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Catherine M. Riseng

Publications and source records attributed to Catherine M. Riseng.

6 recordsLinked to original sources

Predicting Lake Huron Dreissena spp. spatial distribution patterns from environmental characteristics

Invasive dreissenid mussels ( Dreissena polymorpha and Dreissena rostriformis bugensis ) have altered Great Lakes ecosystems through a multitude of effects on benthic habitats, food web structure, and nutrient cycling. This study explores whether spatially continuous geographic data of environmental factors can be utilized to predict Dreissena spp. spatial distributions on a lake-wide scale. Categorical variables were also assessed for significant relationships with Dreissena spp. biomass. Point observations from the 2017 Lake Huron benthic survey under the Cooperative Science and Monitoring Initiative (CSMI) were utilized for in situ measurements of dreissenid presence and biomass at 119 sites across Lake Huron. Basin, bathymetric zone, and tributary influence were found to have statistically significant relationships to dreissenid biomass. A boosted regression tree (BRT) model (ROC score 0.707) was developed to spatially predict dreissenid presence probability across Lake Huron from six environmental explanatory variables: April, May, and October chlorophyll, June dissolved organic carbon, January bottom temperature, and May bottom temperature. The importance of food availability and bottom temperature illuminated relationships between dreissenid mussels and periods of benthic-pelagic mixing in the spring and fall seasons. Future models could be improved through advancements in survey technology for improved geographic characterization of mussel habitat characteristics and environmental constraints.

Lake Huron

Interactive mapping of nonindigenous species in the Laurentian Great Lakes

Nonindigenous species pose significant risks to the health and integrity of ecosystems around the world. Tracking and communicating the spread of these species has been of interest to ecologists and environmental managers for many years, particularly in the bi-national Laurentian Great Lakes of North America. In this paper, we introduce the Great Lakes Aquatic Nonindigenous Species Information System (GLANSIS) Map Explorer. The Map Explorer provides access to records of documented nonindigenous species and their spatial distributions. Users may view the distributions of well-known nonindigenous species (such as zebra mussels) as well as perform custom queries. Additional map layers allow users to compare the distribution of nonindigenous species to environmental conditions. This tool serves to communicate knowledge to diverse stakeholder groups and to enable further in-depth research on nonindigenous species.

Laurentian Great Lakes

Are changes in lower trophic levels limiting prey-fish biomass and production in Lake Michigan?

To improve understanding of how recent changes in lower trophic levels in Lake Michigan could be affecting prey-fish biomass and production, the Lake Michigan Committee (LMC) convened a Lower Trophic Level Task Group and provided several charges that are responded to in this report. First, we compiled a comprehensive summary of lower trophiclevel data in Lake Michigan, separating out nearshore versus offshore trends over time. Declining trends were prevalent in offshore time series for phosphorus, chlorophyll a, biomass of total crustacean zooplankton, biomass of herbivorous cladocerans, and density of Diporeia spp. In the nearshore, declining trends were evident only for biomass of cyclopoid copepods and density of Diporeia spp. Second, we hypothesized specific mechanisms by which changes in lower trophic levels could affect prey-fish biomass and production and described the degree of empirical support for each mechanism. The best-supported hypothesis was that declining invertebrate prey (especially Diporeia spp.) was responsible for declining growth of prey fish, especially over the last decade when competition for prey resources should otherwise have been lessened due to declining prey-fish densities. As a result, declining growth potentially limits the prey-fish biomass that could have been attained had growth been maintained at the levels that were achieved in the 1980s and earlier. Third, we prioritized several lower trophic-level indicators that fishery managers could use to better inform decision making. The top-ranked indicator was annual reporting of Alewife (Alosa pseudoharengus) condition. Fourth, we prioritized the key monitoring and research gaps that limit our current understanding of how lower trophic levels influence fish production. The highest-priority monitoring gap was coordinated sampling of the nearshore, which, if accomplished, would complement annual reporting on offshore sampling. The top-ranked knowledge gap was identifying bottlenecks that regulate fish recruitment, given that recent changes in zooplankton distribution and abundance could be suppressing survival of larval fish and, ultimately, the biomass and production of prey fish. We provided three specific recommendations for the LMC to consider as they seek to better incorporate lower trophiclevel changes into their management decision process: (1) implement a coordinated and standardized nearshore monitoring program, (2) encourage funding agencies to use our prioritized lists in their decision processes, and (3) foster the already improved dialogue between those researching lower trophic levels and those researching fisheries.

