Dominant height growth and site index curves for Calabrian pine (Pinus brutia Ten.) in central Cyprus
Author
Abstract
Suggested Citation
DOI: 10.1016/j.rser.2011.10.010
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- Aertsen, Wim & Kint, Vincent & van Orshoven, Jos & Özkan, Kürşad & Muys, Bart, 2010. "Comparison and ranking of different modelling techniques for prediction of site index in Mediterranean mountain forests," Ecological Modelling, Elsevier, vol. 221(8), pages 1119-1130.
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.- Seyed Naghibi & Hamid Pourghasemi, 2015. "A Comparative Assessment Between Three Machine Learning Models and Their Performance Comparison by Bivariate and Multivariate Statistical Methods in Groundwater Potential Mapping," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(14), pages 5217-5236, November.
- Alexandra M. Thorn & Jonathan R. Thompson & Joshua S. Plisinski, 2016. "Patterns and Predictors of Recent Forest Conversion in New England," Land, MDPI, vol. 5(3), pages 1-17, September.
- Eslam Mohammed Abdelkader & Abobakr Al-Sakkaf & Ghasan Alfalah & Nehal Elshaboury, 2022. "Hybrid Differential Evolution-Based Regression Tree Model for Predicting Downstream Dam Hazard Potential," Sustainability, MDPI, vol. 14(5), pages 1-21, March.
- Saeedeh Eskandari & Mahdis Amiri & Nitheshnirmal Sãdhasivam & Hamid Reza Pourghasemi, 2020. "Comparison of new individual and hybrid machine learning algorithms for modeling and mapping fire hazard: a supplementary analysis of fire hazard in different counties of Golestan Province in Iran," 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. 104(1), pages 305-327, October.
- Kint, V. & Aertsen, W. & Fyllas, N.M. & Trabucco, A. & Janssen, E. & Özkan, K. & Muys, B., 2014. "Ecological traits of Mediterranean tree species as a basis for modelling forest dynamics in the Taurus mountains, Turkey," Ecological Modelling, Elsevier, vol. 286(C), pages 53-65.
- Aleksandr Lebedev & Valery Kuzmichev, 2020. "Verification of two- and three-parameter simple height-diameter models for birch in the European part of Russia," Journal of Forest Science, Czech Academy of Agricultural Sciences, vol. 66(9), pages 375-382.
- Hunt, Allen G. & Faybishenko, Boris & Powell, Thomas L., 2020. "A new phenomenological model to describe root-soil interactions based on percolation theory," Ecological Modelling, Elsevier, vol. 433(C).
- Tingyu Zhang & Quan Fu & Hao Wang & Fangfang Liu & Huanyuan Wang & Ling Han, 2022. "Bagging-based machine learning algorithms for landslide susceptibility modeling," 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. 110(2), pages 823-846, January.
- Confalonieri, R. & Bregaglio, S. & Acutis, M., 2012. "Quantifying plasticity in simulation models," Ecological Modelling, Elsevier, vol. 225(C), pages 159-166.
- Huseyin Ozturk & Ersin Namli & Halil Ibrahim Erdal, 2016. "Reducing Overreliance on Sovereign Credit Ratings: Which Model Serves Better?," Computational Economics, Springer;Society for Computational Economics, vol. 48(1), pages 59-81, June.
- Pecchi, Matteo & Marchi, Maurizio & Burton, Vanessa & Giannetti, Francesca & Moriondo, Marco & Bernetti, Iacopo & Bindi, Marco & Chirici, Gherardo, 2019. "Species distribution modelling to support forest management. A literature review," Ecological Modelling, Elsevier, vol. 411(C).
- Hamid Reza Pourghasemi & Soheila Pouyan & Mojgan Bordbar & Foroogh Golkar & John J. Clague, 2023. "Flood, landslides, forest fire, and earthquake susceptibility maps using machine learning techniques and their combination," 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. 116(3), pages 3797-3816, April.
- Indrajit Chowdhuri & Subodh Chandra Pal & Rabin Chakrabortty & Sadhan Malik & Biswajit Das & Paramita Roy, 2021. "Torrential rainfall-induced landslide susceptibility assessment using machine learning and statistical methods of eastern Himalaya," 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. 107(1), pages 697-722, May.
- Hillary Mugiyo & Vimbayi G. P. Chimonyo & Mbulisi Sibanda & Richard Kunz & Cecilia R. Masemola & Albert T. Modi & Tafadzwanashe Mabhaudhi, 2021. "Evaluation of Land Suitability Methods with Reference to Neglected and Underutilised Crop Species: A Scoping Review," Land, MDPI, vol. 10(2), pages 1-24, January.
- Díaz-Yáñez, Olalla & Mola-Yudego, Blas & González-Olabarria, José Ramón, 2019. "Modelling damage occurrence by snow and wind in forest ecosystems," Ecological Modelling, Elsevier, vol. 408(C), pages 1-1.
- Bosy A. El-Haddad & Ahmed M. Youssef & Hamid R. Pourghasemi & Biswajeet Pradhan & Abdel-Hamid El-Shater & Mohamed H. El-Khashab, 2021. "Flood susceptibility prediction using four machine learning techniques and comparison of their performance at Wadi Qena Basin, Egypt," 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. 105(1), pages 83-114, January.
More about this item
Keywords
Cyprus; Difference equations; Growth model; Pinus brutia; Site index;All these keywords.
Statistics
Access and download statisticsCorrections
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:rensus:v:16:y:2012:i:2:p:1323-1329. 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.elsevier.com/wps/find/journaldescription.cws_home/600126/description#description .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.