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Animal- borne telemetry devices provide essential insights into the life- history strate -gies of far- ranging species and allow us to understand how they interact with their environment. Many species in the seabird family Alcidae undergo a synchronous molt of all primary flight feathers during the non- breeding season, making them flightless and more susceptible to environmental stressors, including severe storms and prey shortages. However, the timing and location of molt remain largely unknown, with most information coming from studies on birds killed by storms or shot by hunters for food. Using light- level geolocators with saltwater immersion loggers, we develop a method for determining flightless periods in the context of the annual cycle. Four Atlantic puffins (Fratercula arctica) were equipped with geolocator/immersion loggers on each leg to attempt to overcome issues of leg tucking in plumage while sitting on the water, which confounds the interpretation of logger data. Light- level and saltwa -ter immersion time- series data were combined to correct for this issue. This approach was adapted and applied to 40 puffins equipped with the standard practice deploy -ments of geolocators on one leg only. Flightless periods consistent with molt were identified in the dual- equipped birds, whereas molt identification in single- equippedbirds was less effective and definitive and should be treated with caution. Within the dual- equipped sample, we present evidence for two flightless molt periods per non- breeding season in two puffins that undertook more extensive migrations (>2000 km) and were flightless for up to 77 days in a single non- breeding season. A biannual flight feather molt is highly unusual among non- passerine birds and may be unique to birds that undergo catastrophic molt, i.e., become flightless when molting. Although our conclusions are based on a small sample, we have established a freely available meth -odological framework for future investigation of the molt patterns of this and other seabird species.auks, flightless molt, Fratercula, Geolocator tracking, life-history strategies, puffin, seabird ecology, wet–dry sensor

Funder: Research England, Funder: UK Joint Nature Conservation Committee (DEFRA), Predicting how populations may respond to climate change and anthropogenic pressures requires detailed knowledge of demographic traits, such as survival and reproduction. However, the availability of these data varies greatly across space and taxa. Therefore, it is common practice to conduct population assessments by filling in missing values from surrogate species or other populations of the same species. Using these independent surrogate values concurrently with observed data neglects the life‐history trade‐offs that connect the different aspects of a population's demography. Consequently, this approach introduces biases that could ultimately lead to erroneous management decisions. We use a Bayesian hierarchical framework to combine fragmented multi‐population data with established life‐history theory and reconstruct population‐specific demographic data across a substantial part of a species breeding range. We apply our analysis to a long‐lived colonial species, the black‐legged kittiwake Rissa tridactyla, that is classified as globally Vulnerable and is highly threatened by increasing anthropogenic pressures, including offshore renewable energy development. We then use a projection analysis to examine how the reconstructed demographic parameters may improve population assessments, compared to models that combine observed data with independent surrogate values. Demographic parameters reconstructed using a hierarchical framework can be utilised in a range of population modelling approaches. They can also be used as reference estimates to assess whether independent surrogate values are likely to over or underestimate missing demographic parameters. We show that surrogate values from independent sources are often used to fill in missing parameters that have large potential demographic impact, and that resulting biases are driven in unpredictable directions thus precluding assessments from being consistently precautionary. Synthesis and applications. Our study dramatically increases the spatial coverage of population‐specific demographic data for black‐legged kittiwakes. The reconstructed demographic parameters presented can also be used immediately to reduce uncertainty in the consenting process for offshore wind development in the United Kingdom and Ireland. More broadly, we show that the reconstruction approach used here provides a new avenue for improving evidence‐based management and policy action for animal and plant populations with fragmented and error prone demographic data.