Assessing ecosystem sustainability and management using fuzzy logic

Concern about the negative impacts of growth and development on protected area ecosystems has drawn attention to methods for assessing ecosystem sustainability and management. Existing non-stochastic and stochastic methods for assessing weak and strong sustainability of ecosystems have several limitations. The non-stochastic method does not account for errors in measuring attributes, stochastic variability in attributes, and uncertainty about the relationship between ecosystem attributes and states (degrees) of ecosystem sustainability. Although the stochastic method better accounts for errors in measuring attributes, and stochastic variability in attributes than the non-stochastic method, it requires information about the probability distributions of attributes for different states of sustainability. Such information is not readily available. The fuzzy logic method overcomes the limitations of the non-stochastic and stochastic methods, but requires fuzzifying an index of sustainability in the case of weak sustainability, fuzzifying individual attributes in the case of strong sustainability, specifying and estimating membership functions for low, medium and high ecosystem sustainability, selecting a rule to determine whether an ecosystem is strongly sustainable based on the conclusions for fuzzy propositions, and specifying fuzzy sets for truth qualifiers when evaluating conditional and qualified propositions. Whether the benefits outweigh the costs of using the fuzzy logic method depends on the knowledge, data, and information available about the ecosystem, the expertise of the persons doing the assessment, and other factors. The non-stochastic, stochastic and fuzzy logic methods can be used to rank management alternatives and select a preferred alternative in cases where the current state of the ecosystem is unsustainable. Ranking management alternatives using a fuzzy logic method requires ordering the fuzzy scores for alternatives. All three methods for ranking management alternatives call for a group preference ordering for management alternatives in cases where individuals in the group have different preferences for alternatives. (c) 2006 Elsevier B.V. All rights reserved.