The dehesas of the southwestern Iberian Peninsula are 'man-made' ecosystems characterised by a savannah-like physiognomy. The trees are viewed as an integrated part of the system, and as a result are planted, managed, and regularly pruned. Palynological and historical evidence of the manipulation of initial ecosystems by man to obtain a savannah-like ecosystem is presented. The ecological functions of the tree are detailed using results obtained at two complementary scales. At the local scale, strong soil structural differences and functional differences in water budget and patterns of water use are observed under and outside the tree canopy. Using the concept of ecosystem mimicry, the two coexistent components of dehesas can be compared to two distant stages of a secondary succession characterised by very different behaviours. At the regional scale, evidence of relationships between tree density and mean annual precipitation over more than 5000 km2 suggests that the structure of these man-made agroecosystems have adjusted over the long-term and correspond to an optimal functional equilibrium based on the hydrological equilibrium hypothesis. Finally, the future of dehesas in the face of contemporary exogenous threats of economic and global environmental origin is discussed.

The dehesa system of southern Spain and Portugal as a natural ecosystem mimic

Beaucoup de recherche en science du sol utilise les statistiques pour confirmer les impressions et interpretations dans les champs et en laboratoire. De nombreux scientifiques manquent de formation en methodes statistiques, et en consequence appliquent les techniques les plus elementaires dans un contexte errone et sans comprehension. Cet article se concentre sur les abus et les malentendus les plus courants et indique l'utilisation correcte. Il differencie la variance et l'ecart type pour mesurer la dispersion de l'erreur standard qui indique la confiance que l'on peut avoir dans les moyennes. Il souligne l'importance de presenter les moyennes et les differences entre elles par opposition a la significance statistique, qui est au mieux d'un interet secondaire. Il incite les lecteurs a examiner leurs donnees de pres et a les explorer avant de decider d'effectuer toute transformation en vue d'analyses plus formelles, et il met en evidence ce que l'on peut achever en utilisant des logarithmes des variables individuelles et des composantes principales des donnees multivariables.

Statistics to support soil research and their presentation

The spatial distributions of selected soil properties in two adjacent sites in southwest Michigan were examined to evaluate the potential effects of chronic disturbance on resource heterogeneity. One site was a cultivated field that had been cleared, plowed, and cropped annually for decades prior to sampling while the other, uncultivated field was cleared of original forest in 1960 after which it was mown annually but never plowed or cropped. We took replicate samples from a 330-point unaligned grid across the sites for soil pH, gravimetric moisture, inorganic phosphorus, total carbon, and net nitrification and nitrogen mineralization potentials. Soils in the cultivated site contained less than half as much carbon as in the uncultivated site, but had higher levels of inorganic phosphorus and moisture, and higher soil pH. Potential net nitrogen mineralization and nitrification rates did not differ between sites. Geostatistical analysis showed that almost all properties examined were strongly autocorelated within each site; structural variance as a proportion of sample variance ranged from 30–95% for all properties, and for any given property differed little between sites. The distance over which this dependence was expressed, however, was for all properties but pH substantially less in the uncultivated site (7–26 m) as compared to the tilled site (48–108m), especially for total C and net nitrification and N mineralization. These results suggest that the spatial pattern and scale of soil variability can differ markedly among edaphically identical sites and that these differences can be related to disturbance history.

The spatial variability of soil resources following long-term disturbance.

The concept of spatial scale is fundamental to geography, as are the problems of integrating data obtained at different scales. The availability of GIS has provided an appropriate environment to re-scale data prior to subsequent integration, but few tools with which to implement the re-scaling. This sparsity of appropriate tools arises primarily because the nature of the spatial variation of interest is often poorly understood and, specifically, the patterns of spatial dependence and error are unknown. Spatial dependence can be represented and modelled using geostatistical approaches providing a basis for the subsequent re-scaling of spatial data (e.g., via spatial interpolation). Geostatistical techniques can also be used to model the effects of re-scaling data through the geostatistical operation of regularization. Regularization provides a means by which to re-scale the statistics and functions that describe the data rather than the data themselves. These topics are reviewed in this paper and the importance of the spatial scale problems that remain is emphasized.

Spatial Scale Problems and Geostatistical Solutions: A Review

Establishing an air pollution monitoring network for intra-urban population exposure assessment: A location-allocation approach

Keywords: Geostatistique ; statistique ; amenagement Reference Record created on 2005-06-20, modified on 2016-08-08

Jonathan Cohen

Papers

Statistical Methods in Soil and Land Resource Survey