Empiricists and modellers use information on energy density, proximate composition, stable isotopes, fatty acids, thiamine, and bioaccumulative tracers (e.g., PCBs and mercury) to understand the state and inter-relationships of aquatic food webs. Data exist in many published and unpublished sources, but are not consolidated in an easily accessible database that would serve as a vital resource to i) provide basic estimates of these diet-derived measures of body composition, ii) understand sources of variation in the underlying data, iii) facilitate exploration and development of data proxies, and iv) assist in study design. We designed GLATAR (Great Lakes Aquatic Tissue Analysis Repository, glatar.org) to address this need. GLATAR is an open-access, searchable database linked to a web-based toolbox to visualise and generate user-defined summaries on diet-derived ecological metrics, with a focus on taxa of importance to the Great Lakes. GLATAR currently contains over 50,000 records on energy density, chemical tracers, and proximate body composition from 67 species of fish and 72 invertebrate taxa. We hope this user-friendly interface will entice others to upload their published and unpublished data to the repository, enriching the breadth of data accessible to researchers. In this way, GLATAR will become a ‘living’ and interactive resource for empiricists and modellers working in freshwater ecosystems as they make critical decisions related to growth, production, and consumption across a diverse group of economically and ecologically important aquatic species.

Life history theory examines how characteristics of organisms, such as age and size at maturity, may vary through natural selection as evolutionary responses that optimize fitness. Here we ask how predictions of age and size at maturity differ for the three classical fitness functions-intrinsic rate of natural increase r, net reproductive rate R0, and reproductive value Vx-for semelparous species. We show that different choices of fitness functions can lead to very different predictions of species behavior. In one's efforts to understand an organism's behavior and to develop effective conservation and management policies, the choice of fitness function matters. The central ingredient of our approach is the maturation reaction norm (MRN), which describes how optimal age and size at maturation vary with growth rate or mortality rate. We develop a practical geometric construction of MRNs that allows us to include different growth functions (linear growth and nonlinear von Bertalanffy growth in length) and develop two-dimensional MRNs useful for quantifying growth-mortality trade-offs. We relate our approach to Beverton-Holt life history invariants and to the Stearns-Koella categorization of MRNs. We conclude with a detailed discussion of life history parameters for Great Lakes Chinook Salmon and demonstrate that age and size at maturity are consistent with predictions using R0 (but not r or Vx) as the underlying fitness function.

Bioenergetics modeling is a widely used tool in fisheries management and research. Although popular, currently available software (i.e., Fish Bioenergetics 3.0) has not been updated in over 20 years and is incompatible with newer operating systems (i.e., 64-bit). Moreover, since the release of Fish Bioenergetics 3.0 in 1997, the number of published bioenergetics models has increased appreciably from 56 to 105 models representing 73 species. In this article, we provide an overview of Fish Bioenergetics 4.0 (FB4), a newly developed modeling application that consists of a graphical user interface (Shiny by RStudio) combined with a modeling package used in the R computing environment. While including the same capabilities as previous versions, Fish Bioenergetics 4.0 allows for timely updates and bug fixes and can be continuously improved based on feedback from users. In addition, users can add new or modified parameter sets for additional species and formulate and incorporate modifications such as habitat-dependent functions (e.g., dissolved oxygen, salinity) that are not part of the default package. We hope that advances in the new modeling platform will attract a broad range of users while facilitating continued application of bioenergetics modeling to a wide spectrum of questions in fish biology, ecology, and management.

Genetic diversity has been hypothesized to promote fitness of individuals and populations, but few studies have examined how genetic diversity varies with ontogeny. We examined patterns in population and individual genetic diversity and the effect of genetic diversity on individual fitness among life stages (adults and juveniles) and populations of captive yellow perch (Perca flavescens) stocked into two ponds and allowed to spawn naturally. Significant genetic structure developed between adults and offspring in a single generation, even as heterozygosity and allelic richness remained relatively constant. Heterozygosity had no effect on adult growth or survival, but was significantly and consistently positively related to offspring length throughout the first year of life in one pond but not the other. The largest individuals in the pond exhibiting this positive relationship were more outbred than averaged size individuals and also more closely related to one another than they were to average-sized individuals, suggesting potential heritability of body size or spawn timing effects. These results indicate that the influence of heterozygosity may be mediated through an interaction, likely viability selection, between ontogeny and environment that is most important during early life. In addition, populations may experience significant genetic change within a single generation in captive environments, even when allowed to reproduce naturally. Accounting for the dynamic influences of genetic diversity on early life fitness could lead to improved understanding of recruitment and population dynamics in both wild and captive populations.

