1. Ecological data are increasingly collected by networks of collaborators using replicated designs and methods, which can significantly improve the quality and quantity of data collected throughout the ecological niche and geographic range of a species. The coordinated generation and management of data is critical to producing coherent datasets (Standard Data Products) across multiple sites that can be used by different researchers, over extended time periods and for multiple purposes. 2. Here, we describe and use a Quality Assurance framework for the design, collection and production of reproducible Standard Data Products for population ecology. We identified six critical project elements of a Quality Assurance framework (QA1-6) to produce ecological Standard Data Products with high immediate and future value. 3. We applied the Quality Assurance framework to the Plantpopnet project as a case-study. Plantpopnet is a coordinated distributed system for demography and population macroecology which uses the model species Plantago lanceolata. We mapped Plantpopnet activities to the Quality Assurance Framework as: QA1) Measurable objectives: research project objectives with data requirements, QA2) Process control: governance policies, QA3) Project specific procedures: model organism selection and data collection protocol, QA4) Supporting production of high quality data: recruitment, retention and engagement of participants, QA5) Data management: data management plan and reproducible data cleaning workflow, QA6) Production and management of outputs: Standard Data Products and papers. The framework allows for flexibility and adaptation to changing circumstances. 4. Explicit use of Quality Assurance, project and data management tools together with standardised ecological methods enabled the design, collection, maintenance and sustainability of high-quality data products. We provide a Quality Assurance framework together with governance documents, code and data for a reproducible Standard Data Product. This framework can be applied to the goals of the Plantpopnet project as well as facilitate future research and applications of coordinated distributed ecology projects more generally.

Spatial isolation is a key driver of population-level variability in traits and genotypes worldwide. Geographical distance between populations typically increases isolation, but organisms face additional environmental barriers when dispersing between suitable habitat patches. Despite the predicted universal nature of the causes of isolation, global comparisons of isolation effects across taxa and geographic systems are few. We assessed the strength of isolation due to geographic and macroclimatic distance for paired marine island and paired mainland populations within the same species. Our meta-analysis included published measurements of phenotypic traits and neutral genetic diversity from 1832 populations of 112 plant and animal species at a global scale. As expected, phenotypic differentiation was higher between marine islands than between populations on the mainland, but spatial patterns of neutral genetic diversity did not vary between the two systems. Geographic distance had comparatively weak effects on the spatial patterns of phenotypes and neutral genetic diversity, but only phenotypic trait variability showed signal of system-dependence. These results suggest that spatial patterns of phenotypic variation are determined by system-dependent eco-evolutionary pressures, while the spatial variability of neutral genetic diversity might be universal. Our approach demonstrates that global biodiversity models that include island biology studies may progress our understanding of the interacting effects of spatial habitat structure, geographic- and environmental distances on biological processes underlying spatial population variability. We formulate future research directions for empirical tests and global syntheses in the field.

Phenotypic plasticity can mask population genetic differentiation, reducing the predictability of trait-environment relationships. In short-lived plants, reproductive traits may be more genetically determined due to their direct impact on fitness, whereas vegetative traits may show higher plasticity to buffer short-term perturbations. Combining a multi-treatment greenhouse experiment with global field observations for the short-lived Plantago lanceolata, we 1) disentangled the genetic and plastic responses of functional traits to a set of environmental drivers and 2) assessed the utility of trait-environment relationshisps inferred from observational data for predicting genetic differentiation. Reproductive traits showed distinct genetic differentiation that was highly predictable from observational data, but only when correcting traits for differences in their (labile) biomass component. Vegetative traits showed higher plasticity and contrasting genetic and plastic responses, leading to unpredictable trait patterns. Our study suggests that genetic differentiation may be inferred from observational data only for the traits most closely related with fitness.