Caz M. Taylor

Predicting the consequences of carry-over effects for migratory populations.

Migratory animals present a unique challenge for predicting population size because they are influenced by events in multiple stages of the annual cycle that are separated by large geographic distances. Here, we develop a model that incorporates non-fatal carry-over effects to predict changes in population size and show how this can be integrated with predictive models of habitat loss and deterioration. Examples from Barn swallows, Greater snow geese and American redstarts show how carry-over effects can be estimated and integrated into the model. Incorporation of carry-over effects should increase the predictive power of models. However, the challenge for developing accurate predictions rests both on the ability to estimate parameters from multiple stages of the annual cycle and to understand how events between these periods interact to influence individual success.

Population dynamics in migratory networks

Migratory animals are comprised of a complex series of interconnected breeding and nonbreeding populations. Because individuals in any given population can arrive from a variety of sites the previous season, predicting how different populations will respond to environmental change can be challenging. In this study, we develop a population model composed of a network of breeding and wintering sites to show how habitat loss affects patterns of connectivity and species abundance. When the costs of migration are evenly distributed, habitat loss at a single site can increase the degree of connectivity (mixing) within the entire network, which then acts to buffer global populations from declines. However, the degree to which populations are buffered depends on where habitat loss occurs within the network: a site that has the potential to receive individuals from multiple populations in the opposite season will lead to smaller declines than a site that is more isolated. In other cases when there are equal costs of migration to two or more sites in the opposite season, habitat loss can result in some populations becoming segregated (disconnected) from the rest of the network. The geographic structure of the network can have a significant influence on relative population sizes of sites in the same season and can also affect the overall degree of mixing in the network, even when sites are of equal intrinsic quality. When a migratory network is widely spaced and migration costs are high, an equivalent habitat loss will lead to a larger decline in global population size than will occur in a network where the overall costs of migration are low. Our model provides an important foundation to test predictions related to habitat loss in real-world migratory networks and demonstrates that migratory networks will likely produce different dynamics from traditional metapopulations. Our results provide strong evidence that estimating population connectivity is a prerequisite for successfully predicting changes in migratory populations.

Predicting conditions for migration: effects of density dependence and habitat quality

Migration is widespread among animals, but the factors that influence the decision to migrate are poorly understood. Within a single species, populations may be completely migratory, completely sedentary or partially migratory. We use a population model to derive conditions for migration and demonstrate how migratory survival, habitat quality and density dependence on both the breeding and non-breeding grounds influence conditions for migration and the proportion of migrants within a population. Density dependence during the season in which migratory and sedentary individuals use separate sites is necessary for partial migration. High levels of density dependence at the non-shared sites widen the range of survival values within which we predict partial migration, whereas increasing the strength of density dependence at the shared sites narrows the range of survival values within which we predict partial migration. Our results have important implications for predicting how contemporary populations with variable migration strategies may respond to changes in the quality or quantity of habitat.

Large-Scale Impacts of the Deepwater Horizon Oil Spill: Can Local Disturbance Affect Distant Ecosystems through Migratory Shorebirds?

The 2010 Deepwater Horizon oil spill, the largest ever accidental release of oil into marine waters, affected hundreds of miles of US northern Gulf of Mexico coastline that is important habitat for migratory shorebirds. Shorebirds are particularly susceptible to oil contamination because of their subsurface probe-foraging behavior and reliance on intertidal habitat. More than one million migratory shorebirds representing 28 species were potentially exposed to Deepwater Horizon oil during their 2010–2011 nonbreeding season. Although only 8.6% of the shorebirds trapped from fall 2010 to spring 2011 showed visible signs of oiling, nonlethal effects and degradation of habitat can affect populations in ways that carry over into subsequent seasons. Here, we discuss how the spill could affect populations of migratory shorebirds through acute mortality, as well as through long-term and indirect pathways. We also discuss the potential impacts on ecosystems far from the spill, including prairie grasslands and the Arctic, where migratory shorebirds breed.

The importance of stopover habitat for developing effective conservation strategies for migratory animals

Although stopover habitats are used by many species as refuelling stations during migration and can be critical for survival and successful reproduction, they are rarely incorporated in year-round population models and conservation strategies. We incorporate stopover habitat into a density-dependent population model and then use this model to examine how optimizing one-time land purchase strategies for a migratory population is influenced by variation in the quality and the strength of density-dependence in a stopover habitat used for both fall and spring migration. As the strength of the density-dependence in the stopover habitat increases, the optimal amount of stopover habitat purchased increases while the amount of habitat during the stationary periods of the annual cycle (breeding and wintering) decreases. Any change in the cost of purchasing stopover habitat affects investment strategies in all three periods of the annual cycle. When the quality of the stopover habitat is high, the optimal strategy is to invest in low-quality habitat during breeding and wintering and when the stopover habitat quality is low, the optimal strategy switches to investing in high-quality habitat during the stationary periods. We apply this model to a threatened warbler population and demonstrate how purchase decisions to conserve stopover habitat that are not coordinated with conservation actions on the breeding and wintering grounds can potentially result in a lower population carrying-capacity compared to considering habitat in all three periods of the annual cycle simultaneously. Our model provides potential guidelines for developing conservation strategies for animals that rely on refueling habitats between the stationary breeding and non-breeding periods of the migratory cycle.

