Ecological impacts of diversified agroforestry on soil nutrients and bacterial communities in Pinus massoniana plantations in the southern subtropics

Abstract

Converting forests from single-species to mixed-species planting affects soil chemical and biological properties, yet its impacts within medicinal plant-based agroforestry systems remain largely unexamined. This research assessed the soil nutrient spectrum and bacterial community composition in a monoculture Pinus massoniana (CK) and various agroforestry models: (M1) Pinus massoniana and Alpina oxyphylla, (M2) Pinus massoniana and Ficus simplicissima, (M3) Pinus massoniana and Amomum villosum, and (M4) Pinus massoniana and Curcuma longa, within both field soil and rhizosphere environments. Results showed significant (p < 0.05) improvements in soil pH and cation exchange capacity (CEC) in agroforestry systems. Agroforestry models exhibited greater variability in soil macronutrient distribution, including nitrogen, potassium, calcium, magnesium, and sulfur (N, K, Ca, Mg, S), compared to monocultures. Specifically, Curcuma longa (M4C.RS) had 46.12 % higher total N content than monoculture Pinus massoniana. Micronutrients were higher in agroforestry rhizospheres, except for total zinc, which was higher in monoculture Pinus massoniana. Bacterial community analysis revealed dominant phyla including Acidobacteriota, Proteobacteria, Actinobacteria, and Chloroflexi. Agroforestry models had higher abundance of Proteobacteria, while monoculture had higher Acidobacteriota. Alpha diversity metrics, including Chao1 and Shannon indices, indicated higher species richness and evenness in agroforestry models, particularly in the rhizosphere of Amomum villosum (M3A.RS) and Curcuma longa (M4C.RS). Phylogenetic analysis indicated greater genetic diversity in agroforestry models, in terms of species richness and phylogenetic variation especially for Proteobacteria. Cluster analysis and NMDS revealed close grouping of agroforestry models, with dbRDA showing significant associations between environmental variables (pH, CEC, and nutrient profile), emphasizing their critical role in shaping bacterial community composition, supported by Spearman correlation. Functional prediction (PICRUSt2) indicated metabolism as the predominant functional category. Therefore, transition from monoculture to agroforestry, especially with Curcuma longa (M4), significantly enhanced soil fertility and ecosystem sustainability.