Search Results (170)

Marine ecological assets (MEAs) comprise habitats, living resources, and ecosystem services and are globally fundamental to biodiversity conservation, climate regulation, and sustainable development. However, the establishment of systematic frameworks for MEA definition, classification, and valuation faces considerable conceptual and methodological challenges, particularly in rapidly industrializing nations with urgent marine conservation priorities. We reviewed the theoretical evolution, methodological development, and practical implementation of MEA accounting in China and propose an integrated framework that bridges conceptual gaps and supports evidence-based policy for sustainable marine governance. Our comprehensive analysis covers domestic and international literature, policy documents, technical standards, and case studies. We developed a definition that incorporates ownership attributes and dynamic management elements, and constructed a three-in-one classification system that integrates resource characteristics, ecological functions, and governance needs from existing international frameworks adapted to the governance context in China. We identified seven multidimensional MEA attributes and systematically evaluated mainstream valuation methods (market-based, alternative market, and hypothetical market approaches) across different marine ecosystem types (e.g., estuaries, coral reefs, mangrove forests). The review provides a coherent theoretical foundation for advancing MEA accounting in China and offers practical pathways for integrating accounting outcomes into policy mechanisms such as ecological compensation, blue carbon trading, and marine spatial planning. Our framework contributes to the operationalization of the philosophy that “lucid waters and lush mountains are invaluable assets” in marine governance and may provide preliminary insights for other nations developing MEA capital accounts to achieve sustainable development goals, although cross-national comparative validation is necessary to assess applicability beyond the Chinese context. Full article

As coastal communities face escalating climate risks driven by climate change and biodiversity loss, integrating mangrove ecosystems into sustainability-oriented governance frameworks spanning ecological conservation, climate adaptation, and natural capital accounting has become a global priority. However, quantifying their protection values based on spatiotemporal shoreline dynamics under extreme disturbance remains challenging. Focusing on Dongzhai Harbor (China), this study integrates multi-temporal remote sensing (2010–2021), shoreline evolution analysis, and the Replacement Cost Method to assess ecosystem resilience against Super Typhoon Rammasun in 2014. Results show mangroves exhibited substantial post-disturbance resilience, with only 6.10% area loss following Typhoon Rammasun and 46% natural recovery within six years. Bootstrap confidence intervals for the mangrove-shoreline association overlapped zero across all three temporal periods, indicating that the observational data do not support a statistically confirmed causal protection effect at the landscape scale. This finding underscores that spatially co-occurring ecosystem services do not automatically imply causation, reinforcing the need for empirically grounded valuation in sustainable land-use planning. Because mangroves naturally establish in sheltered environments, the observed spatial overlap between mangroves and the shoreline cannot be interpreted as direct evidence of causal shoreline stabilization. Based on this framework, the potential protection value reached 907.65 × 10⁴ CNY yr⁻¹ across 32.57 km of weighted coastline aligned with mangroves. Notably, erosional segments contributed 50.5% of this value despite comprising only 27.3% of the length, indicating that the replacement-cost estimate is concentrated in erosional segments under the assumed parameters. While acknowledging the need for local biophysical validation and uncertainty analysis in scaling, these findings support integrating dynamic nature-based solutions into territorial planning and Gross Ecosystem Product accounting. The resulting valuation framework offers a replicable pathway for advancing multi-dimensional sustainability encompassing climate-adaptive coastal governance, natural capital integration, and evidence-based coastal spatial planning. Full article

Mangrove ecosystems provide critical coastal protection, biodiversity support, and carbon storage, yet they remain vulnerable to degradation caused by coastal development, pollution, and climate-related pressures. This study monitors mangrove dynamics in Al-Birk, Asir Region, Saudi Arabia, using Google Earth Engine (GEE), multi-temporal Landsat imagery, spectral indices, and Random Forest (RF) classification. Landsat imagery from 2016 to 2021 was processed to derive NDVI, MSAVI2, EVI, and NDWI, and supervised RF classification was applied to map annual mangrove extent and associated land-cover classes. The RF classifier achieved an overall accuracy of 92.5% and a Kappa coefficient of 0.89. Results indicate that classified mangrove extent increased from approximately 1069 ha in 2016 to 1540 ha in 2021, representing a net gain of 471 ha and a 44% increase over the study period. A localized decline was detected between 2020 and 2021, indicating spatially uneven vegetation dynamics. The findings provide a spatial baseline for monitoring mangrove change and supporting coastal conservation planning in Saudi Arabia. While the detected expansion is temporally consistent with ongoing restoration initiatives, the study does not establish direct causality between policy interventions and observed spatial changes. Full article

