Jason C. Doll

Detection of pharmaceuticals and personal care products (PPCPs) in near-shore habitats of southern Lake Michigan

Pharmaceuticals and personal care products (PPCPs) have been documented throughout the United States freshwaters but research has focused largely on lotic systems. Because PPCPs are designed to have a physiological effect, it is likely that they may also influence aquatic organisms. Thus, PPCPs may negatively impact aquatic ecosystems. The objectives of this research were to quantify PPCP abundance in near-shore habitats of southern Lake Michigan and identify factors related to PPCP abundance. Stratified sampling was conducted seasonally at four southern Lake Michigan sites. All sites and depths had measurable PPCP concentrations, with mean individual compound concentrations of acetaminophen (5.36 ng/L), caffeine (31.0 ng/L), carbamazepine (2.23 ng/L), cotinine (4.03 ng/L), gemfibrozil (7.03 ng/L), ibuprofen (7.88 ng/L), lincomycin (4.28 ng/L), naproxen (6.32 ng/L), paraxanthine (1,7-dimethylxanthine; 46.2 ng/L), sulfadimethoxine (0.94 ng/L), sulfamerazine (0.92 ng/L), sulfamethazine (0.92 ng/L), sulfamethoxazole (26.0 ng/L), sulfathiazole (0.92 ng/L), triclocarban (5.72 ng/L), trimethoprim (5.15 ng/L), and tylosin (3.75 ng/L). Concentrations of PPCPs varied significantly among sampling times and locations (river mouth vs offshore), with statistical interactions between the main effects of site and time as well as time and location. Concentrations of PPCPs did not differ with site or depth. Temperature, total carbon, total dissolved solids, dissolved oxygen, and ammonium concentrations were related to total pharmaceutical concentrations. These data indicate that PPCPs are ubiquitous and persistent in southern Lake Michigan, potentially posing harmful effects to aquatic organisms.

A national reconnaissance of trace organic compounds (TOCs) in United States lotic ecosystems.

We collaborated with 26 groups from universities across the United States to sample 42 sites for 33 trace organic compounds (TOCs) in water and sediments of lotic ecosystems. Our goals were 1) to further develop a national database of TOC abundance in United States lotic ecosystems that can be a foundation for future research and management, and 2) to identify factors related to compound abundance. Trace organic compounds were found in 93% of water samples and 56% of sediment samples. Dissolved concentrations were 10-1000× higher relative to sediment concentrations. The ten most common compounds in water samples with detection frequency and maximum concentration were sucralose (87.5%, 12,000ng/L), caffeine (77.5%, 420ng/L), sulfamethoxazole (70%, 340ng/L), cotinine (65%, 130ng/L), venlafaxine (65%, 1800ng/L), carbamazepine (62.5%, 320ng/L), triclosan (55%, 6800ng/L), azithromycin (15%, 970ng/L), diphenylhydramine (40%, 350ng/L), and desvenlafaxine (35%, 4600ng/L). In sediment, the most common compounds were venlafaxine (32.5%, 19ng/g), diphenhydramine (25%, 41ng/g), azithromycin (15%, 11ng/g), fluoxetine (12.5%, 29ng/g) and sucralose (12.5%, 16ng/g). Refractory compounds such as sucralose may be good indicators of TOC contamination in lotic ecosystems, as there was a correlation between dissolved sucralose concentrations and with the total number of compounds detected in water. Discharge and human demographic (population size) characteristics were not good predictors of compound abundance in water samples. This study further confirms the ubiquity of TOCs in lotic ecosystems. Although concentrations measured rarely approached acute aquatic-life criteria, the chronic effects, bioaccumulative potential, or potential mixture effects of multiple compounds are relatively unknown.

