Improved estimates of certainty in stable-isotope-based methods for tracking migratory animals

Ecological Applications (Impact Factor: 4.13). 03/2008; 18(2):549-559. DOI: 10.1890/07-0058.1

ABSTRACT The use of stable-hydrogen isotopes (delta D) has become a common tool for estimating geographic patterns of movement in migratory animals. This method relies on broad and relatively predictable geographic patterning in delta D values of precipitation, but these patterns are not estimated without error. In addition, delta D measurements are relatively imprecise, particularly for organic tissue. Most models for estimating geographic locations have ignored these sources of error. Common modeling approaches include regression, range-matching, and likelihood-based assignment tests (including discriminant analysis). Here, we show the benefits of a simple stochastic extension to likelihood-based assignment tests that incorporates two estimable sources of error and describe the resulting influence on the certainty of assigning breeding origins for wintering American Redstarts (Setophaga ruticilla), a small Nearctic-Neotropical migratory bird. Through simulation, we incorporated both spatial interpolation error associated with models of delta D in precipitation and analytical error associated with the measurement of delta D in tissue samples. In general, assignments that did not include these sources of error fell within the ranges of the stochastic results, but the difference in proportion of birds assigned to any one breeding region varied by as much as 54%. To explore how the distribution of assignments generated from error models influenced the application of these results, we developed a simple model of winter habitat loss. We removed the proportion of Redstarts wintering at a particular site from the global population and then used the isotope-based assignments to predict the resulting population declines for each breeding region. This gave distributions of change in population sizes, some of which included no change or even a population increase. The sources of error we modeled may challenge the degree of certainty in the use of stable-isotope-based data on connectivity to predict population dynamics of migratory animals. We suggest that stronger inference will result from incorporating these sources of error into future studies that use delta D or other stable isotopes to infer the geographic origin of individuals.

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    ABSTRACT: The population dynamics of migratory animals requires understanding how individuals move, survive, and reproduce throughout the year. How sequential life history events interact to influence population abundance depends upon how populations are spatially connected, termed their migratory connectivity. Developing predictive models of population dynamics for these species requires integrating patterns of migratory connectivity and demographic population processes across the annual cycle. In this thesis, I used the the iconic monarch butterfly (Danaus plexippus) as a model to understand the population dynamics of long-distance migratory animals. In the first chapter, I geographically connected multiple breeding generations of monarch butterflies during an entire breeding season. Breeding monarchs moved north over successive generations but, by late summer, butterflies were moving south to breed. The implication is that monarchs have complex movement patterns over multiple breeding generations and multiple geographic locations are necessary to ensure population viability. In the second chapter, I experimentally measured density-dependent competition amongst larvae and adult monarch butterflies. Female butterflies did not lay fewer eggs under increasing density. However, larval mortality increased across a range of larval densities which correspond to densities commonly observed in field surveys in some geographic regions during the breeding season suggesting density dependence could operate dynamically in space and time across the breeding season. In the third chapter, I developed a stochastic, density-dependent population model that linked migratory connectivity and demographic vital rates across the annual cycle. I found that under continuing habitat loss and projected climate change scenarios, the monarch butterfly population will decline at such a rate that it will meet the IUCN criteria to be listed as vulnerable. In contrast to the traditional conservation focus on the wintering grounds, my results suggest that monarch population abundance is most sensitive to changes in vital rates on the breeding grounds. The results of these studies provide a model system where year-round population models can be used to quantify contributions to population growth across the annual cycle. Ultimately, developing structured quantitative models is a necessary prerequisite to formally address conservation decision-making for long-distance migratory animals at continental scales.
    11/2013, Degree: PhD, Supervisor: D. Ryan Norris, Tara G. Martin
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    ABSTRACT: Satellite-based tracking of migratory waterfowl is an important tool for understanding the potential role of wild birds in the long-distance transmission of highly pathogenic avian influenza. However, employing this technique on a continental scale is prohibitively expensive. This study explores the utility of stable isotope ratios in feathers in examining both the distances traveled by migratory birds and variation in migration behavior. We compared the satellite-derived movement data of 22 ducks from 8 species captured at wintering areas in Bangladesh, Turkey, and Hong Kong with deuterium ratios (δD) in the feathers of these and other individuals captured at the same locations. We derived likely molting locations from the satellite tracking data and generated expected isotope ratios based on an interpolated map of δD in rainwater. Although δD was correlated with the distance between wintering and molting locations, surprisingly, measured δD values were not correlated with either expected values or latitudes of molting sites. However, population-level parameters derived from the satellite-tracking data, such as mean distance between wintering and molting locations and variation in migration distance, were reflected by means and variation of the stable isotope values. Our findings call into question the relevance of the rainfall isotope map for Asia for linking feather isotopes to molting locations, and underscore the need for extensive ground truthing in the form of feather-based isoscapes. Nevertheless, stable isotopes from feathers could inform disease models by characterizing the degree to which regional breeding populations interact at common wintering locations. Feather isotopes also could aid in surveying wintering locations to determine where high-resolution tracking techniques (e.g. satellite tracking) could most effectively be employed. Moreover, intrinsic markers such as stable isotopes offer the only means of inferring movement information from birds that have died as a result of infection. In the absence of feather based-isoscapes, we recommend a combination of isotope analysis and satellite-tracking as the best means of generating aggregate movement data for informing disease models.
    Ecological Indicators 10/2014; 45:266–273. DOI:10.1016/j.ecolind.2014.04.027 · 3.23 Impact Factor
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    ABSTRACT: 1. As a result of predictable large-scale continental gradients in the isotopic composition of precipitation, stable isotopes of hydrogen (δ2H) are useful endogenous markers for delineating long-distance movements of animals. Models to predict patterns of δ2H in precipitation (δ2Hp), and consequently determine likely geographic origin of migratory animals, have traditionally used static, amount-weighted long-term average values of δ2Hp over the growing season. However, animal tissues reflect H incorporated from food webs that integrate precipitation over a single year's growing season or portions thereof. Inter-annual variation in precipitation and other climatic variables may lead to deviations from predictions derived from long-term mean precipitation isotopic values and could therefore lead to assignment errors for specific years and locations that are atypical.2. We examined whether using biologically relevant short-term δ2Hp isoscapes can improve estimates of geographic origin in comparison with long-term isoscapes. Using δ2H data from known-origin tissues of two migratory organisms in North America and Europe, we compared the accuracy, precision, and similarity of assigned origins using both short- and long-term δ2Hp isoscapes.3. Relative to long-term δ2Hp isoscapes, using short-term isoscapes for assignment often resulted in dissimilar regions of likely origin but did not significantly improve accuracy or precision. This was likely due to reduced spatial coverage in the data used to generate the short-term δ2Hp isoscapes.4. We suggest that continued efforts to collect precipitation isotope data with a large spatiotemporal range will benefit future research on incorporating temporal variation in the amount and isotopic composition of precipitation into geospatial assignment models.This article is protected by copyright. All rights reserved.
    Methods in Ecology and Evolution 09/2014; 5(9):891-900. DOI:10.1111/2041-210X.12229 · 5.32 Impact Factor


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