Michael B. Wunder

A test of geographic assignment using isotope tracers in feathers of known origin

We used feathers of known origin collected from across the breeding range of a migratory shorebird to test the use of isotope tracers for assigning breeding origins. We analyzed δD, δ13C, and δ15N in feathers from 75 mountain plover (Charadrius montanus) chicks sampled in 2001 and from 119 chicks sampled in 2002. We estimated parameters for continuous-response inverse regression models and for discrete-response Bayesian probability models from data for each year independently. We evaluated model predictions with both the training data and by using the alternate year as an independent test dataset. Our results provide weak support for modeling latitude and isotope values as monotonic functions of one another, especially when data are pooled over known sources of variation such as sample year or location. We were unable to make even qualitative statements, such as north versus south, about the likely origin of birds using both δD and δ13C in inverse regression models; results were no better than random assignment. Probability models provided better results and a more natural framework for the problem. Correct assignment rates were highest when considering all three isotopes in the probability framework, but the use of even a single isotope was better than random assignment. The method appears relatively robust to temporal effects and is most sensitive to the isotope discrimination gradients over which samples are taken. We offer that the problem of using isotope tracers to infer geographic origin is best framed as one of assignment, rather than prediction.

IMPROVED ESTIMATES OF CERTAINTY IN STABLE-ISOTOPE-BASED METHODS FOR TRACKING MIGRATORY ANIMALS

The use of stable-hydrogen isotopes (deltaD) 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 deltaD values of precipitation, but these patterns are not estimated without error. In addition, deltaD 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 deltaD in precipitation and analytical error associated with the measurement of deltaD 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 deltaD or other stable isotopes to infer the geographic origin of individuals.

A method for investigating population declines of migratory birds using stable isotopes: origins of harvested lesser scaup in North America.

Background Elucidating geographic locations from where migratory birds are recruited into adult breeding populations is a fundamental but largely elusive goal in conservation biology. This is especially true for species that breed in remote northern areas where field-based demographic assessments are logistically challenging. Methodology/Findings Here we used hydrogen isotopes (δD) to determine natal origins of migrating hatch-year lesser scaup (Aythya affinis) harvested by hunters in the United States from all North American flyways during the hunting seasons of 1999–2000 (n = 412) and 2000–2001 (n = 455). We combined geospatial, observational, and analytical data sources, including known scaup breeding range, δD values of feathers from juveniles at natal sites, models of δD for growing-season precipitation, and scaup band-recovery data to generate probabilistic natal origin landscapes for individual scaup. We then used Monte Carlo integration to model assignment uncertainty from among individual δD variance estimates from birds of known molt origin and also from band-return data summarized at the flyway level. We compared the distribution of scaup natal origin with the distribution of breeding population counts obtained from systematic long-term surveys. Conclusions/Significance Our analysis revealed that the proportion of young scaup produced in the northern (above 60°N) versus the southern boreal and Prairie-Parkland region was inversely related to the proportions of breeding adults using these regions, suggesting that despite having a higher relative abundance of breeding adults, the northern boreal region was less productive for scaup recruitment into the harvest than more southern biomes. Our approach for evaluating population declines of migratory birds (particularly game birds) synthesizes all available distributional data and exploits the advantages of intrinsic isotopic markers that link individuals to geography.

Using Isoscapes to Model Probability Surfaces for Determining Geographic Origins

This chapter describes a modeling framework for using isoscapes to describe probable geographic origins of sampled material. The approach first inverts an isoscape model and then adds known or estimated components of variance to create a single continuous posterior probability density that describes the probability of any given location as the origin. The posterior density is defined analytically or by Monte Carlo methods, depending on the complexity of the variance structure. The model must be trained with material of known origin and can be used to determine spatially-explicit probability densities for geographic origin of individual samples. Individual densities can be used in aggregate to find spatial structure in the geographic origins for populations of samples. To illustrate the approach, I explore simulated data for a hypothetical example from wildlife forensics involving the determination of cross-seasonal connectivity in a migratory bird species.

Tracking multi-generational colonization of the breeding grounds by monarch butterflies in eastern North America.

Insect migration may involve movements over multiple breeding generations at continental scales, resulting in formidable challenges to their conservation and management. Using distribution models generated from citizen scientist occurrence data and stable-carbon and -hydrogen isotope measurements, we tracked multi-generational colonization of the breeding grounds of monarch butterflies (Danaus plexippus) in eastern North America. We found that monarch breeding occurrence was best modelled with geographical and climatic variables resulting in an annual breeding distribution of greater than 12 million km2 that encompassed 99% occurrence probability. Combining occurrence models with stable isotope measurements to estimate natal origin, we show that butterflies which overwintered in Mexico came from a wide breeding distribution, including southern portions of the range. There was a clear northward progression of monarchs over successive generations from May until August when reproductive butterflies began to change direction and moved south. Fifth-generation individuals breeding in Texas in the late summer/autumn tended to originate from northern breeding areas rather than regions further south. Although the Midwest was the most productive area during the breeding season, monarchs that re-colonized the Midwest were produced largely in Texas, suggesting that conserving breeding habitat in the Midwest alone is insufficient to ensure long-term persistence of the monarch butterfly population in eastern North America.