ABSTRACT The proliferation of double‐crested cormorants (DCCOs; Phalacrocorax auritus ) in North America has raised concerns over their potential negative impacts on game, cultured and forage fishes, island and terrestrial resources, and other colonial water birds, leading to increased public demands to reduce their abundance. By combining fish surplus production and bird functional feeding response models, we developed a deterministic predictive model representing bird–fish interactions to inform an adaptive management process for the control of DCCOs in multiple colonies in Michigan. Comparisons of model predictions with observations of changes in DCCO numbers under management measures implemented from 2004 to 2012 suggested that our relatively simple model was able to accurately reconstruct past DCCO population dynamics. These comparisons helped discriminate among alternative parameterizations of demographic processes that were poorly known, especially site fidelity. Using sensitivity analysis, we also identified remaining critical uncertainties (mainly in the spatial distributions of fish vs. DCCO feeding areas) that can be used to prioritize future research and monitoring needs. Model forecasts suggested that continuation of existing control efforts would be sufficient to achieve long‐term DCCO control targets in Michigan and that DCCO control may be necessary to achieve management goals for some DCCO‐impacted fisheries in the state. Finally, our model can be extended by accounting for parametric or ecological uncertainty and including more complex assumptions on DCCO–fish interactions as part of the adaptive management process.

Fish proximate body composition is of great interest in aquaculture because it affects fish appetite, growth and the efficiency of food utilization. Proximate body composition also affects other aspects of fish biology and ecology, including reproduction, survival, and energy value to predators. Two very strong relationships among body components are revealed by taking into account fish body size in terms of water mass. There is a very strong relationship between water mass and protein mass, with the amount of water per unit protein decreasing in larger fish. The strength of this relationship and its presence in a variety of fish species suggest a physiological or biochemical cause. Similarly, there is a very strong relationship between water mass and ash mass, with the amount of water per unit ash decreasing in larger fish. These two strong relationships enable fish body composition to be predicted from wet weight and percent water. Calculated water mass is used to predict mass of protein and ash, then lipid mass is found by subtraction of water, protein, and ash from body mass. Results from this approach suggest that there is virtually no functional relationship between body lipid and body water. Fish energy density can be calculated from proximate composition. These relationships should be useful in studying fish bioenergetics and other aspects of fish growth.

The long-term goal of this research program is to develop and validate bioenergetic models for juvenile salmonid production oriented toward practical hatchery applications. As an initial step toward attainment of this goal, the efficacy of the model was evaluated by comparing model simulations with published data for the growth of a wild strain of coho salmon and a domestic strain selected for its rapid growth characteristics. Model simulations were consistent with the observed growth for each strain when the consumption rate model coefficient was adjusted to account for differences in the stomach size. In an independent study, the growth and proximate composition of juvenile Chinook salmon were measured in response to high and low lipid diets supplied at two different feeding rates. Model simulations were closely comparable to these data when the model coefficients for consumption and apparent respiration rate were adjusted to account for ration and body lipid content. These insights and the successful simulation of measured growth data for eight different combinations of ration, food composition, and coho strain are useful and necessary steps needed to support the development of credible production-scale management models for juvenile salmonid fish production and waste by-product generation from aquaculture and mariculture activities.

This paper demonstrates that conventional bioenergetic models, that are commonly used to simulate fish growth or consumption, violate basic requirements of energy conservation when improperly applied for cases where the energy density of the fish is either a function of fish wet weight or an independent function of time. It appears that many previously published modeling results suffer from this deficiency unless the authors have made perspicuous provisions to avoid implicit imbalances that occur in the equations under these conditions. The incorrect solutions tend to overestimate fish growth and net energy consumption. The magnitude of these errors is a function of how rapidly the fish energy density changes as the fish increases in size. The errors can be as much as 30% for small fish in the range of 1 to 5g per individual where the energy density changes rapidly. Although this mathematical error does not occur if fish energy density is modeled as a constant, this assumption is probably inadequate for most applications and results in a substantial “biological error.” It is recommended that published results for these various cases be critically reviewed and corrected where warranted. The errors can be readily eliminated when the bioenergetic model equations are handled properly as demonstrated in this paper.

