Search Results (383)

Tropical rainforests play a vital role in maintaining global ecological balance, carbon cycling, and biodiversity conservation, making research on their biomass dynamics scientifically significant. This study integrates multi-source remote sensing data, including canopy height derived from GEDI and ICESat-2 satellite-borne lidar, Landsat imagery, and environmental variables, to estimate forest biomass dynamics in Hainan’s tropical rainforests at a 30 m spatial resolution, involving a correlation analysis of factors influencing spatiotemporal changes in Hainan Tropical Rainforest biomass. The research aims to investigate the spatiotemporal variations in forest biomass and identify key environmental drivers influencing biomass accumulation. Four machine learning algorithms—Backpropagation Neural Network (BP), Convolutional Neural Network (CNN), Random Forest (RF), and Gradient Boosting Decision Tree (GBDT)—were applied to estimate biomass across five forest types from 2003 to 2023. Results indicate the Random Forest model achieved the highest accuracy (R² = 0.82). Forest biomass and carbon stocks in Hainan Tropical Rainforest National Park increased significantly, with total carbon stocks rising from 29.03 million tons of carbon to 42.47 million tons of carbon—a 46.36% increase over 20 years. These findings demonstrate that integrating multimodal remote sensing data with advanced machine learning provides an effective approach for accurately assessing biomass dynamics, supporting forest management and carbon sink evaluations in tropical rainforest ecosystems. Full article

Madhuca hainanensis is a rare, endemic tree species of Hainan Island, with considerable ecological and economic value. Its natural regeneration is severely limited by habitat fragmentation and environmental stress. To investigate its adaptive across environmental gradients, we established experimental plots in the Jianfengling area of Hainan Tropical Rainforest National Park, encompassing elevation (400–1000 m) and canopy closure (30%–90%) gradients. Sapling growth and health were monitored for one year, alongside measurements of soil physicochemical properties and leaf photosynthetic pigment content. The results indicate that elevation was the primary factor influencing growth, with saplings at lower elevations exhibiting higher increments in height, diameter, and crown spread. While canopy closure was not statistically significant, moderate openness (30%–50%) at low elevations favored growth, whereas high-elevation, heavily shaded conditions constrained development. Sapling health declined over time, particularly in high-elevation and high-canopy-closure plots, and the interaction between elevation and canopy closure amplified physiological stress. Redundancy analysis revealed that elevation and canopy closure jointly explained ~36%–38% of the variance in growth and health, with chlorophyll a, carotenoids, and soil available phosphorus also contributing to sapling performance. These findings indicate that M. hainanensis is highly sensitive to light and elevation-related environmental gradients, and that low-elevation sites with moderate canopy openness are optimal for restoration and cultivation. This study provides a scientific basis for in situ conservation, wild reintroduction, and management of this threatened endemic species. Full article

Ecological theory suggests that interspecific interactions and environmental heterogeneity promote temporal niche partitioning, whereby species segregate their activity along diel and seasonal axes. For ectotherms, temperature is a critical niche dimension because heat availability regulates activity and phenology. Here, we used data from a hyperdiverse rainforest in the Ecuadorian Amazon to compare community dynamics across two temporal scales and to test their relationship with temperature fluctuations. Butterflies were periodically sampled using Pollard walks in a permanent plot over eight field campaigns spanning two years. We compared environmental temperature fluctuations, diversity metrics, and niche-overlap estimates of community assemblages at both diel and seasonal scales. We recorded 1003 individuals representing 222 species. Temperature differences among seasons were comparable to those observed across times of day. Consistently, our analyses revealed distinct community assemblages across both diel and seasonal scales. Furthermore, butterfly activity tended to increase during warmer hours and in warmer seasons, yet overlap in activity within these timeframes was low at both the species and subfamily levels. These results highlight the contribution of both abiotic drivers and biotic interactions in structuring butterfly temporal abundance. More broadly, our study underscores the importance of explicitly considering temporal dimensions when examining tropical biodiversity. Full article

