Competition indices after reduced impact logging in the Brazilian Amazon.

Competition for resources can affect growth and increase mortality in forest stands. The effects of this process are little known, especially in areas subjected to forest management which show distinct growth dynamics when compared to unmanaged natural areas. This study aimed to estimate, evaluate and select the best fit competition indices (CI) for individual trees in a managed forest in the eastern Amazon. The data used originated from 18 permanent plots of 1 ha each, which were monitored for 12 years after Reduced Impact Logging (RIL). For the competition analysis, 23 indices were tested. CIs were evaluated based on graphical analyses and linear correlation coefficients(r)between each index and variables, basal area growth(ΔG), probability of mortality(Pm), and post-logging period (PLP). In addition, the partial F-test was applied to verify how well the calculated CIs explain the variations observed in ΔGandP(m). The distance-independent index for BAL (Basal Area Larger) performed the best. For the distance-dependent and semi-independent indices, the best interactions with the variables tested occurred in radii of 15 and 20 m away from the object tree. The largest trees presented higher values ofΔG. While P(m)was similar among the three tree classes, larger trees had a slightly higher P(m)due to thier low density of individuals. The results obtained in this study may help to include CIs in growth and production models at the individual tree level in tropical rainforests, especially in those managed in the Brazilian Amazon.

A 7000-year history of changing plant trait composition in an Amazonian landscape; the role of humans and climate.

Tropical forests are shifting in species and trait composition, but the main underlying causes remain unclear because of the short temporal scales of most studies. Here, we develop a novel approach by linking functional trait data with 7000 years of forest dynamics from a fossil pollen record of Lake Sauce in the Peruvian Amazon. We evaluate how climate and human disturbances affect community trait composition. We found weak relationships between environmental conditions and traits at the taxon level, but strong effects for community-mean traits. Overall, community-mean traits were more responsive to human disturbances than to climate change; human-induced erosion increased the dominance of dense-wooded, non-zoochorous species with compound leaves, and human-induced fire increased the dominance of tall, zoochorous taxa with large seeds and simple leaves. This information can help to enhance our understanding of forest responses to past environmental changes, and improve predictions of future changes in tropical forest composition.

A methodological framework to assess the carbon balance of tropical managed forests.

BACKGROUND: Managed forests are a major component of tropical landscapes. Production forests as designated by national forest services cover up to 400 million ha, i.e. half of the forested area in the humid tropics. Forest management thus plays a major role in the global carbon budget, but with a lack of unified method to estimate carbon fluxes from tropical managed forests. In this study we propose a new time- and spatially-explicit methodology to estimate the above-ground carbon budget of selective logging at regional scale. RESULTS: The yearly balance of a logging unit, i.e. the elementary management unit of a forest estate, is modelled by aggregating three sub-models encompassing (i) emissions from extracted wood, (ii) emissions from logging damage and deforested areas and (iii) carbon storage from post-logging recovery. Models are parametrised and uncertainties are propagated through a MCMC algorithm. As a case study, we used 38 years of National Forest Inventories in French Guiana, northeastern Amazonia, to estimate the above-ground carbon balance (i.e. the net carbon exchange with the atmosphere) of selectively logged forests. Over this period, the net carbon balance of selective logging in the French Guianan Permanent Forest Estate is estimated to be comprised between 0.12 and 1.33 Tg C, with a median value of 0.64 Tg C. Uncertainties over the model could be diminished by improving the accuracy of both logging damage and large woody necromass decay submodels. CONCLUSIONS: We propose an innovating carbon accounting framework relying upon basic logging statistics. This flexible tool allows carbon budget of tropical managed forests to be estimated in a wide range of tropical regions.

Carbon recovery dynamics following disturbance by selective logging in Amazonian forests.

When 2 Mha of Amazonian forests are disturbed by selective logging each year, more than 90 Tg of carbon (C) is emitted to the atmosphere. Emissions are then counterbalanced by forest regrowth. With an original modelling approach, calibrated on a network of 133 permanent forest plots (175 ha total) across Amazonia, we link regional differences in climate, soil and initial biomass with survivors' and recruits' C fluxes to provide Amazon-wide predictions of post-logging C recovery. We show that net aboveground C recovery over 10 years is higher in the Guiana Shield and in the west (21 ±3 Mg C ha-1) than in the south (12 ±3 Mg C ha-1) where environmental stress is high (low rainfall, high seasonality). We highlight the key role of survivors in the forest regrowth and elaborate a comprehensive map of post-disturbance C recovery potential in Amazonia.

Rapid tree carbon stock recovery in managed Amazonian forests.

While around 20% of the Amazonian forest has been cleared for pastures and agriculture, one fourth of the remaining forest is dedicated to wood production. Most of these production forests have been or will be selectively harvested for commercial timber, but recent studies show that even soon after logging, harvested stands retain much of their tree-biomass carbon and biodiversity. Comparing species richness of various animal taxa among logged and unlogged forests across the tropics, Burivalova et al. found that despite some variability among taxa, biodiversity loss was generally explained by logging intensity (the number of trees extracted). Here, we use a network of 79 permanent sample plots (376 ha total) located at 10 sites across the Amazon Basin to assess the main drivers of time-to-recovery of post-logging tree carbon (Table S1). Recovery time is of direct relevance to policies governing management practices (i.e., allowable volumes cut and cutting cycle lengths), and indirectly to forest-based climate change mitigation interventions.