A River Valley Segment Classification of Michigan Streams Based on Fish and Physical Attributes

Water resource managers are frequently interested in river and stream classification systems to generalize stream conditions and establish management policies over large spatial scales. We used fish assemblage data from 745 river valley segments to develop a two‐level, river valley segment‐scale classification system of rivers and streams throughout Michigan. Regression tree analyses distinguished 10 segment types based on mean July temperature and network catchment area and 26 segment types when channel gradient was also considered. Nonmetric multidimensional scaling analyses suggested that fish assemblages differed among segment types but were only slightly influenced by channel gradient. Species that were indicative of specific segment types generally had habitat requirements that matched segment attributes. A test of classification strength using fish assemblage data from an additional 77 river valley segments indicated that the classification system performed significantly better than random groupings of river valley segments. Our classification system for river valley segments overcomes several weaknesses of the classifications previously used in Michigan, and our approach may prove beneficial for developing classifications elsewhere.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/141625/1/tafs1621.pd

Classifying Regional Variation in Thermal Regime Based on Stream Fish Community Patterns

Although the importance of water temperature to the ecology of stream fishes is well documented, relatively little information is available on the extent of regional variation in thermal regime and its influence on stream fish distribution and abundance patterns. In streams draining the heterogeneous glacial landscape of Michigan’s Lower Peninsula, regional variation in summer mean temperature and temperature fluctuation is among the highest reported in the literature. We developed a habitat classification to simplify the description of thermal regimes and to describe the relationships between available thermal regimes and distribution patterns of stream fishes. Changes in community composition, species richness, and standing stocks of key fish species occurred across gradients in mean temperature and temperature fluctuation. These changes were used to identify three mean temperature categories (cold, <19°C; cool, 19–<22°C; and warm, ≥22°C) and three temperature fluctuation categories (stable, <5°C; moderate, 5–<10°C; and extreme, ≥10°C). The combination of these categories resulted in a 3 × 3 matrix with nine discrete thermal regimes. The classification developed in this study provides a framework for descriptions of the realized thermal niche of stream fishes, and can be used as a baseline for measurement of changes in distribution patterns associated with future climate warming. Our results suggest that observed differences in community structure among sites are largely attributable to spatial variation in mean temperature and temperature fluctuation. Thus, accounting for the linkage between regional variation in thermal regime and fish community structure should improve our ability to effectively assess and manage stream resources.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/141912/1/tafs0018.pd

Classification Tree Models for Predicting Distributions of Michigan Stream Fish from Landscape Variables

Traditionally, fish habitat requirements have been described from local‐scale environmental variables. However, recent studies have shown that studying landscape‐scale processes improves our understanding of what drives species assemblages and distribution patterns across the landscape. Our goal was to learn more about constraints on the distribution of Michigan stream fish by examining landscape‐scale habitat variables. We used classification trees and landscape‐scale habitat variables to create and validate presence‐absence models and relative abundance models for Michigan stream fishes. We developed 93 presence‐absence models that on average were 72% correct in making predictions for an independent data set, and we developed 46 relative abundance models that were 76% correct in making predictions for independent data. The models were used to create statewide predictive distribution and abundance maps that have the potential to be used for a variety of conservation and scientific purposes.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/141481/1/tafs0976.pd

Developing User‐Friendly Habitat Suitability Tools from Regional Stream Fish Survey Data

We developed user‐friendly fish habitat suitability tools (plots) for fishery managers in Michigan; these tools are based on driving habitat variables and fish population estimates for several hundred stream sites throughout the state. We generated contour plots to show patterns in fish biomass for over 60 common species (and for 120 species grouped at the family level) in relation to axes of catchment area and low‐flow yield (90% exceedance flow divided by catchment area) and also in relation to axes of mean and weekly range of July temperatures. The plots showed distinct patterns in fish habitat suitability at each level of biological organization studied and were useful for quantitatively comparing river sites. We demonstrate how these plots can be used to support stream management, and we provide examples pertaining to resource assessment, trout stocking, angling regulations, chemical reclamation of marginal trout streams, indicator species, instream flow protection, and habitat restoration. These straightforward and effective tools are electronically available so that managers can easily access and incorporate them into decision protocols and presentations.Received April 9, 2010; accepted November 8, 2010Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/141005/1/nafm0041.pd

Population Biology of Steelhead in the Little Manistee River, Michigan.

Large numbers of steelhead (Salmo gairdneri) annually migrate into many of the rivers located in Michigan's northwestern lower peninsula. Knowledge of the magnitude and dynamics of wild steelhead populations in these rivers is limited. During 1981-1986 I examined the characteristics and dynamics of one of these populations by quantitatively assessing three life stages: parr, emigrant, and returning adult. Annual densities of age-1+ parr were relatively high and extremely consistent--this consistency was apparently related to an abundance of spawners and stable river discharge. Emigrant populations consisted mostly of age-2 smolts. Smolts were relatively abundant and large. Smolt migrations peaked in mid-May. Overwinter survival to age-2 smolts varied from 13 to 90%, resulting in smolt yields ranging from 10,000 to 72,000. Minimum estimates of annual adult runs during 1979-1986 ranged from 5,800 to 19,800 fish. Adult abundance was high relative to other Great Lakes populations. Returning adult populations showed consistent age structures, sex ratios, and size at lake age. Most returning fish were maiden spawners. Upstream migrations took place during fall-winter and spring periods, while spawning occurred during late winter and spring. Returns of a marked cohort showed that 71% of the returning adults were produced in the river. Minimum estimates of lake survival for two smolt cohorts were 48 and 17%, suggesting that survival in Lake Michigan is extremely high. Fluctuations in adult abundance were apparently influenced both by smolt abundance and by factors which affected the population during lake life. The latter may have included smolt density-dependent survival and r and om environmental effects. The biology of the study population likely represents that of populations in rivers located in Michigan's northwestern lower peninsula. These rivers provide spawning and rearing conditions similar to the study river and empty into Lake Michigan. Management efforts need to focus on the preservation and enhancement of these valuable populations.Ph.D.ZoologyAquatic sciencesUniversity of Michiganhttp://deepblue.lib.umich.edu/bitstream/2027.42/161321/1/8702831.pd