Understanding the diversity patterns within a region is helpful for the implementation of conservation management. Xishuangbanna, located in southwestern China, is notable for its diverse plant species and belongs to a tropical–subtropical transition area. This study investigated the biodiversity patterns for four types of primary forests in Xishuangbanna, namely tropical rainforests, tropical monsoon forests, tropical low-montane evergreen broadleaf forests, and tropical seasonal moist forests. The difference in the forests alongside a set of environments was assessed using non-metric dimensional scaling and partial least-squares discriminant analysis. And, we calculated and compared four diversity metrics for each forest, including species richness, phylogenetic diversity, standardized phylogenetic diversity, and standardized mean phylogenetic distance, and calculated their correlation with 22 environments using multiple stepwise regressions. The results showed that tropical rainforests had the highest biodiversity on account of species richness (with an average of about 40 species) and phylogenetic diversity (with an average of about 3000). Although the values of standardized mean phylogenetic distance were lower than zero for all forests, the tropical seasonal moist forests ranked first. Not only species composition and environments’ differences, especially the temperature seasonality, minimum temperature of the coldest month, latitude, and precipitation of the driest quarter, primarily influenced the forest groupings. The variance in species richness (R² = 0.57) and phylogenetic diversity (R² = 0.54) was best explained by a model integrating forest type, soil, climate, and geographic factors. In contrast, the variance in standardized phylogenetic diversity (R² = 0.48) and standardized mean phylogenetic distance (R² = 0.39) was primarily influenced by soil and climate factors. We suggest that tropical rainforests and tropical seasonal moist forests should be conservation priorities in conservation management. This study provides insights into community assembly mechanisms and the enhancement of biodiversity conservation management in transitional areas. Full article

The Miocene epoch witnessed the emergence of modern biomes and biodiversity hotspots. Understanding its history in South China is crucial for informing conservation under modern climate change, yet quantitative constraints on the evolution of climate and vegetation from the tropical–subtropical transition zone remain scarce. Here, we present the first quantitative Miocene paleoclimatic and paleoecological reconstructions based on an integrated analysis of leaf-based proxies applied to exceptionally preserved and highly diverse dicotyledonous leaf megafossils from the Erzitang Formation, Guiping Basin, Guangxi. Results indicate a mean annual temperature of 22.3 °C and mean annual precipitation of 1991 mm, with a monsoon intensity index higher than present, indicating a humid monsoonal climate regime. Vegetation analysis identifies the Miocene Guiping flora as tropical forest. Rather than a simple forest replacement, South China maintained dynamic tropical forest patches that expanded northward to 23° N under Asian monsoons, forming a mosaic with evergreen broad-leaved forests. Overall, the Miocene Guiping vegetation represents a tropical forest situated in a tropical rainforest to seasonal forest ecotone under a humid monsoonal climate, rather than a per-humid rainforest, underscoring the pivotal role of monsoon evolution in shaping low-latitude forest patterns and providing a deep-time benchmark for predicting vegetation responses to future climate change. Full article

Functional traits provide key insights into plant ecological strategies and responses to environmental heterogeneity, yet the role of intraspecific trait variability (ITV) in tropical rainforests remains underexplored. We examined ITV in six leaf traits—leaf thickness (LT), leaf area (LA), specific leaf area (SLA), leaf dry matter content (LDMC), leaf nitrogen content (LNC), and stomatal density (SD)—in saplings of 15 dominant tree species across ridge and valley habitats in a Sri Lankan tropical lowland rainforest. We compared interspecific and intraspecific variation and quantified trait plasticity using the plasticity index. Significant ITV was observed for LT, LA, and SD, with ridge individuals showing smaller, thicker leaves with lower SD. SLA, LDMC, and LNC exhibited no overall habitat-level differences, though species-specific divergent responses were detected. Interspecific variation exceeded ITV for most traits, except for LNC, where ITV accounted for 55% of total variation. Trait plasticity varied among traits, with LNC showing the highest plasticity. These results indicate that individuals adjust leaf traits in response to fine-scale habitat heterogeneity, reflecting shifts in resource-use strategies. Overall, ITV is ecologically meaningful and should be incorporated into community-level studies and ecosystem models to improve predictions of plant community dynamics and ecosystem functioning under environmental change. Full article

