Human-induced eutrophication degrades freshwater systems worldwide by reducing water quality and altering ecosystem structure and function. We compared current total nitrogen (TN) and phosphorus (TP) concentrations for the U.S. Environmental Protection Agency nutrient ecoregions with estimated reference conditions. In all nutrient ecoregions, current median TN and TP values for rivers and lakes exceeded reference median values. In 12 of 14 ecoregions, over 90% of rivers currently exceed reference median values. We calculated potential annual value losses in recreational water usage, waterfront real estate, spending on recovery of threatened and endangered species, and drinking water. The combined costs were approximately $2.2 billion annually as a result of eutrophication in U.S. freshwaters. The greatest economic losses were attributed to lakefront property values ($0.3-2.8 billion per year, although this number was poorly constrained) and recreational use ($0.37-1.16 billion per year). Our evaluation likely underestimates economic losses incurred from freshwater eutrophication. We document potential costs to identify where restoring natural nutrient regimes can have the greatest economic benefits. Our research exposes gaps in current records (e.g., accounting for frequency of algal blooms and fish kills) and suggests further research is necessary to refine cost estimates.

Understanding how gene flow influences adaptive divergence is important for predicting adaptive responses. Theoretical studies suggest that when gene flow is high, clustering of adaptive genes in fewer genomic regions would protect adaptive alleles from among-population recombination and thus be selected for, but few studies have tested this hypothesis with empirical data. Here, we used RADseq to generate genomic data for six fish species with contrasting life histories from six reaches of the Upper Mississippi River System, USA. We then conducted genome scans for genomic islands of divergence to examine the distribution of adaptive loci and investigated whether these loci were found in inversions. We found that gene flow varied among species, and adaptive loci were clustered more tightly in species with higher gene flow. For example, the two species with the highest overall F ST (0.03 -0.07) and therefore lowest gene flow showed little evidence of clusters of adaptive loci, with adaptive loci spread uniformly across the genome. In contrast, nearly all adaptive loci in the species with the lowest F ST (0.0004) were found in a single large putative inversion. Two other species with intermediate gene flow (F ST ~ 0.004) also showed clustered genomic architectures, with most islands of divergence clustered on a few chromosomes. These results provide important empirical evidence to support the hypothesis that increasingly clustered architectures of local adaptation are associated with high gene flow. Our study utilized a unique system with species spanning a large gradient of life histories to highlight the importance of gene flow in shaping adaptive divergence.

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Rehabilitation of large Anthropocene rivers requires engagement of diverse stakeholders across a broad range of sociopolitical boundaries. Competing objectives often constrain options for ecological restoration of large rivers whereas fewer competing objectives may exist in a subset of tributaries. Further, tributaries contribute toward building a “portfolio” of river ecosystem assets through physical and biological processes that may present opportunities to enhance the resilience of large river fishes. Our goal is to review roles of tributaries in enhancing mainstem large river fish populations. We present case histories from two greatly altered and distinct large-river tributary systems that highlight how tributaries contribute four portfolio assets to support large-river fish populations: 1) habitat diversity, 2) connectivity, 3) ecological asynchrony, and 4) density-dependent processes. Finally, we identify future research directions to advance our understanding of tributary roles and inform conservation actions. In the Missouri River United States, we focus on conservation efforts for the state endangered lake sturgeon, which inhabits large rivers and tributaries in the Midwest and Eastern United States. In the Colorado River, Grand Canyon United States, we focus on conservation efforts for recovery of the federally threatened humpback chub. In the Missouri River, habitat diversity focused on physical habitats such as substrate for reproduction, and deep-water habitats for refuge, whereas augmenting habitat diversity for Colorado River fishes focused on managing populations in tributaries with minimally impaired thermal and flow regimes. Connectivity enhancements in the Missouri River focused on increasing habitat accessibility that may require removal of physical structures like low-head dams; whereas in the Colorado River, the lack of connectivity may benefit native fishes as the disconnection provides refuge from non-native fish predation. Hydrologic variability among tributaries was present in both systems, likely underscoring ecological asynchrony. These case studies also described density dependent processes that could influence success of restoration actions. Although actions to restore populations varied by river system, these examples show that these four portfolio assets can help guide restoration activities across a diverse range of mainstem rivers and their tributaries. Using these assets as a guide, we suggest these can be transferable to other large river-tributary systems.

Environmental change has and will continue to adversely influence aquatic communities. Efforts to model impacts of environmental change on fisheries have largely focused on cold water, commercial, and recreationally valued species, even though warm water, non-game species have important roles in ecosystem services and processes. We developed species distribution models for fourteen warm water fish species native to the central United States and evaluated environmental drivers and predictive performance. We used an ensemble model approach produced by combining forecasts of five single-model techniques. Response plots and variable importance calculations were used to evaluate the influence of individual variables. The predictive performance of the ensemble models was assessed using area under the curve of the receiver operating characteristic plot (AUC). AUC values indicate ensemble models performed better than single-model types, suggesting ensemble models are more reliable and applicable for management purposes than single models. Most models were influenced by a mix of climate, land use, and geophysical variables; however, climate variables were the dominant environmental drivers across models. Given the high sensitivity of models to climate and land use, we expect future climate and land use changes to influence distributions.