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Soil quality is a critically important component of soil within ecosystems, and our understanding of soil quality variation and its driving factors in tropical forests is limited. This study collected soil samples at 0–20 cm depths from two typical tropical forests (tropical rainforest and rubber plantation) on Hainan Island, China's largest tropical island, during dry and rainy seasons. A soil quality index (SQI) using principal component analysis was applied to measure soil quality based on 21 soil properties. The soil properties' spatial and seasonal changes and their driving factors were simultaneously collected for a holistic analysis of the ecosystems. The results were summarized as follows: (i) The SQI of the rubber plantation decreased by 26.48% compared to the tropical rainforest on the island, while four soil properties investigated (soil pH, total phosphorus, cellulose decomposition, and actinomycetes) increased. (ii) The SQI of different soil types in the two tropical forests displayed an apparent discrepancy. Within the same soil type, the SQI of tropical rainforests showed no obvious differences, while there was a notable spatial discrepancy among rubber plantations in dispersed geographical positions belonging to varied climatic zones. (iii) The SQI of the tropical rainforest was significantly higher in the wet season than in the dry season. In contrast, there were no significant differences between the two seasons for rubber plantations, indicating that soil quality in the tropical rainforest was more sensitive to seasonal changes than soil quality in rubber plantations. Overall, we concluded that except for land use and soil type, spatial variability and seasonal pattern also played essential roles in soil quality on the tropical island. The results from the SQI are expected to provide novel information regarding the sustainable use of tropical forests on Hainan Island. [ABSTRACT FROM AUTHOR]

The experiment was conducted to study the effect of low protein diets supplemented with threonine on growth performance and feed digestibility of Hainan pigs. 64 Hainan pigs with the body weight of (55.31±3.09) kg were randomly divided into four groups, with four replicates in each group and four pigs in each replicate. The pigs in control group were fed with 16% crude protein level and 0.6% threonine level. The crude protein level of trial groups I, group II and group III was 14%, and the supplemental level of threonine was 0.6%, 0.8% and 1.0%, respectively. The experimental group was balanced with lysine, tryptophan, valine and arginine. The experiment lasted for 35 d. The results showed that adding threonine to low protein diet to 0.8% could restore the production performance of Hainan pigs to normal diet level (P>0.05). Low protein diet supplemented with threonine significantly increased the apparent digestibility of CP and P of Hainan pigs (P<0.05), and the apparent digestibility of CP of pigs in group III and group II were 13.46% and 12.03% higher than that in control group. Compared with control group, the apparent digestibility of phosphorus of pigs in group II was increased by 9.02%, and that in group III was increased by 8.00% (P<0.05). The experiment indicates that dietary crude protein reduced to 14% and threonine supplemented to 0.8% can improve feed utilization rate without reducing growth rate of Hainan pigs, and it was suggested to be used in production of Hainan pigs. [ABSTRACT FROM AUTHOR]

Land management policies and their spatial planning are crucial factors leading to the rise of future habitat risks. However, the differences in future habitat risks under various spatial policies and their combinations remain unclear, and there is a lack of targeted measures to manage these risks in China's territorial spatial planning. The study developed a feasible framework to tackle this issue. Eight future land use scenarios were simulated based on the combination of land management policies and spatial planning data, and then the habitat risks associated with each scenario were evaluated. Moreover, the study quantified habitat risk variations across diverse scenarios by examining the spatiotemporal changes in risk centers and their associated risk values. Lastly, the study identified critical risk zones based on the assessment results of risk levels and suggested relevant control strategies. The study area chosen was Hainan Island, a region experiencing rapid urbanization and possessing significant ecological resources. The results suggest that while development plans mitigate habitat loss, they accelerate the movement speed of the risk gravity center by up to 5 times. Under the implementation of farmland protection policies, the overall risk levels exhibit a noticeable increase, with the risk level at the center of gravity rising by up to 3.5 times. Implementing ecological protection red lines reduces the transfer rate of habitat risk centers by at least 0.4 times but generally leads to increased habitat risk levels. This study reveals future habitat risk under China's major land management policies and strengthens habitat risk management worldwide. [Display omitted] • A viable framework for managing future habitat risks was established. • Future habitat risks under various planning policies in China were quantified. • Urban construction plans accelerate the movement of risk centers by up to 5 times. • Farmland protection policies escalate the overall risk level by up to 3.5 times. • Ecological protection policies have diverse impacts on future habitat risks. [ABSTRACT FROM AUTHOR]

