Optimizing site selection and harvest age for large Chinese fir in complex subtropical terrains, China

Abstract

Chinese fir (Cunninghamia lanceolata) is a key resource in China’s timber industry. However, there are no site-specific cultivation guidelines for producing large-diameter trees and enhancing forest productivity and timber quality while addressing the complexities of Chinese tropical terrains. This study identifies key site factors using the Boruta algorithm and establishes diameter growth curves through K-means clustering and mixed-effects modeling to estimate how many years are required to reach target diameters. It is based on sample plot data from Chinese fir plantations across seven provinces in subtropical China. The results show that: (1) soil type and depth, and elevation have a strong influence on growth; (2) of the six basic growth models compared, the Korf model performed best, with the coefficient of determination (R²) of 0.6154. The predictive accuracy was significantly improved by introducing a mixed-effects model, which increased the R² value to 0.7535; (3) at a designated harvesting age of 26 years, diameters at breast height (DBH) were approximately 30, 27, and 26 cm under STG6, STG4, and STG8, respectively, all exceeding the large-size timber threshold (DBH≥25 cm), demonstrating strong cultivation potential; and, (4) to attain a 25 cm DBH, STG6, STG4, and STG8 required 18, 21, and 24 years, respectively. Growth rate slowed significantly after 30 years, suggesting that the rotation period should be limited to within 30 years to optimize management efficiency. In this study, we developed a robust growth prediction model suitable for diverse site conditions and propose a site-specific management strategy that provides the basis for the precision cultivation and sustainable management of large-size Chinese fir plantations.

Keywords

Site conditions / Chinese fir / Large-size tree / Mixed-effect model / Target diameter

References

[1] Abrantes KKB, Paiva LM, de Almeida RG, Urbano E, Ferreira AD, Mazucheli J. Modeling the individual height and volume of two integrated crop-livestock-forest systems of Eucalyptus spp. in the Brazilian Savannah. Acta Sci Agron, 2019, 41(1 42626

[2] Banaś J, Šafařík D, Utnik-Banaś K, Hlaváčková P. Identifying long-run and short-run relationships in the European Union softwood market. For Policy Econ, 2022, 143 102821

[3] Bravo-Oviedo A, Tomé M, Bravo F, Montero G, del Río M. Dominant height growth equations including site attributes in the generalized algebraic difference approach. Can J for Res, 2008, 389): 2348-2358

[4] Calama R, Montero G. Interregional nonlinear height-diameter model with random coefficients for stone pine in Spain. Can J for Res, 2004, 34(1): 150-163

[5] Chazdon RL, Guariguata MR. Natural regeneration as a tool for large-scale forest restoration in the tropics. Biotropica, 2016, 48(6): 716-730

[6] Clark PW, D’Amato AW, Evans KS, Schaberg PG, Woodall CW. Ecological memory and regional context influence performance of adaptation plantings in northeastern US temperate forests. J Appl Ecol, 2022, 59(1): 314-329

[7] Coops NC, Tompalski P, Goodbody TRH, Achim A, Mulverhill C. Framework for near real-time forest inventory using multi source remote sensing data. Forestry, 2023, 96(1): 1-19

[8] Corona P, Scotti R, Tarchiani N. Relationship between environmental factors and site index in Douglas-fir plantations in central Italy. For Ecol Manag, 1998, 110(1–3): 195-207

[9] Dannenmann M, Gasche R, Ledebuhr A, Holst T, Mayer H, Papen H. The effect of forest management on trace gas exchange at the pedosphere–atmosphere interface in beech (Fagus sylvatica L.) forests stocking on calcareous soils. Eur J Forest Res, 2007, 126(2): 331-346

[10] Degenhardt F, Seifert S, Szymczak S. Evaluation of variable selection methods for random forests and omics data sets. Brief Bioinform, 2019, 20(2): 492-503

[11] Drobyshev I, Simard M, Bergeron Y, Hofgaard A. Does soil organic layer thickness affect climate–growth relationships in the black spruce boreal ecosystem?. Ecosystems, 2010, 13(4): 556-574

[12] Duan AG, Lei J, Hu XY, Zhang JG, Du HL, Zhang XQ, Guo WF, Sun JJ. Effects of planting density on soil bulk density, pH and nutrients of unthinned Chinese fir mature stands in south subtropical region of China. Forests, 2019, 10(4): 351

[13] Duan GS, Lei XD, Zhang XQ, Liu XZ. Site index modeling of larch using a mixed-effects model across regional site types in northern China. Forests, 2022, 135815

