Search Results (563)

Ecosystem restoration represents a promising solution for enhancing ecosystem services and environmental sustainability. However, border regions—characterized by ecological fragility and geopolitical complexity—remain underrepresented in ecosystem service and restoration research. To fill this gap, we coupled spatially explicit models (e.g., InVEST and RUSLE) with scenario analysis to quantify the ecosystem service potential that could be achieved in China’s Tibetan borderlands under two interacting agendas: ecological restoration and border-strengthening policies. Restoration feasibility was evaluated through combining local biophysical constraints, economic viability (via restoration-induced carbon gains vs. opportunity costs), operational practicality, and simulated infrastructure expansion. The results showed that per-unit-area ecosystem services in border counties (particularly Medog, Cona, and Zayu) exceed that of interior Tibet by a factor of two to four. Combining these various constraints, approximately 4–17% of the border zone remains cost-effective for grassland or forest restoration. Under low carbon pricing (US$10 t⁻¹ CO₂), the carbon revenue generated through restoration is insufficient to offset the opportunity cost of agricultural production, constituting a major constraint. Habitat quality, soil conservation, and carbon sequestration increase modestly when induced by restoration, but a pronounced carbon–water trade-off emerges. Planned infrastructure reduces restoration benefits only slightly, whereas raising the carbon price to about US$50 t⁻¹ CO₂ substantially expands such benefits. These findings highlight both the opportunities and limits of ecosystem restoration in border regions and point to carbon pricing as the key policy lever for unlocking cost-effective restoration. Full article

Willow stands (Salix spp.) are an essential part of riparian ecosystems, as they sustain biodiversity and provide bioenergy solutions. The present review synthesizes the global scientific literature about the management of willow stands. In order to achieve this goal, we used a dual approach combining bibliometric analysis with traditional literature review. As such, we consulted 416 publications published between 1978 and 2024. This allowed us to identify key species, ecosystem services, conservation strategies, and management issues. The results we have obtained show a diversity of approaches, with an increase in short-rotation coppice (SRC) systems and the multiple roles covered by willow stands (carbon sequestration, biomass production, riparian restoration, and habitat provision). The key trends we have identified show a shift toward topics such as climate resilience, ecological restoration, and precision forestry. This trend has become especially pronounced over the past decade (2014–2024), as reflected in the increasing use of these keywords in the literature. However, as willow systems expand in scale and function—from biomass production to ecological restoration—they also raise complex challenges, including invasive tendencies in non-native regions and uncertainties surrounding biodiversity impacts and soil carbon dynamics over the long term. The present review is a guide for forest policies and, more specifically, for future research, linking the need to integrate and use adaptive strategies in order to maintain the willow stands. Full article

The ongoing decade of UN restoration matches with the European goal of bringing nature back into our lives, including in urban systems, and Nature Restoration Regulation. Within such a framework, this work is aimed at highlighting the ecological rationale and strategic value of an NRRP measure devoted to forest restoration in Italian Metropolitan Cities, and at assessing respective preliminary results. Therefore, the measure’s overarching goal (not to create urban parks or gardens, but activate forest recovery), geographic extent and scope (over 4000 ha and more than 4 million planted trees and shrubs across the country), plantation model (mandatory use of native species consistent with local potential vegetation, density of 1000 seedlings per ha, use of at least four tree and four shrub species in each project, with a minimum proportion of 70% for trees, certified provenance for reproductive material), and compulsory management activities (maintenance and replacement of any dead plants for at least five years), are herein shown and explained under an ecological perspective. Current implementation outcomes were thus assessed in terms of coherence and expected biodiversity benefits, especially with respect to ecological and biogeographic consistency of planted forests, representativity in relation to national and European plant diversity, biogeographic interest and conservation concern of adopted plants, and potential contribution to the EU Habitats Directive. Compliance with international strategic goals and normative rules, along with recognizable advantages of the measure and limitations to be solved, are finally discussed. In conclusion, the forestation model proposed for the Italian Metropolitan Cities proved to be fully applicable in its ecological rationale, with expected benefits in terms of biodiversity support plainly met, and even exceeded, at the current stage of implementation, especially in terms of the contribution to protected habitats. These promising preliminary results allow the model to be recognized at the international level as a good practice that may help achieve protection targets and sustainable development goals within and beyond urban systems. Full article

