• Energy Research

AbstractForests are a substantial terrestrial carbon sink, but anthropogenic changes in land use and climate have considerably reduced the scale of this system1. Remote-sensing estimates to quantify carbon losses from global forests2–5 are characterized by considerable uncertainty and we lack a comprehensive ground-sourced evaluation to benchmark these estimates. Here we combine several ground-sourced6 and satellite-derived approaches2,7,8 to evaluate the scale of the global forest carbon potential outside agricultural and urban lands. Despite regional variation, the predictions demonstrated remarkable consistency at a global scale, with only a 12% difference between the ground-sourced and satellite-derived estimates. At present, global forest carbon storage is markedly under the natural potential, with a total deficit of 226 Gt (model range = 151–363 Gt) in areas with low human footprint. Most (61%, 139 Gt C) of this potential is in areas with existing forests, in which ecosystem protection can allow forests to recover to maturity. The remaining 39% (87 Gt C) of potential lies in regions in which forests have been removed or fragmented. Although forests cannot be a substitute for emissions reductions, our results support the idea2,3,9 that the conservation, restoration and sustainable management of diverse forests offer valuable contributions to meeting global climate and biodiversity targets.

Abstract Species’ traits and environmental conditions determine the abundance of tree species across the globe. The extent to which traits of dominant and rare tree species differ remains untested across a broad environmental range, limiting our understanding of how species traits and the environment shape forest functional composition. We use a global dataset of tree composition of >22,000 forest plots and 11 traits of 1663 tree species to ask how locally dominant and rare species differ in their trait values, and how these differences are driven by climatic gradients in temperature and water availability in forest biomes across the globe. We find three consistent trait differences between locally dominant and rare species across all biomes; dominant species are taller, have softer wood and higher loading on the multivariate stem strategy axis (related to narrow tracheids and thick bark). The difference between traits of dominant and rare species is more strongly driven by temperature compared to water availability, as temperature might affect a larger number of traits. Therefore, climate change driven global temperature rise may have a strong effect on trait differences between dominant and rare tree species and may lead to changes in species abundances and therefore strong community reassembly.

AbstractIn the past, human migrations have been associated with climate change. As our civilizations developed, humans depended less on the environment, in particular on climate, because technological and economic development in the span of human history allowed us to adapt to and overcome environmental discomfort. Asian Russia (east of the Urals to the Pacific) is known to be sparsely populated. The population is concentrated along the forest-steppe in the south, with its comfortable climate and thriving agriculture on fertile soils. We use current and predicted climate scenarios to evaluate the climate comfort of various landscapes to determine the potential for human settlers throughout the 21st century. Climate change scenarios are taken from 20 CMIP5 general circulation models. Two CO2Representative Concentration Pathway scenarios, RCP 2.6 representing mild climate change and RCP 8.5 representing more extreme changes, are applied to the large subcontinental territory of Asian Russia. The ensemble January and July temperature anomaly means and annual precipitation are calculated with respect to the baseline 1961–1990 climate. Three climate indices, which are important for human livelihood and well-being, are calculated based on January and July temperatures and annual precipitation: Ecological Landscape Potential, winter severity, and permafrost coverage. Climates predicted by the 2080s over Asian Russia would be much warmer and milder. Ensemble means do not show extreme aridity. The permafrost zone is predicted to significantly shift to the northeast. Ecological Landscape Potential would increase 1–2 categories from ‘low’ to ‘relatively high’ which would result in a higher capacity for population density across Asian Russia. Socio-economic processes and policy choices will compel the development that will lead to attracting people to migrate throughout the century. Therefore, understanding ecological landscape potential is crucial information for developing viable strategies for long-term economic and social development in preparation for climate migration and strategic adaptation planning.

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.