Development and evaluation of habitat suitability criteria for use in the instream flow incremental methodology

Abstract

The Instream Flow Incremental Methodology (IFIM) is a habitat-based tool used to evaluate the environmental consequences of various water and land use practices. As such, knowledge about the conditions that provide favorable habitat for a species, and those that do not, is necessary for successful implementation of the methodology. In the context of IFIM, this knowledge is defined as habitat suitability criteria: characteristic behavioral traits of a species that are established as standards for comparison in the decision-making process. Habitat suitability criteria may be expressed in a variety of types and formats. The type, or category, refers to the procedure used to develop the criteria. Category I criteria are based on professional judgment, with little or no empirical data. Category II criteria have as their source, microhabitat data collected at locations where target organisms are observed or collected. These are called “utilization” functions because they are based on observed locations that were used by the target organism. These functions tend to be biased by the environmental conditions that were available to the fish or invertebrates at the time they were observed. Correction of the utilization function for environmental availability creates category III, or “preference” criteria, which tend to be much less site specific than category II criteria. There are also several ways to express habitat suitability in graphical form. The binary format establishes a suitable range for each variable as it pertains to a life stage of interest, and is presented graphically as a step function. The quality rating for a variable is 1.0 if it falls within the range of the criteria, and 0.0 if it falls outside the range. The univariate curve format established both the usable range and the optimum range for each variable, with conditions of intermediate usability expressed along the portion between the tails and the peak of the curve. Multivariate probability density functions, which can be used to compute suitability for several variables simultaneously, are conveyed as three dimensional figures with suitability on the z-axis, and two independent variables on the x-y plane. These functions are useful for incorporating interactive terms between two or more variable. Such interactions can also be demonstrated using conditional criteria, which are stratified by cover type or substrate size. Conditional criteria may be of any category or format, but are distinguishable by two or more sets of functional relationships for each life stage.