Situated in the southern hilly-mountain belt of China’s “Three Zones and Four Belts Strategy”, Gannan region is a critical ecological shelter belt for the Ganjiang River. Decades of intensive mineral extraction and irrational agricultural development have rendered it into an ecologically fragile area. Consequently, multiple restoration initiatives have been implemented in the region over recent decades. However, it remains unclear how relationships among ecosystem services have evolved under these interventions and how future ecosystem management should be optimized based on these changes. Thus, in this study, we simulated and assessed the spatiotemporal dynamics of five key ESs in Gannan region from 1990 to 2020. Through integrated correlation, clustering, and redundancy analyses, we quantified ES interactions, tracked the evolution of ecosystem service bundles (ESBs), and identified their socio-ecological drivers. Despite a 31% decline in water yield, ecological restoration initiatives drove substantial improvements in key regulating services: carbon storage increased by 6.9 × 10¹² gC while soil conservation rose by 4.8 × 10⁸ t. Concurrently, regional habitat quality surged by 45% in mean scores, and food production increased by 2.1 × 10⁵ t. Critically, synergistic relationships between habitat quality, soil retention, and carbon storage were progressively strengthened, whereas trade-offs between food production and habitat quality intensified. Further analysis revealed that four distinct ESBs—the Agricultural Production Bundle (APB), Urban Development Bundle (UDB), Eco-Agriculture Transition Bundle (ETB), and Ecological Protection Bundle (EPB)—were shaped by slope, forest cover ratio, population density, and GDP. Notably, 38% of the ETB transformed into the EPB, with frequent spatial interactions observed between the APB and UDB. These findings underscore that future ecological restoration and conservation efforts should implement coordinated, multi-service management mechanisms. Full article

Water infiltration into soil is a key process in regulating the hydrological cycle and sustaining ecosystem services in high-Andean environments. However, limited information is available regarding its dynamics in these ecosystems. This study evaluated the influence of three types of vegetation cover and soil properties on water infiltration in a high-Andean environment. A double-ring infiltrometer, the Water Drop Penetration Time (WDPT, s) method, and laboratory physicochemical characterization were employed. Soils under forest cover exhibited significantly higher quasi-steady infiltration rates (i_s, 0.248 ± 0.028 cm·min⁻¹) compared to grazing areas (0.051 ± 0.016 cm·min⁻¹) and agricultural lands (0.032 ± 0.013 cm·min⁻¹). Soil organic matter content was positively correlated with i_s. The modified Kostiakov infiltration model provided the best overall fit, while the Horton model better described infiltration rates approaching i_s. Sand and clay fractions, along with K⁺, Ca²⁺, and Mg²⁺, were particularly significant during the soil’s wet stages. In drier stages, increased Na⁺ concentrations and decreased silt content were associated with higher water repellency. Based on WDPT, agricultural soils exhibited persistent hydrophilic behavior even after drying (median [IQR] from 0.61 [0.38] s to 1.24 [0.46] s), whereas forest (from 2.84 [3.73] s to 3.53 [24.17] s) and grazing soils (from 4.37 [1.95] s to 19.83 [109.33] s) transitioned to weakly or moderately hydrophobic patterns. These findings demonstrate that native Andean forest soils exhibit a higher infiltration capacity than soils under anthropogenic management (agriculture and grazing), highlighting the need to conserve and restore native vegetation cover to strengthen water resilience and mitigate the impacts of land-use change. Full article

