[1] Cao M, Woodward F I. Net primary and ecosystem production and carbon stocks of terrestrial ecosystems and their responses to climate change[J]. Global Change Biology, 1998, 4(2): 185-198. doi: 10.1046/j.1365-2486.1998.00125.x
[2] 胡海清, 罗斯生, 罗碧珍, 等. 林火干扰对广东省2种典型针叶林森林生物碳密度的影响[J]. 林业科学研究, 2020, 33(1):19-27.
[3] 张少伟, 张弓乔, 惠刚盈. 内蒙古大兴安岭森林净初级生产力时空格局分析[J]. 林业科学研究, 2019, 32(5):74-82.
[4] Jenkins, J C, Chojnacky, D C, Heath, L S, et al. National-scale biomass estimators for United States tree species[J]. Forest Science, 2004, 49(1): 12-35.
[5] Ter-Mikaelian M T, Korzukhin M D. Biomass equations for sixty-five North American tree species[J]. Forest Ecology and Management, 1997, 97: 1-24. doi: 10.1016/S0378-1127(97)00019-4
[6] 曾伟生. 全国立木生物量方程建模方法研究[D]. 北京: 中国林业科学研究院, 2001.
[7] Kittredge J. Estimation of the amount of foliage of trees and stands[J]. Journal of Forestry, 1944, 42(12): 905-912.
[8] Wang C K. Biomass allometric equations for 10 co-occurring tree species in chinese temperate forests[J]. Forest Ecology and Management, 2006, 222(1): 9-16.
[9] Zianis D, Xanthopoulos G, Kalabokidis K, et al. Allometric equations for aboveground biomass estimation by size class for Pinus brutia Ten.trees growing in north and south Aegean Islands, Greece[J]. European Journal of Forest Research, 2011, 130(2): 145-160. doi: 10.1007/s10342-010-0417-9
[10] Ozdemir E, Makineci E, Yilmaz E, et al. Biomass estimation of individual trees for coppice-originated oak forests[J]. European Journal of Forest Research, 2019, 138(4): 623-637. doi: 10.1007/s10342-019-01194-2
[11] 罗 红, 李百炼. 异速生长模型研究概述[J]. 生态学杂志, 2011, 30(9):2060-2065.
[12] 薛春泉, 徐期瑚, 林丽平, 等. 广东主要乡土阔叶树种含年龄和胸径的单木生物量模型[J]. 林业科学, 2019, 55(2):97-108. doi: 10.11707/j.1001-7488.20190210
[13] 薛春泉, 徐期瑚, 林丽平, 等. 广东主要乡土阔叶树种单木生物量生长模型[J]. 华南农业大学学报, 2019, 40(2):65-75. doi: 10.7671/j.issn.1001-411X.201806031
[14] Rohner B, Waldner P, Lischke H, et al. Predicting individual-tree growth of central European tree species as a function of site, stand, management, nutrient, and climate effects[J]. European Journal of Forest Research, 2018, 137(1): 29-44. doi: 10.1007/s10342-017-1087-7
[15] Zeide B. Analysis of growth equations[J]. Forest Science, 1993, 39(3): 594-616. doi: 10.1093/forestscience/39.3.594
[16] 张建国, 段爱国. 理论生长方程与直径结构模型的研究[M]. 北京: 科学出版社, 2004.
[17] Russell M B, Weiskittel A R, Kershaw J A. Comparing strategies for modeling individual-tree height and height-to-crown base increment in mixed-species Acadian forests of northeastern North America[J]. European Journal of Forest Research, 2014, 133(6): 1121-1135. doi: 10.1007/s10342-014-0827-1
[18] Wensel L, Meerschaert W, Biging G. Tree height and diameter growth models for northern California conifers[J]. Hilgardia, 1987, 55(8): 1-20. doi: 10.3733/hilg.v55n08p020
[19] Sharma M, Yin Zhang S. Height–diameter models using stand characteristics for Pinus banksiana and Picea mariana[J]. Scandinavian Journal of Forest Research, 2004, 19(5): 442-451. doi: 10.1080/02827580410030163
[20] Reineke, L. H. Perfecting a stand-density index for even-aged forests[J]. Journal of Agricultural Research, 1933, 46(7): 627-638.