We evaluated relationships between residential development intensity and littoral zone habitat and disturbance characteristics in 332 Michigan lakes 4 ha and larger. We also developed a landscape-based model to estimate lakeshore status in more than 6500 unsampled lakes. Residential development had strong negative effects on large woody debris and strong positive effects on shoreline armoring and docks at both local and whole-lake scales. Lakes having greater cumulative residential development showed greater littoral zone impacts at local scales. Littoral habitats were more heavily impacted in larger lakes and in lakes in southern Michigan. Results of our predictive modeling identified the following as important predictors of residential shoreline development: the amount of urban land use, public ownership, and wetlands in a 100 m buffer around a lake as well as distance to major population centers. Statewide estimates of shoreline development showed that in southern Michigan only 8% of lakes were undeveloped and that 23% had low and 69% had high development intensity. In contrast, 30% of northern Michigan lakes were undeveloped and 48% had low and only 22% had high development intensity. Land planning policy and lake management should consider cumulative effects of lakeshore development as well as the effects of region and lake type. Our study provides the basis for developing regional strategies to protect, restore, and manage lake ecosystems.

We related fish species patterns and landscape-scale environmental data from 216 Michigan lakes to identify repeatable types of fish assemblages, identify environmental factors related to assemblage types, and classify fish assemblages in unsampled lakes. Multivariate regression tree modeling of fish species abundances identified six assemblage types that were explained by degree-days during the ice-free period, lake surface area, and mean lake surface temperature. Warmwater species dominated southern lakes, while coolwater and coldwater species had higher abundances in northern lakes. Coolwater species were present in large southern lakes, whereas warmwater species were excluded from northern lakes that had low mean surface temperatures or low degree-days. These results suggest that patterns of lake fish assemblages are shaped by differences in climate as well as lake-specific differences in surface temperature regimes and in vertical availability of coldwater and coolwater habitats. Because we related fish patterns to readily available landscape-level data, our approach can be used to characterize fish assemblages in all lakes across broad geographic extents.

In temperate environments, seasonal selective sources of mortality (e.g., starvation and predation) may drive season-specific energy allocation patterns of young-of-year fish. However, when quantifying such phenomena, the effect of ration is rarely considered. We conducted two experiments to investigate the effect of ration on seasonal energy allocation patterns of age-0 largemouth bass (Micropterus salmoides) during summer and fall. In a laboratory experiment designed to evaluate short-term effects of ration on energy allocation, recent ration history strongly affected body dimensions and length-adjusted energy content. In outdoor raceways, young largemouth bass grew at different rates under different ration levels. In response, length-adjusted energy content, a size-independent index of condition, differed among raceway ration treatments during late summer. However, during fall, high- and low-growth treatment fish expressed similar length-adjusted energy content. Thus, while low-growth fish appeared to allocate a disproportionately low amount of energy to growth of energy-rich storage tissue during late summer, as winter approached, low-growth fish switched and instead allocated a disproportionately high amount of energy to storage tissue. We conclude that energy availability (via ration level) affects short-term energy allocation patterns and may interactively influence seasonal shifts in energy allocation patterns.

Assessment of lake impairment status and identification of threats’ type and source is essential for protection of intact, enhancement of modified, and restoration of impaired lakes. For regions in which large numbers of lakes occur, such assessment has usually been done for only small fractions of lakes due to resource and time limitation. This study describes a process for assessing lake impairment status and identifying which human disturbances have the greatest impact on each lake for all lakes that are 2 ha or larger in the state of Michigan using readily available, georeferenced natural and human disturbance databases. In-lake indicators of impairment are available for only a small subset of lakes in Michigan. Using statistical relationships between the in-lake indicators and landscape natural and human-induced measures from the subset lakes, we assessed the likely human impairment condition of lakes for which in-lake indicator data were unavailable using landscape natural and human disturbance measures. Approximately 92% of lakes in Michigan were identified as being least to marginally impacted and about 8% were moderately to heavily impacted by landscape human disturbances. Among lakes that were heavily impacted, more inline lakes (92%) were impacted by human disturbances than disconnected (6%) or headwater lakes (2%). More small lakes were impacted than medium to large lakes. For inline lakes, 90% of the heavily impacted lakes were less than 40 ha, 10% were between 40 and 405 ha, and 1% was greater than 405 ha. For disconnected and headwater lakes, all of the heavily impacted lakes were less than 40 ha. Among the anthropogenic disturbances that contributed the most to lake disturbance index scores, nutrient yields and farm animal density affected the highest number of lakes, agricultural land use affected a moderate number of lakes, and point-source pollution and road measures affected least number of lakes. Our process for assessing lake condition represents a significant advantage over other routinely used methods. It permits the evaluation of lake condition across large regions and yields an overall disturbance index that is a physicochemical and biological indicator weighted sum of multiple disturbance factors. The robustness of our approach can be improved with increased availability of high-resolution disturbance datasets.

