Despite rising demand for agricultural products, agricultural land abandonment is increasing, especially in developed countries, leading to recolonization by natural vegetation. This phenomenon impacts ecosystem services, biodiversity, and the economy, causing, for example, the loss of agrobiodiversity, soil erosion, and increased frequency and intensity of fires. Monitoring and understanding the drivers of agricultural abandonment are crucial for protecting historic landscapes. The aim of the study was to assess land use in the 1950s in areas of the Latium region that are currently classified as natural and semi-natural (about 736,000 hectares), and analyze the dynamics of renaturalized agroforestry landscapes. The diachronic land use analysis highlighted that approximately 76,700 hectares of today's wilderness areas were used for agriculture in the 1950s, with 70% consisting of arable land and 17% comprising complex cropping and farming systems. Grasslands covered more than 136,000 hectares, 57% of which are still preserved, while 40% have transitioned to forest or shrubland. Forest land use class increased from 25.59% in 1954 to 31.39% in 2006. The loss of agricultural land has significant implications for the economic sustainability of extensive livestock farming, the self-sufficiency of the food system, and also the proliferation of ungulates, a phenomenon that has become increasingly difficult to manage in Italy. At the same time, the loss of grasslands leads to the simplification of the landscape with a consequent loss of biodiversity. This phenomenon has also been observed in Natura 2000 sites, where around 30% of grasslands, including habitats of priority importance, have been lost. This decline highlights the critical challenges that must be addressed to achieve the goals of the “Nature Restoration Law”, which sets habitat restoration targets of 20% by 2030 and 100% by 2050, and the reduced capacity of these new simplified landscapes to provide ecosystem services.

Introduction: Loss of biodiversity in agroecosystems is considered a significant problem. Therefore, to protect this biodiversity, policies that are consonant with and strategically support ecosystems should be considered. Given the importance of biodiversity in sustainable agricultural systems and the observed agricultural variability in Guilan Province over the past two decades, this study was conducted to determine the biodiversity variability of crop and horticultural species in Guilan Province, northern Iran.

Methods: The data were classified into different groups: cereals, industrial crops, pulses, forage crops, orchards, and vegetables. All raw data were entered into Microsoft Excel (version 2013) based on region and year. Subsequently, several biodiversity indices—including Shannon–Wiener, Margalef, Menhinick, Simpson, richness, evenness, and Berger–Parker—were calculated.

Results: The results revealed significant variation in agrobiodiversity indices within Guilan Province during the study period. For instance, the Shannon–Wiener index for crop species increased from 0.62 to 0.66, while for horticultural products, it increased from 1.82 to 1.97. This increase was notably higher for horticultural products compared to crop species. The findings also indicated that Guilan Province does not exhibit an optimal situation concerning the Shannon–Wiener index, and from the perspective of cultivated species, there was relatively high similarity among townships. A significant factor contributing to the shift in dominance among horticultural species was the expansion of kiwi and citrus cultivation in the province.

Conclusion: Overall, these results suggest that species diversity in Guilan Province was low in most townships. The trend of changes in the indices demonstrated that biodiversity in many regions decreased from 1998 to 2014, in some cases reaching its lowest level. Therefore, methods such as cultivating diverse varieties of crops and horticultural species, implementing crop rotation, and employing intercropping strategies could be utilized to enhance the sustainability of agroecosystems in this province.

