Search Results (326)

Land use change is the most direct factor driving the supply and alteration of ecosystem services. This study employed the Dyna-CLUE tool to simulate future land use distributions under two scenarios—the Constrained Trend (CT) and Optimized Target-driven (OT) scenarios—based on land use data from 2010. Subsequently, their corresponding ecosystem service values (ESVs) were calculated, with the simulation outcomes revealing distinct land use layouts under each scenario. Under the CT scenario, grassland and urban areas expanded, whereas farmland and water bodies declined, reflecting a trend of urbanization at the expense of rural landscapes. In contrast, the OT scenario demonstrated a cessation of built-up land expansion, accompanied by marked increases in forest and water coverage, changes that facilitated the restoration of coastal watersheds, enhancing wetland provision and improving overall ESV. Consequently, per capita ESV increased substantially—from 1751 CNY in 2018 to 2356 CNY, matching the 2010 level—primarily due to the conversion of grasslands and farmlands into forests and wetlands. The OT scenario also improved the spatial distribution of ESVs, forming interconnected ecological zones around urban areas. The results underscore that policies restraining built-up expansion, promoting afforestation, and restoring wetlands can significantly improve ecosystem services and contribute to sustainability. Full article

Vegetation restoration in water-limited regions typically increases evapotranspiration (ET) while reducing runoff. Over the past four decades, Daihai Lake in China’s northwest inland river basin has experienced significant shrinkage. Previous studies attribute this primarily to climate change and water resource exploitation, yet the impact of vegetation dynamics remains insufficiently examined. This study analyzed changes in the water budget across different vegetation types in the Daihai Lake Basin, based on remote sensing-derived precipitation and ET data, and employed correlation analysis to examine the relationships between environmental factors (such as climate change, afforestation projects, and water-saving irrigation) and lake shrinkage. Our findings revealed that afforestation has expanded forest cover by 69.42 km² since 2000, accounting for 73.95% of the total forest area. Notably, forest ET demonstrated the strongest negative correlation (r = −0.89, p < 0.001) with lake area among all vegetation types. Grasslands emerged as the primary water-surplus vegetation, contributing 81.34% to the basin’s total water surplus. The synergistic effects of precipitation reduction, temperature increase, and enhanced ET from forest expansion drove the shrinkage of the lake. These results highlight the need for science-based vegetation management in arid and semi-arid regions, where we recommend adopting shrub-grass combined restoration approaches to enhance the sustainability of ecological restoration. Full article

Afforestation of former agricultural land is widely promoted as a strategy to mitigate climate change and support sustainable land management. However, soils subjected to long-term cultivation often retain chemical legacies that may persist for decades after land-use change, influencing soil functioning and ecosystem development. This study investigates the persistence of selected agricultural soil chemical properties following afforestation using a chronosequence approach. Post-agricultural soils afforested for 15, 40, and 80 years were examined on Dystric Brunic Arenosols developed from sandy parent material. Composite samples were collected from forest-floor horizons (Ol and Ofh) and upper mineral horizons (A and B). The analyzed parameters included organic carbon (Corg), total nitrogen (Nt), sulfur (S), soil pH, hydrolytic acidity (Ha), exchangeable base cations (EBC), and cation exchange capacity (CEC). The results show that agricultural soil legacies persist for several decades after afforestation. Soils under the 15-year-old stand were characterized by higher exchangeable calcium, higher base saturation, and lower hydrolytic acidity, reflecting the persistence of historical liming. With increasing stand age, soil acidity increased, and base-cation concentrations declined, while organic carbon accumulated mainly in forest-floor horizons. These findings highlight the importance of considering agricultural soil legacies when evaluating the sustainability of afforestation and its role in long-term ecosystem services. Full article

Following successful national forest restoration projects, South Korea has designated and operates Leading Forest Management Zones (LFMZs) to improve forest quality and promote sustainable use. The objective of this study is to comparatively evaluate the operational characteristics of 26 LFMZs (5 national and 21 private forests) based on complete long-term data from 2013 to 2024 and to identify ownership-based structural differences in integrated forest management performance. Five core indicators representing the forest management cycle (afforestation, timber harvest, forest products, forest roads, and forest tending) were analyzed using multivariate statistical methods. Permutational Multivariate Analysis of Variance (PERMANOVA) results revealed statistically significant structural differences between national and private forest management systems (F = 13.22, p = 0.001, R² = 0.47). Non-metric multidimensional scaling (NMDS) identified forest road development and timber harvest intensity as the primary drivers of these differences. National forest LFMZs exhibited consistently higher and more balanced management intensity across all indicators, supported by stable institutional frameworks and professional management capacity. In contrast, private forest LFMZs showed substantial variability in performance, reflecting differences in ownership structure and regional conditions. Correlation analysis further demonstrated strong positive relationships among afforestation, forest tending, forest road development, and timber harvest, underscoring the importance of integrated forest management. These findings provide empirical evidence to support differentiated, ownership-sensitive forest management strategies and contribute to strengthening sustainable forest governance in South Korea under climate change and socio-economic transitions. Full article

