title: Ecological boundary detection using Bayesian areal wombling.
abstract: The study of ecological boundaries and their dynamics is of fundamental importance to much of ecology, biogeography, and evolution. Over the past two decades, boundary analysis (of which wombling is a subfield) has received considerable research attention, resulting in multiple approaches for the quantification of ecological boundaries. Nonetheless, few methods have been developed that can simultaneously (1) analyze spatially homogenized data sets (i.e., areal data in the form of polygons rather than point-reference data); (2) account for spatial structure in these data and uncertainty associated with them; and (3) objectively assign probabilities to boundaries once detected. Here we describe the application of a Bayesian hierarchical framework for boundary detection developed in public health, which addresses these issues but which has seen limited application in ecology. As examples, we analyze simulated spread data and the historic pattern of spread of an invasive species, the hemlock woolly adelgid (Adelges tsugae), using county-level summaries of the year of first reported infestation and several covariates potentially important to influencing the observed spread dynamics. Bayesian areal wombling is a promising approach for analyzing ecological boundaries and dynamics related to changes in the distributions of native and invasive species.
authors.affiliation: University of Maryland Center for Environmental Science, Appalachian Lab, Frostburg, Maryland 21532, USA. mfitzpatrick@umces.edu
authors.forename: Matthew C
authors.initials: MC
authors.lastname: Fitzpatrick
authors.forename: Evan L
authors.initials: EL
authors.lastname: Preisser
authors.forename: Adam
authors.initials: A
authors.lastname: Porter
authors.forename: Joseph
authors.initials: J
authors.lastname: Elkinton
authors.forename: Lance A
authors.initials: LA
authors.lastname: Waller
authors.forename: Bradley P
authors.initials: BP
authors.lastname: Carlin
authors.forename: Aaron M
authors.initials: AM
authors.lastname: Ellison
mesh_terms: D000818:Animals; D001042:Aphids / Q000502:physiology*; D001499:Bayes Theorem; D003710:Demography; D017753:Ecosystem; D008954:Models, Biological; D014481:United States