Author
John T. Curtis
Bio: John T. Curtis is an academic researcher from University of Wisconsin-Madison. The author has contributed to research in topics: Vegetation (pathology) & Plant community. The author has an hindex of 26, co-authored 52 publications receiving 18439 citations.
Papers published on a yearly basis
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TL;DR: It is shown that nature of unit variation is a naajor problenl in systematies, and that whether this variation is diserete, continuous, or in some other form, there is a need for appliGation of (uantitative and statistical methods.
Abstract: INTRODUCTION A renewed interest in objeetive and quantitative approaehes to the elassifieation of plant communities has led, within the past decade, to an extensive exalllination of systematic theory and technique. This examination, ineluding the work of Sorenson (1948), Motyka et al. (1950), Curtis & McIntosh (1951), Brown & Curtis (1952), Ramensky (1952), Whittaker (1954, 1956), Goodall (1953a, 1954b)? deVries (1953), Guinoehet (1954, 1955), Webb (1954), Eughes (1954) and Poore (1956) has acconlpanied theoretie studies in taxonomy [Fisher (1936), Womble (1951), Clifford & Binet (1954), Gregg (1954)] and in statisties (Isaaeson 1954). It is a Gonclusion of many of these studies that nature of unit variation is a naajor problenl in systematies, and that whether this variation is diserete, continuous, or in some other form, there is a need for appliGation of (uantitative and statistical methods. In eeologic elassifieation, an inereased use of ordinate systellls, sr hiGh has been stimulated by the developnlent of more effieient sampling teehniques and the collection of stand data on a large seale, has prompted the proposal of the term \"ordination\" ( Goodall 1953b ) . Goodall (1954a) has defined ordination as \"an arrangenlent of units in a unior multi-dinlensional order\" as synonylllous with \"Ordnung,\" (Ramensky
9,549 citations
2,110 citations
TL;DR: Whitford as discussed by the authors deals with upland hardwood forests of the p)rairie-forest border region of Wisconsin and their interrelations with each other and with certain physical factors of the environment.
Abstract: It has been said that the desirable order of ecological research in a given region is first, the study of communities, second, the study of the individual species, and last, the study of the habitat (Yapp 1922). Sociological investigations of constituent species and their numerical relations should precede autecological studies if the latter are to have maximum meaning. This sequence should lead to a greater efficiency in research, in that an initial knowledge of any natural groupings of species may enable the autecology of the groups to be studied simultaneously, with a resultant saving in time and travel expenses. The grossly inadequate state of autecological knowledge of even our most common species indicates that the current haphazard method of attack is faulty; if aggregations of species occur together under similar environmental conditions in nature, they could be studied in a systematic program. A long-term investigation of the communities of Wisconsin has been underway since 1946 with a view to determining the existence and the floristic nature of such aggregations (Curtis and Greene 1949). The present paper deals with the upland hardwood forests of the p)rairie-forest border region of the state and their interrelations with each other and with certain physical factors of the environment. Deep appreciation is expresse(l to Professor P. B. Whitford, hlio
1,410 citations
1,126 citations
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TL;DR: Which elements of this often-quoted strategy for graphical representation of multivariate (multi-species) abundance data have proved most useful in practical assessment of community change resulting from pollution impact are identified.
Abstract: In the early 1980s, a strategy for graphical representation of multivariate (multi-species) abundance data was introduced into marine ecology by, among others, Field, et al. (1982). A decade on, it is instructive to: (i) identify which elements of this often-quoted strategy have proved most useful in practical assessment of community change resulting from pollution impact; and (ii) ask to what extent evolution of techniques in the intervening years has added self-consistency and comprehensiveness to the approach. The pivotal concept has proved to be that of a biologically-relevant definition of similarity of two samples, and its utilization mainly in simple rank form, for example ‘sample A is more similar to sample B than it is to sample C’. Statistical assumptions about the data are thus minimized and the resulting non-parametric techniques will be of very general applicability. From such a starting point, a unified framework needs to encompass: (i) the display of community patterns through clustering and ordination of samples; (ii) identification of species principally responsible for determining sample groupings; (iii) statistical tests for differences in space and time (multivariate analogues of analysis of variance, based on rank similarities); and (iv) the linking of community differences to patterns in the physical and chemical environment (the latter also dictated by rank similarities between samples). Techniques are described that bring such a framework into place, and areas in which problems remain are identified. Accumulated practical experience with these methods is discussed, in particular applications to marine benthos, and it is concluded that they have much to offer practitioners of environmental impact studies on communities.