Against the backdrop of rapid urbanization in western China, which has triggered remarkable land-use changes and habitat degradation, Chengdu, as a developed city in China, plays a demonstrative and leading role in the economic and social development of China during the transition period. Therefore, integrated modeling approaches are required to balance development and conservation. This study responds to this need by conducting a scenario-based assessment of urbanization-induced land-use changes and regional habitat quality dynamics in Chengdu (1990–2030), using the FLUS-InVEST model. By integrating remote sensing-derived land-use data from 1990, 1995, 2000, 2005, 2010, 2015, and 2020, we simulate future regional habitat quality under three policy scenarios: natural development, ecological priority, and cropland protection. Key findings include the following: (1) From 1990 to 2020, cropland decreased by 1917.78 km², while forestland and built-up areas increased by 509.91 km² and 1436.52 km², respectively. Under the 2030 natural development scenario, built-up expansion and cropland reduction are projected. Ecological priority policies would enhance forestland (+4.2%) but slightly reduce cropland. (2) Regional habitat quality declined overall (1990–2020), with the sharpest drop (ΔHQ = −0.063) occurring between 2000 and 2010 due to accelerated urbanization. (3) Scenario analysis reveals that the ecological priority strategy yields the highest regional habitat quality (HQ_mean = 0.499), while natural development results in the lowest (HQ_mean = 0.444). This study demonstrates how the FLUS-InVEST model can quantify the trade-offs between urbanization and regional habitat quality, offering a scientific framework for balancing development and ecological conservation in rapidly urbanizing regions. The findings highlight the effectiveness of ecological priority policies in mitigating habitat degradation, with implications for similar cities seeking sustainable land-use strategies that integrate farmland protection and forest restoration. Full article

Invasive plant species pose an increasing threat to mangroves globally. This study assessed the impact of Paspalum vaginatum invasion on carbon loss and early recovery following four years of restoration in a mangrove forest with Rhizophora racemosa in Benin. Organic carbon was quantified in the total biomass, including both aboveground and belowground components, as well as in the soil to a depth of −50 cm. In addition, soil gas fluxes of CO₂, CH₄, and N₂O were measured. Three sites were evaluated: a conserved mangrove, a site degraded by P. vaginatum, and the same site post-restoration via hydrological rehabilitation and reforestation. Invasion significantly reduced carbon storage, especially in soil, due to lower biomass, incorporation of low C/N ratio organic residues, and compaction. Restoration recovered 7.8% of the total biomass carbon compared to the conserved mangrove site, although soil organic carbon did not rise significantly in the short term. However, improvements in deep soil C/N ratios (15–30 and 30–50 cm) suggest enhanced soil organic matter recalcitrance linked to R. racemosa reforestation. Soil CO₂ emissions dropped by 60% at the restored site, underscoring restoration’s potential to mitigate early carbon loss. These results highlight the need to control invasive species and suggest that restoration can generate additional social benefits. Full article

