RESUMO
Understanding the invasion of moso bamboo (Phyllostachys edulis) into adjacent evergreen broadleaf forest based on functional traits is crucial due to its significant influence on ecosystem processes. However, existing research has primarily focused on above- or below-ground traits in isolation, lacking a comprehensive integration of both. In this study, we conducted a trait-based analysis including 23 leaf traits and 11 root traits in three forest types - bamboo forest, mixed bamboo and broadleaf forest, and evergreen broadleaf forest - to investigate trait differences, phenotypic integration, and above- and below-ground resource strategies in bamboo and broadleaf species. Our findings demonstrated significant differences in leaf and root key traits between bamboo and broadleaf species, strongly supporting the "phenotypic divergence hypothesis". Bamboo exhibited stronger trait correlations compared to broadleaf species, indicating higher phenotypic integration. Above- and below-ground strategies were characterized by trade-offs rather than coordination, resulting in a multi-dimensional trait syndrome. Specifically, a unidimensional leaf economics spectrum revealed that bamboo with higher leaf N concentrations (LNC), P concentrations (LPC), and specific leaf area (SLA) adopted a "fast acquisitive" above-ground strategy, while broadleaf species with thicker leaves employed a "slow conservative" above-ground strategy. A two-dimensional root trait syndrome indicated a "conservation" gradient with bamboo adopting a "slow conservative" below-ground strategy associated with higher root tissue density (RTD), and broadleaf species exhibiting a "fast acquisitive" below-ground strategy linked to higher root N concentrations (RNC) and P concentrations (RPC), and a "collaboration" gradient probably ranging from broadleaf species with a "do-it-yourself" strategy characterized by high specific root length (SRL), to bamboo adopting an "outsourcing" strategy with thicker roots. In conclusion, key trait divergence from coexisting broadleaf species, higher phenotypic integration, and multi-dimensional opposite above- and below-ground resource strategies confer competitive advantages to moso bamboo, shedding light on the mechanistic understanding of its invasion into subtropical evergreen broadleaf forest and providing theoretical guidance for maintaining the stability of subtropical forest ecosystem.
RESUMO
Introduction: The pivotal roles of both abundant and rare bacteria in ecosystem function are widely acknowledged. Despite this, the diversity elevational patterns of these two bacterial taxa in different seasons and influencing factors remains underexplored, especially in the case of rare bacteria. Methods: Here, a metabarcoding approach was employed to investigate elevational patterns of these two bacterial communities in different seasons and tested the roles of soil physico-chemical properties in structuring these abundant and rare bacterial community. Results and discussion: Our findings revealed that variation in elevation and season exerted notably effects on the rare bacterial diversity. Despite the reactions of abundant and rare communities to the elevational gradient exhibited similarities during both summer and winter, distinct elevational patterns were observed in their respective diversity. Specifically, abundant bacterial diversity exhibited a roughly U-shaped pattern along the elevation gradient, while rare bacterial diversity increased with the elevational gradient. Soil moisture and N:P were the dominant factor leading to the pronounced divergence in elevational distributions in summer. Soil temperature and pH were the key factors in winter. The network analysis revealed the bacteria are better able to adapt to environmental fluctuations during the summer season. Additionally, compared to abundant bacteria, the taxonomy of rare bacteria displayed a higher degree of complexity. Our discovery contributes to advancing our comprehension of intricate dynamic diversity patterns in abundant and rare bacteria in the context of environmental gradients and seasonal fluctuations.