Date of Award

2025

Degree Type

Thesis

Degree Name

Master of Science in Biological and Environmental Sciences (MSBES)

Department

Natural Resources Science

First Advisor

Scott R. McWilliams

Abstract

Birds are declining across North America, and migratory birds represent the majority of these declines. As such, there has been an increased interest in understanding long-term trends in both abundance and phenology for individual species of migratory birds so that informed conservation decisions can be made to best meet the needs of at-risk species in the face of global threats, such as anthropogenic climate change. In this thesis, I analyzed 52 years (1970-2021) of autumn hatch-year bird banding data from the Block Island Banding Station on Block Island, RI to assess long-term changes in both autumn migratory songbird abundance (Chapter 1) and autumn migration phenology (Chapter 2).

For Chapter 1, I performed model selection using AICc to determine the abundance trend for 22 species of migratory birds and compared the results to trends from Manomet Conservation Sciences and the USGS Breeding Bird Survey. My candidate models included both traditional models (no change, linear, and quadratic), as well as breakpoint models, which accounted for abrupt changes in slope throughout the study period. Eighteen of 22 species were best represented by breakpoint models, all declined steeply in the first two decades of the study, and all breakpoints occurred within the same 10-year period (1976-1986). After the breakpoint, 17 out of 18 species were classified as either stable or recovering and only one species continued to decline. Only four species had trends best described by traditional models, with two exhibiting linear trends, one with a quadratic trend, and one showing no change in abundance during the study period. Comparisons with Manomet and the Breeding Bird Survey highlight the importance of timescale choice when analyzing, classifying, and interpreting abundance trends for the purpose of making relevant conservation decisions to protect vulnerable species.

For Chapter 2, I characterized long-term changes in autumn migration phenology of 17 species of migratory birds using the same 52-year long bird banding dataset as Chapter 1. Again, we ran four models for each species (no change, linear, quadratic, cubic) and performed model selection using AICc to determine the best model for each phenology trend. We then used linear mixed-effects models to determine the combination of regional weather and life history traits that best predicted mean passage date on Block Island. Nine of the species delayed their autumn migration, 1 species migrated earlier, and 7 species did not change their passage date over time. Short-distance migrants migrated later than long-distance migrants, and species delayed their migration when the frequency of favorable wind profits increased, or the timing of favorable wind profits were delayed. The relationship between autumn temperature and mean passage date varied by autumn diet. Species with low-fruit autumn diets migrated later with warmer temperatures than species with high-fruit diets. These results suggest that not only are the majority of species delaying their autumn migration in southern New England, but some species may have the phenological flexibility to adjust their phenology based on interannual fluctuations in environmental conditions. Understanding both long-term phenology patterns and their drivers is critically important for predicting how migratory birds will continue to respond to anthropogenic climate change.

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Available for download on Thursday, May 27, 2027

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