Erratum: Inter-comparison of multiple statistically downscaled climate datasets for the Pacific Northwest, USA.

This corrects the article DOI: 10.1038/sdata.2018.

Inter-comparison of multiple statistically downscaled climate datasets for the Pacific Northwest, USA.

Statistically downscaled climate data have been widely used to explore possible impacts of climate change in various fields of study. Although many studies have focused on characterizing differences in the downscaling methods, few studies have evaluated actual downscaled datasets being distributed publicly. Spatially focusing on the Pacific Northwest, we compare five statistically downscaled climate datasets distributed publicly in the US: ClimateNA, NASA NEX-DCP30, MACAv2-METDATA, MACAv2-LIVNEH and WorldClim.

Modeling long-term changes in tundra carbon balance following wildfire, climate change, and potential nutrient addition.

To investigate the underlying mechanisms that control long-term recovery of tundra carbon (C) and nutrients after fire, we employed the Multiple Element Limitation (MEL) model to simulate 200-yr post-fire changes in the biogeochemistry of three sites along a burn severity gradient in response to increases in air temperature, CO concentration, nitrogen (N) deposition, and phosphorus (P) weathering rates. The simulations were conducted for severely burned, moderately burned, and unburned arctic tundra. Our simulations indicated that recovery of C balance after fire was mainly determined by the internal redistribution of nutrients among ecosystem components (controlled by air temperature), rather than the supply of nutrients from external sources (e.

Modeling carbon-nutrient interactions during the early recovery of tundra after fire.

Fire frequency has dramatically increased in the tundra of northern Alaska, USA, which has major implications for the carbon budget of the region and the functioning of these ecosystems, which support important wildlife species. We investigated the postfire succession of plant and soil carbon (C), nitrogen (N), and phosphorus (P) fluxes and stocks along a burn severity gradient in the 2007 Anaktuvuk River fire scar in northern Alaska. Modeling results indicated that the early regrowth of postfire tundra vegetation was limited primarily by its canopy photosynthetic potential, rather than nutrient availability, because of the initially low leaf area and relatively high inorganic N and P concentrations in soil.

Uncertainty analysis of vegetation distribution in the northern high latitudes during the 21st century with a dynamic vegetation model.

This study aims to assess how high-latitude vegetation may respond under various climate scenarios during the 21st century with a focus on analyzing model parameters induced uncertainty and how this uncertainty compares to the uncertainty induced by various climates. The analysis was based on a set of 10,000 Monte Carlo ensemble Lund-Potsdam-Jena (LPJ) simulations for the northern high latitudes (45(o)N and polewards) for the period 1900-2100. The LPJ Dynamic Global Vegetation Model (LPJ-DGVM) was run under contemporary and future climates from four Special Report Emission Scenarios (SRES), A1FI, A2, B1, and B2, based on the Hadley Centre General Circulation Model (GCM), and six climate scenarios, X901M, X902L, X903H, X904M, X905L, and X906H from the Integrated Global System Model (IGSM) at the Massachusetts Institute of Technology (MIT).