Ecoregion-based height-diameter models for Crimean pine

References

• Adame P, del Río M, Canellas I. 2008. A mixed nonlinear height-diameter model for pyrenean oak (Quercus pyrenaica Willd.). For Ecol Manage. 256(1–2):88–98. doi:https://doi.org/10.1016/j.foreco.2008.04.006.
   Web of Science ®Google Scholar
• Álvarez-González JG, Ruíz González AD, Rodriguez Soalleiro R, Barrio Anta M. 2005. Ecoregional site index models for Pinus pinaster in Galicia (northwestern Spain). Ann For Sci. 62(2):115–127. doi:https://doi.org/10.1051/forest:2005003.
   Web of Science ®Google Scholar
• Atalay İ. 2014. Ecoregions of Turkey. İzmir (Turkey): Meta Basim.
   Google Scholar
• Bailey RG. 2009. Ecosystem geography: from ecoregions to sites. Springer Science & Business Media.
   Google Scholar
• Bernert JA, Eilers JM, Freemark KE, Ribic C. 1997. A quantitative method for delineating regions: an example for the western corn belt plains ecoregion of the USA. Environ Manage. 21(3):405–420. doi:https://doi.org/10.1007/s002679900038.
   PubMed Web of Science ®Google Scholar
• Brooks JR, Wiant HV. 2005. Evaluating ecoregion-based height-diameter relationship of five economically important Appalachian hardwood species in West Virginia. In: McRoberts RE, Reams GA, Van Deusen PC, McWilliams WH, editors. Proceedings of seventh annual forest inventory and analysis symposium. Portland (OR); p. 237–242.
   Google Scholar
• Calama R, Montero G. 2004. Interregional nonlinear height diameter model with random coefficients for stone pine in Spain. Can J For Res. 34(1):150–163. doi:https://doi.org/10.1139/x03-199.
   Web of Science ®Google Scholar
• Çatal Y, Carus S. 2018. A height-diameter model for brutian pine (Pinus brutia Ten.) plantations in southwestern Turkey. Appl Ecol Environ Res. 16(2):1445–1459. doi:https://doi.org/10.15666/aeer/1602_14451459.
   Web of Science ®Google Scholar
• Curtis RO. 1967. Height-diameter and height-diameter-age equations for second-growth Douglas-fir. For Sci. 13(4):365–375.
   Google Scholar
• Curtis RO, Clendenan G, DeMars DJ 1981. A new stand simulator for coast douglas-fir: DFSIM users guide. USDA Forest Service General Technical Report, PNW-128., Portland.
   Google Scholar
• Ercanli İ, Kahriman A, Yavuz H. 2012. The construction of diameter-height models based on nonlinear mixed effect regression equations for oriental spruce located in mixed oriental spruce-scotch pine stands at Trabzon Forest District. SDU Fac For J. 13(2):75–84.
   Google Scholar
• Gaffrey D. 1988. Forstamts-und Bestandsindividuelles Sortimentierungsprogramm als Mittel zur Planung, Aushaltung und Simulation. Göttingen: Diplomarbeit Forscliche Fakultät, Universität Göttingen.
   Google Scholar
• GDF. 2019. Forestry statistics 2019. Ankara (Turkey):General Directorate of Forestry Publications.
   Google Scholar
• Huang S. 1999. Ecoregion-based individual tree height-diameter models for lodgepole pine in Alberta. West J Appl For. 14(4):186–193. doi:https://doi.org/10.1093/wjaf/14.4.186.
   Google Scholar
• Huang S, Price D, Titus SJ. 2000. Development of ecoregion-based height-diameter models for white spruce in boreal forests. For Ecol Manage. 129(1–3):125–141. doi:https://doi.org/10.1016/S0378-1127(99)00151-6.
   Web of Science ®Google Scholar
• Meyer HA. 1940. A mathematical expression for height curves. J For. 38(5):415–420.
   Google Scholar
• Mirkovich JL. 1958. Normale visinske krive za chrast kitnak I bukvu v NR Srbiji. Zagreb Glasnik Sumarskog Fakulteta. 13:43–56.
   Google Scholar
• Misir N. 2010. Generalized height-diameter models for Populus tremula L. stands. Afr J Biotechnol. 9(28):4348–4355.
   Google Scholar
• Neter J, Wassermaann W, Kutner M. 1990. Applied linear statistical models. 2 ed. Irwin: Homewood Illinois; p. 1181.
   Google Scholar
• Nilson A. 1999. Pidev metsakorraldus-mis see on. Pidev metsakorraldus. EPMÜ Metsandusteaduskonna Toimetised. 32:4–13.
