A fundamental difference between dose-response relationship in human toxicology and ecology is that individuals studied may not necessarily be the individuals at risk. Second, they are usually vulnerable to confounding factors. For example, the response of soil microorganisms to heavy metal amendment using such measurable endpoints as soil dehydrogenase activity, antifreeze protein (AFP) content, microbial respiration, and microbial biomass measured in samples containing different concentrations of the heavy metals in sewage is an example of attempts to develop stressor dose-response relationship as an indirect approach for assessing the bioavailability of nickel to humans via ingestion of plants grown in such a soil. However, a stressor dose-response relationship established in this case addresses several tox-icological issues. First, the microbial activities measured are meant to assess the effects of the heavy metals on the microbial population as well as plant uptake of nitrogen through the activity of nitrogen-fixing bacteria that may be present in the soil. The data obtained can be used to determine the level of ecological toxicity (ED50) for guiding decision on heavy metal-laden sewage disposed in farmlands. The foregoing indicates that except clear-cut objectives that are established from the onset of an ecological risk assessment, the outcome may be of little or no practical use.
Ecological stressor/dose-response has often been applied to the soil ecosystem for evaluating the effects of heavy metals on the microbial activity through the use of enzyme (arylsulfatase) activity as a measurable endpoint. The effects are then fitted to a logistic dose-response model and graphical ED50 determined like in human dose-response curves. Attempts have also been made to evaluate the ecological risks at the landscape level by developing a science-based ecological dose-response curve to help define appropriate and socially acceptable thresholds or limits of 'acceptable change' of an ecosystem by measuring the ecological response (i.e., abundance of species productivity) using a continuum of human disturbance already existing in a region. Statistical relationships were developed that tie the abundance of particular species to different levels of human disturbance.
Although the stressor dose-response concept provides the scientific framework for establishing the impact of increasing human and natural disturbances, it is believed that science cannot provide the acceptable threshold of human activity since threshold must be set by society by integrating tradeoff factors between economic growth and the level of ecological risk people are willing to accept. The stressor-response analysis, as opposed to traditional dose-response relationship, in human health risk assessment describes the relationship between the magnitude, frequency, or duration of the stressor and the magnitude of response in ecological risk assessment.
Ecological risk assessments evaluate ecological effects of chemical or physical stressors at the individual, population, community, ecosystem, and even landscape levels. Toxicological effects of exposure to xenobiotics must be well defined for dose-response to be meaningful. The stressor dose-response analysis may focus on different aspects of the stressor dose-response relationship depending on the assessment objectives, the conceptual model, and the type of data used for analysis. For example, it could be invoked in situations such as the accidental discharge of pesticides or chemicals on land by humans or in water systems, draining of wetlands, human-induced forest decline resulting from acid deposition, etc.
In summary, the following are unresolved issues related to stressor dose-response relationship needing further studies in ecological risk assessment:
• quantifying cumulative impacts and stress dose-response relationships for multiple stressors;
• methodology for predicting ecosystem recovery;
• improving the quantification of indirect effects;
• describing stressor-response relationships for physical perturbation;
• distinguishing ecosystem changes due to natural processes from those caused by man;
• models that reflect compensatory processes at population and evolutionary timescale;
• logical frameworks and guidance for conducting wildlife risk assessment to support a variety of environmental decision contexts;
• methods that allow extrapolation of effects across species and levels of biological organization; and
• data sets and systems needed for wildlife risk assessment, and mechanistic population models for particular species and classes of species that use these data.
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