Efforts to mitigate climate change through the Reduced Emissions from Deforestation and Degradation (REDD) depend on mapping and monitoring of tropical forest carbon stocks and emissions over large geographic areas. With a new integrated use of satellite imaging, airborne light detection and ranging, and field plots, we mapped aboveground carbon stocks and emissions at 0.1-ha resolution over 4.3 million ha of the Peruvian Amazon, an area twice that of all forests in Costa Rica, to reveal the determinants of forest carbon density and to demonstrate the feasibility of mapping carbon emissions for REDD. We discovered previously unknown variation in carbon storage at multiple scales based on geologic substrate and forest type. From 1999 to 2009, emissions from land use totaled 1.1% of the standing carbon throughout the region. Forest degradation, such as from selective logging, increased regional carbon emissions by 47% over deforestation alone, and secondary regrowth provided an 18% offset against total gross emissions. Very high-resolution monitoring reduces uncertainty in carbon emissions for REDD programs while uncovering fundamental environmental controls on forest carbon storage and their interactions with land-use change.

African savannas are undergoing management intensification, and decision makers are increasingly challenged to balance the needs of large herbivore populations with the maintenance of vegetation and ecosystem diversity. Ensuring the sustainability of Africa's natural protected areas requires information on the efficacy of management decisions at large spatial scales, but often neither experimental treatments nor large-scale responses are available for analysis. Using a new airborne remote sensing system, we mapped the threedimensional (3-D) structure of vegetation at a spatial resolution of 56 cm throughout 1640 ha of savanna after 6-, 22-, 35-, and 41-year exclusions of herbivores, as well as in unprotected areas, across Kruger National Park in South Africa. Areas in which herbivores were excluded over the short term (6 years) contained 38%-80% less bare ground compared with those that were exposed to mammalian herbivory. In the longer-term (> 22 years), the 3-D structure of woody vegetation differed significantly between protected and accessible landscapes, with up to 11-fold greater woody canopy cover in the areas without herbivores. Our maps revealed 2 scales of ecosystem response to herbivore consumption, one broadly mediated by geologic substrate and the other mediated by hillslope-scale variation in soil nutrient availability and moisture conditions. Our results are the first to quantitatively illustrate the extent to which herbivores can affect the 3-D structural diversity of vegetation across large savanna landscapes.ecological sustainability ͉ ecosystem heterogeneity ͉ Kruger National Park ͉ park management ͉ protected areas ͉ South Africa ͉ vegetation structure

Despite the importance of fire in shaping savannas, it remains poorly understood how the frequency, seasonality, and intensity of fire interact to influence woody vegetation structure, which is a key determinant of savanna biodiversity. We provide a comprehensive analysis of vertical and horizontal woody vegetation structure across one of the oldest savanna fire experiments, using new airborne Light Detection and Ranging (LiDAR) technology. We developed and compared high-resolution woody vegetation height surfaces for a series of large experimental burn plots in the Kruger National Park, South Africa. These 7-ha plots (total area approximately 1500 ha) have been subjected to fire in different seasons and at different frequencies, as well as no-burn areas, for 54 years. Long-term exposure to fire caused a reduction in woody vegetation up to the 5.0-7.5 m height class, although most reduction was observed up to 4 m. Average fire intensity was positively correlated with changes in woody vegetation structure. More frequent fires reduced woody vegetation cover more than less frequent fires, and dry-season fires reduced woody vegetation more than wet-season fires. Spring fires from the late dry season reduced woody vegetation cover the most, and summer fires from the wet season reduced it the least. Fire had a large effect on structure in the densely wooded granitic landscapes as compared to the more open basaltic landscapes, although proportionally, the woody vegetation was more reduced in the drier than in the wetter landscapes. We show that fire frequency and fire season influence patterns of vegetation three-dimensional structure, which may have cascading consequences for biodiversity. Managers of savannas can therefore use fire frequency and season in concert to achieve specific vegetation structural objectives.

High-resolution mapping of tropical forest carbon stocks can assist forest management and improve implementation of large-scale carbon retention and enhancement programs. Previous high-resolution approaches have relied on field plot and/or light detection and ranging (LiDAR) samples of aboveground carbon density, which are typically upscaled to larger geographic areas using stratification maps. Such efforts often rely on detailed vegetation maps to stratify the region for sampling, but existing tropical forest maps are often too coarse and field plots too sparse for high-resolution carbon assessments. We developed a top-down approach for high-resolution carbon mapping in a 16.5 million ha region (> 40%) of the Colombian Amazon – a remote landscape seldom documented. We report on three advances for large-scale carbon mapping: (i) employing a universal approach to airborne LiDAR-calibration with limited field data; (ii) quantifying environmental controls over carbon densities; and (iii) developing stratification- and regression-based approaches for scaling up to regions outside of LiDAR coverage. We found that carbon stocks are predicted by a combination of satellite-derived elevation, fractional canopy cover and terrain ruggedness, allowing upscaling of the LiDAR samples to the full 16.5 million ha region. LiDAR-derived carbon maps have 14% uncertainty at 1 ha resolution, and the regional map based on stratification has 28% uncertainty in any given hectare. High-resolution approaches with quantifiable pixel-scale uncertainties will provide the most confidence for monitoring changes in tropical forest carbon stocks. Improved confidence will allow resource managers and decision makers to more rapidly and effectively implement actions that better conserve and utilize forests in tropical regions

Current markets and international agreements for reducing emissions from deforestation and forest degradation (REDD) rely on carbon (C) monitoring techniques. Combining field measurements, airborne light detection and ranging (LiDAR)‐based observations, and satellite‐based imagery, we developed a 30‐meter‐resolution map of aboveground C density spanning 40 vegetation types found on the million‐hectare Island of Hawaii. We estimate a total of 28.3 teragrams of C sequestered in aboveground woody vegetation on the island, which is 56% lower than Intergovernmental Panel on Climate Change estimates that do not resolve C variation at fine spatial scales. The approach reveals fundamental ecological controls over C storage, including climate, introduced species, and land‐use change, and provides a fourfold decrease in regional costs of C measurement over field sampling alone.