Distribution and Modelling of Carbon Stocks in Understorey Vegetation and Young Trees in the Xiaoxing'an Mountains Forests

According to the understory vegetation data surveyed in Jiayin County in 2021, the understory vegetation biomass was calculated, the carbon content of each species was measured, the carbon reserves and carbon density of various places were calculated, and the allocation of carbon reserves in the understory vegetation layer was analyzed. The reverse distance interpolation and reclassification tools were used to make the spatial distribution pattern map of the carbon reserves and carbon density of the understory vegetation in Jiayin County. The progressive regression analysis of the carbon reserves and the carbon reserves of shrubs and young layers in Jiayin County: The carbon reserves of understvegetation layer in Jiayin County is 282245.023 t, and the average carbon density is 0.437 t/hm², among which the carbon reserves of shrub and young layer account for 91.65%, and the carbon reserves of herbaceous layer account for 8.35%. The carbon reserve of understory vegetation layer is mainly affected by shrubs and young trees, but less affected by herbs. In terms of spatial distribution, the altitude of high carbon density in shrub and young layer is above 300 m; the area of high carbon density in herbaceous layer is concentrated at 153-474 m; the carbon reserve in understory vegetation layer is consistent with that of shrubs and young layer. The carbon reserves and carbon density in the understory vegetation layer first increased and then decreased with the altitude, and the carbon density reached 0.8956 t / hm 2 at the altitude of 500-600 m. Order of carbon reserves under different altitude forests: hilly area> low mountainous area> plain area; order of carbon density: low mountainous area> hilly area> plain area. If the optimal herb layer carbon storage model was 0.400, there is no collinearity among factors; for the carbon storage model of optimal shrubs and saplings of 6 main forest types, the lowest model fitting R2 was 0.534 and the highest was 0.929, and there is no collinearity among all factors.