An experiment in >1000 river and riparian sites found spatial patterns and controls of carbon processing at the global scale.

Riparian ecosystems support mosaics of terrestrial and aquatic plant species that enhance regional biodiversity and provide important ecosystem services to humans. Species composition and the distribution of functional traits – traits that define species in terms of their ecological roles – within riparian plant communities are rapidly changing in response to various global change drivers. Here, we present a conceptual framework illustrating how changes in dependent wildlife communities and ecosystem processes can be predicted by examining shifts in riparian plant functional trait diversity and redundancy (overlap). Three widespread examples of altered riparian plant composition are: shifts in the dominance of deciduous and coniferous species; increases in drought‐tolerant species; and the increasing global distribution of plantation and crop species. Changes in the diversity and distribution of critical plant functional traits influence terrestrial and aquatic food webs, organic matter production and processing, nutrient cycling, water quality, and water availability. Effective conservation efforts and riparian ecosystems management require matching of plant functional trait diversity and redundancy with tolerance to environmental changes in all biomes.

The measurement of stream metabolism (gross primary production and respiration) has become more feasible with the availability of more reliable dissolved oxygen (DO) probes. Such metabolic measurements offer important opportunities in fundamental and applied research, especially in relating stream metabolic responses to human and other pressures. The accurate determination of the reaeration coefficient is one challenge for making reliable ecological inferences from DO measurements made over many diel periods (i.e., months or years). We outline three methods for calculating atmospheric reaeration but concentrate on the use of statistical estimation to simultaneously estimate reaeration and metabolic rates using Bayesian model fitting. While there are existing programs (ModelMaker and Bayesian Metabolic Model [BaMM]), these are either slow or unable to be used easily for fitting multiple days of metabolic data (one to many months). Our implementation, BAyesian Single-station Estimation (BASE), uses freely available software (R and OpenBUGS), includes a batch mode that can fit data for many days, and provides visual and statistical measures of "goodness-of-fit." We compare the results of the BASE, ModelMaker, and BaMM programs.Measures of stream metabolism as rates of aquatic primary production and ecosystem-wide respiration are integrative indicators of aquatic ecosystem condition (Mulholland et al. 2005). Primary production and ecosystem respiration rates are governed by the complex interactions of hydrology, riparian and in-stream vegetation, geomorphology, climate, chemistry and biology of the stream environment, and the condition of the catchment that the stream drains (Mulholland et al. 2001;Grace and Imberger 2006;Young et al. 2008).A major goal of stream metabolism measurements is to use metabolic values to infer the condition of the ecosystem, or to evaluate the response of metabolism to potential pressures, usually of human origins, operating at multiple spatial and temporal scales (Bunn et al. 1999;Fellows et al. 2006). Disentangling the effects of these pressures from other factors affecting metabolic behavior, especially the effect of cloud cover on rates of primary production, is often problematic when analyses rely on profiles from only a few days.Longer-term data collection has become more common (e.g., Roberts and Mulholland 2007) and, when coupled with more reliable measurement of concentrations of dissolved oxygen (DO), offers the prospect of using stream metabolism to investigate differences among systems and evaluation of long-term (e.g., multiyear) trends . The availability of nonconsumptive, fluorescence-based probes for measuring (DO) over the past decade has much enhanced the applicability and convenience of the open-water method because these new generation DO probes have little signal drift, which was a problem for earlier probes (Almeida et al. 2014). Odum (1956) proposed the method for determining stream metabolism in lotic systems by monitoring the temporal change in DO concent...

Concern about the functional consequences of unprecedented loss in biodiversity has prompted biodiversity-ecosystem functioning (BEF) research to become one of the most active fields of ecological research in the past 25 years. Hundreds of experiments have manipulated biodiversity as an independent variable and found compelling support that the functioning of ecosystems increases with the diversity of their ecological communities. This research has also identified some of the mechanisms underlying BEF relationships, some context-dependencies of the strength of relationships, as well as implications for various ecosystem services that mankind depends upon. In this paper, we argue that a multitrophic perspective of biotic interactions in random and nonrandom biodiversity change scenarios is key to advance future BEF research and to address some of its most important remaining challenges. We discuss that the study and the quantification of multitrophic interactions in space and time facilitates scaling up from small-scale biodiversity manipulations and ecosystem function assessments to management-relevant spatial scales across ecosystem boundaries. We specifically consider multitrophic conceptual frameworks to understand and predict the context-dependency of BEF relationships. Moreover, we highlight the importance of the eco-evolutionary underpinnings of multitrophic BEF relationships. We outline that FAIR data (meeting the standards of findability, accessibility, interoperability, and reusability) and reproducible processing will be key to advance this field of research by making it more integrative. Finally, we show how these BEF insights may be implemented for ecosystem management, society, and policy. Given that human well-being critically depends on the multiple services provided by diverse, multitrophic communities, integrating the approaches of evolutionary Eisenhauer et al.