IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v495y2024ics0304380024001777.html
   My bibliography  Save this article

The performance of 3-PG model in Chinese fir plantations with different initial densities in southern China

Author

Listed:
  • Nie, Wen
  • Liu, Jianfeng
  • Wang, Qi
  • Huang, Ruizhi
  • Zhao, Yipei
  • Yang, Shaowei
  • Sun, Jingyi
  • Xiao, Wenfa
  • Duan, Aiguo
  • Xiao, Yihua
  • Wang, Zuyuan

Abstract

Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.) is the most widely distributed conifer species in the subtropical region of southern China. Due to its ecological and economic significance, accurate prediction of growth of Chinese fir plantations is crucial for forest management and industrial timber production. In this study, we employed a physiologically process-based model (3-PG) to simulate the growth dynamic of Chinese fir plantations under various initial planting densities in southern China. Calibration and validation results indicated that the model outputs have strong correlations with the observed data (R2 > 0.79, p < 0.01), except foliage biomass and root biomass. Self-thinning will occur earlier at higher initial planting densities, and stand DBH and height will increase dramatically afterwards. Sensitivity analysis further revealed that the FR (soil fertility rating), alphaCx and gammaN1 parameters were highly sensitive in the 3-PG model (p < 0.01), while their sensitivity was influenced by stand age and initial density variations. This study confirmed that the parameter-specific optimized 3-PG model could accurately predict the growth process of Chinese fir plantations under different densities. It will provide a scientific reference for regional-scale management of Chinese fir plantations.