The Con Dao archipelago hosts the oldest MPA in Vietnam and is recognized as a regional marine biodiversity hotspot. Here, we applied environmental DNA (eDNA) metabarcoding to assess coastal fish diversity across four major habitat types: coral reefs, seagrass beds, mangroves, and a harbour in the Con Dao archipelago. Using MiFish-U 12S primers at eight stations, we detected 282 operational taxonomic units, corresponding to 144 fish taxa. Fish assemblages exhibited strong habitat structuring: community composition differed markedly among habitats, with minimal overlap. Only three species were shared across all habitats. Multivariate analyses confirmed that habitat type, rather than spatial distance among sites, was the primary driver of community differentiation. Mangrove and seagrass supported distinct assemblages that were underrepresented in existing species checklists and MPA management frameworks. Notably, eDNA detected cryptic and non-commercial species overlooked by conventional survey methods. These results substantially expand the known fish diversity of the Con Dao Archipelago and highlight the need to incorporate habitat heterogeneity, particularly non-reef ecosystems, into MPA design and monitoring. Although eDNA metabarcoding is subject to amplification biases and limited taxonomic resolution in reference databases, it offers a powerful complement to traditional surveys for characterizing under-sampled habitats. Full article

Mangroves are crucial for biodiversity conservation, coastal protection, and supporting local livelihoods. Mangroves may also protect coasts from storms and rising sea levels and can play a major role in climate mitigation. Threats to their health include activities such as infrastructural development, urban encroachment, aquaculture and crop farming, and oil and gas exploration. We review the threats and opportunities for the restoration of mangrove ecosystems on the coasts of Africa, which are highly impacted by oil spills. The most important challenge for mangrove restoration identified in this review is the restoration of appropriate hydrologic and salinity regimes prior to natural recruitment or the active planting of propagules. Full article

Mangrove extent has increased in many regions under strengthened conservation policies and large-scale restoration programs. Nevertheless, mangrove ecosystems continue to face multiple pressures, including limited total area, habitat degradation, biodiversity decline, and biological invasion, and localized deterioration in ecosystem structure and function has been increasingly reported. Despite extensive mapping efforts, the spatiotemporal dynamics of mangrove degradation—particularly in tidally influenced environments—remain insufficiently understood. Focusing on the Nanliu River Delta, the largest deltaic mangrove system in the Northern Beibu Gulf of China, this study integrates long-term Landsat time-series imagery (1990–2025) with deep learning to quantify both mangrove extent change and canopy degradation. To mitigate tidal inundation effects, a NDVI Pseudo-P75 compositing strategy was applied using Google Earth Engine (GEE), enabling consistent observation of mangrove canopies across tidal stages. Global Mangrove Watch v4 (GMW-V4) and HGMF2020 mangrove dataset for China were used as reference labels to train a ResNet34–UNet segmentation framework incorporating Digital Elevation Model (DEM) constraints. The model achieved high classification performance, with an IoU of 0.822 for mangroves and 0.981 for background, yielding a mean IoU of 0.902. The resulting maps, following manual verification, provided a robust basis for spatiotemporal and degradation analyses. Canopy condition was further assessed using the Enhanced Vegetation Index (EVI), which is less prone to saturation in high-biomass mangrove stands. Results show that mangrove area in the Nanliu River Delta expanded from 266 ha in 1990 to 1414 ha in 2025, with the annual expansion rate after 2005 being nearly seven times higher than that before 2005. Despite this net gain, a cumulative loss of 347.45 ha was recorded, primarily during 1990–2000, with approximately 70% converted to aquaculture and coastal engineering. Spatial analysis revealed that mangrove expansion occurred predominantly seaward, whereas both mangrove loss and canopy degradation exhibited an inverse J-shaped relationship with seawall proximity. More than 80% of mangrove loss occurred within 200 m of seawalls, indicating concentrated anthropogenic encroachment, while 75.6% of canopy degradation was observed within 350 m, potentially reflecting landward forest senescence. These results indicate a transition in dominant threats from permanent land conversion in the late 20th century to more subtle, internal functional degradation in recent decades, underscoring the need to complement extent-based assessments with canopy condition monitoring in mangrove conservation and management. Full article