[21] 国家林业局. 立木生物量模型及碳计量参数-马尾松: LY/T 2263-2014[S]. 北京: 中国林业出版社, 2014.
[22] 国家林业局. 立木生物量模型及碳计量参数-栎树: LT/T 2658-2016[S]. 北京: 中国林业出版社, 2016a.
[23] 国家林业局. 立木生物量模型及碳计量参数-木荷: LY/T2660-2016[S]. 北京: 中国林业出版社, 2016b.
[24] 曹 磊, 李海奎. 两种相容性生物量模型的比较—以广东省3个阔叶树种为例[J]. 生态学杂志, 2019, 38(6):1916-1925.
[25] Richards F J. A flexible growth function for empirical use[J]. Journal of Experimental Botany, 1959, 10(2): 290-301. doi: 10.1093/jxb/10.2.290
[26] 唐守正, 李　勇, 符利勇. 生物数学模型的统计学基础[M]. 北京: 科学出版社, 2015.
[27] 唐守正, 郎奎建, 李海奎. 统计和生物数学模型计算(ForStat教程)[M]. 北京: 科学出版社, 2009.
[28] 曾伟生, 唐守正. 立木生物量方程的优度评价和精度分析[J]. 林业科学, 2011, 47(11):106-113. doi: 10.11707/j.1001-7488.20111117
[29] Berk K N. Validating regression procedures with new data[J]. Technimetrics, 1984, 26(4): 331-338. doi: 10.1080/00401706.1984.10487985
[30] Kozak A, Kozak R. Does cross validation provide additional information in the evaluation of regression models[J]. Canadian Journal of Forest Research, 2003, 33(6): 976-987. doi: 10.1139/x03-022
[31] Ketterings Q M, Coe R, van Noordwijk M, et al. Reducing uncertainty in the use of allometric biomass equations for predicting above-ground tree biomass in mixed secondary forests[J]. Forest Ecology and Management, 2001, 146(1-3): 199-209. doi: 10.1016/S0378-1127(00)00460-6
[32] 曾伟生, 唐守正. 非线性模型对数回归的偏差校正及与加权回归的对比分析[J]. 林业科学研究, 2011, 24(2):137-143.
[33] 曾伟生, 骆期邦, 贺东北. 论加权回归与建模[J]. 林业科学, 1999, 35(5):5-11. doi: 10.3321/j.issn:1001-7488.1999.05.002
[34] Zeng W S, Zhang H R, Tang S Z. 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[J]. Canadian Journal of Forest Research, 2011, 41(7): 1547-1554. doi: 10.1139/x11-068
[35] Fang J Y, Chen A P, Peng C, et al. Changes in forest biomass carbon storage in China between 1949 and 1998[J]. Science, 2001, 262(5525): 2320-2322.
[36] 龙时胜, 曾思齐, 甘世书, 等. 基于林木多期直径测定数据的异龄林年龄估计方法[J]. 中南林业科技大学学报: 自然科学版, 2018, 38(9):1-8.
[37] 龙时胜, 曾思齐, 甘世书, 等. 基于林木多期直径测定数据的异龄林年龄估计方法Ⅱ[J]. 中南林业科技大学学报: 自然科学版, 2019, 39(6):23-29.
[38] 惠淑荣, 于洪飞. 日本落叶松林分生长量Richards生长方程的建立与应用[J]. 生物数学学报, 2003, 18(2):204-206. doi: 10.3969/j.issn.1001-9626.2003.02.011
[39] Wang M, Borders B E, Zhao D. An empirical comparison of two subject-specific approaches to dominant heights modeling: The dummy variable method and the mixed model method[J]. Forest Ecology and Management, 2008, 255(7): 2659-2669. doi: 10.1016/j.foreco.2008.01.030