Sustainable Land Use Practices Research Articles

32 years of changes in river paths and coastal landscape in Bangladesh, Bengal Basin

AbstractThis study examines the geomorphological changes and environmental impacts on the coastline and the evolution of major river systems in Bangladesh over the past 32 years using remote sensing and GIS analyses. The central coastal area, characterized by fine sediments, has experienced significant land erosion due to the dynamics of the Meghna Estuary and its depositional patterns. In contrast, the southwestern Sundarbans Forest coast has remained relatively stable, aided by mangrove root stabilization despite anthropogenic threats. Channel migration analysis revealed the Brahmaputra River’s persistent braided configuration, while its tributaries, Teesta and Dharla, increased meandering nature due to reduced water availability and human interventions. The Ganges-Padma system displayed a shift towards a more sinuous channel pattern driven by reduced water discharge due to the Farakka Barrage construction in the upstream and a minor decrease in precipitation. The Upper Meghna River maintained moderate sinuosity with stable anastomosed patterns, whereas the lower Meghna River’s convergence with the Jamuna and Padma Rivers increased its susceptibility to erosion. These findings highlight the interplay of natural processes and human activities in shaping the coastal and fluvial landscapes of Bangladesh and the Bengal Basin, emphasizing the need for sustainable land-use practices and adaptive management strategies to mitigate future risks associated with sea-level rise and river course changes.

Assessment of coastal flood risk scenarios on infrastructure in the Keta municipality in Ghana using a GIS approach

Coastal flooding and erosion, caused by climate change-induced sea level rise, pose significant threats to low-lying coastal areas worldwide. The African continent, including Ghana, has experienced severe impacts from these hazards, affecting the socio-economic development of coastal communities. This research focuses on the Keta municipality in Ghana. The Keta municipality is highly vulnerable to coastal flooding and erosion due to its low elevation and the construction of the Akosombo hydroelectric dam. This research aims to predict the impact of coastal flooding on infrastructure in the Keta municipality using different flood scenarios. It also fills the existing knowledge gap in understanding how future flood risk can impact on critical infrastructure and consequently on other vital socio-economic sectors in the coastal community of Keta. The study utilizes a Geographic Information System (GIS)-based approach, combining various datasets, including topographic data, administrative shapefiles, field survey points, and infrastructure data. Two flood scenarios were considered to assess areas at risk: a 2.5-m sea level flood scenario representing potential climate change events and a worst-case 5-m sea level flood scenario. The findings reveal that 3.3 km2 (9 %) of coastal land area, 3.9 km of roads, and 69 structures are at risk under a 2.5m sea level rise scenario, increasing to 7.1 km2 (19.4 %), 13.6 km of roads, and 667 structures under a 5m scenario. The study highlights the urgency of addressing these risks to protect coastal communities' socio-economic development and livelihoods. Recommendations include implementing appropriate coastal management strategies, improving infrastructure resilience, and promoting sustainable land-use practices. By understanding and addressing the future impact of coastal flooding, decision-makers can mitigate climate change's adverse effects on coastal areas and ensure the region's long-term sustainability.

Farmers’ Willingness to Accept Afforestation in Farming Land and Its Influencing Factors in Fragile Landscapes Based on the Contingent Valuation Method

Afforestation (AF) in farmland has been widely used as an alternative and sustainable land-use practice to address socioeconomic and environmental challenges. The aim of this study is to estimate farmers’ willingness to accept (WTA) compensation and land, both of which are equally significant for policymakers to ensure the effective implementation of AF and achieve desired outcomes. This topic has not been sufficiently explored in previous research. This study focused on areas characterized by insecure farming conditions, backward economies, and fragile landscapes, where farmers are generally unfamiliar with AF or compensation for ecosystem services under payment for ecosystem services programs. It assessed their attitudes towards the WTA AF, compensation, and land as an alternative practice, which remains under-researched. This is crucial for designing effective AF programs in the future to improve livelihood and enhance the quantity and quality of the environment. This study used the contingent valuation method to estimate the minimum WTA compensation and maximum land for the forgone loss and alternative land-use practices. A questionnaire survey was conducted in Hupsekot municipality, Nepal, with 232 farmer households. The ordinal logistic regression model was used to analyze influencing factors of WTA compensation and land. The result showed that farmers’ average WTA compensation was NPR 1268.67 (USD 9.76)/Kattha/year, with 2.64 Kattha land available for AF. The factors, including socioeconomic characters and attitudes toward the environmental situation and forests, significantly influenced WTA values and provided potential target factors to achieve maximum AF land within a lower budget.