[14] Duncker PS, Barreiro SM, Hengeveld GM, Lind T, Mason WL, Ambrozy S, Spiecker H (2012) Classification of forest management approaches: a new conceptual framework and its applicability to European forestry. Ecol Soc 17(4). https://www.jstor.org/stable/26269224

[15] Fang ZX, Bailey RL. Nonlinear mixed effects modeling for slash pine dominant height growth following intensive silvicultural treatments. For Sci, 2001, 473287-300

[16] Fang ZX, Bailey RL, Shiver BD. A multivariate simultaneous prediction system for stand growth and yield with fixed and random effects. For Sci, 2001, 47(4): 550-562

[17] Farrelly N, Ní Dhubháin Á, Nieuwenhuis M. Site index of Sitka spruce (Picea sitchensis) in relation to different measures of site quality in Ireland. Can J for Res, 2011, 41(2): 265-278

[18] Felix-Henningsen P, Liu LW, Zakosek H. Distribution and genesis of red and yellow soils in the central subtropics of southeast China. CATENA, 1989, 16(1): 73-89

[19] Feng JJ, Cao YW, Manda T, Hwarari D, Chen JH, Yang LM. Effects of environment change scenarios on the potential geographical distribution of Cunninghamia lanceolata (lamb.) hook. in China. Forests, 2024, 15(5 830

[20] Gao WF, Dong C, Gong YH, Ma S, Shen JH, Lin SQ. Site quality evaluation model of Chinese fir plantations for machine learning and site factors. Sustainability, 2023, 1521): 15587

[21] Grigoreva O, Runova E, Savchenkova V, Hertz E, Voronova A, Ivanov V, Shvetsova V, Grigorev I, Lavrov M. Comparative analysis of thinning techniques in pine forests. J for Res, 2022, 3341145-1156

[22] Guo GZ, Duan AG, Zhang JG, Liao SS (2020) Long-term effects of site and density on timber assortment structure of Chinese fir plantations in south subtropical area, China. https://doi.org/10.13275/j.cnki.lykxyj.2020.01.005

[23] Gustafsson L, Kouki J, Sverdrup-Thygeson A. Tree retention as a conservation measure in clear-cut forests of northern Europe: a review of ecological consequences. Scand J for Res, 2010, 25(4): 295-308

[24] Hartigan JA, Wong MA. Algorithm AS 136: a K-means clustering algorithm. Appl Stat, 1979, 28(1): 100

[25] He HM, Zhu GY, Ma W, Liu FH, Zhang XQ. Additivity of stand basal area predictions in canopy stratifications for natural oak forests. For Ecol Manag, 2021, 492 119246

[26] Huang F, Zhang CL, Zeng YF, Yan Y, Li MX, Su ZY, Jia XR. Research hotspots and trends of large-diameter trees based on bibliometric data. Sustainability, 2024, 1611 4826

[27] Hui GY, Hu YB, Luo YW, Zhang XL. Study on the mechanism of producing high quality wood of Chinese fir. For Res, 2000, 132177-181in Chinese

[28] Kang HJ, Seely B, Wang GY, Innes J, Zheng DX, Chen PL, Wang TL, Li QL. Evaluating management tradeoffs between economic fiber production and other ecosystem services in a Chinese-fir dominated forest plantation in Fujian Province. Sci Total Environ, 2016, 557: 80-90

[29] Komlós M, Botta-Dukát Z, Bölöni J, Aszalós R, Veres K, Winkler D, Ónodi G. Tall, large-diameter trees and dense shrub layer as key determinants of the abundance and composition of bird communities in oak-dominated forests. J for Res, 2024, 35(1): 62

[30] Kursa MB, Rudnicki WR. Feature selection with the Boruta package. J Stat Softw, 2010, 36111-13

[31] Li YF, Ye SM, Hui GY, Hu YB, Zhao ZH. Spatial structure of timber harvested according to structure-based forest management. For Ecol Manag, 2014, 322: 106-116

[32] Li YH, Li C, Song Y, Guo Y, Yao LH. Anatomical, physical, and mechanical parameters of clone plantation tree, Cunninghamia lanceolata. BioResources, 2021, 16(2): 3494-3519

[33] Li XY, Duan AG, Zhang JG. Site index for Chinese fir plantations varies with climatic and soil factors in southern China. J for Res, 2022, 33(6): 1765-1780

[34] Li XY, Duan AG, Zhang JG. Long-term effects of planting density and site quality on timber assortment structure based on a 41-year plantation trial of Chinese fir. Trees for People, 2023, 12 100396

