Aboveground biomass variability across intact and degraded forests in the Brazilian Amazon

©2016. American Geophysical Union. All Rights Reserved. Deforestation rates have declined in the Brazilian Amazon since 2005, yet degradation from logging, fire, and fragmentation has continued in frontier forests. In this study we quantified the aboveground carbon density (ACD) in intact and degraded forests using the largest data set of integrated forest inventory plots (n = 359) and airborne lidar data (18,000 ha) assembled to date for the Brazilian Amazon. We developed statistical models relating inventory ACD estimates to lidar metrics that explained 70% of the variance across forest types. Airborne lidar-ACD estimates for intact forests ranged between 5.0 ± 2.5 and 31.9 ± 10.8 kg C m−2. Degradation carbon losses were large and persistent. Sites that burned multiple times within a decade lost up to 15.0 ± 0.7 kg C m−2 (94%) of ACD. Forests that burned nearly 15 years ago had between 4.1 ± 0.5 and 6.8 ± 0.3 kg C m−2 (22–40%) less ACD than intact forests. Even for low-impact logging disturbances, ACD was between 0.7 ± 0.3 and 4.4 ± 0.4 kg C m−2 (4–21%) lower than unlogged forests. Comparing biomass estimates from airborne lidar to existing biomass maps, we found that regional and pantropical products consistently overestimated ACD in degraded forests, underestimated ACD in intact forests, and showed little sensitivity to fires and logging. Fine-scale heterogeneity in ACD across intact and degraded forests highlights the benefits of airborne lidar for carbon mapping. Differences between airborne lidar and regional biomass maps underscore the need to improve and update biomass estimates for dynamic land use frontiers, to better characterize deforestation and degradation carbon emissions for regional carbon budgets and Reduce Emissions from Deforestation and forest Degradation (REDD+)

Local and global Fokker-Planck neoclassical calculations showing flow and bootstrap current modification in a pedestal

In transport barriers, particularly H-mode edge pedestals, radial scale lengths can become comparable to the ion orbit width, causing neoclassical physics to become radially nonlocal. In this work, the resulting changes to neoclassical flow and current are examined both analytically and numerically. Steep density gradients are considered, with scale lengths comparable to the poloidal ion gyroradius, together with strong radial electric fields sufficient to electrostatically confine the ions. Attention is restricted to relatively weak ion temperature gradients (but permitting arbitrary electron temperature gradients), since in this limit a delta-f (small departures from a Maxwellian distribution) rather than full-f approach is justified. This assumption is in fact consistent with measured inter-ELM H-Mode edge pedestal density and ion temperature profiles in many present experiments, and is expected to be increasingly valid in future lower collisionality experiments. In the numerical analysis, the distribution function and Rosenbluth potentials are solved for simultaneously, allowing use of the exact field term in the linearized Fokker-Planck collision operator. In the pedestal, the parallel and poloidal flows are found to deviate strongly from the best available conventional neoclassical prediction, with large poloidal variation of a different form than in the local theory. These predicted effects may be observable experimentally. In the local limit, the Sauter bootstrap current formulae appear accurate at low collisionality, but they can overestimate the bootstrap current near the plateau regime. In the pedestal ordering, ion contributions to the bootstrap and Pfirsch-Schluter currents are also modified

Calculation of the bootstrap current profile for the TJ-II stellarator

Calculations of the bootstrap current for the TJ-II stellarator are presented. DKES and NEO-MC codes are employed; the latter has allowed, for the first time, the precise computation of the bootstrap transport coefficient in the long mean free path regime of this device. The low error bars allow a precise convolution of the monoenergetic coefficients, which is confirmed by error analysis. The radial profile of the bootstrap current is presented for the first time for the 100_44_64 configuration of TJ-II for three different collisionality regimes. The bootstrap coefficient is then compared to that of other configurations of TJ-II regularly operated. The results show qualitative agreement with toroidal current measurements; precise comparison with real discharges is ongoing

On the NASA GEDI and ESA CCI biomass maps: aligning for uptake in the UNFCCC global stocktake

Earth Observation data are uniquely positioned to estimate forest aboveground biomass density (AGBD) in accordance with the United Nations Framework Convention on Climate Change (UNFCCC) principles of 'transparency, accuracy, completeness, consistency and comparability'. However, the use of space-based AGBD maps for national-level reporting to the UNFCCC is nearly non-existent as of 2023, the end of the first global stocktake (GST). We conduct an evidence-based comparison of AGBD estimates from the NASA Global Ecosystem Dynamics Investigation and ESA Climate Change Initiative, describing differences between the products and National Forest Inventories (NFIs), and suggesting how science teams must align efforts to inform the next GST. Between the products, in the tropics, the largest differences in estimated AGBD are primarily in the Congolese lowlands and east/southeast Asia. Where NFI data were acquired (Peru, Mexico, Lao PDR and 30 regions of Spain), both products show strong correlation to NFI-estimated AGBD, with no systematic deviations. The AGBD-richest stratum of these, the Peruvian Amazon, is accurately estimated in both. These results are remarkably promising, and to support the operational use of AGB map products for policy reporting, we describe targeted ways to align products with Intergovernmental Panel on Climate Change (IPCC) guidelines. We recommend moving towards consistent statistical terminology, and aligning on a rigorous framework for uncertainty estimation, supported by the provision of open-science codes for large-area assessments that comprehensively report uncertainty. Further, we suggest the provision of objective and open-source guidance to integrate NFIs with multiple AGBD products, aiming to enhance the precision of national estimates. Finally, we describe and encourage the release of user-friendly product documentation, with tools that produce AGBD estimates directly applicable to the IPCC guideline methodologies. With these steps, space agencies can convey a comparable, reliable and consistent message on global biomass estimates to have actionable policy impact

Diverse anthropogenic disturbances shift Amazon forests along a structural spectrum.

Amazon forests are being degraded by myriad anthropogenic disturbances, altering ecosystem and climate function. We analyzed the effects of a range of land-use and climate-change disturbances on fine-scale canopy structure using a large database of profiling canopy lidar collected from disturbed and mature Amazon forest plots. At most of the disturbed sites, surveys were conducted 10?30 years after disturbance, with many exhibiting signs of recovery. Structural impacts differed in magnitude more than in character among disturbance types, producing a gradient of impacts. Structural changes were highly coordinated in a manner consistent across disturbance types, indicating commonalities in regeneration pathways. At the most severely affected site ? burned igapó (seasonally flooded forest) ? no signs of canopy regeneration were observed, indicating a sustained alteration of microclimates and consequently greater vulnerability to transitioning to a more open-canopy, savanna-like state. Notably, disturbances rarely shifted forests beyond the natural background of structural variation within mature plots, highlighting the similarities between anthropogenic and natural disturbance regimes, and indicating a degree of resilience among Amazon forests. Studying diverse disturbance types within an integrated analytical framework builds capacity to predict the risk of degradation-driven forest transitions