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As a fundamental element of global carbon storage, the storage carbon in terrestrial ecosystem is significant for climate change mitigation. Land use/cover change (LUCC) is a main impact element of ecosystems’ carbon storage. Evaluating the relation between land use change and carbon storage is vital for lowering global carbon emissions. Taking Hainan Island as an example, this paper employs the InVEST as well as the CA-Markov models to assess and predict how different land use affects carbon storage in various situations from 2000 to 2020 and from 2030 to 2050 on Hainan Island. The influence factors, together with driving mechanisms of carbon storage spatial distribution are quantitatively analyzed as well in this paper. The results demonstrate that, from 2000 to 2020, Hainan Island’s net increase in built land was 605.49 km2, representing a growth rate of 77.05%. Over the last 20 years, Hainan Island’s carbon storage and density have decreased by 5.90 Tg and 1.75 Mg/hm2, respectively. The sharp rise in built land mainly makes the carbon storage decline. From 2030 to 2050, land use changes on Hainan Island are expected to result in differing degrees of carbon storage loss in various scenarios. In 2050, Hainan Island’s carbon storage will decline by 17.36 Tg in the Natural Development Scenario (NDS), 13.61 Tg in the Farmland Protection Scenario (FPS), and 8.06 Tg in the Ecological Protection Scenario (EPS) compared to 2020. The EPS can efficiently maintain carbon sequestration capability, but it cannot effectively prevent cropland area loss. Regarding the carbon storage’s spatial distribution, Hainan Island generally exhibits a pattern of high carbon storages in the low and middle carbon storages in the surrounding areas. Areas with high value are primarily located in Hainan Island’s central and southern mountainous areas, whereas areas with low value are primarily located in surrounding areas with lower elevations, primarily encompassing built land and cropland. Geographic detection presented the spatial differentiation of carbon storage in Hainan Island is mainly influenced by factors like slope, land use intensity, and DEM, as well as its interaction with other factors is significantly strengthened (p

Xylaria is a widely distributed genus in the Ascomycota phylum that can decompose wood. It is an essential decomposer in ecosystems and a source of bioactive secondary metabolites. Based on morphological characteristics and molecular evidence, this article thoroughly describes two new species discovered on the fallen leaves in Hainan Tropical Rainforest National Park, along with illustrations and comparisons with similar species. Xylaria diaoluoshanensis is characterized by filamentous stromata with long infertile apexes, ascospores sometimes with non-cellular appendages. Xylaria fulvotomentosa differentiates itself from other Xylaria species that grow on fallen leaves by its stroma surface, being yellow tomentose. These two new species of the genus Xylaria were found by phylogenetic analysis using the ITS-β-tubulin-RPB2 sequence dataset. Furthermore, a species first discovered in China, X. petchii, is described. Finally, a search table for 44 species related to fallen leaves and petioles in the world is established.

Tropical rainforests in the central hilly section of Hainan Island are the source of the Nandu, Changhua, and Wanquan rivers, which are crucial for water conservation and ecological protection. The quantitative assessment of water yield in the three basins is beneficial for developing regional water resource protection plans, establishing ecological compensation mechanisms, and maintaining ecological balance. Based on land use data from five periods between 1980 and 2020, this paper adopts the InVEST model and geographic detectors to investigate the spatial-temporal variation characteristics and driving factors of water yield in three major basins of Hainan Island. The results demonstrate that forestland, which makes up more than 70% of the total area in the three basins of Hainan Island, is the predominant land use type. With a depth of 1269.18 mm, Wanquan Basin is the deepest of the three basins, followed by Nandu Basin and Changhua Basin. The total water yield of three basins shows a slightly decreasing trend from 17.991 billion m3 in 1980 to 17.864 billion m3 in 2020. The spatial distribution of water yield is high in the southeast region and low in the northwest region, with strong autocorrelation and significant aggregation. According to geographic detection, land use type is the dominant factor for the spatial differentiation of water yield in the three basins, with a contribution rate of 0.563, and soil type and annual precipitation are important impact factors. The interaction and synergy of soil types and land use types jointly affect the spatial differentiation of water yield in the basin. The results of this study can provide data support and scientific references for biodiversity conservation and ecosystem restoration in the three major basins of Hainan Island.

