2 resultados para PLANT-SPECIES RICHNESS

em Corvinus Research Archive - The institutional repository for the Corvinus University of Budapest


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Examined area can be found at Balaton Uplands National Park (Hungary). 5 sample areas were examined in Badacsonytördemic: 1: 32 hectare under-grazed pasture, 2: 38 hectare overgrazed pasture, 3: 34 hectare hayfield, 4: trampled area, 5: beaten track. Livestock population was 118 in the monitored pastures. Sampling was executed along five 52m long circular transects, within 5cm × 5cm interlocking quadrates. Based on the data we can state that the curve of the drinking area was the highest of speciesarea examinations however weed appeared because of degradation which provided more species. According to species-area examinations overgrazed areas were richer in species then other examined areas. Based on diversity data drinking area considered degraded, while meadow and overgrazed areas was considered as proper state. Diversity of meadow was larger, but dominance of economically useful species was smaller. The amount of less valuable species – Carex hirta – increased.

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The article deals with the changing visual value of deciduous species. Due to climate change, the climatic patterns found on the plants’ growing area may change. Therefore, foliage of deciduous trees changes itscolor in the fall season witha different timing and intensity. This shift can modify the functional, ornamental and ecological value of these plants in the fall season, which is of special interest in the context of landscape design. However, this effect of climate change hasn’t been examined in terms of landscape architecture yet.In the article we are looking for deciduous species that can be appropriate subjectsforresearch, we are giving suggestions for choosing the right location for a future research and proposing available resources of satellite images, that can provide the basis for evaluation of leaf coloring. We also review already existing methods for calculating the degree of fall leaf coloring.We propose a novel method of satellite image processing to evaluate the coloring of a stand. Leaf Coloring Index (LCI) shows the leaf color’s relation to the color realms. LCI is appropriate for setting up a phenological model based onclimate data in a future research. Based on future climate models, the change of the examined stand’s visual value can be predicted. The results might affect the future use of plant species in landscape architecture.