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Across watershed science, two key variables emerge–streamflow and solute concentration–which serve as the basis for efforts ranging from basic watershed biogeochemistry research to policy decisions surrounding watershed management. However, we rarely account for how error in discharge (Q) impacts estimates of downstream nutrient loading. Here, we examined the impact of uncertainty in streamflow measurements on estimates of downstream nitrate export using publicly available data from the U.S. Geological Survey (USGS). We characterized how uncertainty in stage-discharge relationships impacts annual flux estimates across 70 USGS gages. Our results indicate the interquartile range of relative error in Q was 33% across these USGS sites. We documented a wide range in mean error in annual nitrate loads; some sites were underestimated (−105%), while predicted loads at other sites vastly overestimated (500%). Overall, any error in estimating Q leads to significant unpredictability of annual nutrient loads, which are often used as critical success benchmarks for governmental nutrient reduction strategies. Moreover, error in annual nitrate loads (as mass, kg) increases with mean Q; thus, as high flows become more unpredictable and intense under future climate change, error in estimates of downstream nutrient loading may also increase. Together, this indicates that error in Q may drastically influence our measures of water quality success and decrease our ability to accurately quantify progress towards algal bloom and ‘dead zone’ reduction.

 

The United States of America has a diverse collection of freshwater mussels comprising 301 species distributed among 59 genera and two families (Margaritiferidae and Unionidae), each having a unique suite of traits. Mussels are among the most imperilled animals and are critical components of their ecosystems, and successful management, conservation and research requires a cohesive and widely accessible data source. Although trait-based analysis for mussels has increased, only a small proportion of traits reflecting mussel diversity in this region has been collated. Decentralized and non-standardized trait information impedes large-scale analysis. Assembling trait data in a synthetic dataset enables comparison across species and lineages and identification of data gaps. We collated data from the primary literature, books, state and federal reports, theses and dissertations, and museum collections into a centralized dataset covering information on taxonomy, morphology, reproductive ecology and life history, fish hosts, habitats, thermal tolerance, geographic distribution, available genetic information, and conservation status. By collating these traits, we aid researchers in assessing variation in mussel traits and modelling ecosystem change.

 

Positive biodiversity–ecosystem functioning (BEF) relationships observed in experiments can be challenging to identify in natural communities. Freshwater animal communities are disproportionately harmed by global change that results in accelerated species loss. Understanding how animal-mediated ecosystems functions may change as a result of global change can help determine whether biodiversity or species-specific conservation will be effective at maintaining function. Unionid mussels represent half of imperiled species in freshwater ecosystems globally and perform important ecological functions such as water filtration and nutrient recycling. We explored BEF relationships for 22 naturally assembled mussel aggregations spanning three river basins. We used the Price equation to partition the contributions of species richness, composition, and context dependent interactions to two functions of interests: spatially-explicit standing-stock biomass (indirect proxy for function) and species-specific nitrogen (N) excretion rates (direct measure of N recycling). Random and non-random species loss each reduced biomass and N recycling. Many rare species with low contributions to biomass contributed to standing-stock biomass in all basins. Widespread species had variable function across sites, such that context dependent effects (CDEs) outweighed richness effects on standing-stock biomass in two basins, and were similar to richness effects in the third. Richness effects outweighed CDEs for N recycling. Thus, many species contributed a low proportion to overall N-recycling; a product we attribute to the high evenness and functional effect trait diversity associated with these communities. The loss of low-functioning species reduced the function of persisting species. This novel result using observational data adds evidence that positive species interactions, such as interspecific facilitation, may be a mechanism by which biodiversity enhances ecosystem functions. Our work stresses the importance of evaluating species-specific contributions to functions in diverse systems, such as nutrient cycling when maintaining specific animal-mediated functions is a management goal because indirect proxies may not completely characterize BEF relationships. 

