IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v220y2009i13p1670-1680.html
   My bibliography  Save this article

Evaluation of the forest growth simulator SILVA on dominant trees in mature mixed Silver fir–Norway spruce stands in South-West Germany

Author

Listed:
  • Mette, Tobias
  • Albrecht, Axel
  • Ammer, Christian
  • Biber, Peter
  • Kohnle, Ulrich
  • Pretzsch, Hans

Abstract

Forest growth simulators go beyond a mere tabulation of empirical measurements by employing biometric models that functionally describe the dependence of forest growth of the initial forest structure, growth conditions and management regime. This makes them very flexible and allows predicting growth reactions for unknown and/or complex forest growth scenarios. When simulation outcomes are to be used in silvicultural strategic planning, the results are of direct and delicate importance, and the correct simulator performance must be ascertained. This is especially so when the considered forest situation differs from the forest data used to parameterise the model (e.g. different geographical region).

Suggested Citation

  • Mette, Tobias & Albrecht, Axel & Ammer, Christian & Biber, Peter & Kohnle, Ulrich & Pretzsch, Hans, 2009. "Evaluation of the forest growth simulator SILVA on dominant trees in mature mixed Silver fir–Norway spruce stands in South-West Germany," Ecological Modelling, Elsevier, vol. 220(13), pages 1670-1680.
    • Handle: RePEc:eee:ecomod:v:220:y:2009:i:13:p:1670-1680
    DOI: 10.1016/j.ecolmodel.2009.03.018
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380009002026
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ecolmodel.2009.03.018?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. R. B. Myneni & C. D. Keeling & C. J. Tucker & G. Asrar & R. R. Nemani, 1997. "Increased plant growth in the northern high latitudes from 1981 to 1991," Nature, Nature, vol. 386(6626), pages 698-702, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Pretzsch, Hans, 2022. "Facilitation and competition reduction in tree species mixtures in Central Europe: Consequences for growth modeling and forest management," Ecological Modelling, Elsevier, vol. 464(C).
    2. Schmid, Ueli & Frehner, Monika & Glatthorn, Jonas & Bugmann, Harald, 2023. "ProForM: A simulation model for the management of mountain protection forests," Ecological Modelling, Elsevier, vol. 478(C).
    3. M. Bošeľa & R. Petráš & Š. Šmelko, 2011. "Site classification vs. wood production: a case study based on Silver fir growth dynamics in the Western Carpathians," Journal of Forest Science, Czech Academy of Agricultural Sciences, vol. 57(10), pages 409-421.