Trend of soil salinization in Africa and implications for agro-chemical use in semi-arid croplands

Soil salinization is a gradual degradation process that begins as a minor problem and grows to become a significant economic loss if no control action is taken. It progressively alters the soil environment which eventually negatively affects plants and organism that were not originally adapted for saline conditions. Soil salinization arises from diverse sources such as side-effects of long-term use of agro-chemicals, saline parent rocks, periodic inundation of soil with saline water, etc. In Africa, soil salinization has not been adequately documented particularly in the croplands. The objective of this study was to identify trends of cropland salinization in Africa and how its relationship with long-term land use practices affected the soil environment. The study analysed soil salinization between 1965 and 2020 using measured electrical conductivity (EC), spatial modelling with environmental covariates, and national statistics on cropland expansion and application of mineral fertilizers, herbicides, and pesticides. The results showed increasing trends of EC in Africa due to climatic and land use drivers. Increasing trends of EC, which evidenced salinization, was found in 31 million hectares of topsoils and 18 million hectares of subsoils. About 2 million hectares of croplands were depicted with salinization and >25 million hectares at the risk of salinization in the arid and semi-arid areas. The study also found statistical relationships between semi-arid cropland salinization and trends of agro-chemical use and cropland sizes. There were significant (p < 0.001) positive correlations between semi-arid cropland salinization and trends of cropland expansion and applied nitrogenous fertilizers. It found that increasing trend of applied mineral nitrogenous fertilizers could double the odds of salinization in semi-arid croplands while cropland expansion could increase the odds of semi-arid cropland salinization by >10 %. These findings present ground-breaking baseline information for future works on sustainable land-use practices that can control cropland soil salinization in Africa.

Post-fire Effects on Soil Properties in High altitude Mixed-conifer Forest of Nepal

Studies on the effects of wildfires on soil are common in mixed-conifer forests worldwide; however, such studies are less frequent in the context of high-altitude mixed-conifer forests. In this research, we analyzed the soil physicochemical properties 14 years after a high-intensity wildfire. Soil samples were collected from a depth of 0–10 cm across 100 composite samples, representing both control and burnt areas. Our findings revealed significant changes in soil characteristics in the burnt area compared to the control area. Specifically, the average soil pH, electrical conductivity, and available potassium increased by 3 %, 81 %, and 53 %, respectively, in the burnt area, while available phosphorus decreased by 6 %. Conversely, the average total nitrogen and organic matter showed non-significant decreases of 20 % and 12 % in the burnt area compared to the control area. No significant differences were found in slope aspects. Electrical conductivity and available potassium varied significantly among upper (3300–3500 m), middle (3100–3300 m), and lower (2900–3100 m) altitude ranges. Principal component analysis explained a total of 50.1 % of the variance, with approximately 27.4 % explained by the first axis and 22.7 % by the second axis. The control and burnt areas were closely clustered, indicating similar soil properties. Electrical conductivity, available potassium, and pH were more linked to the burnt forests, while nitrogen and organic matter were more associated with the control forests. Consequently, post-fire restoration efforts should consider potential changes in soil nutrient availability to facilitate successful vegetation recovery. This study enhances the formulation of more precise post-fire land management strategies, improves forest restoration initiatives, and promotes sustainable land-use practices by comparing unburnt natural forests.

Water quality management in a tropical karstic system influenced by land use in Chiapas, Mexico

Urbanization and agricultural activities are increasingly threatening karstic systems and the water resources they provide, which are crucial for the livelihood of rural communities. Over the past decade, the Río Grande de Comitán-Lagos de Montebello (RGC-LM) watershed in Chiapas, Mexico, has experienced significant deterioration in water quality. The objective of this study was to analyze the water quality dynamics within the RGC-LM watershed and their potential interaction with land use change. We conducted assessments of the physicochemical and microbiological parameters across the lotic and lentic systems within the watershed over eight monitoring campaigns (from 2013 to 2020). Cluster Analysis (CA) and Principal Component Analysis (PCA) statistical approaches were performed to identify the main drivers of surface water quality variability. This approach aims to enhance water quality assessments within environmental management strategies, with the goal of promoting sustainable land-use practices aimed at protecting and improving water resources within the watershed. Our findings indicate that there is a substantial difference between the upper and lower watershed water quality. The good water quality conditions observed in the higher altitude lakes (mountain lakes) can be attributed to favorable topographical features, specific land use patterns, and effective conservation measures. In contrast, the lotic system in the middle watershed and the lentic water bodies located at lower altitudes (plain lakes) exhibit signs of water quality degradation due to inefficient wastewater treatment and agricultural runoff. This study highlights the importance of implementing adequate environmental management strategies to address these water quality challenges effectively. Given the pressing issue of water quality degradation in karstic environments, we emphasize on the need for increased monitoring frequency of both physicochemical and microbiological parameters to capture seasonal variations and to further understand the vulnerability of water resources in karstic environments. Future assessment of nutrient concentrations, pesticide levels, and blue-green algae populations will also be crucial for evaluating the trophic state at a watershed scale.