Understanding how vegetation structure influences invertebrate diversity is critical for tropical forest conservation because invertebrates play key roles in ecosystem functioning. This study investigates the role of vegetation and selected microhabitats in shaping harvestmen assemblages across primary and planted forests in the Amazon rainforest. Our findings challenge the traditional view that vegetation quantity alone drives invertebrate distribution, revealing that specific plant species play a key role in shaping harvestmen assemblages. Notably, Geaya sp. (Sclerosomatidae) was strongly associated with specific arboreal species, especially Tetragastris altissima and Attalea maripa, and was identified as a bioindicator of trees. Tree diversity provides critical habitats in primary forests, illustrating how changes in tree composition can disproportionately impact specialist species. Two species of harvestmen were also identified as bioindicators of forest quality. For instance, Geaya sp. was exclusively linked to primary forests, while the cosmetid Gryne sp. emerged as moderately associated with this type of forest with high structural complexity. By identifying the specific relationships between harvestmen and vegetation, this study demonstrates their potential for monitoring ecosystem health and emphasizes the importance of preserving keystone plant species to maintain ecological integrity in tropical forests. Full article

Aboveground biomass (AGB) is a key indicator of forest structure and carbon sequestration, yet its dynamics under concurrent anthropogenic disturbances remain poorly understood. This study investigates the spatiotemporal dynamics and driving mechanisms of AGB in the Jianfengling tropical lowland rainforest (JFLTLR) within Hainan Tropical Rainforest National Park (NRHTR) from 2015 to 2023. Six machine learning models—Extreme Gradient Boosting (XGBoost), Gradient Boosting Machine (GBM), Support Vector Machine (SVM), k-Nearest Neighbors (KNN), Decision Tree (DT), and Random Forest (RF)—were evaluated, with RF achieving the highest accuracy (R² = 0.83). Therefore, RF was employed to generate high-resolution annual AGB maps based on Sentinel-1/2 data fusion, field surveys, socio-economic indicators, and topographic variables. Human pressure was quantified using the Human Influence Index (HII). Threshold analysis revealed a critical breakpoint at ΔHII ≈ 0.1712: below this level, AGB remained relatively stable, whereas beyond it, biomass declined sharply (≈−2.65 mg·ha⁻¹ per 0.01 ΔHII). Partial least squares structural equation modeling (PLS-SEM) identified plantation forests as the dominant negative driver, while GDP (−0.91) and road (−1.04) exerted strong indirect effects through HII, peaking in 2019 before weakening under ecological restoration policies. Spatially, biomass remained resilient within central core zones but declined in peripheral regions associated with road expansion. Temporally, AGB exhibited a trajectory of decline, partial recovery, and renewed loss, resulting in a net reduction of ≈ 0.0393 × 10⁶ mg. These findings underscore the urgent need for a “core stabilization–peripheral containment” strategy integrating disturbance early-warning systems, transportation planning that minimizes impacts on high-AGB corridors, and the strengthening of ecological corridors to maintain carbon-sink capacity and guide differentiated rainforest conservation. Full article

Although mountain vertical vegetation belts are key in revealing the response to climate change and the maintenance mechanism of biodiversity, traditional field surveys and remote sensing methods face significant limitations in the structurally complex tropical humid mountainous regions of Hainan Island. As bryophytes are good microclimate indicators and characteristic components of the structure of the tropical rainforest, they may be useful tools for the construction of a general scheme of the altitudinal zonation of tropical rainforests. We surveyed bryophyte communities across eight elevations and three vegetation types at LiMu Mountain, southern China. Bryophyte species alpha diversity increased significantly as elevation increased, while beta diversity showed the contrasting pattern. Bryophyte community composition differed significantly along elevation gradients and the distribution of vegetation types was clearly distinguished by three significantly different bryophyte assemblages with specific elevational range. Hierarchical partitioning revealed that microclimate outweighed topography in structuring communities, aligning with global patterns of bryophyte thermal sensitivity. Bryophytes are effective bioindicators for tropical rainforest elevational zonation, reflecting fine-scale environmental gradients. Their sensitivity to microclimate supports their utility in monitoring vegetation shifts under climate change, particularly in topographically complex regions. Full article

