Complex bioindication and environmental stress assessment

• Published in: Ecological indicators Vol. 6; no. 1; pp. 114 - 136
• Main Author: Fraenzle, O
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 2006
• Subjects: Bioindicators; Chemical risk assessment; Strain; Stress; Chemical risk assessment; Bioindicators; Stress; Strain
• ISSN: 1470-160X; 1872-7034
• DOI: 10.1016/j.ecolind.2005.08.015

The indicative quality of bioindicators, ranging from organelles, organs or single organisms to complex ecosystems, depends on inherent ecophysiological properties, population dynamics, and stress reactions with regard to physical and chemical changes in site conditions as described in Section 2 of the present contribution. Section 3 provides a systematic review of both typology and rational selection of bioindicators on the species, population, biocenotic, and ecosystem levels. It is to show that the primary task of bioindicators is the general determination of physiological effects in the sense of strain reactions rather than the direct measurement of environmental concentrations of stressors. Thus, in early recognition perspective the lack of specificity has the advantage of a broad-based caveat, inducive to subsequent systematic search for quantitative causal inter-relationships. A further advantage of biomonitoring is its comparatively low cost on the one hand and the integrative recording character on the other. Contrary to these positive aspects of bioindicator use there is, however, an essential deficiency resulting from the highly variable susceptibility of the test species exposed to stressors, which leads to difficulties in comparing specific effect data. In view of such problems, the possibilities of fuzzy logic approaches for evaluative data interpretation and inter- and intraspecific comparison purposes are emphasized. Active and passive biomonitoring approaches on the basis of single-species reactions yield spatially valid data only on condition the underlying sampling networks are implemented in compliance with geostatistical requirements or the corresponding test methodologies of variogram analysis and kriging procedures, respectively. Analogously, also the selection of complex bioindicators such as biocenoses or ecosystems must be based on rigid criteria of spatial and temporal representativeness. The last section then is a critical comparative appraisal of the problems encountered in biomonitoring, which leads to a set of suggestions for improving both the technical practicability and the data quality of biomonitoring approaches.