Predicting Seabird Foraging Habitat for Conservation Planning in Atlantic Canada: Integrating Telemetry and Survey Data Across Thousands of Colonies

Abstract

Conservation of mobile organisms is difficult in the absence of detailed information about movement and habitat use. While the miniaturization of tracking devices has eased the collection of such information, it remains logistically and financially difficult to track a wide range of species across a large geographic scale. Predictive distribution models can be used to fill this gap by integrating both telemetry and census data to construct distribution maps and inform conservation goals and planning. We used tracking data from 520 individuals of 14 seabird species in Atlantic Canada to first compare foraging range and distance to shorelines among species across colonies, and then developed tree-based machine-learning models to predict foraging distributions for more than 5000 breeding sites distributed along more than 5000 km of shoreline. Despite large variability in foraging ranges among species, tracking data revealed clusters of species using similar foraging habitats (e.g., nearshore vs. offshore foragers), and within species, foraging range was highly colony-specific. Even with this variability, distance from the nesting colony was an important predictor of distribution for nearly all species, while distance from coastlines and bathymetry (slope and ruggedness) were additional important predictors for some species. Overall, we demonstrated the utility of tree-based machine-learning approach when modeling tracking data to predict distributions at un-sampled colonies. Although tracking and colony data have some shortcomings (e.g., fewer data for some species), where results need to be interpreted with care in some cases, applying methods for modeling breeding season distributions of seabirds allows for broader-scale conservation assessment. The modeled distributions can be used in decisions about planning for offshore recreation and commercial activities and to inform conservation planning at regional scales.

Assessing the importance of individual‐ and colony‐level variation when using seabird foraging ranges as impact assessment and conservation tools

“…These findings support previous research in which breeding adults from larger colonies were found to forage further afield than those from smaller colonies (Lewis et al 2001, Ballance et al 2009, Patterson et al 2022. Given the apparent links between colony size and foraging range across seabirds (Jovani et al 2016) and the availability of census data for many breeding populations (Mitchell et al 2004, Ronconi et al 2022) adjusting expectations of foraging range in relation to colony size may provide a way to refine foraging distance-based approaches in the absence of colony-specific tracking data. Longer foraging ranges also have the potential to drive inter-population differences in demography if they result in declines in the provisioning rate of chicks, constraining chick growth (Gaston et al 1983), or lower and more variable rates of adult survival (Horswill et al 2023).…”

“…We believe accounting for this amount of variation within an applied setting is likely to be important and emphasizes the preference for collecting colony-specific data when possible. As tracking at larger scale becomes more practicable and habitat modelling procedures develop, such methods may therefore begin to supersede simpler foraging range-based assumptions (Matthiopoulos et al 2022, Ronconi et al 2022). Among-individual differences appeared to be relatively important in explaining variation in Shag foraging ranges but less so in the other species examined.…”

“…In some cases, multi-colony tracking studies can provide wide-scale predictions about seabird distributions beyond the immediate colonies surveyed through species distribution modelling (Wakefield et al 2017, Cleasby et al 2020a, Ronconi et al 2022). However, these models rely upon large amounts of data and are currently only available for a small subset of species.…”

Geographic, ecological, and temporal patterns of seabird mortality during the 2022 HPAI H5N1 outbreak on the island of Newfoundland

“…Storm-petrel ecology may partially explain their seeming lack of infection. They forage hundreds of kilometres offshore beyond the foraging ranges of gannets, auks, and gulls that breed in NFLD, and are unlikely to contact infected allospecific birds at sea (Ronconi et al 2022). They also nest in burrows, which generally restrict contact with conspecifics, and are nocturnal (Pollet et al 2021), so they are less likely to contact allospecific birds at the colony.…”

Using foraging range and colony size to assess the vulnerability of breeding seabirds to oil across regions lacking at-sea distribution data

“…However, this still relies on some level of distributional data to inform the SDMs, as well as adequate data on environmental conditions that influence seabird at-sea distributions. Tracking data can also be used to create distribution maps and provide data to SDMs, especially over discrete areas and smaller suites of species (Augé et al 2018, Carneiro et al 2020, Fauchald et al 2021, Ronconi et al 2022). However, despite the large, and increasing, amount of tracking data available, both for the breeding and nonbreeding season (Lascelles et al 2016, Oppel et al 2018, Davies et al 2021), data are still limited for many species and locations.…”