<p>Understanding how forest conversion and mycorrhizal disruption shape microbial phosphorus (P) cycling is essential for managing nutrient sustainability in subalpine forest ecosystems. We assessed the influence of long-term land-use change and short-term root trenching (ectomycorrhizal inputs reduction) on phospholipid fatty acid (PLFA)-derived microbial biomass pools, P-related functional genes, enzyme stoichiometry, root litter P mass remaining, and P fractions in paired natural and plantation <i>Picea asperata</i> forests on the eastern Tibetan Plateau. Natural forests exhibited more modular P-related gene networks, higher resin-Pi concentrations, and lower root litter P retention than plantations. Plantation soils had higher abundance of P-mineralization genes than natural forest&#xa0;soils but lower network connectivity and partial fragmentation following root trenching. Piecewise structural equation models revealed that forest type had stronger statistical associations with microbial gene composition, enzyme stoichiometry, and soil P partitioning than root trenching. Root trenching was statistically associated with PLFA-derived microbial biomass pools (PLFA-PC1) shifts that covaried with soil P fractions in natural forests but not in plantations. These findings highlight forest-type-related differences in microbial associations with soil phosphorus fractions and in gene co-occurrence network structure following root trenching. Microbial networks in natural forests were more modular and more strongly associated with soil P fractions, whereas plantations exhibited reduced network connectivity and limited covariation. Recognizing these belowground structural patterns, particularly the potential role of intact root–mycorrhizal networks, may help inform forest management strategies aimed at sustaining microbial-soil P linkages under land-use change. This study provides a data-driven foundation for future hypothesis testing on microbial indicators of biogeochemical variation in forest systems.</p>

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Forest-conversion legacies and root trenching shape PLFA-derived microbial biomass pools and phosphorus-cycling indicators in subalpine forests

  • Lixia Wang,
  • Shiyu Song,
  • Lin Xu,
  • Li Zhang,
  • Han Li,
  • Chengming You,
  • Sining Liu,
  • Hongwei Xu,
  • Jiao Li,
  • Bo Tan,
  • Zhenfeng Xu

摘要

Understanding how forest conversion and mycorrhizal disruption shape microbial phosphorus (P) cycling is essential for managing nutrient sustainability in subalpine forest ecosystems. We assessed the influence of long-term land-use change and short-term root trenching (ectomycorrhizal inputs reduction) on phospholipid fatty acid (PLFA)-derived microbial biomass pools, P-related functional genes, enzyme stoichiometry, root litter P mass remaining, and P fractions in paired natural and plantation Picea asperata forests on the eastern Tibetan Plateau. Natural forests exhibited more modular P-related gene networks, higher resin-Pi concentrations, and lower root litter P retention than plantations. Plantation soils had higher abundance of P-mineralization genes than natural forest soils but lower network connectivity and partial fragmentation following root trenching. Piecewise structural equation models revealed that forest type had stronger statistical associations with microbial gene composition, enzyme stoichiometry, and soil P partitioning than root trenching. Root trenching was statistically associated with PLFA-derived microbial biomass pools (PLFA-PC1) shifts that covaried with soil P fractions in natural forests but not in plantations. These findings highlight forest-type-related differences in microbial associations with soil phosphorus fractions and in gene co-occurrence network structure following root trenching. Microbial networks in natural forests were more modular and more strongly associated with soil P fractions, whereas plantations exhibited reduced network connectivity and limited covariation. Recognizing these belowground structural patterns, particularly the potential role of intact root–mycorrhizal networks, may help inform forest management strategies aimed at sustaining microbial-soil P linkages under land-use change. This study provides a data-driven foundation for future hypothesis testing on microbial indicators of biogeochemical variation in forest systems.