological environment optimization in the alpine meadow regions.

An optimization-simulation modeling framework for exploring the dynamic correlation between the coordinated development of the human-nature nexus and land use under uncertainty

Sustainable land use optimization (LUO) requires simultaneously reconciling human development and nature conservation, and effectively adapting to changes in socioeconomic development. We proposed a modeling framework that includes stochastic simulation of population and GDP uncertainty, multidimensional LUO, and spatial land use simulation combining random forests and cellular automata. The framework can (1) balance the multidimensional contradictory conflicts between human-nature nexus (HNN); (2) obtain the dynamic correlation and probability distribution of land use with the dimensional objectives and the HNN; and (3) obtain the dynamic response of land use to changes in socioeconomic development and the elasticity space of land use. The framework was applied to Hubei Province in the middle reaches of the Yangtze River. The results indicated that by 2030, the land use intervals that can cope with uncertainty and achieve high levels of HNN coordination of 0.66–0.69 at 51,500–55,500 (km2) for cultivated land, 47,750–49,750 (km2) for forestland, 1,950–2,350 (km2) for grassland, 9,300–10,100 (km2) for construction land, 11,249–11,418 (km2) for water area, and 285–307 (km2) for unused land. This study elucidates the complex dynamic correlation between HNN and land use, and provides regions with LUO decisions that can respond to changing conditions and promote a harmonious HNN development.

Applying conditioners to address the issues of carbon loss and cadmium pollution in the karst paddy-oil crop system

The fragile ecosystem and unique parent material in the karst region lead to severe carbon loss and cadmium pollution. Additionally, the rice-oilseed rotation system exacerbates the accumulation of cadmium in crops. Therefore, it is necessary to find a sustainable land use approach that ensures crop quality while promoting soil carbon sequestration. This article provides an overview of cutting-edge technologies to enhance soil carbon sequestration capacity, and it discovers that the application of amendments has a significant effect on reducing cadmium content in crops and improving soil organic carbon levels. Through experimental analysis, The results indicate that the conditioner in group T4 (Humic acids) can effectively passivate cadmium elements in the soil, reducing the cadmium content in rice and rapeseed tissues. Overall, our research indicates that humic acid amendments not only enhance soil carbon sequestration capacity but also significantly reduce cadmium content in crops and increase crop yields. These findings highlight the significant value of humic acid amendments in the rice-oilseed rotation system in the karst region, providing scientific evidence and theoretical support for promoting sustainable development in the area.

Editorial: Scaling-up sustainable land management in the drylands of Sub-Saharan Africa

Editorial: Scaling-up sustainable land management in the drylands of Sub-Saharan Africa

Exploring land use dynamics in rural areas. An analysis of eight cases in the Global North

Rural areas are pivotal in the global economy, hence rural development planners and decision makers face significant technical and information management challenges, hindering their ability to assess sustainable development and formulate strategies. These challenges, coupled with shifts in traditional rural activities, aging populations, and climate change impacts, create inequalities and threaten rural communities. Therefore, developing approaches for the assessment of changes in rural areas are required. In recent years, remote sensing has emerged as a useful tool for monitoring the complex dynamics of rural regions, with a notable increase in the accessibility and use of freely available satellite data and platforms for tracking changes in land use and land cover (LULC). In light of this trend, this article analyzes the spatio-temporal trends in eight different development regions in Japan, Germany, Poland and Spain and integrates them with population data. This research relied on the utilization of openly available datasets - satellite imagery from Landsat and WorldPop population data, processed in Google Earth Engine (GEE). The time series of Landsat imagery were employed to analyze changes in LULC over a 20-year period from 2000 to 2020 in each test site. Unique combinations (i.e. each pixel history) were systematically examined and categorized based on established rules, with improbable scenarios marked as "uncertain." The comparison demonstrates that all eight regions have unique spatial, temporal and thematic characteristics. The most significant changes observed include the transformation of tree-covered areas into built-up areas in the case of Tsukuba and into agricultural lands in Shibushi. In the Bodzentyn and Połaniec communes in Poland, agricultural lands have transitioned into forested areas. In Spain, there is an increase in built-up areas, particularly at the outskirts of established towns. In Germany, the results indicate an expansion of built-up and agricultural areas in the Fürth region, while the Regen region experienced an increase in agricultural land. Incorporating population data reveals relationships between different types of LULC conversions and population trends, showing clear positive trends in areas transformed from agricultural and tree-covered land to built-up areas, with the most profound changes observed in Spanish cases and Tsukuba. The findings from automatic LULC classification highlight the usefulness of this tool in identifying socio-economic changes, especially when it is integrated with and compared to statistical data. Policy makers and planners at local levels should consider these specific values as a foundational reference point for shaping their plans related to sustainable development, land use, environmental preservation, and resource management.