Soil microbial communities play a crucial role in ecosystem functioning. Past research has examined the effects of forest conversion on soil microbial composition and diversity, but it remains unknown how networks within these communities respond to forest conversion, including when tropical rainforests are replaced with rubber plantations. Microbial networks are viewed as critical indicators of soil health and quality. They consist of two parts: nodes and edges. In this study, we used data from Illumina sequencing and shotgun metagenome sequencing to analyze bacterial and fungal community network structure in a large number of soil samples from tropical rainforests and rubber plantation sites on Hainan Island, China. Our results showed that only 5 %–10 % of shared network edges (i.e., links between species A and B existing in both rubber plantations and rainforests) were observed in both bacterial and fungal communities, which indicates that forest conversion altered the soil microbial network structure. The identity of keystone operational taxonomic units (OTUs) differed entirely between rubber plantation and rainforest sites, further underscoring the altered network structure. More edges and more negative correlations within the soil bacterial–fungal networks were observed at rubber plantation sites (dry season: 4284 total edges, 844 negative; rainy season: 7257 total edges, 1744 negative) than at rainforest sites (dry season: 3650 total edges, 149 negative; rainy season: 6018 total edges, 489 negative), demonstrating that soil bacterial–fungal network structure was more complex and stable in rubber plantations than in rainforests. For bacteria, a larger number of network edges were observed among bacterial networks in samples from tropical rainforest than in samples from rubber plantations, indicating that rainforest bacterial networks were more complex than those from rubber plantations. However, soil fungal networks from rubber plantations showed more links, suggesting that forest conversion increased fungal network complexity. More edges of network and more links between species and functions were observed in the rainy season than in the dry season, indicating that seasonal changes had a strong effect on network structure and function. Further analysis shows that soil pH, potassium (AK), and total nitrogen (TN) had more links with species of some phyla. In conclusion, forest conversion results in an increase in soil pH as well as a decrease in AK and TN, and these changes as well as seasonal variations had a great impact on soil microbial composition, network structure and function. [ABSTRACT FROM AUTHOR]

Land-use changes can alter soil properties and thus affect soil quality. Our understanding of how forest conversion (from tropical rainforest to rubber plantations) affects soil properties and soil quality is limited. An ideal testing ground for analyzing such land-use change and its impacts is Hainan Island, the largest tropical island in China. Based on 21 soil physicochemical and biological properties, a soil quality index (SQI) employed principal component analysis to assess soil quality changes from the conversion of tropical rainforests to rubber plantations. The results showed that (i) soil available potassium, available phosphorus, microbial biomass carbon, cellulose decomposition, acid phosphatase, and urease were vital soil properties for soil quality assessment on Hainan Island. (ii) The SQI of rubber plantations decreased by 26.48% compared to tropical rainforests, while four investigated soil properties (soil pH, total phosphorus, cellulose decomposition, and actinomyces) increased. (iii) The SQI of both the tropical rainforests and rubber plantations showed significant spatial differences, which, under tropical rainforests, was more sensitive to seasonal changes than those under rubber plantations. (iv) Structural equation modeling suggested that forest conversion directly impacted soil quality and, indirectly impacted soil qualities' spatial variation by their interaction with soil types and geographical positions. Overall, though the conversion of tropical rainforest to rubber plantation did not decrease all soil properties, the tropical rainforest with its high soil quality should be protected. [ABSTRACT FROM AUTHOR]

