M. Craig Barber

Application of ecosystem‐scale fate and bioaccumulation models to predict fish mercury response times to changes in atmospheric deposition

Management strategies for controlling anthropogenic mercury emissions require understanding how ecosystems will respond to changes in atmospheric mercury deposition. Process-based mathematical models are valuable tools for informing such decisions, because measurement data often are sparse and cannot be extrapolated to investigate the environmental impacts of different policy options. Here, we bring together previously developed and evaluated modeling frameworks for watersheds, water bodies, and food web bioaccumulation of mercury. We use these models to investigate the timescales required for mercury levels in predatory fish to change in response to altered mercury inputs. We model declines in water, sediment, and fish mercury concentrations across five ecosystems spanning a range of physical and biological conditions, including a farm pond, a seepage lake, a stratified lake, a drainage lake, and a coastal plain river. Results illustrate that temporal lags are longest for watershed-dominated systems (like the coastal plain river) and shortest for shallow water bodies (like the seepage lake) that receive most of their mercury from deposition directly to the water surface. All ecosystems showed responses in two phases: A relatively rapid initial decline in mercury concentrations (20-60% of steady-state values) over one to three decades, followed by a slower descent lasting for decades to centuries. Response times are variable across ecosystem types and are highly affected by sediment burial rates and active layer depths in systems not dominated by watershed inputs. Additional research concerning watershed processes driving mercury dynamics and empirical data regarding sediment dynamics in freshwater bodies are critical for improving the predictive capability of process-based mercury models used to inform regulatory decisions.

A review and comparison of models for predicting dynamic chemical bioconcentration in fish

Over the past 20 years, a variety of models have been developed to simulate the bioconcentration of hydrophobic organic chemicals by fish. These models differ not only in the processes they address but also in the way a given process is described. Processes described by these models include chemical diffusion through the gills interlamellar water, epithelium, and lamellar blood plasma: advective chemical transport to and from the gill by ventilation and perfusion, respectively; and internal chemical deposition by thermodynamic partitioning to lipid and other organic phases. This article reviews the construction and associated assumptions of 10 of the most widely cited fish bioconcentration models. These models are then compared with respect to their ability to predict observed uptake and elimination rates using a common database for those model parameters that they have in common. Statistical analyses of observed and predicted exchange rates reveal that rates predicted by these models can be calibrated almost equally well to observed data. This fact is independent of how well any given model is able to predict observed exchange rates without calibration. The importance of gill exchange models and how they might by improved are also discussed.

Dietary uptake models used for modeling the bioaccumulation of organic contaminants in fish

Numerous models have been developed to predict the bioaccumulation of organic chemicals in fish. Although chemical dietary uptake can be modeled using assimilation efficiencies, bioaccumulation models fall into two distinct groups. The first group implicitly assumes that assimilation efficiencies describe the net chemical exchanges between fish and their food. These models describe chemical elimination as a lumped process that is independent of the fishs egestion rate or as a process that does not require an explicit fecal excretion term. The second group, however, explicitly assumes that assimilation efficiencies describe only actual chemical uptake and formulates chemical fecal and gill excretion as distinct, thermodynamically driven processes. After reviewing the derivations and assumptions of the algorithms that have been used to describe chemical dietary uptake of fish, their application, as implemented in 16 published bioaccumulation models, is analyzed for largemouth bass (Micropterus salmoides), walleye (Sander vitreus = Stizostedion vitreum), and rainbow trout (Oncorhynchus mykiss) that bioaccumulate an unspecified, poorly metabolized, hydrophobic chemical possessing a log K(OW) of 6.5 (i.e., a chemical similar to a pentachlorobiphenyl).

Predictive Habitat Models for the Occurrence of Stream Fishes in the Mid-Atlantic Highlands

Abstract In most wadeable streams of the mid-Atlantic Highlands region of the eastern USA, physical habitat alteration is the primary stressor for fish. Models that predict the occurrence of stream-fish species based on habitat measures can be useful in management, and predicted probability of occurrence can be a measure of habitat suitability with which to compare alternative habitat management scenarios and assess the effectiveness of stream restoration. We developed such models for each of 13 mid-Atlantic Highlands stream-fish species and species groups by using multiple logistic regression and six instream habitat measures: depth, temperature, substrate, percent riffles, cover, and riparian vegetation. The predictive ability of the models ranged from 61% to 79% in cross-validation and from 38% to 85% on an independent data set. The models predicted well for both the original and test data sets for black bass Micropterus spp., brook trout Salvelinus fontinalis, darters Etheostoma and Percina spp., shin...

