Stuart H. Hurlbert

Bio: Stuart H. Hurlbert is an academic researcher from San Diego State University. The author has contributed to research in topics: Population & Pseudoreplication. The author has an hindex of 33, co-authored 82 publications receiving 16238 citations. Previous affiliations of Stuart H. Hurlbert include University of California, Riverside.

Pseudoreplication and the Design of Ecological Field Experiments

Abstract: Pseudoreplication is defined. as the use of inferential statistics to test for treatment effects with data from experiments where either treatments are not replicated (though samples may be) or replicates are not statistically independent. In ANOVA terminology, it is the testing for treatment effects with an error term inappropriate to the hypothesis being considered. Scrutiny of 176 experi- mental studies published between 1960 and the present revealed that pseudoreplication occurred in 27% of them, or 48% of all such studies that applied inferential statistics. The incidence of pseudo- replication is especially high in studies of marine benthos and small mammals. The critical features of controlled experimentation are reviewed. Nondemonic intrusion is defined as the impingement of chance events on an experiment in progress. As a safeguard against both it and preexisting gradients, interspersion of treatments is argued to be an obligatory feature of good design. Especially in small experiments, adequate interspersion can sometimes be assured only by dispensing with strict random- ization procedures. Comprehension of this conflict between interspersion and randomization is aided by distinguishing pre-layout (or conventional) and layout-specifit alpha (probability of type I error). Suggestions are offered to statisticians and editors of ecological j oumals as to how ecologists' under- standing of experimental design and statistics might be improved.

The Nonconcept of Species Diversity: A Critique and Alternative Parameters.

Abstract: The recent literature on species diversity contains many semantic, conceptual, and technical problems. It is suggested that, as a result of these problems, species diversity has become a meaningless concept, that the term be abandoned, and that ecologists take a more critical approach to species—number relations and rely less on information theoretic and other analogies. As multispecific collections of organisms possess numerous statistical properties which conform to the conventional criteria for diversity indices, such collections are not intrinsically arrangeable in linear order along some diversity scale. Several such properties or "species composition parameters" having straightforward biological interpretations are presented as alternatives to the diversity approach. The two most basic of these are simply ▵1=[n/n—1][1—Σi(N_i/_N)2] =the proportion of potential interindividual encounters which is interspecific (as opposed to intraspecific), assuming every individual in the collection can encounter all other individuals, E(Sn) = Σi [1—(N—Nin)/(Nn)] =the expected number of species in a sample of n individuals selected at random from a collection containing N individuals, S species, and Ni individuals in the ith species.

The Measurement of Niche Overlap and Some Relatives

Abstract: Existing overlap indices are examined and are judged to be inadequate on the grounds (1) that they lack simple and appropriate biological interpretations, and (2) that they ignore possible variation among resource states in abundance or availability (a_i). Two indices interpretable in terms of encounters are proposed. Niche overlap (L) is measured as the degree to which frequency of interspecific encounter is higher or lower than it would be if each species utilized each resource state in proportion to its abundance (a_i). Directional overlap (Z_(xy)) is measured as the density of species Y encountered, on the average, by an individual of species X. When resource states are equal in size, L is equivalent to Lloyd's `interspecies patchiness,' and Z_(x(y)) is equivalent to his `mean crowding on species 1 by species 2.' Indices which in corporate variation in resource state abundance are also developed for mean crowding, patchiness and niche breadth. See full-text article at JSTOR

Spatial distribution of the montane unicorn

Abstract: Analyse de la repartition de 5 populations de l'espece recemment decouverte Monoceros montanus.Ces donnees fournissent la base d'une discussion sur l'approche mathematique de l'analyse de repartition spatiale

Ecosystem Alteration by Mosquitofish (Gambusia affinis) Predation

Abstract: In artificial pools Gambusia affinis greatly reduced rotifer, crustacean, and insect populations and thus permitted extraordinary development of phytoplankton populations (2x108 cells per milliliter). Other effects included decreased optical transmissivity and increased temperature of the water, decreased amounts of dissolved inorganic phosphorus, and increased amounts of dissolved organic phosphorus, inhibition of Spirogyra, and replacement of one annelid, Chaetogaster, by another, Aeolosoma.

The Design and Analysis of Experiments

Abstract: THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

A new method for non-parametric multivariate analysis of variance

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.

Ecological Diversity and its Measurement

Abstract: Definitions of diversity. Measuring species diversity. Choosing an index and interpreting diversity measures. Sampling problems. Structural diversity. Applications of diversity measures. Summary.

Experimental Design and Data Analysis for Biologists

Abstract: An essential textbook for any student or researcher in biology needing to design experiments, sample programs or analyse the resulting data The text begins with a revision of estimation and hypothesis testing methods, covering both classical and Bayesian philosophies, before advancing to the analysis of linear and generalized linear models Topics covered include linear and logistic regression, simple and complex ANOVA models (for factorial, nested, block, split-plot and repeated measures and covariance designs), and log-linear models Multivariate techniques, including classification and ordination, are then introduced Special emphasis is placed on checking assumptions, exploratory data analysis and presentation of results The main analyses are illustrated with many examples from published papers and there is an extensive reference list to both the statistical and biological literature The book is supported by a website that provides all data sets, questions for each chapter and links to software

Pseudoreplication and the Design of Ecological Field Experiments

Abstract: Pseudoreplication is defined. as the use of inferential statistics to test for treatment effects with data from experiments where either treatments are not replicated (though samples may be) or replicates are not statistically independent. In ANOVA terminology, it is the testing for treatment effects with an error term inappropriate to the hypothesis being considered. Scrutiny of 176 experi- mental studies published between 1960 and the present revealed that pseudoreplication occurred in 27% of them, or 48% of all such studies that applied inferential statistics. The incidence of pseudo- replication is especially high in studies of marine benthos and small mammals. The critical features of controlled experimentation are reviewed. Nondemonic intrusion is defined as the impingement of chance events on an experiment in progress. As a safeguard against both it and preexisting gradients, interspersion of treatments is argued to be an obligatory feature of good design. Especially in small experiments, adequate interspersion can sometimes be assured only by dispensing with strict random- ization procedures. Comprehension of this conflict between interspersion and randomization is aided by distinguishing pre-layout (or conventional) and layout-specifit alpha (probability of type I error). Suggestions are offered to statisticians and editors of ecological j oumals as to how ecologists' under- standing of experimental design and statistics might be improved.