The use of ellipses of equal concentration is suggested for the analysis of pattern in ordination scattergrams produced directly by environmental variables, or with axes obtained by numerical methods. The potentials of the method are illustrated by some examples using structural characteristics of mixed forest type of NE Italy and environmental variables estimated by ecological indicator values.
A program in FORTRAN 77 for spatial pattern based on the methods of nearest-neighbor and autocorrelation is presented. It has been used with the option for autocorrelation to analyse the spatial pattern of 120 species and other variables as life-growth forms, chorological elements and classes of environmental variables, along transects from open grasslands to groups of trees (NR) in the Karst area near Trieste. The results proved that both the species and the other variables show significant pattern. Particularly a high degree of significance has been found for the variables of higher hierarchical meaning than species and especially for the classes of environmental variables. The number of entities with significant pattern increases in function of the length of the transect. The results prove that along the transect there is a composite ecologica] gradient which produces significant changes of vegetation pattern at different hierarchical levels, both structural and chorological.
The flowering of Rubio longifoliae-Quercetum rotundifoliae fraxinetosum orni Costa. Peris & Figuerola. The flowering of Rubio longifoliae-Quercetum rotundifoliae fraxinetosum orni Costa, Peris & Figuerola 1982 is studied during the dry year 1983 in the "carrascal" maquis-wood of the Barranco Real (Valencia, Spain). The formation is characterised by high frequencies of multiple flowerings - more of one flowering along the year. The "optimum" flowering - highest frequency in a taxon - is pertaining to the spring, while the "suboptimum" flowering - low frequencies in a taxon - is autumnal and it is related with the season whose pluviometric values are highest.