{"title":"孟加拉东北地区马沙藤叶面积和叶生物量估算的异速生长模型","authors":"Niamjit Das","doi":"10.7747/JFES.2014.30.4.351","DOIUrl":null,"url":null,"abstract":"Leaf area (A0) and leaf biomass (M0) estimation are significant prerequisites to studying tree physiological processes and modeling in the forest ecosystem. The objective of this study was to develop allometric models for estimating A0 and M0 of Swietenia mahagoni L. from different tree parameters such as DBH and tree height of mahogany plantations in the northeastern region of Bangladesh. A total of 850 healthy and well formed trees were selected randomly for sampling in the five study sites. Then, twenty two models were developed based on different statistical criteria that propose reliable and accurate models for estimating the A0 and M0 using non-destructive measurements. The results exposed that model iv and xv were selected on a single predictor of DBH and showed more statistically accuracy than other models. The selected models were also validated with an additional test data set on the basis of linear regression and t-test for mean difference between observed and predicted values. After that, a comparison between the best logarithmic and non-linear allometric model shows that the non-linear model produces systematic biases and underestimates A0 and M0 for larger trees. As a result, it showed that the bias-corrected logarithmic model iv and xv can be used to help quantify forest structure and functions, particularly valuable in future research for estimating A0 and M0 of S. mahagoni in this region.","PeriodicalId":237267,"journal":{"name":"Journal of forest and environmental science","volume":"56 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Allometric Modeling for Leaf Area and Leaf Biomass Estimation of Swietenia mahagoni in the North-eastern Region of Bangladesh\",\"authors\":\"Niamjit Das\",\"doi\":\"10.7747/JFES.2014.30.4.351\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Leaf area (A0) and leaf biomass (M0) estimation are significant prerequisites to studying tree physiological processes and modeling in the forest ecosystem. The objective of this study was to develop allometric models for estimating A0 and M0 of Swietenia mahagoni L. from different tree parameters such as DBH and tree height of mahogany plantations in the northeastern region of Bangladesh. A total of 850 healthy and well formed trees were selected randomly for sampling in the five study sites. Then, twenty two models were developed based on different statistical criteria that propose reliable and accurate models for estimating the A0 and M0 using non-destructive measurements. The results exposed that model iv and xv were selected on a single predictor of DBH and showed more statistically accuracy than other models. The selected models were also validated with an additional test data set on the basis of linear regression and t-test for mean difference between observed and predicted values. After that, a comparison between the best logarithmic and non-linear allometric model shows that the non-linear model produces systematic biases and underestimates A0 and M0 for larger trees. As a result, it showed that the bias-corrected logarithmic model iv and xv can be used to help quantify forest structure and functions, particularly valuable in future research for estimating A0 and M0 of S. mahagoni in this region.\",\"PeriodicalId\":237267,\"journal\":{\"name\":\"Journal of forest and environmental science\",\"volume\":\"56 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-11-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of forest and environmental science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.7747/JFES.2014.30.4.351\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of forest and environmental science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.7747/JFES.2014.30.4.351","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
摘要
叶面积(A0)和叶生物量(M0)的估算是研究森林生态系统树木生理过程和建模的重要前提。本研究旨在利用孟加拉东北部红木人工林不同树木参数(胸径和树高)建立估算mahagoni swetenia L. A0和M0的异速生长模型。在五个研究地点随机抽取了850棵健康和发育良好的树木进行采样。然后,根据不同的统计准则建立了22个模型,为无损测量估计A0和M0提供了可靠和准确的模型。结果表明,模型iv和模型xv是在一个单一的胸径预测因子上选择的,并且比其他模型具有更高的统计准确性。选取的模型在线性回归和观测值与预测值平均差的t检验的基础上,用额外的检验数据集进行验证。之后,对最佳对数异速生长模型和非线性异速生长模型的比较表明,非线性模型会产生系统偏差,并且低估了较大树木的A0和M0。结果表明,修正偏倚的对数模型iv和xv可用于量化森林结构和功能,对未来研究估算该地区mahagoni的A0和M0具有重要价值。
Allometric Modeling for Leaf Area and Leaf Biomass Estimation of Swietenia mahagoni in the North-eastern Region of Bangladesh
Leaf area (A0) and leaf biomass (M0) estimation are significant prerequisites to studying tree physiological processes and modeling in the forest ecosystem. The objective of this study was to develop allometric models for estimating A0 and M0 of Swietenia mahagoni L. from different tree parameters such as DBH and tree height of mahogany plantations in the northeastern region of Bangladesh. A total of 850 healthy and well formed trees were selected randomly for sampling in the five study sites. Then, twenty two models were developed based on different statistical criteria that propose reliable and accurate models for estimating the A0 and M0 using non-destructive measurements. The results exposed that model iv and xv were selected on a single predictor of DBH and showed more statistically accuracy than other models. The selected models were also validated with an additional test data set on the basis of linear regression and t-test for mean difference between observed and predicted values. After that, a comparison between the best logarithmic and non-linear allometric model shows that the non-linear model produces systematic biases and underestimates A0 and M0 for larger trees. As a result, it showed that the bias-corrected logarithmic model iv and xv can be used to help quantify forest structure and functions, particularly valuable in future research for estimating A0 and M0 of S. mahagoni in this region.