Bontemps, J. D. & Bouriaud, O. Predictive approaches to forest site productivity: Recent trends, challenges and future perspectives. Forestry 87, 109–128 (2014).
Google Scholar
Skovsgaard, J. P. & Vanclay, J. K. Forest site productivity: a review of the evolution of dendrometric concepts for even-aged stands. Forestry 81, 13–31 (2008).
Google Scholar
Albert, M. & Schmidt, M. Climate-sensitive modelling of site-productivity relationships for Norway spruce (Picea abies (L.) Karst) and common beech (Fagus sylvatica L.). For. Ecol. Manag. 259, 739–749 (2010).
Google Scholar
Véga, C. & St-Onge, B. Mapping site index and age by linking a time series of canopy height models with growth curves. For. Ecol. Manag. 257, 951–959 (2009).
Google Scholar
Hägglund, B. & Lundmark, J. E. Site index estimation by means of site properties of Scots pine and Norway spruce in Sweden. Stud. For. Suec. 138, 5–38 (1977).
Johansson, T. Site index curves for common alder and grey alder growing on different types of forest soil in Sweden. Scand. J. For. Res. 14, 441–453 (1999).
Google Scholar
Raulier, F., Lambert, M.-C., Pothier, D. & Ung, C.-H. Impact of dominant tree dynamics on site index curves. For. Ecol. Manag. 184, 65–78 (2003).
Google Scholar
Corral Rivas, J. J., Álvarez González, J. G., Ruíz González, A. D. & von Gadow, K. Compatible height and site index models for five pine species in El Salto, Durango (Mexico). For. Ecol. Manag. 201, 145–160 (2004).
Google Scholar
Tewari, V. P., Rivas, J. J. C., VilČko, F. & Von Gadow, K. Height-Growth and site index equations for social forestry plantations of acacia nilotica and eucalyptus hybrid in gujarat state of India. For. Trees Livelihoods 17, 125–140 (2007).
Google Scholar
Monserud, R. A. & Rehfeldt, G. E. Genetic and environmental components of variation of site index in inland douglas-fir. For. Sci. 36, 1–9 (1990).
Alvarez-González, J. G., Ruiz-González, A. D., Rodríguez-Soalleiro, R. & Barrio-Anta, M. Ecorregional site index models for Pinus pinaster in Galicia (northwestern Spain). Ann. For. Sci. 62, 115–127 (2005).
Google Scholar
Bravo-Oviedo, A., Tomé, M., Bravo, F., Montero, G. & del Río, M. Dominant height growth equations including site attributes in the generalised algebraic difference approach. Can. J. For. Res. 38, 2348–2358 (2008).
Google Scholar
Johansson, T. Site index curves for Norway spruce plantations on farmland with different soil types. Stud. For. Suec. 198, 1–19 (1995).
Adams, J. P., Matney, T. G., Land, S. B. Jr., Belli, K. L. & Duzan, H. W. Jr. Incorporating genetic parameters into a loblolly pine growth-and-yield model. Can. J. For. Res. 36, 1959–1967 (2006).
Google Scholar
Buford, M. A. & Burkhart, H. E. Genetic improvement effects on growth and yield of loblolly pine plantations. For. Sci. 33, 707–724 (1987).
Monserud, R. A. Height growth and site index curves for inland Douglas-fir based on stem analysis data and forest habitat type. For. Sci. 30, 943–965 (1984).
García, O. Dynamical implications of the variability representation in site-index modelling. Eur. J. For. Res. 130, 671–675 (2010).
Google Scholar
Calama, R., Cañadas, N. & Montero, G. Inter-regional variability in site index models for even-aged stands of stone pine (Pinus pinea L.) in Spain. Ann. For. Sci. 60, 259–269 (2003).
Google Scholar
Adame, P., Hynynen, J., Cañellas, I. & del Río, M. Individual-tree diameter growth model for rebollo oak (Quercus pyrenaica Willd.) coppices. For. Ecol. Manag. 255, 1011–1022 (2008).
Google Scholar
Bravo-Oviedo, A., del Río, M. & Montero, G. Geographic variation and parameter assessment in generalised algebraic difference site index modelling. For. Ecol. Manag. 247, 107–119 (2007).
Google Scholar
Bontemps, J. & Bouriaud, O. Predictive approaches to forest site productivity: recent trends, challenges and future perspectives. Forestry 87, 1–20 (2013).
Claessens, H., Pauwels, D., Thibaut, A. & Rondeux, J. Site index curves and autecology of ash, sycamore and cherry in Wallonia (Southern Belgium). Forestry 72, 171–182 (1999).
Google Scholar
Karlsson, K. Height growth patterns of Scots pine and Norway spruce in the coastal areas of western Finland. For. Ecol. Manag. 135, 205–216 (2000).