Assessing the environmental factors affecting the sustainability of Aini Falaj system.

This study investigates the spatial distribution patterns and environmental factors influencing the Aini Falaj system in a specific study area. The research findings are presented through the lens of the following four categories: collinearity diagnostics, spatial autocorrelation analysis, kernel density (KD) findings, and multivariate geographically weighted regression (MGWR) analysis. The collinearity diagnostics were applied to examine the interrelationships among 18 independent environmental variables. The results indicate the absence of significant multicollinearity concerns, with most variables showing values below the critical threshold of five for variance inflation factors (VIFs). The selected variables indicate minimal intercorrelation, suggesting that researchers should be confident utilizing them in subsequent modelling or regression analyses. A spatial autocorrelation analysis using Moran's Index revealed positive spatial autocorrelation and significant clustering patterns in the distribution of live and non-functional Aini Falajs. High concentrations of live or dead Falajs tended to be surrounded by neighbouring areas with similar characteristics. These findings provide insights into the ecological preferences and habitat associations of Aini Falajs, thereby aiding conservation strategies and targeted studies. The kernel density (KD) analysis depicted distribution patterns of live and dry Aini Falajs through hotspots and cold spots. Specific regions exhibited high-density areas of live Falajs, indicating favourable environmental conditions or historical factors contributing to their concentrated distribution. Identifying these high-density zones can enhance our understanding of the spatial patterns and potential factors influencing the prevalence and sustainability of Aini Falajs. The multivariate geographically weighted regression (MGWR) models revealed strong associations between the live or dead status of Aini Falajs and environmental factors. The precipitation, topographic wetness index (TWI), aspect and slope exerted positive impacts on the live status, while evaporation, solar radiation, distance to drains and drain density exerted negative influences. Similar associations were observed for the dead status, emphasising the importance of controlling evaporation, shading mechanisms, proper drainage planning and sustainable land-use practices. This study provides valuable insights into the spatial distributions and factors influencing the live and dead status of Aini Falajs, thereby contributing to our understanding of their ecological dynamics and guiding conservation efforts and management strategies.

Lowland Tropical Peatlands – A Brief Review of Their Important Role in the Global Carbon Cycle and Biodiversity Support

Tropical peatlands are crucial ecosystems, storing vast carbon reserves and supporting rich biodiversity. Despite covering a small land area, they play significant roles in global carbon cycling and climate regulation. However, these ecosystems face escalating threats from human activities, including agricultural expansion and peatland drainage. This paper provides a concise overview of tropical peatlands, focusing on their distribution, characteristics, and ecological importance in Southeast Asia, Africa, and South America. It highlights the diverse vegetation communities and notable animal species found in peat swamp forests, underscoring their conservation value. Peatland degradation leads to increased greenhouse gas emissions, land subsidence, and loss of traditional livelihoods for local communities. Addressing these challenges requires integrated approaches, including conservation efforts to protect and restore intact peat swamp forests, sustainable land-use practices, and policy interventions to regulate land management. Research collaboration between scientists, policymakers, and local communities is essential for developing evidence-based conservation strategies. By prioritizing the preservation of tropical peatlands, we can mitigate climate change impacts, conserve biodiversity, and safeguard the well-being of local communities.

Spatio-temporal classification of land use and land cover and its changes in Kerala using remote sensing and machine learning approach.