Reconciling landscape and local views of aquatic communities: lessons from Michigan trout streams

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/71475/1/j.1365-2427.1997.00152.x.pd

Distributions of Stream Fishes and their Relationship to Stream Size and Hydrology in Michigan’s Lower Peninsula

We examined the distribution and abundance patterns of 69 fish species that commonly occur in the rivers of Michigan’s lower peninsula to develop a simple, empirically based model for describing fish assemblages. We used cluster analysis to group fishes that shared similar abundance patterns at 226 stream sites. The 17 clusters we identified explained about 39% of the variation in species abundances among the stream sites, providing a reasonable, albeit simplified, picture of general associations of fishes in lower Michigan streams. Known ecological differences among species and further analyses suggested that a measure of cluster abundance should not be used to predict the abundances of its constituent species. We selected catchment area (CA) and low‐flow yield (LFY; 90% exceedence flow divided by catchment area) as axes for plotting fish distributions and rivers because these variables link catchment‐scale features of the landscape to multiple, site‐scale characteristics of stream habitat (e.g., temperature, velocity, and depth) important to fishes. As a measure of groundwater loading to streams, LFY, which integrates the geological, landform, and soil characteristics of catchments, reached its highest values in basins predominated by highly permeable soils and relatively steep topography. Plots of fish clusters and species abundances on LFY‐CA axes provided insight into the structure of fish assemblages in lower Michigan streams. When plotted on LFY−CA axes, the 17 fish clusters were distributed in a meaningful pattern that reflected stream size and temperature preferences of constituent species. The LFY‐CA axes provided an empirically derived framework for comparing Michigan streams and for assessing the physical and biological potential of different river reaches. This has allowed fishery managers to better explain, justify, and build public support for river management plans and actions. Although the relationships among LFY, CA, and fish abundances we describe are specific to lower Michigan streams, our approach could be used to develop similar models specific to other regions.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/141068/1/tafs0070.pd

A GIS Model of Subsurface Water Potential for Aquatic Resource Inventory, Assessment, and Environmental Management

Biological, chemical, and physical attributes of aquatic ecosystems are often strongly influenced by groundwater sources. Nonetheless, widespread access to predictions of subsurface contributions to rivers, lakes, and wetlands at a scale useful to environmental managers is generally lacking. In this paper, we describe a “neighborhood analysis” approach for estimating topographic constraints on spatial patterns of recharge and discharge and discuss how this index has proven useful in research, management, and conservation contexts. The Michigan Rivers Inventory subsurface flux model (MRI-DARCY) used digital elevation and hydraulic conductivity inferred from mapped surficial geology to estimate spatial patterns of hydraulic potential. Model predictions were calculated in units of specific discharge (meters per day) for a 30-m 2 -cell raster map and interpreted as an index of potential subsurface water flux (shallow groundwater and event through-flow). The model was evaluated by comparison with measurements of groundwater-related attributes at watershed, stream segment, and local spatial scales throughout Lower Michigan (USA). Map-based predictions using MRI-DARCY accounted for 85% of the observed variation in base flow from 128 USGS gauges, 69% of the observed variation in discharge accrual from 48 river segments, and 29% of the residual variation in local groundwater flux from 33 locations as measured by hyporheic temperature profiles after factoring out the effects of climate. Although it does not incorporate any information about the actual water table surface, by quantifying spatial variation of key constraints on groundwater-related attributes, the model provides strata for more intensive study, as well as a useful spatial tool for regional and local conservation planning, fisheries management, wetland characterization, and stream assessment.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/48165/1/267_2003_Article_18.pd

Comparison between Model‐Predicted and Field‐Measured Stream Habitat Features for Evaluating Fish Assemblage‐Habitat Relationships

The use of model‐predicted, local‐scale habitat data as inputs in analyses intended to evaluate multiscale fish assemblage‐habitat relationships in streams has become increasingly common as the scale at which such studies are conducted has increased. We used fish assemblage and habitat data from 208 wadeable streams in Wisconsin and Michigan to determine whether model‐predicted habitat data would yield results similar to those of field‐measured data in multiscale analyses of fish assemblage‐habitat relationships. Predictions of local habitat features from landscape variables were generated by means of generalized additive modeling with likelihood‐based boosting. Relationships between fish assemblage measures and landscape and local habitat features were studied via partial constrained multivariate ordination analyses. The total variation explained in the fish assemblage data sets was similar for model‐predicted local habitat features and field‐measured data, as was the proportion of variation explained that was due independently to local and regional (i.e., landscape) habitat features. We observed dissimilar results in the magnitude of ordination scores for local habitat features and the directional relationships between local habitat ordination scores and individual species and assemblage metric scores. Our findings indicate that model‐predicted, local‐scale habitat data can be useful for evaluating the relative strengths of local and regional habitat features in structuring fish assemblages, but caution may be necessary when evaluating species‐habitat or assemblage metric‐habitat relationships.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/141812/1/tafs0580.pd