Nature-based Solutions (NbS) have emerged as transformative approaches to address societal challenges, support biodiversity, and enhance human well-being. Globally, NbS are recognized for their potential to mitigate climate change impacts such as coastal flooding. Despite growing policy interest, limited empirical evidence exists on their real-world effectiveness, particularly in Africa. The core objective of this study was to evaluate how community perceptions, awareness, and demographic factors influence the acceptance and effectiveness of NbS for flood risk reduction in selected coastal communities of Rivers State, Nigeria. Specifically, it aimed to assess community perceptions and awareness of NbS, identify demographic, geographic, and psychosocial factors influencing these perceptions, and analyze how risk perception and local knowledge affect acceptance. The study addressed three key questions: (1) How do community perceptions affect NbS acceptance and implementation? (2) What factors shape awareness and understanding of NbS in Kula, Oyorokoto, and Bonny? (3) How do perceptions vary across demographic groups? To answer these, a structured survey of 1224 respondents was conducted: 61% were male and 39% female, with most aged 31–50 years (80%). Education emerged as a key factor—about 49% of respondents had at least secondary or post-secondary education, which showed a significant link with positive perceptions of NbS (χ² = 460.98, p < 0.001, Cramer’s V = 0.434). Occupation also shaped views: traders (36.8%) and fishers (24.5%) formed the majority, with occupational patterns showing moderate influence (χ² = 112.68, p < 0.001, Cramer’s V = 0.215). Overall, awareness was the strongest predictor, with communities reporting higher NbS awareness demonstrating significantly greater acceptance (OR = 0.06, p < 0.001). These findings highlight that targeted awareness-raising, education, and community engagement are critical to promoting mangrove conservation, afforestation, and ecosystem restoration, ultimately strengthening resilience to climate-induced risks in coastal communities. Full article

Palynological analysis of seventy-seven cutting samples from six boreholes in the Marañón Basin (northeastern Peru) has identified five distinct Neogene marine incursion events (ME-1 to ME-5), challenging existing models that depict them as short-lived episodes. The diverse palynological assemblages, comprising spores, pollen, freshwater algae, and critical marine indicators—including dinoflagellate cysts, foraminiferal test linings, and copepod eggs—reveal that these incursions were protracted and recurrent, each associated with a maximum flooding surface and bounded by intervals of continental sedimentation. The stratigraphic record shows the earliest event ME-1 (Aquitanian to Late Burdigalian, 23.03–17.7 Ma) identified across all studied wells. ME-2 (latest Burdigalian to Middle Langhian, 17.0–16.1 Ma) is also recorded basin-wide. ME-3 (latest Burdigalian to earliest Langhian 16.5–15.7 Ma) registered in two wells. ME-4 (Late Langhian to latest Serravallian, 14.6–11.62 Ma) registered in only two wells and ME-5 (Early Tortonian, 11.6–10 Ma) is documented exclusively in the southernmost well, culminating in Zanclean (~5.5–3.6 Ma) mangrove development. We interpret the ingress routes for ME-1 to ME-3 to be westward via the Marañón Portal or northward from the Caribbean, associating them with the Proto-Pebas and Pebas systems. In contrast, ME-4 would also be from Amazon trunk or Paraná Portal associated with the Pebas Phase, and ME-5 likely originated from the south through the Paraná Portal, linking it to the Acre Phase. These results demonstrate that Miocene marine incursions into western Amazonia were not brief episodes but represented prolonged periods of marine influence, facilitated by sustained subsidence in the Marañón retro-arc foreland basin. This history reveals a dynamic connectivity throughout the Neogene, with marine conditions acting as persistent biogeographic barriers that critically shaped the region’s Miocene biodiversity patterns. This refined chronology provides a comprehensive regional framework, significantly advancing our understanding of Amazonian paleogeography. Full article