Due to climate change, seedling damage caused by drought stress is expected to increase in both afforestation sites and nurseries. Therefore, to ensure stable seedling production under high-temperature conditions and to cultivate seedlings with enhanced drought tolerance through hardening treatments, the development of an effective irrigation system is required. Conventional physiological methods for non-destructive drought detection, such as chlorophyll fluorescence and leaf temperature measurements, require expensive and manual operation, thereby limiting their real-time applicability in forest nurseries. This study evaluated the applicability of using image-based leaf angle measurements for drought stress detection in Quercus acutissima Carruth. seedlings. One-year-old seedlings were grown under two water regimes—well-watered (CT: control) and unwatered (DT: drought)—through Day 8. Statistical analyses (RMANOVA) revealed that changes in the leaf angle parameter PMD–MD (the difference between the previous and current measurement days) showed treatment effects similar to those of the physiological responses ΦNO (quantum yield of non-regulated energy dissipation) and qL (fraction of open PSII reaction centers) to drought on Day 6. Leaf angle reflected drought stress but did not precede physiological changes, indicating its role as a complementary rather than an early indicator. Multiple regression models identified AT (air temperature), SM (soil moisture), Fm′ (maximum fluorescence in the light-adapted state), and VPD (vapor pressure deficit) as the main factors influencing leaf angle variation. Although leaf angle was affected by combined environmental stresses such as high temperature, it was less sensitive to heat stress than physiological responses based on RMANOVA results. These results indicate the potential of image-based leaf angle measurements for drought stress detection. To establish plant-based smart irrigation systems, future studies should validate and refine this approach using larger datasets. Full article

Land use/land cover (LULC) change significantly influences a range of environmental and socio-economic issues, including climate change, deforestation, biodiversity loss, soil degradation, ecosystem services, and food security, at local, regional, and global levels. In the northwestern Himalayan region, particularly in Rajouri district of Jammu and Kashmir (J&K), LULC change has profound environmental and socio-economic implications. Understanding the temporal and spatial dimensions of LULC change is crucial for assessing the impact of human activities on the region’s environment. The present study aimed to analyze LULC change in Rajouri district of J&K, India over a 30-year period from 1990 to 2020 and to project future LULC dynamics for the next 30 years up to 2050. Landsat imagery with a supervised classification technique was used for classification and generation of LULC maps. Moreover, CA Markov model was used to predict the future LULC status of the area. The model validation exhibited strong performance, with Kappa statistics exceeding 0.90, indicating a high level of reliability in the projections. The results indicate considerable changes in different land use classes from 1990 to 2020. Over the 30-year period, dense forest showed the maximum reduction of about −20.69 Km², followed by open forest (−15.87 Km²) and grassland (−13.75 Km²). Wasteland showed the maximum increase of about +28.24 Km², followed by built-up (+17.90 Km²) and cropland (+12.50 Km²). The cumulative impact of deforestation from 1990 to 2020 amounts to approximately 43.17 Km², while afforestation efforts only managed to reclaim 6.61 Km² of land. The future prediction using the CA Markov model suggests further changes in LULC patterns, with built-up, cropland, and wasteland projected to increase exponentially by 2050, accompanied by sharp declines in forests. Therefore, policymakers should prioritize sustainable land management and forest conservation strategies to mitigate the potential negative impacts of LULC changes on the environment, ensuring balanced and sustainable development. Full article

