The terrestrial forest carbon pool is poorly quantified, in particular in regions with low forest inventory capacity. By combining multiple satellite observations of synthetic aperture radar (SAR) backscatter around the year 2010, we generated a global, spatially explicit dataset of above-ground live biomass (AGB; dry mass) stored in forests with a spatial resolution of 1 ha. Using an extensive database of 110 897 AGB measurements from field inventory plots, we show that the spatial patterns and magnitude of AGB are well captured in our map with the exception of regional uncertainties in high-carbon-stock forests with AGB >250 Mg ha⁻¹, where the retrieval was effectively based on a single radar observation. With a total global AGB of 522 Pg, our estimate of the terrestrial biomass pool in forests is lower than most estimates published in the literature (426–571 Pg). Nonetheless, our dataset increases knowledge on the spatial distribution of AGB compared to the Global Forest Resources Assessment (FRA) by the Food and Agriculture Organization (FAO) and highlights the impact of a country's national inventory capacity on the accuracy of the biomass statistics reported to the FRA. We also reassessed previous remote sensing AGB maps and identified major biases compared to inventory data, up to 120 % of the inventory value in dry tropical forests, in the subtropics and temperate zone. Because of the high level of detail and the overall reliability of the AGB spatial patterns, our global dataset of AGB is likely to have significant impacts on climate, carbon, and socio-economic modelling schemes and provides a crucial baseline in future carbon stock change estimates. The dataset is available at https://doi.org/10.1594/PANGAEA.894711 (Santoro, 2018).

Although the effect of pollution on forest health and decline received much attention in the 1980s, it has not been considered to explain the ‘Divergence Problem’ in dendroclimatology; a decoupling of tree growth from rising air temperatures since the 1970s. Here we use physical and biogeochemical measurements of hundreds of living and dead conifers to reconstruct the impact of heavy industrialisation around Norilsk in northern Siberia. Moreover, we develop a forward model with surface irradiance forcing to quantify long‐distance effects of anthropogenic emissions on the functioning and productivity of Siberia’s taiga. Downwind from the world’s most polluted Arctic region, tree mortality rates of up to 100% have destroyed 24,000 km² boreal forest since the 1960s, coincident with dramatic increases in atmospheric sulphur, copper, and nickel concentrations. In addition to regional ecosystem devastation, we demonstrate how ‘Arctic Dimming’ can explain the circumpolar ‘Divergence Problem’, and discuss implications on the terrestrial carbon cycle.

Previous regional studies in Siberia have demonstrated climate warming and associated changes in distribution of vegetation and forest types, starting at the end of the 20th century. In this study we used two regional bioclimatic envelope models to simulate potential changes in forest types distribution and developed new regression models to simulate changes in stand height in tablelands and southern mountains of central Siberia under warming 21st century climate. Stand height models were based on forest inventory data (2850 plots). The forest type and stand height maps were superimposed to identify how heights would change in different forest types in future climates. Climate projections from the general circulation model Hadley HadCM3 for emission scenarios B1 and A2 for 2080s were paired with the regional bioclimatic models. Under the harsh A2 scenario, simulated changes included: a 80%-90% decrease in forest-tundra and tundra, a 30% decrease in forest area, a ∼400% increase in forest-steppe, and a 2200% increase in steppe, forest-steppe and steppe would cover 55% of central Siberia. Under sufficiently moist conditions, the southern and middle taiga were simulated to benefit from 21st century climate warming. Habitats suitable for highly-productive forests (30-40 m stand height) were simulated to increase at the expense of less productive forests (10-20 m). In response to the more extreme A2 climate the area of these highly-productive forests would increase 10%-25%. Stand height increases of 10 m were simulated over 35%-50% of the current forest area in central Siberia. In the extremely warm A2 climate scenario, the tall trees (25-30 m) would occur over 8%-12% of area in all forest types except forest-tundra by the end of the century. In forest-steppe, trees of 30-40 m may cover some 15% of the area under sufficient moisture.