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Ambiguous definitions and metrics create risks for forest conservation and accountability. Since 2005, negotiations under the United Nations Framework Convention on Climate Change (UNFCCC) have focused considerable attention on the role that reducing emissions from deforestation and forest degradation (REDD+) can play in climate change mitigation. As global interest in reducing deforestation has grown, numerous governments, corporate groups, and civil society organizations have set time-bound targets for achieving “zero deforestation.” Some targets specify “net deforestation,” some “gross deforestation,” and some do not specify at all (see the table). Public- and private-sector policy-makers who commit to deforestation reduction targets, and those who advocate for them, are often unclear about their implications. This lack of clarity may lead to perverse outcomes, including governments celebrating reductions of deforestation when large areas of native forest have been cut down and “zero deforestation” certification of agricultural commodities produced on land recently cleared of native forest cover. Progress toward goals of forest conservation, climate change mitigation, and associated cobenefits would be better served and more readily monitored by setting separate time-bound targets for reductions in the clearing of native forests (gross deforestation) and increases in the establishment of new forests on previously cleared lands (reforestation). Net deforestation targets, inherently and erroneously, equate the value of protecting native forests with that of planting new ones.

Estimates of carbon emissions from tropical deforestation differ widely. How much carbon is emitted from tropical deforestation? Attempts to answer this question have generally relied on data from national inventories. More recently, sufficient satellite data have become available to provide independent estimates. On page 1573 of this issue, Harris et al. ( 1 ) report a global estimate of tropical deforestation emissions derived entirely from satellite data. For the period from 2000 to 2005, those emissions are much lower than previously reported.

At the Amazon estuary, the oldest logging frontier in the Amazon, no studies have comprehensively explored the potential long-term population and yield consequences of multiple timber harvests over time. Matrix population modeling is one way to simulate long-term impacts of tree harvests, but this approach has often ignored common impacts of tree harvests including incidental damage, changes in post-harvest demography, shifts in the distribution of merchantable trees, and shifts in stand composition. We designed a matrix-based forest management model that incorporates these harvest-related impacts so resulting simulations reflect forest stand dynamics under repeated timber harvests as well as the realities of local smallholder timber management systems. Using a wide range of values for management criteria (e.g., length of cutting cycle, minimum cut diameter), we projected the long-term population dynamics and yields of hundreds of timber management regimes in the Amazon estuary, where small-scale, unmechanized logging is an important economic activity. These results were then compared to find optimal stand-level and species-specific sustainable timber management (STM) regimes using a set of timber yield and population growth indicators. Prospects for STM in Amazonian tidal floodplain forests are better than for many other tropical forests. However, generally high stock recovery rates between harvests are due to the comparatively high projected mean annualized yields from fast-growing species that effectively counterbalance the projected yield declines from other species. For Amazonian tidal floodplain forests, national management guidelines provide neither the highest yields nor the highest sustained population growth for species under management. Our research shows that management guidelines specific to a region's ecological settings can be further refined to consider differences in species demographic responses to repeated harvests. In principle, such fine-tuned management guidelines could make management more attractive, thus bridging the currently prevalent gap between tropical timber management practice and regulation.

Millions of hectares of future timber concessions are slated to be implemented within large public forests under the forest law passed in 2006 by the Brazilian Congress. Additional millions of hectares of large, privately owned forests and smaller areas of community forests are certified as well managed by the Forest Stewardship Council, based on certification standards that will be reviewed in 2007. Forest size and ownership are two key factors that influence management objectives and the capacity of forest managers to achieve them. Current best ecological practices for timber production from Brazil's native Amazon forests are limited to reduced-impact logging (RIL) systems that minimize the environmental impacts of harvest operations and that obey legal restrictions regarding minimum diameters, rare species, retention of seed trees, maximum logging intensity, preservation of riparian buffers, fire protection, and wildlife conservation. Compared with conventional, predatory harvesting that constitutes >90% of the region's timber production, RIL dramatically reduces logging damage and helps maintain forest cover and the presence of rare tree species, but current RIL guidelines do not assure that the volume of timber removed can be sustained in future harvests. We believe it is counterproductive to expect smallholders to subscribe to additional harvest limitations beyond RIL, that larger private forested landholdings managed for timber production should be sustainable with respect to the total volume of timber harvested per unit area per cutting cycle, and that large public forests should sustain volume production of individual harvested species. These additional requirements would improve the ecological sustainability of forest management and help create a stable forest-based sector of the region's economy, but would involve costs associated with lengthened cutting cycles, reduced harvest intensities, and/or postharvest silviculture to promote adequate growth and regeneration.