The Aravalli Mountain System (AMS) is one of the oldest fold orogens in the world, serving as a natural boundary against desertification in north-western India. The AMS has high environmental importance and faces accelerated soil degradation driven by both anthropogenic pressures and climatic shifts. Still, high-resolution measurements of soil erosion processes have not been conducted on the AMS scale. The present study assesses long-term LULC transitions between 2001 and 2021, identifies high-resolution short-term LULC dynamics between 2017 and 2024, and models spatiotemporal soil erosion dynamics using the RUSLE model. The findings indicate that LULC has changed rapidly, with built-up areas increasing by 53 per cent at the expense of rangelands and croplands. These drivers resulted in a 13.8 per cent increase in the mean annual soil loss between 2017 and 2024, from 1.59 to 1.81 t/ha/yr, while forest cover has increased over the timescale, as is evident in this study. The steep slopes, susceptible soils, and mining areas are strongly associated with erosion hotspots. Increased soil erosion in the AMS despite a significant increase in afforestation highlights that local conservation cannot compensate for massive land conversion. The present study provides a scalable, high-resolution framework for assessing soil erosion in vulnerable old mountain systems globally for sustainable land-use planning, mineral governance, and integrated conservation to protect for future generations. Full article

Long-term fire histories are well-documented across most North American temperate forest systems, yet the fire regimes of high-alpine treeline environments remain poorly understood. Here, we present a millennial-scale fire history from the Sawtooth Fen Palsa (SFP), a rare permafrost fen palsa located in the high-alpine treeline ecotone of the Beartooth Plateau, Wyoming, a permafrost system now unraveling due to recent decades of rapid warming. Analysis of paleoenvironmental proxies from peat sediments overlying the permafrost reveals a multi-century peak in fire activity at the beginning of the record, ca. 10,000 cal yr BP, coinciding with the afforestation of newly deglaciated, ice-free sites. This initial surge in high-severity fire activity was followed by a decline when solar-orbitally driven increases in growing-season temperatures likely promoted forest opening and more surface fire activity within the SFP watershed. High-severity fire activity increased again during the mid-Holocene (ca. 5800–5000 cal yr BP), when effective moisture increased, favoring subalpine forest expansion and increased connectivity of woody biomass (sagebrush and forest), enhancing the potential for canopy fire spread. Only two small fire episodes were recorded in recent millennia when a rapid change in the sedimentation rate may indicate a partial loss of the sediment record. Rapid warming in recent decades has triggered the formation of dozens of thermal collapse ponds across the fen palsa. The frequency of these features has more than doubled since 2000 CE, underscoring the degradation of underlying permafrost in response to changing climatic conditions. Continued warming is expected to cause the complete loss of the permafrost lens and alter ecosystem dynamics, disturbance regimes, and carbon and nutrient cycling in alpine systems throughout the Rocky Mountains. Full article

Reliable hydrologic modeling in arid, topographically complex watersheds depends on accurate land-use/land-cover (LULC) representation. This study evaluates how different LULC categorization methods affect simulated runoff for the Wadi Hatta watershed (UAE) using a GIS-driven machine learning framework that combines high-resolution remote sensing with hydrologic modeling. LULC maps were generated in Google Earth Engine using Random Forest (RF) and Support Vector Machine (SVM) classifiers applied to Sentinel-2 (10 m) and Landsat 8/9 (30 m) imageries and compared with the 10 m ESRI predefined LULC dataset. The resulting LULC classifications were converted to SCS Curve Numbers and used in HEC-HMS hydrologic modeling to simulate runoff under a 50-year design storm, under consistent meteorological and physical conditions. Results show that Sentinel-2 + SVM achieved the highest classification accuracy (overall accuracy up to 0.86) and produced the earliest and highest simulated peak discharge (11.4 m³/s), reflecting improved detection of impervious surfaces. In contrast, the Landsat-9 + RF scenario yielded the lowest peak (7.5 m³/s), consistent with a higher proportion of pervious land covers. LULC change analysis between 2017 and 2024 showed increases in forest cover (1.0–3.3%) and built-up areas (6.0–7.9%) driven by afforestation and urban expansion. These results demonstrate that LULC input resolution and classifier selection significantly influence hydrologic model sensitivity and runoff estimates, underscoring the need for carefully selected, high-resolution LULC products in flood risk assessment and water resource planning in data-scarce arid environments. Full article

