Forests are among the most vital and indispensable components of our ecosystems. However, increasing population pressure and associated infrastructural development have led to significant degradation of forest resources, particularly in developing regions. This study examines the temporal dynamics of forest canopy density over a 30-year period and identifies areas of disturbance within the forested landscapes of Keonjhar and Sundargarh districts, situated in northern and north-western Odisha, India. Forest canopy density changes were assessed using Landsat imagery from 1988 and 2021. Remote sensing-based biophysical indices such as AVI, BSI, and SSI were employed to develop a forest canopy density (FCD) model. Results indicate that approximately 17% of the forested area has been converted to bare land, and nearly 10% of the dense and moderately dense forested area has been converted to open forest in this period. Additionally, secondary datasets, including road networks, railway lines, mining areas, settlements, and industrial zones were integrated to analyze human-induced disturbances and delineate disturbance zones within the forests. A trend analysis of NDVI from 1988 to 2021 was conducted to validate these zones. Increasing mining activities, infrastructure development, settlement growth, and industrial waste dumping are identified as primary contributors to the increasing disturbance within the forest ecosystems of Keonjhar and Sundargarh districts. These findings highlight the urgent need for sustainable forest management and conservation strategies in this region.

Due to drought and underground water extraction, many plains in Iran are experiencing subsidence. Among these areas, we can mention the southwestern part of Tehran, which has a large resident population and has suffered severe subsidence in the last two decades. In order to study subsidence, various ground and aerial methods are used, and the interferometric synthetic aperture radar (InSAR) system is one of those techniques that measures accurate values of ground surface displacement with high spatial resolution across a large study area. The small baseline subset (SBAS) method is a remote sensing-based technique to analyze the time series of radar interferometry. It is particularly important to examine subsidence patterns over different time frames in a geographical area and their relationship with climatic parameters, such as precipitation, in remote sensing. In this context, this research uses the SBAS method to obtain the average displacement velocity field of southwest Tehran for the period from 2014 to 2017. The maximum amount of subsidence in this area is 174 mm per year along the satellite's line of sight and 227 mm per year in the vertical direction. The time series obtained from InSAR shows the uplift during certain periods. This uplift is attributed to rainfall exceeding 20 mm before the uplift events, particularly in the last six measurements, where heavy rain has resulted in an uplift of up to 50 mm.

We examine how renewable energy adoption (REA) and social welfare (SW) initiatives shape corporate profitability in Saudi Arabia, a critical test case for resource-dependent economies undergoing sustainability transitions under Vision 2030. Employing a dynamic panel Generalized Method of Moments model and quartile regression on 48 firms (2010–2024), the analysis dissects heterogeneous effects across low-, mid-, and high-profitability tiers. Results reveal that RE adoption drives profitability most for high-profit firms, leveraging scalable infrastructure and innovation, while SW initiatives like job creation and training disproportionately benefit low-profit firms by stabilizing operations. Mid-profit firms uniquely capitalize on RE-SW synergies, balancing green innovation with workforce development. These findings challenge narratives of sustainability as a profitability trade-off, aligning with the Porter Hypothesis and Stakeholder Theory. Policy implications advocate for tiered strategies: RE incentives for high-profit firms, training subsidies for low-profit firms, and synergy-focused industrial zones for mid-profit firms. By tailoring interventions to financial contexts, Saudi Arabia can harmonize Vision 2030’s sustainability goals with equitable growth, offering a model for resource-rich economies navigating green transitions.

Medicinal plants have been essential to indigenous practices since ancient times. The Sunderbani region in Jammu and Kashmir (India) hosts a wealth of medicinal plants and traditional wisdom. However, these resources have faced threats due to socio-cultural changes, urbanization, and economic development, highlighting the need for conservation measures. Therefore, this study focuses on documenting the ethnobotanical knowledge of the study area. With prior consent, interviews and group discussions were conducted with traditional healers and locals to collect the data. The collected data were analysed using various quantitative indices. The study identified 66 plant taxa used to treat 12 ailment categories. Herbs constituted 45.45% of the plants, with leaves being the most frequently use plant part (40.5%). Asteraceae emerged as the dominant family. The majority of raw drugs were prepared as powders (32.5%). Prominent plants based on use report (UR) and use value (UV) included Terminalia bellirica (UR 51, UV 0.055), Phyllanthus emblica (UR 48, UV 0.052), Terminalia chebula (UR 47, UV 0.051), and Grewia optiva (UR 46, UV 0.050). Diseases of the circulatory system (ICD code 11) had the highest Informant Consensus Factor (ICF 0.97), while respiratory diseases (ICD code 12) had the lowest (ICF 0.15). Families like Phyllanthaceae (FUV 0.052) and Combretaceae (FUV 0.048) were highly cited. Many folk claims were novel and documented for the first time. The Sunderbani region is a repository of unique medicinal plants and traditional knowledge. Exploring the novel plant uses could serve as a lead for pharmacological research and future drug development while emphasizing the need for conservation efforts.