Suggested Citation

  • Nie, Wen & Liu, Jianfeng & Wang, Qi & Huang, Ruizhi & Zhao, Yipei & Yang, Shaowei & Sun, Jingyi & Xiao, Wenfa & Duan, Aiguo & Xiao, Yihua & Wang, Zuyuan, 2024. "The performance of 3-PG model in Chinese fir plantations with different initial densities in southern China," Ecological Modelling, Elsevier, vol. 495(C).
    • Handle: RePEc:eee:ecomod:v:495:y:2024:i:c:s0304380024001777
    DOI: 10.1016/j.ecolmodel.2024.110789
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380024001777
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ecolmodel.2024.110789?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Xenakis, Georgios & Ray, Duncan & Mencuccini, Maurizio, 2008. "Sensitivity and uncertainty analysis from a coupled 3-PG and soil organic matter decomposition model," Ecological Modelling, Elsevier, vol. 219(1), pages 1-16.
    2. Gupta, Rajit & Sharma, Laxmi Kant, 2019. "The process-based forest growth model 3-PG for use in forest management: A review," Ecological Modelling, Elsevier, vol. 397(C), pages 55-73.
    3. Kai Cheng & Haitao Yang & Shengli Tao & Yanjun Su & Hongcan Guan & Yu Ren & Tianyu Hu & Wenkai Li & Guangcai Xu & Mengxi Chen & Xiancheng Lu & Zekun Yang & Yanhong Tang & Keping Ma & Jingyun Fang & Qi, 2024. "Carbon storage through China’s planted forest expansion," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    4. Song, Xiaodong & Bryan, Brett A. & Almeida, Auro C. & Paul, Keryn I. & Zhao, Gang & Ren, Yin, 2013. "Time-dependent sensitivity of a process-based ecological model," Ecological Modelling, Elsevier, vol. 265(C), pages 114-123.
    5. Karl-Heinz Erb & Thomas Kastner & Christoph Plutzar & Anna Liza S. Bais & Nuno Carvalhais & Tamara Fetzel & Simone Gingrich & Helmut Haberl & Christian Lauk & Maria Niedertscheider & Julia Pongratz & , 2018. "Unexpectedly large impact of forest management and grazing on global vegetation biomass," Nature, Nature, vol. 553(7686), pages 73-76, January.
    6. Belinda E. Medlyn & Remko A. Duursma & Melanie J. B. Zeppel, 2011. "Forest productivity under climate change: a checklist for evaluating model studies," Wiley Interdisciplinary Reviews: Climate Change, John Wiley & Sons, vol. 2(3), pages 332-355, May.
    7. Forrester, David I. & Tang, Xiaolu, 2016. "Analysing the spatial and temporal dynamics of species interactions in mixed-species forests and the effects of stand density using the 3-PG model," Ecological Modelling, Elsevier, vol. 319(C), pages 233-254.
    8. Yamaura, Yuichi & Yamada, Yusuke & Matsuura, Toshiya & Tamai, Koji & Taki, Hisatomo & Sato, Tamotsu & Hashimoto, Shoji & Murakami, Wataru & Toda, Kenichiro & Saito, Hitoshi & Nanko, Kazuki & Ito, Erik, 2021. "Modeling impacts of broad-scale plantation forestry on ecosystem services in the past 60 years and for the future," Ecosystem Services, Elsevier, vol. 49(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Xie, Yalin & Lei, Xiangdong & Shi, Jingning, 2020. "Impacts of climate change on biological rotation of Larix olgensis plantations for timber production and carbon storage in northeast China using the 3-PGmix model," Ecological Modelling, Elsevier, vol. 435(C).
    2. Nölte, Anja & Yousefpour, Rasoul & Hanewinkel, Marc, 2020. "Changes in sessile oak (Quercus petraea) productivity under climate change by improved leaf phenology in the 3-PG model," Ecological Modelling, Elsevier, vol. 438(C).
    3. Lessa Derci Augustynczik, Andrey & Yousefpour, Rasoul, 2021. "Assessing the synergistic value of ecosystem services in European beech forests," Ecosystem Services, Elsevier, vol. 49(C).
    4. Gupta, Rajit & Sharma, Laxmi Kant, 2019. "The process-based forest growth model 3-PG for use in forest management: A review," Ecological Modelling, Elsevier, vol. 397(C), pages 55-73.
    5. Forrester, David I. & England, Jacqueline R. & Paul, Keryn I. & Roxburgh, Stephen H., 2024. "Sensitivity analysis of the FullCAM model: Context dependency and implications for model development to predict Australia's forest carbon stocks," Ecological Modelling, Elsevier, vol. 489(C).
    6. Barbosa, Lorena Oliveira & dos Santos, Juscelina Arcanjo & Gonçalves, Anny Francielly Ataide & Campoe, Otávio Camargo & Scolforo, José Roberto Soares & Scolforo, Henrique Ferraço, 2023. "Competition in forest plantations: Empirical and process-based modelling in pine and eucalypt plantations," Ecological Modelling, Elsevier, vol. 483(C).
    7. Mathys, A.S. & Coops, N.C. & Simard, S.W. & Waring, R.H. & Aitken, S.N., 2018. "Diverging distribution of seedlings and mature trees reflects recent climate change in British Columbia," Ecological Modelling, Elsevier, vol. 384(C), pages 145-153.
    8. Myrgiotis, Vasileios & Blei, Emanuel & Clement, Rob & Jones, Stephanie K. & Keane, Ben & Lee, Mark A. & Levy, Peter E. & Rees, Robert M. & Skiba, Ute M. & Smallman, Thomas Luke & Toet, Sylvia & Willia, 2020. "A model-data fusion approach to analyse carbon dynamics in managed grasslands," Agricultural Systems, Elsevier, vol. 184(C).
    9. Stephen B. Stewart & Anthony P. O’Grady & Daniel S. Mendham & Greg S. Smith & Philip J. Smethurst, 2022. "Digital Tools for Quantifying the Natural Capital Benefits of Agroforestry: A Review," Land, MDPI, vol. 11(10), pages 1-32, September.
    10. Janusz Szmyt & Monika Dering, 2024. "Adaptive Silviculture and Climate Change—A Forced Marriage of the 21st Century?," Sustainability, MDPI, vol. 16(7), pages 1-31, March.
    11. Beverly E. Law & William R. Moomaw & Tara W. Hudiburg & William H. Schlesinger & John D. Sterman & George M. Woodwell, 2022. "Creating Strategic Reserves to Protect Forest Carbon and Reduce Biodiversity Losses in the United States," Land, MDPI, vol. 11(5), pages 1-15, May.
    12. Tang, Zhang-Chun & Zuo, Ming J. & Xiao, Ningcong, 2016. "An efficient method for evaluating the effect of input parameters on the integrity of safety systems," Reliability Engineering and System Safety, Elsevier, vol. 145(C), pages 111-123.
    13. Pretzsch, Hans & Forrester, David I. & Rötzer, Thomas, 2015. "Representation of species mixing in forest growth models. A review and perspective," Ecological Modelling, Elsevier, vol. 313(C), pages 276-292.
    14. Turley, Marianne C. & Ford, E. David, 2009. "Definition and calculation of uncertainty in ecological process models," Ecological Modelling, Elsevier, vol. 220(17), pages 1968-1983.
    15. Bagnara, Maurizio & Van Oijen, Marcel & Cameron, David & Gianelle, Damiano & Magnani, Federico & Sottocornola, Matteo, 2018. "Bayesian calibration of simple forest models with multiplicative mathematical structure: A case study with two Light Use Efficiency models in an alpine forest," Ecological Modelling, Elsevier, vol. 371(C), pages 90-100.
    16. Lei Chang & Han Luo & Huijia Liu & Wenxin Xu & Lixin Zhang & Yuefen Li, 2024. "Tracking Land-use Trajectory and Other Potential Drivers to Uncover the Dynamics of Carbon Stocks of Terrestrial Ecosystem in the Songnen Plain," Land, MDPI, vol. 13(5), pages 1-20, May.
    17. Simant Rimal & Marc Djahangard & Rasoul Yousefpour, 2022. "Forest Management under Climate Change: A Decision Analysis of Thinning Interventions for Water Services and Biomass in a Norway Spruce Stand in South Germany," Land, MDPI, vol. 11(3), pages 1-18, March.
    18. Suman Paudel & Gustavo A. Ovando-Montejo & Christopher L. Lant, 2021. "Human Appropriation of Net Primary Production: From a Planet to a Pixel," Sustainability, MDPI, vol. 13(15), pages 1-12, August.
    19. Chen, Yizhao & Fei, Xinran & Groisman, Pavel & Sun, Zhengguo & Zhang, Jianan & Qin, Zhihao, 2019. "Contrasting policy shifts influence the pattern of vegetation production and C sequestration over pasture systems: A regional-scale comparison in Temperate Eurasian Steppe," Agricultural Systems, Elsevier, vol. 176(C).
    20. Collalti, Alessio & Perugini, Lucia & Santini, Monia & Chiti, Tommaso & Nolè, Angelo & Matteucci, Giorgio & Valentini, Riccardo, 2014. "A process-based model to simulate growth in forests with complex structure: Evaluation and use of 3D-CMCC Forest Ecosystem Model in a deciduous forest in Central Italy," Ecological Modelling, Elsevier, vol. 272(C), pages 362-378.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecomod:v:495:y:2024:i:c:s0304380024001777. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/ecological-modelling .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.