| 摘要: |
| 【目的】研究红树植物木榄的生物量预测模型，为有效估算红树植物各器官生物量奠定基础。【方法】以广东湛江红树林自然保护区的木榄（Bruguiera gymnorrhiza）为研究对象，将基径（D）和树高（H）这2个因子派生为多个一元及多元变量，包括D、H、D2、DH和D2H,用其作为变量构建直线方程和指数方程来预测木榄各器官（木材、树皮、树冠）、地上部分、地下部分以及全株总生物量，并对直线方程和指数方程的预测效果进行比较。【结果】指数方程对木榄各器官及全株总生物量的预测效果优于直线方程；在所有的一元回归方程中，木榄各器官及全株生物量与D之间具有较强的相关性，决定系数较高，且以D或D2为预测变量所构建方程的残差平方和（RSS）、均方根误差（RMSE）和赤池信息准则（AIC）值较以H为变量构建的方程小，说明D的预测效果优于H。所有预测模型对木榄地上部分生物量的预测效果均优于地下部分，用D或D与H结合预测地下部分生物量的效果均不理想。双变量指数模型的RSS、RMSE和AIC值普遍较单变量模型小，说明DH和D2H的统计效力更好，预测效果更佳。D2H和DH与木榄各器官生物量之间具有较强的相关性，且以D2H为预测变量的指数模型预测木榄各器官、地上部分及全株生物量的RSS、RMSE和AIC值，以及以DH为预测变量的指数模型预测木榄地下部分生物量的RSS、RMSE和AIC值均较其他模型小。【结论】以D2H为预测变量的指数模型对木榄各器官、地上部分及全株生物量的预测拟合效果最好，以DH为预测变量的指数模型对木榄地下部分生物量的预测拟合效果最佳，可以将其作为最优的生物量预测模型用于木榄各器官及全株生物量估算。 |
| 关键词: 木榄 红树植物 生物量预测模型 直线方程 指数方程 |
| DOI： |
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| 基金项目:广东省林业科技创新项目（2014KJCX021-02） |
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| Biomass model of Bruguiera gymnorrhiza in Guangdong |
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HUANG Runxia,WU Zhuoling,PENG Jiangwei,et al
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| Abstract: |
| 【Objective】This paper studied the mangrove biomass prediction model of Bruguiera gymnorrhiza to provide basis for effective estimating biomass of organs of mangrove.【Method】In this study,we selected B. gymnorrhiza in the Mangrove Forest Nature Reserve in Zhanjiang,Guangdong,The basal diameter (D) and tree height (H) were converted into multiple elements variables,multivariate variables and polynomial variables including D,H,D2,DH,and D2H.These predictor variables were used to construct linear equation and exponential equation to predict biomass of each organ (wood,bark and canopy),aboveground,underground and whole plant.The prediction results of linear equation and exponential equation were also compared.【Result】The exponential equation was better than the linear equation for predicting total biomass.In all unit regression equations,there was a strong correlation between biomass and D with higher coefficient of determination.The RSS,RMSE and AIC values of the equations constructed with D or D2 were smaller than with H,indicating that the prediction with D was better than H.All prediction models had better prediction on aboveground biomass than underground biomass,and it was not ideal to predict underground biomass with D and H or DH and D2H.The RSS,RMSE and AIC values of the multivariate variables model were smaller than the unit variable model,which showed that DH and D2H were better.There was a strong correlation between biomass of B. gymnorrhiza and D2H or DH,and the RSS,RMSE and AIC values of the exponential model with D2H as the predictor variable in predicting wood biomass,bark biomass,canopy biomass,aboveground biomass and total biomass were smaller than other models.The RSS,RMSE and AIC values of the exponential model with DH as the predictor variable in predicting underground biomass were smaller than other models.【Conclusion】The exponential model with D2H as the predictor variable had the best fitting effect on wood biomass,bark biomass,canopy biomass, aboveground biomass and total biomass,and the exponential model with DH as the predictor variable had the best fitting effect on underground biomass.The models can be used to estimate biomass of B. gymnorrhiza. |
| Key words: Bruguiera gymnorrhiza mangrove plants biomass prediction model linear equation exponential equation |