Many studies have been carried‐out on the effects of forest conversion on soil microbial community composition and diversity. However, impacts on soil microbial functions and how diversity changes across scales are poorly understood. To fill the research gap, we used metagenomic sequencing and 16S rRNA and ITS gene sequences to evaluate the microbial composition, diversity, and function of 260 soil samples collected from tropical rainforest and rubber plantation sites across Hainan Island, South China. The results revealed that: (a) Forest conversion resulted in shifts in microbial composition (from the Proteobacteria to Chloroflexi), archaeal composition (from Thaumarchaeota to Bathyarchaeota), and fungal composition (from Basidiomycota to Ascomycota). (b) Bacterial alpha, beta, and gamma diversity were not reduced by forest conversion. However, fungal beta diversity was lower in the plantations, resulting in a decrease in gamma diversity. Archaeal beta diversity was higher in rainforest versus rubber plantation soils, but archaeal gamma diversity showed the opposite pattern. (c) Soil functional composition and diversity did not differ with forest type; however, genes related to metabolism and degradation processes were significantly more abundant in the tropical rainforest. These changes in gene abundance could alter ecosystem processes. (d) Soil pH and environmental heterogeneity were the main drivers of microbial taxonomic composition and functional gene composition. Land use explained 13.28% of the variation in taxonomic composition but did not explain changes in functional gene composition. We concluded that land use changes can alter soil microbial community structure and have profound effects on ecosystem functions and processes. [ABSTRACT FROM AUTHOR]

Updated and accurate maps of tropical forests and industrial plantations, like rubber plantations, are essential for understanding carbon cycle and optimal forest management practices, but existing optical-imagery-based efforts are greatly limited by frequent cloud cover. Here we explored the potential utility of integrating 25-m cloud-free Phased Array type L-band Synthetic Aperture Radar (PALSAR) mosaic product and multi-temporal Landsat images to map forests and rubber plantations in Hainan Island, China. Based on structure information detected by PALSAR and yearly maximum Normalized Difference Vegetation Index (NDVI), we first identified and mapped forests with a producer accuracy (PA) of 96% and user accuracy (UA) of 98%. The resultant forest map showed reasonable spatial and areal agreements with the optical-based forest maps of Fine Resolution Observation and Monitoring Global Land Clover (FROM-GLC) and GlobalLand30. We then extracted rubber plantations from the forest map according to their deciduous features (using minimum Land Surface Water Index, LSWI) and rapid changes in canopies during Rubber Defoliation and Foliation (RDF) period (using standard deviation of LSWI) and dense canopy in growing season (using maximum NDVI). The rubber plantation map yielded a high accuracy when validated by ground truth-based data (PA/UA > 86%) and evaluated with three farm-scale rubber plantation maps (PA/UA >88%). It is estimated that in 2010, Hainan Island had 2.11 × 10 6 ha of forest and 5.15 × 10 5 ha of rubber plantations. This study has demonstrated the potential of integrating 25-m PALSAR-based structure information, and Landsat-based spectral and phenology information for mapping tropical forests and rubber plantations. [ABSTRACT FROM AUTHOR]

Rubber (Hevea brasiliensis Muell.) plantations constitute one of the most important agro-ecosystems in the tropical region of China and Southeast Asia, playing an important role in the carbon budget there. Accurately obtaining their biomass over a large area is challenging because of difficulties in acquiring the Diameter at Breast Height (DBH) through remote sensing and the problem of biomass saturation. The stand age, which is closely related to the forest biomass, was proposed for biomass estimation in this study. A stand age map at an annual scale for Hainan Island, which is the second largest natural rubber production base in China, was generated using all Landsat and Sentinel-2 (LS2) data (1987–2017). Scatter plots and the correlation coefficient method were used to explore the relationship (e.g., biomass saturation) between rubber biomass and different LS2-based variables. Subsequently, a regression model fitted with the stand age (R2 = 0.96) and a Random Forest (RF) model parameterizing with LS2-based variables and/or the stand age were respectively employed to estimate rubber biomass for Hainan Island. The results show that rubber biomass was saturated around 65 Mg/ha with all LS2-based variables. The regression model estimated biomass accurately (R2 = 0.79 and Root Mean Square Error (RMSE) = 14.00 Mg/ha) and eliminated the saturation problem significantly. In addition to LS2-based variables, adding a stand age parameter to the RF models was found to significantly improve the prediction accuracy (R2 = 0.82–0.96 and RMSE = 4.08–10.59 Mg/ha, modeling using samples of different biomass sizes). However, all RF models overestimated the biomass of young plantations and underestimated the biomass of old plantations. A hybrid model integrating the optimal results of RF and regression models reduced estimation bias and generated the best performance (R2 = 0.83 and RMSE = 12.48 Mg/ha). The total rubber biomass of Hainan Island in 2017 was about 5.40 × 107 Mg. The northward and westward expansions after 2000 had great impact on the biomass distribution, leading to a higher biomass density for the inland coastal strip from south to northeast and a lower biomass density in the northern and western regions. [ABSTRACT FROM AUTHOR]