Soil organic matter (SOM) molecular composition governs its stability and ecological functions in forest ecosystems. Nevertheless, how land-use changes (LUCs) regulate the SOM molecular composition remains poorly understood, particularly the underlying mechanisms mediated by soil properties. This study investigated the effects of LUCs on SOM molecular composition in a subtropical coastal region and examined the driving roles of soil nutrient availability and enzyme activities. The research was conducted in Huanghai National Forest Park, Jiangsu Province, China, focusing on four land-use types converted from historical wheat cropland (W, as control): monoculture plantations of Ginkgo biloba (G) and Metasequoia glyptostroboides (M), a ginkgo–metasequoia mixed forest (GM), and a ginkgo–wheat agroforestry system (GW). Soil samples were collected from 0 to 20 cm and 20–40 cm layers and analyzed for SOM molecular compositions using solid-state ¹³C nuclear magnetic resonance (NMR) spectroscopy. Soil chemical properties and enzyme activity activities were also determined, with redundancy analysis (RDA) and correlation analysis applied to identify key influencing factors. Results demonstrated that LUCs significantly altered SOM molecular composition. The GW system exhibited the highest proportion of labile O-alkyl carbon (42.65%), while the M plantation accumulated greatest levels of stable aromatic carbon (up to 49.25%). During the initial decades following afforestation, soil nutrient availability and enzyme activities were confirmed as pivotal drivers of SOM molecular variation. Specifically, available potassium (AK), ammonium nitrogen (AN), and the carbon/phosphorus (C/P) ratio were significantly correlated with specific SOM components (p < 0.05). The elevated O-alkyl carbon proportion in GW was closely associated with its higher invertase activity. Notably, vertical differentiation in SOM stability was observed across land-use types, with the agroforestry system achieving the highest carbon pool management index in surface soil but showing a weakened capacity for subsoil C stabilization. RDA further confirmed that AK and AN were dominant factors shaping SOM molecular composition. In conclusion, LUCs modulate SOM chemical composition and stability primarily through altering soil nutrient availability and associated enzyme activities. Agroforestry system facilitates labile C accumulation in surface soil, whereas monoculture plantations are more conducive to stable C sequestration, especially in subsoil layers. These findings provide novel mechanistic insights into SOM dynamics following LUCs and offer a theoretical basis for formulating tailored management strategies to enhance C sequestration efficiency in subtropical coastal ecosystems. Full article

Greenhouse gases emitted by humans have exacerbated global climate change. Forests can effectively sequester atmospheric carbon dioxide through photosynthesis, and afforestation has been widely adopted worldwide to mitigate climate change. Cunninghamia lanceolata and Pinus massoniana, as major afforestation tree species, are extensively cultivated in southern China. However, the mechanisms by which climate, topography, biodiversity, forest structure, and forest growth status affect the productivity of these two species remain unclear. This study used forest inventory data from Lishui City combining the Biomod2 model with a structural equation model (SEM) to investigate the differential effects of biotic and abiotic factors on the productivity of the two tree species. The results showed that at the same diameter at breast height (DBH), the biomass of P. massoniana reached 384.67 kg, accounting for 188.75% of that of C. lanceolata (211.07 kg). The dominant climatic factors affecting C. lanceolata and P. massoniana were different; the most important climatic factors affecting C. lanceolata were Bio 17, Bio 15, Bio 05, Bio 08, and Bio 02, while those affecting P. massoniana were Bio 18, Bio 04, and Bio 01. Furthermore, the explanatory power of the structural equation model (SEM) optimized by the Biomod2 model was effectively improved. Biodiversity and forest growth factors were the most important biotic factors affecting C. lanceolata (p < 0.01), while structural diversity and forest growth factors were the most important biotic factors affecting P. massoniana (p < 0.05). Biodiversity and structural diversity exerted divergent effects on C. lanceolata and P. massoniana in different growth stages, exerting negative effects in the early growth stage and positive effects in the late growth stage. These outcomes were jointly driven by the selection effect and niche complementarity. This study recommends the forest management practices should select tree species based on local conditions. Full article

Changes in land use patterns due to urbanisation impact local weather patterns by influencing Land Surface Temperatures (LSTs). Despite rapid urbanisation in the Delhi-NCR (National Capital Region), the peri-urban fringes of Haryana, such as the Central Circle Forest (CCF) region, in the past three decades, a comprehensive 30-year analysis that integrates LST, the Normalised Difference Vegetation Index (NDVI), the Normalised Difference Built-up Index (NDBI), and Land Use/Land Cover (LULC) is lacking. The current study on the decadal analysis covering the 1993 to 2023 time period shows an increase in built-up areas (14.6–38.4%), a decline in NDVI (−0.01 to −0.08), a 6 °C rise in summer LST, and weak correlations between LST and NDVI. A significant increase in summer mean LSTs was observed, with some regions reaching temperatures beyond 35 °C in the selected districts. The LST and LULC zonal statistics revealed that the open fields/agricultural land and floodplains of the Yamuna River have adversely affected the weather pattern with rising LST. The average NDVI declined from −0.01 in 1993 to −0.08 in 2023, indicating a loss of vegetative buffers. Meanwhile, NDBI trends from 2003 to 2023 showed that built-up areas have steadily grown, and LULC data highlighted 38.43% of the built-up area in 2023. Correlation analysis showed a weak negative relationship between LST and NDVI (r = −0.47), suggesting diminishing cooling effects of vegetation, while a weak positive correlation between LST and NDBI indicates that urban expansion is significantly contributing to the urban heat island effect. This study emphasises the need for green infrastructure, afforestation, and water conservation in urban planning frameworks to enhance climate resilience and ecological sustainability. Full article

