openAccessArticle: FalsePage Range: 67-67doi: 10.1016/j.ecocom.2012.03.002Harvest Date: 2016-01-12 15:11:21issueName:cover date: 2012-09-01pubType: Original Research Articl

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We investigated the spatial pattern of tree recruitment 15 years after clear‐cutting in two logged strips in the Peruvian Amazon, focusing on differences between seed dispersal modes and cohorts, and relating these to spatial patterns of seed dispersal in the years immediately following clearing. Most trees that recruited in logged strips belonged to taxa dispersed by birds or nonvolant mammals, with smaller numbers dispersed by bats or wind. Seed dispersal patterns differed, with few mammal‐dispersed seeds reaching strips, bird‐dispersed seeds more abundant near the forest edge than strip centers, and bat‐ and wind‐dispersed seeds more evenly distributed. However, this pattern was not reflected in the tree recruits, except in the deferment cut half of strip 2. Different dispersal modes were differentially represented in different cohorts; for example, in strip 1 bird‐dispersed trees predominated in early cohorts, while trees dispersed by nonvolant mammals predominated in later cohorts. Our finding that trees dispersed by mammals (which disperse the majority of commercial trees in Amazonia) successfully regenerate from seed in the interior of logged strips highlights the value of maintaining these animals in forest management systems.

To study the impacts of selective logging behaviors on a forest landscape, we developed an intermediate-scale spatial model to link cross-scale interactions of timber harvesting, a fine-scale human activity, with coarse-scale landscape impacts. We used the Lotka-Volterra predator-prey model with Holling's functional response II to simulate selective logging, coupled with a cellular automaton model to simulate logger mobility and forest fragmentation. Three logging scenarios were simulated, each varying in timber harvesting preference and logger mobility. We quantified forest resilience by evaluating (1) the spatial patterns of forest fragmentation, (2) the time until the system crossed a threshold into a deforested state, and (3) recovery time. Our simulations showed that logging behaviors involving decisions made about harvesting timber and mobility can lead to different spatial patterns of forest fragmentation. They can, together with forest management practices, significantly delay or accelerate the transition of a forest landscape to a deforested state and its return to a recovered state. Intermediate-scale models emerge as useful tools for understanding cross-scale interactions between human activities and the spatial patterns that are created by anthropogenic land use.