The agrochemicals used on crops can reach watercourses, affecting water quality and biologic communities. The aim of this research was to study the effects of horticulture on the water quality and invertebrate assemblages of adjacent streams in Buenos Aires province, Argentina. Four streams draining horticultural basins were compared with another four considered less disturbed: two of the latter located in a Biosphere Reserve and the other two in extensive livestock-raising basins. Pesticides were detected in the horticulture-related streams, while nutrient concentrations were significantly higher than in the less-disturbed streams. The macroinvertebrate assemblages differed: the less-disturbed streams exhibited a significantly higher taxa richness and density. Hyalella sp. and Simocephalus vetulus were dominant, whereas Entomobryoidea, Dugessidae, and Glossiphoniidae were dominant in the horticulture-associated streams. Ephemeroptera (Caenis and Baetidae) were well represented in the less-disturbed streams and rare or absent in the horticulture-adjacent streams. Multivariate analysis indicated that the horticulture-impacted sites contained high nutrient concentrations and tolerant taxa, while the less-disturbed sites corresponded to lower nutrient concentrations and sensitive taxa. We propose Hyalella sp. and S. vetulus as water-quality indicators in pampean streams and conclude that intensive agrochemical applications in horticulture increase nutrient and pesticide loads affecting the macroinvertebrate assemblages of adjacent streams.
The radar altimeter data sets are used to study several dynamical characteristic of the World's Oceans because the artificial satellites have a global coverage. One of the most important applications is related to the Mean Sea Level changes. The authors take into account the TOPEX/Poseidon data for the Mediterranean Sea and the Iberian Atlantic in order to compute the trend of the Mean Sea Level by means of two different procedures: the linear regression and fractal geometry. The first one leads to very well known results but the errors in the estimation are quite large and the second leads to more reliable results.
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