Local‐ and landscape‐scale impacts of clear‐cuts and climate change on surface water dissolved organic carbon in boreal forests

Abstract

Forest harvesting and climate change may significantly increase concentrations and fluxes of dissolved organic carbon (DOC) in boreal surface waters. However, the likely magnitude of any effect will vary depending on the landscape-element type and spatial scale. We used a chain of hydrological, empirical, and process-based biogeochemical models coupled to an ensemble of downscaled Regional Climate Model experiments to develop scenario storylines for local-and landscape-scale effects of forest harvesting and climate change on surface water DOC concentrations and fluxes. Local-scale runoff, soil temperature, and DOC dynamics were simulated for a range of forest and wetland landscape-element types and at the larger landscape scale. The results indicated that climate change will likely lead to greater winter flows and earlier, smaller spring peaks. Both forest harvesting and climate change scenarios resulted in large increases in summer and autumn runoff and higher DOC fluxes. Forest harvesting effects were clearly apparent at local scales. While at the landscape scale, approximately 1 mg L À1 (or 10%) of the DOC in surface waters can be attributed to clear-cuts, both climate change and intensified forestry can each increase DOC concentrations by another 1 mg L À1 in the future, which is less than that seen in many waterbodies recovering from acidification. These effects of forestry and climate change on surface water DOC concentrations are additive at a landscape scale but not at the local scale, where a range of landscape-element specific responses were observed.

Using dry and wet year hydroclimatic extremes to guide future hydrologic projections

“…The old greenhouse gas scenario (SRES based) became outdated in the meantime; the new Representative Concentration Pathway (RCP) based scenarios could have been used in current climate change impact studies. However, because the focus of this paper lies on the methodology rather than on the impact results, it is acceptable to rely on an old SRES scenario in line with our other recent studies in this region (Jungqvist et al, 2014;Oni et al, , 2015b. Precipitation and temperature values (2061-2090) were obtained by averaging the values of the RCM grid cell with centre coordinates closest to the centre of the catchment and of its eight neighbouring grid cells.…”

Effects of Climate Change on CO2 Concentration and Efflux in a Humic Boreal Lake: A Modeling Study

“…Predictions of climate‐related changes in stream water concentration of DOC in the boreal zone vary from a slight decline (Laudon et al, ) to a strong increase (Larsen et al, ). Modeling studies estimate a low to moderate increase, roughly of the order of 5% to 15%, in organic carbon concentrations in boreal streams (Holmberg et al, ; Köhler et al, ; Oni et al, ). However, the literature analysis by Laudon et al () suggests that stream water DOC concentration will decline as mean annual atmospheric temperature rises above 3 °C.…”

Soil temperature responses to climate change along a gradient of upland–riparian transect in boreal forest

“…How this might shift under changing climate and/or forest management is a subject of ongoing debate (Grillakis et al 2016;Oni et al 2015). While most climate change studies examine riparian-upland areas as a lumped entity and base assessments on changes in air temperature, less work has focused on spatial variation of soil temperature responses as a metric of climate change.…”

“…The calibrated COUP model was run with bias corrected series to simulate comparable present day RCM simulations and then future RCMs projections (2061-2010) for effective comparison. More information about the bias correction procedure can be found in Supp 2 or elsewhere in the literature (Jungqvist et al 2014;Oni et al 2014Oni et al , 2015Oni et al , 2016 3 Results…”

“…To assess potential climate change impacts, we used outputs from an ensemble of 15 regional climate models (RCM) run under the A1B emission scenario (Supp 2). Each RCM was bias corrected for precipitation and air temperature data using distribution mapping method (see Oni et al 2014Oni et al , 2015. Bias correction was based on monthly values which were estimated from daily weather series available from the Svartberget catchment.…”