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Dryad

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

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Dec 05, 2022 version files 7.60 KB

Abstract

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.