Monitoring the α-biodiversity indicators of mangrove forests and understanding their spatiotemporal trends can guide mangrove restoration strategies. Taking Qinglan Port in Hainan Province, China, as our study area, we compared multiple machine learning methods to predict the spatial distribution of α-biodiversity indicator Shannon’s diversity index (SHDI) by integrating LiDAR points and Worldview-2 images. In addition, the relationship between mangrove forests’ SHDI values and growth years was analyzed. The study extracted 28 spectral features and 99 LiDAR features from Worldview-2 and LiDAR data, respectively. The RReliefF method was adopted to select informative features. Four machine learning methods, including support vector machines (SVMs), extreme gradient boosting (XGBoost), deep neural networks (DNNs), and Gaussian process regression (GPR), were used to establish SHDI prediction models. The leave-one-out cross-validation (LOOCV) method was used to evaluate prediction accuracy, and the optimal model was adopted to generate a spatial map of SHDI. Based on Google Earth and Worldview-2 images, the spatial regions of mangrove forests in 2008, 2013, 2018, and 2023 were identified. The SHDI values within different restoration periods were statistically analyzed by using the mangroves’ spatiotemporal distributions. The results showed that RReliefF selected a total of 30 features, including 13 spectral features and 17 LiDAR features. Using preferred features, GPR had the highest prediction accuracy, with an LOOCV R² of 0.51, followed by SVM (R² = 0.44) and DNN (R² = 0.32); the accuracy of XGBoost (R² = 0.29) was relatively poor. The increased areas of rehabilitated mangrove forests in the periods of 2008–2013, 2013–2018, and 2018–2023 were 0.31 km², 0.13 km², and 1.35 km², respectively. Mangroves growing before 2008 owned the highest mean SHDI value of 0.74, followed by mangroves in 2008–2013 and 2013–2018; mangrove forests restored in 2018–2023 had the lowest mean SHDI value of 0.63. The results indicated that mangrove SHDI can be predicted by integrating LiDAR and Worldview-2. The mangrove population exhibited more diverse α-biodiversity characteristics as growth time increased. In subsequent mangrove restoration processes, planting mangroves of diverse species is beneficial to ensure the stability of the mangrove community. Full article

Understanding the services provided by coastal ecosystems is vital for their study, preservation, and restoration. Mangrove forests, in particular, provide key ecosystem services: they sequester carbon, support fisheries and biodiversity, and facilitate sustainable tourism. In the Caribbean and the Gulf of Mexico, mangrove-related services have been studied extensively, but often via fragmented approaches. This meta-analysis combines a literature review, bibliometric tools, and thematic mapping to identify emerging trends and long-standing gaps. We analyzed 61 peer-reviewed studies across 21 sovereign states and U.S. states, which highlighted shifting research priorities and a lack of convergence—defined herein as the failure of individual studies to examine multiple ecosystem service categories (regulating, cultural, supporting, and provisioning) simultaneously to assess potential trade-offs. While early research emphasized supporting services such as fishery nurseries, recent studies focus on regulating services, especially carbon sequestration. Stakeholder engagement remains limited, with only 18% of studies incorporating local perspectives. We argue for greater integration of stakeholder input and convergence across service categories to enhance the scientific basis for mangrove management and policy design. Full article

Accurate estimation of tree biomass and volume is essential for sustainable forest management, climate change mitigation, and ecosystem service assessment. Recent advances in unmanned aerial vehicle (UAV) technology enable the acquisition of ultra-high-resolution optical and three-dimensional data, providing a resource-efficient alternative to traditional field-based inventories. This review synthesizes 181 peer-reviewed studies on UAV-based estimation of tree biomass and volume across forestry, agricultural, and urban ecosystems, integrating bibliometric analysis with qualitative literature review. The results reveal a clear methodological shift from early structure-from-motion photogrammetry toward integrated frameworks combining three-dimensional canopy metrics, multispectral or LiDAR data, and machine learning or deep learning models. Across applications, tree height, crown geometry, and canopy volume consistently emerge as the most robust predictors of biomass and volume, enabling accurate individual-tree and plot-level estimates while substantially reducing field effort and ecological disturbance. UAV-based approaches demonstrate particularly strong performance in orchards, plantation forests, and urban environments, and increasing applicability in complex systems such as mangroves and mixed forests. Despite significant progress, key challenges remain, including limited methodological standardization, insufficient uncertainty quantification, scaling constraints beyond local extents, and the underrepresentation of biodiversity-rich and structurally complex ecosystems. Addressing these gaps is critical for the operational integration of UAV-derived biomass and volume estimates into sustainable land management, carbon accounting, and climate-resilient monitoring frameworks. Full article

As an essential blue carbon ecosystem, mangroves play a vital role in coastal protection, biodiversity conservation, and climate regulation. However, their complex and variable growth environments pose challenges for precise monitoring. Hainan Island represents a region within China where mangrove forests are the most concentrated and diverse in type. In recent years, ecological restoration efforts have led to the recovery of their coverage areas. This study analyzed the spatial distribution, canopy height, and aboveground carbon storage variations in Hainan mangrove forests. Deep-learning and multiple machine-learning algorithms were used to integrate multitemporal Sentinel-2 remote sensing imagery from 2019 to 2023 with unmanned aerial vehicle observations and field survey data. Multi-rule image fusion and deep-learning techniques effectively enhanced mangrove identification accuracy. The mangrove classification achieved an overall accuracy exceeding 90%. The mangrove area in Hainan increased from 3948.83 ha in 2019 to 4304.29 ha in 2023. Gradient-boosted decision tree (GBDT) models estimated average canopy height with a high coefficient of determination (R² = 0.89), and Random Forest (RF) models yielded the best estimations of total above-ground carbon stock with strong agreement to field observations. Integrating multisource remote sensing data with artificial intelligence algorithms enabled high-precision dynamic monitoring of mangrove distribution, structure, and carbon storage to provide scientific support for the assessment, management, and carbon sink accounting of Hainan mangrove ecosystems. Full article

