The Research On Dynamic Multi-objective Optimization Model Of Forest Structure Under CMIP5 Model

Global climate change significantly affects the growth,distribution,and other processes of forests,so it is particularly critical to predict and optimize forest growth by simulating the growth and harvest of forests under climate change.This paper takes the plot data of Longhushan Forest Farm in South Dongting Lake as the research object,considers the forest growth and change of three different climate scenarios under CMIP5 mode,and combines the technical means of various spatial structure parameters of natural secondary forest to establish the forest level.The multi-objective optimization model of dynamic forest spatial structure under different climate changes,and the performance analysis of the algorithm,the multi-race particle swarm optimization(MRPSO)was selected to optimize and evaluate the forest spatial structure.It has important theoretical and practical significance for promoting the health and stability of natural secondary forests.The main research work and conclusions of this paper are as follows:(1)Analyzed the climate change trend of the sample plots from 1980 to 2016,and found that the changes of temperature and rainfall in the plots showed certain regularities and characteristics.The climate simulation output of three different scenarios(typical concentrations RCP2.6,RCP4.5,RCP8.5)in the CMIP5 Earth system model is down-scaled by the ClimateAP model to obtain average climate data for different scenarios,based on the acquired data.The reparameterization method reconstructs the tree height-diameter diameter growth model of forest trees under climate change,and tests and evaluates the model.Finally,based on the forest data of 2018,it predicts three kinds of 2021 according to the model.The growth of forests under climate scenarios and the changes in multiple indicators of forest spatial structure under different climate changes.(2)By testing the performance of four intelligent algorithms,the multi-ethnic particle swarm optimization algorithm has stronger global search ability and faster convergence than the general intelligent optimization algorithm.Therefore,the multi-ethnic PSO algorithm is used to solve the problem.The problem of dynamic multi-objective optimization of forest structure,and the improvement of the algorithm according to the actual situation of forest spatial structure under climate change,the inertia factor calculated by linear decreasing formula is selected,and the climate detection factor is added,and the sample is calculated according to the actual problem.The average growth amount of the dominant tree species is used as the threshold value,and the average value of the Euclidean distance difference between the new fitness value and the original fitness value is used as an environmental detection operator,and the climate change is judged by comparing the magnitude of the sum.(3)According to the existing multi-objective optimization model of natural forest dynamic spatial structure,the mixed degree,competition index,angular scale,forest index,spatial density,open ratio,size ratio are selected as the optimization objective function.The comprehensive evaluation of forest spatial structure in the district analyzes the problem of spatial structure optimization,and the forest structure under three climate scenarios(RCP2.6,RCP4.5,RCP8.5)in 2018 and 2021 respectively.The experimental simulation is carried out,and the corresponding forest adjustment strategy is given to optimize the forest structure.Then,the target indexes of the forest stands before and after the adjustment are compared,and the adjusted mixed degree,forest index,open ratio,health are obviously found.The degree and the stand homogeneity index increased compared with the previous one.The competition index,angular scale and spatial density index decreased compared with the previous one.At the same time,the experiment found that the sensitivity of each indicator under different climate scenarios The degree is different,and the extent of the change is different.This paper explores the growth of forest trees in the future three climate scenarios under CMIP5 mode and the changes of forest spatial structure under different climate scenarios,and uses improved multi-ethnic groups.The PSO algorithm performs dynamic multi-objective optimization of forest spatial structure under climate change.The research shows the importance of forest spatial structure optimization under different clinmate scenarios,and provides certain operational measures and technical support for future forest response to climate change.