Geology topics

F. Joseph Margraf

Publications and source records attributed to F. Joseph Margraf.

6 recordsLinked to original sources

USGS2016

Who Knew? Inconnu

In 1999, I moved to Alaska to serve as unit leader of the U.S. Geological Survey Alaska Cooperative Fish and Wildlife Research Unit and professor of fisheries in the School of Fisheries and Ocean Sciences at the University of Alaska Fairbanks. What was unusual about this move was that before this I was an easterner and southerner, having done my graduate work in fisheries at Texas A&M University and been stationed in the Coop Unit Program in Ohio, West Virginia, and Maryland. I had never worked with salmonids of any sort. To me fish with adipose fins also had whiskers! I suddenly found myself working in the land of salmon experts, and I didn't even reliably know the names—scientific, common, or colloquial—of the five (or is it six?) common Pacific salmon species in Alaska. I had to quickly find a research niche that probably didn't involve salmon.

Fisheries↗

USGS2015

Bioelectrical impedance analysis: A new tool for assessing fish condition

Bioelectrical impedance analysis (BIA) is commonly used in human health and nutrition fields but has only recently been considered as a potential tool for assessing fish condition. Once BIA is calibrated, it estimates fat/moisture levels and energy content without the need to kill fish. Despite the promise held by BIA, published studies have been divided on whether BIA can provide accurate estimates of body composition in fish. In cases where BIA was not successful, the models lacked the range of fat levels or sample sizes we determined were needed for model success (range of dry fat levels of 29%, n = 60, yielding an R 2 of 0.8). Reduced range of fat levels requires an increased sample size to achieve that benchmark; therefore, standardization of methods is needed. Here we discuss standardized methods based on a decade of research, identify sources of error, discuss where BIA is headed, and suggest areas for future research.

Fisheries↗

USGS2015

Chronicling long-term predator responses to a shifting forage base in Chesapeake Bay: an energetics approach

The population of Striped Bass Morone saxatilis in Chesapeake Bay has increased significantly since the 1980s because of management efforts while the relative abundance of some key prey fish has declined since the 1970s. We examined the trophic interactions and prey consumption patterns of Striped Bass in Chesapeake Bay to determine how Striped Bass have responded to changing prey resources. Seasonal diet, growth, and thermal data were collected from 1955 to 1959, 1990 to 1992, and 1998 to 2001; these data were coupled with a bioenergetics model approach to characterize temporal patterns in prey consumption for Striped Bass. The estimates were compared across each period to build a historical prey consumption profile from 1955 to 2001. Prey consumption dynamics for Striped Bass have changed dramatically between 1955 and 2001. In general, Striped Bass in the early and late 1990s consumed less Atlantic Menhaden Brevoortia tyranus and more Bay Anchovy Anchoa mitchilli than during the 1950s. The largest differences in consumption were observed in the younger age-classes. During 1998–2001, age-1 and age-2 Striped Bass consumed, respectively, 15.5 and 11.9 times less Atlantic Menhaden than during the 1950sand 12.2 and 7.2 less than during 1990–1992. Bay Anchovy were almost absent in the diet of bass age 3 and older during the 1950s but were consumed by the age-3+ group during 1990–1992 and to a greater extent during 1998–2001. Age-3+ Striped Bass during 1998–2001, on average, consumed twice as much Bay Anchovy than during 1990–1992. Blue crab Callinectes sappidus were consumed only by age 2 in the 1950s and 1990–1992 and by ages 2 and older in 1998–2001. Age-2 bass consumed 8.8 more blue crab in 1990–1992 and 7.5 times more in 1998–2001 than during the 1950s. The patterns in the consumption of Atlantic Menhaden coincided with increased consumption of Bay Anchovy and blue crab, possibly as a result of the declines in Atlantic Menhaden relative abundance in Chesapeake Bay. The difference in consumption was also evident in the total energy consumed; age-1 and age-6 Striped Bass consumed 1.6 times more energy in 1955–1959 than during 1998–2001. Our research demonstrates how the elements of Striped Bass feeding, including diet composition, amount of food eaten, and consumption rates, are affected by prey resources.