[35] Lindstrom ML, Bates DM. Nonlinear mixed effects models for repeated measures data. Biometrics, 1990, 46(3): 673-687

[36] Liu ZH, Huang TB, Wu Y, Zhang XL, Liu CX, Yu ZB, Xu C, Ou GL. Aboveground biomass inversion of forestland in a Jinsha River dry-hot valley by integrating high and medium spatial resolution optical images: a case study on Yuanmou County of Southwest China. Ecol Inform, 2024, 83 102796

[37] Liu ZH, Huang TB, Zhang XL, Wu Y, Xu XW, Wang ZH, Zou FY, Zhang C, Xu C, Ou GL. Interacting sentinel-2A, sentinel 1A, and GF-2 imagery to improve the accuracy of forest aboveground biomass estimation in a dry-hot valley. Forests, 2024, 15(4 731

[38] Lundmark H, Josefsson T, Östlund L. The introduction of modern forest management and clear-cutting in Sweden: ridö state forest 1832–2014. Eur J for Res, 2017, 1362): 269-285

[39] Lundqvist B. On the height growth in cultivated stands of pine and spruce in Northern Sweden. Medd Statens Skogforskinst, 1957, 47(2): 1-64

[40] Lutz JA, Larson AJ, Swanson ME, Freund JA. Ecological importance of large-diameter trees in a temperate mixed-conifer forest. PLoS ONE, 2012, 7(5 e36131

[41] Lutz JA, Larson AJ, Freund JA, Swanson ME, Bible KJ. The importance of large-diameter trees to forest structural heterogeneity. PLoS ONE, 2013, 812 e82784

[42] Lutz JA, Furniss TJ, Johnson DJ, Davies SJ, Allen D, Alonso A, Anderson-Teixeira KJ, Andrade A, Baltzer J, Becker KML, Blomdahl EM, Bourg NA, Bunyavejchewin S, Burslem DFRP, Cansler CA, Cao K, Cao M, Cárdenas D, Chang LW, Chao KJ, Chao WC, Chiang JM, Chu CJ, Chuyong GB, Clay K, Condit R, Cordell S, Dattaraja HS, Duque A, Ewango CEN, Fischer GA, Fletcher C, Freund JA, Giardina C, Germain SJ, Gilbert GS, Hao ZQ, Hart T, Hau BCH, He FL, Hector A, Howe RW, Hsieh CF, Hu YH, Hubbell SP, Inman-Narahari FM, Itoh A, Janík D, Kassim AR, Kenfack D, Korte L, Král K, Larson AJ, Li YD, Lin Y, Liu SR, Lum S, Ma KP, Makana JR, Malhi Y, McMahon SM, McShea WJ, Memiaghe HR, Mi XC, Morecroft M, Musili PM, Myers JA, Novotny V, de Oliveira A, Ong P, Orwig DA, Ostertag R, Parker GG, Patankar R, Phillips RP, Reynolds G, Sack L, Song GM, Su SH, Sukumar R, Sun IF, Suresh HS, Swanson ME, Tan S, Thomas DW, Thompson J, Uriarte M, Valencia R, Vicentini A, Vrška T, Wang XG, Weiblen GD, Wolf A, Wu SH, Xu H, Yamakura T, Yap S, Zimmerman JK. Global importance of large-diameter trees. Glob Ecol Biogeogr, 2018, 277): 849-864

[43] LY/T2809-2017 (2017) Technical regulation for cultivation of Chinese fir large-size timber. https://ndls.org.cn/standard/detail/b95e12cbdb3e1e9102244376b67d0e7f. (in Chinese)

[44] LY/T2908-2017 (2017) Regulations for age-class and age-group division of main tree-species. https://ndls.org.cn/standard/detail/e288ed0e2af0b35e4c2c60fd06e3c723. (in Chinese)

[45] MacKenzie WH, Mahony CR. An ecological approach to climate change-informed tree species selection for reforestation. For Ecol Manag, 2021, 481 118705

[46] Martins FB, Soares CPB, da Silva GF. Individual tree growth models for Eucalyptus in northern Brazil. Sci Agric, 2014, 71(3): 212-225

[47] Nepal P, Johnston CMT, Ganguly I. Effects on global forests and wood product markets of increased demand for mass timber. Sustainability, 2021, 13(24): 13943

