Phytoclimatic Stages and Vegetation in Baden - Württemberg and Emilia - Romagna (original) (raw)

A phytoclimatic map of Europe

Cybergeo: European Journal of Geography

A high resolution, quantitative phytoclimatic map of Europe (PME) is presented. Ecological studies and landscape planning need quantitative and reproducible tools to assess the environment and to define land based ecological units characterized by spatial and temporal boundaries. At small scales, Phytoclimatic maps seem appropriate to fulfill such requisites because climate determines broad ecosystem type and distribution. PME is based on Defaut’s system of phytoclimatic stages (DSPS). DSPS relies on a combination of mean annual temperature, mean temperature of the warmest month, thermal continentality and aridity/humidity index Qn2. Boundaries of phytoclimatic stages are defined by zonal phytosociological syntaxa. PME was developed by GIS processing, by kriging interpolation of phytoclimatic temperature classes, aridity/moisture and thermal continentality of 1113 climatological stations. PME shows fifty different phytoclimatic stages. Distribution and coverage of such stages and their main plant formations are described and discussed. PME was compared to the Map of the Natural Vegetation of Europe (MNVE) by Kappa analysis. Good agreement was found between PME and MNVE, but as expected, PME and MNVE do not match perfectly. Major circumstances that could lead to discordance between the two maps are discussed. In conclusion, it is felt that PME, thanks also to its reliability and relative simplicity could be a useful and robust tool in ecological analysis and environment assessment, as well as in climate change studies, and for educational purposes.

Using woody genera for phytogeographic regionalization at a medium scale: A case study of Italy

Botany, 2016

We present a phytogeographic regionalization based on native woody flora, identifying the most useful taxonomic level, geographic variables, and orographic pattern, selecting Italy as a case study. We generated seven distance matrices among the 20 administrative regions, and using Pearson’s correlation coefficients and PCA, we verified whether distances between regions were invariant across the different sampling strategies. Once this invariance was established, we focused on genera representation. We defined two orographic indices and performed Kruskal–Wish multidimensional scaling and K-means clustering to assess Italy’s phytogeographic regionalization. A major north–south and a minor east–west gradient described the relationships between regions. Floristic diversity was strongly correlated with the region’s orography, with hills being the most important orographic feature that increased plant diversity; the effect of the orographic patterns was independent from the geographic cli...

Correlations among biodiversity, biomass and other plant community parameters using the phytosociological approach: A case study from the south-eastern Alps

Plant Biosystems, 2011

The present study deals with the grassland complex of communities which may be found on the limestones in the south-eastern Alps; these communities show in fact a particular interest for their high biodiversity degree and for their importance for the traditional land-use economy of the south-European mountain regions. Phytosociological relevés corresponding to well-defined plant associations have been used in order to get information on the relationships among plant species diversity, biomass, chorotypes, pollination types, functional strategies and soil characteristics. The analysis was carried out both along an altitudinal and a soil evolution gradient. The analysis of the correlations among the variables and the application of the principal component analysis shows a positive correlation between soil parameters and biomass, eurichory, anemogamy and C- and R-strategies; on the contrary, a negative correlation among stenochory, entomogamy and S-strategy with the soil evolution seems to be present. This article shows how the phytosociological approach can be used to get information and knowledge on the correlations between several variables useful to understand the complex nature of the plant communities in order to support management plans.