Gene flow influences the genomic architecture of local adaptation in six riverine fish species.

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 recombination and thus be selected for, but few studies have tested it with empirical data. Here, we used restriction site-associated sequencing to generate genomic data for six fish species with contrasting life histories from six reaches of the Upper Mississippi River System, USA. We used four differentiation-based outlier tests and three genotype-environment association analyses to define neutral single nucleotide polymorphisms (SNPs) and outlier SNPs that were putatively under selection. We then examined the distribution of outlier SNPs along the genome and investigated whether these SNPs were found in genomic islands of differentiation and inversions. We found that gene flow varied among species, and outlier SNPs were clustered more tightly in species with higher gene flow. The two species with the highest overall FST (0.0303-0.0720) and therefore lowest gene flow showed little evidence of clusters of outlier SNPs, with outlier SNPs in these species spreading uniformly across the genome. In contrast, nearly all outlier SNPs in the species with the lowest FST (0.0003) were found in a single large putative inversion. Two other species with intermediate gene flow (FST  ~ 0.0025-0.0050) also showed clustered genomic architectures, with most islands of differentiation clustered on a few chromosomes. Our results provide important empirical evidence to support the hypothesis that increasingly clustered architecture of local adaptation is associated with high gene flow.

Resisting-Accepting-Directing: Ecosystem Management Guided by an Ecological Resilience Assessment.

As anthropogenic influences push ecosystems past tipping points and into new regimes, complex management decisions are complicated by rapid ecosystem changes that may be difficult to reverse. For managers who grapple with how to manage ecosystems under novel conditions and heightened uncertainty, advancing our understanding of regime shifts is paramount. As part of an ecological resilience assessment, researchers and managers have collaborated to identify alternate regimes and build an understanding of the thresholds and factors that govern regime shifts in the Upper Mississippi River System. To describe the management implications of our assessment, we integrate our findings with the recently developed resist-accept-direct (RAD) framework that explicitly acknowledges ecosystem regime change and outlines management approaches of resisting change, accepting change, or directing change. More specifically, we developed guidance for using knowledge of desirability of current conditions, distance to thresholds, and general resilience (that is, an ecosystem's capacity to cope with uncertain disturbances) to navigate the RAD framework. We applied this guidance to outline strategies that resist, accept, or direct change in the context of management of aquatic vegetation, floodplain vegetation, and fish communities across nearly 2000 river kilometers. We provide a case study for how knowledge of ecological dynamics can aid in assessing which management approach(es) are likely to be most ecologically feasible in a changing world. Continued learning from management decisions will be critical to advance our understanding of how ecosystems respond and inform the management of ecosystems for desirable and resilient outcomes.

Conceptualizing alternate regimes in a large floodplain-river ecosystem: Water clarity, invasive fish, and floodplain vegetation.

Regime shifts - persistent changes in the structure and function of an ecosystem - are well-documented for some ecosystems and have informed research and management of these ecosystems. In floodplain-river ecosystems, there is growing interest from restoration practitioners in ecological resilience, yet regime shifts remain poorly understood in these ecosystems. To understand how regime shifts may apply to floodplain-river ecosystems, we synthesize our understanding of ecosystem dynamics using an alternate regimes conceptual framework. We present three plausible sets of alternate regimes relevant to natural resource management interests within the Upper Mississippi River and Illinois River. These alternate regimes include: 1) a clear water and abundant vegetation regime vs. a turbid water and sparse vegetation regime in lentic, off-channel areas, 2) a diverse native fish community regime vs. an invasive-dominated fish community regime, and 3) a regime characterized by a diverse and dynamic mosaic of floodplain vegetation types vs. one characterized as a persistent invasive wet meadow monoculture. For each set of potential alternate regimes, we review available literature to synthesize known or hypothesized feedback mechanisms that reinforce regimes, controlling variables that drive regime transitions, and current restoration pathways. Our conceptual models provide preliminary support for the existence of alternate regimes in floodplain-river ecosystems. Quantitatively testing hypotheses contained within the conceptual model are important next steps in evaluating the model. Ultimately, the synthesis and evaluation of alternate regimes can inform the utility of resilience concepts in restoration and management on the Upper Mississippi River and Illinois River and improve our understanding of ecosystem dynamics in other large, heavily managed floodplain-river ecosystems.

Improving ecosystem health in highly altered river basins: a generalized framework and its application to the Mississippi-Atchafalaya River Basin.

Continued large-scale public investment in declining ecosystems depends on demonstrations of "success". While the public conception of "success" often focuses on restoration to a pre-disturbance condition, the scientific community is more likely to measure success in terms of improved ecosystem health. Using a combination of literature review, workshops and expert solicitation we propose a generalized framework to improve ecosystem health in highly altered river basins by reducing ecosystem stressors, enhancing ecosystem processes and increasing ecosystem resilience. We illustrate the use of this framework in the Mississippi-Atchafalaya River Basin (MARB) of the central United States (U.S.), by (i) identifying key stressors related to human activities, and (ii) creating a conceptual ecosystem model relating those stressors to effects on ecosystem structure and processes. As a result of our analysis, we identify a set of landscape-level indicators of ecosystem health, emphasizing leading indicators of stressor removal (e.g., reduced anthropogenic nutrient inputs), increased ecosystem function (e.g., increased water storage in the landscape) and increased resilience (e.g., changes in the percentage of perennial vegetative cover). We suggest that by including these indicators, along with lagging indicators such as direct measurements of water quality, stakeholders will be better able to assess the effectiveness of management actions. For example, if both leading and lagging indicators show improvement over time, then management actions are on track to attain desired ecosystem condition. If, however, leading indicators are not improving or even declining, then fundamental challenges to ecosystem health remain to be addressed and failure to address these will ultimately lead to declines in lagging indicators such as water quality. Although our model and indicators are specific to the MARB, we believe that the generalized framework and the process of model and indicator development will be valuable in an array of altered river basins.