Sacred Groves are ecologically significant forest patches preserved through traditional beliefs and community-based conservation practices. They contribute to environmental sustainability by sequestering carbon, conserving native biodiversity, preventing soil erosion, enriching soil fertility, regulating hydrological cycles, supporting natural regeneration, and maintaining ecological connectivity. Therefore, the current study investigates the variation in tree biomass components and regeneration attributes across twelve Sacred Groves in Himachal Pradesh, India, within the north–western Himalayan region. The primary objective was to assess their contribution to conserving biomass accumulation potential and regeneration status with adjacent forests impacted by anthropogenic pressures. Twelve sites (S1–S12) were selected across elevations ranging from 1400 m to 3000 m, categorized into Sacred Groves and Adjoining Forests. This study found consistently higher biomass in Sacred Groves, with total biomass ranging from 280.09 to 1530.21 t ha⁻¹ (mean 885.84 t ha⁻¹), compared to 341.56 to 967.96 t ha⁻¹ (mean 593.20 t ha⁻¹) in adjoining forests. Sacred Groves also exhibited superior natural regeneration, with recruit densities ranging from 750 to 7,500 ha⁻¹, establishment rates from 25.49% to 183.72%, and regeneration success between 60% and 275%. These results underscore the ecological maturity, stability, and resilience of Sacred Groves, emphasizing their critical role in maintaining biodiversity, enhancing carbon storage, and providing essential ecosystem services. As such, Sacred Groves are vital for supporting long-term ecological health and mitigating the impacts of increasing anthropogenic pressures and climate change. Their preservation is crucial for sustaining the ecological balance in the region.

The National Capital Territory of Delhi in India is a rapidly metropolitanized city, and like many others, it faces the risk of urban flooding. The city experiences pluvial flooding, a phenomenon where stormwater drainage systems are unable to handle the volume of water from heavy rainfall and is highly vulnerable to both riverine and urban flooding, posing significant threats to public health, infrastructure, and the local economy. Recent data from the Delhi Traffic Police indicates an increasing frequency of waterlogging incidents in this area between 2011 and 2021. This paper examines the flood risks and identifies parameters that exploit the vulnerability of an area to pluvial flooding, using the case of Kamla Market Circle in the central district of Delhi. It is a densely populated area in the district that has recently become prone to stormwater flooding. The research employs a literature study and field surveys to investigate these factors. The key parameters analysed, such as the degree of urbanisation, shifts in land-use, the capacity and performance of the stormwater drainage system, usage patterns by the local community, and the microtopography of the Kamla Market Circle, may have collectively contributed to the area's heightened vulnerability to pluvial flooding. The findings show that drainage inefficiencies and disruptions to the natural slope due to altered microtopography are the most critical contributors to recurring water accumulation. Moreover, informal modifications to streetscapes and inadequate waste management exacerbate localised flooding. A few context-specific interventions, such as improving surface permeability and regular drainage maintenance, are briefly discussed. This paper presents potential mitigation strategies to address the identified pluvial flood risks in the Kamla Market Circle of Delhi. By offering a comprehensive understanding of the area's flood vulnerabilities, the research aims to support the development of effective, location-specific flood management approaches for this high-risk urban zone.

Urban expansion and industrial development are pivotal drivers of climate change, amplifying greenhouse gas emissions and altering both local and global climate systems. Rapid urbanization is linked to increased energy consumption, urban heat island effects, and changing precipitation patterns, as seen in metropolitan areas such as Bursa and Baghdad. While industrial growth promotes economic advancement, it significantly elevates carbon emissions, often surpassing mitigation efforts. Land-use policies that favor automobile-centric growth further intensify transportation emissions, undermining technical solutions. To examine these interconnected dynamics, this study adopts a conceptual and theoretical approach, developing an analytical framework to assess how energy systems, transportation networks, and land-use patterns influence emissions and climate vulnerability. Emphasizing systemic linkages rather than isolated elements, the analysis reveals that industrial expansion accelerates carbon emissions beyond current mitigation capacities, while urban sprawl heightens heat island effects. Although practical implementation is constrained by socio-economic and governance barriers, conceptual modeling suggests that integrated land-use strategies, low-carbon infrastructure, and adaptive urban planning could substantially reduce climate risks. These findings underscore the urgent need for comprehensive policies that address both immediate and long-term consequences. Transitioning toward decarbonized economies, sustainable urban planning, and diversified energy portfolios is critical to ensuring environmental resilience in an increasingly urbanized world.

