Exploring long-term trends in microcystin toxin values associated with persistent harmful algal blooms in Grand Lake St Marys.

High external nutrient loads from agricultural runoff have led to persistent and highly toxic algal blooms in Grand Lake St Marys (GLSM) for decades. These pervasive blooms are concurrent with long-term (2009 - 2021) toxin and environmental monitoring, providing a robust weekly dataset for modeling microcystins. Median weekly microcystin concentrations (23.2 µg/L) routinely exceeded World Health Organization recreational limits (20 µg/L) for the study period (ranged 0.03 - 185.0 µg/L). Here, we used a Bayesian hierarchical dynamic linear model to hindcast weekly microcystin toxins using external nutrient loads from tributary data as well as internal lake nutrient and physicochemical concentrations. Overall, lake TN was the biggest driver of microcystin concentration in GLSM. Likewise, TN:TP was a strong negative driver of microcystin (i.e. low N:P ratios align with lower total microcystins), suggesting that N availability directly impacts toxins. External nutrient loading was positively related to microcystin during winter and spring; however, there was no relationship detected between toxin and external loading during summer or fall (particulate phosphorus exhibited the strongest signal but all external nutrients were unsurprisingly correlated). This lack of direct correlation on a weekly timescale between external loads and cyanobacterial toxins during the summer months likely results from nutrient saturation and reflects the importance of internal loading for bloom maintenance as supported by the correlation between in-lake TN and microcystin. Thus, management goals to reduce the highest biomass and toxins in the summer should focus on reduction of winter and spring external nutrient loads. Supporting this, both 2010 and 2021 had lower rain in the first half of the year (winter/spring), resulting in less loading, and experienced smaller/later low toxicity blooms. This suggests that, although internal nutrient loads are important for bloom maintenance, reduced external loads are an effective management strategy even in nutrient saturated systems such as GLSM.

Incorporation of feeding functional group information informs explanatory patterns of long-term population changes in fish assemblages.

The objective of this study was to evaluate long term trends of fish taxa in southern Lake Michigan while incorporating their functional roles to improve our understanding of ecosystem level changes that have occurred in the system over time. The approach used here highlighted the ease of incorporating ecological mechanisms into population models so researchers can take full advantage of available long-term ecosystem information. Long term studies of fish assemblages can be used to inform changes in community structure resulting from perturbations to aquatic systems and understanding these changes in fish assemblages can be better contextualized by grouping species according to functional groups that are grounded in niche theory. We hypothesized that describing the biological process based on partial pooling of information across functional groups would identify shifts in fish assemblages that coincide with major changes in the ecosystem (e.g., for this study, shifts in zooplankton abundance over time). Herein, we analyzed a long-term Lake Michigan fisheries dataset using a multi-species state space modeling approach within a Bayesian framework. Our results suggested the population growth rates of planktivores and benthic invertivores have been more variable than general invertivores over time and that trends in planktivores can be partially explained by ecosystem changes in zooplankton abundance. Additional work incorporating more ecosystem parameters (e.g., primary production, etc.) should be incorporated into future iterations of this novel modeling concept.

Spatial Distribution of a Tree Trunk Specialist Spider: Relative Role of Landscape Versus Microhabitat Drivers.

By completely censusing a 1 ha forest dynamics plot it was possible to identify the variables (spider mass, size, sex and tree species, size, and bark roughness) that influenced the spatial distribution of adult Drapetisca alteranda Chamberlin 1909 (Araneae: Linyphiidae), a sheet web spider that specializes in lower tree trunks in North American forests. To account for spatial autocorrelation, a conditional autoregressive random effect was included in the zero-inflated Poisson generalized linear mixed model. Parameters estimated were produced by Bayesian inference with vague prior probability distributions and the best of 16 models were selected using Watanabe-Akaike Information Criterion. The best model showed that larger diameter trees located at higher plot elevations were more likely to have D. alteranda present. Smooth bark tree species such as paper birch and American basswood tended to have the most spiders while rough bark species had the least. The relationship between tree diameter and D. alteranda abundance also varied by tree species. Paper birch and quaking aspen tend to produce a greater slope compared to the other species, indicating that as these trees get larger, the abundance of D. alteranda increases at a higher rate than on other tree species. Spider sex and size were not associated with height on the trunk or tree species selection, nor were they associated with microhabitats such as bark furrow depth. Landscape-level factors largely predict D. alteranda abundance and distribution, suggesting that spatial autocorrelation should be considered when modeling the abundance of even small organisms, such as spiders.

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.

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

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 (Rapoport's rule) and body size (Bergmann's rule) with latitude in North American sucker fishes (Cypriniformes: Catostomidae). While numerous tests of Rapoport's and Bergmann's 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. Rapoport's 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 Rapoport's rule while two suggested a pattern was present. Conversely, Bergmann's 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.

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.

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.

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.