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Reliability of differing densities of sample grids used for the monitoring of forest condition in Europe
Authors:Michael Köhl  John L Innes  Edgar Kaufmann
Institution:(1) Swiss Federal Institute for Forest, Snow and Landscape Research, Zürcherstrasse 111, CH-8903 Birmensdorf, Switzerland
Abstract:Concern about the possible deterioration of forest health led to the establishment in the 1980s of inventories of forest condition throughout Europe. International standardisation of the programmes was sought and a number of recommendations were made concerning sampling and assessment procedures. One of the most important rulings was that the assessment should be made on a systematic grid, the minimum density of which was 16×16 km. However, many countries adopted denser sampling grids, with 4×4 km being used in several countries and 1×1 km being used in the Netherlands. With five or more years of monitoring completed, there is a growing belief that a rapid and irreversible decline in forest health is not occurring. Consequently, some countries/regions are seeking to reduce their annual investment in forest health monitoring.The precision of national/regional estimates of forest health can be directly related to the sample size. As the sample size decreases, so also does the precision of the estimates. This is illustrated using data collected in Switzerland in 1992 and using grid densities of 4×4 km, 8×8 km, 12×12 km and 16×16 km. The value of the data is dependent on the sample size and the degree to which it is broken down (by region or species). The loss of precision associated with most subdivisions at the 8×8 km grid level remains acceptable, but a sharp deterioration in the precision occurs at the 12×12 km and 16×16 km grid levels. This has considerable implications for the interpretation of the inventories from those countries using a 16×16 km grid. In Switzerland, a reduction from the current 4×4 km grid to an 8×8 km grid (i.e. 75% reduction in sample size) would have relatively little impact on the overall results from the annual inventories of forest health.
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