Rainwater irrigation is relatively an uncommon practice in Pakistan, yet certain areas still utilize rainwater harvesting to address water scarcity. A north-south oriented belt, parallel to the Khirthar foothills and along the Indus River floodplain in Sindh province, has been identified as suitable for rainwater-based agriculture. Over time, easterly alluvial deposits have expanded, supporting agricultural growth. The main objective of this study was to explore the potential of rainwater harvesting and storage in Kacho, Sindh, for sustaining agriculture and mitigating water shortages. To achieve this, field surveys, water quantification techniques, construction of small reservoirs, and satellite image analysis were applied to assess available water resources and cultivation potential. Research findings indicate progressive improvements in water conservation, with 33.3% retained in 2017, 44.4% in 2018–2019, 38.9% in 2020, 66.6% in 2021, 88.5% in 2022, and 107.5% in 2023. Correspondingly, wheat productivity has increased from 450 kg in 2017 to 815 kg in 2023 in the selected study area. These findings demonstrate the effectiveness of rainwater irrigation in mitigating water shortages and enhancing crop yields. Ultimately, sustainable rainwater conservation is a viable solution for strengthening food security and agricultural resilience in arid regions of Pakistan.

Forest fires are one of the most serious environmental disasters that endanger the natural forest ecosystem. Forest fire catastrophes have recently received a lot of attention because of their escalating numbers and the effects of global climate change. Recognizing fire occurrence and their patterns is important in identifying fire risks to mitigate the potential fire-prone areas surrounding human settlements and potential protected areas. Additionally, smoke emissions from fires endanger public health and natural systems, plus the added impact of natural triggers such as rainfall may cause debris floods or landslides initiated from the burnt areas. This study seeks to highlight burnt area mapping of the environmentally protected area of Mayurbhanj District, Odisha, India, which was devastated in the year 2021 due to a massive forest fire event. The main aim of this study was to create a map that would be a reliable risk indicator of forest fire zones in a defined region of interest, which is important and famous as a unique Geotourism and recreational destination. The study of the forest fire probability (risk zones) involved the investigation of an array of pertinent natural and geomorphological independent variables, such as vegetation type, climate, topography, road buffer, historical fire data, etc. Multi-criteria decision model (MCDM), i.e., analytic hierarchy processes (AHP) and Fuzzy Analytic Hierarchy Processes (FAHP) were used to comparatively assign weightage as per their influence on the prevailing fire risk. Results indicate that 1,058 km² (30.79% of the study area) is highly susceptible to wildfires, posing a significant threat to biodiversity. Satellite-derived fire risk indices and historical MODIS fire data effectively delineate high-risk zones after the severe 2021 wildfire, highlighting the urgent need for mitigation. By leveraging modelling and geospatial analytics, this study presents a scalable wildfire risk management approach, offering valuable insights for policymakers and disaster mitigation authorities in fire-prone landscapes of touristic importance.

Forest structure is a key to effective forest management. This study analyzed diameter and height data collected from two plots in Tuyen Quang, Vietnam to elucidate the structural characteristics and carbon stocks of the forests. The forest volume varied between 77.59 and 103.93 m³, while the carbon stock ranged from 32.53 to 43.83 (Ton/ha). Additionally, the number of carbon credits spanned from 119.38 to 160.86. The best function for simulating the diameter frequency distribution was Wakeby and Gen. Gamma (4P). Meanwhile, the best function for the height frequency distribution was Dagum and Log-Logistic (3P). The regression between diameter and height was best described by the Power and Naslund equation. A strong association between diameter, height and forest tree quality was revealed in both plots. Good trees were typically clustered within groups with larger diameters and heights, whereas bad trees were predominantly found in the smallest groups. These findings will support the assessment of a forest's ecological functions, contributing to effective carbon sequestration initiatives and climate change mitigation efforts in the future.