Effective monitoring of selective logging from remotely sensed data requires an understanding of the spatial and temporal thresholds that constrain the utility of those data, as well as the structural and ecological characteristics of forest disturbances that are responsible for those constraints. Here we assess those thresholds and characteristics within the context of selective logging in the Bolivian Amazon. Our study combined field measurements of the spatial and temporal dynamics of felling gaps and skid trails ranging from <1 to 19 months following reduced-impact logging in a forest in lowland Bolivia with remote-sensing measurements from simultaneous monthly ASTER satellite overpasses. A probabilistic spectral mixture model (AutoMCU) was used to derive per-pixel fractional cover estimates of photosynthetic vegetation (PV), non-photosynthetic vegetation (NPV), and soil. Results were compared with the normalized difference in vegetation index (NDVI). The forest studied had considerably lower basal area and harvest volumes than logged sites in the Brazilian Amazon where similar remote-sensing analyses have been performed. Nonetheless, individual felling-gap area was positively correlated with canopy openness, percentage liana coverage, rates of vegetation regrowth, and height of remnant NPV. Both liana growth and NPV occurred primarily in the crown zone of the felling gap, whereas exposed soil was limited to the trunk zone of the gap. In felling gaps >400 m², NDVI, and the PV and NPV fractions, were distinguishable from unlogged forest values for up to six months after logging; felling gaps <400 m² were distinguishable for up to three months after harvest, but we were entirely unable to distinguish skid trails from our analysis of the spectral data.

To examine rates of aboveground biomass accumulation (ABA) in global secondary forests following stand-clearing disturbances, we compiled aboveground biomass data from 283 known-age plots drawn from chronosequence and long-term studies. We focused on three likely influences on ABA for which data are readily available: climate, soil texture, and forest type. Growing-season degree-years (GSDY, stand age × growing-season length × growing-season temperature) generally predicted ABA better than stand age alone. Using regression analyses and slope homogeneity tests, we determined that broadleaf forest plots on sandy textured soils exhibited slower GSDY-adjusted ABA than those on nonsandy soils. On nonsandy soils, the GSDY-adjusted ABAs of tropical and nontropical plots were indistinguishable; tropical forest post-disturbance ABA was not particularly slow. Compared to broadleaf forests, needle-leaf forest, GSDY-adjusted ABA was less sensitive to soil texture and was intermediate in rate between sandy and nonsandy broadleaf forest ABA. Foliar nutrient concentration did not significantly influence the GSDY-adjusted ABA of a subset of the nonsandy broadleaf forests for which foliar nutrient data were available. At the global scale, differences in climate (represented by growing-season length and temperature) and moisture-holding capacity (represented by soil texture) are the principal independent factors influencing ABA in most post-disturbance secondary forests.

Despite research demonstrating that water and nutrient availability exert strong effects on multiple ecosystem processes in tropical forests, little is known about the effect of these factors on the demography and population dynamics of tropical trees. Over the course of 5 years, we monitored two common Amazonian secondary forest species—Lacistema pubescens and Myrcia sylvatica—in dry-season irrigation, litter-removal and control plots. We then evaluated the effects of altered water and nutrient availability on population demography and dynamics using matrix models and life table response experiments. Our results show that despite prolonged experimental manipulation of water and nutrient availability, there were nearly no consistent and unidirectional treatment effects on the demography of either species. The patterns and significance of observed treatment effects were largely dependent on cross-year variability not related to rainfall patterns, and disappeared once we pooled data across years. Furthermore, most of these transient treatment effects had little effect on population growth rates. Our results suggest that despite major experimental manipulations of water and nutrient availability—factors considered critical to the ecology of tropical pioneer tree species—autogenic light limitation appears to be the primary regulator of tree demography at early/mid successional stages. Indeed, the effects of light availability may completely override those of other factors thought to influence the successional development of Amazonian secondary forests.