Land use and land cover (LULC) analysis gives important information on how the region has evolved over time. Kerala, a land with an extensive and dynamic history of land-use changes, has, until now, lacked comprehensive investigations into this history. So the current study focuses on Kerala, one of the ecologically diverse states in India with complex topography, through Landsat images taken from 1990 to 2020 using two different machine learning classifications, random forest (RF) and classification and regression trees (CART) on Google Earth Engine (GEE) platform. RF and CART are versatile machine learning algorithms frequently employed for classification and regression, offering effective tools for predictive modelling across diverse domains due to their flexibility and data-handling capabilities. Normalised Difference Vegetation Index (NDVI), Normalised Differences Built-up Index (NDBI), Modified Normalised Difference Water Index (MNDWI), and Bare soil index (BSI) are integral indices utilised to enhance the precision of land use and land cover classification in satellite imagery, playing a crucial role by providing valuable insights into specific landscape attributes that may be challenging to identify using individual spectral bands alone. The results showed that the performance of RF is better than that of CART in all the years. Thus, RF algorithm outputs are used to infer the change in the LULC for three decades. The changes in the NDVI values point out the loss of vegetation for the urban area expansion during the study period. The increasing value of NDBI and BSI in the state indicates growth in high-density built-up areas and barren land. The slight reduction in the value of MNDWI indicates the shrinking water bodies in the state. The results of LULC showed the urban expansion (158.2%) and loss of agricultural area (15.52%) in the region during the study period. It was noted the area of the barren class, as well as the water class, decreased steadily from 1990 to 2020. The results of the current study will provide insight into the land-use planners, government, and non-governmental organizations (NGOs) for the necessary sustainable land-use practices.

Smallholder farmers' vulnerability to climate change and variability: Evidence from three agroecologies in the Upper Blue Nile, Ethiopia

This study delves into the profound impact of climate change on agriculture in Ethiopia, particularly the vulnerabilities faced by smallholder farmers and the resulting implications for poverty. Focusing on three distinct agroecologies, namely: highland, midland, and lowland zones. The study employed a robust methodology, combining a cross-sectional survey, spatial-temporal trend analysis using GIS, and the development of an overall vulnerability index through the balanced weighted average method. The study, encompassing 646 households, combines data from a variety of sources and analytical tools like the vulnerability index, ArcGIS 10.8, and ERDA's IMAGINE 2015. Utilizing the LVI-IPCC scale, the study shows that climate change is an immediate vulnerability in all agroecological zones. It identifies highland areas as the most sensitive and exposed regions, while lowland households are found to be the most vulnerable in terms of overall vulnerabilities. The research reveals specific challenges faced by communities, such as inadequate health facilities and insufficient food and water supplies in both highland and lowland agroecosystems. Additionally, our investigation has observed a significant alteration in land use practices, specifically the shift from communal grazing land to private cultivation and plantations, emphasizing eucalyptus. This alteration enhances the ecosystem's vulnerability to climate disturbances. The study suggests targeted interventions, such as advocating for sustainable land-use practices, afforestation, and adopting climate-smart agriculture practices. It is important to implement policy measures that prioritize conserving and restoring shrubland, grazing land, and natural forests to ensure both long-term socio-economic and ecosystem resilience. The study's nuanced insights are instrumental in understanding the diverse challenges posed by climate change in Ethiopian agriculture, supporting informed policymaking and sustainable interventions.

Assessing the performance of wind erosion prediction models of RWEQ and SWEEP by direct measurements in an arid region

Wind erosion field studies allow researchers to conduct simulations under natural conditions, thus play a significant role in investigating wind erosion processes. Direct measurements are also used to validate and improve existing erosion models. There is a need to develop sustainable land-use practices and management strategies and to assess potential current and future trends of wind erosion risk in arid and semi-arid regions. This study assessed wind erosion-induced soil losses in 11 different wind cases encountered within the wheat-fallow production system in a semi-arid region of Türkiye between 2017 and 2020 to eliminate the wind erosion threats on soil resources. Direct measurements and two estimation models (RWEQ and SWEEP) were employed to assess soil loss. Grid sampling method and BEST® sediment traps were utilized to measure wind-blown soil in the field directly. Present findings revealed that wind erosion threatened both plots in different seasons. The wheat-cultivated plot was highly susceptible to wind erosion in autumn when winter cereals are sown, while the fallow plot showed susceptibility in spring. Throughout the entire measurement period (3-years), wind erosion-induced soil transportation was measured as 1383 kg ha−1 for fallow plots and 2548 kg ha−1 for wheat-cultivated plots. Model performance was assessed through correlations (r), root mean square error (RMSE) and d-test results. The results demonstrated that the calibrated RWEQ (RWEQcal) model provided reasonably accurate estimates of wind erosion for both fallow and wheat-cultivated lands, with relatively low RMSE values of 0.34 and 0.46, d-test values of 0.26 and 0.27, and correlation coefficients of 0.69 and 0.85, respectively. Model results highlighted the importance of model calibration for local conditions; otherwise, they may produce underestimated and overestimated results.