This study explores the potential for afforestation in Portugal that could balance wood and non-wood forest production under future climate change scenarios. The Climate Envelope Models (CEM) approach was employed with three main objectives: (1) to model the current distribution of key Portuguese forest species—eucalypts, maritime pine, umbrella pine, chestnut, and cork oak—based on their suitability for wood and non-wood production; (2) to project their potential distribution for the years 2070 and 2090 under two Shared Socioeconomic Pathway (SSP) scenarios: SSP2–4.5 (moderate) and SSP5–8.5 (high emissions); and (3) to generate integrated species distribution maps identifying both current and future high-suitability zones to support afforestation planning, reflecting climatic compatibility under fixed thresholds. Species’ current CMEs were produced using an additive Boolean model with a set of environmental variables (e.g., temperature-related and precipitation-related, elevation, and soil) specific to each species. Species’ current CEMs were validated using forest inventory data and the official Land Use and Land Cover (LULC) map of Portugal, and a good agreement was obtained (>99%). By the end of the 21st century, marked reductions in species suitability are projected, especially for chestnut (36%–44%) and maritime pine (25%–35%). Incorporating future suitability projections and preventive silvicultural practices into afforestation planning is therefore essential to ensure climate-resilient and ecologically friendly forest management. Full article

Afforestation is recognized as a highly effective strategy for enhancing ecosystem carbon sequestration. However, the changes and drivers of soil organic carbon (SOC) following afforestation are still debated due to climate differences. Clarifying these responses is critical for improving the effectiveness of afforestation-based carbon sequestration strategies. In this study, we analyzed nine 20-year-old afforestation sites (coniferous and broad-leaved) along a Chinese climatic gradient to quantify SOC and its fractional changes following farmland-to-forest conversion, and to identify the dominant factors controlling SOC sequestration across climatic gradients and forest types. The results showed that afforestation enhanced SOC (5.1%–210.5%, p < 0.05) in humid and semi-humid regions, but showed no significant effect in semi-arid regions, and it even reduced SOC in arid regions (−19%–−53.8%). Across all climatic zones, mineral-associated organic carbon was the dominant contributor to SOC accumulation throughout the entire soil profile (0–60 cm). Climatic-scale analyses based on the aridity index determined that root and litter C/N ratios were the primary drivers of SOC sequestration in coniferous forests, whereas in broad-leaved forests, they were more strongly controlled by soil physicochemical properties, particularly total nitrogen, bulk density, and soil water content. This study identified that SOC responses to afforestation are strongly mediated by climate and forest type, which is helpful for managers to take targeted measures to increase soil carbon sequestration in forest management. Full article

Air pollution is a major but often under-integrated driver of forest dynamics at the global scale. This review combines a bibliometric analysis of 258 peer-reviewed studies with a synthesis of ecological, physiological, and biogeochemical evidence to clarify how multiple air pollutants influence forest structure, function, and regeneration. Research output is dominated by Europe, East Asia, and North America, with ozone, nitrogen deposition, particulate matter, and acidic precipitation receiving the greatest attention. Across forest biomes, air pollution affects growth, wood anatomy, nutrient cycling, photosynthesis, species composition, litter decomposition, and soil chemistry through interacting pathways. Regional patterns reveal strong context dependency, with heightened sensitivity in mountain and boreal forests, pronounced ozone exposure in Mediterranean and peri-urban systems, episodic oxidative stress in tropical forests, and long-term heavy-metal accumulation in industrial regions. Beyond being impacted, forests actively modify atmospheric chemistry through pollutant filtration, aerosol interactions, and deposition processes. The novelty of this review lies in explicitly framing air pollution as a dynamic driver of forest change, with direct implications for afforestation and restoration on degraded lands. Key knowledge gaps remain regarding combined pollution–climate effects, understudied forest biomes, and the scaling of physiological responses to ecosystem and regional levels, which must be addressed to support effective forest management under global change. Full article