A Simple Protocol for Using a LDH-Based Cytotoxicity Assay to Assess the Effects of Death and Growth Inhibition at the Same Time

Analyzing the effects on cell growth inhibition and/or cell death has been an important component of biological research. The MTS assay and LDH-based cytotoxicity assays are two of the most commonly used methods for this purpose. However, data here showed that MTS cell proliferation assay could not distinguish the effects of cell death or cell growth inhibition. In addition, the original LDH-based cytotoxicity protocol grossly underestimated the proportion of dead cells in conditions with growth inhibition. To overcome the limitation, we present here a simple modified LDH-based cytotoxicity protocol by adding additional condition-specific controls. This modified protocol thus can provide more accurate measurement of killing effects in addition to the measurement of overall effects, especially in conditions with growth inhibition. In summary, we present here a simple, modified cytotoxicity assay, which can determine the overall effects, percentage of cell killing and growth inhibition in one 96-well based assay. This is a viable option for primary screening for many laboratories, and could be adapted for high throughput screening.

Geographic Variation of Strontium and Hydrogen Isotopes in Avian Tissue: Implications for Tracking Migration and Dispersal

Background Isotopes can provide unique solutions to fundamental problems related to the ecology and evolution of migration and dispersal because prior movements of individuals can theoretically be tracked from tissues collected from a single capture. However, there is still remarkably little information available about how and why isotopes vary in wild animal tissues, especially over large spatial scales. Methodology/Principal Findings Here, we describe variation in both stable-hydrogen (δDF) and strontium (87Sr/86SrF) isotopic compositions in the feathers of a migratory songbird, the Tree Swallow (Tachycineta bicolor), across 18 sampling sites in North America and then examine potential mechanisms driving this variation. We found that δDF was correlated with latitude of the sampling site, whereas 87Sr/86SrF was correlated with longitude. δDF was related to δD of meteoric waters where molting occurred and 87Sr/86SrF was influenced primarily by the geology in the area where feathers were grown. Using simulation models, we then assessed the utility of combining both markers to estimate the origin of individuals. Using 13 geographic regions, we found that the number of individuals correctly assigned to their site of origin increased from less than 40% using either δD or 87Sr/86Sr alone to 74% using both isotopes. Conclusions/Significance Our results suggest that these isotopes have the potential to provide predictable and complementary markers for estimating long-distance animal movements. Combining isotopes influenced by different global-scale processes may allow researchers to link the population dynamics of animals across large geographic ranges.

Novel statistical methods for integrating genetic and stable isotope data to infer individual-level migratory connectivity

Methods for determining patterns of migratory connectivity in animal ecology have historically been limited due to logistical challenges. Recent progress in studying migratory bird connectivity has been made using genetic and stable‐isotope markers to assign migratory individuals to their breeding grounds. Here, we present a novel Bayesian approach to jointly leverage genetic and isotopic markers and we test its utility on two migratory passerine bird species. Our approach represents a principled model‐based combination of genetic and isotope data from samples collected on the breeding grounds and is able to achieve levels of assignment accuracy that exceed those of either method alone. When applied at large scale the method can reveal specific migratory connectivity patterns. In Wilsons warblers (Wilsonia pusilla), we detect a subgroup of birds wintering in Baja that uniquely migrate preferentially from the coastal Pacific Northwest. Our approach is implemented in a way that is easily extended to accommodate additional sources of information (e.g. bi‐allelic markers, species distribution models, etc.) or adapted to other species or assignment problems.

Whitebark Pine Stand Condition, Tree Abundance, and Cone Production as Predictors of Visitation by Clark's Nutcracker

Background Accurately quantifying key interactions between species is important for developing effective recovery strategies for threatened and endangered species. Whitebark pine (Pinus albicaulis), a candidate species for listing under the Endangered Species Act, depends on Clarks nutcracker (Nucifraga columbiana) for seed dispersal. As whitebark pine succumbs to exotic disease and mountain pine beetles (Dendroctonus ponderosae), cone production declines, and nutcrackers visit stands less frequently, reducing the probability of seed dispersal. Methodology/Principal Findings We quantified whitebark pine forest structure, health metrics, and the frequency of nutcracker occurrence in national parks within the Northern and Central Rocky Mountains in 2008 and 2009. Forest health characteristics varied between the two regions, with the northern region in overall poorer health. Using these data, we show that a previously published model consistently under-predicts the proportion of survey hours resulting in nutcracker observations at all cone density levels. We present a new statistical model of the relationship between whitebark pine cone production and the probability of Clarks nutcracker occurrence based on combining data from this study and the previous study. Conclusions/Significance Our model clarified earlier findings and suggested a lower cone production threshold value for predicting likely visitation by nutcrackers: Although nutcrackers do visit whitebark pine stands with few cones, the probability of visitation increases with increased cone production. We use information theoretics to show that beta regression is a more appropriate statistical framework for modeling the relationship between cone density and proportion of survey time resulting in nutcracker observations. We illustrate how resource managers may apply this model in the process of prioritizing areas for whitebark pine restoration.

Determining geographic patterns of migration and dispersal using stable isotopes in keratins

Abstract Stable isotopes in metabolically inert tissues of migratory animals can be used to infer migratory and dispersal histories. The general approach for estimating geographic origins of migratory animals based on stable isotope values of their keratinous tissues is to develop or calibrate an assignment model based on tissues of known geographic origin. This paper reviews the general forms and evaluates the application of the 3 assignment approaches. Two of these approaches are considered as nominal assignment frameworks because they require prior declaration of named locations as the set of candidate origins. Individual samples can be sorted into the most likely location using a classification tree or a likelihood-based assignment test. The 3rd and more recent approach is considered a continuous assignment framework because it does not require a predetermined list of candidate locations. This approach depends on an underlying mechanistic geographic model of variation in isotope values. Such models can be developed directly from spatially intensive sampling of keratins or by calibrating a spatial model for isotopes in physical (water or soil) or biological (dietary species) resources. Productive approaches to increase spatial resolution of assignment models will use experiments designed to identify specific geographic-based, variance-generating mechanisms, especially if the contributing factors can be quantified for animals that are released back to the wild.