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Dynamics of Postfire Aboveground Carbon in a Chronosequence of Chinese Boreal Larch Forests
Author(s) -
Yang Yuan Z.,
Cai Wen H.,
Yang Jian,
White Megan,
Lhotka John M.
Publication year - 2018
Publication title -
journal of geophysical research: biogeosciences
Language(s) - English
Resource type - Journals
eISSN - 2169-8961
pISSN - 2169-8953
DOI - 10.1029/2018jg004702
Subject(s) - chronosequence , larch , taiga , environmental science , boreal , ecosystem , snag , ecology , carbon sink , disturbance (geology) , forestry , forest ecology , carbon cycle , physical geography , geography , geology , biology , habitat , paleontology
Boreal forests store a large proportion of the global terrestrial carbon (C), while wildfire plays a crucial role in determining their C storage and dynamics. The aboveground C (AC) pool is an important component of forest C stocks. To quantify the turning point (transforming from C source to C sink) and recovery time of postfire AC, and assess how stand density affects the AC, 175 plots from eight stand age classes were surveyed as a chronosequence in the Great Xing'an Mountains of Northeast China. Linear and nonlinear regression analyses were conducted to describe postfire AC recovery patterns. The results showed that (1) postfire AC exhibited a skewed U‐shaped pattern with the turning point at approximately year 30, when the change rate of AC shifted from negative to positive, (2) it took more than 120 years for this forest ecosystem to recover 80% of AC in unburned old‐growth (200 years) stands, and (3) there was an overall positive relationship between AC and stand density over the entire range of stand age classes; and such relationship was stronger during the early‐ and late‐successional stages, but weaker ( p > 0.05) during the midsuccessional stage. Although boreal larch forests have been C sinks under historical fire free intervals, predicted increases in fire frequency could potentially shift it to a C source. Understanding postfire AC dynamics in boreal larch forests is central to predicting C cycling response to wildfire and provides a framework for assessing ecosystem resilience to disturbance in this region.