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Modelling the distribution of migratory species has rarely been extended beyond breeding and wintering ranges despite many species showing much more complex movement patterns with multiple stopovers. We aimed to create a temporally explicit species distribution model describing the full annual distribution cycle, and use it to model the complex seasonal shifts in distribution of the common cuckoo Cuculus canorus, a declining long-distance migrant. To do this we used full-year satellite telemetry occurrence data, with their associated temporal information, to inform a temporally explicit species distribution model using MaxEnt. The resulting full-year distribution model was highly predictive (AUC ? 0.894) and appeared to have generality at the species-level despite being informed by data from a single breeding population. Comparison of our methodology with seasonal distribution models describing the breeding, winter and migration ranges separately showed that our full-year method provided more general and extensive predictions and performed better when tested with an independent dataset. When species distribution models based on a single season exclude environmental conditions experienced by birds in other parts of the annual cycle they risk underestimating niche breadth and neglecting the importance of stopover habitat. Conversely, models which simply average conditions across a season may miss the significance of finer scale within-season movements and overestimate niche breadth. In contrast, our framework for a full-year migrant distribution model successfully captures the finer-scale changes expected in seasonal environments and can be used to inform conservation management at every stage of migration. The full-year model framework appears to produce temporal distribution models generalised to the species-level from occurrence data limited to few individuals of a single population and may have particular utility when aiming to describe the distribution of species with complex migration patterns from telemetry data. | |
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