No abstract

Because people wish to preserve their health and do something equivalent for ecosystems, the metaphor of ecosystem health springs to mind. This paper presents the argument that it is a mistake for environmental scientists to treat this metaphor as reality. First, the metaphor fails because it misrepresents both ecology and health science. Ecosystems are not organisms, so they do not behave like organisms and do not have properties of organisms such as health. Also, health is not an operational concept for physicians or health risk assessors because they must predict, diagnose, and treat specific states called diseases or injuries; they do not calculate indexes of health. Second, attempts to operationally define ecosystem health result in the creation of indexes of heterogeneous variables. Such indexes have no meaning; they cannot be predicted, so they are not applicable to most regulatory problems; they have no diagnostic power; effects on one component are eclipsed by responses of other components; and the reason for a high or low index value is unknown. Their only virtue is that they reduce the complex array of ecosystem responses to various disturbances to one number with a reassuring name. A better alternative is to assess the real array of ecosystem responses so that causes can be diagnosed, future states can be predicted, and benefits of treatments can be compared.

Abstract-Increased ionic concentrations are associated with the impairment of benthic invertebrate assemblages. However, the causal nature of that relationship must be demonstrated so that it can be used to derive a benchmark for conductivity. The available evidence is organized in terms of six characteristics of causation: co-occurrence, preceding causation, interaction, alteration, sufficiency, and time order. The inferential approach is to weight the lines of evidence using a consistent scoring system, weigh the evidence for each causal characteristic, and then assess the body of evidence. Through this assessment, the authors found that a mixture containing the ions Ca þ , Mg þ , HCO À 3 , and SO À 4 , as measured by conductivity, is a common cause of extirpation of aquatic macroinvertebrates in Appalachia where surface coal mining is prevalent. The mixture of ions is implicated as the cause rather than any individual constituent of the mixture. The authors also expect that ionic concentrations sufficient to cause extirpations would occur with a similar salt mixture containing predominately HCO À 3 , SO 2À 4 , Ca 2þ , and Mg 2þ in other regions with naturally low conductivity. This case demonstrates the utility of the method for determining whether relationships identified in the field are causal. Environ. Toxicol.

Ecological risk assessments must have clearly defined endpoints that are socially and biologically relevant, accessible to prediction and measurement, and susceptible to the hazard being assessed. Most ecological assessments do not have such endpoints, in part because the endpoints of toxicity tests or other measurements of effects are used as assessment endpoints. This article distinguishes assessment and measurement endpoints in terms of their roles in risk assessments and explains how the criteria for their selection differ. It then presents critical discussions of possible assessment and measurement endpoints for regional ecological risk assessments. Finally, the article explains how endpoint selection is affected by the goal of the assessment. Generic goals for regional risk assessment include explanation of observed regional effects, evaluation of an action with regional implications, and evaluation of the state of a region. Currently, population level assessment endpoints such as abundance and range are the most generally useful. For higher levels (ecosystems and regions), data are generally not available and the validity of models has not been demonstrated, and for lower level effects (physiological, and organismal) are not relevant, However, landscape descriptors, material export, and other regional-scale measurement endpoints show promise for regional assessments.

No abstract

Biological surveys have become a common technique for determining whether aquatic communities have been injured. However, their results are not useful for identifying management options until the causes of apparent injuries have been identified. Techniques for determining causation have been largely informal and ad hoc. This paper presents a logical system for causal inference. It begins by analyzing the available information to generate causal evidence; available information may include spatial or temporal associations of potential cause and effect, field or laboratory experimental results, and diagnostic evidence from the affected organisms. It then uses a series of three alternative methods to infer the cause: Elimination of causes, diagnostic protocols, and analysis of the strength of evidence. If the cause cannot be identified with sufficient confidence, the reality of the effects is examined, and if the effects are determined to be real, more information is obtained to reiterate the process.

Biological surveys have become a common technique for determining whether aquatic communities have been injured. However, their results are not useful for identifying management options until the causes of apparent injuries have been identified. Techniques for determining causation have been largely informal and ad hoc. This paper presents a logical system for causal inference. It begins by analyzing the available information to generate causal evidence; available information may include spatial or temporal associations of potential cause and effect, field or laboratory experimental results, and diagnostic evidence from the affected organisms. It then uses a series of three alternative methods to infer the cause: Elimination of causes, diagnostic protocols, and analysis of the strength of evidence. If the cause cannot be identified with sufficient confidence, the reality of the effects is examined, and if the effects are determined to be real, more information is obtained to reiterate the process.

The concept of chronic toxicity has caused confusion in fish toxicology because it has developed four connotations: long duration, inclusion of all life stages, low severity, and high sensitivity. To compare alternate chronic tests and expressions of test results, we extracted concentration‐response data from published life‐cycle, partial‐life‐cycle, and early life‐stage tests and derived concentration‐response relationships by nonlinear regression. The effects examined were reductions in parental survival, fecundity, hatching success, larval survival, weight of early juveniles, and weight of early juveniles per egg. On the average, the most sensitive effect was reduction in fecundity, not effects on early life stages. We also found that maximum acceptable toxicant concentrations (MATCs) corresponded to fairly high levels of effect; mean reductions at the MATC were parental survival, 20%; fecundity, 42%; hatching, 12%; larval survival, 19%; weight, 20%; and weight/egg, 35%. These results indicate that, on average, MATCs are concentrations that cause substantial effects and that MATCs estimated from early life‐stage tests are not good substitutes for life‐cycle tests. We suggest that the acute‐chronic dichotomy be abandoned in favor of tests and benchmarks based on concentration‐duration‐response dynamics.