Biodiversity Conservation Strategies and their Impact on Ecosystem Health in Mozambique

Purpose: The aim of the study was to analyze the biodiversity conservation strategies and their impact on ecosystem health in Mozambique. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: Biodiversity conservation strategies in Mozambique have enhanced ecosystem health, promoting species richness and habitat preservation. Through protected area management and community-based initiatives, threatened species and ecosystems have shown signs of recovery. Sustainable land management and habitat restoration projects have bolstered ecosystem resilience. However, challenges like habitat fragmentation and illegal wildlife trade persist, demanding ongoing research and integrated conservation approaches for sustained biodiversity and ecosystem health. Unique Contribution to Theory, Practice and Policy: Resilience theory, community-based natural resource management (CBNRM) & political ecology may be used to anchor future studies on biodiversity conservation strategies and their impact on ecosystem health in Mozambique. Implement community-based conservation initiatives that empower local communities to actively participate in biodiversity conservation efforts. Ensure that biodiversity conservation is mainstreamed into national development policies and strategies in Mozambique

Impact of Deforestation on Water Quality in Cameroon

Purpose: The aim of the study was to analyze the impact of deforestation on water quality in Cameroon. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: Deforestation in Cameroon significantly impacts water quality, as evidenced by increased sedimentation, higher pollutant levels, and elevated risks of waterborne diseases. Loss of forest cover reduces natural filtration capacities, leading to higher concentrations of contaminants in water sources. Alterations in hydrological patterns and changes in land use further exacerbate these issues, affecting water availability and aquatic habitats. Unique Contribution to Theory, Practice and Policy: Hydrological cycle theory, land use/land cover change (LU/LC) theory & ecosystem services theory may be used to anchor future studies on impact of deforestation on water quality in Cameroon. Implement land-use planning measures that prioritize the conservation and sustainable management of forest ecosystems, including protected area designation, forest restoration initiatives, and sustainable forest management practices. Develop and enforce policies that incentivize forest conservation and sustainable land management practices, such as payment for ecosystem services schemes, land-use zoning regulations, and carbon offset programs.

Impacts of Cropland Utilization Patterns on the Sustainable Use Efficiency of Cropland Based on the Human–Land Perspective

Confronted with China’s burgeoning population and finite arable land resources, the enhancement of sustainable arable land efficiency is of paramount importance. This study, grounded in the United Nations Sustainable Development Goals (SDGs), introduces a robust framework for assessing sustainable arable land use. Utilizing the Sustainable Utilization of Arable Land (SUA) indicator system, the DGA–Super-SBM model, the Malmquist–Luenberger production index, and the TO–Fisher–OSM algorithm, we evaluated the efficiency of sustainable utilization of arable land (ESUA) in 52 prefecture-level cities within China’s major grain-producing regions of the Yellow and Huaihai Seas. We analyzed the cropland utilization patterns from 2010 to 2020, examining the influence of these patterns on sustainable utilization efficiency. Our findings indicate that between 2010 and 2020, the arable land usage in these regions exhibited minimal transformation, primarily shifting towards construction land and conversely from grassland and water systems. Notably, the ESUA of arable land demonstrated an upward trend, characterized by pronounced spatial clustering, enduring high efficiency in the northern regions, and a significant surge in the southern sectors. The declining ESUA (D-ESUA) trend was general but increased in half of the cities. The change in the center of gravity of ESUA correlated with the north–south movement of the proportion of cultivated land area, the turn-in rate, and the turn-out rate, yet moved in the opposite direction to that of cultivated land density and yield per unit area. Variables such as the replanting index, cropland density, yield per unit area, and cropland turn-in rate significantly affected ESUA. These findings offer a scientific basis and decision-making support for optimizing the utilization pattern of arable land and achieving a rational allocation of arable land resources.

