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Patterns of biomass, carbon, and nitrogen storage distribution dynamics after the invasion of pine forests by Bursaphelenchus xylophilus (Nematoda: Aphelenchoididae) in the three Gorges Reservoir Region

Gao, Ruihe, Luo, Youqing, Wang, Zhuang, Yu, Hanjun, Shi, Juan
Journal of forestry research 2018 v.29 no.2 pp. 459-470
Bursaphelenchus xylophilus, Pinus, bark, biomass, carbon, coniferous forests, ecological invasion, forest ecosystems, forest litter, forest stands, mineral soils, nitrogen, nitrogen content, overstory, prediction, roots, stemwood, trees, understory, vascular wilt, China
Masson pine stands infected by Pine wilt disease (PWD) in the Three Gorges Reservoir Region of central China were surveyed to quantify the immediate responses and subsequent trajectories of biomass, carbon (C), and nitrogen (N) in stand-level major ecosystem compartments. The biomasses of above- and belowground tree components, as well as of the understory, forest floor, and mineral soil (0–40 cm), were determined within each stand. C and N storage were also estimated for each ecosystem compartment. Overstory biomass decreased steadily with the extent of PWD infection. Understory biomass ranged from 1.97 to 4.16 Mg ha⁻¹, and the observed value for forest floor biomass was 12.89–22.59 Mg ha⁻¹. The highest mean C and N concentrations were found in the stem bark and needles of Masson pine, respectively, while the lowest were found in the semi- to fully decomposed layer of the forest floor and stem wood of Masson pine, respectively. The C and N storage of aboveground trees, tree roots, and the aboveground ecosystem decreased with the extent of PWD infection. However, the C and N contents of the understory, forest floor, and total mineral soil initially declined after PWD infection before recovering over the following several years. Those result concluded that the biomass, C, and N storage of different forest ecosystem compartments have experienced certain variations following the PWD epidemic. This is vital to understand the shifts in stand-level C and N allocation in PWD-damaged forest stands, as well as for predicting the responses of regional and global C and N cycling.