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The relationships between community structure and soil properties (pH, P, N, Ca, Mg, CaCO₃ and clay content) were examined in a swamp forest from the northern part of Turkey. Statistically significant correlations were found between the soil variables and three different associations (Fraxino excelsioris-Fraxinetum angustifoliae, Carpino orientalis-Pterocaryetum fraxinifoliae, Acero campestris-Alnetum glutinosae) according to CCA ordination. P, Mg, Ca and clay content of soil were found as four significant variables for species composition in the studied forest.
Data collected from 85 sample plots in Yazili Canyon Nature Park (deep, limestone valley; length - 6 km, area – 600 ha, height – 100–400 m) located in Mediterranean region (Turkey) yielded 24 endemic vascular plants. The endemic plant diversity and all vascular plant diversity indices were calculated for each sample plot using Simpson index. Regression analysis was performed between environmental factors, plant diversity and canopy closure. Endemic plant diversity showed a positive correlation with vascular plant diversity, and a negative correlation with slope position and altitude. A significant quadric relationship was observed between the endemic plant diversity and aspect variable. RDA (redundancy analysis) and CCA (canonical correspondence analysis) based on linear regressions were applied to determine the environmental factors affecting the distribution of endemic species, and the best model based on total variance explained was selected. According to RDA based on linear regression, habitat selection of endemics is strongly correlated with aspect, slope position and altitude. Lower altitude zone (300–500 m), the north aspect and lower slope including valley bottom of Yazili canyon were observed to be the most suitable areas for endemics.
Distinction of the geographic areas intended for hierarchical sequence of vegetation classes involves the hierarchical classification of ecosystems. In this context, it is essential to determine the effective environmental characteristics at each hierarchical level of vegetation distinction. The study was carried out in order to classify and hierarchical mapping the Buldan forest district (area 190,000 km², altitude 400–1400 m a.s.l. covered in 40% with Mediterranean pine and oak forest, in 60% – by arable and pasture land). 56 sample plots (20 m × 20 m) were taken. At each sample plot, environmental characteristics (56 variables) and vascular plant species (108 species in total) were recorded. The relationships between environmental variables and the distribution of plants (presence/absence) were investigated by two hierarchical approaches for both of floristic data matrix and environment matrix by using cluster analysis, stepwise discriminate analysis and chi square test. Interspecific correlation analysis was also applied to determine the indicator species at each level of divisions. Two subdistricts were distinguised: Ortakcı-Cagir subdistrict (characteristic species association with Pinus brutia, Pistacia terebinthus, Nerium oleander, Ficus carica, Olea europea) and Suleymanli subdistrict (species association with Pinus nigra, Cistus laurifolius, Prunus divarcata and Rosa canina). Two sections in Suleymanli subdistrict were distinguished: Kocaalan section with characteristic association of Pinus nigra, Cistus laurifolius, Drypteris pallida and Ericek section – characterized with an association of Creategus monogina, Astragalus sp. and Pistacia terebintus. The altitude was the fundamental variable affecting on site classification at the level of subdistrict. Longitude was the most important variable affecting on discrimination of the sections of Suleymanli subdistrict. This local study offers a model including statistical processes which can be applied to the other forest areas for large scale classification of vegetation and environmental relations. Application of this model based on hierarchical classification of ecosystem units is also important for estimation of the changes of natural vegetation in ecosystems in the future due to global climatic change.
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