This chapter contains sections titled: Introduction Centrarchid bioenergetics models Food consumption and feeding energetics Metabolic rate Energetic wastes (egestion, excretion, and SDA) Growth energetics Reproductive energetics Synthesis Research needs References

Fish proximate composition and energy density can influence growth, survival, and reproduction, so it is important to develop models to understand the patterns and predict dynamic changes. This paper presents three such models. Model I describes the general pattern of changes in lipid, protein, ash, and energy density that occur with changes in water content. The key assumption this model is that there is a fixed amount of water associated with each gram of protein and a much smaller fixed amount of water associated with each gram of lipid. In combination with a mass balance constraint, this explains the commonly observed linear relationship between the fraction lipid and the fraction water. Because energy density varies in direct proportion to the fractions lipid and protein, the linear relationship between body composition and fraction water makes energy density also a linear function of the fraction water. The model is fitted to data for lake trout Salvelinus namaycush and coho salmon Oncorhynchus kisutch for a limited range in wet weight. Model 2 describes the pattern of proximate composition and energy density that occurs with variation in body size. A strong pattern was found between the mass of water and the mass of protein, suggesting strict control of body water. The model is fitted to data for common carp Cyprinus carpio and bluegill Lepomis macrochirus. This analysis shows that the relationship between body composition, energy density, and fraction water is expected to vary with body size because both the water : protein ratio and the fraction ash change with body size. Model 3 demonstrates how this approach can be used to predict changes in fish body composition and energy density during starvation, as might be done with a bioenergetics model. This model is fitted to data from a starvation experiment involving largemouth bass Micropterus salmoides.

−Increased understanding of fish growth and predator-prey interactions can advance the scientific basis for fisheries management. This study addresses several topics involving fish growth, predators, and prey. First, two laboratory experiments assessed how largemouth bass Micropterus salmoides allocate new tissue to growth in weight and growth in length. Results show that when fish condition is good, increases in weight are primarily allocated to increasing in length while maintaining condition, whereas when condition is poor, increases in weight are primarily allocated to improving condition. Second, a mathematical model was developed to help summarize the information from these experiments in terms of changes in relative weight in relation to recent growth rate. For juvenile largemouth bass, relative weight appears to be a useful index of average growth rate and food consumption over the previous few weeks. Third, because larger bluegills Lepomis macrochirus can be predators on smaller bluegills, measurements were made on the gape and maximum body depth of a wide size range of bluegills; laboratory experiments evaluated the predicted gape limitation. New equations were developed to relate gape of bluegills as predators and maximum body depth of bluegills as prey. Fourth, pond experiments were conducted to assess juvenile walleye Sander vitreus and adult bluegill predator growth and predation rates in the presence of different densities of juvenile bluegills as prey. Average growth of individually marked walleyes generally increased with density of bluegill prey. An experiment in ponds over winter indicated that adult bluegills are not likely to cause appreciable predatory mortality when age-0 bluegills are potential prey. Increased understanding of fish growth and predator-prey interactions can advance the scientific basis for fisheries management. Fish are gape-limited predators, so predator body size affects the sizes of prey that can be ingested. Fish growth rate determines size and gape at a given age and growth rate is influenced by food availability. Increased knowledge of growth rate and size-specific predator-prey interactions has the potential to help in managing the size distributions of predators and prey in fish communities. Growth rate may affect fish condition as measured by relative weight (Wege and Anderson 1978; Blackwell et al. 2000). Increased understanding of how fish allocate new tissue to growth in length and growth in condition can give insight into the expected relationship between relative weight and growth rate. In order to interpret field measurements of relative weight, information is needed on how quickly relative weight changes in response to changes in growth rate or food consumption. For example, if relative weight reflects long-term average food consumption, then relative weight would be expected to correlate with annual growth rate. On the other hand, if relative weight reflects short-

The species-area pattern for plants and animals predicts larger areas generally contain greater species richness. Also, it is recognized that the number of species increases from north to south with temperature. Our analyses of the distribution of Michigan fishes support these observations. The common log-log slope value of about 0.25 for species-area relationship was found for the Upper and Lower peninsulas of Michigan as well as the Great Lakes watersheds of Superior, Huron and Erie (Michigan was an exception with a value of 0.44). The number of species per 2500 square kilometers increased from 50 species for the Upper Peninsula to 73 species for the southern Lower Peninsula as the latitude decreased from 47 degrees to 42 degrees, and the Great Lakes watersheds showed a similar pattern. The increase in species number from north to south correlated with a measured increase in growing degree days. The multiple regression of area and growing degree days of watersheds against number of species resulted in an increase in adjusted r(2) to 0.67 from 0.38 for the regression of species-area alone. Species diversity of Michigan fishes is strongly influenced by watershed area and growing degree days temperatures.