12,446 citations
TL;DR: In this article, a non-parametric method for multivariate analysis of variance, based on sums of squared distances, is proposed. But it is not suitable for most ecological multivariate data sets.
Abstract: Hypothesis-testing methods for multivariate data are needed to make rigorous probability statements about the effects of factors and their interactions in experiments. Analysis of variance is particularly powerful for the analysis of univariate data. The traditional multivariate analogues, however, are too stringent in their assumptions for most ecological multivariate data sets. Non-parametric methods, based on permutation tests, are preferable. This paper describes a new non-parametric method for multivariate analysis of variance, after McArdle and Anderson (in press). It is given here, with several applications in ecology, to provide an alternative and perhaps more intuitive formulation for ANOVA (based on sums of squared distances) to complement the description pro- vided by McArdle and Anderson (in press) for the analysis of any linear model. It is an improvement on previous non-parametric methods because it allows a direct additive partitioning of variation for complex models. It does this while maintaining the flexibility and lack of formal assumptions of other non-parametric methods. The test- statistic is a multivariate analogue to Fisher's F-ratio and is calculated directly from any symmetric distance or dissimilarity matrix. P-values are then obtained using permutations. Some examples of the method are given for tests involving several factors, including factorial and hierarchical (nested) designs and tests of interactions.
12,328 citations
Book•
30 Sep 1988
TL;DR: In this paper, the authors define definitions of diversity and apply them to the problem of measuring species diversity, choosing an index and interpreting diversity measures, and applying them to structural and structural diversity.
Abstract: Definitions of diversity. Measuring species diversity. Choosing an index and interpreting diversity measures. Sampling problems. Structural diversity. Applications of diversity measures. Summary.
10,957 citations
TL;DR: It is shown that nature of unit variation is a naajor problenl in systematies, and that whether this variation is diserete, continuous, or in some other form, there is a need for appliGation of (uantitative and statistical methods.
Abstract: INTRODUCTION A renewed interest in objeetive and quantitative approaehes to the elassifieation of plant communities has led, within the past decade, to an extensive exalllination of systematic theory and technique. This examination, ineluding the work of Sorenson (1948), Motyka et al. (1950), Curtis & McIntosh (1951), Brown & Curtis (1952), Ramensky (1952), Whittaker (1954, 1956), Goodall (1953a, 1954b)? deVries (1953), Guinoehet (1954, 1955), Webb (1954), Eughes (1954) and Poore (1956) has acconlpanied theoretie studies in taxonomy [Fisher (1936), Womble (1951), Clifford & Binet (1954), Gregg (1954)] and in statisties (Isaaeson 1954). It is a Gonclusion of many of these studies that nature of unit variation is a naajor problenl in systematies, and that whether this variation is diserete, continuous, or in some other form, there is a need for appliGation of (uantitative and statistical methods. In eeologic elassifieation, an inereased use of ordinate systellls, sr hiGh has been stimulated by the developnlent of more effieient sampling teehniques and the collection of stand data on a large seale, has prompted the proposal of the term \"ordination\" ( Goodall 1953b ) . Goodall (1954a) has defined ordination as \"an arrangenlent of units in a unior multi-dinlensional order\" as synonylllous with \"Ordnung,\" (Ramensky
9,549 citations
4,445 citations