Maryland, Virginia↗

USGS2012

A remote-sensing, GIS-based approach to identify, characterize, and model spawning habitat for fall-run chum salmon in a sub-arctic, glacially fed river

At northern limits of a species’ distribution, fish habitat requirements are often linked to thermal preferences, and the presence of overwintering habitat. However, logistical challenges and hydrologic processes typical of glacial systems could compromize the identification of these habitats, particularly in large river environments. Our goal was to identify and characterize spawning habitat for fall-run chum salmon Oncorhynchus keta and model habitat selection from spatial distributions of tagged individuals in the Tanana River, Alaska using an approach that combined ground surveys with remote sensing. Models included braiding, sinuosity, ice-free water surface area (indicating groundwater influence), and persistent ice-free water (i.e., consistent presence of ice-free water for a 12-year period according to satellite imagery). Candidate models containing persistent ice-free water were selected as most likely, highlighting the utility of remote sensing for monitoring and identifying salmon habitat in remote areas. A combination of ground and remote surveys revealed spatial and temporal thermal characteristics of these habitats that could have strong biological implications. Persistent ice-free sites identified using synthetic aperture radar appear to serve as core areas for spawning fall chum salmon, and the importance of stability through time suggests a legacy of successful reproductive effort for this homing species. These features would not be captured with a one-visit traditional survey but rather required remote-sensing monitoring of the sites through time.

Transactions of the American Fisheries Society↗

USGS2005

Non-lethal estimation of body composition of Yukon River salmon

Because of the importance of Chinook salmon to commercial and subsistence fisheries on the Yukon River, further study of the factors that may affect the success of this species and our ability to manage the fisheries is warranted. Critical to these studies is the determination of the amount of lipids (fat) stored and available to the fish as its primary energy source for migration and spawning. Recent developments of Bioelectrical Impedance Analysis (BIA) promise a simple, non-lethal means of estimating proximate composition (e.g. fat, protein, water content) for field applications with fish. The goal of the project was to develop BIA models for Chinook salmon from the Yukon River watershed that would permit the non-lethal estimation of body proximate composition for use in field studies. Our results clearly demonstrated that BIA can be used to estimate proximate composition and energy density of salmon. While some minor refinements were suggested, the methodology can be used in a wide variety of field applications. For instance, application of the BIA models to predict energy levels of fish during their migration will allow evaluation of management programs, while also yielding data that can be used to evaluate energy use along the migratory path. Correlations of energy level with ongoing tagging, radio-tracking, and genetic studies also have the potential to allow managers and scientists to understand the relationship between fat content and distance to spawning location. These models have the potential for application to this species in other river systems. They also provide tools for a variety of other scientific investigation such as: 1) differences in energy stores in spawning and recruitment success; 2) effects of global warming on migratory salmonid stocks; and 3) differences in annual flow and temperature regiments upon migratory energy costs and resulting recruitment success.

Alaska, Yukon↗

USGS1991

Low-cost field estimation of yellow perch daily ration

We used 2 yearsˈ diel food weight data from stomachs of Lake Erie yellow perch Perca flavescens to make Elliott‐Persson (E–P) estimates of daily ration and to construct consumption response surface (CRS) regression models. The CRS models provided relatively accurate, low‐cost estimates of daily ration from only one to four fish collections – compared with nine for the E–P procedure. Besides reducing daily sampling effort, CRS models allowed flexibility in fish collection times, thus alleviating the need for 24‐h associations with sampling sites. Independent variables for CRS models included the food weight in fish stomachs from a particular collection (adjusted for water temperature) and the time of day when a fish collection was made. Accuracy of CRS model estimates of yellow perch daily ration relative to E–P estimates was evaluated with a jackknife‐like procedure. Effectiveness of CRS models arose from significant relationships that existed between food weights in yellow perch stomachs throughout certain periods of the day and average food weight in stomachs over 24 h. Similar relationships, and hence low‐cost estimation potential, are expected for other fish species with regular diel feeding activity. Because CRS models reduce time requirements in the field, they should allow more detailed coverage of important spatial and temporal variability in multiday food consumption studies for fishes. The CRS models also showed spatial robustness and a desirable capacity to estimate daily rations in years beyond those for which the models were developed.

Transactions of the American Fisheries Society↗