Widespread occurrence of fires in Amazonian forests is known to be associated with extreme droughts, but historical data on the location and extent of forest fires are fundamental to determining the degree to which climate conditions and droughts have affected fire occurrence in the region. We used remote sensing to derive a 23-year time series of annual landscape-level burn scars in a fragmented forest of the eastern Amazon. Our burn scar data set is based on a new routine developed for the Carnegie Landsat Analysis System (CLAS), called CLAS-BURN, to calculate a physically based burn scar index (BSI) with an overall accuracy of 93%% (Kappa coefficient 0.84). This index uses sub-pixel cover fractions of photosynthetic vegetation, non-photosynthetic vegetation, and shade/burn scar spectral end members. From 23 consecutive Landsat images processed with the CLAS-BURN algorithm, we quantified fire frequencies, the variation in fire return intervals, and rates of conversion of burned forest to other land uses in a 32 400 km 2 area. From 1983 to 2007, 15%% of the forest burned; 38%% of these burned forests were subsequently deforested, representing 19%% of the area cleared during the period of observation. While 72%% of the fire-affected forest burned only once during the 23-year study period, 20%% burned twice, 6%% burned three times, and 2%% burned four or more times, with the maximum of seven times. These frequencies suggest that the current fire return interval is 5-11 times more frequent than the estimated natural fire regime. Our results also quantify the substantial influence of climate and extreme droughts caused by a strong El Niño Southern Oscillation (ENSO) on the extent and likelihood of returning forest fires mainly in fragmented landscapes. These results are an important indication of the role of future warmer climate and deforestation in enhancing emissions from more frequently burned forests in the Amazon.

Biomass accumulation in the secondary forests of abandoned pastures and slash-and-burn agricultural fallows is an important but poorly constrained component of the regional carbon budget for the Brazilian Amazon. Using empirical relationships derived from a global analysis, we predicted potential aboveground biomass accumulation (ABA) for the region's regrowth forests based on soil texture and climate data. For regrowth forests on nonsandy soils, the globally derived relationship provided a nearly unbiased linear predictor of Amazonian validation data consisting of 66 stands at seven sites; there was no significant difference between stands that regrew following use as pasture land and those that regrew following slash-and-burn agriculture. For regrowth forests on nonsandy soil, the 1 sigma error range of our ABA model was 58%-171% for the Amazonian validation data. For regrowth forests on sandy soils, the validation data were limited to 19 stands at one site, and the globally derived relationship was substantially biased multiplicatively and nonlinearly. Hence we developed a regional refinement by adding to our validation data ABA values from the two Amazonian sites with sandy soil that had previously been included in the global analysis. Based on a conservative jackknife goodness-of-fit assessment (leaving out one site at a time), we calculated a 1 sigma error range of 42%-158% for our sandy soil Amazonian regrowth forest ABA model. We present our predictions of potential regrowth forest ABA as a set of 0.5° resolution maps for the region at 5, 10, and 20 years following abandonment.

Recent analyses of timber exploitation in Amazonia conclude that a variety of socioeconomic and ecological factors in the region make a stable and profitable logging industry virtually impossible. Most of these studies focus on large-scale timber industries and their dependence on over-exploitation of a small number of high-value timbers. In this article we discuss the economic, ecological, and social aspects of Amazonian logging in a region where the timber industry appeared to have collapsed after stocks of high-value timber were exhausted. We show that forestry in a post-boom phase, currently found in many areas of Amazonia, differs from the better-described \"boom\" period in its scale of operations, in the range of timbers cut, in management practices employed, and in the costs and benefits of production. Results of a seven-year study show that when sawtimber, poles and firewood are produced in a management system that combines forestry and agriculture they can provide significant additional income for Amazonian smallholders.