Abstract

Abstract. Boreal forests are subject to a wide range of temporally and spatially variable environmental conditions driven by season, climate, and disturbances such as forest harvesting and climate change. We captured dissolved organic carbon (DOC) from surface organic (O) horizons in a boreal forest hillslope using passive pan lysimeters in order to identify controls and hot moments of DOC mobilization from this key C source. We specifically addressed (1) how DOC fluxes from O horizons vary on a weekly to seasonal basis in forest and paired harvested plots and (2) how soil temperature, soil moisture, and water input relate to DOC flux trends in these plots over time. The total annual DOC flux from O horizons contain contributions from both vertical and lateral flow and was 30 % greater in the harvested plots than in the forest plots (54 g C m−2 vs. 38 g C m−2, respectively; p=0.008). This was despite smaller aboveground C inputs and smaller soil organic carbon stocks in the harvested plots but analogous to larger annual O horizon water fluxes measured in the harvested plots. Water input, measured as rain, throughfall, and/or snowmelt depending on season and plot type, was positively correlated to variations in O horizon water fluxes and DOC fluxes within the study year. Soil temperature was positively correlated to temporal variations of DOC concentration ([DOC]) of soil water and negatively correlated with water fluxes, but no relationship existed between soil temperature and DOC fluxes at the weekly to monthly scale. The relationship between water input to soil and DOC fluxes was seasonally dependent in both plot types. In summer, a water limitation on DOC flux existed where weekly periods of no flux alternated with periods of large fluxes at high DOC concentrations. This suggests that DOC fluxes were water-limited and that increased water fluxes over this period result in proportional increases in DOC fluxes. In contrast, a flushing of DOC from O horizons (observed as decreasing DOC concentrations) occurred during increasing water input and decreasing soil temperature in autumn, prior to snowpack development. Soils of both plot types remained snow-covered all winter, which protected soils from frost and limited percolation. The largest water input and soil water fluxes occurred during spring snowmelt but did not result in the largest fluxes of DOC, suggesting a production limitation on DOC fluxes over both the wet autumn and snowmelt periods. While future increases in annual precipitation could lead to increased DOC fluxes, the magnitude of this response will be dependent on the type and intra-annual distribution of this increased precipitation.

Highlights

  • Boreal forests occupy 11 % of the total land surface and span a variety of topographies and climate zones (Bonan and Shugart, 1989)

  • This study revealed a 30 % greater annual mobilization of dissolved organic carbon (DOC) from O horizons in 10-year-old harvested plots compared with forest plots

  • To monthly timescales, both forest and harvested O horizon DOC flux patterns mirrored those of water fluxes, while the contribution of DOC concentration variations to observed temporal differences was less evident in DOC flux patterns (Fig. 2d, e, f)

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Summary

Introduction

Boreal forests occupy 11 % of the total land surface and span a variety of topographies and climate zones (Bonan and Shugart, 1989) They contain organic-matter-rich soils that store approximately 19 % of the global soil organic carbon (SOC) pool (Pan et al, 2011). While losses of SOC as CO2 to the atmosphere, representing approximately 40 % of boreal forest gross primary production (Luyssaert et al, 2007), are accounted for, losses of SOC as DOC to surface waters are often not included in carbon budget models. This is despite the potential for DOC losses to offset ecosystem carbon sink estimates (Gielen et al, 2011; Webb et al, 2019). A mechanistic understanding of the role of DOC at the ecosystem scale is necessary for accurate accounting of the net ecosystem carbon balance (NECB) and for predicting how ecosystems will function under changing environmental conditions (Chapin et al, 2006; Marin-Spiotta et al, 2014)

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