L. Orlóci - Böcker

There are many books and computer programs dealing look ahead rather than pondering the past. This is a with data analysis. It would be easy to count at least a manual of recent views that evolved in the study of hundred, yet few of these would show applications in vegetation. This book is intended to emphasize the new vegetation science. Today in the face of environmental acquisitions which we believe significantly affect the degradation caused by anthropogenic pressures on the future of vegetation analysis: biosphere there is added urgency to study vegetation 1. Vegetation is a 'fuzzy' system, it must be treated as processes and dynamics in order to understand their role such at the set level, where the idea ofconceptualized in regulating the water, oxygen and the carbon cycles, in patterns must drive the research design. relation to global warming and ozone layer depletion. It 2. Vegetation cannot be seen only in the perspective of a is well known that ecology was developed first in vegeta­ traditional taxonomy based on the species concept; tion studies (see Acot 1989) but after an active period character sets of ecological value must enter into marked by intensive phytoclimatic and synecological consideration and a hierarchical analysis of patterns studies, vegetation science entered in a rather dormant and processes should be the basis of comparisons. period. Other ecological disciplines such as animal popu­ 3.

Information analysis, a popular subject among vegetation ecologists not too many years ago, is revisited in this short monograph. The overview provided and the systematic presentation of ideas and algorithms should interest data analysts with backgrounds in this or other fields of natural science where the question of classifi- cation is addressed. The text gives the detailed descriptions and the listings of the computer programs. The authors were recipients of grant support from the Italian Consiglio Nazionale delle Ricerche "Gruppo Biologia Naturalistica" (E. Feoli) and the Canadian Na- tional Science and Engineering Research Council (L. Orl6ci) during completion of the project. The respective institutions of the University of Western Ontario and the University of Trieste provided facilities and computer time. Mrs. Stefani Tichbourne (London) typed the manuscript, Mr. Aulo Zampar (Trieste) gave computing assis- tance and Mr. Furio Poropat (Trieste) translated some programs. We are most grateful to them. E. Feoli M. Lagonegro L.

Information analysis, a popular subject among vegetation ecologists not too many years ago, is revisited in this short monograph. The overview provided and the systematic presentation of ideas and algorithms should interest data analysts with backgrounds in this or other fields of natural science where the question of classifi- cation is addressed. The text gives the detailed descriptions and the listings of the computer programs. The authors were recipients of grant support from the Italian Consiglio Nazionale delle Ricerche "Gruppo Biologia Naturalistica" (E. Feoli) and the Canadian Na- tional Science and Engineering Research Council (L. Orl6ci) during completion of the project. The respective institutions of the University of Western Ontario and the University of Trieste provided facilities and computer time. Mrs. Stefani Tichbourne (London) typed the manuscript, Mr. Aulo Zampar (Trieste) gave computing assis- tance and Mr. Furio Poropat (Trieste) translated some programs. We are most grateful to them. E. Feoli M. Lagonegro L.

(RANKIN) of equivocation information (1-:) and interaction information (M). The method is described in the present paper for I: and in a previous paper (Orloci, 1976) for M. The results presented in this paper suggest that for Species Rank order Information Percentage of total* species to be weighted according to their suitability to I· M I M r M characterize isolated groups of releves in a phytosociolo­ 5 7 54.15 2.31 17.97 0.82 gical table, the equivocation information may serve as a 9 5 49.86 23.19 16.55 8.22 3 3 9 47.79 0.56 15.86 0.20 suitable weight. The appropriate formulations are derived 6 4 8 36.18 1.18 12.01 0.42 4 5 3 24.36 59.34 8.09 21.03 and computed for some data from a salt marsh community. 8 6 4 24.25 39.04 8.05 13.84 10 7 I 21.96 71.17 7.29 25.23 7 8 2 18.67 69.01 6.20 24.46 9 10 18.40 6.11 10 6 5.64 16.31 1.87 5.78 References Total 301.00* 282.11 * 100.00 100.00 Feoli, E. 1973. An index for weighing characters in monothetic classifications. (Italian with English summary). Giorn. Bot. Ita!' 107: 263-268. Gower, J.e. 1967. A comparison of some methods of cluster is a monotone, increasing function of sample size if .. ).