The potency of coffee plants in agroforestry system in Baringin Village, Agam Regency, West Sumatra to support social forestry program and its contribution to mitigate climate change

This study investigates the viability of coffee agroforestry systems in supporting Indonesia’s Social Forestry Program and contributing to climate change mitigation efforts. Conducted in the KUPS Kopi Data Baringin management area of West Sumatra, this research assesses the potential of coffee cultivation within an agroforestry system in Baringin Village, Agam District. Data collection encompassed a comprehensive census for social and economic aspects and purposive sampling for vegetation analysis. Findings revealed a diverse range of 29 tree species from 16 families, alongside eight types of agricultural crops from five families. Tree species exhibited lower diversity and abundance indices, while herbaceous and shrub categories demonstrated moderate diversity. Notably, Coffea canephora, the coffee species, exhibited a carbon content of 3.49 tons per hectare, contributing to climate change mitigation efforts and functioning as a valuable CO2 equivalent sink estimated at approximately 13 tons per hectare. Furthermore, the adoption of coffee agroforestry systems resulted in a notable increase in monthly income for KUPS members. These findings underscore the potential of coffee agroforestry systems as a sustainable land-use practice, supporting the Social Forestry Program objectives and making substantial contributions to climate change mitigation in Indonesia’s forest and land management strategies.

GIS and remote sensing-based site suitability analysis for a new abattoir: a case study in Adola Woyu town, Ethiopia

ABSTRACT This study aimed to determine the ideal location for an abattoir in Adola Woyu town, taking into account environmental considerations by utilizing remote sensing and GIS, and collaborated with Ethiopia’s national urban planning agency for guidance on urban land use planning. The study analyzed various factors such as land use, cover, elevation, slope, streams, distance from roads, high-tension lines, social services, and boreholes. Researchers found acceptable areas with a highly attractive location of 1.27%, 28.42% being suitable, 21.54% being somewhat suitable, and 48.75% being unsuitable by hierarchical weighting utilizing the MCE approach. The highly desirable areas are in the north-west, north-east, and south-east, classified as bare land. The suitable areas are near the edges of built-up zones, while the unsuitable sites are in developed areas. The study’s main objective is to have the abattoir situated in an ideal location to minimize environmental impact from liquid and solid waste, airborne waste, and noise pollution while promoting sustainable land-use practices. The results are readily applicable for land-use planners and managers to make informed decisions on the strategic placement of the abattoir. By implementing the study’s recommendations, we can effectively minimize negative impacts on adjacent ecosystems while promoting responsible and sustainable development practices.

An Analysis of land-use Carbon Emissions in Dongguan City Under the Background of Carbon Neutrality and Peak-Carbon

The “Peak-Carbon and Carbon Neutrality” targets proposed by China are formulated with a strategic consideration of coordinating both international and domestic contexts. Aligned with these goals, our study delves into Dongguan, a pivotal city in southern China, focusing on its challenges and opportunities in mitigating climate change and achieving carbon neutrality. Utilizing three periods of remote sensing image data (2002, 2012, and 2022) and applying the carbon emission coefficient method, the research specifically investigates the role of land-use types and transitions in influencing carbon emissions and emission intensity in Dongguan. Notably, the study identifies construction land-use as a significant contributor to carbon emissions, hindering the attainment of carbon neutrality and peak-carbon objectives. The findings prompt the proposal of targeted policies to address this issue and promote sustainable land-use practices, providing a more precise lens on the interplay between land use and carbon emissions in Dongguan.