Google Scholar
Martín-Benito, D., Gea-Izquierdo, G., del Río, M. & Cañellas, I. Long-term trends in dominant-height growth of black pine using dynamic models. For. Ecol. Manag. 256, 1230–1238 (2008).
Google Scholar
Dyrekcja Generalna Lasów Państwowych, Raport o stanie lasów w Polsce (2018).
Socha, J. Long-term effect of wetland drainage on the productivity of Scots pine stands in Poland. For. Ecol. Manag. 274, 172–180 (2012).
Google Scholar
Bravo, F. & Montero, G. Site index estimation in Scots pine (Pinus sylvestris L.) stands in the High Ebro Basin (northern Spain) using soil attributes. Forestry 74, 395–406 (2001).
Google Scholar
Gadow, K.; Hui, G. Modelling Forest Development, Vol. 57, Forestry Sciences (Springer Netherlands, Dordrecht, 1999). ISBN 978–1–4020–0276–2.
Schwappach, A. Ertragstafeln der Wichtigeren Holzarten (Druckerei Merkur, Prag, 1943).
Szymkiewicz, B. Niektóre zagadnienia dotyczące tablic zasobności drzewostanów sosnowych. Pr. IBL Seria A 67 (1948)
Szymkiewicz, B. Tablice Zasobności i Przyrostu Drzewostanów (Państwowe Wydawnictwo Rolnicze i Leśne, Warszawa, 2001). ISBN 83–09–01745–6.
Pretzsch, H., Biber, P., Schütze, G., Uhl, E. & Rötzer, T. Forest stand growth dynamics in Central Europe have accelerated since 1870. Nat. Commun. 5, 4967 (2014).
Google Scholar
Socha, J. & Orzeł, S. Dynamic site index curves for Scots pine (Pinus sylvestris L.) in southern Poland. Sylwan 157, 26–38 (2013).
Socha, J., Tymińska-Czabańska, L., Grabska, E. & Orzeł, S. Site index models for main forest-forming tree species in Poland. Forests 11, 8–10 (2020).
Esri Inc. ArcGIS Pro (Version 2.2.0). Esri Inc. https://www.esri.com/en-us/arcgis/products/arcgis-pro/overview (2020).
Caudullo, G., Welk, E. & San-Miguel-Ayanz, J. Chorological maps for the main European woody species. Data Br. 12, 662–666 (2017).
Google Scholar
Zielony, R., Kliczkowska, A. Regionalizacja Przyrodniczo-Leśna Polski 2010 (2012). ISBN 9788361633624.
Carmean, W. H. Site index curves for upland oaks in the central states. For. Sci. 18, 109–120 (1972).
Mehtätalo, L. & Lappi, J. Biometry for Forestry and Environmental Data: with Examples in R 1st edn. (Chapman and Hall/CRC, Boca Raton, 2020).
Google Scholar
Nigh, G. Engelmann spruce site index models: a comparison of model functions and parameterisations. PLoS ONE 10, e0124079 (2015).
Google Scholar
Pinheiro J., Bates D., & DebRoy S. S. D. nlme: Linear and Nonlinear Mixed Effects Models (2020).
Wang, M., Borders, B. E. & Zhao, D. An empirical comparison of two subject-specific approaches to dominant heights modeling: the dummy variable method and the mixed model method. For. Ecol. Manag. 255, 2659–2669 (2008).
Google Scholar
Bronisz, K. & Mehtätalo, L. Mixed-effects generalised height–diameter model for young silver birch stands on post-agricultural lands. For. Ecol. Manage. 460, 117901 (2020).
Google Scholar
Wang, M., Bhatti, J., Wang, Y. & Varem-Sanders, T. Examining the gain in model prediction accuracy using serial autocorrelation for dominant height prediction. For. Sci. 57, 241–251 (2011).
R Core Team. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. URL http://www.R-project.org/ (2020).
Bailey, R. L. & Clutter, J. L. Base-age invariant polymorphic site curves. For. Sci. 20, 155–159 (1974).
Cieszewski, J. & Bailey, L. Generalized algebraic difference approach: theory based derivation of dynamic site equations with polymorphism and variable asymptotes. For. Sci. 46, 116–126 (2000).
Cieszewski, C. J. Three methods of deriving advanced dynamic site equations demonstrated on inland Douglas-fir site curves. Can. J. For. Res. For. 31, 165–173 (2001).
Google Scholar
Krumland, B. & Eng, H. Site index systems for major young-growth forest and Woodland species in North California. Calif. For. 4, 1–220 (2005).
Cieszewski, C. J. Developing a well-behaved dynamic site equation using a modified hossfeld IV function Y 3 = (axm)/(c + x m–1), a simplified mixed-model and scant subalpine fir data. For. Sci. 49, 539–554 (2003).