Miscellaneous Publication

Landscape prediction and mapping of game fish biomass, an ecosystem service of Michigan rivers

The increased integration of ecosystem service concepts into natural resource management places renewed emphasis on prediction and mapping of fish biomass as a major provisioning service of rivers. The goals of this study were to predict and map patterns of fish biomass as a proxy for the availability of catchable fish for anglers in rivers and to identify the strongest landscape constraints on fish productivity. We examined hypotheses about fish responses to total phosphorus (TP), as TP is a growth-limiting nutrient known to cause increases (subsidy response) and/or decreases (stress response) in fish biomass depending on its concentration and the species being considered. Boosted regression trees were used to define nonlinear functions that predicted the standing crops of Brook Trout Salvelinus fontinalis , Brown Trout Salmo trutta , Smallmouth Bass Micropterus dolomieu , panfishes (seven centrarchid species), and Walleye Sander vitreus by using landscape and modeled local-scale predictors. Fitted models were highly significant and explained 22–56% of the variation in validation data sets. Nonlinear and threshold responses were apparent for numerous predictors, including TP concentration, which had significant effects on all except the Walleye fishery. Brook Trout and Smallmouth Bass exhibited both subsidy and stress responses, panfish biomass exhibited a subsidy response only, and Brown Trout exhibited a stress response. Maps of reach-specific standing crop predictions showed patterns of predicted fish biomass that corresponded to spatial patterns in catchment area, water temperature, land cover, and nutrient availability. Maps illustrated predictions of higher trout biomass in coldwater streams draining glacial till in northern Michigan, higher Smallmouth Bass and panfish biomasses in warmwater systems of southern Michigan, and high Walleye biomass in large main-stem rivers throughout the state. Our results allow fisheries managers to examine the biomass potential of streams, describe geographic patterns of fisheries, explore possible nutrient management targets, and identify habitats that are candidates for species management.

Michigan

A spatial classification and database for management, research, and policy making: The Great Lakes aquatic habitat framework

Managing the world's largest and most complex freshwater ecosystem, the Laurentian Great Lakes, requires a spatially hierarchical basin-wide database of ecological and socioeconomic information that is comparable across the region. To meet such a need, we developed a spatial classification framework and database — Great Lakes Aquatic Habitat Framework (GLAHF). GLAHF consists of catchments, coastal terrestrial, coastal margin, nearshore, and offshore zones that encompass the entire Great Lakes Basin. The catchments captured in the database as river pour points or coastline segments are attributed with data known to influence physicochemical and biological characteristics of the lakes from the catchments. The coastal terrestrial zone consists of 30-m grid cells attributed with data from the terrestrial region that has direct connection with the lakes. The coastal margin and nearshore zones consist of 30-m grid cells attributed with data describing the coastline conditions, coastal human disturbances, and moderately to highly variable physicochemical and biological characteristics. The offshore zone consists of 1.8-km grid cells attributed with data that are spatially less variable compared with the other aquatic zones. These spatial classification zones and their associated data are nested within lake sub-basins and political boundaries and allow the synthesis of information from grid cells to classification zones, within and among political boundaries, lake sub-basins, Great Lakes, or within the entire Great Lakes Basin. This spatially structured database could help the development of basin-wide management plans, prioritize locations for funding and specific management actions, track protection and restoration progress, and conduct research for science-based decision making.

Great Lakes

Changing ecosystem dynamics in the Laurentian Great Lakes: Bottom-up and top-down regulation

Understanding the relative importance of top-down and bottom-up regulation of ecosystem structure is a fundamental ecological question, with implications for fisheries and water-quality management. For the Laurentian Great Lakes, where, since the early 1970s, nutrient inputs have been reduced, whereas top-predator biomass has increased, we describe trends across multiple trophic levels and explore their underlying drivers. Our analyses revealed increasing water clarity and declines in phytoplankton, native invertebrates, and prey fish since 1998 in at least three of the five lakes. Evidence for bottom-up regulation was strongest in Lake Huron, although each lake provided support in at least one pair of trophic levels. Evidence for top-down regulation was rare. Although nonindigenous dreissenid mussels probably have large impacts on nutrient cycling and phytoplankton, their effects on higher trophic levels remain uncertain. We highlight gaps for which monitoring and knowledge should improve the understanding of food-web dynamics and facilitate the implementation of ecosystem-based management.

Illinois, Indiana, Michigan, Minnesota, new York,