Spatially Balanced Survey Designs for Large Scale Monitoring Programs

Don L. Stevens, Jr.

Statistics Department

Oregon State University

Corvallis, Oregon

Spatial pattern is a dominant feature of environmental response variables. The pattern is shaped by geographic, metrological, and anthropogenic stressors that all have pattern themselves. If the response and stressor patterns are well-understood, a sampling design to monitor a response can utilize that information to locate sample points at key sites. However, in a period of large-scale climate change, relationships will not be static, and a more robust design may be preferable. The Generalized Random Tessellation Stratified (GRTS) design was developed in the USEPA's Environmental Monitoring and Assessment Program in the 1990's. Spatially balanced designs, such as GRTS, ensure that spatial distribution of the sample points closely matches the spatial distribution of the domain. Thus, patterns in the response will be sampled in proportion to their extent in the domain. The GRTS design has features, such as dynamic sample adjustment and easy accommodation of variable probability, that make it well-suited for large-scale monitoring programs. This talk will give a brief description of GRTS, describe its functionality, and illustrate its application to large-scale monitoring programs in the U.S. and Australia.