Hot and toxic: Temperature regulates microcystin release from cyanobacteria

The mechanisms regulating toxin release by cyanobacteria are poorly understood despite the threat cyanotoxins pose to water quality and human health globally. To determine the potential for temperature to regulate microcystin release by toxin-producing cyanobacteria, we evaluated seasonal patterns of water temperature, cyanobacteria biomass, and extracellular microcystin concentration in a eutrophic freshwater lake dominated by Planktothrix agardhii. We replicated seasonal variation in water temperature in a concurrent laboratory incubation experiment designed to evaluate cause-effect relationships between temperature and toxin release. Lake temperature ranged from 3 to 27°C and cyanobacteria biomass increased with warming up to 18°C, but declined rapidly thereafter with further increases in temperature. Extracellular microcystin concentration was tightly coupled with temperature and was most elevated between 20 and 25°C, which was concurrent with the decline in cyanobacteria biomass. A similar trend was observed in laboratory incubations where productivity-specific microcystin release was most elevated between 20 and 25°C and then declined sharply at 30°C. We applied generalized linear mixed modeling to evaluate the strength of water temperature as a predictor of cyanobacteria abundance and microcystin release, and determined that warming≥20°C would result in a 36% increase in microcystin release when Chlorophyll a was ≤50μgl-1. These results show a temperature threshold for toxin release in P. agardhii, which demonstrates a potential to use water temperature to forecast bloom severity in eutrophic lakes where blooms can persist year-round with varying degrees of toxicity.

Body size and geographic range do not explain long term variation in fish populations: a Bayesian phylogenetic approach to testing assembly processes in stream fish assemblages.

We combine evolutionary biology and community ecology to test whether two species traits, body size and geographic range, explain long term variation in local scale freshwater stream fish assemblages. Body size and geographic range are expected to influence several aspects of fish ecology, via relationships with niche breadth, dispersal, and abundance. These traits are expected to scale inversely with niche breadth or current abundance, and to scale directly with dispersal potential. However, their utility to explain long term temporal patterns in local scale abundance is not known. Comparative methods employing an existing molecular phylogeny were used to incorporate evolutionary relatedness in a test for covariation of body size and geographic range with long term (1983 – 2010) local scale population variation of fishes in West Fork White River (Indiana, USA). The Bayesian model incorporating phylogenetic uncertainty and correlated predictors indicated that neither body size nor geographic range explained significant variation in population fluctuations over a 28 year period. Phylogenetic signal data indicated that body size and geographic range were less similar among taxa than expected if trait evolution followed a purely random walk. We interpret this as evidence that local scale population variation may be influenced less by species-level traits such as body size or geographic range, and instead may be influenced more strongly by a taxon’s local scale habitat and biotic assemblages.

Predicting biological impairment from habitat assessments

The goal of biological monitoring programs is to determine impairment classification and identify local stressors. Biological monitoring performs well at detecting impairment but when used alone falls short of determining the cause of the impairment. Following detection a more thorough survey is often conducted using extensive biological, chemical, and physical analysis coupled with exhaustive statistical treatments. These methods can be prohibitive for small programs that are limited by time and budget. The objective of this study was to develop a simple and useful model to predict the probability of biological impairment based on routinely collected habitat assessments. Biological communities were assessed with the Index of Biotic Integrity (IBI), and habitat was assessed with the Qualitative Habitat Evaluation Index. Two models were constructed from a validation dataset. The first predicted a binary outcome of impaired (IBI < 35) or non-impaired (IBI ≥ 35) and the second predicted a categorical gradient of impairment. Categories include very poor, poor, fair, good, and excellent. The models were then validated with an independently collected dataset. Both models successfully predicted biological integrity of the validation dataset with an accuracy of 0.84 (binary) and 0.75 (categorical). Based on the binary outcome model, 22 sites were observed to be impaired while the model predicted them to not be impaired. The categorical model misclassified 47 samples while only seven of those were misclassified by two or more categories. The impairment source was subsequently identified by known stressors. The models developed here can be easily applied to other datasets from the Eastern Corn Belt Plain to aid in stressor identification by predicting the probability of observing an impaired fish community based on habitat. Predicted probabilities from the models can also be used to support conclusions that have already been determined.

