Investigating effects of local atmospheric and global climatic conditions on avian migration across spatial and temporal scales, with a focus on North American aerial insectivores

Abstract

Every spring and fall, billions of birds migrate to and from their breeding and wintering grounds; however, despite migratory birds being the subject of many studies, large gaps remain in our understanding of the process of avian migration. In fact, avian migration is difficult to study because birds are small, thus difficult to track, and move across large spatial and temporal scales, often at night. However, the data revolution has allowed citizen-science programs such as eBird (Sullivan et al., 2009) to flourish. In fact, citizen-science programs, which allow members of the general public to participate in scientific research, have benefited from our improved ability to process large quantities of data, making it possible to track the continental-scale movements of many avian species. Furthermore, recent technological advances have allowed remote-sensing technologies such as weather surveillance radar (WSR) and acoustic sensors to be used to detect avian migrants in the air (Robinson et al., 2010; Van Doren et al., 2023). My dissertation leverages these incredible innovations to understand how avian migrants respond to changes in local atmospheric conditions during a single migration season and how they have been responding to global climate change in the eastern United States across migration seasons. Thus, my dissertation makes use of data-driven approaches to elucidate the factors impacting avian migration at a variety of spatial and temporal scales.The first two chapters of my dissertation are motivated by the threat that global climate change poses to life on Earth. In fact, global climate change has a number of negative effects on plants and animals; therefore, understanding how they are responding to global climate change is critical for their conservation. For instance, it is well-documented that the phenology (i.e., the timing of the annual life-cycle events such as the migration and reproduction) of many plants and animals has shifted in response to global climate change (Parmesan & Yohe, 2003; J. M. Cohen et al., 2018). Phenological shifts are concerning because they can lead to mismatches between interacting species if these species are not able to shift their phenologies in tandem with one another (Visser et al., 1998; Stenseth & Mysterud, 2002). As a result, phenological mismatches may reduce species’ fitness (i.e., their survival and reproductive success), which could lead to population declines and, ultimately, species loss, thus fueling the current biodiversity crisis (Both et al., 2006a). Avian migrants form a system that is well-suited to study the effects of global climate change on phenology because they track seasonally available resources; thus, they are sensitive to changes in their environment and function as valuable indicators of global change. Over the past few decades, a number of species have shifted their migration phenology (i.e., their timing of migration) and, in particular, their spring migration phenology in response to global climate change (Møller et al., 2008a; Hurlbert & Liang, 2012; Mayor et al., 2017a; Horton et al., 2020; Youngflesh et al., 2021). There is considerable variation in the magnitude and direction of these phenological shifts both among and within species, suggesting that some species are more sensitive to climate change and exhibit more spatial variation in sensitivity than others. However, the mechanisms driving inter- and intraspecific variation in sensitivity are not well understood. For the first chapter of my dissertation, I used eBird data between 2002 and 2019 to investigate the mechanisms driving variation in the sensitivity of species’ spring migration phenology to air temperature change within and across species. I considered these mechanisms in ten species of aerial insectivores (i.e., birds that feed on insects while flying), as the migration phenology of aerial insectivores is sensitive to the emergence of insects and, thus, to changes in air temperature. I found that the migration phenology of most of these species—seven out of ten, to be exact—was more sensitive in places that had become warmer between 2002 and 2019, suggesting that climate warming is exerting pressure on species to become more sensitive. I also investigated the ability of species-specific traits to modulate sensitivity across species. These traits included mean body size, migration distance, migration speed, and arrival day, and I found that arrival day was the only trait that predicted sensitivity to air temperature change. Thus, this chapter sheds light on the mechanisms driving both variation in phenological shifts among species and across space. The second chapter of my dissertation builds on the first chapter by investigating the effects of the phenological shifts that I uncovered in aerial insectivores in the first chapter on the population trends of these species. In fact, since the 1970s, many species of birds in North America, including aerial insectivores, have experienced steep population declines, but the causes of these declines are not well understood (Rosenberg et al., 2019; Spiller & Dettmers, 2019a). It has been hypothesized that phenological mismatches between birds and their food sources, driven by global climate change, play a role in precipitating some of these declines, but this hypothesis has not been properly tested in North American birds, including aerial insectivores that breed in North America (Clark & Hobson, 2022). Therefore, for the second chapter of my dissertation, I examined the effect of phenological sensitivity to climate change, which I estimated in the first chapter, on the population trends of the same ten aerial insectivores that I studied in the first chapter using data from the North American Breeding Bird Survey (BBS), a citizen-science program (Ziolkowski et al., 2024). I then compared the effect of this factor to that of two other factors, change in vegetation green-up phenology and human footprint, which are also thought to influence species’ population trends. I found that these three factors had statistically significant effects on the population trends of eight, three, and two species, respectively, with sensitivity having an effect on the greatest number of species and exhibiting the greatest effects compared to the other two factors. Additionally, although human footprint was only found to be positively associated with the population trends of two species, Chimney Swift and Purple Martin, this association was as predicted, as these two species rely on humans to provide structures for them to nest in. Thus, this chapter sheds light on the factors that shape migrant species’ ability to persist in the face of a changing climate. The third and final chapter of my dissertation aims to elucidate the effects of atmospheric circulation patterns on avian migrants in flight. This chapter is also motivated by global climate change, albeit in a different manner. In fact, global climate change is projected to alter atmospheric circulation patterns around the globe (Zeng et al., 2019); therefore, it is important to characterize the current effects of atmospheric circulation patterns, including those of wind, on avian migrants to predict their effects in the future. For instance, global climate change is projected to alter the Great Plains low-level jet that generates winds that blow from the south across the Great Plains, which would affect birds migrating across the Great Plains in the spring and fall (Zhou et al., 2021). With that in mind, my collaborators and I decided to conduct a local study in Oklahoma to see if we could integrate data from multiple sensors used to detect birds to better understand the effects of wind on avian migrants; these sensors had never been deployed together in this manner before. Specifically, my collaborators and I designed a multi-sensor array consisting of a weather surveillance radar (WSR), a mobile WSR, a novel sensor capable of detecting birds flying in front of the moon, called LunAero, and an acoustic sensor capable of recording avian nocturnal flight calls. We deployed this array at a field site in central Oklahoma on select nights in the spring of 2021, and I integrated data from this array with wind data to assess the effects of wind on the movements of spring migrants aloft. I found that avian migration intensity was negatively correlated with wind speed, suggesting that spring migrants favor weaker winds. Furthermore, I found that migrants took advantage of the presence of strong winds blowing from the south by adjusting their flight direction to match the direction of those winds. This study demonstrates the potential for multi-sensor arrays to provide a more comprehensive picture of the ways in which avian migrants move in response to changing atmospheric conditions aloft.