Dominant height growth equations including site attributes in the generalized algebraic difference approach Andre ´ s Bravo-Oviedo, Margarida Tome ´ , Felipe Bravo, Gregorio Montero, and Miren del Rı ´o Abstract: We present a new dynamic dominant height growth model based on Cieszewski’s generalized algebraic difference approach (GADA) advanced dynamic site equation strengthened by the use of explicit climate and soil variables (i.e., H = f(H0,T0, T, site conditions)). The results suggest that the inclusion of climatic variables would improve the applicability of the inter-regional model in regions in which climate and soil type lead to intra-regional variability. The new model reduces the bias present in a previous dynamic model that did not include climatic at- tributes and improves the model efficiency across the different age classes. Climate has a multiplicative effect on dominant tree growth in the early development stages (<20 years) and an additive effect in older stands. Re ´sume ´: Nous pre ´sentons ici un nouveau mode `le dynamique de croissance en hauteur dominante fonde ´ sur l’e ´quation de la me ´thode de la diffe ´rence alge ´brique ge ´ne ´ralise ´e (GADA) de l’indice de qualite ´ de station de Cieszewski renforce ´e par l’utilisation des variables explicites du climat et du sol, c.-a `-d. H = f(H 0 , T 0 , T,e ´tat du site). Les re ´sultats indiquent que l’inclusion des variables climatiques permettrait d’ame ´liorer l’applicabilite ´ du mode `le interre ´gional dans les re ´gions ou ` le climat et le type de sol sont a ` l’origine de la variabilite ´ intrare ´gionale. Le nouveau mode `le permet de re ´duire le biais pre ´sent dans un mode `le dynamique pre ´ce ´dent qui n’incluait pas les caracte ´ristiques climatiques et ame ´liore l’efficacite ´ de ce mode `le pour l’ensemble des classes d’a ˆge. Le climat exerce un effet multiplicateur sur la croissance des arbres domi- nants durant les premiers stades de de ´veloppement (<20 ans) et un effet additif dans les vieux peuplements. [Traduit par la Re ´daction] Introduction Mediterranean maritime pine (MMP; Pinus pinaster Ait.) is widely distributed in the Mediterranean basin, occupying approximately 4  10 6 ha (Ribeiro et al. 2001). The species grows in a wide range of climatic conditions; from pure Mediterranean climate conditions such as those found in eastern Spain, Italy, and southern France to the continental climate of inland Spain or the Atlantic climate of western France, Portugal, and northwestern Spain. Soil origin varies, from igneous and metamorphic rocks such as granite or gneiss in Portugal and western Spain to eocene sands in cen- tral Spain, bunt sandstone in eastern Spain, or dolomite in southeastern Spain and eastern Italy. Climatic and edaphic variability combined with the isolated nature of the stands leads to genetic variation (Salvador et al. 2000; Gonza ´lez- Martı ´nez et al. 2001), which is reflected in tree attributes such as straightness (Rı ´o et al. 2004), drought tolerance, or growth (Alı ´a et al. 1997). In recent years, various models have attempted to explain the regional variability in growth (Calama et al. 2003; Wang et al. 2004; A ´ lvarez-Gonza ´lez et al. 2005; Adame et al. 2006). However, intra-regional variability can be significant in limited areas, such as those with Mediterranean condi- tions, in which different growth patterns and growth values for certain attributes are found within the same natural re- gion. In addition, forest researchers are facing new chal- lenges beyond the scope of regional studies, as climate change and its effect on species distribution as well as on tree and stand growth becomes more evident. The Mediterranean area is considered to be more sensitive to climate change than other areas (IPCC 1996). The mech- anisms by which plants adapt to their changing environment are not expected to develop as quickly as would be required to keep pace with the changing climate, so adaptive forest management strategies are needed to obtain goods and serv- ices from the forest in a sustainable manner. Including local growth trends could help to develop these strategies. Mixed effects modeling is a commonly used approach for Received 15 October 2007. Accepted 6 June 2008. Published on the NRC Research Press Web site at cjfr.nrc.ca on 30 July 2008. A. Bravo-Oviedo, 1 G. Montero, and M. del Rı ´o. Departamento Sistemas y Recursos Forestales — Deparment of Forest Systems and Resources, Centro de Investigacio ´n Forestal, Instituto Nacional de Investigacio ´n y Tecnologı ´a Agraria y Alimentaria and Institute on Sustainable Forest Management. Ctra. A. Corun ˜a, km 7,5 28040, Madrid, Spain. M. Tome ´. Technical University of Lisbon, Instituto Superior de Agronomia. Centro de estudos Florestais, Tapada de Ajuda, 1349-017, Lisboa, Portugal. F. Bravo. Sustainable Forest Management Group, University of Valladolid and Institute on Sustainable Forest Management, Avda, Madrid, 44, 34004 Palencia, Spain. 1 Corresponding author (e-mail: bravo@inia.es). 2348 Can. J. For. Res. 38: 2348–2358 (2008) doi:10.1139/X08-077 # 2008 NRC Canada