Aim: Current interest in forecasting changes to species ranges has resulted in a multitude of approaches to species distribution models (SDMs). However, most approaches include only a small subset of the available information, and many ignore smaller‐scale processes such as growth, fecundity and dispersal. Furthermore, different approaches often produce divergent predictions with no simple method to reconcile them. Here, we present a flexible framework for integrating models at multiple scales using hierarchical Bayesian methods.Location: Eastern North America (as an example).Methods: Our framework builds a metamodel that is constrained by the results of multiple sub‐models and provides probabilistic estimates of species presence. We applied our approach to a simulated dataset to demonstrate the integration of a correlative SDM with a theoretical model. In a second example, we built an integrated model combining the results of a physiological model with presence–absence data for sugar maple (Acer saccharum), an abundant tree native to eastern North America.Results: For both examples, the integrated models successfully included information from all data sources and substantially improved the characterization of uncertainty. For the second example, the integrated model outperformed the source models with respect to uncertainty when modelling the present range of the species. When projecting into the future, the model provided a consensus view of two models that differed substantially in their predictions. Uncertainty was reduced where the models agreed and was greater where they diverged, providing a more realistic view of the state of knowledge than either source model.Main conclusions: We conclude by discussing the potential applications of our method and its accessibility to applied ecologists. In ideal cases, our framework can be easily implemented using off‐the‐shelf software. The framework has wide potential for use in species distribution modelling and can drive better integration of multi‐source and multi‐scale data into ecological decision‐making.

Background and Aims Trees invest in both primary (e.g. height) and secondary (e.g. diameter) growth. The trade-off between these investments varies between species and changes with the tree growing environment. To better establish this trade-off, readily available allometric exponents relating height to diameter at breast height (γ_h,dbh) and stem volume to diameter at breast height (α_v,dbh) were simultaneously studied.

The relationships between climate and wood density components, i.e., minimum ring density, maximum ring density and mean ring density have been studied mainly in dominant trees. However, the applicability of the findings to trees of other dominance classes is unclear. The aim of this study was to address whether climate differentially influences wood density components among dominance classes. X-ray densitometry data was obtained from 72 black spruce (Picea mariana (Mill.) B.S.P.) trees harvested in Northwestern Ontario, Canada. Dominant, co-dominant and intermediate trees were sampled and the data analysed using mixed-effect modelling techniques. For each density component, models were first fitted to the pooled data using ring width and cambial age as predictors, before monthly climatic variables were integrated into the models. Then, separate models were fitted to the data from each dominance class. In general, the addition of climatic factors led to a small but significant improvement in model performance. The predicted historical trends were well synchronized with the observed data. Our results indicate that trees from all dominance classes in a stand should be sampled in order to fully characterize wood density-climate relationships.

Relationships between wood density and climatic variables have generally been developed from unmanaged stands near the treeline. Using black spruce (Picea mariana (Mill.) B.S.P.) samples from the managed boreal zone in Canada, we investigated whether the relationship between mean ring density (MRD) and climatic variables is altered by silvicultural practices. We analysed the MRD of 10 384 growth rings from 72 trees sampled among 18 stands (nine thinned, nine controls) across Quebec, Canada. We constructed a mixed-effects model relating MRD to cambial age and ring width (RW). Model residuals (ε_M1), i.e. the difference between observed and predicted MRD, were then related to monthly temperature and precipitation of the year of ring formation and the year before. After thinning, RW slightly increased while MRD remained constant, thus lowering the strength of the relationship between MRD and RW. ε_M1 were positively related to spring temperatures and negatively related to summer temperatures and precipitation. No effect of thinning on the relationship between ε_M1 and climatic variables was observed. The sample trees grew in less limiting conditions than at the treeline so the reduced strength of the relationship between MRD and growth rate in thinned stands may result from a higher photosynthetic capacity. Such results may have implications in forest management as thinning could increase the value of black spruce wood.

Forest managers have to take into account multiple objectives such as stand yield, wood quality attributes, ecological constraints and social considerations when making their decisions. The objective of the present study is to build (i) a dynamicmodulus of elasticity (MOE_dyn) model and (ii) a core wood density (WD_core) model for white spruce plantations in theBas-Saint-Laurent Region (Québec, Canada) to quantify their inter- and intra-stand variations in order for managers tobetter weigh their different options. Using data obtained from 54 sample plots in 31 white spruce plantations from Eastern Québec, the MOE_dynof 143 trees and the WD_coreof 162 trees were analysed. Dendrometric and stand variables wereused to build a MOE_dynlinear mixed-effect model and a WD multiple linear regression model. The MOE_dynmodel explained 66.8% of the total variation, 1.1% of which originated from inter-stand variations. MOE_dynwas proportionalto diameter at breast height (DBH) and non-linearly decreased with tree growth rate. The WD_coremodel explained 16.0%of the total variation. The intra-stand variations were represented by a negative relationship between WD_coreand growthrate. Inter-stand variations were accounted for by site index and altitude. The performance of the MOE_dynmodel was satisfactory and in accordance with the literature. However, the WD_coremodel was below standard, mainly as a consequenceof unaccounted intra-individual variations. Nonetheless, raw simulations using these models suggest that white sprucewood from plantations may benefit from intensive forest management.