%0 Journal Article
%A Hulme-Beaman, A
%A Rudzinski, A
%A Cooper, JEJ
%A Lachlan, RF
%A Dobney, K
%A Thomas, MG
%D 2020
%F discovery:10108044
%J Methods in Ecology and Evolution
%K Biogeography, identification, morphology, phylogeography, provenancing, spatial, mapping, trait, mapping
%T GEOORIGINS: A new method and r package for trait mapping and geographic provenancing of specimens without categorical constraints
%U https://discovery.ucl.ac.uk/id/eprint/10108044/
%X 1. Biologists often seek to geographically provenance organisms using their traits.  This is typically achieved by defining spatial groups using distinct patterns of trait  variation.  2. Here, we present a new spatial provenancing and trait boundary identification  methodology, based on correlations between geographic and trait distances that  require no a priori group assumptions. We apply this to three datasets where  spatial provenance is sought: morphological rat and vole dentition data (human  commensal translocation datasets); and birdsong data (cultural transmission dataset). We also present the results of cross-validation testing.  3. Spatial provenancing is possible with differing degrees of accuracy for each  dataset, with birdsong providing the most accurate geographic origin (identifying an average spatial region of 0.22 km2   as the area of origin with 99.9%  confidence).  4. Our method has a wide range of potential applications to diverse data types—  including phenotypic, genetic and cultural—to identify trait boundaries and  spatially provenance the origin of unknown or translocated specimens where  trait differences are geographically structured and correlated with spatial  separation.
%Z © 2020 The Authors. Methods in Ecology and Evolution published by John Wiley & Sons Ltd on behalf of British Ecological Society    This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.