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Space‐time tradeoffs in the development of precipitation‐based isoscape models for determining migratory origin
Authors:Hannah B. Vander Zanden  Michael B. Wunder  Keith A. Hobson  Steven L. Van Wilgenburg  Leonard I. Wassenaar  Jeffrey M. Welker  Gabriel J. Bowen
Affiliation:1. Dept of Geology and Geophysics, Univ. of Utah, Salt Lake City, USA;2. Dept of Integrative Biology, Campus Box 171, PO Box 1763364, Univ. of Colorado Denver, Denver, USA;3. Environment Canada, Saskatoon, Saskatchewan, Canada;4. Environment Canada, Saskatoon, Canada;5. International Atomic Energy Agency, Vienna International Centre, Vienna, Austria;6. Dept of Biological Sciences, Univ. of Alaska Anchorage, CPISB 101 Anchorage, USA
Abstract:Precipitation stable isotope patterns over continental scales provide a fundamental tool for tracking origins of migratory species. Hydrogen isotopes from rain and environmental waters are assimilated into animal tissues and may thereby reveal the location where tissues were synthesized. Predictive isotopic maps (or isoscapes) of stable hydrogen isotope values in precipitation (δ2Hp) are typically generated by time‐averaging observations from a global network of stations that have been sampled irregularly in space and time. We previously demonstrated that restricting the temporal range in δ2Hp isoscapes to biologically relevant time frames did not improve predictions of geographic origin for two migratory species in North America and Europe; rather, it decreased the accuracy of assignment. Here, we examined whether the reduction in assignment accuracy stemmed from a decrease in the number of sampling stations available to support isoscape development for shorter time periods. Multiple regression models were used to predict the hydrogen isotope composition in precipitation using isotopic measurements from each station along with a suite of independent variables. The reduction in the number of stations with δ2Hp measurements used to estimate isoscape model parameters did not alter the accuracy and precision of assignments consistently. We also examined accuracy across a range of reduced station numbers and found that mean accuracy was affected only at very low numbers of stations, indicating that the spatial isotopic patterns in precipitation that are useful for assignment applications can be characterized with data from relatively limited data stations. The number and spatial distribution of stations may have more influence when geostatistical models are used to generate isoscapes, as they incorporate spatial correlation in the dataset. The results can be used to guide future research in understanding how data availability and constraints in creating δ2Hp isoscapes may affect predictions of geographic origins.
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