Interpreting biological variation: seeds, populations and sensitivity thresholds

Abstract

Abstract Seeds offer a unique perspective from which to view biology. An individual seed is an autonomous biological entity that must rely on its own resources (and resourcefulness) to persist after dispersal and to time its transition to germination and seedling growth to coincide with environmental opportunities for survival. At the same time, seed biology in agriculture and ecology is determined largely by the behaviours of populations of individual seeds. The percentage of seeds in a population that is in a particular state (e.g. dormant, germinated, dead) at a given time is a fundamental metric of seed biology. This duality of individual diversity underlying consistent population-wide behaviour patterns can be described quantitatively using population-based threshold (PBT) models. While conceptually simple, these models are highly flexible and can describe the wide diversity of responses of seed populations to temperature, water potential, hormones, oxygen, light, ageing and combinations of these factors. This seed behaviour is linked to respiratory rates of individual seeds, indicating that basic metabolic processes within seeds vary among individuals in accordance with PBT principles. Looking more broadly across microbial, plant and animal biology, examples of cellular diversity in hormonal sensitivity, gene expression, developmental responses and signalling abound. This variation often is termed ‘noise’, and analysis efforts are focused on extracting mean signals from this variation to understand regulatory pathways. However, extension of the PBT approach to the cellular and molecular levels suggests that population sensitivity distributions and recruitment phenomena may underlie many fundamental biological processes. Thus, concepts and quantitative approaches developed for the analysis of seed populations can be applied across biological scales from molecules to ecosystems to interpret inherent biological variation and provide mechanistic insights into the nature of biological regulatory systems.