The use of environmental DNA (eDNA) to assess aquatic biodiversity is a growing field with great potential for monitoring and managing threatened species, like freshwater mussel (Unionidae) populations. Freshwater mussels are globally imperiled and serve essential roles in aquatic systems as a food source and as a natural water filter making their management essential for ecosystem health. Unfortunately, mussel populations are often understudied, and challenges exist to accurately and efficiently describe the full suite of species present. Multispecies eDNA approaches may also be more challenging where freshwater mussel populations are most diverse due to ongoing and significant taxonomic restructuring that has been further complicated by molecular phylogenies using mitochondrial genes. For this study, we developed a microfluidic metabarcoding array that targets a wide range of species, from invertebrates to fishes, with an emphasis on detecting unionid mussels known to be present in the Sipsey River, Alabama. We compared mussel species diversity across six sites with well-studied mussel assemblages using eDNA surveys and traditional quadrat surveys in 2016. We examined how factors such as mussel population density, biomass and location in the river substrate impacted our ability to detect certain species; and investigated unexpected eDNA detections through phylogenetic analysis. Our eDNA results for fish and mussel species were broadly consistent with the data from traditional electrofishing and quadrat-based field surveys, although both community eDNA and conventional sampling detected species unique to that method. Our phylogenetic analysis agreed with other studies that treat Pleurobema decisum and P. chattanoogaense as synonymous species; however, they are still listed as unique species in molecular databases which complicates their identity in a metabarcoding assay. We also found that Fusconaia flava and F. cerina are indistinguishable from one another using a portion of the NADH dehydrogenase Subunit 1 (ND1) marker, which may warrant further investigation into whether or not they are synonymous. Our results show that many factors impacted our ability to detect and correctly identify Unionidae mussel species. Here we describe the obstacles we faced, including the murky phylogeny of Unionidae mussels and turbid river conditions, and our development of a potentially impactful freshwater mussel monitoring eDNA assay. 

Accelerating the design and implementation of environmental flows (e-flows) is essential to curb the rapid, ongoing loss of freshwater biodiversity and the benefits it provides to people. However, the effectiveness of e-flow programs may be limited by a singular focus on ensuring adequate flow conditions at local sites, which overlooks the role of other ecological processes. Recent advances in metasystem ecology have shown that biodiversity patterns and ecosystem functions across river networks result from the interplay of local (environmental filtering and biotic interactions) and regional (dispersal) ecological processes. No guidelines currently exist to account for these processes in designing e-flows. We address this gap by providing a step-by-step operational framework that outlines how e-flows can be designed to conserve or restore metasystem dynamics. Our recommendations are relevant to diverse regulatory contexts and can improve e-flow outcomes even in basins with limited in situ data.

 

The loose‐equilibrium concept (LEC) predicts that ecological assemblages change transiently but return towards an earlier or average structure. The LEC framework can help determine whether assemblages vary within expected ranges or are permanently altered following environmental change.

Long‐lived, slow‐growing animals typically respond slowly to environmental change, and their assemblage dynamics may respond over decades, which transcends most ecological studies. Unionid mussels are valuable for studying dynamics of long‐lived animals because they can live >50 years and occur in dense, species‐rich assemblages (mussel beds). Mussel beds can persist for decades, but disturbance can affect species differently, resulting in variable trajectories according to differences in species composition within and among rivers.

We used long‐term data sets (10–40 years) from seven rivers in the eastern United States to evaluate the magnitude, pace and directionality of mussel assemblage change within the context of the LEC.

Site trajectories varied within and among streams and showed patterns consistent with either the LEC or directional change. In streams that conformed to the LEC, rank abundance of dominant species remained stable over time, but directional change in other streams was driven by changes in the rank abundance and composition of dominant species.

Characteristics of mussel assemblage change varied widely, ranging from those conforming to the LEC to those showing strong directional change. Conservation approaches that attempt to maintain or create a desired assemblage condition should acknowledge this wide range of possible assemblage trajectories and that the environmental factors that influence those changes remain poorly understood.