Abstract
Data from systematic sampling may be independent or autocorrelated. In the latter case geostatistical tools are used to identify the spatial patterns within the universe sampled. Special formulas have been derived by Russo & Bresler (1982) to estimate the variance of a value averaged over several transect samples. We applied these formulas to the green biomass of the dominant perennial steppe grass, Stipa tenacissima or alfa, in a 400 km2 region in North-West Algeria; thirty years ago, this region was considered one of the best sites for alfa. A two-level sampling design was implemented with stratification of the region and systematic sampling within each stratum; globally the study included fifteen transects, representing 713 1 m2 quadrats. Autocorrelation up to 500 meters was detected in five semi-variograms or correlograms, which were fitted to linear models with a sill. Biomass averaged only 165 (±55) kg ha-1. We discuss the processes that have lead to the rapid degradation of alfa steppes in northern Algeria and the variation in spatial patterns of alfa stands. Ignoring autocorrelation in systematic sampling leads to biased estimates of variances and standard errors.
Published Version
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