The evolution of migration in a seasonal environment

Despite the fact that migration occurs in a wide variety of taxa worldwide, little is known about the conditions under which migration is expected to evolve from an ancestral resident population. We develop a model that focuses on ecological factors affecting the evolution of migration in a seasonal environment within a genetically explicit framework. We model the evolution of migration for two common types of migration: ‘shared breeding’ where migrants share a breeding ground with residents and migrate to a separate non-breeding area, versus ‘shared non-breeding’, where migrants share a non-breeding ground with residents and migrate to a separate breeding area. Ecologically, migration is more easily established in the shared-breeding case versus the shared-non-breeding case. Genetically, the additive effect of a migratory allele affects its establishment more in the shared-non-breeding case versus the shared-breeding case, whereas the dominance effect of the allele affects its establishment more in the shared-breeding case versus the shared-non-breeding case. Generally, migratory alleles can invade even when residents are competitively superior to migrants during the shared season. Partial migration occurs when the population is polymorphic for migratory and non-migratory alleles, and is dependent upon which season is shared and the additive and dominance behaviour of the migratory allele.

Metapopulation models for seasonally migratory animals

Metapopulation models are widely used to study species that occupy patchily distributed habitat, but are rarely applied to migratory species, because of the difficulty of identifying demographically independent subpopulations. Here, we extend metapopulation theory to describe the directed seasonal movement of migratory populations between two sets of habitat patches, breeding and non-breeding, with potentially different colonization and extinction rates between patch types. By extending the classic metapopulation model, we show that migratory metapopulations will persist if the product of the two colonization rates exceeds the product of extinction rates. Further, we develop a spatially realistic migratory metapopulation model and derive a landscape metric—the migratory metapopulation capacity—that determines persistence. This new extension to metapopulation theory introduces an important tool for the management and conservation of migratory species and may also be applicable to model the dynamics of two host–parasite systems.

Effects of breeding versus winter habitat loss and fragmentation on the population dynamics of a migratory songbird

Many migratory species are in decline and understanding these declines is challenging because individuals occupy widely divergent and geographically distant habitats during a single year and therefore populations across the range are interconnected in complex ways. Network modeling has been used to show, theoretically, that shifts in migratory connectivity patterns can occur in response to habitat or climate changes and that habitat loss in one region can affect sub-populations in regions that are not directly connected. Here, we use a network model, parameterized by integrating long-term monitoring data with direct tracking of -100 individuals, to explain population trends in the rapidly declining Wood Thrush (Hylocichla mustelina) and to predict future trends. Our model suggests that species-level declines in Wood Thrush are driven primarily by tropical deforestation in Central America but that protection of breeding habitat in some regions is necessary to prevent shifts in migratory connectivity and to sustain populations in all breeding regions. The model illustrates how shifts in migratory connectivity may lead to unexpected population declines in key regions. We highlight current knowledge gaps that make modeling full life-cycle population demographics in migratory species challenging but also demonstrate that modeling can inform conservation while these gaps are being filled.

Relationship between stopoveR site choice of migRating sandpipeRs, theiR population status, and enviRonmental stRessoRs

Measures of animal behavior can be used in a variety of situations to make inferences about the environment and population status. Work by our research group shows that migratory shorebirds adjust their usage of, and behavior at, stopover sites in response to environmental conditions. Motivated by this, we built an individual-based model of migrating shorebirds moving through a sequence of alternating small and large stopover sites. birds at larger sites are safer from predators, but we assumed that less food is available than at small sites. In the model, both predation risk and food intake are densitydependent, and the behavior of migrants is controlled by two rules: one that determines whether a bird will depart a stopover site, and one that controls the individual’s foraging versus vigilance intensity. The optimal behavior is calculated by maximizing a payoff function that depends on arrival date and arrival energy stores at the final site. We used this model to predict mass gain, foraging intensity, and usage by migrants of small and large sites under various conditions. We examined the effects of a flyway-wide reduction in the amount of food, a flyway-wide increase in predation danger, and the effects of lowering the overall population size. The mass action of many individuals, each optimizing its migration timing and routing, leads to the emergence of distinctive patterns of behavior and site choice under these differing environmental conditions. When food availability is reduced throughout the flyway, our model predicts that foraging intensity increases at every stopover site, thereby forcing birds to accept greater danger to maintain the fitness benefit of a timely arrival to the breeding area. A flyway-wide increase in predation danger results in fewer migrants choosing (and/or migrants staying a shorter time at) small stopover sites, balanced by a higher usage of large sites. These effects contrast with what is observed under true population declines, when the usage of both small and large sites declines.

Assessing costs of carrying geolocators using feather corticosterone in two species of aerial insectivore

Despite benefits of using light-sensitive geolocators to track animal movements and describe patterns of migratory connectivity, concerns have been raised about negative effects of these devices, particularly in small species of aerial insectivore. Geolocators may act as handicaps that increase energetic expenditure, which could explain reported effects of geolocators on survival. We tested this ‘Energetic Expenditure Hypothesis’ in 12 populations of tree swallows (Tachycineta bicolor) and barn swallows (Hirundo rustica) from North America and Europe, using measurements of corticosterone from feathers (CORTf) grown after deployment of geolocators as a measure of physiology relevant to energetics. Contrary to predictions, neither among- (both species) nor within-individual (tree swallows only) levels of CORTf differed with respect to instrumentation. Thus, to the extent that CORTf reflects energetic expenditure, geolocators apparently were not a strong handicap for birds that returned post-deployment. While this physiological evidence suggests that information about migration obtained from returning geolocator-equipped swallows is unbiased with regard to levels of stress, we cannot discount the possibility that corticosterone played a role in reported effects of geolocators on survival in birds, and suggest that future studies relate corticosterone to antecedent factors, such as reproductive history, and to downstream fitness costs.