Using participatory mapping for a shared understanding of deforestation dynamics in Murehwa district, Zimbabwe

This paper presents the results of a study using participatory mapping to collectively understand deforestation dynamics in Murehwa, a communal area approximately 90 km northeast of Harare, Zimbabwe’s capital city. The study engaged smallholder farmers in a deliberative process through participatory mapping exercises in 15 villages. For each exercise, participants collaboratively drew two maps of their village, one for 1990 and another for 2021. They depict village boundaries, land uses and the magnitude of change between the two dates. Participatory mapping served as a platform for collective thinking, with the resulting maps used to facilitate discussions. They involved comparing land use between the two maps and identifying the drivers of the observed changes. Thematic approach was used to analyse the discussions in order to come up with collectively identified drivers of land use changes. The findings show that deforestation and resulting land use changes are primarily rooted in economic depression, selling of wood, tobacco farming, veld fires, unauthorised wood exploitation, illegal selling of land, increase in gardening, agricultural expansion and population growth. These results lay a foundational step towards the co-construction of a governance framework for practising agriculture in forest-adjacent areas. Moreover, the paper shares methodological reflections and experiences intended to promote initiatives where the construction of a shared understanding facilitates sustainable land-use practices that foster natural resource conservation.

Assessment of environmental degradation of lakes of Nainital district: an ecohydrological perspective

Human activities have degraded lakes in Uttarakhand, endangering their vital role in urban sustainability, which includes providing essential services like water supply, flood mitigation, agriculture support, and biodiversity conservation in the Himalayan region. This study focused on Nainital district lakes, utilizing remote sensing and GIS techniques to assess their condition. Time series Landsat 8 satellite imageries acquire by USGS earth explorer from 2017 and 2022 were captured, pre-processed, and subjected to spectral-based classification algorithms in ArcGIS software to calculate Normalised Difference Vegetation Index (NDVI), Normalised Difference Water Index (NDWI), and Normalised Difference Built-up Index (NDBI) indices to assess changes in vegetation, water bodies, and build-up area in and around the lakes respectively. The results indicate a decrease in built-up areas for Nainital district lakes from 2017 to 2022: Naini Lake (1.42%), Bhimtal Lake (1.83%), Naukuchiatal Lake (1.45%), Sattal Lake (2.18%), Khurpatal Lake (2.25%), and Sariyatal Lake (1.3%). Additionally, Bhimtal, Naukuchiatal, and Khurpatal lakes exhibited reductions in shrub and grass vegetation by approximately 12%, 16%, and 0% over the five-year period. Notably, Sattal and Khurapatal lakes demonstrated significant decreases in built-up areas, likely attributed to restoration efforts or landslides. Findings emphasize the need for conservation, sustainable land-use practices, and effective management to protect lake ecosystems.

Landslide susceptibility mapping and management in Western Serbia: an analysis of ANFIS- and SVM-based hybrid models

Landslide susceptibility mapping (LSM) is essential for land-use planning, as it helps to identify areas at risk of landslides and enables effective prevention measures to be taken. Various statistical and machine learning (ML) models are used in LSM, including SVM and ANFIS, which have shown promising results. However, determining which model performs better remains a key challenge. To address this issue, this paper aims to compare six hybrid models constructed with two well-known and powerful ML models, namely SVM and ANFIS, and three meta-heuristic algorithms, namely Genetic Algorithm (GA), Differential Evolution (DE), and Cultural Algorithm (CA), for LSM in a case study in western Serbia. In the process of building the models, 359 landslide sites and 14 determinants were used. The accuracy of the models was evaluated using several indexes, including Root Mean-Squared Error (RMSE), coefficient of determination (R2), and Area under the Receiver Operating Characteristic Curve (AUROC). The modeling results showed that the SVM-GA model has the highest accuracy (AUROC = 0.78) in predicting landslide incidence, followed by the ANFIS-GA (AUROC = 0.775), SVM-CA (AUROC = 0.773), ANFIS-DE (AUROC = 0.771), SVM-DE (AUROC = 0.76), and ANFIS-CA (AUROC = 0.65) models in validation phase. Therefore, the study suggested that SVM-based hybrid models are more accurate than ANFIS-based models for LSM, and thus, modelers may use SVM-based hybrid models for such applications. This study provides valuable insights into identifying the most appropriate and effective models for LSM, which can help to mitigate the risks associated with landslides and ensure sustainable land-use practices.