Land use and land cover are important factors affecting ecosystem services through alteration of the natural environment. The purpose of this study was to assess the impact of changes in land use and land cover (LULC) on ecosystem service values (ESV) in Sekela Woreda. As part of the study, the spatial and temporal dynamics of LULC over the last three decades were analysed. Using ArcGIS 10.6 software, ESVs were obtained for each LULC class. The results of the research show that during the study period, there were changes in land use and land cover in the study area, with agricultural land declining by 4,079.66 ha (–14.98 %) and water bodies by 125.15 ha (–45%), while the area of wasteland, scrubland, woodlands and water bodies increased by 2670.57 ha (7.9%), 363.78 ha (3.87%) and woodlands by 1169.62 (3.22%), respectively. The research has shown that changes in land use and land cover have resulted in a decrease in ESVs of 0.865686 over the last 30 years (1985–2015). Consequently, LULC has had a negative impact on ecosystem services and functions over the past 30 years. Therefore, in order to manage ecosystems in this area in a sustainable manner, it is necessary to protect natural resources and take appropriate intervention measures.

The reduction of pesticides through organic farming releases some agricultural pest species from human control. We propose that this results in higher pest populations and indirectly, via plant diversity, affects avian community structure in agricultural landscapes. Therefore, we collected data on vegetation diversity (trees, bushes, herbs), from organic agrolandscapes and analyzed how vegetation diversity impacted the diversity and structure of insects and birds. The aim of this research is: i) To investigate the ecological, taxonomic, and functional structure of biodiversity in organic agricultural landscapes and its impact on ecosystem services. ii) To propose mechanisms for managing bird population in organic agro-ecosystems, considering biotic and transabiotic links. We used botanical, forestry and ecological methods to assess biodiversity. We found that plant diversity increases and species dominance decreases in ecotones approaching forest belts, insect diversity depends on the crop planted in fields, and bird diversity depends on landscape connectivity and structure. Fourteen families of insects occurred in the winter wheat field, 22 families in the buckwheat field, and 15 families in the soybean field. Among these, phytophages (40-69%) dominated, parasitic species ranged from 18 to 24%, and predators accounted for 7-26% of the total number of individuals collected. Twenty-eight bird species (6 food specialists) fed in the fields, dominated by species with broad diets. The list of species feeding in an area depended on the qualitative characteristics of the forest belt surrounding the area. We conclude that birds can serve as a practical pest control if combined with additional organic farming economic and environmental management strategies. To preserve biodiversity, it is important to take into account the structure of the forest shelterbelts, types of habitats due to the expansion of fields’ margins (ecotones), plants that resistant to damage by phytophagous insects, as well as tree species that can attract birds as a food base. Results on existing environmental risks and ways to mitigate them in organic farming can be used for systemic analyses of biodiversity structure in agro-landscapes: fields, their margins, forest shelterbelts, etc.

This study investigates the relationship between environmental performance and ecological sustainability by analyzing data from 168 countries using two widely recognized indicators: the Environmental Performance Index (EPI) and the Ecological Footprint (EF) per capita. Contrary to common assumptions that strong environmental governance correlates with lower ecological impact, the findings reveal a moderate positive relationship between EPI and EF (Pearson's r = 0.57; Spearman's ρ = 0.65, p < 0.001). This finding suggests that countries with higher EPI scores often exhibit larger ecological footprints, primarily driven by affluence and consumption intensity. Linear regression results further substantiate this link, with EPI emerging as a significant predictor of EF (β = 0.107, p < 0.001), explaining 32.4% of the variance. Cluster and principal component analyses reveal four country typologies, distinguishing between high-performing but high-impact nations and those achieving more sustainable balances. Case studies, including Germany, Saint Lucia, Saudi Arabia, and Guatemala, illustrate the spectrum of governance-impact dynamics. These results challenge the adequacy of governance-centric indicators and highlight the need for integrated sustainability frameworks that combine policy metrics with consumption-based impact measures. By questioning the assumption that environmental performance is synonymous with ecological sustainability, this research calls for a fundamental rethinking of how sustainability is measured, communicated, and pursued in the era of planetary boundaries.