Genomics-informed conservation units reveal spatial variation in climate vulnerability in a migratory bird

Identifying genetic conservation units (CUs) in threatened species is critical for the preservation of adaptive capacity and evolutionary potential in the face of climate change. However, delineating CUs in highly mobile species remains a challenge due to high rates of gene flow and genetic signatures of isolation by distance. Even when CUs are delineated in highly mobile species, the CUs often lack key biological information about what populations have the most conservation need to guide management decisions. Here we implement a framework for CU identification in the Canada Warbler (Cardellina canadensis), a migratory bird species of conservation concern, and then integrate demographic modelling and genomic offset to guide conservation decisions. We find that patterns of whole genome genetic variation in this highly mobile species are primarily driven by putative adaptive variation. Identification of CUs across the breeding range revealed that Canada Warblers fall into two evolutionarily significant units (ESU), and three putative adaptive units (AUs) in the South, East, and Northwest. Quantification of genomic offset, a metric of genetic changes necessary to maintain current gene-environment relationships, revealed significant spatial variation in climate vulnerability, with the Northwestern AU being identified as the most vulnerable to future climate change. Alternatively, quantification of past population trends within each AU revealed the steepest population declines have occurred within the Eastern AU. Overall, we illustrate that genomics-informed CUs provide a strong foundation for identifying current and future regional threats that can be used to inform management strategies for a highly mobile species in a rapidly changing world.

An ecologist's introduction to continuous-time multi-state models for capture-recapture data

Recent technological advances have led to a rapid increase in the collection of capture-recapture data in continuous time. Unlike traditional capture-recapture data, the detection times from these technologies are themselves random variables and analysis of these data, therefore, requires models that properly account for stochasticity in both state transitions and detection times. Despite the ubiquity of continuously collected capture-recapture data, the mathematical concepts needed to fit continuous-time models remain unfamiliar to many ecologists. In this paper, I provide an introduction to continuous-time models, with a focus on multi-state capture-recapture data. After reviewing the basic structure of these models, I describe several variations, including constant parameters, temporal variation in state transition rates and autocorrelation in detections. To aid comprehension, each model is accompanied by code to simulate data and fit the model in Stan. Although the models presented in this guide are only a small subset of the variations that are possible to suit the needs of specific datasets or questions, the concepts and code will hopefully serve as a foundation for future analyses, allowing ecologists to develop new and creative approaches to continuous-time modelling.

Empirical tests of habitat selection theory reveal that conspecific density and patch quality, but not habitat amount, drive long-distance immigration in a wild bird

Individuals that disperse long distances from their natal site must select breeding patches with no prior knowledge of patch suitability. Despite decades of theoretical studies examining which cues dispersing individuals should use to select breeding patches, few empirical studies have tested the predictions of these theories at spatial scales relevant to long‐distance dispersal in wild animal populations. Here, we use a novel assignment model based on multiple intrinsic markers to quantify natal dispersal distances of Wood Thrush (Hylocichla mustelina) breeding in forest fragments. We show that long‐distance natal dispersal in this species is more frequent than commonly assumed for songbirds and that habitat selection by these individuals is driven by density‐dependence and patch quality but not the amount of habitat surrounding breeding patches. These results represent an important contribution to understanding habitat selection by dispersing individuals, especially with regards to long‐distance dispersal.

Using value of information to prioritize research needs for migratory bird management under climate change: a case study using federal land acquisition in the United States

