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dc.contributor.authorMagozzi, Sarah
dc.contributor.authorVander Zanden, Hannah B.
dc.contributor.authorWunder, Michael B.
dc.contributor.authorTrueman, Clive N.
dc.contributor.authorPinney, Kailee
dc.contributor.authorPeers, Dori
dc.contributor.authorDennison, Philip E.
dc.contributor.authorHorns, Joshua J.
dc.contributor.authorŞekercioğlu, Çağan H.
dc.contributor.authorBowen, Gabriel J.
dc.date.accessioned2020-12-25T05:17:09Z
dc.date.available2020-12-25T05:17:09Z
dc.date.issued2020-12-11
dc.date.submitted2020-02-18
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/315610
dc.description.abstractVariations 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.
dc.languageen
dc.publisherFrontiers Media S.A.
dc.rightsAttribution 4.0 International (CC BY 4.0)en
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en
dc.subjectEcology and Evolution
dc.subjectagent-based
dc.subjectphysiology
dc.subjectisoscape
dc.subjectmodels
dc.subjectmechanistic
dc.subjectisotopic variation
dc.subjecthydrogen
dc.subjectoxygen
dc.titleCombining Models of Environment, Behavior, and Physiology to Predict Tissue Hydrogen and Oxygen Isotope Variance Among Individual Terrestrial Animals
dc.typeArticle
dc.date.updated2020-12-25T05:17:08Z
prism.publicationNameFrontiers in Ecology and Evolution
prism.volume8
dc.identifier.doi10.17863/CAM.62716
dcterms.dateAccepted2020-11-18
rioxxterms.versionofrecord10.3389/fevo.2020.536109
rioxxterms.versionVoR
rioxxterms.licenseref.urihttp://creativecommons.org/licenses/by/4.0/
dc.identifier.eissn2296-701X


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Attribution 4.0 International (CC BY 4.0)
Except where otherwise noted, this item's licence is described as Attribution 4.0 International (CC BY 4.0)