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Abstract We present a newly developed design for a self‐contained benthic chamber for conducting in situ ecosystem experiments in streams, with a focus on biogeochemical processes such as ecosystem metabolism and nutrient cycling. Our design expands upon smaller, portable chamber designs and is meant to answer questions at larger scales. These new chambers allow for a high level of experimental control in the field and can be used to generate spatially explicit data regarding ecosystem processes and to test mechanistic hypotheses. They are built to be deployed within the stream over periods of weeks to months and to withstand natural hydraulic forces of the benthic zone. First, we describe the materials and steps that are needed to construct these chambers in detail. Then, we report the methods and results of a multi‐part, diagnostic field study meant to demonstrate the performance and utility of the design. We quantified solute dynamics using a conservative tracer injection, then we estimated ecosystem metabolism across the study site and performed nutrient additions. We detected asymptotic declines in tracer concentrations, calculated nutrient removal rates, and mapped hotspots of ecosystem metabolism. Flow velocity and water depth imposed limitations, but with appropriate methodological forethought these limitations can be minimized. The capacity of our design to accommodate complex, three‐dimensional habitats and macrofauna, along with the capability to generate spatially explicit data, are the main advances we present. These advances provide a novel method whereby motivated users can connect mechanistic hypothesis testing with natural ecological processes through ecosystem‐level field experiments. 

ABSTRACT Freshwater mussels (Bivalvia: Unionida) are among the most imperilled freshwater taxa. Yet, there is a lack of basic life history information for mussels, including data on their growth and longevity. These data help inform conservation efforts, as they can indicate whether species or populations may be vulnerable to decline and inform which species may be best adapted to certain habitats. We aimed to quantify growth and longevity in five mussel species from four river systems in the southeastern United States and test whether growth was related to stream flow. We also interpreted our findings in the context of life history theory.To model mussel growth and longevity, we cut radial thick sections from the shells of mussels and used high‐resolution photography to image the shells. We identified annual growth rings (annuli) and used von Bertalanffy growth models to estimate growth rate (K) and maximum age (A_max) across 13 mussel populations. We then used biochronological methods to remove age‐related variation in annual growth in each shell. We tested whether annual growth was correlated with stream flow using discharge‐based statistics.We found substantial variation inKandA_maxamong species and among populations of the same species.Kwas negatively related toA_max. We did not find consistent correlations between annual growth and stream flow.Our estimates ofKandA_maxalign with previous studies on closely related species and populations. They also match the eco‐evolutionary prediction that growth rate and longevity are negatively related. Life history theory predicts that short‐lived species with higher growth rates should be better adapted to environments with cyclical disturbance regimes, whereas longer‐lived species with low growth rates should be better adapted to stable environments. The lack of correlation between annual growth and stream flow suggests that mussel growth may be limited by other factors in our study system.While some species seem to have relatively narrow ranges for growth and longevity, other species show wide variation among populations. This highlights the need for species‐ and population‐specific conservation efforts. Fundamental life history information can be integrated with other species traits to predict how freshwater taxa may respond to ecological threats. 

Abstract Increases in species richness with habitat area (species–area relationship, or SAR) and increases in ecosystem function with species richness (biodiversity–ecosystem functioning, or BEF) are widely studied ecological patterns. Incorporating functional trait analysis into assemblage datasets may help clarify interpretations of SAR and BEF relationships in natural ecological systems. For example, life history theory can be used to make predictions about what species are most important in generating ecosystem function given a certain set of environmental conditions. We used quantitative assemblage data for freshwater mussels at nine sites in western Alabama, USA, to test for SAR and BEF relationships. At each site, we calculated species richness, mussel assemblage density, and two fundamental metrics of ecosystem function: biomass and secondary production. We also tested whether the proportional biomass and production contributions from species belonging to each of three life history strategies—opportunistic strategistsadapted to unstable or frequently disturbed habitats,periodic strategistsadapted to habitats subject to predictable large‐scale disturbances, andequilibrium strategistsadapted to stable habitats—varied longitudinally with stream drainage area, a proxy for habitat area. Species richness increased with stream size (SAR), and both biomass and production increased with species richness (BEF) and mussel density. There were few longitudinal changes in the proportional contributions of the different life history strategy classifications that we used, but the invasive clamCorbicula flumineacontributed proportionally more biomass and production at sites that had smaller drainage areas. This study provides further evidence for a clear longitudinal SAR in stream‐dwelling taxa. It also suggests BEF relationships for biomass and secondary production in natural assemblages but underscores the importance of assemblage density in BEF studies that use observational field data. Variation in proportional biomass and production contributions by different life history strategies was likely limited by the size of the stream size gradient in our study, as contributions were uniformly high for species with life history traits better adapted to stable and productive habitats such as mid‐sized rivers with low or predictable hydrologic disturbance frequencies. This highlights the need to understand how organisms' functional traits govern their relationships to the environment at different scales.