The Qinghai–Tibetan Plateau (QTP), often referred to as the “Third Pole” of the world, harbors alpine grassland ecosystems that play an essential role as global carbon sinks, helping to mitigate the pace of climate change. Nonetheless, alterations in natural environmental conditions coupled with escalating human activities have disrupted the seasonal growth cycles of grasslands, thereby intensifying degradation processes. To date, the key drivers and lifecycle dynamics of Grassland Depletion across the QTP remain contentious, limiting our comprehension of its ecological repercussions and regulatory mechanisms. This study comprehensively investigates grassland degradation on the Qinghai–Tibetan Plateau, analyzing its drivers and changes in ecological suitability during the growing season. By integrating natural factors (e.g., precipitation and temperature) and anthropogenic influences (e.g., population density and grazing intensity), it examines observational data from over 160 monitoring stations collected between the 1980s and 2020. The findings reveal three distinct phases of grassland degradation: an acute degradation phase in 1990 (GDI, Grassland Degradation Index = 2.53), a partial recovery phase from 1996 to 2005 (GDI < 2.0) during which the proportion of degraded grassland decreased from 71.85% in 1990 to 51.22% in 2005, and a renewed intensification of degradation after 2006 (GDI > 2.0), with degraded grassland areas reaching 56.39% by 2020. Among the influencing variables, precipitation emerged as the most significant driver, interacting closely with anthropogenic factors such as grazing practices and population distribution. Specifically, the combined impacts of precipitation with population density, grazing pressure, and elevation were particularly notable, yielding interaction q-values of 0.796, 0.767, and 0.752, respectively. Our findings reveal that while grasslands exhibit superior carbon sink potential relative to forests, their productivity and ecological functionality are undergoing considerable declines due to the compounded effects of multiple interacting factors. Consequently, the spatial distribution of ecologically suitable zones has contracted significantly, with the remaining high-suitability regions concentrating in the “twin-star” zones of Baingoin and Zanda grasslands, areas recognized as focal points for future ecosystem preservation. Furthermore, the effects of climate change and intensifying anthropogenic activity have driven the reduction in highly suitable grassland areas, shrinking from 41,232 km² in 1990 to 24,485 km² by 2020, with projections indicating a further decrease to only 2844 km² by 2060. This study sheds light on the intricate mechanisms behind Grassland Depletion, providing essential guidance for conservation efforts and ecological restoration on the QTP. Moreover, it offers theoretical underpinnings to support China’s carbon neutrality and peak carbon emission goals. Full article

This study aimed to predict the potential habitats of Luciola unmunsana using a species distribution model (SDM). Luciola unmunsana is an endemic species that lives only in South Korea, and because its females do not have genus wings and are less fluid, it is difficult to collect, so research related to its distribution and restoration is relatively understudied. Therefore, this study predicted the potential habitats of Luciola unmunsana across South Korea using the single model Maximum Entropy (MaxEnt) and a multi-model ensemble model to prepare basic data necessary for a conservation and habitat restoration plan for the species. A total of 39 points of occurrence were built based on public data and prior research from the Jeonbuk Green Environment Support Center (JGESC), the Global Biodiversity Information Facility (GBIF), and the National Institute of Biological Resources (NIBR). Among the input variables, climate variables were based on the shared socioeconomic pathway (SSP) scenario-based ecological climate index, while nonclimate variables were based on topography, land cover maps, and the Enhanced Vegetation Index (EVI). The main findings of this study are summarized below. First, in predicting Luciola unmunsana potential habitats, the EVI, water network analysis, land cover, and annual precipitation (Bio12) were identified as good predictors in both models. Accordingly, areas with high vegetation activity in their forests, adjacent to water resources, and stable humidity were predicted as potential habitats. Second, by overlaying the predicted potential habitats and highly significant variables, we found that areas with high vegetation vigor within their forests, proximity to water systems, and relatively high annual precipitation, which can maintain stable humidity, are potential habitats for Luciola unmunsana. Third, literature surveys used to predict potential habitat sites, including Geumsan-gun, Chungcheongnam-do, Yeongam-gun, Jeollabuk-do, Mudeungsan Mountain, Gwangju-si, Korea, and Gijang-gun, Busan-si, Korea, confirmed the occurrence of Luciola unmunsana. This study is significant in that it is the first to develop a regional SDM for Luciola unmunsana, whose population is declining due to urbanization. In addition, by applying various environmental variables that reflect ecological characteristics, it contributes to more accurate predictions of the potential habitats of this species. The predicted results can be used as basic data for the future conservation of Luciola unmunsana and the establishment of habitat restoration strategies. Full article

Typhoons are major climate disturbances that significantly impact coastal ecosystems, particularly mangrove forests. This study examines the effects of typhoons on mangrove communities at different stages of recovery, focusing on how environmental factors influence carbon storage and net ecosystem exchange (NEE). Three mangrove sites were selected based on their recovery age: young, moderately restored, and mature. The results revealed that typhoons had the most pronounced effect on young mangroves, resulting in significant reductions in both above-ground and soil carbon storage. In contrast, mid-aged and mature mangroves demonstrated greater resilience, with mature mangroves recovering most rapidly in terms of community structure and carbon storage. Key factors such as wind speed, heavy rainfall, and changes in photosynthetically active radiation (PAR) contributed to carbon storage losses, particularly in young mangrove forests. This study underscores the importance of recovery age in determining mangrove resilience to extreme weather events and offers insights for enhancing restoration and conservation strategies to mitigate the impacts of climate change on coastal carbon sequestration. Full article