Understanding ecological response to physical characteristics in side channels of a large floodplain-river ecosystem.

Side channels in large floodplain rivers serve a variety of important ecological roles, particularly in reaches where habitat conditions have been degraded or diminished. We developed hypotheses regarding side channel ecological structure whereby we expected species richness of young-of-year fishes to generally be higher in shallower, more physically heterogeneous side channels with lower velocities, with differences based on reproductive guild. We also hypothesized species richness of adult fishes to be higher in side channels with greater heterogeneity that could support diverse foraging resources and provide refugia during extreme flow conditions. To test these hypotheses, we used a 28-year fish community dataset from the Upper Mississippi and Illinois Rivers. Across six study reaches, we assessed metrics of side channel physical size, heterogeneity, and connectivity that were hypothesized to explain variance of fish community response, while accounting for site-level factors across 52 side channels using multilevel models. We then used these side channel-level characteristics in a K-means cluster analysis to classify 1126 side channels across 32 reaches of the river system. Our results indicated that the relative explanatory contributions of physical metrics varied by response variable, providing varying evidence in support of our hypotheses, and indicating that different forms of heterogeneity matter in different ways. Side channel-level factors were more explanatory of fish community responses in side channels of upstream reaches compared to downstream reaches and percent wet forest was the most explanatory side channel-level factor of fish community responses across all models. Our classification of side channels indicated strong spatial contrasts in the abundance and diversity of side channels across reaches. Scaling up to understand how the diversity and abundance of different types of side channels contributes to landscape-scale ecological functions and processes would be useful for establishing targets for reach-scale physical heterogeneity.

An assessment of the relation between metal contaminated sediment and freshwater mussel populations in the Big River, Missouri.

The Big River in southeast Missouri drains the largest historical lead mining area in the United States. Ongoing releases of metal contaminated sediments into this river are well documented and are suspected of suppressing freshwater mussel populations. We characterized the spatial extent of metal contaminated sediments and evaluated its relationship with mussel populations in the Big River. Mussels and sediments were collected at 34 sites with potential metal effects and 3 reference sites. Analysis of sediment samples showed that lead (Pb) and zinc (Zn) concentrations were 1.5 to 65 times greater than background concentrations in the reach extending 168 km downstream from Pb mining releases. Mussel abundance decreased acutely downstream from these releases where sediment Pb concentrations were highest and increased gradually as Pb sediment concentrations attenuated downstream. We compared current species richness with historical survey data from three reference rivers with similar physical habitat characteristics and human effects, but without Pb-contaminated sediment. Big River species richness was on average about one-half that expected based on reference stream populations and was 70-75 % lower in reaches with high median Pb concentrations. Sediment Zn and cadmium, and particularly Pb, had significant negative correlations with species richness and abundance. The association of sediment Pb concentrations with mussel community metrics in otherwise high-quality habitat indicates that Pb toxicity is likely responsible for depressed mussel populations observed within the Big River. We used concentration-response regressions of mussel density verses sediment Pb to determine that the Big River mussel community is adversely affected when sediment Pb concentrations are above 166 ppm, the concentration associated with 50 % decreases in mussel density. Based on this assessment of metals concentrations sediment and mussel fauna, our findings indicate that sediment in approximately 140 km of the Big River with suitable habitat has a toxic effect to mussels.

Identifying monitoring information needs that support the management of fish in large rivers.

Management actions intended to benefit fish in large rivers can directly or indirectly affect multiple ecosystem components. Without consideration of the effects of management on non-target ecosystem components, unintended consequences may limit management efficacy. Monitoring can help clarify the effects of management actions, including on non-target ecosystem components, but only if data are collected to characterize key ecosystem processes that could affect the outcome. Scientists from across the U.S. convened to develop a conceptual model that would help identify monitoring information needed to better understand how natural and anthropogenic factors affect large river fishes. We applied the conceptual model to case studies in four large U.S. rivers. The application of the conceptual model indicates the model is flexible and relevant to large rivers in different geographic settings and with different management challenges. By visualizing how natural and anthropogenic drivers directly or indirectly affect cascading ecosystem tiers, our model identified critical information gaps and uncertainties that, if resolved, could inform how to best meet management objectives. Despite large differences in the physical and ecological contexts of the river systems, the case studies also demonstrated substantial commonalities in the data needed to better understand how stressors affect fish in these systems. For example, in most systems information on river discharge and water temperature were needed and available. Conversely, information regarding trophic relationships and the habitat requirements of larval fishes were generally lacking. This result suggests that there is a need to better understand a set of common factors across large-river systems. We provide a stepwise procedure to facilitate the application of our conceptual model to other river systems and management goals.