Decisions about management of natural resources are increasingly being based on the analysis of complex databases that contain geographic and/or spatial information. These databases are usually complex, with longitudinal measurements on each experimental unit and with spatial correlation either between measures of a given unit and/or between measures from different units. Although there is a vast literature on spatial, longitudinal and other multivariate data modeling and analysis, the rapid development of tools such as Monte Carlo methods for integration and optimization have set the stage for the application of more advanced statistical modeling techniques in fields concerned with natural resource management. The primary objective of this workshop is to bring together scientists from various areas of statistics (spatial data analysis, longitudinal data analysis, Monte Carlo methods, sampling, multivariate modeling, Bayesian statistics, hierarchical modeling) and from other areas where statistical methods for the modeling and analysis of spatial or geographic data are required, with a focus on natural resource management problems. The workshop will be divided into three sub-themes
(i) Hydrology/climatology/meteorology
(ii) Resource selection functions
(iii) Spatial-temporal statistical modeling of zoonotic diseases