Developing countries are required to produce robust estimates of forest carbon stocks for successful implementation of climate change mitigation policies related to reducing emissions from deforestation and degradation (REDD). Here we present a “benchmark” map of biomass carbon stocks over 2.5 billion ha of forests on three continents, encompassing all tropical forests, for the early 2000s, which will be invaluable for REDD assessments at both project and national scales. We mapped the total carbon stock in live biomass (above- and belowground), using a combination of data from 4,079 in situ inventory plots and satellite light detection and ranging (Lidar) samples of forest structure to estimate carbon storage, plus optical and microwave imagery (1-km resolution) to extrapolate over the landscape. The total biomass carbon stock of forests in the study region is estimated to be 247 Gt C, with 193 Gt C stored aboveground and 54 Gt C stored belowground in roots. Forests in Latin America, sub-Saharan Africa, and Southeast Asia accounted for 49%, 25%, and 26% of the total stock, respectively. By analyzing the errors propagated through the estimation process, uncertainty at the pixel level (100 ha) ranged from ±6% to ±53%, but was constrained at the typical project (10,000 ha) and national (>1,000,000 ha) scales atca. ±5% andca. ±1%, respectively. The benchmark map illustrates regional patterns and provides methodologically comparable estimates of carbon stocks for 75 developing countries where previous assessments were either poor or incomplete.

Quantifying changes in the rates of forest clearing in Indonesia from 1990 to 2005 usingremotely sensed data sets Matthew C Hansen, Stephen V Stehman, Peter V Potapov et al. Aboveground carbon loss in natural and managed tropical forests from 2000 to 2012 A Tyukavina, A Baccini, M C Hansen et al. Satellite-based primary forest degradation assessment in the Democratic Republic of the Congo, 2000-2010 I Zhuravleva, S Turubanova, P Potapov et al. Using spatial statistics to identify emerging hot spots of forest loss Nancy L Harris, Elizabeth Goldman, Christopher Gabris et al. Remotely sensed forest cover loss shows high spatial and temporal variation acrossSumatera and

A coherent and effective remote sensing (RS) contribution to biodiversity monitoring requires careful consideration of scale in all its dimensions, including spatial, temporal, spectral, and angular, along with biodiversity at different levels of biological organization. Recent studies of the relationship between optical diversity (spectral diversity) and biodiversity reveal a scale dependence that can be influenced by the RS methods used, vegetation type, and degree and nature of disturbance. To better understand these issues, we call for multi-scale field campaigns that test the effect of sampling scale, vegetation type, and degree of disturbance on the ability to detect different kinds of biodiversity, along with the development of improved models that incorporate both physical and biological principles as well as ecological and evolutionary theory. One goal of these studies would be to more closely match instrumentation and sampling scales to biological definitions of biodiversity and so improve optical diversity (spectral diversity) as a proxy for biodiversity. The ultimate goal would be to design and implement a truly effective, “scale-aware” global biodiversity monitoring system employing RS methods. Such a system could improve our understanding of the distribution and functional importance of biodiversity and enhance our ability to manage ecosystems for resilience and sustainability in a changing world.