Suchergebnisse

Background Currently, about 400 million hectares of tropical moist forests worldwide are designated production forests, about a quarter of which are managed by rural communities and indigenous peoples. There has been a gradual impoverishment of forest resources inside selectively logged forests in which the volume of timber extracted over the first cutting cycle was mostly from large, old trees that matured over a century or more and grew in the absence of strong anthropological pressures. In forests now being logged for a second and third time, that volume has not been reconstituted due in part to the lack of implementation of post-logging silvicultural treatments. This depletion of timber stocks renders the degraded forests prone to conversion to other land uses. Although it is essential to preserve undisturbed primary forests through the creation of protected areas, these areas alone will not be able to ensure the conservation of all species on a pan-tropical scale, for social, economic and political reasons. The conservation of tropical forests of tomorrow will mostly take place within human-modified (logged, domesticated) forests. In this context, silvicultural interventions are considered by many tropical foresters and forest ecologists as tools capable of effectively conserving tropical forest biodiversity and ecosystem services while stimulating forest production. This systematic review aims to assess past and current evidence of the impact of silviculture on tropical forests and to identify silvicultural practices appropriate for the current conditions in the forests and forestry sectors of the Congo Basin, Amazonia and Southeast Asia. Methods This systematic review will undertake an extensive search of literature to assess the relative effectiveness of different silvicultural interventions on timber production and the conservation value of forests, and to determine whether there is a relationship between sustainability of timber harvesting and the maintenance/conservation of other ecosystem services and biodiversity in production forests. Data will be extracted for meta-analysis of at least sub-sets of the review questions. Findings are expected to help inform policy and develop evidence-based practice guidelines on silvicultural practices in tropical forests.

Aim: The accurate mapping of forest carbon stocks is essential for understanding the global carbon cycle, for assessing emissions from deforestation, and for rational land-use planning. Remote sensing (RS) is currently the key tool for this purpose, but RS does not estimate vegetation biomass directly, and thus may miss significant spatial variations in forest structure. We test the stated accuracy of pantropical carbon maps using a large independent field dataset. Location: Tropical forests of the Amazon basin. The permanent archive of the field plot data can be accessed at: http://dx.doi.org/10.5521/FORESTPLOTS.NET/2014_1 Methods: Two recent pantropical RS maps of vegetation carbon are compared to a unique ground-plot dataset, involving tree measurements in 413 large inventory plots located in nine countries. The RS maps were compared directly to field plots, and kriging of the field data was used to allow area-based comparisons. Results: The two RS carbon maps fail to capture the main gradient in Amazon forest carbon detected using 413 ground plots, from the densely wooded tall forests of the north-east, to the light-wooded, shorter forests of the south-west. The differences between plots and RS maps far exceed the uncertainties given in these studies, with whole regions over- or under-estimated by > 25%, whereas regional uncertainties for the maps were reported to be < 5%. Main conclusions: Pantropical biomass maps are widely used by governments and by projects aiming to reduce deforestation using carbon offsets, but may have significant regional biases. Carbon-mapping techniques must be revised to account for the known ecological variation in tree wood density and allometry to create maps suitable for carbon accounting. The use of single relationships between tree canopy height and above-ground biomass inevitably yields large, spatially correlated errors. This presents a significant challenge to both the forest conservation and remote sensing communities, because neither wood density nor species ...