Growth and yield models for uneven-aged forest stands managed under a selection system in northern Iran

Year 2019, Volume: 7 Issue: 3, 321 - 333, 29.10.2019

Siavash Kalbi , Asghar Fallah Shaban Shataee Pete Bettinger Rassoul Yousefpour

https://doi.org/10.31195/ejejfs.569197

Cited By: 4

Abstract

Predicting future forest growth and yield is a key
element of sustainable forest management. Hyrcanian forests are the most
valuable forests in the north of Iran, and industrial harvesting occurs only in
this area of the country. While uneven-aged Hyrcanian forests are one of the most important vegetated
areas, and the only commercial forests in Iran, there is a lack of growth and
yield models for management and planning purposes. The aim of this study is to develop distance-independent
individual tree growth and yield models for uneven-aged forests in northern
Iran managed under selection systems.A distance-independent diameter growth
model, a static height model, an ingrowth model, and a survival model for
uneven-aged stands of Fagus orientalis
Lipsky were developed using measurements from Sangdeh, within the Mazandaran
providence in Iran. The models are based on 130 permanent sample plots
established in 2009 and remeasured in 2014. For modeling diameter and height
growth, we employed mixed effect regression. For modeling survival, we used
binary logistic regression analysis. Ingrowth was modeled using multilinear
regression. Results showed the best growth and yield model had relative RMSE
and bias values, respectively, that were 31.9% and 6.3% for the diameter growth
model, 11.3% and 0.17% for the height model, and 22% and 0.14% for the ingrowth
model. Wald tests and other model evolution parameters showed that the
parameter estimates for tree mortality were statistically significant. Overall
results indicated that growth and yield model performance was consistent with
expectations, and that the general fit to the validation data was acceptable

Keywords

Individual-tree model, mixed effect regression, diameter and height growth, tree mortality

