Allison Byrd

Date of Award


Level of Access Assigned by Author

Campus-Only Thesis

Degree Name

Master of Science (MS)


Ecology and Environmental Sciences


Brian Olsen

Second Committee Member

Rebecca Holberton

Third Committee Member

David Evers


Climate change has the potential to shift and restrict ranges for a suite of species. The birds of the boreal ecosystem, like the Common Loon (Gavia immer), may be particularly at risk given the changes predicted for this biome. Current range models for this iconic water bird predict that large sections of the United States may lose the loon in the next 100 years, but these models are based on habitat correlations and not the demographic mechanisms that will actually produce the change. The primary goal of our research was to understand the factors that determine loon vulnerability to climatic change at multiple scales. We applied a recursive partitioning technique to analyze loon presence/absence in 288 lakes across the southern edge of their North American distribution using 112 abiotic and landscape-level factors. The resulting binary tree (“decision tree”) classified lakes into groups based on the probability of loon presence, while maximizing homogeneity within the resultant two nodes. The most significant splits in the cross-validated tree were created using lake salinity, acidity, and sulfate levels. We employed similar methods to compare loon occupancy and seasonal fecundity at a smaller scale (New England) to elucidate potential demographic mechanisms of loon persistence. Results from twenty potential predictors suggest that similar processes are driving loon presence/absence both continentally and within New England (lake salinity, alkalinity, and lake surface area). Loon productivity, on the other hand, was best predicted using the size of the lake and its drainage basin. Lake surface area and characteristics of the drainage basin are thus good predictors of both loon distribution and loon productivity, and are thus also likely to be useful in predicting range shifts in the future. As few (if any) of the predictors of productivity in the best decision trees are likely to change dramatically with climate, these outcomes suggest that future range alteration for loons due to climate change are likely to be more sensitive to annual adult survival (which will influence breeding ground settlement patterns) than environmental factors encountered on the breeding grounds.

After highlighting the environmental factors that predict loon occupancy and productivity, we explored environmental predictors of individual energetic condition. Physiological measures may offer more information about the likelihood of loon persistence, because they can identify covariance between energetic condition and breeding habitat quality. We used blood metabolites and behavioral observations to evaluate the energetic costs of common loons (Gavia immer) breeding on lakes across a gradient of environmental, spatial, and social conditions. Using samples collected over two years (n=97) along the species’ southern breeding range edge (ME, NH, MA, MT, WA), we identified the number of offspring, daily maximum temperature, and latitude as the most important drivers of the energetic cost of maintaining a breeding territory. Specifically we found that: 1) loons with two chicks expend more energy than those with one, 2) loons near the southern range edge expend more energy to produce a given brood size than those nearer the range center and, 3) birds breeding in warmer temperatures expend more energy than those in cooler temperatures (controlling for year, territory type, and calendar date, free glycerol levels, size-corrected body mass, and longitude). We suggest that as environmental conditions change in the coming years, blood metabolites offer a promising predictor of population collapse along range boundaries. Energetic condition deteriorated toward the southern range edge and in warmer conditions, controlling for the number of offspring produced, which suggests that loons may be sensitive to increasing global temperatures. We suggest that as environmental conditions change in the coming years, blood metabolites offer a promising predictor of population collapse along range boundaries.