Browsing by Author "Graham, Emily B."

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    Co-located contemporaneous mapping of morphological, hydrological, chemical, and biological conditions in a 5th-order mountain stream network, Oregon, USA
    Ward, Adam S.; Zarnetske, Jay P.; Baranov, Viktor; Blaen, Phillip J.; Brekenfeld, Nicolai; Chu, Rosalie; Derelle, Romain; Drummond, Jennifer D.; Fleckenstein, Jan H.; Garayburu-Caruso, Vanessa; Graham, Emily B.; Hannah, David; Harman, Ciaran J.; Herzog, Skuyler; Hixson, Jase; Knapp, Julia L. A.; Krause, Stefan; Kurz, Marie J.; Lewandowski, Joerg; Li, Angang; Marti, Eugenia; Miller, Melinda C.; Milner, Alexander M.; Neil, Kerry; Orsini, Luisa; Packman, Aaron I.; Plont, Stephen; Renteria, Lupita; Roche, Kevin; Royer, Todd; Schmadel, Noah M.; Segura, Catalina; Stegen, James; Toyoda, Jason; Wells, Jacqueline; Wisnoski, Nathan I.; Wondzell, Steven M. (2019-10-22)
    A comprehensive set of measurements and calculated metrics describing physical, chemical, and biological conditions in the river corridor is presented. These data were collected in a catchment-wide, synoptic campaign in the H. J. Andrews Experimental Forest (Cascade Mountains, Oregon, USA) in summer 2016 during low-discharge conditions. Extensive characterization of 62 sites including surface water, hyporheic water, and streambed sediment was conducted spanning 1st- through 5th-order reaches in the river network. The objective of the sample design and data acquisition was to generate a novel data set to support scaling of river corridor processes across varying flows and morphologic forms present in a river network. The data are available at https://doi.org/10.4211/hs.f4484e0703f743c696c2e1f209abb842 (Ward, 2019).
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    Microbes as Engines of Ecosystem Function: When Does Community Structure Enhance Predictions of Ecosystem Processes?
    Graham, Emily B.; Knelman, Joseph E.; Schindlbacher, Andreas; Siciliano, Steven; Breulmann, Marc; Yannarell, Anthony; Bemans, J. M.; Abell, Guy; Philippot, Laurent; Prosser, James; Foulquier, Arnaud; Yuste, Jorge C.; Glanville, Helen C.; Jones, Davey L.; Angel, Foey; Salminen, Janne; Newton, Ryan J.; Buergmann, Helmut; Ingram, Lachlan J.; Hamer, Ute; Siljanen, Henri M. P.; Peltoniemi, Krista; Potthast, Karin; Baneras, Lluis; Hartmann, Martin; Banerjee, Samiran; Yu, Ri-Qing; Nogaro, Geraldine; Richter, Andreas; Koranda, Marianne; Castle, Sarah C.; Goberna, Marta; Song, Bongkeun; Chatterjee, Amitava; Nunes, Olga C.; Lopes, Ana R.; Cao, Yiping; Kaisermann, Aurore; Hallin, Sara; Strickland, Michael S.; Garcia-Pausas, Jordi; Barba, Josep; Kang, Hojeong; Isobe, Kazuo; Papaspyrou, Sokratis; Pastorelli, Roberta; Lagomarsino, Alessandra; Lindstrom, Eva S.; Basiliko, Nathan; Nemergut, Diana R. (Frontiers, 2016-02-24)
    Microorganisms are vital in mediating the earth's biogeochemical cycles; yet, despite our rapidly increasing ability to explore complex environmental microbial communities, the relationship between microbial community structure and ecosystem processes remains poorly understood. Here, we address a fundamental and unanswered question in microbial ecology: 'When do we need to understand microbial community structure to accurately predict function?' We present a statistical analysis investigating the value of environmental data and microbial community structure independently and in combination for explaining rates of carbon and nitrogen cycling processes within 82 global datasets. Environmental variables were the strongest predictors of process rates but left 44% of variation unexplained on average, suggesting the potential for microbial data to increase model accuracy. Although only 29% of our datasets were significantly improved by adding information on microbial community structure, we observed improvement in models of processes mediated by narrow phylogenetic guilds via functional gene data, and conversely, improvement in models of facultative microbial processes via community diversity metrics. Our results also suggest that microbial diversity can strengthen predictions of respiration rates beyond microbial biomass parameters, as 53% of models were improved by incorporating both sets of predictors compared to 35% by microbial biomass alone. Our analysis represents the first comprehensive analysis of research examining links between microbial community structure and ecosystem function. Taken together, our results indicate that a greater understanding of microbial communities informed by ecological principles may enhance our ability to predict ecosystem process rates relative to assessments based on environmental variables and microbial physiology.
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    Spatial and temporal variation in river corridor exchange across a 5th-order mountain stream network
    Ward, Adam S.; Wondzell, Steven M.; Schmadel, Noah M.; Herzog, Skuyler; Zarnetske, Jay P.; Baranov, Viktor; Blaen, Phillip J.; Brekenfeld, Nicolai; Chu, Rosalie; Derelle, Romain; Drummond, Jennifer D.; Fleckenstein, Jan H.; Garayburu-Caruso, Vanessa; Graham, Emily B.; Hannah, David; Harman, Ciaran J.; Hixson, Jase; Knapp, Julia L. A.; Krause, Stefan; Kurz, Marie J.; Lewandowski, Joerg; Li, Angang; Marti, Eugenia; Miller, Melinda C.; Milner, Alexander M.; Neil, Kerry; Orsini, Luisa; Packman, Aaron I.; Plont, Stephen; Renteria, Lupita; Roche, Kevin; Royer, Todd; Segura, Catalina; Stegen, James; Toyoda, Jason; Wells, Jacqueline; Wisnoski, Nathan I. (2019-12-20)
    Although most field and modeling studies of river corridor exchange have been conducted at scales ranging from tens to hundreds of meters, results of these studies are used to predict their ecological and hydrological influences at the scale of river networks. Further complicating prediction, exchanges are expected to vary with hydrologic forcing and the local geomorphic setting. While we desire predictive power, we lack a complete spatiotemporal relationship relating discharge to the variation in geologic setting and hydrologic forcing that is expected across a river basin. Indeed, the conceptual model of Wondzell (2011) predicts systematic variation in river corridor exchange as a function of (1) variation in baseflow over time at a fixed location, (2) variation in discharge with location in the river network, and (3) local geomorphic setting. To test this conceptual model we conducted more than 60 solute tracer studies including a synoptic campaign in the 5th-order river network of the H. J. Andrews Experimental Forest (Oregon, USA) and replicate-intime experiments in four watersheds. We interpret the data using a series of metrics describing river corridor exchange and solute transport, testing for consistent direction and magnitude of relationships relating these metrics to discharge and local geomorphic setting. We confirmed systematic decrease in river corridor exchange space through the river networks, from headwaters to the larger main stem. However, we did not find systematic variation with changes in discharge through time or with local geomorphic setting. While interpretation of our results is complicated by problems with the analytical methods, the results are sufficiently robust for us to conclude that space-for-time and time-for-space substitutions are not appropriate in our study system. Finally, we suggest two strategies that will improve the interpretability of tracer test results and help the hyporheic community develop robust datasets that will enable comparisons across multiple sites and/or discharge conditions.