    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. Ding, Yimin & Wang, Weiguang & Song, Ruiming & Shao, Quanxi & Jiao, Xiyun & Xing, Wanqiu, 2017. "Modeling spatial and temporal variability of the impact of climate change on rice irrigation water requirements in the middle and lower reaches of the Yangtze River, China," Agricultural Water Management, Elsevier, vol. 193(C), pages 89-101.
    2. F. Nelson & O. Anisimov & N. Shiklomanov, 2002. "Climate Change and Hazard Zonation in the Circum-Arctic Permafrost Regions," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 26(3), pages 203-225, July.
    3. Zhang, Yixiao & He, Tao & Liang, Shunlin & Zhao, Zhongguo, 2023. "A framework for estimating actual evapotranspiration through spatial heterogeneity-based machine learning approaches," Agricultural Water Management, Elsevier, vol. 289(C).
    4. Craig D. Idso, 2001. "Earth's Rising Atmospheric Co2 Concentration: Impacts on the Biosphere," Energy & Environment, , vol. 12(4), pages 287-310, July.
    5. Jörg Kaduk & Sietse Los, 2011. "Predicting the time of green up in temperate and boreal biomes," Climatic Change, Springer, vol. 107(3), pages 277-304, August.
    6. Patricia Arrogante-Funes & Carlos J. Novillo & Raúl Romero-Calcerrada, 2018. "Monitoring NDVI Inter-Annual Behavior in Mountain Areas of Mainland Spain (2001–2016)," Sustainability, MDPI, vol. 10(12), pages 1-24, November.
    7. Lausch, Angela & Salbach, Christoph & Schmidt, Andreas & Doktor, Daniel & Merbach, Ines & Pause, Marion, 2015. "Deriving phenology of barley with imaging hyperspectral remote sensing," Ecological Modelling, Elsevier, vol. 295(C), pages 123-135.
    8. Shi, Yusheng & Sasai, Takahiro & Yamaguchi, Yasushi, 2014. "Spatio-temporal evaluation of carbon emissions from biomass burning in Southeast Asia during the period 2001–2010," Ecological Modelling, Elsevier, vol. 272(C), pages 98-115.
    9. Zongxing, Li & Qi, Feng & Zongjie, Li & Xufeng, Wang & Juan, Gui & Baijuan, Zhang & Yuchen, Li & Xiaohong, Deng & Jian, Xue & Wende, Gao & Anle, Yang & Fusen, Nan & Pengfei, Liang, 2021. "Reversing conflict between humans and the environment － The experience in the Qilian Mountains," Renewable and Sustainable Energy Reviews, Elsevier, vol. 148(C).
    10. Kathuroju, Naven & White, Michael A. & Symanzik, Jürgen & Schwartz, Mark D. & Powell, James A. & Nemani, Ramakrishna R., 2007. "On the use of the advanced very high resolution radiometer for development of prognostic land surface phenology models," Ecological Modelling, Elsevier, vol. 201(2), pages 144-156.
    11. Mo, Yu & Momen, Bahram & Kearney, Michael S., 2015. "Quantifying moderate resolution remote sensing phenology of Louisiana coastal marshes," Ecological Modelling, Elsevier, vol. 312(C), pages 191-199.
    12. Richard Tol, 2013. "The economic impact of climate change in the 20th and 21st centuries," Climatic Change, Springer, vol. 117(4), pages 795-808, April.
    13. Yangyang Wu & Lei Gu & Siliang Li & Chunzi Guo & Xiaodong Yang & Yue Xu & Fujun Yue & Haijun Peng & Yinchuan Chen & Jinli Yang & Zhenghua Shi & Guangjie Luo, 2022. "Responses of NDVI to Climate Change and LUCC along Large-Scale Transportation Projects in Fragile Karst Areas, SW China," Land, MDPI, vol. 11(10), pages 1-16, October.
    14. Shanin, Vladimir & Komarov, Alexander & Khoraskina, Yulia & Bykhovets, Sergey & Linkosalo, Tapio & Mäkipää, Raisa, 2013. "Carbon turnover in mixed stands: Modelling possible shifts under climate change," Ecological Modelling, Elsevier, vol. 251(C), pages 232-245.
    15. Ken Mix & Vicente Lopes & Walter Rast, 2012. "Growing season expansion and related changes in monthly temperature and growing degree days in the Inter-Montane Desert of the San Luis Valley, Colorado," Climatic Change, Springer, vol. 114(3), pages 723-744, October.
    16. Rongjun Wu & Qi Li, 2021. "Assessing the soil moisture drought index for agricultural drought monitoring based on green vegetation fraction retrieval methods," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 108(1), pages 499-518, August.
    17. Andrew MacLachlan & Eloise Biggs & Gareth Roberts & Bryan Boruff, 2017. "Urban Growth Dynamics in Perth, Western Australia: Using Applied Remote Sensing for Sustainable Future Planning," Land, MDPI, vol. 6(1), pages 1-14, January.
    18. Prates-Clark, Cássia Da Conceição & Saatchi, Sassan S. & Agosti, Donat, 2008. "Predicting geographical distribution models of high-value timber trees in the Amazon Basin using remotely sensed data," Ecological Modelling, Elsevier, vol. 211(3), pages 309-323.
    19. F. Orlandi & H. Garcia-Mozo & A. Dhiab & C. Galán & M. Msallem & B. Romano & M. Abichou & E. Dominguez-Vilches & M. Fornaciari, 2013. "Climatic indices in the interpretation of the phenological phases of the olive in mediterranean areas during its biological cycle," Climatic Change, Springer, vol. 116(2), pages 263-284, January.
    20. Yongcai Dang & Hongshi He & Dandan Zhao & Michael Sunde & Haibo Du, 2020. "Quantifying the Relative Importance of Climate Change and Human Activities on Selected Wetland Ecosystems in China," Sustainability, MDPI, vol. 12(3), pages 1-17, January.

    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:220:y:2009:i:13:p:1670-1680. 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.