４个竹种高生长模型的比较

Comparison of the Height Growth Tendencies of Four Species of Bamboos

竹子隶属禾本科竹亚科,拥有生长快、成材早、用途广和可再生等优点,竹林还是我国南方森林资源重要组成部分。为合理利用竹类资源,研究不同竹种的生长速率具有重要意义。目前已经存在诸多用于描述温度对外温生物发育速率影响的数学模型,而这些模型只要经过积分变换即可转换为生物个体增长模型。研究选择3个个体生长模型(BSM、von Bertalanffy模型和Logistic模型),用于描述4种竹子的高生长趋势,利用决定系数(R2)和曲率用于评判这些模型的优劣,R2越大,则表明拟合优度越好,内禀曲率和参数效果曲率相对临界曲率越小,模型参数设置则更为合理。研究表明:Logistic模型对不同竹种不同个体高生长数据的拟合结果优于BSM模型和von Bertalanffy模型,表现为决定系数大和参数效果曲率小。Logstic模型结构相对简单,也是描述动植物生长通用性最强的模型,模型的广泛适用性对描述和模拟包括竹类植物在内的生物有机体生长总体趋势和个体差异具有重要意义。

Bamboo is subordinate to Bambusoideae(Gramineae),which has the advantages of fast growth,early mature,widely use and renewable,and is an essential part of forest resources in South China.In order to make rational use of bamboo resources,it is significant to study the growth rate of different bamboo species.At present,there are many mathematical models used in describing the effect of temperature on the growth rate of poikilothermic ectotherms,and these models can be transformed into individual growth models only by integral transformation.In this study,three growth models(BSM model,von Bertalanffy model and Logistic model)are used to describe the height growth of four bamboo species,the advantages and disadvantages of different models can be evaluated by using the coefficient of determination(R 2)and curvatures.The larger R 2,smaller rms.ic(the root-mean-square intrinsic curvature)and rms.pec(the root-mean-square parameter-effects curvature),indicate higher goodness of fit and more reasonable parameter structure for a model.The largest R 2 and the least rms.pec are presented by the Logistic model,suggesting that its fitted results are better than those of the BSM model and the von Bertalanffy model for different bamboo species and different individual height growth data.Relatively,the Logistic model has a simple structure and is the most universal model for describing the growth of animals and plants.Simultaneously,the extensive applicability of the model has an important significance in describing and simulating the growth trend and individual difference of biological organisms.