Abstract
•The sheer size and carbon storage capacity of boreal forests make them globally important, while their potential fragility in the face of recent, rapid climatic changes fosters particular interest in these high latitude regions.The DGS extension of LANDIS-II is a free and open-source model that simulates climate, vegetation, wildfire, soil carbon and nitrogen dynamics, soil moisture (1–50 user-defined depths down to 4 m) and temperature (including permafrost down to 75 m) in a fully-coupled, spatially-explicit framework.•Across three field sites, DGS generally captured the variation in soil moisture and temperature across depths, seasons, and years much better than its predecessor NECN, which had unrealistically high seasonal fluctuations in soil temperature and unrealistically low soil moisture.•When DGS was applied at the landscape scale, ignitions, area burned, and soil temperature increased under projected changes in climate, while soil moisture was relatively unchanged.•Simulated biomass declined under climate change, which differs from other modeling studies in this region, but is consistent with the browning trends observed from remote sensing data.•Climate change exacerbated the existing shifts in forest type from conifer to hardwoods, primarily due to declines in the biomass density of black and white spruce.•DGS could be applied in other forested regions to better understand and project vegetation, disturbance, hydrologic, and cryospheric feedbacks and their consequences for species composition and above- and belowground carbon dynamics.
Boreal ecosystems account for 29% of the world's total forested area and contain more carbon than any other terrestrial biome. Over the past 60 years, Alaska has warmed twice as rapidly as the contiguous U.S. and wildfire activity has increased, including the number of fires, area burned, and frequency of large wildfire seasons. These recent and rapid changes in climate and wildfire have implications for future vegetation composition, structure, and biomass in interior Alaska, given that the vegetation is highly dependent on active layer thickness, soil moisture, organic layer depth, and plant-available nutrients. Here we developed a new succession extension (DGS) of the LANDIS-II forest landscape model which integrates a vegetation dynamics model (NECN) with a soil carbon model (DAMM-McNiP), a hydrologic model (SHAW), and a deep soil profile permafrost model (GIPL) in a spatially-explicit framework. DGS Succession uses the algorithms in the NECN Succession extension of LANDIS-II to simulate growth, mortality and reproduction of vegetation but has three major improvements. First, the simple bucket model in NECN was replaced with a physically-based model (SHAW) that simulates energy and water fluxes (e.g. snow depth, evapotranspiration, soil moisture) at multiple levels in the canopy and soil. Second, the active, slow, and passive soil pools in NECN were replaced by seven soil pools that are measurable in the field, with carbon and nitrogen dynamics dictated by DAMM-McNiP. Finally, soil temperature and soil moisture are simulated only at one depth in NECN, but in DGS, soil temperature (and hence permafrost dynamics) are simulated at as many as 50 user-defined depths down to 4 m with SHAW and 75 m with GIPL. During the initial calibration phase, DGS was applied at three inventory sites at the Bonanza Creek Long Term Ecological Research area in Interior Alaska where climate forcings, species biomass, soil temperature, and/or soil moisture were available. For the landscape-scale simulations, DGS was run with the SCRPPLE fire extension of LANDIS-II under two scenarios of climate using a ∼400,000 ha landscape that included the inventory sites. Across all three sites, DGS generally captured the variation in soil moisture and temperature across depths, seasons, and years reasonably well, though there were some discrepancies at each site. DGS had better agreement with field measurements of soil moisture and temperature than its predecessor NECN which produced unrealistically low soil moisture and unrealistically high seasonal fluctuations in soil temperature. At the landscape scale, ignitions, area burned, and soil temperature increased under climate change, as expected, while soil moisture was relatively unchanged across climate scenarios. Biomass tended to decline under climate change, which differs from other modeling studies in this region but is consistent with the browning trends observed from remote sensing data. Simulating climate, vegetation succession, hydrology, permafrost, carbon and nutrient cycling, and wildfire in an integrated, spatially-explicit framework like LANDIS-II will allow us to disentangle the drivers and ecosystem responses in this rapidly changing ecosystem, as well as other forested systems with complex hydrologic, biochemical, cryospheric, and vegetation feedbacks.