In response to global habitat loss, many governmental and non-governmental organizations have implemented land acquisition programs to protect critical habitats permanently for priority species. The ability of these protected areas to meet future management objectives may be compromised if the effects of climate change are not considered in acquisition decisions. Unfortunately, the effects of climate change on ecological systems are complex and plagued by uncertainty, making it difficult for organizations to prioritize research needs to improve decision-making. Herein, we demonstrate the use of qualitative value of information analysis to identify and prioritize which sources of uncertainty should be reduced to improve land acquisition decisions to protect migratory birds in the face of climate change. The qualitative value of information analysis process involves four steps: (i) articulating alternative hypotheses; (ii) determining the magnitude of uncertainty regarding each hypothesis; (iii) evaluating the relevance of each hypothesis to acquisition decision-making; and (iv) assessing the feasibility of reducing the uncertainty surrounding each hypothesis through research and monitoring. We demonstrate this approach using the objectives of 3 U.S. federal land acquisition programs that focus on migratory bird management. We used a comprehensive literature review, expert elicitation, and professional judgement to evaluate 11 hypotheses about the effect of climate change on migratory birds. Based on our results, we provide a list of priorities for future research and monitoring to reduce uncertainty and improve land acquisition decisions for the programs considered in our case study. Reducing uncertainty about how climate change will influence the spatial distribution of priority species and biotic homogenization were identified as the highest priorities for future research due to both the value of this information for improving land acquisition decisions and the feasibility of reducing uncertainty through research and monitoring. Research on how changes in precipitation patterns and winter severity will influence migratory bird abundance is also expected to benefit land acquisition decisions. By contrast, hypotheses about phenology and migration distance were identified as low priorities for research. By providing a rigorous and transparent approach to prioritizing research, we demonstrate that qualitative value of information is a valuable tool for prioritizing research and improving management decisions in other complex, high-uncertainty cases where traditional quantitative value of information analysis is not possible. Given the inherent complexity of ecological systems under climate change, and the difficulty of identifying management-relevant research priorities, we expect this approach to have wide applications within the field of natural resource management.

Modeling spatially and temporally complex range dynamics when detection is imperfect

Species distributions are determined by the interaction of multiple biotic and abiotic factors, which produces complex spatial and temporal patterns of occurrence. As habitats and climate change due to anthropogenic activities, there is a need to develop species distribution models that can quantify these complex range dynamics. In this paper, we develop a dynamic occupancy model that uses a spatial generalized additive model to estimate non-linear spatial variation in occupancy not accounted for by environmental covariates. The model is flexible and can accommodate data from a range of sampling designs that provide information about both occupancy and detection probability. Output from the model can be used to create distribution maps and to estimate indices of temporal range dynamics. We demonstrate the utility of this approach by modeling long-term range dynamics of 10 eastern North American birds using data from the North American Breeding Bird Survey. We anticipate this framework will be particularly useful for modeling species' distributions over large spatial scales and for quantifying range dynamics over long temporal scales.

Estimability of migration survival rates from integrated breeding and winter capture-recapture data

Long-distance migration is a common phenomenon across the animal kingdom but the scale of annual migratory movements has made it difficult for researchers to estimate survival rates during these periods of the annual cycle. Estimating migration survival is particularly challenging for small-bodied species that cannot carry satellite tags, a group that includes the vast majority of migratory species. When capture-recapture data are available for linked breeding and non-breeding populations, estimation of overall migration survival is possible but current methods do not allow separate estimation of spring and autumn survival rates. Recent development of a Bayesian integrated survival model has provided a method to separately estimate the latent spring and autumn survival rates using capture-recapture data, though the accuracy and precision of these estimates has not been formally tested. Here, I used simulated data to explore the estimability of migration survival rates using this model. Under a variety of biologically realistic scenarios, I demonstrate that spring and autumn migration survival can be estimated from the integrated survival model, though estimates are biased toward the overall migration survival probability. The direction and magnitude of this bias are influenced by the relative difference in spring and autumn survival rates as well as the degree of annual variation in these rates. The inclusion of covariates can improve the model's performance, especially when annual variation in migration survival rates is low. Migration survival rates can be estimated from relatively short time series (4-5 years), but bias and precision of estimates are improved when longer time series (10-12 years) are available. The ability to estimate seasonal survival rates of small, migratory organisms opens the door to advancing our understanding of the ecology and conservation of these species. Application of this method will enable researchers to better understand when mortality occurs across the annual cycle and how the migratory periods contribute to population dynamics. Integrating summer and winter capture data requires knowledge of the migratory connectivity of sampled populations and therefore efforts to simultaneously collect both survival and tracking data should be a high priority, especially for species of conservation concern.