Mangrove ecosystems along the Indian Ocean coast show great biodiversity, adapting to harsh environmental conditions of high salinity and higher organic matter, and they are a host for a range of microbial communities with special features that produce unique secondary metabolites. Of this, mangrove-associated endophytic fungi, the second largest ecological group of marine fungi, show the greater potential, being a diverse pool for discovering novel bio-actives with pharmacological and biotechnological interest. This review summarizes the research findings on structural diversity and the associated pharmacological activities of secondary metabolites produced by mangrove-associated fungi along the Indian Ocean coast reported over the period of 2002–2025, based on the literature retrieved from Google Scholar. The total of 302 secondary metabolites is presented mainly from classes of polyketides (208), alkaloids (34), and terpenoids (60). Interestingly, 164 compounds were identified, as first reported in those publications. These compounds have been reported to show diverse biological activities, and the most prominent activities are cytotoxic, antibacterial, antifungal, antioxidant, enzyme inhibitory, and anti-inflammatory effects. The structural novelty and pharmacological activities of these metabolites highlight the importance of mangrove fungi as promising sources for new drug discovery and advancing industrial biotechnology. Therefore, this review highlights the insight into the possible application of these chemical compounds in the future drug industry, as well as in biotechnology for advancing human well-being. Furthermore, though significant progress has been made in exploring the fungi community from mangroves of the African and Middle Eastern coasts, the Indian coast mangrove fungi are yet to be explored more for novel discoveries. Full article

Mangrove ecosystems underpin coastal livelihoods and biodiversity in Mozambique, yet gendered patterns of resource use and their implications for management remain underexplored. This study explores how artisanal fishing and shellfish collection differ between men and women on Inhaca Island (Maputo Bay), focusing on how these gender-specific practices shape livelihood outcomes, spatial use of mangroves, and perceptions of ecological change. To address this question, we combined structured interviews (n = 35; 51.4% men, 48.6% women) and camera-trap monitoring in two mangrove areas during September 2024 to document fishing practices, catch characteristics, spatial patterns, and ecological perceptions. We found pronounced gendered divisions of labor and space use: men, using boats and nets, harvested a median of 15 kg of fish per day for commercial sale, generating cash income, whereas women collected a median of 3 kg of shellfish by hand, primarily for household consumption. Camera traps confirmed pronounced spatial segregation in mangrove use: women foraged in targeted areas, and men traversed broader zones, both synchronizing their activities with tidal and daylight cycles. By integrating social and ecological data, the study revealed nuanced gender roles and resource pressures, with 82.9% of participants reporting declines in fish and shellfish stocks, emphasizing mangroves’ critical role in livelihoods, biodiversity, and climate resilience. Our findings highlight the value of mixed-method approaches for understanding socio-ecological dynamics and advocate for gender-sensitive conservation policies, strengthened Community Fisheries Councils, and infrastructure investments to regulate resource use, enhance mangrove management, and promote equitable livelihoods in Mozambique’s coastal communities. Full article

China’s coastal wetlands play a crucial role in maintaining biodiversity and providing essential ecosystem services. However, the absence of high-resolution wetland type maps poses substantial challenges for effective conservation and management. This study proposes a two-step classification framework that integrates pixel-based Random Forest algorithms with object-based hierarchical decision trees, utilizing Landsat-8 time-series imagery to generate a detailed wetland map comprising 10 wetland types and 5 non-wetland categories. The results reveal distinct spatial patterns along China’s coastline: freshwater wetlands and riverine systems dominate the northern regions, whereas southern coastal zones feature extensive tidal flats, aquaculture ponds, and mangrove ecosystems. The proposed method achieved an overall accuracy of 89.76% and a Kappa coefficient of 0.891, demonstrating its effectiveness for large-scale wetland mapping. This study provides robust technical support for the sustainable conservation and ecological management of coastal wetlands. Full article