Exploring dietary patterns and their association with environmental sustainability and body mass index in children and adolescents: Insights from the National Food, Nutrition and Physical Activity Survey 2015–2016

ObjectiveTo adapt four dietary patterns for children and adolescents, and study their associations with sustainability (greenhouse-gas emissions-GHGE and land use-LU), and health (body mass index-BMI) indicators. Research methods & proceduresDietary intake of children (3-9y) and adolescents (10-17y) from the National Food, Nutrition and Physical Activity Survey 2015–2016, Portugal (n = 1153) was assessed through two non-consecutive interviews: one-day food diaries (children), and 24-h recalls (adolescents), using an automated multiple-pass method, including a picture book for portion sizes estimation. Adherence to the Eat-Lancet and World Health Organization (WHO) recommendations, Mediterranean and Atlantic diets were evaluated using adapted versions for pediatrics of the World Index for Sustainability and Health (WISH), Diet Quality Index (DQI), Mediterranean Diet Score (MDS) and Southern-European Atlantic Diet (SEAD), respectively. Diet-related GHGE and LU were estimated using the SHARP-Indicators database. BMI (measured) z-scores were classified according to WHO criteria. A standardized weighted health-sustainability composite index was created (BMI + 0.5*GHGE+0.5*LU). Adjusted linear regression models were computed. ResultsWISH, DQI, MDS, and SEAD had weighted mean scores (range) of 50 (0−130), 24 (9–36), 20 (8–32), and 17 (8–32), respectively. All dietary patterns were associated with lower environmental impact, particularly in children, but not with BMI. Only MDS explained both health and sustainability indicators in childhood (composite index: sd.β = −0·223,95%CI:-0·347,-0·072,R2 = 25.1 %), and adolescence (composite index: sd.β = −0·159,95%CI:-0·315,-0·003,R2 = 31.3 %). ConclusionThe Mediterranean diet was the most related to (higher) environmental sustainability and (lower) BMI. However, in children (not adolescents), the WISH, DQI, and SEAD showed then same associations.

Association Analysis of the Spatial and Temporal Changes in Vegetation Photosynthesis Levels with Land Cover Changes in China Based on Solar-Induced Fluorescence

Understanding the relationship between vegetation photosynthesis levels and land use changes is crucial for assessing ecosystem health and plant growth status. Existing studies have not fully considered temporal and spatial dimensions, resulting in an incomplete understanding of the relationship between vegetation photosynthesis levels and land use. Based on solar-induced fluorescence (SIF) data from 2001 to 2022, this study used the Mann-Kendall (MK) test and spatial association analysis to explore the associations between temporal and spatial changes in vegetation photosynthesis levels and land cover change (LCC) in China. The contributions and findings are as follows: (1) A computational framework was utilized to comprehensively measure the spatial correlation between LCCs and chlorophyll levels based on their spatial co-occurrence. (2) The MK test results of the annual and monthly average vegetation photosynthesis levels revealed that most regions in China exhibited increasing trends, accounting for 90.01% and 91.78%, respectively. Moreover, the vegetation photosynthesis levels in western China had a downward trend, indicating that the vegetation ecosystem in this region may be under a certain degree of pressure or may face the risk of degradation. (3) Some economically developed provinces are facing ecological pressures caused by urbanization and industrialization, which have led to the degradation of vegetation ecosystems and a decrease in vegetation photosynthesis levels. (4) Highly supportive areas of the land use–vegetation photosynthesis level association analysis were mainly distributed in grassland and forest areas, indicating the effectiveness of forest protection and grassland management policies. Moreover, the decrease in vegetation photosynthesis mainly occurred in barren areas, illustrating that the management and protection of this type of land still need to be strengthened. These findings underscore the complex interplay between land use and vegetation health, providing insights for sustainable land management policies.

State infrastructural power in a neopatrimonialist democratization context: Why Tunisian sustainable land management fails

State infrastructural power in a neopatrimonialist democratization context: Why Tunisian sustainable land management fails

Diversity and composition of agroforestry species in two agro-ecological zones of Rwanda

This study delves into the diversity and composition of agroforestry species in Rwanda's Eastern Plateau and Eastern Savannah agro-ecological zones. Examining these systems across diverse landscapes is crucial for selecting species adapted to local conditions. We surveyed four landscapes with varying tree cover levels, using stratified random sampling to allocate 240 plots for detailed field inventory. We analyzed dendrometric characteristics of woody vegetation, focusing on plants with ≥ 4 cm diameter at breast height (DBH). Exotic tree species comprised over 75% of trees across all landscapes. Diversity indices indicated significant differences in plant communities between the Eastern Savannah and Eastern Plateau, with higher diversity in the former. Sørensen's similarity coefficient for woody species between the two regions showed a moderate level of similarity (approximately 53%). However, there was a significant difference in the equitability of on-farm tree species between the zones, suggesting non-identical distribution patterns. The most common and dominant tree species were Grevillea robusta, Mangifera indica, and Persea americana, primarily used for timber and fruit production. Most encountered trees were small and scattered, with nearly 80% having a DBH below 20 cm, highlighting the prevalence of young trees. The dominance of exotic species emphasizes the need for further research on their impact on agricultural biodiversity, informing sustainable land management practices in Rwanda and similar contexts.