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Age shapes fundamental processes related to behaviour, survival and reproduction, where age influences reproductive success, non‐random mating with respect to age can magnify or mitigate such effects. Consequently, the correlation in partners' age across a population may influence its productivity. Despite widespread evidence for age‐assortative mating, little is known about what drives this assortment and its variation. Specifically, the relative importance of active (same‐age mate preference) and passive processes (assortment as a consequence of other spatial or temporal effects) in driving age assortment is not well understood.In this paper, we compare breeding data from a great tit and mute swan population (51‐ and 31‐year datasets, respectively) to tease apart the contributions of pair retention, cohort age structure and active age‐related mate selection to age assortment in species with contrasting life histories.Both species show age‐assortative mating and variable assortment between years. However, we demonstrate that the drivers of age assortment differ between the species, as expected from their life histories and resultant demographic differences. In great tits, pair fidelity has a weak effect on age‐assortative mating through pair retention; variation in age assortment is primarily driven by fluctuations in age structure from variable juvenile recruitment. Age‐assortative mating is, therefore, largely passive, with no evidence consistent with active age‐related mate selection. In mute swans, age assortment is partly explained by pair retention, but not population age structure, and evidence exists for active age‐assortative pairing.This difference is likely to result from shorter life‐spans in great tits compared with mute swans, leading to fundamental differences in their population age structure, whereby a larger proportion of great tit populations consist of a single age cohort. In mute swans, age‐assortative pairing through mate selection may also be driven by greater age‐dependent variation in fitness.The study highlights the importance of considering how different life histories and demographic differences arising from these affect population processes that appear congruent across species. We suggest that future research should focus on uncovering the proximate mechanisms that lead to variation in active age‐assortative mate selection (as seen in mute swans); and the consequences of variation in age structure on the ecological and social functioning of wild populations. [ABSTRACT FROM AUTHOR]

The integration and synthesis of the data in different areas of science is drastically slowed and hindered by a lack of standards and networking programmes. Long‐term studies of individually marked animals are not an exception. These studies are especially important as instrumental for understanding evolutionary and ecological processes in the wild. Furthermore, their number and global distribution provides a unique opportunity to assess the generality of patterns and to address broad‐scale global issues (e.g. climate change).To solve data integration issues and enable a new scale of ecological and evolutionary research based on long‐term studies of birds, we have created the SPI‐Birds Network and Database (www.spibirds.org)—a large‐scale initiative that connects data from, and researchers working on, studies of wild populations of individually recognizable (usually ringed) birds. Within year and a half since the establishment, SPI‐Birds has recruited over 120 members, and currently hosts data on almost 1.5 million individual birds collected in 80 populations over 2,000 cumulative years, and counting.SPI‐Birds acts as a data hub and a catalogue of studied populations. It prevents data loss, secures easy data finding, use and integration and thus facilitates collaboration and synthesis. We provide community‐derived data and meta‐data standards and improve data integrity guided by the principles of Findable, Accessible, Interoperable and Reusable (FAIR), and aligned with the existing metadata languages (e.g. ecological meta‐data language).The encouraging community involvement stems from SPI‐Bird's decentralized approach: research groups retain full control over data use and their way of data management, while SPI‐Birds creates tailored pipelines to convert each unique data format into a standard format. We outline the lessons learned, so that other communities (e.g. those working on other taxa) can adapt our successful model. Creating community‐specific hubs (such as ours, COMADRE for animal demography, etc.) will aid much‐needed large‐scale ecological data integration. [ABSTRACT FROM AUTHOR]