Landscape structure, predictability of forest regeneration trajectories, and recovery rate on secondary forests

Abandonment of agricultural lands promotes the global expansion of
secondary forests, which are critical for preserving biodiversity and
ecosystem functions and services. Such roles largely depend, however, on
two essential successional attributes, trajectory and recovery rate, which
are expected to depend on landscape-scale forest cover in non- linear
ways. This dataset is the synthesis outcome of 22 independent databases
from studies of woody plant species recovery as part of the research
project entitled "Impacts of landscape structure on secondary
tropical forest regeneration". This work aimed to understand the
effect of landscape-level disturbance on forest regeneration, specifically
through the predictability of trajectories and the recovery rate of these
forests. Using a multiscale approach and a large vegetation dataset (843
plots, 3511 tree species) from 22 secondary forest chronosequences
distributed across the Neotropics, we show that successional trajectories
of woody plant species richness, stem density, and basal area are less
predictable in landscapes (4-km radius) with intermediate (40-60%) forest
cover than in landscapes with high (>60%) forest cover. This
supports theory suggesting that high spatial and environmental
heterogeneity in intermediately deforested landscapes can increase the
variation in key ecological factors for forest recovery (e.g. seed
dispersal, seedling recruitment), increasing the uncertainty of
successional trajectories. Regarding the recovery rate, only the species
richness is positively related to forest cover in relatively small (1-km
radius) landscapes. These findings highlight the importance of using a
spatially-explicit landscape approach in restoration initiatives and
suggest that these initiatives can be more effective in more forested
landscapes, especially if implemented across spatial extents of 1-4 km
radius.