title: Using statistical power analysis as a tool when designing a monitoring program: experience from a large-scale Swedish landscape monitoring program.
abstract: The National Inventory of Landscapes in Sweden (NILS) is a large-scale, sample-based monitoring program that combines aerial photointerpretation with field inventory to follow landscape-scale biophysical conditions and changes. A statistical power analysis was conducted before the NILS program began in 2003 with the aim to determine an appropriate sampling effort and compare some design alternatives. The chosen sampling effort was then evaluated in a second power analysis conducted just before the first 5-year re-inventory rotation started. The latter power analysis revealed which magnitude of actual change might be detected within the future for different central monitoring variables. This article reports results from these power analyses and discusses our experiences in using power analysis as a tool for designing large-scale monitoring programs. The results showed that even quite small changes in the more common variables, such as land cover types and more common plant species, can be detected on the national scale. However, on the regional scale, or for less common variables, changes will be more difficult to detect. The power analyses have revealed the size level of changes that will be possible to detect. The results have also generated incentives for further improvements of NILS, e.g., input to the modification and revision of the variable content, flow and hierarchy, and incentives for launching other complementary monitoring programs connected to NILS. They have also created a basis for a better and more user-oriented communication of results from NILS to different stakeholders.
authors: Department of Forest Resource Management, Swedish University of Agricultural Sciences, 901 83 Umea, Sweden. Pernilla.Christensen@slu.se
authors: Pernilla
authors: P
authors: Christensen
authors: Anna
authors: A
authors: Hedström Ringvall
mesh_terms: D003627:Data Interpretation, Statistical; D004784:Environmental Monitoring / Q000379:methods*; D015233:Models, Statistical; D012107:Research Design; D013548:Sweden
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