Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4758868 | Agricultural and Forest Meteorology | 2018 | 12 Pages |
â¢The quantity of the boreal forest C sink was measured under the gradient N addition.â¢We developed an allometric equation by biomass measurement for larch and birch.â¢Separating the effect of N addition on different C pools will improve current model.â¢Policy makers might consider how using N deposition to reduce C emission.
An increase in nitrogen (N) deposition has been proposed to cause boreal forests to capture and store a globally significant quantity of carbon (C), but the size of the boreal forest C sink remains uncertain after N addition. Therefore, we conducted a N addition experiment using four N addition rates (0, 2.5, 5.0 and 7.5 g N mâ2 yrâ1) in the boreal zone of northeastern China to determine the changes in forest C sequestration and to investigate the mechanisms of the changes in C sequestration after N addition. Our data show that N addition increases the total C sequestration, but the efficiency of this effect is reduced as the N addition rate increases. We also found that the amount and the mechanism of the C sequestration increase in above- and belowground C pools vary with different amounts of N addition. Low- and medium-N addition increased the above- and belowground C sequestration, and the potential mechanisms responsible for such C accumulation include N-induced increases in photosynthesis via a decrease in the foliar C content and increases in root mass via increased plant C allocation in the roots. However, high-N addition decreases aboveground C sequestration by inhibiting photosynthesis and increases belowground C sequestration by inhibiting soil C losses. Our data indicate that the response patterns of above- and belowground C pools to different amounts of N addition may involve several complex biochemical processes and occur by different mechanisms; therefore, separating the effects of N addition on above- and belowground C sequestration will help improve and validate current modeling efforts.