The ecoregion and watershed frameworks are landscape-based classifications that have been used to group waterbodies with respect to measures of community structure; however, they have yet to be evaluated for grouping lakes for demographic characteristics of fish populations. We used a multilevel modeling approach to determine if variability in mean fish length at age could be partitioned by ecoregions and watersheds. For the ecoregions analysis, we then examined if within-ecoregion variability could be explained by local water quality and lake morphometry characteristics. We used data from agency surveys conducted during 1974–1984 for age 2 and 3 fish of seven common warm and coolwater fish species. Variance in mean length at age between ecoregions for all species was not significant, and between-watershed variance estimates were only significant in 3 out of 14 analyses; however, the total amount of variation between watersheds was very small (ranging from 1.8% to 3.7% of the total variance), indicating that ecoregions and watersheds were ineffective in partitioning variability in mean length at age. Within ecoregions, water quality and lake morphometric characteristics accounted for 2%–23% of the variation in mean length at age. Measures of lake productivity were the most common significant covariates, with mean length at age increasing with increasing lake productivity. Much of the variability in mean length at age was not accounted for, suggesting that other local factors such as biotic interactions, fish density, and exploitation are important. The results indicate that the development of an effective regional framework for managing inland lakes will require a substantial effort to understand sources of demographic variability and that managers should not rely solely on ecoregions or watersheds for grouping lakes with similar growth rates.

–Although it is generally agreed upon that the hydrology of river valleys plays an important role in shaping the composition and structure of riparian ecosystems, relevant hydrologic drivers are difficult to measure across broad regions and often inadequately specified in riparian studies. In this paper, we describe an empirical-statistical method using map-based models to predict the composition of riparian forests along the major rivers of Lower Michigan. Our approach, based on regional climate as well as both local and catchment-scale hydrology and physiography, accounted for between 84% and 99% of the observed classification probability for five riparian ecotypes at 94 locations. Using parameters from our models, we combined map-based estimates of groundwater flux and flood dynamics with climatic indices to extrapolate and map initial predictions of riparian character throughout much of Michigan’s Lower Peninsula. Although our ability to account for long-term variation under specific hydrologic conditions was relatively poor, we nonetheless were able to distinguish and characterize riparian conditions with an overall predictive accuracy of 84%. Although climate and hydrology are not the only determinants of riparian conditions, our results suggest that the interactions of groundwater supply and flood dynamics, as described by our spatial predictions, drive a significant portion of the spatial variation in riparian ecosystem character. The results also suggest strong variation in the relative and spatial scales of hydrologic determinants leading to specific riparian ecotypes. Models that provide insight into factors controlling diversity in riparian composition, structure, and function, also provide a context for understanding riparian contributions to in-stream habitat and water quality studies.

In 1995, the Fisheries Division of the Michigan Department of Natural Resources formed a Resource Inventory Planning Committee to develop a statewide sampling program for inland waters. The goal of this sampling program was to provide information needed for the management and conservation of Michigan's aquatic resources. Because sampling provides information to a variety of users for multiple purposes, the sampling plan we designed included several subprograms, some of which are under local control and some of which are centrally administered with a broad statistical design. Centrally administered subprograms included designs to (1) evaluate stocking success using angler surveys, (2) evaluate the characteristics of lake fish communities across the state, and (3) evaluate the characteristics of stream fish communities across the state. Two of the major topics addressed by the committee were standardization of sampling gear and choice of sampling sites (i.e., particular lakes or stream segments). Although sampling gear standardization generated much discussion, the choice of sampling sites proved to be a much more contentious issue, primarily because it shifted much of the control over choice of sampling sites from local fishery managers to a more centralized system. Balancing the needs for information at a local scale with needs for larger scale data collections remains a challenge, and continues to generate conflict within the Fisheries Division. This is best addressed by explicitly recognizing the tension between these needs and basing the allocation of sampling resources on a rational basis developed by discussion among all organizational levels.