Spatial and temporal drivers of avian population dynamics across the annual cycle

Untangling the spatial and temporal processes that influence population dynamics of migratory species is challenging, because changes in abundance are shaped by variation in vital rates across heterogeneous habitats and throughout the annual cycle. We developed a full-annual-cycle, integrated, population model and used demographic data collected between 2011 and 2014 in southern Indiana and Belize to estimate stage-specific vital rates of a declining migratory songbird, the Wood Thrush (Hylocichla mustelina). Our primary objective was to understand how spatial and temporal variation in demography contributes to local and regional population growth. Our full-annual-cycle model allowed us to estimate (1) age-specific, seasonal survival probabilities, including latent survival during both spring and autumn migration, and (2) how the relative contribution of vital rates to population growth differed among habitats. Wood Thrushes in our study populations experienced the lowest apparent survival rates during migration and apparent survival was lower during spring migration than during fall migration. Both mortality and high dispersal likely contributed to low apparent survival during spring migration. Population growth in high-quality habitat was most sensitive to variation in fecundity and apparent survival of juveniles during spring migration, whereas population growth in low-quality sites was most sensitive to adult apparent breeding-season survival. These results elucidate how full-annual-cycle vital rates, particularly apparent survival during migration, interact with spatial variation in habitat quality to influence population dynamics in migratory species.

Incorporating breeding abundance into spatial assignments on continuous surfaces

Determining the geographic connections between breeding and nonbreeding populations, termed migratory connectivity, is critical to advancing our understanding of the ecology and conservation of migratory species. Assignment models based on stable isotopes historically have been an important tool for studying migratory connectivity of small-bodied species, but the low resolution of these assignments has generated interest into combining isotopes with other sources in information. Abundance is one of the most appealing data sources to include in isotope-based assignments, but there are currently no statistical methods or guidelines for optimizing the contribution of stable isotopes and abundance for inferring migratory connectivity. Using known-origin stable-hydrogen isotope samples of six Neotropical migratory bird species, we rigorously assessed the performance of assignment models that differentially weight the contribution of the isotope and abundance data. For two species with adequate sample sizes, we used Pareto optimality to determine the set of models that simultaneously minimized both assignment error rate and assignment area. We then assessed the ability of the top models from these two species to improve assignments of the remaining four species compared to assignments based on isotopes alone. We show that the increased precision of models that include abundance is often offset by a large increase in assignment error. However, models that optimally weigh the abundance data relative to the isotope data can result in higher precision and, in some cases, lower error than models based on isotopes alone. The top models, however, depended on the distribution of relative breeding abundance, with patchier distributions requiring stronger downweighting of abundance, and we present general guidelines for future studies. These results confirm that breeding abundance can be an important source of information for studies investigating broad-scale movements of migratory birds and potentially other taxa.

Quantifying drivers of population dynamics for a migratory bird throughout the annual cycle

Worldwide, migratory species are undergoing rapid declines but understanding the factors driving these declines is hindered by missing information about migratory connectivity and the lack of data to quantify environmental processes across the annual cycle. Here, we combined range-wide information about migratory connectivity with global remote-sensing data to quantify the relative importance of breeding and non-breeding environmental processes to persistent long-term population declines of a migratory songbird, the wood thrush (Hylocichla mustelina). Consistent with theoretical predictions about population limitation of migratory birds, our results suggest that habitat loss and climate have contributed to the observed declines in wood thrush breeding abundance, yet the relative importance of breeding versus non-breeding factors is population-specific. For example, high-abundance core breeding populations appear to be more limited by habitat loss, whereas low-abundance, peripheral populations appear to be limited by climate-driven seasonal interactions. Further, our analysis indicates that the relative impact of breeding habitat loss is at least three to six times greater than the impact of equivalent non-breeding habitat loss and therefore the steepest regional declines have likely been driven by the loss of breeding habitat. These results underscore the need for population-specific conservation strategies implemented throughout the annual cycle to reverse long-term declines.

