Multispecies Toxicity Tests

Measurement of PICT usually involves carrying out short-term (multispecies) toxicity tests on whole communities from clean and contaminated sites. Pollution tolerance is quantified by reduced sensitivity of the toxicant in these tests. The increased tolerance may result from replacement of sensitive species by less sensitive ones, development of heritable tolerance by one or more species, and/or short-term nonheritable acclimation. A significant increase in community tolerance compared to the baseline tolerance at reference sites suggests that the community has been adversely affected by toxicants. In this way, PICT can establish causal linkages between contaminants and effects in monitoring studies (Blanck 2002). 

These properties are especially important in the design, data analysis, and interpretation of multispecies toxicity tests, field studies, and environmental risk assessment and will be discussed in the appropriate sections. This alternate approach rejects the smooth transition of effects and recognizes that ecosystems have fundamentally different properties and are expected to react unexpectedly to contaminants. 

Multispecies toxicity tests, as their name implies, involve the inclusion of two or more organisms and are usually designed so that the organisms interact. The effects of a toxicant upon various aspects of population dynamics... 

One of the most crucial aspects of a toxicity test is the suitability and health of the test organisms or, in the case of multispecies toxicity tests, the introduced community. It is also important to define clearly the goals of the toxicity test. If the protection of a particular economic resource such as a salmon fishery is of overriding importance, it may be important to use a salmonid and its food sources as test species. Toxicity tests are performed to gain an overall picture of the toxicity of a compound to a variety of species. Therefore the laboratory test species is taken only as representative of a particular class or, in many cases, phyla. 

The most important parameter is a clear identification of the specific question that the toxicity test is supposed to answer. The determination of the LC50 within a tight confidence interval will often require many fewer organisms than the determination of an effect at the low end of the dose-response curve. In multispecies toxicity tests and field studies, the inherent variability or noise of these systems requires massive data collection and reduction efforts. It is also important to determine ahead of time whether a hypothesis testing or regression approach to data analysis should be attempted. 

Over the last 20 years a variety of multispecies toxicity tests have been developed. These tests, usually referred to as microcosms or mesocosms, range in size from 1 1 (the mixed flask culture) to thousands of liters in the case of the pond mesocosms. A review by Gearing (1989) listed 11 freshwater artificial stream methods, 22 laboratory freshwater microcosms ranging from 0.1 to 8,4001, and 18 outdoor freshwater microcosms ranging from 8 to 18,000,000 1. In order to evaluate and design multispecies toxicity tests, it is crucial to understand the fundamental differences compared to singlespecies tests. A more extensive discussion has been published (Landis, Matthews, and Matthews 1996) and the major points are summarized below. 

As discussed in Chapter 2, ecological structures including multispecies toxicity tests have the fundamental property of being historical. Brooks et al. (1989), in an extensive literature review and detailed derivation, concluded that ecological systems are time-directed, or in other words, irreversible with respect to time. Drake (1991) has experimentally demonstrated the historical aspects of ecological structure in a series of microcosm experiments. Design... 

Evolutionary events also occur within multispecies toxicity tests. Species or strains resistant to xenobiotics do arise. Simple microbial microcosms (chemostats) are often used to force the evolution of new metabolic pathways for pesticide and xenobiotic degradation. 

Microcosms do not have some of the characteristics of naturally synthesized ecological structures. Perhaps primary is that multispecies toxicity tests are by nature smaller in scale, thus reducing the number of species that can survive in these enclosed spaces compared to natural systems. This feature is very important since after dosing, every experimental design must make each replicate an island to prevent cross contamination and to protect the environment. Therefore the dynamics of extinction and the coupled stochastic and deterministic features of island biogeography produce effects that must be separated from that of the toxicant. Ensuring that each replicate is as similar as possible over the short term minimizes the differential effects of the enforced isolation, but eventually divergence occurs. 

The design of multispecies toxicity tests runs into a classical dilemma. If the system incorporates all of the heterogeneity of a naturally synthesized ecological structure, then it can become unique, thereby losing the statistical power needed for typical hypothesis testing. If multispecies toxicity tests are complex systems and subject to community conditioning, then the tests are not repeatable in the same sense as a single-species toxicity test or biochemical assay. 

Since the information about past events can be kept in a variety of forms, from the dynamics of populations to the genetic sequence of mitochondria, it is necessary to be able to incorporate each of these types of data into the design and analysis of the experiment. Assumptions about recovery are invalid and tend to cloud the now-apparent dynamics of multispecies toxicity tests. The ramifications are critical to the analysis and interpretation of these tests. 

Data Analysis and Interpretation of Multispecies Toxicity Tests... 

A large number of data analysis methods have been used to examine the dynamics of these structures. The analysis techniques should be able to detect patterns, given the properties of multispecies toxicity tests described above. In order to conduct proper statistical analysis, the samples should be true replicates and in sufficient number to generate the required statistical power. The analysis techniques should be multivariate, able to detect a variety of patterns, and to perform hypothesis testing on those patterns. 

