Growth model of carbon storage and driving force of carbon sequestration capacity of natural secondary forests

  Objective  This paper aims to establish a growth model of carbon storage of the natural secondary forests after logging disturbance and the corresponding carbon sink model, so as to analyze the driving effect of different factors on carbon sequestration capacity, which can provide references for quantitative evaluation of carbon sequestration capacity.

  Method  Totally 111 sample plot data for the natural secondary forests were selected based on the data of the 9th National Forest Inventory in Jilin Province of northeastern China. Based on the Richards theoretical growth equation, taking the average tree carbon storage of the sample plot as the dependent variable and the average age of the sample plot as the independent variable, a carbon storage classified growth model was established by grouping the age and iterative algorithm, and the carbon sink classified growth model was obtained by deriving the age in the carbon storage classified growth model. The coefficient of determination (R²) and the root mean square error (RMSE) were used to evaluate the effect of model fitting. Based on a linear model, taking geographical factors, topographic factors, climate factors, soil factors and forest stand factors as independent variables, the interactions of qualitative and quantitative factors were introduced to analyze the driving force of carbon sequestration capacity.

  Result  (1) The R² of the natural secondary forest carbon storage classified growth model was 0.965 6, and the RMSE was 2.612 7 kg, this model had a good goodness of fit. (2) The ages of the largest carbon sinks in each level were 8, 10, 13, 17 and 29 years. Calculated at a density of 1 000 plants per hectare, the threshold between levels in 5 years was 1.84 t/ha, and by 30 years increased to 10.78 t/ha, the threshold between each level increased with age. (3) The first-order qualitative, first-order, and second-order quantitative interaction model had the highest explanation for the average tree carbon storage, and R² was 0.919 2. Compared with the main effect model without interaction terms, R² was increased by 0.088 5. (4) For the average tree carbon storage, geographic factors (longitude and latitude), topographic factors (altitude, landform, slope aspect, slope position and slope degree), litter layer thickness, climate factors (annual average temperature, extreme minimum temperature, humidity index, frost-free days), soil factor (soil thickness) and stand factors (age and dominant tree species) had significant effects. For 20 years of carbon density by different classifications, geographic factor (latitude), topographic factors (landform, slope degree and slope aspect), climate factors (extreme maximum temperature, hottest monthly average temperature and humidity index), soil factors (soil type and gravel content) and stand factor (dominant tree species) had significant effects, while factors such as altitude and humus thickness existed in the interaction terms, and their main effects were not significant.

  Conclusion  The carbon density of different level thresholds of the natural secondary forests is different in varied time periods. With the increase of age, the thresholds between levels continue to increase, but the relative magnitudes in carbon storage between different levels are decreasing. The introduction of interaction could help improve the interpretation degree of forest carbon sequestration. Geographical factors such as latitude, topographical factors such as slope degree and slope aspect, climate factors such as humidity index, and stand factors such as dominant tree species are the key factors affecting the carbon sequestration capacity of the natural secondary forests.