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Jennifer S. Sauer

Publications and source records attributed to Jennifer S. Sauer.

6 recordsLinked to original sources

Can data from disparate long-term fish monitoring programs be used to increase our understanding of regional and continental trends in large river assemblages?

Understanding trends in the diverse resources provided by large rivers will help balance tradeoffs among stakeholders and inform strategies to mitigate the effects of landscape scale stressors such as climate change and invasive species. Absent a cohesive coordinated effort to assess trends in important large river resources, a logical starting point is to assess our ability to draw inferences from existing efforts. In this paper, we use a common analytical framework to analyze data from five disparate fish monitoring programs to better understand the nature of spatial and temporal trends in large river fish assemblages. We evaluated data from programs that monitor fishes in the Colorado, Columbia, Illinois, Mississippi, and Tallapoosa rivers using non-metric dimensional scaling ordinations and associated tests to evaluate trends in fish assemblage structure and native fish biodiversity. Our results indicate that fish assemblages exhibited significant spatial and temporal trends in all five of the rivers. We also document native species diversity trends that were variable within and between rivers and generally more evident in rivers with higher species richness and programs of longer duration. We discuss shared and basin-specific landscape level stressors. Having a basic understanding of the nature and extent of trends in fish assemblages is a necessary first step towards understanding factors affecting biodiversity and fisheries in large rivers.

PLoS ONE↗

Long-term fish monitoring in large rivers: Utility of “benchmarking” across basins

In business, benchmarking is a widely used practice of comparing your own business processes to those of other comparable companies and incorporating identified best practices to improve performance. Biologists and resource managers designing and conducting monitoring programs for fish in large river systems tend to focus on single river basins or segments of large rivers, missing opportunities to learn from those conducting fish monitoring in other rivers. We briefly examine five long-term fish monitoring programs in large rivers in the United States (Colorado, Columbia, Mississippi, Illinois, and Tallapoosa rivers) and identify opportunities for learning across programs by detailing best monitoring practices and why these practices were chosen. Although monitoring objectives, methods, and program maturity differ between each river system, examples from these five case studies illustrate the important role that long-term monitoring programs play in interpreting temporal and spatial shifts in fish populations for both established objectives and newly emerging questions. We suggest that deliberate efforts to develop a broader collaborative network through benchmarking will facilitate sharing of ideas and development of more effective monitoring programs.

Colorado River, Columbia River, Illinois River, Mi↗

Monitoring rationale, strategy, issues, and methods: UMRR-EMP LTRMP fish component

The Long Term Resource Monitoring Program (LTRMP), an element of the multiagency partnership Upper Mississippi River Restoration-Environmental Management Program, has been monitoring fishes in the Upper Mississippi River System (UMRS) for over two decades, using scientific and highly standardized methods. Today, the LTRMP’s data assets represent one of the world’s largest and most extensive datasets on a great river. Methods and procedures used over the past two decades have been documented and have proven a key tool towards gaining data that are (a) scientifically valid, (b) comparable over time, and (c) comparable over space. These procedures manuals coordinate and standardize methods, procedures, and field behaviors in the execution of long-term monitoring, permitting the informed management and control of important sources of error actually under program control. As LTRMP databases have matured in scope and accumulated more years' worth of data, their utility in research and management in the UMRS basin has increased notably. To maximize their utility, data users need not only be aware of “how the data were collected,” as portrayed in the procedures manuals, but also “why the data were collected in the way they were, at the scales they were, and in the manner that they were.” Whereas the procedures manuals contribute information as to the “how” the data were gained, this document seeks to contribute information as to the “why.” As such, this document is intended to be a companion document to the procedures manuals. Herein, we present information on the rationale for monitoring nearly one-fifth of the entire North American freshwater fish fauna (representing the greatest freshwater fish diversity on the planet at temperate latitudes); strategies employed and their reasoning; and discussions on issues associated with the sampling design itself, data arising therefrom, and uses of those data in different contexts.

