Amazon deforestation has been measured by remote sensing for three decades. In comparison, selective logging has been mostly invisible to satellites. We developed a large-scale, high-resolution, automated remote-sensing analysis of selective logging in the top five timber-producing states of the Brazilian Amazon. Logged areas ranged from 12,075 to 19,823 square kilometers per year (±14%) between 1999 and 2002, equivalent to 60 to 123% of previously reported deforestation area. Up to 1200 square kilometers per year of logging were observed on conservation lands. Each year, 27 million to 50 million cubic meters of wood were extracted, and a gross flux of ∼0.1 billion metric tons of carbon was destined for release to the atmosphere by logging.
Investigators from many diverse disciplines—agrono mists, atmospheric chemists, ecologists, geochemists, meteorologists, and microbiologists—all study emissions
The net ecosystem exchange of carbon dioxide was measured by eddy covariance methods for 3 years in two old-growth forest sites near Santarém, Brazil. Carbon was lost in the wet season and gained in the dry season, which was opposite to the seasonal cycles of both tree growth and model predictions. The 3-year average carbon loss was 1.3 (confidence interval: 0.0 to 2.0) megagrams of carbon per hectare per year. Biometric observations confirmed the net loss but imply that it is a transient effect of recent disturbance superimposed on long-term balance. Given that episodic disturbances are characteristic of old-growth forests, it is likely that carbon sequestration is lower than has been inferred from recent eddy covariance studies at undisturbed sites.
Tropical tree height-diameter (H:D) relationships may vary by forest type and region making large-scale estimates of above-ground biomass subject to bias if they ignore these differences in stem allometry. We have therefore developed a new global tropical forest database consisting of 39 955 concurrent H and D measurements encompassing 283 sites in 22 tropical countries. Utilising this database, our objectives were: 1. to determine if H:D relationships differ by geographic region and forest type (wet to dry forests, including zones of tension where forest and savanna overlap). 2. to ascertain if the H:D relationship is modulated by climate and/or forest structural characteristics (e.g. stand-level basal area, A). 3. to develop H:D allometric equations and evaluate biases to reduce error in future local-to-global estimates of tropical forest biomass. Annual precipitation coefficient of variation (PV), dry season length (SD), and mean annual air temperature (TA) emerged as key drivers of variation in H:D relationships at the pantropical and region scales. Vegetation structure also played a role with trees in forests of a high A being, on average, taller at any given D. After the effects of environment and forest structure are taken into account, two main regional groups can be identified. Forests in Asia, Africa and the Guyana Shield all have, on average, similar H:D relationships, but with trees in the forests of much of the Amazon Basin and tropical Australia typically being shorter at any given D than their counterparts elsewhere. The region-environment-structure model with the lowest Akaike's information criterion and lowest deviation estimated stand-level H across all plots to within amedian −2.7 to 0.9% of the true value. Some of the plot-to-plot variability in H:D relationships not accounted for by this model could be attributed to variations in soil physical conditions. Other things being equal, trees tend to be more slender in the absence of soil physical constraints, especially at smaller D. Pantropical and continental-level models provided less robust estimates of H, especially when the roles of climate and stand structure in modulating H:D allometry were not simultaneously taken into account.