Sharma, R. P., Brunner, A., Eid, T. & Øyen, B.-H. Modelling dominant height growth from national forest inventory individual tree data with short time series and large age errors. For. Ecol. Manag. 262, 2162–2175 (2011).
Google Scholar
Anta, M. B. et al. Development of a basal area growth system for maritime pine in northwestern Spain using the generalised algebraic difference approach. Can. J. For. Res. 36, 1461–1474 (2006).
Google Scholar
Cieszewski, C. J., Harrison, M. & Martin, S. W. Examples of practical methods for unbiased parameter estimation in self-referencing functions. In Proceedings of the First International Conference on Measurements and Quantitative Methods and Management and The 1999 Southern Mensur (ed. Cieszewski, C. J.) (2000).
Nunes, L., Patrício, M., Tomé, J. & Tomé, M. Modeling dominant height growth of maritime pine in Portugal using GADA methodology with parameters depending on soil and climate variables. Ann. For. Sci. 68, 311–323 (2011).
Google Scholar
Cieszewski, C. J. Comparing properties of self-referencing models based on nonlinear-fixed-effects versus nonlinear-mixed-effects modeling approaches. Math. Comput. For. Nat. Sci. 10, 46–57 (2018).
Seynave, I. et al. Picea abies site index prediction by environmental factors and understorey vegetation: a two-scale approach based on survey databases. Can. J. For. Res. 35, 10 (2005).
Google Scholar
Brandl, S. et al. Static site indices from different national forest inventories: harmonisation and prediction from site conditions. Ann. For. Sci. 75, 1–17 (2018).
Google Scholar
Breda, N., Huc, R. & André Granier, E. D. Temperate forest trees and stands under severe drought: a review of ecophysiological responses, adaptation processes and long-term consequences. Ann. For. Sci. 63, 625–644 (2006).
Google Scholar
Loik, M. E., Breshears, D. D., Lauenroth, W. K. & Belnap, J. A multi-scale perspective of water pulses in dryland ecosystems: climatology and ecohydrology of the western USA. Oecologia 141, 269–281 (2004).
Google Scholar
Kundzewicz, Z. W., Hov, Ø., Okruszko, T. Zmiany klimatu i ich wpływ na wybrane sektory w Polsce. 257 (2017).
Barrio Anta, M. & Dieguez-Aranda, U. Site quality of pedunculate oak (Quercus robur L.) stands in Galicia (northwest Spain). Eur. J. For. Res. 124, 19–28 (2005).
Google Scholar
Bowman, D. M. J. S., Brienen, R. J. W., Gloor, E., Phillips, O. L. & Prior, L. D. Detecting trends in tree growth: not so simple. Trends Plant Sci. 18, 11–17 (2013).
Google Scholar
Isaev, A., Korovin, G., Zamolodkchikov, D., Utkin, A. & Pryaznikov, A. Carbon stock and depostion in phytomass of the Russian forests 247–256 (Kluwer, Amsterdam, 1995).
Fang, J. Y. & Wang, Z. M. Forest biomass estimation at regional and global levels, with special reference to China’s forest biomass. Ecol. Res. 16, 587–592 (2001).
Google Scholar
Schroeder, P., Brown, S., Mo, J., Birdsey, R. & Cieszewski, C. Biomass estimation for temperate broadleaf forests of the United States using inventory data. For. Sci. 43, 424–434 (1997).
Bravo-Oviedo, A., Gallardo-Andrés, C., del Río, M. & Montero, G. Regional changes of Pinus pinaster site index in Spain using a climate-based dominant height model. Can. J. For. Res. 40, 2036–2048 (2010).
Google Scholar
Woodbury, P. B., Smith, J. E., Weinstein, D. & Laurence, J. Assessing potential climate change effects on loblolly pine growth: a probabilistic regional modeling approach. For. Ecol. Manag. 107, 99–116 (1998).
Google Scholar
Latta, G., Temesgen, H. & Barrett, T. M. B. M. Mapping and imputing potential productivity of Pacific Northwest forests using climate variables. Can. J. For. Res. 39, 1197–1207 (2009).
Coops, N. C., Hember, R. & Waring, R. H. Assessing the impact of current and projected climates on Douglas-Fir productivity in British Columbia, Canada, using a process-based model (3-PG). Can. J. For. Res. 40, 511–524 (2010).
Google Scholar
Coops, N. C., Coggins, S. B. & Kurz, W. a Mapping the environmental limitations to growth of coastal Douglas-fir stands on Vancouver Island, British Columbia. Tree Physiol. 27, 805–815 (2007).
Google Scholar
Source: Ecology - nature.com