Climate stress is increasingly affecting how vegetation grows and how land is used, especially in regions like Sylhet. This study explores these changes by combining climate data with satellite imagery to understand how shifts in temperature and rainfall over the past decades have influenced the area’s natural and built environments. We used climate records from the Bangladesh Meteorological Department alongside satellite-based vegetation indices (NDVI) and land use classifications derived through advanced image processing and GIS techniques. Landsat imagery from 1988 to 2025 was analyzed to calculate NDVI and assess land cover changes. Results indicate that average temperature increased during this period, while rainfall maintained a steady trend. Dense vegetation declined significantly, with more than 38 km² converted to sparse vegetation and about 7.6 km² transformed into urban areas. Additionally, sparse vegetation loss to urban and barren land exceeded 140 km², reflecting rapid urban expansion and growing anthropogenic pressure on natural ecosystems. Our findings reveal that rising temperatures and changing rainfall patterns have led to a noticeable decline in vegetation health and forest cover. At the same time, urban areas in Sylhet, particularly Sylhet Sadar, have expanded, increasing impervious surfaces. The growth of urban areas shows a scattered pattern that becomes more compact over time, shaped by population growth and the region’s topography. Statistical analysis confirms that higher temperatures negatively impact vegetation, while fluctuations in rainfall and expanding urbanization contribute to wetland loss and degradation of agricultural lands. This study highlights how climate and human activities are intertwined in shaping land use and vegetation in Sylhet. It emphasizes the need for ongoing monitoring using geospatial tools and adopting land management strategies that can help the region adapt and build resilience against these environmental stresses.

This study evaluates crop water consumption and irrigation requirements in Eskişehir, located in the semi-arid Central Anatolia region of Türkiye, by comparing three widely used estimation methods. Seasonal crop evapotranspiration (ETc) and net irrigation water requirement (NIWR) values were calculated for the period 2016–2022 using (i) the Blaney–Criddle method (State Hydraulic Works, DSİ), (ii) the CROPWAT 8.0 model, and (iii) the locally developed SuET software, both based on the Penman–Monteith approach. A drought scenario was also constructed using the climatic averages of the region’s driest recorded years (1994, 1995, 2007, and 2008).

The findings reveal considerable discrepancies among methods. For maize, the average NIWR was 377.5 mm according to DSİ, whereas CROPWAT and SuET yielded higher values, averaging 639.7 mm and 619.7 mm respectively. Similar differences were observed for alfalfa (NIWR: DSİ 503.5 mm, CROPWAT 789.2 mm, SuET 734.8 mm) and sunflower (DSİ 288.5 mm, CROPWAT 559.8 mm, SuET 636.4 mm). Under drought conditions, ETc values increased sharply. For example, CROPWAT estimated ETc for sunflower as 772.3 mm in 2016, rising to 927.3 mm in the drought scenario; SuET estimates rose from 708.9 mm to 752.1 mm.

The use of well-established models such as CROPWAT and SuET—both based on the validated FAO Penman–Monteith method—ensures methodological consistency and comparability. The inclusion of DSİ’s Blaney–Criddle-based institutional records enables practical benchmarking and enhances the relevance of the findings.

These results emphasize the need for adaptive irrigation planning and provide crucial insights for improving water allocation strategies in drought-prone regions of Central Anatolia.

