Sampling of a population is frequently required to understand trends and patterns in natural resource management because financial and time constraints preclude a complete census. A rigorous probability-based survey design specifies where to sample so that inferences from the sample apply to the entire population. Probability survey designs should be used in natural resource and environmental management situations because they provide the mathematical foundation for statistical inference. Development of long-term monitoring designs demand survey designs that achieve statistical rigor and are efficient but remain flexible to inevitable logistical or practical constraints during field data collection. Here we describe an approach to probability-based survey design, called the Reversed Randomized Quadrant-Recursive Raster, based on the concept of spatially balanced sampling and implemented in a geographic information system. This provides environmental managers a practical tool to generate flexible and efficient survey designs for natural resource applications. Factors commonly used to modify sampling intensity, such as categories, gradients, or accessibility, can be readily incorporated into the spatially balanced sample design.

The term trend describes the continuing directional change in the value of an indicator, generally upward or generally downward. Many policy questions concern trend across a number of sites, such as lakes in a region, rather than trend at a single site. Power to detect regional trend seldom is discussed, and monitoring designs suitable for detecting such trends rarely are explored. Components of variance and temporal sampling designs play central roles in characterizing trend detection. We present relative numerical values of important components of variance, developed from the Surface Waters component of U.S. EPA's Environmental Monitoring and Assessment Program (EMAP) field data, and use them as a basis for further assumptions of values. We discuss power curves in general and present them in relation to temporal designs, years of field observation, components of variance, and the level of trend detected. Revisit designs give adequate power for moderate trend in 10-15 yr, even when revisits are less frequent than annually.

No abstract

No abstract

No abstract