丁贵杰, 周志春, 王章荣. 2006. 马尾松纸浆用材林培育与利用. 北京:中国林业出版社 (Ding G J, Zhou Z C, Wang Z R. 2006. Cultivation and utilization of Masson pine pulpwood plantation. Beijing:China Forestry Publishing House.[in Chinese]) 封晓辉,程瑞梅,肖文发,等. 2011. 北亚热带生长期温度对马尾松径向生长的影响. 生态学杂志, 30(4):650-655. (Feng X H, Cheng R M, Xiao W F, et al. 2011. Effects of air temperature in growth season on Masson pine (Pinus massoniana) radial growth in north subtropical region of China. Chinese Journal of Ecology, 30(4):650-655.[in Chinese]) 符利勇, 曾伟生, 唐守正. 2011a. 利用混合模型分析地域对国内马尾松生物量的影响. 生态学报, 31(19):5797-5808. (Fu L Y, Zeng W S, Tang S Z. 2011a. Analysis the effect of region impacting on the biomass of domestic Masson pine using mixed model. Acta Ecologica Sinica, 31(19):5797-5808.[in Chinese]) 符利勇, 李永慈, 李春明, 等. 2011b. 基于两水平非线性混合模型对杉木林优势高生长量研究. 林业科学研究, 24(6):720-726. (Fu L Y, Li Y C, Li C M, et al. 2011b. Study of the dominant height for Chinese fir plantation using two-level nonlinear mixed effects model. Forest Research, 24(6):720-726.[in Chinese]) 符利勇, 雷渊才, 曾伟生. 2014. 几种相容性生物量模型及估计方法的比较. 林业科学, 50(6):42-54. (Fu L Y, Lei Y C, Zeng W S. 2014. Comparison of several compatible biomass models and estimation approaches. Scientia Silvae Sinicae, 50(6):42-54.[in Chinese]) 国家气候变化评估报告编辑委员会. 2007. 国家气候变化评估报告. 北京:科学出版社 (Editorial Committee of National Climate Change Assessment Report. 2007. National climate change assessment report. Beijing:Science Press.[in Chinese]) 唐守正, 李勇, 符利勇. 2015. 生物数学模型的统计学基础.2版. 北京:科学出版社. (Tang S Z, Li Y, Fu L Y. 2015. Statistical foundation for biomathematical models.2nd ed. Beijing:Higher Education Press.[in Chinese]) 唐守正, 张会儒, 胥辉. 2000. 相容性生物量模型的建立及其估计方法研究. 林业科学, 36(zk):19-27. (Tang S Z, Zhang H R, Xu H. 2000. Study on establish and estimate method of compatible biomass model. Scientia Silvae Sinicae, 36(zk):19-27.[in Chinese]) 唐守正, 郎奎建, 李海奎. 2008. 统计和生物数学模型计算(ForStat教程). 北京:科学出版社. (Tang S Z, Lang K J, Li H K. 2008. Statistics and computation of biomathematical models (ForStat course). Beijing:Science Press.[in Chinese]) 曾伟生, 唐守正. 2010a. 利用混合模型方法建立全国和区域相容性立木生物量方程. 中南林业调查规划,29(4):1-6. (Zeng W S, Tang S Z. 2010a. Using mixed-effects modeling method to establish compatible national and regional single-tree biomass equations. Central South Forest Inventory and Planning, 29(4):1-6.[in Chinese]) 曾伟生, 唐守正. 2010b. 利用度量误差模型方法建立相容性立木生物量方程系统. 林业科学研究, 23(6):797-802. (Zeng W S, Tang S Z. 2010b. Using measurement error modeling method to establish compatible single-tree biomass equations system. Forest Research, 23(6):797-802.[in Chinese]) Bi H, Turner J, Lambert M J. 2004. Additive biomass equations for native eucalypt forest trees of temperate Australia. Trees, 18(4):467-479. Dong L H, Zhang L J, Li F R. 2015. A three-step proportional weighting system of nonlinear biomass equations. Forest Science, 61(1):35-45. Fu L Y, Lei X D, Hu Z D, et al. 2017a. Integrating regional climate change into allometric equations for estimating tree aboveground biomass of Masson pine in China. Annals of Forest Science, 74:42. doi:10.1007/s13595-017-0636-z. Fu L Y, Sharma R P, Hao K J, et al. 2017b. A generalized interregional nonlinear mixed-effects crown width model for Prince Rupprecht larch in northern China. Forest Ecology and Management, 389:364-373. Fu L Y, Zeng W S, Tang S Z, et al. 2012. Using linear mixed model and dummy variable model approaches to construct compatible single-tree biomass equations at different scales-a case study for Masson pine in southern China. Journal of Forest Science, 58(3):101-115. Fu L Y, Zeng W S, Zhang H R, et al. 2014. Generic linear mixed-effects individual-tree biomass models for Pinus massoniana Lamb. in Southern China. Southern Forests, 76(1):47-56. Fu L Y, Lei Y C, Wang G X, et al. 2016. Comparison of seemingly unrelated regressions with error-invariable models for developing a system of nonlinear additive biomass equations. Trees, 30(3):839-857. Hijmans R J, Cameron S E, Parra J L, et al. 2005. Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology, doi:10.1002/joc.1276. IPCC. 2007. Climate change 2007:the physical science basis.UK:Cambridge University Press. Parresol B R. 1999. Assessing tree and stand biomass:a review with examples and, critical comparisons. Forest Science, 45(4):573-593. Parresol B R. 2001. Additivity of nonlinear biomass equations. Canadian Journal of Forest Research, 31(5):865-878. R Core Team. 2012. R:a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. Waring R H,Running S W. 1998. Forest ecosystems:analysis at multiple scales. 2nd ed. Academic Press, San Diego, Calif. Zeng W S, Tang S Z. 2012. Modeling compatible single-tree biomass equations of Masson pine (Pinus massoniana) in southern China. Journal of Forestry Research, 23(4):593-598. Zeng W S, Zhang H R, Tang S Z. 2011. Using the dummy variable model approach to construct compatible single-tree biomass equations at different scales-a case study for Masson pine (Pinus massoniana) in Southern China. Canadian Journal of Forest Research, 41(7):1547-1554. Zeng W S, Tang S Z, Xiao Q. 2014. Calorific values and ash contents of different parts of Masson pine trees in southern China. Journal of Forestry Research, 25(4):779-786. Zeng W S. 2015. Using nonlinear mixed model and dummy variable model approaches to develop origin-based individual tree biomass equations. Trees, 29(1):275-283. Zeng W S, Duo H R, Lei X D, et al. 2017. Individual tree biomass equations and growth models sensitive to climate variables for Larix spp. in China. European Journal of Forest Research, doi:10.1007/s10342-017-1024-9. Zou W T, Zeng W S, Zhang L J, et al. 2015. Modeling crown biomass for four pine species in China. Forests, 6(2):433-449. |