Understanding the impact of long-term partial substitution of chemical nitrogen fertilizer with organic fertilizers (partial organic fertilizers substitution) on soil nitrogen components, mineralization, and availability is necessary to foresee nitrogen (N) dynamics. The present study was conducted a long-term field experiment to investigate the effect of 12 years of fertilizer application on soil nutrient concentrations, enzymatic activities, and N mineralization in a rubber plantation. Treatments included: unfertilized as control (CK), 100% recommended dose of chemical fertilizer (CF), and integrated application of 50% chemical and 50% organic fertilizer (cow manure) (CF+M). The soil physicochemical properties, including total nitrogen (TN) and six labile N components (microbial biomass nitrogen (MBN), particulate organic nitrogen (PON), dissolved organic nitrogen (DON), light fraction organic nitrogen (LFON)), ammonium nitrogen (NH 4 +-N), and nitrate nitrogen (NO 3 --N); five soil enzymes (urease (UE), leucine aminopeptidase (LAP), N-acetyl-glucosaminidase (NAG), Acid phosphatase activity (AcP), and β-1,4-Glucosidase (BG)), and soil organic nitrogen mineralization were determined. Compared with CF, CF+M treatment significantly increased soil pH, TN, MBN, LFON, DON, PON, NH 4 +-N, NO 3 --N, organic carbon (SOC), total phosphorus (TP), available phosphorus (AP), and available potassium (AK) concentrations, while significantly decreased the soil bulk density (BD) and the proportion of soil silt and clay particles. In 0-20 cm soil layer, CF+M treatment significantly decreased the activities of BG but increased AcP. Meanwhile, CF+M treatment significantly increased the NAG and LAP activities in the topsoil layer and UE activities in the subsoil layer. CF+M treatment had high cumulative mineral N production (N t) and N mineralization potential (N 0) but were low net soil N ammonification rates (Net N AM), net soil N nitrification rates (Net N NM), and net soil N mineralization rates (Net N Min) than CF. The piecewiseSEM analysis showed that 99% of the variation in N t and 97% of N Min were explained, with TN and it’s labile components and soil physicochemical properties being the most important direct influencing factor for N t and Net N Min, respectively. Conclusively, partial organic fertilizers substitution could facilitate N availability and soil N supply capacity by affecting soil organic N mineralization and improving soil environmental condition of the rubber plantation. These results suggest that the combine application of chemical fertilizer and manure is a useful management practice and provide theoretical guidance and scientific basis for rational fertilization of rubber plantations in the tropics.

To date, few studies have assessed the impact of forest conversion or seasonal changes on soil microbial community assembly. To fill this research gap, 16S rRNA and ITS gene sequences were used to evaluate the effects of forest conversion and seasonal changes on the assembly of 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. Thus, forest conversion decreased the importance of stochasticity 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 conversion did not have a direct impact on the assembly of bacterial or fungal communities, but exerted indirect effects via soil pH and soil AK.

The effects of forest conversion from natural forest to agricultural system on soil microbial composition still need further study. Especially, impact on soil function after forest conversion is not yet known. In this study, by using metagenomic sequencing as well as 16S and ITS sequencing technology, we evaluated the soil microbial composition, diversity and functions based on a large number of soil samples of tropical rainforest and rubber plantation across the whole island of Hainan, south China. The results showed that (1) forest conversion changed microbial composition from bacterial groups of Proteobacteria to Chloroflexi, and fungal groups from Basidiomycota to Ascomycota. (2) The bacterial alpha diversity, beta diversity as well as the total diversity did not decrease after forest conversion. However, beta diversity of fungal community reduced resulting a net loss of total OTU richness. (3) There was no difference in soil functional compositions and diversity between rubber plantations and rainforest, however, the relative gene abundance of most COG functions, KEGG functions, CAZy functions as well as Antibiotic gene were significantly different between rubber plantation and tropical rainforest. (4) Soil pH and environmental heterogeneity were the main driver for microbial taxonomic composition and gene functional composition. Land use did not result in changes of functional gene composition, but the relative abundance of functional gene. The changed relative abundance gene would alter the ecosystem processes. In conclusion, our results confirmed that land use changes alter the soil microbial community structure and can have profound effects on ecosystem functions and processes.