{"title":"杉木人工林叶面积建模","authors":"Yancheng Qu, Yihang Jiang, Hanyue Chen, Yuxin Hu, Quang V. Cao, Anli Luo, Jian-guo Zhang, Xiongqing Zhang","doi":"10.1139/cjfr-2023-0127","DOIUrl":null,"url":null,"abstract":"Leaf area is an important ecophysiological variable for quantifying the potential production of trees, since it is closely related to tree growth. However, it is difficult to measure the leaf area completely because of the large number of leaves, so it is particularly important to develop accurate species-specific leaf area models. In this study, using 144 parse trees from 48 plots of different climate zones and ages of Chinese fir, tree leaf area models were developed based on sapwood area at breast height (SABH), diameter at breast height (DBH), and diameter at crown base (DCB), respectively. The results showed that the population-averaged levels of nonlinear mixed-effects (NLME) models were better than the plot-levels and base models, and the leaf area models based on DCB performed the best. Finally, the NLME model (16) based on DCB was used as the final model for tree leaf area of Chinese fir plantations, which was consistent with the pipe model theory. All the variables had certain biological and statistical significance and were easy to obtain in the field work (nondestructive). In addition, this study can also provide a reference for other tree species in predicting tree leaf area.","PeriodicalId":9483,"journal":{"name":"Canadian Journal of Forest Research","volume":"172 1","pages":"0"},"PeriodicalIF":1.7000,"publicationDate":"2023-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Modeling tree leaf area of Chinese fir plantations\",\"authors\":\"Yancheng Qu, Yihang Jiang, Hanyue Chen, Yuxin Hu, Quang V. Cao, Anli Luo, Jian-guo Zhang, Xiongqing Zhang\",\"doi\":\"10.1139/cjfr-2023-0127\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Leaf area is an important ecophysiological variable for quantifying the potential production of trees, since it is closely related to tree growth. However, it is difficult to measure the leaf area completely because of the large number of leaves, so it is particularly important to develop accurate species-specific leaf area models. In this study, using 144 parse trees from 48 plots of different climate zones and ages of Chinese fir, tree leaf area models were developed based on sapwood area at breast height (SABH), diameter at breast height (DBH), and diameter at crown base (DCB), respectively. The results showed that the population-averaged levels of nonlinear mixed-effects (NLME) models were better than the plot-levels and base models, and the leaf area models based on DCB performed the best. Finally, the NLME model (16) based on DCB was used as the final model for tree leaf area of Chinese fir plantations, which was consistent with the pipe model theory. All the variables had certain biological and statistical significance and were easy to obtain in the field work (nondestructive). In addition, this study can also provide a reference for other tree species in predicting tree leaf area.\",\"PeriodicalId\":9483,\"journal\":{\"name\":\"Canadian Journal of Forest Research\",\"volume\":\"172 1\",\"pages\":\"0\"},\"PeriodicalIF\":1.7000,\"publicationDate\":\"2023-10-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Canadian Journal of Forest Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1139/cjfr-2023-0127\",\"RegionNum\":3,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"FORESTRY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Canadian Journal of Forest Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1139/cjfr-2023-0127","RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"FORESTRY","Score":null,"Total":0}
Modeling tree leaf area of Chinese fir plantations
Leaf area is an important ecophysiological variable for quantifying the potential production of trees, since it is closely related to tree growth. However, it is difficult to measure the leaf area completely because of the large number of leaves, so it is particularly important to develop accurate species-specific leaf area models. In this study, using 144 parse trees from 48 plots of different climate zones and ages of Chinese fir, tree leaf area models were developed based on sapwood area at breast height (SABH), diameter at breast height (DBH), and diameter at crown base (DCB), respectively. The results showed that the population-averaged levels of nonlinear mixed-effects (NLME) models were better than the plot-levels and base models, and the leaf area models based on DCB performed the best. Finally, the NLME model (16) based on DCB was used as the final model for tree leaf area of Chinese fir plantations, which was consistent with the pipe model theory. All the variables had certain biological and statistical significance and were easy to obtain in the field work (nondestructive). In addition, this study can also provide a reference for other tree species in predicting tree leaf area.
期刊介绍:
Published since 1971, the Canadian Journal of Forest Research is a monthly journal that features articles, reviews, notes and concept papers on a broad spectrum of forest sciences, including biometrics, conservation, disturbances, ecology, economics, entomology, genetics, hydrology, management, nutrient cycling, pathology, physiology, remote sensing, silviculture, social sciences, soils, stand dynamics, and wood science, all in relation to the understanding or management of ecosystem services. It also publishes special issues dedicated to a topic of current interest.