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habitat suitability index models and instream flow suitability curves

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4. Deep (mean depth> 15 m); <strong>and</strong>5. Low fertility (TDS< 125 but> 50 mg/l).HSI = number of attributes present5Regression ModelsLayher (1983) developed regression equations to predict st<strong>and</strong>ing crop ofspotted bass in streams in Kansas <strong>and</strong> Oklahoma. In Kansas, <strong>habitat</strong> variablesof turbidity, mean depth, minimum width, mean width, pH, percent riffles, <strong>and</strong>temperature accounted for the significant variation in st<strong>and</strong>ing crop. Meanwidth, pH, turbidity, temperature, nitrates, mean depth, <strong>and</strong> minimum widthexplained the variation in st<strong>and</strong>ing crop in Oklahoma streams. Layher (1983)reports the methods of analysis <strong>and</strong> provides guidance on potential use of the<strong>models</strong> to predict st<strong>and</strong>ing crop. The regression equations utilize SI's derivedfrom SI graphs as the independent variables. Graphs <strong>and</strong> equations arepresented in Layher (1983). Further information on their use may be obtainedfrom: William G. Layher, Environmental Services Section, Kansas Fish <strong>and</strong>Game, Pratt, Kansas 67124.Aggus <strong>and</strong> Morais (1979) developed regression equations to predict st<strong>and</strong>ingcrop of spotted bass in reservoirs from easily obtainable preconstructiondata. These authors discuss procedures for converting measured or predictedst<strong>and</strong>ing crop values for spotted bass to HSI's.Discriminant Analysis ModelsLayher (1983) used discriminant analysis to determine the relationshipsbetween <strong>habitat</strong> variables <strong>and</strong> presence or absence of spotted bass in streamsin Kansas <strong>and</strong> Oklahoma. The discriminant analysis <strong>models</strong> showed high reliabilityfor predicting presence or absence of spotted bass within each data set.When the Kansas model was applied to Oklahoma streams, however, many misclassificationsresulted, suggesting that the <strong>models</strong> are reliable only overlimited, homogeneous geographical areas. Further information on use of thesediscriminant <strong>models</strong> can be obtained by contacting William G. Layher at theaddress listed in the Regression Models section.INSTREAM FLOW INCREMENTAL METHODOLOGY (IFIM)The U.S. Fish <strong>and</strong> Wildlife Service's Instream Flow Incremental Methodology(IFIM), as outlined by Bovee (1982), is a set of ideas used to assess <strong>instream</strong><strong>flow</strong> problems. The Physical Habitat Simulation System (PHABSIM), described byMilhous et al. (1984), is one component of IFIM that can be used by investigatorsinterested in determining the amount of available <strong>instream</strong> <strong>habitat</strong>21

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