Population Demography of a Neotropical Migratory Songbird in the Face of a Changing Climate

This dissertation investigates the population dynamics and demographic trends of the Prothonotary Warbler (Protonotaria citrea), a migratory songbird that breeds in North America during the spring and summer and overwinters in Central and northern South America. The primary objective of this dissertation is to examine the combined implications of variation in weather and individual traits on demographic traits and to project the effects of climate change on population trajectories of the Prothonotary Warbler. The analyses conducted in this dissertation centered around female Prothonotary Warblers; however, visual identification of a nestling’s sex is impossible in most altricial bird species, including the Prothonotary Warbler. To accurately estimate female juvenile recruitment and survival, I used blood samples collected from 1,219 Prothonotary nestlings over five years to determine the nestling sex ratios in the population used for this research. Sex determination was achieved using molecular sex identification with the avian CHD gene, a reliable and widely used method in avian research. I found no significant deviation from the expected 50:50 sex ratio among male and female nestlings in any year of the study. These results align with Fisher’s sex ratio theory, which predicts a balanced 50:50 male-to-female offspring ratio and is consistent with most altricial species. Moreover, nestling sex was uncorrelated with nestling mass, maternal age, or brood size. Quantifying nestling sex ratios is fundamental to understanding fecundity and population dynamics in sexually reproducing species, particularly when population sizes are low and at risk of local extinction. This study allows for the assumption of a 50:50 ratio in the female-based population studies in Chapters 1 and 2. Many factors impact migratory species’ responses to climate change, including individual traits and environmental conditions at breeding and non-breeding sites. Therefore, to predict and mitigate the effects of climate change on these species, it is crucial to understand the complex relationships among individual traits and environmental conditions and how these factors collectively affect populations. In Chapter 1, I focused on the effects of individual traits and weather on first-year recruitment, a critical aspect of population growth. Using 28 years of data, I developed a piecewise structural equation model that integrates predictor and response variables into a unified causal network. This methodology facilitates testing multiple hypotheses within a single analysis to decipher the direct and indirect influences of multiple predictor and response variables. In doing so, it provided a holistic understanding of the complex interactions between individual traits and environmental factors and their effect on recruitment. My analysis revealed that an increase in the maximum temperature at the start of clutch initiation negatively affected juvenile recruitment, potentially due to the impact of warmer temperatures on female mothers during the egg-laying process. Poor nestling body condition, increased brood size, delayed hatch date, and the mother’s advancing age also negatively impacted juvenile recruitment. Periods of drier and warmer temperatures during the overwintering phase (El Niño) and lower spring precipitation indirectly decrease recruitment by affecting the nestling’s body condition, brood sizes, and hatch date. These findings emphasize the importance of considering multiple predictors and indirect effects in studies of population declines. The accelerating pace of climate change emphasizes the importance of assessing its impacts on populations and projecting future changes in a broad range of species. Migratory birds are particularly vulnerable to such changes with their transcontinental journeys and reliance on specific habitats at different times in their lifecycle. In Chapter 2, I used a stochastic stage-structured integrated population model and Bayesian population viability analysis (IPM-BPVA) to assess the effect of demographic rates on the Prothonotary Warbler’s population trajectory while considering local weather and large-scale climate factors’ influence on demographic rates. The IPM integrates multiple data types to determine robust estimates of demographic rates, including juvenile survival, adult survival, and fecundity rates, providing a comprehensive view of population dynamics and identifying influential climate factors. To predict future population trajectories, the IPM was combined with a Bayesian population viability analysis (BPVA) using future temperature changes based on forecasted temperatures from six general circulation models (GCM) under two representative concentration pathway (RCP) scenarios. I discovered that increasing temperatures and extreme temperature events linked with climate change significantly impact juvenile survival, adult survival, and fecundity, ultimately influencing population growth. Among all demographic rates examined, adult survival, which is negatively correlated with increasing mean temperatures during the breeding season, emerged as the most influential component affecting population growth. The findings projected a consistent population decline over the next 15 years under various climate change scenarios. However, the quasi-extinction rate remained low, suggesting the population will likely persist despite projected declines. Additionally, my research inspected large-scale climate factors, the Atlantic Multidecadal Oscillation (AMO) and Multivariate El Niño Southern Oscillation Index (MEI), during the overwintering period. These factors represent periodic variations in sea-surface temperature and atmospheric pressures, which can significantly influence weather patterns and hence bird survival and reproduction. However, I did not find a significant impact of these climate cycles on the demographic rates of Prothonotary Warblers. These interconnected studies have highlighted the complex interplay between demographic rates, environmental factors, and climatic conditions in migratory species, especially under the shifting climate regime. Additionally, this research emphasizes the necessity of long-term studies in population research, particularly when examining phenomena like climate change. Long-term data collection over extended periods allows for observing and analyzing evolving trends, patterns, and alterations over time. Another crucial reason for continuous monitoring is to mitigate the risks of forecasting climate change impacts based on historical data alone. These extrapolations can be uncertain, especially when the projected changes do not follow a linear trend. Therefore, this research accentuates the importance of ongoing surveillance and the development of robust predictive models to effectively understand the long-term impacts of climate change on species such as the Prothonotary Warbler and their ecosystems