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Aim: Altitudinal and latitudinal treeline ecotones have not consistently responded to climate warming in the direction and/or magnitude predicted by climate alone, suggesting that non‐climatic mechanisms (e.g. biotic interactions) also mediate treeline range dynamics. Through a collaborative research approach, we assessed environmental conditions associated with pre‐dispersal insect cone granivory and how this biotic interaction may govern the reproductive potential, and therefore range dynamics, of spruce‐dominated treelines across northern Canada. Location: In all, 10 boreal forest treelines, tundra and alpine, from Yukon to Newfoundland and Labrador, Canada. Taxa: White spruce (Picea glauca [Moench] Voss), Black spruce (Picea mariana [Mill.] B.S.P.), Strobilomyia spp., Megastigmus spp. Methods: Treeline sites were assessed for presence and magnitude of pre‐dispersal seed granivory by insects along with viable seed availability. We quantified stand density metrics, organic layer depth and understorey vegetation composition at each location and, subsequently, incorporated those variables into generalized linear mixed models to establish predictors of granivory magnitude and viability of available seed. Results: Insect granivory was widespread across sites; however, site‐specific patterns of granivory were associated with increased moss cover and decreased shrub cover and stand density. While all black spruce‐dominated sites exhibited seed viability rates > 50%, the number of seeds produced per cone varied, suggesting that within‐site abiotic conditions and biotic interaction pressures limit successful colonization of novel environments in advance of seed dispersal. Main Conclusions: The modelled relationships between granivory, seed viability and environmental conditions represent an essential step towards generalizing how and when biotic interactions across subarctic treelines influence boreal tree range dynamics before seed dispersal. Connections between granivory magnitude and site‐level treeline characteristics (e.g. stand density, understorey vegetation) will provide a more comprehensive understanding of treeline range dynamics under continued climate change. [ABSTRACT FROM AUTHOR]

Merging robust statistical methods with complex simulation models is a frontier for improving ecological inference and forecasting. However, bringing these tools together is not always straightforward. Matching data with model output, determining starting conditions, and addressing high dimensionality are some of the complexities that arise when attempting to incorporate ecological field data with mechanistic models directly using sophisticated statistical methods. To illustrate these complexities and pragmatic paths forward, we present an analysis using tree‐ring basal area reconstructions in Denali National Park (DNPP) to constrain successional trajectories of two spruce species (Picea mariana and Picea glauca) simulated by a forest gap model, University of Virginia Forest Model Enhanced—UVAFME. Through this process, we provide preliminary ecological inference about the long‐term competitive dynamics between slow‐growing P. mariana and relatively faster‐growing P. glauca. Incorporating tree‐ring data into UVAFME allowed us to estimate a bias correction for stand age with improved parameter estimates. We found that higher parameter values for P. mariana minimum growth under stress and P. glauca maximum growth rate were key to improving simulations of coexistence, agreeing with recent research that faster‐growing P. glauca may outcompete P. mariana under climate change scenarios. The implementation challenges we highlight are a crucial part of the conversation for how to bring models together with data to improve ecological inference and forecasting. [ABSTRACT FROM AUTHOR]