• Land-use changes dominated eco-environmental quality variations in Hainan Island. • Areas of poor eco-environmental quality expanded in residential regions. • Eco-environmental quality of rubber plantation regions increased in Hainan Island. • Eco-environmental quality of rubber plantations was poorer than of forests. Hainan Island is the largest tropical island in China, which is vulnerable to intensifying human activities, such as deforestation and urbanization affecting the quality of the eco-environment on regional scale. To quantify the temporal and spatial changes of the environment, multispectral Landsat data with 30-m spatial resolution was used to establish an Eco-environmental Quality Index (EQI) model for evaluating the ecological status of Hainan Island from 1990 to 2015. According to the EQI value, the study area was divided into different regions marked by five eco-environmental quality levels: excellent , good , normal , poor , and very poor. Finally, temporal and spatial analysis was incorporated into the eco-environmental quality assessment, and the effect of land-use changes on eco-environmental quality was discussed. The results indicated that the overall eco-environmental quality of Hainan Island belonged to the good class but with obvious spatial variation: the eco-environmental quality was excellent in the central mountainous area, good in the flat plane surrounding the mountains, whereas the quality was normal in the coastal areas. From a temporal perspective, the eco-environmental quality of Hainan Island has reduced slightly from 1990 to 2015, while the regions gaining better quality grades have exceeded those becoming worse. Land-use changes dominated eco-environmental quality variations during the study period in Hainan Island: areas of poor eco-environmental quality have expanded in residential regions and eco-environmental quality of rubber plantations has increased since its expanding area has been converted from land of worse eco-environmental quality grades. The EQI results are expected to provide a quantitative foundation for planning sustainable development and the rational use of resources in Hainan Island. [ABSTRACT FROM AUTHOR]

Understanding the assembly of soil microbial communities of tropical forest is of great significance for the protection of biodiversity in tropical areas. Many studies have been carried out on biodiversity and its maintenance mechanism in tropical regions. However, the effects of land use and seasonal variation on the assembly of soil fungal and bacterial communities in tropical forests remains unknown. To fill this research gap, 16S rRNA and ITS sequences were used to evaluate the assembly mechanisms of soil bacterial and fungal communities using 260 soil samples collected from tropical rainforest and rubber plantation sites across Hainan Island, South China. A majority (~60%) of observed OTUs conformed with neutral model expectations, indicating that neutral processes were important for the assembly of soil microbial communities. For bacterial communities, the NST (normalized stochasticity ratio) was higher in the tropical rainforest (0.746 in the dry season, 0.684 in the rainy season) versus rubber plantation sites (0.647, 0.584), regardless of season. This indicated rainforest were more stochastic than rubber plantation for soil bacterial community assembly. For fungal communities, rubber plantation communities showed greater stochasticity (NST = 0.578) than rainforest communities (NST = 0.388) in the dry season, but the reverse was true in the rainy season (NST = 0.852 for rubber plantations; NST = 0.978 for rainforest). Both the NST results and structural equation modeling showed that bacterial communities were more stochastic in the dry season, while fungal communities were more stochastic in the rainy season; the effects of seasonal changes on assembly therefore differed between bacterial and fungal communities. More importantly, forest types did not have a direct impact on the assembly of bacterial or fungal communities, but exerted indirect effects via soil pH and soil available potassium. • Stochastic processes were revealed to have critical effects on community assembly. • Land use did not affect the assembly of community assembly directly. • Soil pH had more influence than season on community assembly. • Forest conversion reduced stochastic processes for bacterial community assembly. • Seasonal changes, affected community assembly, especially for fungal communities. [ABSTRACT FROM AUTHOR]