Open AccessSpace‐time tradeoffs in the development of precipitation‐based isoscape models for determining migratory origin
Author(s) -
Zanden Hannah B.,
Wunder Michael B.,
Hobson Keith A.,
Wilgenburg Steven L.,
Wassenaar Leonard I.,
Welker Jeffrey M.,
Bowen Gabriel J.
Publication year - 2015
Publication title -
journal of avian biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.022
H-Index - 76
eISSN - 1600-048X
pISSN - 0908-8857
DOI - 10.1111/jav.00656
Subject(s) - precipitation , range (aeronautics) , isotope , stable isotope ratio , sampling (signal processing) , spatial ecology , spatial distribution , environmental science , biology , atmospheric sciences , ecology , physical geography , statistics , meteorology , computer science , mathematics , geology , physics , geography , materials science , filter (signal processing) , quantum mechanics , composite material , computer vision
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 ( δ 2 H p ) 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 δ 2 H p 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 δ 2 H p 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 δ 2 H p isoscapes may affect predictions of geographic origins.