Coastal wetland ecosystems harbor rich biodiversity and possess significant ecosystem service value (ESV). Therefore, it offers a range of crucial ecosystem services (ES) for human well-being and socio-economic development. Taking the Hainan Island coastal zone (HICZ) as a case study, the spatio-temporal characteristics of land use and land cover change (LULCC), and its associated ESV in wetland landscapes were analyzed over three time points (2000, 2010 and 2020). We explored the spatio-temporal evolution trajectory of ESV on the basis of geo-information tupu. Then, future land use simulation (FLUS) was employed to predict wetland patterns and ESV under three different scenarios: business as usual (BAU), ecological conservation first (ECF), and economic development first (EDF). The results showed that over the past two decades, a significant proportion (exceeding 80%) of the overall wetland region was comprised of offshore and coastal wetlands (OCW) as well as constructed wetlands (CW); these formed the matrix of the landscape. The area of building land (BL) continued to exhibit a consistent upward trend. Expanding by 2.18 times, it represented the most significant increase in the rate of dynamic changes in BL. The main ES in the HICZ corresponded to the regulation services (53.57%) and the support services (27.58%). The ESV of wetland losses accounted for 45.17% (43.08 × 10⁸ yuan) of the total loss. The spatial differentiation of ESV in the HICZ was larger in the southwest and the northeast regions, while it was comparatively lower in the north. The transformation in the area of early and late change types accounted for 236.46 km² and 356.69 km², respectively. The scenario ECF was achieved with an optimal development of ESV (1807.72 × 10⁸ yuan), which was coordinated with the high-level of development of regional ES functions and the economy. These findings provide valuable information for the sustainable development as well as the protection of ecology and environment of the coastal zone under the background of the construction of Hainan pilot free trade zone in the future.

The National Park of Hainan Tropical Rainforest (NPHTR) plays the crucial role of an ecological barrier for Hainan Island. It also serves as a valuable repository of tropical biological heritage for the world. The scientific establishment of an ecological security pattern (ESP) for the NPHTR is therefore essential for ensuring the robustness and stability of this regional ecosystem, safeguarding tropical biodiversity, and promoting sustainable development. This study integrates ecosystem service functions (ESFs) and ecological sensitivity to identify ecological sources (ESs) so that regional integrity is promoted and ecological security is ensured. Ecological corridors (ECs) are established on the basis of a minimum cumulative resistance (MCR) model and circuit theory. We integrate ESs, nodes, and corridors to construct the ESP of the NPHTR. The areas of extreme importance and sensitivity in the NPHTR account for 25.17% and 25.47% of its overall area, respectively, and are predominantly situated in the higher elevations of its eastern and central regions. Further, the ESs are mainly distributed in its western region, specifically Ba Wangling (BWL), Jian Fengling (JFL), and Ying Geling (YGL), covering an area of 1624.67 km² (38.06% of the total area) of the NPHTR. After correction, 47 ECs with a distance of 870.9 km have been established, with BWL and YGL serving as the core areas. The ecological pinch- and barrier points in the NPHTR cover areas of 11.49 km² and 16.35 km², respectively, primarily consisting of man-made landscapes such as farmlands and buildings. These areas are significantly disturbed by human activities. The NPHTR has an ESP of “one screen, one district, three belts, multiple points, and multiple corridors”. BWL and YGL, which contain numerous sources and corridors, are crucial ecological functional zones. To ensure the horizontal connectivity of rare wildlife, such as of Nomascus hainanus and Cervus eldii hainanus, the NPHTR should establish buffer or development zones. These findings offer valuable insights for the development and planning of ecological civilization on Hainan Island, as well as for the establishment and management of the ESP of other national parks and nature reserves.

