Search

Climate change and land-use activities are increasing fire activity across much of the Siberian boreal forest, yet the climate feedbacks from forest disturbances remain difficult to quantify due to limited information on forest biomass distribution, disturbance regimes and post-disturbance ecosystem recovery. Our primary objective here was to analyse post-fire accumulation of Cajander larch (Larix cajanderi Mayr.) aboveground biomass for a 100 000 km² area of open forest in far northeastern Siberia. In addition to examining effects of fire size and topography on post-fire larch aboveground biomass, we assessed regional fire rotation and density, as well as performance of burned area maps generated from MODIS satellite imagery. Using Landsat imagery, we mapped 116 fire scar perimeters that dated c. 1966--2007.We then mapped larch aboveground biomass by linking field biomass measurements to tree shadows mapped synergistically from WorldView-1 and Landsat 5 satellite imagery. Larch aboveground biomass tended to be low during early succession (≤25 yr, 271±26 gm-2, n = 66 [mean±SE]) and decreased with increasing elevation and northwardly aspect. Larch aboveground biomass tended to be higher during mid-succession (33--38 yr, 746± 100 gm-2, n = 32), though was highly variable. The high variability was not associated with topography and potentially reflected differences in post-fire density of tree regrowth. Neither fire size nor latitude were significant predictors of post-fire larch aboveground biomass. Fire activity was considerably higher in the Kolyma Mountains (fire rotation = 110 yr, fire density = 1.0±1.0 fires yr-1 x 104 km-2) than along the forest-tundra border (fire rotation = 792 yr, fire density = 0.3±0.3 fires yr-1 x 104 km-2). The MODIS burned area maps underestimated the total area burned in this region from 2000--2007 by 40 %. Tree shadows mapped jointly using high and medium resolution satellite imagery were strongly associated (r² ≈ 0.9) with field measurements of forest structure, which permitted spatial extrapolation of aboveground biomass to a regional extent. Better understanding of forest biomass distribution, disturbances and postdisturbance recovery is needed to improve predictions of the net climatic feedbacks associated with landscape-scale forest disturbances in northern Eurasia. [ABSTRACT FROM AUTHOR]

Climate warming and drying are modifying the fire dynamics of many boreal forests, moving them towards a regime with a higher frequency of extreme fire years characterized by large burns of high severity. Plot-scale studies indicate that increased burn severity favors the recruitment of deciduous trees in the initial years following fire. Consequently, a set of biophysical effects of burn severity on postfire boreal successional trajectories at decadal timescales have been hypothesized. Prominent among these are a greater cover of deciduous tree species in intermediately aged stands after more severe burning, with associated implications for carbon and energy balances. Here we investigate whether the current vegetation composition of interior Alaska supports this hypothesis. A chronosequence of six decades of vegetation regrowth following fire was created using a database of burn scars, an existing forest biomass map, and maps of albedo and the deciduous fraction of vegetation that we derived from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery. The deciduous fraction map depicted the proportion of aboveground biomass in deciduous vegetation, derived using a RandomForest algorithm trained with field data sets ( n=69, 71% variance explained). Analysis of the difference Normalized Burn Ratio, a remotely sensed index commonly used as an indicator of burn severity, indicated that burn size and ignition date can provide a proxy of burn severity for historical fires. LIDAR remote sensing and a bioclimatic model of evergreen forest distribution were used to further refine the stratification of the current landscape by burn severity. Our results show that since the 1950s, more severely burned areas in interior Alaska have produced a vegetation cohort that is characterized by greater deciduous biomass. We discuss the importance of this shift in vegetation composition due to climate-induced changes in fire severity for carbon sequestration in forest biomass and surface reflectance (albedo), among other feedbacks to climate. [ABSTRACT FROM AUTHOR]

Boreal forests cover about a fifth of seasonally snow‐covered land over the Northern Hemisphere. Enhancement of longwave radiation beneath coniferous forests has been found to impact the surface energy balance and rates of snowmelt. Although the skill of model‐simulated snowmelt has been shown to be lower for forests than for open areas, model intercomparisons and evaluations of model parameterizations have not yet focused on longwave enhancement. This study uses stand‐scale forcing for the simulation of subcanopy longwave radiation by Community Land Model version 4.5 (CLM4.5) and to drive SNOWPACK, a snow model featuring more complex canopy structure, as a benchmark model for CLM4.5. Simulated subcanopy longwave radiation and longwave enhancement are assessed using measurements from forest stands located within perennially snow‐covered regions. These forest stands, of varying canopy density, cover the range of boreal plant functional types in CLM4.5. CLM4.5 is found to overestimate the diurnal range of subcanopy longwave radiation and longwave enhancement, and simulation errors increase with decreasing cloudiness and increasing vegetation density. Implementation of a parameterization of heat storage by biomass reduces simulation errors but only marginally affects the amplitude of diurnal ranges. These results reaffirm previous findings that simulation of subcanopy longwave radiation can be improved by partitioning the vegetation canopy into two layers. Moreover, this study reveals the variations of simulation errors across meteorological conditions and vegetation density, the latter of which is the most important parameter for longwave enhancement independent of vegetation type. Key Points: Simulation of subcanopy LWR by CLM4.5 was assessed during snowmelt season at forest stands with varying vegetation density and typesDiurnal ranges of subcanopy LWR and LW enhancement are overestimated by CLM4.5 with errors increasing for clearer sky and denser vegetationComparison to SNOWPACK suggests addition of a two‐layer vegetation effect is necessary to reduce overestimated range of LW enhancement [ABSTRACT FROM AUTHOR]