Evaluating effects of contaminants on fish health at multiple levels of biological organization: Extrapolating from lower to higher levels

Citation
Sm. Adams et al., Evaluating effects of contaminants on fish health at multiple levels of biological organization: Extrapolating from lower to higher levels, HUM ECOL R, 6(1), 2000, pp. 15-27
Citations number
30
Categorie Soggetti
Environment/Ecology
Journal title
HUMAN AND ECOLOGICAL RISK ASSESSMENT
ISSN journal
10807039 → ACNP
Volume
6
Issue
1
Year of publication
2000
Pages
15 - 27
Database
ISI
SICI code
1080-7039(200002)6:1<15:EEOCOF>2.0.ZU;2-D
Abstract
Effects of environmental stressors such as contaminants on the health of aq uatic ecosystems usually involve a series of biological responses ranging f rom the biomolecular/biochemical to the population and community levels. To establish relationships and to determine the feasibility of extrapolating between higher and lower levels of biological organization, spatial pattern s in fish responses to contaminant loading were investigated in a stream re ceiving point-source discharges of various contaminants near its headwaters . Relationships among fish responses at four major levels of biological org anization (biochemical/physiological, individual, population, and community levels) were evaluated relative to patterns in contaminant loading along t he spatial gradient of the stream. Both individual and integrated response analysis demonstrated that bioindicators at several levels of biological or ganization displayed similar downstream patterns in their response to conta minant loading within the stream. Some of the bioindicator responses at low er levels of organization appear to be useful for the ecological risk asses sment process because of their sensitivity and apparent relationships to hi gher levels. By identifying and establishing relationships between levels o f biological organization we should be better able to understand the mechan isms of stress responses in ecological systems that could ultimately result in improved predictive capability of ecological risk assessment and also a llow for more informed decisions regarding remedial actions.