Protected area coverage is set to expand in response to climate change and the biodiversity crisis, but we lack assessments of wildfire incidence in protected areas. Here, we quantify biogeographical variation in global patterns of burned area in protected areas. During the twenty-first century, wildfires have burned 2 billion hectares of protected areas—an area the size of Russia and India combined—and, while protected areas only cover 19.2% of semi-natural ecosystems, they concentrate 28.5% of the area burned annually. Wildfire in protected areas increased significantly between 2001 and 2024 (+0.46% yr⁻¹), even after taking into account increases in protected area (+0.27% yr⁻¹), pointing to a disproportional impact of fire on protected areas under increasingly severe fire weather. This pattern showed marked variation across biomes, with the largest disproportionate increases occurring in fire-prone biomes (e.g., Mediterranean and dry tropical forests, tropical grasslands, and xeric shrublands). There were important exceptions to this general trend, and protected area fire was lower than expected in biomes where fire activity is naturally limited by moisture (e.g., tropical rainforests or montane grasslands). Wildfires are important for the health of many ecosystems, and such values of burned area will not always mean a negative outcome. Amidst concerted efforts to expand protected area coverage, such as the Global Biodiversity Framework, our results highlight the need for new management strategies that address the globally increasing impacts of burned area across protected areas under unabated climate change. Full article

The integration of unmanned aerial vehicle-based laser scanning (ULS) and mobile laser scanning (MLS) enables the detection of forest three-dimensional structure in high-density canopy areas and has become an important tool for monitoring and managing forest ecosystems. However, MLS faces difficulties in positioning due to canopy occlusion, making integration challenging. Due to the variations in observation platforms, ULS and MLS point clouds exhibit significant structural discrepancies and limited overlapping areas, necessitating effective methods for feature extraction and correspondence establishment between these features to achieve high-precision registration and integration. Therefore, we propose a registration algorithm that introduces a Feature Deviation Metric to enable feature extraction and correspondence construction for forest point clouds in complex regional environments. The algorithm first extracts surface point clouds using the hidden point algorithm. Then, it applies the proposed dual-threshold method to cluster individual tree features in ULS, using cylindrical detection to construct a Feature Deviation Metric from the feature points and surface point clouds. Finally, an optimization algorithm is employed to match the optimal Feature Deviation Metric for registration. Experiments were conducted in 8 stratified mixed tropical rainforest plots with complex mixed-species canopies in Malaysia and 6 structurally simple, high-canopy-density pure forest plots in anorthern China. Our algorithm achieved an average RMSE of 0.17 m in eight tropical rainforest plots with an average canopy density of 0.93, and an RMSE of 0.05 m in six northern forest plots in China with an average canopy density of 0.75, demonstrating high registration capability. Additionally, we also conducted comparative and adaptability analyses, and the results indicate that the proposed model exhibits high accuracy, efficiency, and stability in high-canopy-density forest areas. Moreover, it shows promise for high-precision ULS-MLS registration in a wider range of forest types in the future. Full article

In tropical regions, the establishment of large-scale exotic plantations has addressed the demand for timber resources but has also disrupted the structural stability of native vegetation and altered soil nutrient cycling, thereby impairing ecosystem functions. Identifying effective restoration strategies for these plantations is crucial for sustainable forest management and ecological security. This study examined Acacia mangium Willd., Cunninghamia lanceolata (Lamb.) Hook., and Pinus caribaea Morelet. plantations in Hainan Tropical Rainforest National Park under three treatments: plantation control, girdling, and natural secondary forest. Vegetation surveys and soil analyses were conducted to explore the relationships between community structure, soil physicochemical properties, and enzyme activities. Diversity indices, Pearson correlations, and redundancy analysis were used to assess plant–soil relationships. The results showed that girdling significantly accelerated succession in C. lanceolata and P. caribaea plantations, increased species diversity, and enhanced the dominance of native species. Shrub-layer diversity indices (H_shrub, D_shrub, E_shrub) were the main drivers of soil properties and enzyme activities, while tree-layer effects were weaker. Girdling regulated soil nutrients and biological activity primarily via changes in community structure. These findings highlight the importance of optimizing shrub-layer structure and enhancing diversity for tropical plantation restoration. Combining forest type conversion with moderate interventions can promote coordinated plant–soil development over time. Full article

