Turbine fuels are often the only aviation fuel available in most of the world. Turbine fuels consist of numerous constituents with varying water solubilities, volatilities and toxicities. This study investigates the toxicity of the water soluble fraction (WSF) of JP-4 using the Standard Aquatic Microcosm (SAM). Multivariate analysis of the complex data, including the relatively new method of nonmetric clustering, was used and compared to more traditional analyses. Particular emphasis is placed on ecosystem dynamics in multivariate space.The WSF is prepared by vigorously mixing the fuel and the SAM microcosm media in a separatory funnel. The water phase, which contains the water-soluble fraction of JP-4 is then collected. The SAM experiment was conducted using concentrations of 0.0, 1.5 and 15% WSF. The WSF is added on day 7 of the experiments by removing 450 ml from each microcosm including the controls, then adding the appropriate amount of toxicant solution and finally bringing the final volume to 3 L with microcosm media. Analysis of the WSF was performed by purge and trap gas chromatography. The organic constituents of the WSF were not recoverable from the water column within several days of the addition of the toxicant. However, the impact of the WSF on the microcosm was apparent. In the highest initial concentration treatment group an algal bloom ensued, generated by the apparent toxicity of the WSF of JP-4 to the daphnids. As the daphnid populations recovered the algal populations decreased to control values. Multivariate methods clearly demonstrated this initial impact along with an additional oscillation seperating the four treatment groups in the latter segment of the experiment. Apparent recovery may be an artifact of the projections used to describe the multivariate data. The variables that were most important in distinguishing the four groups shifted during the course of the 63 day experiment. Even this simple microcosm exhibited a variety of dynamics, with implications for biomonitoring schemes and ecological risk assessments.

In this paper we present the community conditioning hypothesis, “ecological communities retain information about events in their history.” This hypothesis, which was derived from the concept of nonequilibrium community ecology, was developed as a framework for understanding the persistence of dose‐related responses in multispecies toxicity tests. We present data from three standardized aquatic microcosm (SAM) toxicity tests using the water‐soluble fractions from turbine fuels (Jet‐A, JP‐ 4, and JP‐8). In all three tests, the toxicants depressed the Daphnia populations for several weeks, which resulted in algal blooms in the dosed microcosms due to lower predation rates. These effects were short‐lived, and by the second and third months of the experiments, the Daphnia populations appeared to have recovered. However, multivariate analysis of the data revealed dose/response differences that reappeared during the later part of the tests, often due to differences in other consumers (rotifers, ostracods, ciliates), or algae that are not normally consumed (filamentous green algae and bluegreen “algae”). Our findings are consistent with ecological theories that describe communities as the unique product of their etiologies. The implications of this to environmental toxicology are that almost all environmental events leave lasting effects, whether or not we have observed them.

Abstract-In this paper we present the community conditioning hypothesis, ''ecological communities retain information about events in their history.'' This hypothesis, which was derived from the concept of nonequilibrium community ecology, was developed as a framework for understanding the persistence of dose-related responses in multispecies toxicity tests. We present data from three standardized aquatic microcosm (SAM) toxicity tests using the water-soluble fractions from turbine fuels (Jet-A, JP-4, and JP-8). In all three tests, the toxicants depressed the Daphnia populations for several weeks, which resulted in algal blooms in the dosed microcosms due to lower predation rates. These effects were short-lived, and by the second and third months of the experiments, the Daphnia populations appeared to have recovered. However, multivariate analysis of the data revealed dose/response differences that reappeared during the later part of the tests, often due to differences in other consumers (rotifers, ostracods, ciliates), or algae that are not normally consumed (filamentous green algae and bluegreen ''algae''). Our findings are consistent with ecological theories that describe communities as the unique product of their etiologies. The implications of this to environmental toxicology are that almost all environmental events leave lasting effects, whether or not we have observed them.

Ecological risk assessment has evolved so that the interaction among the components is now an implicit assumption. Unlike single species‐based risk assessments, it is often crucial in environmental or ecological risk assessments to be able to describe a system with many interacting components. In addition, some quantifiable description of how different biological communities respond upon the addition of a toxicant or some other stressor is required to adequately describe risk at the ecosystem level. Three methods have been applied at this level: the mean strain measurement used by K. Kersting, the state‐space analysis pioneered by A.R. Johnson, and the nonmetric clustering developed by G. Matthews for ecological data sets and for analysis of standardized aquatic microcosm data. Each method has direct application to the description of an affected ecosystem with‐out reliance upon a single specific and perhaps misleading endpoint. Each also can assign distance or probability measures in order to compare the control to treatment groups. Nonmetric clustering (NMC) has the advantage of not attempting to combine different types of scales or metrics during the multivariate analysis and is robust against interference by random variables. Applications of these methodologies into an ecological risk assessment should have the benefit of combining large interactive data sets into distinct measures to be used as a measure of risk and as a test of the prediction of risk. The primary impact of these methods may be in the selection and interpretation of assessment and measurement endpoints. Much recent debate in toxicological studies has focused on appropriate measurement endpoints for tests. Nonmetric clustering and other multivariate techniques should aid in the selection of these endpoints in ways meaningful at the ecosystem level. We suggest that the search for assessment and measurement endpoints be left to the appropriate multivariate computation algorithms in the case of multispecies situations. Application of these methods in the verification and validation process of risk assessment will serve to check the selection of endpoints during modeling exercises and to improve the presentation of assessment criteria.

Abstract-The community conditioning hypothesis is used as a framework in which to place the layers of effects during and after pesticide intoxication. Community conditioning states that information about the history of a system can be and is written at a variety of organismal and ecological levels. This historical component or etiology determines the future dynamics of a system. The storage of information concerning prior stressor events has been observed in a variety of compartments. Fish populations have been observed to have different genetic structures in populations that have been exposed to toxicant stressors. Analysis of biomarker data from field experiments reveals a variety of patterns, some due to the location of the field plots. Treatment groups within a series of microcosm experiments maintain their identities long after the degradation of the toxicant. The dynamics of the treatment groups in multivariate ecological space are characteristic of a particular treatment. Other microcosm systems differentially respond to invasion depending upon the order of the inoculation of the biotic components, even though at the time of the invasion the systems are indistinguishable. A major factor in the uncertainty of pesticide risk assessment will be the unknown etiology of the system of interest.