[48] Paulo JA, Palma JHN, Gomes AA, Faias SP, Tomé J, Tomé M. Predicting site index from climate and soil variables for cork oak (Quercus suber L.) stands in Portugal. New for, 2015, 462293-307

[49] Pearl R, Reed LJ. On the rate of growth of the population of the United States since 1790 and its mathematical representation. Proc Natl Acad Sci U S A, 1920, 6(6): 275-288

[50] Percel G, Parmain G, Laroche F, Bouget C. The larger, the better? Effects of delayed diameter-limit cutting on old-growth attributes and saproxylic beetle diversity in temperate oak forests. Eur J for Res, 2018, 137(2): 237-249

[51] Perez-Garcia J, Joyce LA, Binkley CS, McGuire AD. Economic impacts of climatic change on the global forest sector: an integrated ecological/economic assessment. Crit Rev Environ Sci Technol, 1997, 27(sup001): 123-138

[52] Raschka S (2018) Model evaluation, model selection, and algorithm selection in machine learning. Preprint at https://arxiv.org/abs/1811.12808

[53] Ray DG, Seymour RS, Scott NA, Keeton WS. Mitigating climate change with managed forests: balancing expectations, opportunity, and risk. J for, 2009, 107(1): 50-51

[54] Richards FJ. A flexible growth function for empirical use. J Exp Bot, 1959, 10(2): 290-301

[55] Sarris D, Christodoulakis D. Topographic and climatic effects on Pinus halepensis s.l. growth at its drought tolerance margins under climatic change. J Forestry Res, 2024, 35(1 102

[56] Schumacher FX (1939) A new growth curve and its application to timber-yield studies

[57] Selvaraj S, Duraisamy V, Huang ZJ, Guo FT, Ma XQ. Influence of long-term successive rotations and stand age of Chinese fir (Cunninghamia lanceolata) plantations on soil properties. Geoderma, 2017, 306: 127-134

[58] Seynave I, Gégout JC, Hervé JC, Dhôte JF, Drapier J, Bruno É, Dumé G. Picea abiessite index prediction by environmental factors and understorey vegetation: a two-scale approach based on survey databases. Can J for Res, 2005, 357): 1669-1678

[59] Sharma M, Parton J. Height–diameter equations for boreal tree species in Ontario using a mixed-effects modeling approach. For Ecol Manag, 2007, 249(3): 187-198

[60] Simonsson P, Gustafsson L, Östlund L. Retention forestry in Sweden: driving forces, debate and implementation 1968–2003. Scand J for Res, 2015, 30(2): 154-173

[61] Socha J. Effect of topography and geology on the site index of Picea abies in the West Carpathian, Poland. Scand J for Res, 2008, 23(3): 203-213

[62] Song CS, Wang YL, Zhang LR, Cui CW, Peng LH, Lin KM, Ou YF, Fan FJ (2022) Effect of thinning intensity on timber structure of Chinese fir plantation. https://doi.org/10.13323/j.cnki.j.fafu(nat.sci.).2022.02.007

[63] Sun H, Lei J, Liu JJ, Li XY, Yuan DY, Duan AG, Zhang JG. Effects of planting density and site index on stand and soil nutrients in Chinese fir plantations. Sustainability, 2025, 17(13 5867

[64] Thiffault E, Hannam KD, Paré D, Titus BD, Hazlett PW, Maynard DG, Brais S. Effects of forest biomass harvesting on soil productivity in boreal and temperate forests—a review. Environ Rev, 2011, 192011): 278-309

[65] Thomas FM. Vertical rooting patterns of mature Quercus trees growing on different soil types in northern Germany. Plant Ecol, 2000, 147(1): 95-103

[66] Tian A, Wang YH, Webb AA, Liu ZB, Ma J, Yu PT, Wang X. Water yield variation with elevation, tree age and density of larch plantation in the Liupan Mountains of the Loess Plateau and its forest management implications. Sci Total Environ, 2021, 752 141752

[67] Van Pham M, Pham TM, Viet Du QV, Bui QT, Van Tran A, Pham HM, Nguyen TN. Integrating Sentinel-1A SAR data and GIS to estimate aboveground biomass and carbon accumulation for tropical forest types in Thuan Chau district, Vietnam. Remote Sens Appl Soc Environ, 2019, 14: 148-157

[68] Villela DM, Nascimento MT, de Aragão LEOC, Da Gama DM. Effect of selective logging on forest structure and nutrient cycling in a seasonally dry Brazilian Atlantic forest. J Biogeogr, 2006, 33(3): 506-516

