Passive Rewilding of Old‐Established Plantations Into Native Forests

Aim: Do multiple environmental conditions filter plant communities in non-native plantations similarly to the natural forests? Do upper forest layers act as additional filters on understory plant diversity? How do multiple environmental conditions and forest structure affect rewilding?. Location: Trentino region (Italy). Methods: Using a stratified random sampling design approach encompassing different elevations and aspects in non-native old-established black pine plantations of the eastern European Alps, we sampled 55 plots over 6200 km2 in which we collected data on abiotic conditions and species cover for each forest layer (tree, shrub, herb), and forest regeneration (i.e., woody juvenile species). We adopted structural equation models (SEMs) to investigate the causal relationships between multiple environmental conditions and forest layer interactions on alpha and beta plant diversity. Furthermore, we ran redundancy analysis (RDA) to test for the effect of multiple environmental conditions and forest structural parameters on the ecology of the herbaceous communities. Results: High- and low-elevation sites had reduced alpha diversity likely because of frost and drought climatic constraints. Shaded conditions due to tree canopy cover directly reduced alpha shrub diversity, and indirectly the herb diversity. Beta diversity of each layer was mainly influenced by slope and elevation. The composition of trees set off a cascading effect, shaping shrub communities and, in turn, the herbaceous and juvenile layers below. Conclusions: Non-native old-established plantations close to the native range of black pine showed high diversity coupled with scarce regeneration. Our insights are crucial for understanding the rewilding of old-established plantation forests. Future plantation programs should consider both the multiple spatial scales of the environmental conditions of the sites and the interaction among vegetation layers to achieve effective rewilding.