Feather corticosterone levels are related to age and future body condition, but not to subsequent fitness, in a declining migratory songbird

In migratory species, breeding and non-breeding locations are geographically separate, yet the effects of conditions from one stage may carry over to affect a subsequent stage. Ideally, to understand the mechanisms and implications of 'carry-over effects', one would need to follow individuals throughout the year, quantify potential environmental causal factors and physiological mediators during multiple life-history stages, and measure downstream fitness. Owing to current limitations of tracking technology, this is impossible for small, long-distance migrants, so indirect methods to characterize carry-over effects are required. Corticosterone (CORT) is a suspected physiological mediator of carry-over effects, but when collected from blood it provides only a physiological snapshot at that point in time. When extracted from feathers, however, feather corticosterone (CORT_f) provides a measure of responses to stressors from previous, and longer, time periods. We collected feathers grown during two life-history stages (post-breeding and subsequent wintering) from individuals of two age classes of a rapidly declining migratory songbird, the cerulean warbler (Setophaga cerulea), on their breeding grounds and quantified CORT_f concentrations. We then monitored reproduction and survival of individuals and analysed relationships among CORT_f and age, body condition and future fitness. Compared with older males, second-year males had higher CORT_f concentrations during both stages. When controlling for age and year, body condition at capture was positively related to CORT_f concentrations from winter (especially for older birds). However, we found no relationships between CORT_f and fitness (as defined by reproduction and survival). Thus, elevated CORT may represent a beneficial physiological response (e.g. hyperphagia prior to migration), particularly for certain life-history stages, and may mediate the condition in which individuals transition between stages. But for those birds that survive migration, subsequent fitness is likely determined by more recent events and local conditions (i.e. on breeding grounds), which have the potential to counteract conditions from the winter.

Habitat features and long-distance dispersal modify the use of social information by a long-distance migratory bird

The processes by which individuals select breeding sites have important consequences for individual tness as well as population- and community-dynamics. Although there is increasing evidence that many animal species use information acquired from conspecics to assess the suitability of potential breeding sites, little is known about how the use of this social information is modified by biotic and abiotic conditions. We used an automated playback experiment to simulate two types of social information, post-breeding public information and pre-breeding location cues, to determine the relative importance of these cues for breeding site selection by a migratory songbird, the American redstart (Setophaga ruticilla). In addition, we used stable hydrogen isotopes to determine the dispersal status of individuals that responded to our experimental treatments and quantify whether long-distance dispersers use different social cues to select breeding sites compared to philopatric individuals. We found that points that received pre-breeding location cue treatments were signi cantly more likely to be settled by redstarts than control points that received no playback. However, we found no evidence the redstarts used post-breeding public information gathered during one season to select breeding sites the following year. Breeding site habitat structure was also a strong predictor of settlement probability, indicating that redstarts modi ed the use of social information based on habitat cues. Furthermore, stable hydrogen isotope signatures from individuals that responded to location cue treatments suggest that long-distance dispersers may rely more heavily on these cues than local recruits. Collectively, these results indicate that redstarts use multiple sources of information to select breeding sites, which could buffer individuals from selecting suboptimal sites when they breed in unfamiliar locations or when habitat quality becomes decoupled from social cues.

Assessing migratory connectivity for a long-distance migratory bird using multiple intrinsic markers

Patterns of migratory connectivity are a vital yet poorly understood component of the ecology and evolution of migratory birds. Our ability to accurately characterize patterns of migratory connectivity is often limited by the spatial resolution of the data, but recent advances in probabilistic assignment approaches have begun pairing stable isotopes with other sources of data (e.g., genetic and mark-recapture) to improve the accuracy and precision of inferences based on a single marker. Here, we combine stable isotopes and geographic variation in morphology (wing length) to probabilistically assign Wood Thrush (Hylocichla mustilena) captured on the wintering grounds to breeding locations. In addition, we use known-origin samples to validate our model and assess potentially important impacts of isotopic and morphological covariates (age, sex, and breeding location). Our results show that despite relatively high levels of mixing across their breeding and nonbreeding ranges, moderate levels of migratory connectivity exist along an east-west gradient. In addition, combining stable isotopes with geographic variation in wing length improved the precision of breeding assignments by 10% and 37% compared to assignments based on isotopes alone or wing length alone, respectively. These results demonstrate that geographical variation in morphological traits can greatly improve estimates of migratory connectivity when combined with other intrinsic markers (e.g., stable isotopes or genetic data). The wealth of morphological data available from museum specimens across the world represents a tremendously valuable, but largely untapped, resource that is widely applicable for quantifying patterns of migratory connectivity.