The Amazon is the largest tropical forest in the world, covering more than 7 million km². This biome holds the largest hydrographic reserve, accounting for 16% of the planet's freshwater. However, Amazonian rivers are threatened by the expansion of illegal gold mining, which pollutes the water bodies with heavy metals and causes changes in fluvial morphology. Ecuador has 120,000 km² of Amazon biome, where at least 1,660 ha have been deforested by illegal gold mining in rivers such as Nangaritza, Zamora, Yutzupino, Jatunyacu, and Punino. This study aimed to calculate geomorphometric parameters over the Punino river channel to assess the impact of illegal gold mining expansion on fluvial morphology, using Sentinel-2 imagery and supervised classification. The methodology was based on three stages: i) the collection and processing of annual satellite image mosaics (2019 and 2023), ii) Land Use and Land Cover Classification (LULC) using Random Forest, and iii) calculation of morphometric parameters. The results revealed that, in 2019, 28.44% of the channels were choppy and 17.43% were sinuous, representing discontinuities in the Punino River. Meanwhile, in 2023, 37.61% of the channels were meandering and only 17.43% were choppy, suggesting an increase in the flow and continuity of the water body. In addition, in these 4 years, an increase in the measured circularity radius of 87.96% of all meanders analysed was recorded. This impact on the fluvial morphology of the Punino River is associated with the expansion of 217 hectares of mining land and the increase in turbid water in 315 hectares. This paper proposes a methodology based on the use of remote sensing, geoprocessing, and river geo-morphometry techniques to assess the impact of illegal gold mining on Amazonian rivers.

The forest complex Ouémé Supérieur–Wari Maro–Monts Kouffé in northern Benin constitutes an ecosystem of great ecological wealth but remains confronted with deforestation and accelerated degradation due to increasing anthropogenic pressures. This study aims to analyze the degradation hotspots in this complex through time and across space, highlighting human and infrastructural factors. To this end, an integrated methodological approach was mobilized, based on a diachronic analysis of multitemporal satellite images (from the years 1986 to 2024), coupled with remote sensing tools and geographic information systems (GISs). The results reveal a substantial increase in cultivated fields and fallows, from 454.12 ha (0.09% of the complex) in 1986 to 29,400.5 ha (6%) in 2024. Forest cover declined by 17.21% over the same period. Conversely, savannas expanded from 116,359.54 ha (23.73%) to 172,550.23 ha (35.19%). Land transformation processes, analyzed using Bogaert’s decision tree, show continuous agricultural expansion, with the number of patches rising from 288 in 1986 to 2,742 in 2024. However, the 2024 pattern is marked by spatial aggregation rather than new patch creation, as indicated by the increase in the average patch size from 1.6 ha to 10.7 ha. Notably, a large share of these aggregated areas is located near roads, suggesting that accessibility plays a key role in land conversion. The linear regression between the proportion of fields/fallows and proximity to asphalt roads shows a determination coefficient R² of 0.72 with a p-value < 0.01, indicating a strong and significant relationship. The fragmentation of the landscape is intensifying, particularly around asphalted roads, as well as unpaved ones. These findings highlight the need for a re-reading of protected forest management strategies, including better supervision of agricultural expansion, regulation of road developments, and increased involvement of local actors in environmental governance mechanisms.

The Ecuadorian Amazon, one of the world's most biodiverse ecosystems, is increasingly threatened by mining activities that encroach on protected areas and Indigenous territories. These conflicts are exacerbated by inadequate regulatory frameworks, resulting in significant environmental and social concerns. This study evaluates the effectiveness of Ecuador's mining laws and regulations over the past fifteen years (2008–2023) by analysing land use and land cover (LULC) changes using multitemporal satellite imagery from the MapBiomas-Ecuador project, processed with Google Earth Engine. Spatial analysis techniques, including Kernel Density Estimation (KDE) with a 500 m cell size and a 2500 m radius, were employed to assess the spatial distribution and intensity of mining activities. The results reveal a notable increase in mining land cover, particularly in critical areas such as water bodies, conservation units, and Indigenous territories. This expansion suggests that the current mining legislation and its enforcement have not been effective in curbing the spread of extractive activities. The combination of remote sensing, detailed LULC data, and non-parametric spatial statistics offers an innovative and comprehensive framework for assessing land-use changes and mining impacts. The findings provide valuable insights for the design of more effective public policies, environmental monitoring, and territorial planning in ecologically sensitive regions of the Ecuadorian Amazon. This research underscores the pressing need for robust regulatory measures and ongoing monitoring to ensure the long-term sustainability of the region’s natural resources.