[69] Vonesh EF, Chinchilli VM. Linear and nonlinear models for the analysis of repeated measurements, 1997, New York, M. Dekker

[70] Wang Y, LeMay VM, Baker TG. Modelling and prediction of dominant height and site index of Eucalyptus globulus plantations using a nonlinear mixed-effects model approach. Can J for Res, 2007, 37(8): 1390-1403

[71] Wang X, Huang XN, Wang YH, Yu PT, Guo JB. Impacts of site conditions and stand structure on the biomass allocation of single trees in larch plantations of Liupan Mountains of northwest China. Forests, 2022, 13(2): 177

[72] Ware GO, Ohki K, Moon LC. The Mitscherlich plant growth model for determining critical nutrient deficiency levels. Agron J, 1982, 74188-91

[73] Wei XX, Peng JF, Li JB, Li JK, Peng M, Li X, Liu YM, Li JX. Climate-growth relationships of Pinus tabuliformis along an altitudinal gradient on Baiyunshan Mountain, Central China. J for Res, 2023, 35(1 28

[74] Williams BA, Beyer HL, Fagan ME, Chazdon RL, Schmoeller M, Sprenkle-Hyppolite S, Griscom BW, Watson JEM, Tedesco AM, Gonzalez-Roglich M, Daldegan GA, Bodin B, Celentano D, Wilson SJ, Rhodes JR, Alexandre NS, Kim DH, Bastos D, Crouzeilles R. Global potential for natural regeneration in deforested tropical regions. Nature, 2024, 6368041): 131-137

[75] Winsor CP. The gompertz curve as a growth curve. Proc Natl Acad Sci U S A, 1932, 18(1): 1-8

[76] Wu CP, Jiang B, Yuan WG, Shen AH, Yang SZ, Yao SH, Liu JJ. On the management of large-diameter trees in China’s forests. Forests, 2020, 11(1 111

[77] Wu CY, Chen DS, Sun XM, Zhang SG. Influence of altitude and tree class on climate-growth relationships in a larch plantation in subtropical China. J for Res, 2023, 346): 1869-1880

[78] Xiang WH, Xu L, Lei PF, Ouyang S, Deng XW, Chen L, Zeng YL, Hu YT, Zhao ZH, Wu HL, Zeng LX, Xiao WF. Rotation age extension synergistically increases ecosystem carbon storage and timber production of Chinese fir plantations in Southern China. J Environ Manag, 2022, 317 115426

[79] Xie GL, Liu S, Chang T, Zhu NH. Forest adaptation to climate change: altitudinal response and wood variation in natural-growth Cunninghamia lanceolata in the context of climate change. Forests, 2024, 15(3 411

[80] Xu JC. China’s new forests aren’t as green as they seem. Nature, 2011, 4777365): 371

[81] Xu T. The summer solstice is the turning point when light and temperature affect the growth of trees. J for Res, 2023, 3461657

[82] Yang GJ, Duan AG, Deng LX., Sun JJ, Xiang CW, Zhang JG (2018) Thinning effects on merchantable wood assortment structure of Cunninghamia lanceolata plantations with different site indices based on permanent data

[83] Yang YQ, Huang S. Comparison of different methods for fitting nonlinear mixed forest models and for making predictions. Can J for Res, 2011, 4181671-1686

[84] You WB, Zhu GY. The minimum target diameter and the harvest age of oak natural secondary forests in different sites conditions: case study in Hunan Province, China. Forests, 2024, 15(1 120

[85] Yu W, Pan C, Guojia H, Feng HL, Chen J, Yu YC. Topsoil organic matter and its effect on the soil nutrients contents of Cunninghamia lanceolata plantations. Chin J Eco Agric, 2021, 2911): 1931-1939in Chinese

[86] Zell J, Hanewinkel M, Seeling U. Financial optimisation of target diameter harvest of European beech (Fagus sylvatica) considering the risk of decrease of timber quality due to red heartwood. Forum Policy Econ, 2004, 6(6): 579-593

[87] Zhang W. Forest site of China, 1997, Beijing, China Science Publishing House563

[88] Zhao Y, Deng XW, Xiang WH, Chen L, Ouyang S. Predicting potential suitable habitats of Chinese fir under current and future climatic scenarios based on Maxent model. Ecol Inform, 2021, 64 101393

[89] Zhu GY, Hu S, Chhin S, Zhang XQ, He P. Modelling site index of Chinese fir plantations using a random effects model across regional site types in Hunan Province, China. Forum Ecol Manag, 2019, 446: 143-150

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