Supporting Institution

this study has no supported

References

• Adame, P., Hynynen, J., Cañellas, I., del Río, M. (2008). Individual-tree diameter growth model for rebollo oak (Quercus pyrenaica Willd.) coppices. For. Ecol. Manage. 255: 1011–1022.Agresti, A. 1996. An Introduction to Categorical Data Analysis; Wiley: New York, NY, USA. 290 p.
• Bayat, M., Pukkala, T., Namiranian, M., and Zobeiri, M. (2013). Productivity and optimal management of the uneven-aged hardwood forests of Hyrcania. Eur. J. For. Res. 132: 851–864.
• Biging, G.S. (1985). Improved estimates of site index curves using a varying-parameter model. Forest Science 31: 248–257.
• Bravo, F., del Río, M., Pando, V., San Martin, R., Montero, G., Ordoñez, C., Cañellas, I. (2002). El diseño de las parcelas del Inventario Forestal Nacionaly la estimación de variables dasométricas. In: Bravo, F., del Río, M., del El Peso, C. (eds.), El Inventario Forestal Nacional. Elemento clave para la Gestión Forestal Sostenible Palencia, pp. 19-35.
• Bravo, F., Pando, V. Ordóñez, C., Lizarralde I. (2008). Modelling ingrowth in mediterranean pine forests: A case study from scots pine (Pinus sylvestris L.) and Mediterranean maritime pine (Pinus pinaster Ait.) stands in Spain. Investigación Agraria: Sistemas y Recursos Forestales. 17(3): 250-260.
• Budhathoki, C.B., Lynch, T.B., Guldin, J.M. (2008). Nonlinear mixed modeling of basal area growth for shortleaf pine. For. Ecol. Manage. 255: 3440–3446.
• Calama, R., Montero, G. 2005. Multilevel linear mixed model for tree diameter increment in stone pine (Pinus pinea): A calibrating approach. Silva Fenn. 39, 37–54.
• Crecente-Campo, F., Soares, P., Tome, M., Dieguez-Aranda U. (2010). Modelling annual individual-tree growth and mortality of Scots pine with data obtained at irregular measurement intervals and containing missing observations. For. Ecol. Manage. 260: 1965-1974.
• Curtis, R.O., Clendenen, G.W., Demars, D.J. (1981). A new stand simulator for Coast Douglas-fir: DFSIM user’s guide. U.S. Forest Service, Pacific Northwest Forest and Range Experiment Station, Portland, Oregon. Gen. Tech. Rep. PNW-128.
• Wykoff, W.R. (1990). A basal area increment model for individual conifers in the northern Rocky Mountains. For. Sci. 36: 1077-1104.
• Daniel, T.W., Helms, J.A., Baker, F.S. (1979). Principles of Silviculture, 2nd edition. McGraw-Hill, New York. 500 p.
• Eid T., Tuhus E. (2001). Models for individual tree mortality in Norway, For. Ecol. Manage. 154: 69–84.
• Ek, A.R. (1974). Nonlinear models for stand table projection in northern hardwood stands. Can. J. For. Res. 4: 23-27.
• Fox, J.C., Ades, P.K., Bi, H. (2001). Stochastic structure and individual-tree growth models. For. Ecol. Manage.154: 261–276.
• Fridman, J., Stahl, G. (2001). A three-step approach for modelling tree mortality in Swedish Forests. Scand. J. For. Res. 16: 455–466.
• Gregoire, T.G. (1987). Generalized error structure for forestry yield models. For. Sci. 33: 423–444.
• Groot, A., Gauthier, S., Bergeron, Y. (2004). Stand dynamics modeling approaches for multicohort management of eastern Canadian boreal forests. Silva Fenn. 38 (4): 437-448.
• Hasenauer, H.E. (2006). Sustainable Forest Management: Growth Models for Europe. Berlin, Heidelberg, Springer-Verlag: 388.
• Kimmins, J.P. (1990). Modeling the sustainability of forest production and yield for a changing and uncertain future. For. Chron, 66:271–280.
• Kimmins, J.P. (1997). Forest ecology: a foundation for sustainable management, 2nd edn. Prentice Hall, New Jersey, p 596.
• Lähde, E., Laiho, O., Norokorpi, Y. (1999). Diversity-oriented silviculture in the Boreal zone of Europe. For. Ecol. Manage. 118:223–243.
• Lappi, J. (1986). Mixed linear models for analyzing and predicting stem form variation of scots pine. Communicationes Instituti Forestalis Fenniae 134. 69 p.
• Lhotka, J.M., Loewenstein, E.F. (2011). An individual-tree diameter growth model for managed uneven-aged oak-shortleaf pine stands in the Ozark Highlands of Missouri, USA. For. Ecol. Manage. 261: 770-778.
• Moser, J.W. (1972). Dynamics of an uneven-aged forest stand. For. Sci. 18: 184-191.
• Øyen, B-H., Nilsen, P., Bøhler, F., Andreassen, K. 2011. Predicting individual tree and stand diameter increment responses of Norway spruce (Picea abies (L.) Karst.) after mountain forest selective cutting. For. Studies. 55: 33–45.
• Peng, C. (2000). Growth and yield models for uneven-aged stands: past, present and future. For. Ecol. Manage. 132: 259-279.
• Pretzsch, H. (2009). Forest Dynamics, Growth and Yield: From Measurement to Model. Berlin, Springer-Verlag: 664.
• Pukkala, T., Lähde, E., Laiho, O. (2009). Growth and yield models for uneven-sized forest stands in Finland. For. Ecol. Manage. 258: 207–216.
• Pukkala, T., Kolstrom, T. (1988). Simulating the development of Norway spruce stands using transition matrix. For. Ecol. Manage. 25: 255-267.
• Schwinning S., Weiner J. (1998). Mechanisms determining the degree of size asymmetry in competition among plants. Oecologia 113: 447–455.
• Searle, S.R., Casella, G., McCulloch, C.E. (1992).Variance components. John Wiley, New York. 501 p.
• Sharma, R.P., Vacek, Z., Vacek, S., Jansa, V., Kučera, M. (2017). Modelling individual tree diameter growth for Norway spruce in the Czech Republic using a generalized algebraic difference approach. J. For. Sci., 63: 227-238.
• Shifley, S.R., Fan, Z., Kabrick, J.M., Jensen, R.G. (2006). Oak mortality risk factors and mortality estimation. For. Ecol. Manage. 229: 16–26.
• Subedi, N., Sharma, M. (2011). Individual-tree diameter growth models for black spruce and jack pine plantations in northern Ontario. For. Ecol. Manage. 261: 2140-2148.
• Trasobares, A., Pukkala, T., Miina J. (2004). Growth and yield model for uneven-aged mixtures of Pinus sylvestris L. and Pinus nigra Arn. in Catalonia, north-east Spain. Annals For. Sci. 6: 9–24.
• Uzoh F.C.C., Oliver W.W. (2008). Individual tree diameter increment model for managed even-aged stands of ponderosa pine throughout the western United States using a multilevel linear mixed effects model. For. Ecol. Manage. 256: 438-445.
• Vanclay, J.K. (1994). Modelling forest growth and yield: applications to mixed tropical forests. CAB International, United Kingdom.
• Yang, Y., Titus, S.J., Huang, S. (2003). Modeling individual tree mortality for white spruce in Alberta. Ecol. Model. 163: 209–222.
• Yao, X., Titus, S.J., MacDonald, S.E. (2001). A generalized logistic model of individual tree mortality for aspen, white spruce, and lodgepole pine in Alberta mixed wood forests. Can. J. For. Res. 31: 283–291.