Over the past few decades, occurrences of extreme climatic events have escalated significantly, with severe repercussions for global ecosystems and socio-economics. northern China (NC), characterized by its complex topography and diverse climatic conditions, represents a typical ecologically vulnerable region where vegetation is highly sensitive to climate change. Therefore, monitoring vegetation dynamics and analyzing the influence of extreme climatic events on vegetation are crucial for ecological conservation efforts in NC. Based on extreme climate indicators and the Normalized Difference Vegetation Index (NDVI), this study employed trend analysis, Ensemble Empirical Mode Decomposition, all subsets regression analysis, and random forest to quantitatively investigate the spatiotemporal variations in historical and projected future NDVI trends in NC, as well as their responses to extreme climatic conditions. The results indicate that from 1982 to 2018, the NDVI in NC generally exhibited a recovery trend, with an average growth rate of 0.003/a and a short-term variation cycle of approximately 3 years. Vegetation restoration across most areas was primarily driven by short-term high temperatures and long-term precipitation patterns. Future projections under different emission scenarios (SSP245 and SSP585) suggest that extreme climate change will continue to follow historical trends. However, increased radiative forcing is expected to constrain both the rate of vegetation growth and its spatial expansion. These findings provide a scientific basis for mitigating the impacts of climate anomalies and improving ecological quality in NC. Full article

Mediterranean subtidal reefs host ecologically significant habitats, including forests of Cystoseira spp., which form complex benthic communities within the photic zone. These habitats are increasingly degraded due to climate change, invasive species, and anthropogenic pressures, particularly in the eastern Mediterranean. In support of habitat monitoring under the EU Natura 2000 directive and the Nature Restoration Regulation, this study investigates the utility of high-resolution satellite remote sensing for mapping subtidal brown algae and associated benthic classes. Using imagery from the SuperDove sensor (Planet Labs, San Francisco, CA, USA), we developed an integrated mapping workflow at the Natura 2000 site GR2420009. Aquatic reflectance was derived using ACOLITE v.20250114.0, and both supervised classification and spectral unmixing were implemented in the EnMAP Toolbox v.3.16.3 within QGIS. A Random Forest classifier (100 fully grown trees) achieved high thematic accuracy across all habitat types (F1 scores: 0.87–1.00), with perfect classification of shallow soft bottoms and strong performance for Cystoseira s.l. (F1 = 0.94) and Seagrass (F1 = 0.93). Spectral unmixing further enabled quantitative estimation of fractional cover, with high predictive accuracy for deep soft bottoms (R² = 0.99; RPD = 18.66), shallow soft bottoms (R² = 0.98; RPD = 8.72), Seagrass (R² = 0.88; RPD = 3.01) and Cystoseira s.l. (R² = 0.82; RPD = 2.37). The lower performance for rocky reefs with other cover (R² = 0.71) reflects spectral heterogeneity and shadowing effects. The results highlight the effectiveness of combining classification and unmixing approaches for benthic habitat mapping using CubeSat constellations, offering scalable tools for large-area monitoring and ecosystem assessment. Despite challenges in field data acquisition, the presented framework provides a robust foundation for remote sensing-based conservation planning in optically shallow marine environments. Full article