Illinois;Iowa;Minnesota;Montana;Wisconsin↗

Finding the Exotic Faucet Snail (Bithynia tentaculata): Investigation of Waterbird Die-Offs on the Upper Mississippi River National Wildlife and Fish Refuge

Beginning in 2002, there have been major waterbird die-offs every spring and fall in Lake Onalaska (Navigation Pool 7 of the Upper Mississippi River) located near La Crosse, Wisconsin. This area is part of the Upper Mississippi River National Wildlife and Fish Refuge (UMR Refuge) and lies within the Mississippi Flyway, through which an estimated 40 percent of the continent's waterfowl migrate. Through the 2006 spring migration, total mortality on the UMR Refuge was estimated at 22,000 to 26,000 birds, primarily American coots (Fulica americana) and lesser scaup (Aythya affinis). Two trematodes (Sphaeridiotrema globulus and Cyathocotyle bushiensis) that use the exotic faucet snail (Bithynia tentaculata) as an intermediate host were found to infect and kill the waterbirds. The faucet snail was introduced into the United States from Europe in the late 1800s. Because Lake Onalaska is a major spring and fall stop-over area for waterfowl in the Mississippi Flyway, concerns were raised that the snail and trematodes may be spreading to other waterfowl stop-over areas on the river. Exploratory sampling for faucet snails was conducted in 2005 and 2006 in navigation Pools 4-9 (excluding Pool 5a which is located between Pools 5 and 6), 11, and 13. Infected snails were found in all the sampled pools except Pool 6. To our knowledge, these are the first records of faucet snails and associated trematodes beyond those found in Pool 7, Lake Onalaska. Waterbird die-offs are becoming a UMR Refuge-wide problem. Information obtained through research and monitoring, including the identification of the origin of infections in snails and birds and the role various environmental factors have on this process, should help guide managers to develop effective mitigation and control measures.

Open-File Report↗

Modelling habitat associations with fingernail clam (Family: Sphaeriidae) counts at multiple spatial scales using hierarchical count models

1. Macroinvertebrate count data often exhibit nested or hierarchical structure. Examples include multiple measurements along each of a set of streams, and multiple synoptic measurements from each of a set of ponds. With data exhibiting hierarchical structure, outcomes at both sampling (e.g. within stream) and aggregated (e.g. stream) scales are often of interest. Unfortunately, methods for modelling hierarchical count data have received little attention in the ecological literature. 2. We demonstrate the use of hierarchical count models using fingernail clam (Family: Sphaeriidae) count data and habitat predictors derived from sampling and aggregated spatial scales. The sampling scale corresponded to that of a standard Ponar grab (0.052 m 2 ) and the aggregated scale to impounded and backwater regions within 38–197 km reaches of the Upper Mississippi River. Impounded and backwater regions were resampled annually for 10 years. Consequently, measurements on clams were nested within years. Counts were treated as negative binomial random variates, and means from each resampling event as random departures from the impounded and backwater region grand means. 3. Clam models were improved by the addition of covariates that varied at both the sampling and regional scales. Substrate composition varied at the sampling scale and was associated with model improvements, and reductions (for a given mean) in variance at the sampling scale. Inorganic suspended solids (ISS) levels, measured in the summer preceding sampling, also yielded model improvements and were associated with reductions in variances at the regional rather than sampling scales. ISS levels were negatively associated with mean clam counts. 4. Hierarchical models allow hierarchically structured data to be modelled without ignoring information specific to levels of the hierarchy. In addition, information at each hierarchical level may be modelled as functions of covariates that themselves vary by and within levels. As a result, hierarchical models provide researchers and resource managers with a method for modelling hierarchical data that explicitly recognises both the sampling design and the information contained in the corresponding data.

Illinois, Iowa, Minnesota, Wisconsin↗

Biota of the upper Mississippi River ecosystem

The Mississippi River is one of the world's major river systems in size, habitat and biotic diversity, and biotic productivity. The navigable Upper Mississippi River, extending 1,370 km (850 mi) from St. Anthony Falls (Minnesota) to the confluence with the Ohio River, has been impounded by 27 locks and dams to enhance commercial navigation. The reach between two consecutive locks and dams is termed a "pool." The upstream portions of many pools are similar to the unimpounded river, whereas the downstream reaches are similar to reservoirs.

Upper Mississippi River↗