Decision-making and demography of greater white-fronted geese
Authors:   , Cunningham Stephanie A. 
Published: September 2024

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI--COLUMBIA AT REQUEST OF AUTHOR.] Greater white-fronted geese (Anser albifrons) are Arctic-nesting waterfowl with breeding ranges distributed throughout the Arctic. Due to this broad distribution, the species has been separated into four to five subspecies, and comprises at least eight populations with distinct migration strategies. There are three populations in North America: the Pacific Flyway, midcontinent, and Tule white-fronted geese. The Pacific Flyway and midcontinent populations have both exhibited increases in recent decades. In contrast, the Greenland white-fronted goose population is of conservation concern, and has shown a declining trend over the past 25 years. Greenland white-fronted geese show analogous characteristics in size and breeding biology to North American white-fronted geese, but recent modeling has indicated that recruitment is limiting population growth in the Greenland population. However, researchers have not yet robustly quantified if low recruitment is the result of decision-making (restraint), or external factors, such as local weather conditions experienced during spring migration (constraint). Therefore, we chose the North American midcontinent and Greenland populations, which exhibit contrasting migration strategies, to investigate behavioral decisions and subsequent reproductive output. xii In many populations, individual fitness can be explained by carry-over effects, which are events occurring earlier in the annual cycle that impact individuals later in the year. Carry-over effects are often manifested as body condition effects in migrating waterfowl, whereby individual decisions result in differential condition that explains reproductive success or failure. Carry over effects can be a result of weather conditions. For example, weather-driven decreases in available resources can affect body condition. Advances in Global Positioning System/accelerometer technologies have vastly increased opportunities for researchers to obtain previously inaccessible information on animal movements, energy expenditure, and fine-scale behaviors, including estimation of time spent feeding. We used Bayesian generalized linear mixed models to quantify behavioral differences in four discrete time periods throughout spring migration and tested the influence of each in describing variation in probability of a breeding attempt. Our results suggested that the most important time period in describing variation between birds that attempted to breed and birds that deferred varied across populations and between energy expenditure (via overall dynamic body acceleration [ODBA]) and feeding behavior. We found a strong interaction effect between population and overall feeding behavior during spring migration. We also assessed the influence of local weather conditions in mediating behavior during the same four time periods. The variation in proportion of time feeding and ODBA explained by precipitation and temperature varied by population and time period, but we consistently saw positive relationships between proportion of time feeding and temperature, and a negative relationship with precipitation, as geese approached breeding areas. ODBA also had a negative relationship with precipitation and positive xiii relationship with temperature, later in spring migration for both populations, indicating that poor conditions experienced by individuals are likely constraining. Advanced statistical approaches such as integrated population models (IPMs) allow for the combination of data sets to provide robust estimates of demographic parameters even in the presence of limited or missing data. These models utilize a joint likelihood for parameter estimation. IPMs are useful tools when data are incomplete and can be used to link demographic rates with landscape variables to steer management decisions, both in the case of threatened and overabundant species. We built an IPM for the Pacific Flyway population of white-fronted geese, which has not been monitored as intensely as other North American waterfowl species such as lesser snow geese (Anser caerulescens caerulescens) or mallard (Anas platyrhynchos). We utilized the fall population index, band recovery and Parts Collection Survey goose tail data to estimate population size, adult and juvenile survival, and age ratio (i.e., productivity). Greater white-fronted geese frequently use rice fields in California's Sacramento Valley as a wintering area. Despite the negative impacts of most land use change, rice fields have provided surrogate wetland habitat for many waterfowl and shorebird species. Waste grains and aquatic vegetation that grows in inundated fields provides food for these birds through the winter. Hence, we predicted that the agricultural intensification in the Sacramento Valley would be an important driver of population growth in the Pacific Flyway population of greater white-fronted geese over the past 40 years. We modeled the effects of rice agriculture, in addition to the Pacific Decadal Oscillation index, which we considered a proxy for conditions on the breeding areas, population size, and harvest, on adult survival and age ratio. While rice agriculture did not explain strong variation in xiv either adult survival or age ratio, we found an effect (although weak) of density dependence on these demographic rates. The population appears to still be growing, and our estimates indicated high adult survival and age ratio. We encourage further banding efforts of this population to better understand the drivers of population growth and links between demographic rates and landscape variables. Stronger inferences may be beneficial to management of not only species of conservation concern, but also overabundant species occupying heavily altered landscapes. Because populations are fundamentally made up of individuals, it is worthwhile to understand not only overall processes that moderate survival and productivity, but also individual factors that are the foundation of these relationships.