However, by definition, these univariate methods of hypothesis testing are inappropriate for multispecies toxicity tests. As such, these methods are an attempt to understand a multivariate system by looking at one univariate projection after another, attempting to find statistically significant differences. Often the power of the statistical tests is quite low due to the few replicates and the high inherent variance of many of the biotic variables. 

Multispecies toxicity tests come in a wide variety of types (artificial streams, generic freshwater, simulated farm ponds, ditches, experimental plots, and forests), and they share basic properties. Experimental designs should take into account the advantage of these properties to ensure an interpretable experimental result. We propose the following design parameters for experimental design, analysis, and interpretation. 

Multispecies toxicity tests are complex structures. Complex structures are nonequilibrium, historical, and nonlinear. To measure the recovery of such a structure is to measure a property that does not exist for a complex structure. 

Multispecies toxicity tests are not repeatable in the strictest sense since each is sensitive to initial conditions. However, common patterns do appear, and these should be the focus of the investigation. 

In multispecies toxicity tests, the interactions among the component species should be understood. 

Multivariate methods are more suitable for the data analysis of multispecies toxicity tests. No one multivariate technique is always best. Given that many responses of multispecies toxicity tests are nonlinear, techniques that do not assume linear relationships may allow a more accurate interpretation of the test system. 

Do not assume that the combination of variables that are best for determining clusters or treatments on one sampling day will be the most appropriate for every sampling day. As the structure and function of the multispecies toxicity test change over time, so will the important variables. 

Landis, W.G., R.A. Matthews, and G.B. Matthews. 1997. The design and analysis of multispecies toxicity tests for pesticide registration. Ecol. Appl. 7 1111-1116. 

Matthews, G.B., R.A. Matthews, and W.G. Landis. 1995. Nonmetric clustering and association analysis Implications for the evaluation of multispecies toxicity tests and field monitoring. Environmental Toxicology and Risk Assessment, Vol. 3, ASTM 1218. J.S. Hughes, G.R. Biddinger, and E. Mones, Eds. American Society for Testing and Materials, Philadelphia, PA, pp. 79-93. 

Discuss the natural source vs. laboratory-derived composition of species in multispecies toxicity tests. 

What are the critical design considerations for multispecies toxicity tests ... 

Toxicity tests using artificially contained communities have long been a resource in environmental toxicology. The nature and design criteria for these types of tests are discussed in Chapter 3. Many different methodologies have been developed (Table 4.12). Each has particular advantages and disadvantages and none have been demonstrated to faithfully reproduce an entire ecosystem. However, as a research tool to look at secondary effects, bioaccumulation and fate, the various multispecies toxicity tests have been demonstrated to be useful. 

The overriding characteristic of a multispecies toxicity test is that it consists of at least two or more interacting species. Which two or more species and their derivation, along with the volume and complexity of substrate and heterogeneity of the environment, are all matters of debate. Much current theory on the coexistence of species and their interactions emphasizes the role of environmental heterogeneity upon the formation and continuance of a... 

Multispecies toxicity tests range widely in size and complexity. This is the case for both aquatic and terrestrial systems. 

Often, impacts are quantified using a reference site as a negative control for comparison to other sites under question. Similarly, multispecies toxicity tests, microcosms, and mesocosms attempt to detect differences between the control treatment and the dosed treatment groups. 

The remainder of this section details the potential application of multivariate methods in the selection of endpoints and in the evaluation of exposure and effects of stressors in ecosystems. Particular reference is made to the application of these methods to the current framework for ecological risk assessment. Examples of the use of multivariate methods in detecting effects and in selecting important measurement variables are covered using both field surveys and multispecies toxicity tests. 

The application of these methods has been examined in a series of field studies and multispecies toxicity tests. These examinations have demonstrated the power and usefulness of multivariate techniques in elucidating patterns in biological communities of varying complexity. 

Apparently as an independent development, A.R. Johnson (1988a) proposed the idea of using a multivariate approach to the analysis of multispecies toxicity tests. This state space analysis is based upon the common representation of complex and dynamic systems as an n-dimensional vector. In other words, the... 

Examples of the Use of Multivariate Methods in Multispecies Toxicity Tests and Field Studies... 

The following examples demonstrate the usefulness of multivariate methods in the evaluation of field ecological data and laboratory multispecies toxicity tests. In each of the examples, several multivariate techniques were used — generally Euclidean and cosine distances (Figure 11.29), principal components, and nonmetric clustering and association analysis. 

In both studies, nonmetric clustering outperformed the metric tests, although both principal components analysis and correspondence analysis yielded some additional insight into large-scaled patterns, which was not provided by the nonmetric clustering results. However, nonmetric clustering provided information without the use of inappropriate assumptions, data transformations, or other dataset manipulations that usually accompany the use of multivariate metric statistics. The success of these studies and techniques led to the examination of community dynamics in a series of two multispecies toxicity tests. 

The multivariate methods described above have been used to examine a series of multispecies toxicity tests. Described below are the data analyses from two published tests using methodology derived from the Standardized Aquatic Microcosm (SAM) (ASTM E1366-91). The method is described in some detail in Chapter 4. 

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