Patterns of plant trait-environment relationships along a forest succession chronosequence
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Land-use change due to socioeconomic factors leads to the abandonment of traditional intensive coppice management in large areas of the mountainous landscapes of the Apennines (Italy). In this study we explored the multivariate relationship between plant species traits, stage of forest succession and environmental gradients. We focused on community-level patterns in plant traits of the vegetation of beech forest understory along the regeneration chronosequence initiated after cessation of coppicing. We hypothesized that the correlations between the traits and environmental factors should increase with succession age due to the decreasing role of chance. Landscape-level heterogeneity, i.e. changing elevation, slope, exposition, bedrock and forest stand age was assessed using a stratified random sampling design. Sixty sites were sampled for stand structure and species composition. We focused on 14 plant traits related to persistence, growth and dispersal. The recently developed data-analytical method, Model-Based Recursive Partitioning, was used to disentangle the relationships between patterns of plant traits and environmental gradients.About half (seven) of the studied plant traits showed significant correlations with succession stand age, elevation, inclination, heat index and bedrock. Contrary to the low number of trait–environment correlations in early succession, eight traits showed significant relationships with one or more abiotic factors in older stages of the post-coppice development. Stand age had the highest independent explanatory power, explaining 40% of variance of SLA, more than 17% of variance of short-distance seed dispersal and more than 15% of variance of both long-term connection and extensive perennial root. Among the other abiotic factors, elevation explained 27% of variance of SLA, inclination explained 6–8% of variance of long-term connection, extensive perennial root, thickening and large bud bank. The observed trait–environmental relationship is assumed to be driven by various environmental factors operating at various levels of complexity. While forest succession in relatively homogeneous landscapes might be driven mainly by environmental factors related to forest succession itself and associated abiotic changes (such as changes in light and soil moisture patterns), in heterogeneous landscapes the succession pathways may be structured by landscape-level environmental factors such as inclination. However, in the present study, forest stand age had the highest explanatory power for most of the investigated traits, supporting the assumption of the overall strong impact of succession-driven environmental factors in trait–environment relationships.
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