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.

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Classification and inventory of the current diversity of forest communities and their environments (i.e. site conditions) were developed based on Kolesnikov's topogenetic classification approach in Angara region (Central Siberia). This classification considers characteristics of forest regeneration dynamics, such as trends and rates of forest regeneration succession in a range of site conditions; therefore, it is used as a basis of a key for a forest regeneration dynamics map. An algorithm of forest regeneration dynamics mapping based on a spatial analysis of multi-band satellite data, a digital elevation model (DEM), and ground data combined with expert estimates of the resulting land cover classes was applied using geographic information system (GIS) "Forests of Central Siberia". Based on this algorithm, Landsat 7 ETM+ satellite imagery, SRTM-3-DEM, and field data were processed for the Angara test site. The resulting maps include two polygonal vector layers: one is forest regeneration stages (stand types) and the other is forest succession series (forest types) in a range of site conditions.

Key words: Central Siberia, site conditions and forest type mapping, geographical information system (GIS), digital elevation model (DEM), remote sensing data. RESUMENSe aplicó un método de clasificación y mapeo automatizado basado en el análisis espacial de un modelo de elevación digital (Shuttle Radar Topography Mission (SRTM) 90m), imágenes satelitales Landsat 5-TM y datos de campo con el fin de clasificar y mapear la condición y vegetación forestal en sitios de prueba. Los mapas vectoriales obtenidos reflejan las condiciones ambientales potenciales del sitio de prueba, los tipos de bosque y los estados sucesionales de la regeneración de la vegetación.Palabras clave: Siberia Central, mapeo de condiciones de sitio y del tipo de bosque, sistema de información geográfica (SIG), modelo de elevación digital (DEM), datos de sensores remotos.

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