Preface to the Princeton Landmarks in Biology Edition vii Preface xi Symbols Used xiii 1. The Importance of Islands 3 2. Area and Number of Speicies 8 3. Further Explanations of the Area-Diversity Pattern 19 4. The Strategy of Colonization 68 5. Invasibility and the Variable Niche 94 6. Stepping Stones and Biotic Exchange 123 7. Evolutionary Changes Following Colonization 145 8. Prospect 181 Glossary 185 References 193 Index 201

The Theory of Island Biogeography

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.

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A new method for non-parametric multivariate analysis of variance

Species richness is a fundamental measurement of community and regional diversity, and it underlies many ecological models and conservation strategies. In spite of its importance, ecologists have not always appreciated the effects of abundance and sampling effort on richness measures and comparisons. We survey a series of common pitfalls in quantifying and comparing taxon richness. These pitfalls can be largely avoided by using accumulation and rarefaction curves, which may be based on either individuals or samples. These taxon sampling curves contain the basic information for valid richness comparisons, including category‐subcategory ratios (species-to-genus and species-toindividual ratios). Rarefaction methods ‐ both sample-based and individual-based ‐ allow for meaningful standardization and comparison of datasets. Standardizing data sets by area or sampling effort may produce very different results compared to standardizing by number of individuals collected, and it is not always clear which measure of diversity is more appropriate. Asymptotic richness estimators provide lower-bound estimates for taxon-rich groups such as tropical arthropods, in which observed richness rarely reaches an asymptote, despite intensive sampling. Recent examples of diversity studies of tropical trees, stream invertebrates, and herbaceous plants emphasize the importance of carefully quantifying species richness using taxon sampling curves.

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Quantifying biodiversity: procedures and pitfalls in the measurement and comparison of species richness

Evolution and measurement of species diversity

Nonparametric multivariate analysis of ecological data using permutation tests has two main challenges: (1) to partition the variability in the data according to a complex design or model, as is often required in ecological experiments, and (2) to base the analysis on a multivariate distance measure (such as the semimetric Bray-Curtis measure) that is reasonable for ecological data sets. Previous nonparametric methods have succeeded in one or other of these areas, but not in both. A recent contribution to Ecological Monographs by Legendre and Anderson, called distance-based redundancy analysis (db-RDA), does achieve both. It does this by calculating principal coordinates and subsequently correcting for negative eigenvalues, if they are present, by adding a constant to squared distances. We show here that such a correction is not necessary. Partitioning can be achieved directly from the distance matrix itself, with no corrections and no eigenanalysis, even if the distance measure used is semimetric. An ecological example is given to show the differences in these statistical methods. Empirical simulations, based on parameters estimated from real ecological species abundance data, showed that db-RDA done on multifactorial designs (using the correction) does not have type 1 error consistent with the significance level chosen for the analysis (i.e., does not provide an exact test), whereas the direct method described and advocated here does.

Fitting multivariate models to community data: a comment on distance‐based redundancy analysis

Considerations involved in developing a suite of indicators to monitor regional environmental health, similar in conception to management use of ‘leading economic indicators’, are described. Linkages between human activities and well being and the state of the environment are considered essential to the evaluation of general environmental health. Biogeochemical and socioeconomic indicators are mutually affected by environmental degradation and examples of both categories of indicators are described. Desirable properties in indicators of environmental health vary with their specific management use. Different indicators are called for when collecting data to assess the adequacy of the environment, monitor trends over time, provide early warning of environmental degradation, or diagnose the cause of an existing problem. Tradeoffs between desirable characteristics, costs, and quality of information are inevitable when choosing indicators for management use. Decisions about what information to collect for which purpose can be made more rationally when available indicators are characterized and matched to management goals.

A proposed framework for developing indicators of ecosystem health

Despite an increased awareness by governments and the general public of the need for protecting all types of aquatic habitats, human impacts continue to impair the services that these ecosystems provide. Increased monitoring activities that locus on all major biological compartments are needed to quantify the present condition of Earth's aquatic resources and to evaluate the effectiveness of regulations designed to rehabilitate damaged ecosystems. Algae are an ecologically important group in most aquatic ecosystems but are often ignored as indicators of aquatic ecosystem change. We attribute this situation both to an underappreciation of the utility of algal indicators among non-phycologists and to a lack of standardized methods for monitoring with algae.

Algae as indicators of environmental change

Biological monitoring part IV—Toxicity testing

Although rather extensive bibliographies give the impression that there is a vast amount of literature on the effects of temperature on aquatic organisms, when one tries to apply this information to specific interactions, such as the effects of temperature changes on chemical toxicity to aquatic organisms, often very little of the evidence is applicable. Although the most useful information on this relationship has been acquired in laboratory situations even this body of literature (which forms the bulk of this paper) is not adequate to make any scientifically justifiable generalizations. Field data on this relationship is almost non-existent and it is unlikely that much will become available unless specific studies are initiated which are directed toward this end. This is equally true of the laboratory information although it seems more likely that this will be generated as a spinoff from other research activities. In order to develop water quality management programs for steam-electric power plants one should understand the relationship between temperature and the response of aquatic organisms to toxic chemicals. Not only do some power plants discharge chlorine and other similar materials as well as heated waste water but those that discharge the latter only may be located near discharges of toxic chemicals. Since temperature and chemical stress to aquatic organisms are most commonly discussed independently we felt a paper covering this relationship would be useful.

The effects of temperature upon the toxicity of chemicals to aquatic organisms

Most biologists agree that at each succeeding level of biological organization new properties appear that would not have been evident even by the most intense and careful examination of lower levels of organization. These levels might be crudely characterized as subcellular, cellular, organ, organism, population, multispecies, community, and ecosystem. The field of ecology developed because even the most meticulous study of single species could not accurately predict how several such species might interact competitively or in predator-prey interactions and the like. Moreover, interactions of biotic and abiotic materials at the level of organization called ecosystem are so complex that they could not be predicted from a detailed examination of isolated component parts. This preamble may seem platitudinous to most biologists who have heard this many times before. This makes it all the more remarkable that in the field of toxicity testing an assumption is made that responses at levels of biological organization above single species can be reliably predicted with single species toxicity tests. Unfortunately, this assumption is rarely explicitly stated and, therefore, often passes unchallenged. When the assumption is challenged, a response is that single species tests have been used for years and no adverse ecosystem or multispecies effects were noted. This could be because single species tests are overly protective when coupled with an enormous application factor or that such effects were simply not detected because there were no systematic, scientifically sound studies carried out to detect them. Probably both of these possibilities occur. However, the important factor is that no scientifically justifiable evidence exists to indicate that degree of reliability with which one may use single species tests to predict responses at higher levels of biological organization. One might speculate that the absence of such information is due to the paucity of reliable tests at higher levels of organization. This situation certainly exists but does not explain the lack of pressure to develop such tests. The most pressing need in the field of toxicity testing is not further perfection of single species tests, but rather the development of parallel tests at higher levels of organization. These need not be inordinately expensive, time consuming, or require any more skilled professionals than single species tests. Higher level tests merely require a different type of biological background. Theoretical ecologists have been notoriously reluctant to contribute to this effort, and, as a consequence, such tests must be developed by associations of professional biologists and other organizations with similar interests.

John Cairns

Papers

A proposed framework for developing indicators of ecosystem health

Algae as indicators of environmental change

Biological monitoring part IV—Toxicity testing

The effects of temperature upon the toxicity of chemicals to aquatic organisms

Are single species toxicity tests alone adequate for estimating environmental hazard