33 resultados para Spatial plant distribution


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Soil properties on the Cap de Creus Peninsula, NE Spain depend primarily on scarce agricultural practices and early abandonment. In the study area, 90% of which is mainly covered by Cistus shrubs, 8 environments representing variations in land use/land cover and soil properties at different depths were identified. In each environment variously vegetated areas were selected and sampled. The soils, collected at different depths, were classified as Lithic Xerorthents according to the United States Department of Agriculture system of soil classification (USDA-NRCS 1975). Differences in soil properties were largely found according to the evolution of the plant canopy and the land use history. To identify underlying patterns in soil properties related to environmental evolution, factor analysis was performed and factor scores were used to determine how the factor patterns varied between soil variables, soil depths and selected environments. The three-factor model always accounted for 80% of the total variation in the data at the different soil depths. Organic matter was the more relevant soil property at 0–2 cm depth, whereas active minerals (silt and clay) were found to be the most relevant soil parameters controlling soil dynamics at the other depths investigated. Results showed that vineyards and olive tree soils are poorly developed and present worse conditions for mineral and organic compounds. Analysis of factor scores allowed independent assessment of soils, depth and plant cover and demonstrated that soils present the best physico-chemical characteristics under Erica arborea and meadows. In contrast, soils under Cistus monspeliensis were less nutrient rich and less well structured

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This paper is about location decisions of Creative Industries and the role played by existent spatial distribution and agglomeration economies of these kinds of activities in order to analyse their location determinants. Our main statistical source is the REIC (Catalan Manufacturing Establishments Register), which has plant-level microdata on location of new plants. Using Count Data Models, our main results show that location determinants are quite similar between both industries and also both non-creative and creative firms are positively influenced by the specialisation level in Creative Industries of municipalities. Moreover, our results provide evidence that the unobserved ‘creative milieu’ has a limited impact on attracting firms. Keywords: creative industries, creative milieu, count data models, industrial location, agglomeration economies

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Chironomidae spatial distribution was investigated at 63 near-pristine sites in 22 catchments of the Iberian Mediterranean coast. We used partial redundancy analysis to study Chironomidae community responses to a number of environmental factors acting at several spatial scales. The percentage of variation explained by local factors (23.3%) was higher than that explained by geographical (8.5%) or regional factors(8%). Catchment area, longitude, pH, % siliceous rocks in the catchment, and altitude were the best predictors of Chironomidae assemblages. We used a k-means cluster analysis to classified sites into 3 major groups based on Chironomidae assemblages. These groups were explained mainly by longitudinal zonation and geographical position, and were defined as 1) siliceous headwater streams, 2) mid-altitude streams with small catchment areas, and 3) medium-sized calcareous streams. Distinct species assemblages with associated indicator taxa were established for each stream category using IndVal analysis. Species responses to previously identified key environmental variables were determined, and optima and tolerances were established by weighted average regression. Distinct ecological requirements were observed among genera and among species of the same genus. Some genera were restricted to headwater systems (e.g., Diamesa), whereas others (e.g., Eukiefferiella) had wider ecological preferences but with distinct distributions among congenerics. In the present period of climate change, optima and tolerances of species might be a useful tool to predict responses of different species to changes in significant environmental variables, such as temperature and hydrology.