Vegetation greenness has been one of the most widely utilized indicators to assess the vegetation growth status for the better ecological environment. However, in typical tourist regions, the impact of the geographical environment, socioeconomic development, and tourism development on vegetation greenness changes is still a challenge. To address this challenge, we used the Google Earth Engine (GEE) cloud platform combined with a series of Landsat remote sensing images to calculate the fractional vegetation cover (FVC) which can be used as an indicator to characterize the spatiotemporal evolution of vegetation greenness in Hainan Island from 2000 to 2020. Furthermore, we employed geographic detector and structural equation models to quantify the relative importance and explanatory power of the geographical environment, socioeconomic development, and tourism development on vegetation greenness changes and to clarify the interaction of mechanisms of various factors in Haikou and Sanya. The results show that the annual growth rate of the FVC in Hainan Island was 0.0025/a. In terms of spatial distribution, the trend of the FVC changes was mainly characterized by non-significant and extremely significant improvement, accounting for 35.34% and 29.38% of the study area. Future vegetation greenness was dominated by weak counter-persistent increase and weak persistent increase. The geographical environmental factors were the main factors affecting vegetation greenness in Haikou, followed by the socioeconomic and the tourism development factors, while the geographical environmental factors also dominate in Sanya, followed by the tourism development factors and finally the socioeconomic factors. Specifically, the spatial distribution of vegetation greenness was primarily influenced by land use types, elevation, slope, and travel services. Geographical environmental factors could indirectly affect changes in socioeconomic and tourism development, thereby indirectly affecting the spatial distribution of vegetation greenness. These findings can provide some significant implications to guide the ecological environmental protection for sustainable development in Hainan Island in China.

In rubber plantations, understory coverage is often disrupted by human activities, which increases the risk of soil erosion under intense rainfall typical of tropical islands. Evaluating the effectiveness of soil and water conservation measures (SWCMs) is crucial for effectively conserving subcanopy resources. This study focused on Hainan Island’s rubber plantations, where nine different SWCMs were implemented, and the runoff and sediment yield were monitored during the rainy season using runoff plots. Through correlation analysis, we identified the primary rainfall characteristic factors leading to soil and water loss on rubber plantation slopes. Path analysis was then used to quantify the impacts of these characteristic factors. The results showed that the SWCMs were significantly more effective in erosion reduction (68.55%) than in runoff reduction (58.95%). Of all the measures, comprehensive SWCMs proved most effective in controlling runoff (71.34%), followed by engineering SWCMs (62.03%) and biological SWCMs (43.51%). Comprehensive SWCMs were also found to be effective in erosion reduction, with a rate of 77.84%, surpassing engineering and biological SWCMs by 7.23% and 20.66%, respectively. Notably, the combination of narrow terraces, contour trenches, and grass planting was the most effective, achieving runoff-reduction rates of 80.94% and erosion-reduction rates of 85.27%. This combination is recommended as a primary prevention method. Rainfall and maximum 30-min intensity (I₃₀) were identified as key variables affecting the efficacy of SWCMs, with rainfall positively correlating with runoff yield and I₃₀ being more closely linked to sediment production. This study provides valuable insights for developing erosion control strategies for sloping garden lands in similar regions and lays theoretical foundations for future ecological restoration projects.

Rainfall erosivity (RE), a pivotal external force driving soil erosion, is impacted by El Niño/Southern Oscillation (ENSO). Studying the spatiotemporal variations in RE and their response to ENSO is essential for regional ecological security. In this study, a daily RE model was identified as a calculation model through an evaluation of model suitability. Daily precipitation data from 1971 to 2020 from 38 meteorological stations on Hainan Island, China, were utilized to calculate the RE. The multivariate ENSO index (MEI), Southern Oscillation Index (SOI), and Oceanic Niño Index (ONI) were used as the ENSO characterization indices, and the effects of ENSO on RE were investigated via cross-wavelet analysis and binary and multivariate wavelet coherence analysis. During the whole study period, the average RE of Hainan Island was 15,671.28 MJ·mm·ha⁻¹·h⁻¹, with a fluctuating overall upward trend. There were spatial and temporal distribution differences in RE, with temporal concentrations in summer (June–August) and a spatial pattern of decreasing from east to west. During ENSO events, the RE was greater during the El Niño period than during the La Niña period. For the ENSO characterization indices, the MEI, SOI, and ONI showed significant correlations and resonance effects with RE, but there were differences in the time of occurrence, direction of action, and intensity. In addition, the MEI and MEI–ONI affected RE individually or jointly at different time scales. This study contributes to a deeper understanding of the influence of ENSO on RE and can provide important insights for the prediction of soil erosion and the development of related coping strategies.