Boreal forest soil carbon fluxes one year after a wildfire: Effects of burn severity and management

The extreme 2018 hot drought that affected central and northern Europe led to the worst wildfire season in Sweden in over a century. The Ljusdal fire complex, the largest area burnt that year (8995 ha), offered a rare opportunity to quantify the combined impacts of wildfire and post-fire management on Scandinavian boreal forests. We present chamber measurements of soil CO2 and CH4 fluxes, soil microclimate and nutrient content from five Pinus sylvestris sites for the first growing season after the fire. We analysed the effects of three factors on forest soils: burn severity, salvage-logging and stand age. None of these caused significant differences in soil CH4 uptake. Soil respiration, however, declined significantly after a high-severity fire (complete tree mortality) but not after a low-severity fire (no tree mortality), despite substantial losses of the organic layer. Tree root respiration is thus key in determining post-fire soil CO2 emissions and may benefit, along with heterotrophic respiration, from the nutrient pulse after a low-severity fire. Salvage-logging after a high-severity fire had no significant effects on soil carbon fluxes, microclimate or nutrient content compared with leaving the dead trees standing, although differences are expected to emerge in the long term. In contrast, the impact of stand age was substantial: a young burnt stand experienced more extreme microclimate, lower soil nutrient supply and significantly lower soil respiration than a mature burnt stand, due to a thinner organic layer and the decade-long effects of a previous clear-cut and soil scarification. Disturbance history and burn severity are, therefore, important factors for predicting changes in the boreal forest carbon sink after wildfires. The presented short-term effects and ongoing monitoring will provide essential information for sustainable management strategies in response to the increasing risk of wildfire

The economics of fungicide use in winter wheat in southern Sweden

In southern Sweden, fungicide treatment of winter wheat is prevalent and recommended almost routinely against leaf blotch diseases. However, yield increases and hence the resulting net returns from fungicide use are highly variable within and between years. These variations raise questions about whether, when and how fungicides should be used. To help answer these questions, a thorough economic evaluation of fungicide use was carried out, based on results from untreated plots and fungicide-treated plots in trials in farmers’ fields, 1983-2007. Scenarios with varying grain prices and costs of fungicide treatment were evaluated and examined. Doubling and tripling the grain price led to the largest impact on the net return from fungicide treatment, followed by increasing cost of the fungicide. Other costs were of minor importance. The mean net return from fungicide use was no more than 12 €/ha over the 25 years (2008 grain prices and costs used in calculations). Furthermore, the mean net return was negative in 10 years and less than 50% of the entries were profitable to treat in 11 years. Changes over time and changes in controllable factors (e.g. fungicide and cultivar choice, crop rotation, techniques) and uncontrollable factors (e.g. emerging and new diseases, price relations) influenced the profitability of fungicide use. Fungicide use was in fact more profitable (mean net return 21 compared with 3 €/ha) during the latter part of the period (1995-2007) than in the earlier part (1983-1994). Improved decision support systems in a holistic framework based on sound economics are urgently needed

Inferring Surface Albedo Prediction Error Linked to Forest Structure at High Latitudes

Predicting the surface albedo of a forest of a given species composition or plant functional type is complicated by the wide range of structural attributes it may display. Accurate characterizations of forest structure are therefore essential to reducing the uncertainty of albedo predictions in forests, particularly in the presence of snow. At present, forest albedo parameterizations remain a nonnegligible source of uncertainty in climate models, and the magnitude attributable to insufficient characterization of forest structure remains unclear. Here we employ a forest classification scheme based on the assimilation of Fennoscandic (i.e., Norway, Sweden, and Finland) national forest inventory data to quantify the magnitude of the albedo prediction error attributable to poor characterizations of forest structure. For a spatial domain spanning ~611,000 km2 of boreal forest, we find a mean absolute wintertime (December–March) albedo prediction error of 0.02, corresponding to a mean absolute radiative forcing ~0.4 W/m2. Further, we evaluate the implication of excluding albedo trajectories linked to structural transitions in forests during transient simulations of anthropogenic land use/land cover change. We find that, for an intensively managed forestry region in southeastern Norway, neglecting structural transitions over the next quarter century results in a foregone (undetected) radiatively equivalent impact of ~178 Mt‐CO2‐eq. year−1 on average during this period—a magnitude that is roughly comparable to the annual greenhouse gas emissions of a country such as The Netherlands. Our results affirm the importance of improving the characterization of forest structure when simulating surface albedo and associated climate effects.publishedVersio