Recent studies suggest that Pb-based ammunition could be an important route of Pb exposure for Indigenous Peoples in tropical rainforests. We analyzed blood lead levels (BLL) and isotopic signatures in 111 humans, 97 wild animals, 81 fish, and potential environmental Pb sources in an Indigenous community in the remote and well-preserved Peruvian Amazon with no history of industrial activity. Median BLL was 11.74 μg dL⁻¹, with BLL ≥ 5 µg dL⁻¹ in 95.8% children <12-yo and 94.5% adults. Pb concentrations in wild animals were 7.00 ± 22.40 mg kg⁻¹ DW in liver, 0.06 ± 0.09 mg kg⁻¹ DW in fish muscle tissues, 17.1 ± 10.8 mg kg⁻¹ in soils and 3.4–3.8 mg L⁻¹ in the main river, although 0.43-0.53 mg L⁻¹ were the Pb levels in decanted water used for drinking and cooking. The similarity of isotopic signatures (^207/206Pb and ^208/206Pb) shows that the main Pb sources for humans are river waters (97.6%) and Pb-based ammunition (78.7%). Fish and wildlife act as Pb transporters from water, and wildlife act as Pb transporter from ammunition. Evidence of high human BLL in a remote, non-industrialized Amazonian area demonstrates the urgency of designing regional policies that include health prevention measures, focused on drinking water filtration systems and the use of non-toxic, Pb-free ammunitions. Full article

This study proposes an Automatic Branch Modeling (ABM) framework that combines AdTree and AdQSM algorithms to reconstruct individual tree models and estimate timber volume from fused Hand-held Laser Scanners (HLS) and Unmanned Aerial Vehicle Laser Scanners (UAV-LS) point cloud data. The research focuses on two 50 × 50 m primary tropical rainforest plots in Hainan Island, China, characterized by dense and vertically stratified vegetation. Key steps include multi-source point cloud registration and noise removal, individual tree segmentation using the Comparative Shortest Path (CSP) algorithm, extraction of diameter at breast height (DBH) and tree height, and 3D reconstruction and volume estimation via cylindrical fitting and convex polyhedron decomposition. Results demonstrate high accuracy in parameter extraction, with DBH estimation achieving R² = 0.89–0.90, RMSE = 2.93–3.95 cm and RMSE% = 13.95–14.75%, while tree height estimation yielded R² = 0.89–0.94, RMSE = 1.26–1.81 m and RMSE% = 9.41–13.2%. Timber volume estimates showed strong agreement with binary volume models (R² = 0.90–0.94, RMSE = 0.10–0.18 m³, RMSE% = 32.33–34.65%), validated by concordance correlation coefficients (CCC) of 0.95–0.97. The fusion of HLS (ground-level trunk details) and UAV-LS (canopy structure) data significantly improved structural completeness, overcoming occlusion challenges in dense forests. This study highlights the efficacy of multi-source LiDAR fusion and 3D modeling for precise forest inventory in complex ecosystems. The ABM framework provides a scalable, non-destructive alternative to traditional methods, supporting carbon stock assessment and sustainable forest management in tropical rainforests. Future work should refine individual tree segmentation and wood-leaf separation to further enhance accuracy in heterogeneous environments. Full article

The rapid expansion of transportation infrastructure on Hainan Island has intensified ecological pressures such as landscape fragmentation and decreased connectivity, threatening the environmental integrity of Hainan Tropical Rainforest National Park. As China’s only tropical island national park, it is important to maintain biodiversity and ecological resilience. Therefore, this study attempts to examine the park and its 5 km buffer zone to assess how transport expansion from 2003 to 2023 has altered land use patterns and landscape connectivity. Through the analysis of multi-period land use data, the land use changes are tracked by using ArcGIS and Fragstats 4.3 software, and the landscape dynamics are quantified. We linked these patterns to ecological processes via a resistance-surface model, which is further refined by spatial structural indices to better reflect ecological realism. Ecological sources were subsequently identified through morphological analysis and ecosystem service evaluation, and circuit theory was applied to delineate potential corridors and construct an ecological security network. The results indicate that (1) transportation development has significantly increased landscape fragmentation and ecological resistance, particularly along major highways; (2) while core forest areas inside the park remain relatively intact, the buffer zones show accelerating degradation; and (3) Although there are many ecological conflict points between the transportation network and the ecological corridor, the construction of animal channels in combination with bridges, tunnels and culverts can effectively improve ecological connectivity and protect the integrity of animal habitat. These findings highlight the vulnerability of ecological integrity as the network expands. The proposed modeling framework provides a more realistic assessment of infrastructure impact and offers a scientific basis for coordinating ecological protection and transport planning in tropical island national parks. Full article