Variation in Stable Hydrogen Isotope Values in a Wetland-Associated Songbird

Reese, Jessica; Tonra, Christopher M.; Viverette, Catherine; Marra, Peter P.; Bulluck, Lesley P.

doi:10.1675/063.041.0304

Cited by 4 publications

(2 citation statements)

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“…A key premise underpinning the utilization of isotope-based methods to infer origin and migration is that tissue grown at the same site are isotopically similar. However, isotopic data from known-origin samples commonly show high levels of variation even among conspecific individuals living at a common site (e.g., Kelly et al, 2002;Meehan et al, 2003;Smith and Dufty, 2005;Wunder et al, 2005;Rocque et al, 2006;Langin et al, 2007;Gow et al, 2012;Haché et al, 2012;van Dijk et al, 2014;Reese et al, 2018). Such variability can often be quantified and incorporated in geographic assignment tests (Hobson et al, 2012(Hobson et al, , 2014 but may limit the utility of such tests.…”

Section: Introductionmentioning

confidence: 99%

“…Although we have a solid understanding of the processes controlling broad-scale isotope patterns (reviewed by Bowen, 2010), a more fundamental understanding of the underlying mechanisms of small-scale isotope variance is needed to improve estimates of such variance and assess the potential utility of isotope-based methods for specific groups or environments. Several studies have investigated the causes of within-site amongindividual isotopic variance through exploratory approaches such as correlation analysis and model selection (e.g., Clegg et al, 2003;Meehan et al, 2003;Smith and Dufty, 2005;Langin et al, 2007;Reese et al, 2018; see also Hobson et al, 2012;Nordell et al, 2016). Relationships between feather δ 2 H values and age have been observed for several taxa (e.g., Meehan et al, 2003;Smith and Dufty, 2005;Langin et al, 2007;Haché et al, 2012;Studds et al, 2012;Gomez et al, 2019) and attributed to age-related differences in diet, access to water, metabolism (Meehan et al, 2003;Langin et al, 2007;Storm-Suke et al, 2012), and/or evaporative water loss (Wolf and Martinez del Rio, 2000;Meehan et al, 2003, McKechnie et al, 2004Smith and Dufty, 2005; but see Kirkley and Gessaman, 1990;Marder et al, 2003).…”

Section: Introductionmentioning

confidence: 99%

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Combining Models of Environment, Behavior, and Physiology to Predict Tissue Hydrogen and Oxygen Isotope Variance Among Individual Terrestrial Animals

et al. 2020

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Variations in stable hydrogen and oxygen isotope ratios in terrestrial animal tissues are used to reconstruct origin and movement. An underlying assumption of these applications is that tissues grown at the same site share a similar isotopic signal, representative of the location of their origin. However, large variations in tissue isotopic compositions often exist even among conspecific individuals within local populations, which complicates origin and migration inferences. Field-data and correlation analyses have provided hints about the underlying mechanisms of within-site among-individual isotopic variance, but a theory explaining the causes and magnitude of such variance has not been established. Here we develop a mechanistic modeling framework that provides explicit predictions of the magnitude, patterns, and drivers of isotopic variation among individuals living in a common but environmentally heterogeneous habitat. The model toolbox includes isoscape models of environmental isotopic variability, an agent-based model of behavior and movement, and a physiology-biochemistry model of isotopic incorporation into tissues. We compare model predictions against observed variation in hatch-year individuals of the songbird Spotted Towhee (Pipilo maculatus) in Red Butte Canyon, Utah, and evaluate the ability of the model to reproduce this variation under different sets of assumptions. Only models that account for environmental isotopic variability predict a similar magnitude of isotopic variation as observed. Within the modeling framework, behavioral rules and properties govern how animals nesting in different locations acquire resources from different habitats, and birds nesting in or near riparian habitat preferentially access isotopically lighter resources than those associated with the meadow and slope habitats, which results in more negative body water and tissue isotope values. Riparian nesters also have faster body water turnover and acquire more water from drinking (vs. from food), which exerts a secondary influence on their isotope ratios. Thus, the model predicts that local among-individual isotopic variance is linked first to isotopic heterogeneity in the local habitat, and second to how animals sample this habitat during foraging. Model predictions provide insight into the fundamental mechanisms of small-scale isotopic variance and can be used to predict the utility of isotope-based methods for specific groups or environments in ecological and forensic research.

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