Open AccessA Bayesian model identifying locations at risk from human‐transported exotic pathogens
Author(s) -
McKelvey Steven C.,
Koch Frank H.,
Smith William D.,
Hawley Kelly R.
Publication year - 2021
Publication title -
natural resource modeling
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.28
H-Index - 32
eISSN - 1939-7445
pISSN - 0890-8575
DOI - 10.1111/nrm.12307
Subject(s) - biological dispersal , sensitivity (control systems) , bayesian probability , sample (material) , bayesian inference , bayes' theorem , computer science , ecology , environmental science , biology , artificial intelligence , engineering , physics , population , demography , electronic engineering , sociology , thermodynamics
A two‐phase Bayesian model is presented for updating risk assessments for locations susceptible to infection by exotic pathogens. Human transportation from previously infected regions to uninfected regions is the main dispersal mechanism. Information embedded in patterns within the transportation flow are exploited in the update process. We explore the sensitivity of the model's outputs to changes in inputs. A sample application of the model to sudden oak death, using fictitious infection data, is performed.