Regional Forest Soil Respiration Modelling Based On The Finite Sample Points In Guangdong And Guangxi

Soil respiration in forest ecosystems is the basis for estimating carbon flux in terrestrial ecosystems and responding to climate change.Predicting forest soil respiration is of great significance to the study of carbon cycle and climate change in terrestrial ecosystems.Forest soil respiration plays different roles in the carbon cycle and climate change at global,national,regional,and community scales,so the prediction models at different scales(global,national,and regional)have different significance.Accurate estimation of soil respiration at the regional scale is an effective way to realize the dynamics of the global carbon cycle under the background of climate change and is of great significance to production and scientific research.However,due to the limited number of sample points,few studies on soil respiration models are at the regional scale.In this paper,a new idea of regional modeling was proposed:a linear model group with the different parameter of the partitions was established based on limited sample points to modify the predicted values of the large-scale forest soil respiration model,This study tried to solve an insufficient number of regional soil respiration modeling points and establish a regional soil respiration model with good generalization.In this paper,we took Guangxi Zhuang Autonomous Region and Guangdong Province(Guangxi and Guangdong)as the research objects,We selected different regional parameters(forest type,temperature and precipitation)to build linear models based on 32 measured sample points in Guangxi and Guangdong,respectively,to modify the predicted values of the two large-scale models.The best predicted regional parameters were selected as regional models to predict the annual forest soil respiration rate and total quantity from 2000 to 2015 in Guangxi and Guangdong.The conclusions were as follows:(1)The results showed that the accuracy of the global model and the national model decreased by 41%and 53%respectively,when the global model and the national model were directly applied in Guangxi and Guangdong Province.In the original national model,due to the lack of input data,only theoretical modeling was carried out.This paper realized the application of the models.(2)Based on 32 measured sample points in Guangxi and Guangdong,the predicted values of the two large-scale models were modified by the linear models,which selected different regional parameters(forest type,temperature and precipitation)as input data,and the accuracy of each regional model was improved at different levels.Among them,the linear model group of the three regions built by precipitation parameters had the best effect,which improved the accuracy of the global model by 39%,11%and 26%,respectively.Therefore,the modeling method of this study could solve the problem that the number of sample points was not enough for modeling,This method effectively modified the large-scale model,which parameters of the linear model were easy to be generalized to other regions.(3)The regional model RS₁with the highest accuracy was selected to predict the forest soil respiration from 2000 to 2015 in Guangxi and Guangdong.The annual forest soil respiration rate in Guangxi and Guangdong fluctuated between 850-1750 g C·m^-2·a^-1.The minimum during the 16 years was 854.92 g C·m^-2·a^-1of 2004,and the maximum was 1725.07 g C·m^-2·a^-1of 2001.The average soil respiration rate of the16 years was 1287.66 g C·m^-2·a^-1.The total annual soil respiration fluctuated from 295 Tg C·a^-1to 600 Tg C·a^-1during the 16 years.The maximum of total soil respiration was 599.99 Tg C·a^-1of 2001,and the minimum was 297.35 Tg C·a^-1of 2004.The average annual total soil respiration during the 16 years was 447.85 Tg C·a^-1.