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Hummingbirds are charismatic fauna that provide important pollination services, including in the continental US, where 15 species regularly breed. Compared to other birds in North America, hummingbirds (family Trochilidae) have a unique exposure route to pesticides because they forage on nectar. Therefore, hummingbirds may be exposed to systemic pesticides borne in nectar. They also may be particularly vulnerable to pesticide exposure due to their small size and extreme metabolic demands. We review relevant factors including hummingbird life history, nectar residue uptake, and avian bioenergetic considerations with the goal of clearly identifying and articulating the specific modeling challenges that must be overcome to develop and/or adapt existing modeling approaches. To help evaluate these factors, we developed a dataset for ruby-throated hummingbirds (Archilochus colubris) and other avian species potentially exposed to pesticides. We used the systemic neonicotinoid pesticide imidacloprid as an illustration and compared results to five other common current use pesticides. We use the structure of Pop-GUIDE to provide a conceptual modeling framework for implementation of MCnest and to compile parameter values and relevant algorithms to predict the effects of pesticide exposure on avian pollinators. Conservative screening assessments suggest the potential for adverse effects from imidacloprid, as do more refined assessments, though many important limitations and uncertainties remain. Our review found many areas in which current USEPA avian models must be improved in order to conduct a full higher-tier risk assessment for avian pollinators exposed to neonicotinoid insecticides, including addition of models suitable for soil and seed treatments within the MCnest environment, ability to include empirical residue data in both nectar and invertebrates rather than relying on existing nomograms, expansion of MCnest to a full annual cycle, and increased representation of spatial heterogeneity. Although this work focuses on hummingbirds, the methods and recommendations may apply more widely to other vertebrate pollinators.

Effective management of wildlife populations benefits from an understanding of the long-term vulnerability of species to anthropogenic stressors. Exposure to potential habitat change is one measure of vulnerability that wildlife managers often use to assess and prioritize individual species or groups of species for resource allocation or direct management actions. We used species distribution models for 15 species occurring in the coastal plain ecoregion of Georgia to estimate the current amount and distribution of potential habitat and then predict exposure to changes in habitat due to inundation from sea level rise (using the Sea Level Affecting Marshes model) and urban growth (using the Slope Land-use Excluded Urban Topology Hillshade Growth model) for four future time points. Our results predict that all focal species were likely to experience some exposure to habitat change from either sea level rise or urbanization, but few species will experience high exposure to change from both stressors. Species that use salt marsh or beach habitats had the highest predicted exposure from sea level rise (25–69%), while species that use more inland habitats had the highest predicted exposure to urban growth (10–20%). Our models are a resource for managers considering tradeoffs between prioritization schemes under two future stressors. Results suggest that managers may need to prioritize species (or their habitats) based on the predicted magnitude of habitat loss, while also contextualizing prioritization with respect to the current amount of available protected habitat and species global vulnerability.