Gill net selectivity of yellow perch

Yellow perch Perca flavescens (Mitchill) are typically collected using multi-mesh gill nets; however, gear selectivity information for this species is sparse. Selectivity using experimental gill nets was determined for yellow perch using data collected from southern Lake Michigan from 2007 to 2012 using stretch mesh sizes of 12.5, 16, 20, 25, 32, 38, 46, 51, 64, and 76 mm. Female selectivity was best described by a model with a skewed (log-normal) distribution while males were best described by a normal distribution. When sex data were combined, the skewed (log-normal) distribution provided the best model. Differences in selectivity between sexes were minimal, but likely due to the variant size structure of the local population sampled, with females the larger sex. These findings suggest that bias in individual gill net selectivity can be used to target specific yellow perch size groups or to replace other gear types with unknown selectivity.

Effects of flow regime on growth rate in freshwater drum, Aplodinotus grunniens

Understanding the influence of flow regime hydrology on fish life history is essential for conservation and management of lotic ecosystems. The objectives of this study were to investigate growth patterns of Wabash River freshwater drum Aplodinotus grunniens relative to age, sex, and long term flow regime variation. Growth was estimated using back-calculated lengths from otolith measurements. Flow regime was described using Indicators of Hydrologic Alteration flow metrics calculated from long-term stream flow data at USGS stations. A generalized linear mixed model was used to model growth as a function of age, sex, and flow regime. Freshwater drum growth was explained by variation in age, sex, and flow magnitude. Freshwater drum exhibited indeterminate growth relative to age. Mean growth rates and mean length at age were lower in males than females. High magnitude flow events were positively correlated with increased growth rates in both males and females. However, the effect of flow magnitude variation on growth was stronger in males. The primary flow regime metrics related to growth were magnitude-based and were not related to timing of flow events. The study provides evidence that long term variation in flow regime is a catalyst for alterations in freshwater drum growth rates.

Bayesian Estimation of Age and Length at 50% Maturity

Abstract Fish age and length at 50% maturity are used extensively in the management of exploited fish populations. These parameters are historically estimated using logistic regression models (e.g., frequentist inference) for individual year-classes and often fail to converge or result in insignificant results when a small sample size is used. The sample-size problem motivated us to evaluate whether a hierarchical logistic regression model fit using frequentist inference or Bayesian inference, could improve our ability to fit these models. Our objective was to compare Bayesian and frequentist inference for estimating age and length at 50% maturity to determine whether the models produced similar values. To make this evaluation, we used a long-term data set of Yellow Perch Perca flavescens from southern Lake Michigan. Frequentist inference of the year-class-specific models resulted in significant results when sample size was sufficiently large, a result that occurred in 76% of the models. The hierarchical ...

Macroecology of North American suckers (Catostomidae): tests of Bergmann's and Rapoport's rules

Abstract Discerning spatial macroecological patterns in freshwater fishes has broad implications for community assembly, ecosystem dynamics, management, and conservation. This study explores the potential interspecific covariation of geographic range (Rapoports rule) and body size (Bergmanns rule) with latitude in North American sucker fishes (Cypriniformes: Catostomidae). While numerous tests of Rapoports and Bergmanns rules are documented in the literature, comparatively few of these studies have specifically tested for these patterns, and none have incorporated information reflecting shared ancestry into analyses of North American freshwater fish through a hierarchical model. This study utilized a hierarchical modeling approach with Bayesian inference to evaluate the role that evolution has played in shaping these distributional corollaries. Rapoports rule was supported at the tribe level but not across family and subfamily groupings. Particularly within the Catostominae subfamily, two tribes reflected strong support for Rapoports rule while two suggested a pattern was present. Conversely, Bergmanns rule was not supported in Catostomidae. This study provides additional information regarding the pervasiveness of these “rules” by expanding inferences in freshwater fishes and specifically addressing the potential for these macroecological patterns to play a role in the distribution of the understudied group Catostomidae.