Hainan Island has undergone rapid landscape transformation leading to habitat fragmentation.Thus, exploring the spatiotemporal change from its past habitat quality provides insights into its future ecological protection. This study investigated the spatiotemporal changes of the habitat quality of Hainan Island from 1980 to 2020 using the InVEST and CA-Markov models and predicted the habitat quality for the time frame of 2020–2040. We found that the habitat quality index first increased from 0.73 in 1980 to 0.74 in 1990 and then will decrease to 0.70 in 2040 with an accelerating rate. The habitat quality inside the national park was significantly better and more stable than that outside the national park. The simulation and prediction results showed that the habitat quality inside the national park would continue to improve from 2020 to 2040, while that outside the national park would decline. The spatial distribution of the changes in the habitat quality of Hainan Island was significantly autocorrelated and clustered, enhanced over time. Our results suggest that the overall decline in the habitat quality of Hainan Island mainly result from the habitat quality change outside the national park, and the habitat quality change inside the national park will play a key role in stabilizing and supporting the habitat quality of Hainan Island, which highlights the importance of national park conservation.

National parks promote the protection of the ecological environment and global biodiversity conservation. However, the changes in land use obviously damages the natural habitat, leading to habitat fragmentation and degradation. Land use changes affect ecosystem service value (ESV) and its spatial distribution. In this study, a framework for the assessment of regional spatial patterns in land use/cover changes (LUCC) and ESV was established; the framework relies on the application of a classical spatial autocorrelation model. Remote sensing data for Hainan Tropical Rain Forest National Park (HNTRFNP) were used as a test case for the autocorrelation model approach to analyzing spatial patterns in ESV. Across HNTRFNP, ESV averaged 6201.44 million USD, with high ESV seen in aquatic and forested areas. Furthermore, land use types in HNTRFNP showed spatial autocorrelation (P

Due to wetland loss, Ottelia cordata (O. cordata, Wallich) Dandy has been categorized as an endangered species on the List of Key Protected Wild Plants in China. Quantifying the relative importance of demographic (i.e., growth, survival, and reproduction) and habitat preference traits on the population dynamics (abundance) of O. cordata could guide how to develop the best recovery strategies of O. cordata, yet currently, there are no studies that investigate this. By monitoring monthly changes in O. cordata abundance and demographic traits (plant height, leaf area, flower sex ratio, and seed number) that were highly correlated with growth rate, photosynthetic rate, and water depth, we identified several relationships. Linear mixed-effect models and variance partition quantified the specific effects of four demographic traits and water depth on O. cordata abundance in three habitat types (paddyfield, stream, and spring). The linear mixed-effect models indicate that among the four demographic traits, height could be significantly positively correlated to abundance in all three habitat types. In contrast, other three traits (leaf area, sex ratio, and seed numbers) were non-significantly associated with abundance across each habitat. Height was determined by water depth, so water depth rather than photosynthetic rate and reproduction rate may promote the development and recovery of O. cordata populations. Variance partition results showed that water depth mediated the positive influence of growth rate on the abundance of O. cordata in the living habitats (paddyfield and spring). In contrast, water depth but not growth rate determined the abundance of O. cordata in the living habitat (stream). However, water depth had a significantly negative impact on the abundance of O. cordata in stream habitats, likely because all of the streams were shallow. Altogether, in the short term for avoiding the potential harm or even extinction of O. cordata, keeping appropriate water depth or transplanting O. cordata to spring should be an effective strategy because the water is not only deep enough but also clear in spring habitats. Additionally, water turbidity was shown to affect the density of O. cordata growth, wherein O. cordata was sparsely distributed when turbidity was high. Therefore, in the long run, to make the population gradually recovery, it will be necessary to restore the degraded wetland. This could be accomplished by reducing water pollution and removing sludge to reduce turbidity and increase hydrological connectivity.