   Google Scholar
• Özçelik R, Diamantopoulou MJ, Crecente-Campo F, Eler U. 2013. Estimating Crimean juniper tree height using nonlinear regression and artificial neural network models. For Ecol Manage. 306:52–60. doi:https://doi.org/10.1016/j.foreco.2013.06.009.
   Web of Science ®Google Scholar
• Özçelik R, Karatepe Y, Gürlevik N, Cañellas I, Crecente-Campo F. 2016. Development of ecoregion-based merchantable volume systems for Pinus brutia Ten. and Pinus nigra Arnold. in southern Turkey. J For Res. 27(1):101–117. doi:https://doi.org/10.1007/s11676-015-0147-4.
   Google Scholar
• Özçelik R, Yavuz H, Karatepe Y, Gürlevik N, Kiriş R. 2014. Development of ecoregion-based height-diameter models for 3 economically important tree species of southern Turkey. Turk J Agric For. 38(3):399–412. doi:https://doi.org/10.3906/tar-1304-115.
   Web of Science ®Google Scholar
• Ozkal M, Atar D, Aydin M, Tunc F. 2021. Comparison of traditional regression models and artificial neural network models for height-diameter modeling in uneven-aged fir stands. Journal of Biometry Studies. 1(1):1–7. doi:https://doi.org/10.29329/JofBS.2021.348.01.
   Google Scholar
• Peng C, Zhang L, Zhou X, Dang Q, Huang S. 2004. Developing and evaluating tree height-diameter models at three geographic scales for black spruce in Ontario. North J Appl For. 21(2):83–92. doi:https://doi.org/10.1093/njaf/21.2.83.
   Google Scholar
• Pienaar LV, Harrison WM, Rheney JW. 1991. PMRC yield prediction system for slash pine plantations in the Atlantic coast flatwoods. Athens: Plantation Management Research Cooperative Technical Report.
   Google Scholar
• Pillsbury NH, McDonald PM, Simon V. 1995. Reliability of tanoak volume equations when applied to different areas. West J Appl For. 10(2):72–78. doi:https://doi.org/10.1093/wjaf/10.2.72.
   Google Scholar
• Poudel KP, Cao QV. 2013. Evaluation of methods to predict Weibull parameters for characterizing diameter distributions. For Sci. 59(2):243–252. doi:https://doi.org/10.5849/forsci.12-001.
   Google Scholar
• Richards FJ. 1959. A flexible growth function for empirical use. J Exp Bot. 10(2):290–301. doi:https://doi.org/10.1093/jxb/10.2.290.
   Web of Science ®Google Scholar
• Saatçioğlu F. 1979. Silvikültür tekniği (Silvikültür II). İstanbul (Turkey): İstanbul University Faculty of Forestry Publications.
   Google Scholar
• Sakici OE, Sağlam F, Seki M. 2018. Single- and double-entry volume equations for Crimean pine stands in Kastamonu Regional Directorate of Forestry. Turkish Journal of Forestry. 19(1):20–29.
   Google Scholar
• SAS Institute Inc. 2004. SAS/ETS® 9.1 User’s guide. Cary (NC):SAS Institute Inc.
   Google Scholar
• Schnute J. 1981. A versatile growth model with statistically stable parameters. Can J Fish Aquat. 38(9):1128–1140. doi:https://doi.org/10.1139/f81-153.
   Web of Science ®Google Scholar
• Sharma M, Parton J. 2007. Height-diameter equations for boreal tree species in Ontario using a mixed-effects modeling approach. For Ecol Manage. 249(3):187–198. doi:https://doi.org/10.1016/j.foreco.2007.05.006.
   Web of Science ®Google Scholar
• Sonmez T. 2009. Generalized height-diameter models for Picea orientalis L. J Environ Biol. 30(5):767–772.
   Web of Science ®Google Scholar
• Stankova TV, Diéguez-Aranda U. 2013. Height-diameter relationships for Scots pine plantations in Bulgaria: optimal combination of model type and application. Ann For Sci. 56(1):149–163.
   Google Scholar
• Temesgen H, Gadow KV. 2004. Generalized height–diameter models—an application for major tree species in complex stands of interior British Columbia. Eur J Forest Res. 123(1):45–51. doi:https://doi.org/10.1007/s10342-004-0020-z.
   Web of Science ®Google Scholar
• van Laar A, Akça A. 2007. Forest mensuration. Germany: Goettingen.
   Google Scholar
• Wang M, Tang S. 2002. Research on universal height-diameter curves. Reality, models and parameter estimation- the forestry scenario. Sesimbra (Portugal).
   Google Scholar
• Zhang L, Peng C, Huang S, Zhou X. 2002. Development and evaluation of ecoregion-based jack pine height-diameter models for Ontario. For Chron. 78(4):530–538. doi:https://doi.org/10.5558/tfc78530-4.
   Google Scholar