Coastal forests in Bangladesh provide various essential ecosystem services. However, these face severe threats from deforestation, land-use changes, and climate change. Understanding community perceptions of these services and their willingness to support restoration is crucial for effective conservation strategies. To analyze these, this study employs machine learning on survey data collected from Chakaria and Moheshkhali Upazilas of Cox’s Bazar District. Gradient Boosting Machine (GBM) model was used to identify key predictors of restoration willingness and compared with Random Forest (RF) and Generalized Linear Model (GLM). Proximity to forests shapes community priorities with stronger support for restoration among those living near the forest. Higher perception levels were linked to various ecosystem services provided by the forest, while forest dependence, age, and education also influenced perception with education and age showing strong negative correlations. The GBM model outperformed RF and the GLM in predicting restoration willingness due to its ability to capture complex relationships. The perceived importance of provisioning and supporting services and restoration awareness influenced willingness, accounting for 55.56% of the variation. Willingness was also shaped by income, forest dependency and awareness. Overall, this study leverages machine learning to align conservation efforts with socio-economic priorities, ensuring the resilience of Bangladesh’s coastal ecosystems. Full article

Mangrove forests serve as critical ecological barriers in coastal zones and play a vital role in global blue carbon sequestration strategies. In recent decades, China’s mangrove ecosystems have experienced complex interactions between degradation and restoration under intense coastal urbanization and systematic conservation efforts. However, the long-term spatiotemporal patterns and driving mechanisms of mangrove ecosystem health changes remain insufficiently quantified. This study developed a multi-temporal analytical framework using Landsat imagery (1986–2021) to derive kernel normalized difference vegetation index (kNDVI) time series—an advanced phenological indicator with enhanced sensitivity to vegetation dynamics. We systematically characterized mangrove growth patterns along China’s southeastern coast through integrated Theil–Sen slope estimation, Mann–Kendall trend analysis, and Hurst exponent forecasting. A Deep Forest regression model was subsequently applied to quantify the relative contributions of environmental drivers (mean annual sea surface temperature, precipitation, air temperature, tropical cyclone frequency, and relative sea-level rise rate) and anthropogenic pressures (nighttime light index). The results showed the following: (1) a nationally significant improvement in mangrove vitality (p < 0.05), with mean annual kNDVI increasing by 0.0072/yr during 1986–2021; (2) spatially divergent trajectories, with 58.68% of mangroves exhibiting significant improvement (p < 0.05), which was 2.89 times higher than the proportion of degraded areas (15.10%); (3) Hurst persistence analysis (H = 0.896) indicating that 74.97% of the mangrove regions were likely to maintain their growth trends, while 15.07% of the coastal zones faced potential degradation risks; and (4) Deep Forest regression id the relative rate of sea-level rise (importance = 0.91) and anthropogenic (nighttime light index, importance = 0.81) as dominant drivers, surpassing climatic factors. This study provides the first national-scale, 30 m resolution assessment of mangrove growth dynamics using kNDVI, offering a scientific basis for adaptive management and blue carbon strategies in subtropical coastal ecosystems. Full article

Inner Mongolia, a typical arid and semi-arid region in northern China, has undergone significant ecological transformation over the past two decades through climate shifts and large-scale ecological restoration projects. However, the relative contributions of climate and anthropogenic drivers to these ecological changes have not been sufficiently quantified. This study presents a comprehensive quantitative evaluation of the relative contributions of climate change, land conversion, and ecological management to changes in four critical ecosystem services—carbon sequestration, hydrological regulation, soil and water conservation, and windbreak and sand fixation—between 2001 and 2020. Using the residual trend method—a technique to separate climate-driven from human-induced effects—we further decomposed human influence into land conversion and management components. The results show that climate change was the primary driver, enhancing carbon sequestration and hydrological regulation but negatively impacting erosion control, with contributions often over 90%. In contrast, human activities had more spatially variable effects; while land conversion improved several services, it also heightened the vulnerability of sand fixation functions. The analysis further revealed ecosystem-type-specific responses, where grasslands and deserts responded better to management measures and forests and croplands showed greater improvements from land conversion. These findings offer crucial insights into the differentiated mechanisms and outcomes of ecological interventions, providing a scientific basis for optimizing restoration strategies and achieving sustainable ecosystem governance in climate-sensitive regions. Full article