Free trade zones are key regions experiencing rapid economic growth, urbanization, and a sharp increase in population density. During the development of free trade zones, these areas undergo drastic transformations in landscape types, large-scale urban construction, heightened resource consumption, and other associated challenges. These factors have led to severe landscape ecological risk (LER). Therefore, conducting comprehensive assessments and implementing effective management strategies for LER is crucial in advancing ecological civilization and ensuring high-quality development. This study takes Hainan Island (HI), China, as a case study and utilizes multi-source data to quantitatively evaluate land use and land cover change (LULCC) and the evolution of the LER in the study area from 2015 to 2023. Additionally, it examines the spatial patterns of LER under three future scenarios projected for 2033: a natural development scenario (NDS), an economic priority scenario (EPS), and an ecological conservation scenario (ECS). Adopting a spatiotemporal dynamic perspective framed by the “historical–present–future” approach, this research constructs a zoning framework for LER management to examine the temporal and spatial processes of risk evolution, its characteristics, future trends, and corresponding management strategies. The results indicate that, over an eight-year period, the area of built-up land expanded by 40.31% (504.85 km²). Specifically, between 2015 and 2018, built-up land increased by 95.85 km², while, from 2018 to 2023, the growth was significantly larger at 409.00 km², highlighting the widespread conversion of cropland into built-up land. From 2015 to 2023, the spatial distribution of LER in the study area exhibited a pattern of high-risk peripheries (central mountainous areas) and low-risk central regions (coastal areas). Compared to 2023, projections for 2033 under different scenarios indicate a decline in cropland (by approximately 17.8–19.45%) and grassland (by approximately 24.06–24.22%), alongside an increase in forestland (by approximately 4.5–5.35%) and built-up land (by approximately 23.5–41.35%). Under all three projected scenarios, high-risk areas expand notably, accounting for 4.52% (NDS), 3.33% (ECS), and 5.75% (EPS) of the total area. The LER maintenance area (65.25%) accounts for the largest proportion, primarily distributed in coastal economic development areas and urban–rural transition areas. In contrast, the LER mitigation area (7.57%) has the smallest proportion. Among the driving factors, the GDP (q = 0.1245) and year-end resident population (q = 0.123) were identified as the dominant factors regarding the spatial differentiation of LER. Furthermore, the interaction between economic factors and energy consumption further amplifies LER. This study proposes a policy-driven dynamic risk assessment framework, providing decision-making support and scientific guidance for LER management in tropical islands and the optimization of regional land spatial planning.

We explored the characteristics of landscape pattern (LP) changes in the Nandu River Basin (NRB) and its dynamic response mechanism to anthropogenic disturbance (AD). This is important for ecological protection and for land use decision-making in the basin in the context of the construction of a free trade port. Land use and land cover change (LULCC) data of 1990, 2000, 2010, and 2020 were analyzed with the help of the LP index, moving window method, hemeroby index, geo-information atlas, and geographic information system (GIS) spatial analysis to reveal the dynamic changes in LP characteristics in the NRB. Furthermore, this paper discusses into the correlation between LP and AD. The results indicate that over the past three decades, the NRB showed a staggered LP, dominated by forestland and cropland, whose total area has decreased by 25.27 km² and 62.75 km², respectively. On the other hand, the built-up land increased by 91.37%. The overall landscape fragmentation, landscape patch homogeneity, and landscape diversity have increased in the NRB. AD is the main reason for the dramatic changes in the LP of urban agglomerations centered in Haikou city. The area of minor disturbance (over 34%) occupies the largest proportion of the land, followed by higher (about 13~25%) and moderate disturbances (about 17~22%). The area of minor and strong disturbances has increased significantly, whereas those of moderate and higher disturbances have significantly decreased. The spatial distribution pattern of AD is gradually increasing from the southwest (natural landscape) to the northeast (human landscape). A transition in areas of low disturbance levels to higher levels is obvious. The area of the atlas that has transitioned from “minor → lighter disturbance (12)” and “higher → minor disturbance (41)” changed changed most significantly during 2000 to 2010 and from 2010 to 2020, occupying 26.79% and 11.99% of the transfer atlas, respectively. All regions encountering disturbances were significantly correlated with the largest patch index (LPI) from 1990 to 2020. The overall AD in the NRB has increased, especially in Haikou. Urbanization is the main factor for an increase in AD. The ecological and environmental management and monitoring in the basin need to be strengthened.

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.