Predicting fish densities in lotic systems: a simple modeling approach

Abstract Fish density models are essential tools for fish ecologists and fisheries managers. However, applying these models can be difficult because of high levels of model complexity and the large number of parameters that must be estimated. We designed a simple fish density model and tested whether it could predict fish densities in lotic systems with meaningful levels of accuracy and precision. We built our 6-parameter model on 2 key assumptions: 1) fish population density is a power function of mean body mass (i.e., the self-thinning relationship), and 2) energetic resources are transferred from lower to higher trophic levels at a nearly constant rate (i.e., trophic transfer efficiency). We estimated the self-thinning and trophic transfer efficiency parameters by randomly sampling from values reported in the primary literature. Remaining parameters were net primary production, trophic level, the production∶biomass ratio, and mean body mass. We used empirical parameter estimates and fish density estimates to test the model in 4 warm-water and 4 cold-water systems. Model accuracy was high in 3 test systems (deviations between the model-predicted densities and empirically observed densities <30%), moderate in 3 test systems (deviations 75–111%), and low in 2 systems (deviations >150%). Model precision was low (e.g., the interquartile ranges of model-predicted densities encompassed ~1 order of magnitude), but appropriate for predicting fish densities at coarse spatial and temporal scales. We concluded that the model is a potentially useful and efficient tool, and we provide recommendations for applying the model. In particular, we emphasize that the model is scalable, and therefore, well-suited for estimating fish densities at large spatial scales. We also point out that the model is a carrying capacity model, and therefore, can be used to predict fish densities in undisturbed systems or to approximate reference conditions.

An integrated ecological modeling system for assessing impacts of multiple stressors on stream and riverine ecosystem services within river basins

We demonstrate a novel, spatially explicit assessment of the current condition of aquatic ecosystem services, with limited sensitivity analysis for the atmospheric contaminant mercury. The Integrated Ecological Modeling System (IEMS) forecasts water quality and quantity, habitat suitability for aquatic biota, fish biomasses, population densities, productivities, and contamination by methylmercury across headwater watersheds. We applied this IEMS to the Coal River Basin (CRB), West Virginia (USA), an 8-digit hydrologic unit watershed, by simulating a network of 97 stream segments using the SWAT watershed model, a watershed mercury loading model, the WASP water quality model, the PiSCES fish community estimation model, a fish habitat suitability model, the BASS fish community and bioaccumulation model, and an ecoservices post-processer. Model application was facilitated by automated data retrieval and model setup and updated model wrappers and interfaces for data transfers between these models from a prior study. This companion study evaluates baseline predictions of ecoservices provided for 1990 - 2010 for the population of streams in the CRB and serves as a foundation for future model development.

Forecasting fish biomasses, densities, productions, and bioaccumulation potentials of Mid-Atlantic wadeable streams

Regional fishery conditions of Mid-Atlantic wadeable streams in the eastern United States are estimated using the Bioaccumulation and Aquatic System Simulator (BASS) bioaccumulation and fish community model and data collected by the US Environmental Protection Agencys Environmental Monitoring and Assessment Program (EMAP). Average annual biomasses and population densities and annual productions are estimated for 352 randomly selected streams. Realized bioaccumulation factors (BAF) and biomagnification factors (BMF), which are dependent on these forecasted biomasses, population densities, and productions, are also estimated by assuming constant water exposures to methylmercury and tetra-, penta-, hexa-, and hepta-chlorinated biphenyls. Using observed biomasses, observed densities, and estimated annual productions of total fish from 3 regions assumed to support healthy fisheries as benchmarks (eastern Tennessee and Catskill Mountain trout streams and Ozark Mountains smallmouth bass streams), 58% of the regions wadeable streams are estimated to be in marginal or poor condition (i.e., not healthy). Using simulated BAFs and EMAP Hg fish concentrations, we also estimate that approximately 24% of the game fish and subsistence fishing species that are found in streams having detectable Hg concentrations would exceed an acceptable human consumption criterion of 0.185 μg/g wet wt. Importantly, such streams have been estimated to represent 78.2% to 84.4% of the Mid-Atlantics wadeable stream lengths. Our results demonstrate how a dynamic simulation model can support regional assessment and trends analysis for fisheries.