Navigating through complexity: a roadmap to disentangle multi‐level drivers of intraspecific seed‐trait variability and prioritise research efforts

Seed traits underpin plant regeneration and are central to predicting species' responses to environmental change, yet their intraspecific variability remains poorly integrated into trait-based frameworks. Progress has been limited by the conflation of processes operating across nested levels, from regions and populations to mother plants and individual seeds, and by weak integration of genetic drivers with environmental and phenotypic data. Drawing on published literature and analyses of seed traits in wild tree populations, we show that substantial seed-trait variation can occur among mother plants and individual seeds within populations, meaning that population-level macroenvironmental variables often capture only part of the observed variation. To address these limitations, we propose a roadmap to disentangle hierarchical drivers of intraspecific trait variability (ITV) in seeds. We outline a strategic plan to quantify seed-trait variation across hierarchical levels, investigate its drivers where variation is concentrated, and assess its consequences for recruitment and demographic outcomes. We recommend coordinated, standardised sampling and experiments that retain mother-plant and individual-seed identity, integrate genetic, environmental and phenotypic data, and use scalable approaches to link seed traits to performance across recruitment stages. Recognising and integrating ITV across nested levels is essential for improving predictions of plant regeneration under environmental change.