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Design criteria and derivation of indicators for ecological position, direction, and risk
Author(s) -
Landis Wayne G.,
McLaughlin John F.
Publication year - 2000
Publication title -
environmental toxicology and chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.1
H-Index - 171
eISSN - 1552-8618
pISSN - 0730-7268
DOI - 10.1002/etc.5620190436
Subject(s) - context (archaeology) , set (abstract data type) , position (finance) , representation (politics) , computer science , ecological indicator , variable (mathematics) , measure (data warehouse) , baseline (sea) , complex system , multivariate statistics , space (punctuation) , variety (cybernetics) , stochastic modelling , ecology , risk analysis (engineering) , data mining , mathematics , statistics , machine learning , artificial intelligence , geography , ecosystem , law , mathematical analysis , oceanography , archaeology , biology , operating system , political science , programming language , medicine , finance , politics , economics , geology
The baseline specifications for indicators for ecological risk assessment and management are presented. These indicators may be related to the assessment space as determined by cultural values and laws. This assessment space is a multivariate expression of the assessment endpoints. The three types of indicators include current position, the probability of leaving the assessment space, and the probability of reentering the assessment space. The formulation of indicators must recognize that ecological systems are dynamically complex and composed of both deterministic and stochastic components. As has been demonstrated in laboratory ecological systems and field experiments, the best impact indicators change over time, eliminating the possibility of a single variable being an accurate measure of position and change. We set six specific requirements for developing a useful set of indicators, as follows. The indicators must be placed in the context of the assessment space. Because projections cause the loss of information, a variety of methods with different assumptions about the nature of the system should be used. The best attributes to measure alteration of the system change over time; to use just one set may result in missing the dynamic complexity of the system and subsequent impacts. Ecological systems are both deterministic and stochastic, and representation of each is important. The stochastic component can have a tremendous impact, changing the overall dynamics. Spatial context is critical in making accurate predictions and must be known.