Biomass Model Of Common Understory In A Natural Secondary Forest In Maoershan, Northeast China

Biomass is significant in the research of global carbon cycle and climate change. Northeast Temperate forest which is the major distribution of forest account for more than one third of forest resource and play a key role in regulation of China and the global carbon balance and climate change. In this study the Northeast natural secondary forest unerstory shrub as the research object, the establishment of regression equation based on measurement factors (plant height, diameter etc.)and shrub biomass. Based on the exploration of Maoershan Mountain shrub biomass stocks from various natural secondary forest, proposed a feasible method to reduce the uncertaintoy in the estimation of size of the ecosystem carbon pool and carbon sink capacity. Provide basic data for accurate estimation of temperate secondary forest biomass and productivity, for evaluation of northeast natural temperate secondary forest shrub layer ecological functions, for regional ecological construction and development of regional ecosystem carbon sequestration management strategies. Based on 8 typical shrub in northeastern china forest, including Syringa reticulate var. amurensis, Acanthopanax senticosus, Viburnum sargentii, Corylus mandshurica, Euonymus alatus, Spiraea ussuriensis, Ribes mandshuricum, Sorbaria sorbifolia. Studing the relationship between aboveground biomass and related factors of 8 typical shrubs. Using different measurement factors as independent variables, through mathematical modeling, selected the optimal biomass regression equation. Results as follows:(1) Power is the main form of 8shrub biomass models, the distribution range of the correlation coefficient R2 is 0.610～0.918. The form of optimal biomass model of Syringa reticulate var. amurensis, Sorbaria sorbifolia, Euonymus alatus, Corylus mandshurica, Spiraea ussuriensis,, Ribes mandshuricum is Power, the form of optimal biomass model of Acanthopanax senticosus, Viburnum sargentii is Quadratic.(2) Using D,H,DH,D2H as independent variables eatablish biomass model of 8 shrub. The advantages of 4 independent variables as follows:Syringa reticulate var. amurensis DH>D2H>D>H; Acanthopanax senticosus DH>D2H>D>H; Viburnum sargentii DH>D2H>D>H; Corylus mandshurica D2H>DH>D>H; Euonymus alatus D2H>DH>D>H; Spiraea ussuriensis D2H>H>DH>D; Ribes mandshuricum H>DH>D2H>D; Sorbaria sorbifolia DH>D2H>D>H.(3) Biomass models use the relative error method (RS<20%,RMA<30%) for accuracy test. The results as follow:Syringa reticulate var. amurensis RS=28.013, RMA=34.389; Acanthopanax senticosus RS=4.164, RMA=22.669; Viburnum sargentii RS=-3.233, RMA=28.388; Corylus mandshurica RS=1.029, RMA=21.783; Euonymus alatus RS=-2.628, RMA=19.419;Spiraea ussuriensis RS=0.149,RMA=61.357;Ribes mandshuricum RS=-4.624, RMA=61.156;Sorbaria sorbifolia RS=1.892,RMA=24.966.