“Whose carbon is it?” Understanding municipalities role in blue carbon ecosystems management in Canada

Blue carbon ecosystems are marine vegetated ecosystems, such as mangroves, salt marshes, kelp forests and seagrass meadows, that naturally sequester and store atmospheric carbon in their deep sediments and biomass. Their ecosystem services extend from carbon capture and storage to coastline protection and flood mitigation, making their management and protection a form of nature-based solution (NbS) for climate change adaptation. However, these ecosystems are subject to degradation and destruction from coastal development and land use change, releasing sequestered carbon into the atmosphere. In Canada, although home to the largest coastline of any country in the world, neither federal nor provincial policy explicitly address the management or protection of blue carbon ecosystems, leaving them susceptible to these threats. Coastal municipalities, however, may play an important role in the current management and protection of blue carbon. Land-use planning decisions on the local level offer an opportunity to protect and conserve coastal ecosystems and the co-benefits these ecosystems provide offer a NbS to address many climate threats faced by coastal communities. This study examines the current and potential role of municipalities in the management, protection and/or restoration of blue carbon ecosystems for sustainable land-use planning practices and carbon pollution mitigation by interviewing municipal staff from coastal municipalities across Canada. Study results demonstrated municipal interest in blue carbon ecosystems for their tangible co-benefits, not carbon sequestration and storage capacity, and that restoring blue carbon ecosystems for living shoreline projects was the most common active management strategy at the local level. However, institutional capacity, a lack of jurisdictional clarity and uncertainty surrounding blue carbon were identified as barriers that hindered municipal engagement in active management strategies, largely restricting them to play a supportive role to blue carbon projects led by local environmental non-governmental organizations.

The complex interplay between plant-microbe and virus interactions in sustainable agriculture: Harnessing phytomicrobiomes for enhanced soil health, designer plants, resource use efficiency, and food security

The present-day climate change scenario represents a substantial peril to the global population concerning food security, given the potential impacts on agricultural productivity, food availability, and accessibility. The excessive use of agrochemicals, as fertilizers and pesticides, leads to the deterioration of soil health as well. Sustainable land-use practices without perturbing the soil ecosystem are achievable only with a comprehensive mechanism. The current need for sustainable agriculture is fulfilled by harnessing the noble services of plant-microbial association. Microhabitats around plant roots represent the region of maximum microbial activity. Microbiomes play a functional role in affecting plant growth, soil fertility and biogeochemical cycles. Plant-microbe interactions are highly specific to the host controlled by root exudates, metabolites, environmental factors and symbiotic associations e.g. legume-rhizobia and plant-fungi association. Proper strategies for the use of microbial inoculants will certainly facilitate the various crop improvement programs. The present review, therefore, exemplifies the various studies on the potential of plant microbiomes for sustainable agricultural ecosystems coupled with assuring food security. The review also summarizes recent trends in plant microbiome diversity, the relationship between host plant and microbe, transgenic plants, designer plants and their role in mitigating soil stress. Nevertheless, the future of the global population and food production rely on the prospects of plant microbiome ingenuity.

Effects of Land-Use Dynamics on Soil Organic Carbon and Total Nitrogen Stock, Western Ethiopia

Soil organic carbon (SOC) and total nitrogen (TN) stock are key indicators of soil quality in tropical regions; however, their status is often degraded, especially due to massive deforestation in natural forest areas associated with extensive agricultural land use. The aim of this study was to investigate the dynamics of SOC and TN stock in different land-use systems in the Abobo woreda, Western Ethiopia. To analyze their status, 80 disturbed (composite) and 45 undisturbed soil samples were collected from the top 20 cm of soil in five major land-use types: natural forestlands, grasslands, recently developed commercial farmlands, old commercial farmlands, and small-scale cultivated lands. The results showed that SOC stock varied significantly across the different land-use types, with mean stock ranging from 32.23 Mg·ha−1 in recently developed commercial farmlands to 54.54 Mg·ha−1 in natural forestlands. The mean TN stock ranged from 2.54 Mg·ha−1 in recently developed commercial farmlands to 4.63 Mg·ha−1 in natural forestlands. With natural forestlands as a baseline and the duration ranging in age from 15 to 45 years since land-use conversion, the mean annual absolute rates of change in SOC and TN stock loss were 0.49, 1.49, 0.39, and 0.45 Mg·ha−1·yr−1 and 0.05, 0.14, 0.03, and 0.04 Mg·ha−1·yr−1 for grasslands, recently developed commercial farmlands, old commercial farmlands, and small-scale cultivated lands, respectively. The results of this study revealed that soil disturbance during forestland conversion to tillage enhanced the decomposition rate of organic matter in recently developed commercial farmlands. Nevertheless, after agricultural abandonment and vegetation restoration, the SOC and TN stock capacities were enriched in the old commercial farmlands. It is, therefore, important to effectively restore vegetation and implement sustainable land-use management practices.