五种气候生产力模型在华北土石山区的适用性分析

Applicability Analysis by Five Climate Productivity Models in Rocky Mountainous Areas of North China

植被净初级生产力(Net Primary Productivity,NPP)是陆地植物的净固碳量,对于全球碳估算研究具有重要意义。华北土石山区作为中国林业工程重点区域,是典型的干旱半干旱气候区,准确估算该地区NPP大小及其变化特征对林业生态工程建设具有重要意义。本文基于河南小浪底森林生态系统国家野外科学观测研究站1980-2020年气候数据,利用Miami模型、Thornthwaite Memorial模型、Chikugo模型、朱志辉模型及周广胜模型共5种气候生产力模型估算,分析NPP的变化趋势,运用随机森林算法探讨NPP影响因素,并以区域MODISNPP数据为标准进行评价,以探究适合估算该地区NPP的气候生产力模型。结果表明:(1)华北土石山区年平均气温、最高气温、最低气温和降水量均呈上升趋势,变化速率分别为0.05℃×a^(-1)、0.04℃×a^(-1)、0.05℃×a^(-1)和1.58mm×a^(-1);年平均太阳辐射和平均相对湿度则呈下降趋势,变化速率分别为0.46MJ×m^(-2)×a^(-1)和0.17个百分点×a^(-1)。(2)采用5种模型计算的华北土石山区NPP均呈上升趋势,但NPP值存在差异,变化范围在739.35~958.48gC×m^(-2)×a^(-1),均值为862.19gC×m^(-2)×a^(-1)。其中Miami模型估算值最大(958.48gC×m^(-2)×a^(-1)),周广胜模型估算值最小(739.35gC×m^(-2)×a^(-1))。(3)随机森林算法表明,降水是影响该地区NPP的关键因子。适用性分析显示,周广胜模型估算值与MODIS NPP最接近,其相对误差、RMSE和MAE分别为1.45%、451.05gC×m^(-2)×a^(-1)和446.03gC×m^(-2)×a^(-1),且相关系数最大(0.49)。综上可知,周广胜模型更适宜该地区的NPP估算,在使用气候生产力模型估算华北土石山区NPP时,应优先考虑使用周广胜模型。

Net Primary Productivity(NPP)is the net carbon sequestration of terrestrial vegetation,which is of great importance for the study of global carbon estimation.The rocky mountainous areas of North China is a typical arid and semi-arid climatic zone,and the accurate estimation of the NPP and its variation characteristics in this area is of great significance for the construction of China's ecological forestry engineering.Based on the climate data from 1980 to 2020 from Henan Xiaolangdi Forest Ecosystem National Observation and Research Station,this paper used 5 climate productivity models,including the Miami model,Thornthwaite Memorial model,Chikugo model,Zhu Zhihui model and Zhou Guangsheng model,to estimate and analyze the changing trend of NPP.The random forest algorithm was used to explore the influencing factors of NPP,and the regional MODIS NPP data was used as the standard to evaluate the suitable climate productivity model for estimating NPP in this area.The results showed that:(1)the annual average temperature,annual average maximum temperature,annual average minimum temperature,and annual precipitation in the rocky mountainous areas of North China showed an upward trend,and the rates were 0.05℃×y^(-1),0.04℃×y^(-1),0.05℃×y^(-1) and 1.58mm×y^(-1),respectively.The annual average solar radiation and annual average relative humidity showed a downward trend,with rates of 0.46MJ×m^(-2)×y^(-1) and 0.17 percent points×y^(-1),respectively.(2)The NPP calculated by 5 models showed an upward trend,but the NPP values were different,ranging from 739.35gC×m^(-2)×y^(-1) to 958.48gC×m^(-2)×y^(-1),with an average of 862.19gC×m^(-2)×y^(-1).Among them,the Miami model had the maximum estimated value(958.48gC×m^(-2)×y^(-1)),and the Zhou Guangsheng model had the minimum estimated value(739.35gC×m^(-2)×y^(-1)).(3)The random forest algorithm showed that precipitation was the predominant factor affecting NPP in the region.The applicability analysis indicated that the estimated value of the Zhou Guangsheng model was the closest to MODIS NPP,with the relative error,RMSE,and MAE of 1.45%,451.05gC×m^(-2)×y^(-1),and 446.03gC×m^(-2)×y^(-1),respectively,and the correlation coefficient was the highest(0.49).This study showed that the Zhou Guangsheng model was more suitable for NPP estimation in this area,and priority should be given to the Zhou Guangsheng model when using the climate productivity model to estimate NPP in the rocky mountainous areas of North China.