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  1. Mordecai, Erin (Ed.)
    Free, publicly-accessible full text available April 1, 2023
  2. Reynolds, Heather (Ed.)
    Free, publicly-accessible full text available November 1, 2022
  3. null (Ed.)
  4. Global loss of biodiversity and its associated ecosystem services is occurring at an alarming rate and is predicted to accelerate in the future. Metacommunity theory provides a framework to investigate multi-scale processes that drive change in biodiversity across space and time. Short-term ecological studies across space have progressed our understanding of biodiversity through a metacommunity lens, however, such snapshots in time have been limited in their ability to explain which processes, at which scales, generate observed spatial patterns. Temporal dynamics of metacommunities have been understudied, and large gaps in theory and empirical data have hindered progress in our understanding ofmore »underlying metacommunity processes that give rise to biodiversity patterns. Fortunately, we are at an important point in the history of ecology, where long-term studies with cross-scale spatial replication provide a means to gain a deeper understanding of the multiscale processes driving biodiversity patterns in time and space to inform metacommunity theory. The maturation of coordinated research and observation networks, such as the United States Long Term Ecological Research (LTER) program, provides an opportunity to advance explanation and prediction of biodiversity change with observational and experimental data at spatial and temporal scales greater than any single research group could accomplish. Synthesis of LTER network community datasets illustrates that long-term studies with spatial replication present an under-utilized resource for advancing spatio-temporal metacommunity research. We identify challenges towards synthesizing these data and present recommendations for addressing these challenges. We conclude with insights about how future monitoring efforts by coordinated research and observation networks could further the development of metacommunity theory and its applications aimed at improving conservation efforts.« less
  5. Disturbances fundamentally alter ecosystem functions, yet predicting their impacts remains a key scientific challenge. While the study of disturbances is ubiquitous across many ecological disciplines, there is no agreed-upon, cross-disciplinary foundation for discussing or quantifying the complexity of disturbances, and no consistent terminology or methodologies exist. This inconsistency presents an increasingly urgent challenge due to accelerating global change and the threat of interacting disturbances that can destabilize ecosystem responses. By harvesting the expertise of an interdisciplinary cohort of contributors spanning 42 institutions across 15 countries, we identified an essential limitation in disturbance ecology: the word ‘disturbance’ is used interchangeably tomore »refer to both the events that cause, and the consequences of, ecological change, despite fundamental distinctions between the two meanings. In response, we developed a generalizable framework of ecosystem disturbances, providing a well-defined lexicon for understanding disturbances across perspectives and scales. The framework results from ideas that resonate across multiple scientific disciplines and provides a baseline standard to compare disturbances across fields. This framework can be supplemented by discipline-specific variables to provide maximum benefit to both inter- and intra-disciplinary research. To support future syntheses and meta-analyses of disturbance research, we also encourage researchers to be explicit in how they define disturbance drivers and impacts, and we recommend minimum reporting standards that are applicable regardless of scale. Finally, we discuss the primary factors we considered when developing a baseline framework and propose four future directions to advance our interdisciplinary understanding of disturbances and their social-ecological impacts: integrating across ecological scales, understanding disturbance interactions, establishing baselines and trajectories, and developing process-based models and ecological forecasting initiatives. Our experience through this process motivates us to encourage the wider scientific community to continue to explore new approaches for leveraging Open Science principles in generating creative and multidisciplinary ideas.« less
  6. Abstract. A comprehensive set of measurements and calculated metricsdescribing physical, chemical, and biological conditions in the rivercorridor is presented. These data were collected in a catchment-wide,synoptic campaign in the H. J. Andrews ExperimentalForest (Cascade Mountains, Oregon, USA) in summer 2016 during low-dischargeconditions. Extensive characterization of 62 sites including surface water,hyporheic water, and streambed sediment was conducted spanning 1st- through5th-order reaches in the river network. The objective of the sample designand data acquisition was to generate a novel data set to support scaling ofriver corridor processes across varying flows and morphologic forms presentin a river network. The data are available at https://doi.org/10.4211/hs.f4484e0703f743c696c2e1f209abb842 (Ward,more »2019).« less
  7. Abstract. Although most field and modeling studies of river corridorexchange have been conducted at scales ranging from tens to hundreds of meters,results of these studies are used to predict their ecological andhydrological influences at the scale of river networks. Further complicatingprediction, exchanges are expected to vary with hydrologic forcing and thelocal geomorphic setting. While we desire predictive power, we lack acomplete spatiotemporal relationship relating discharge to the variation ingeologic setting and hydrologic forcing that is expected across a riverbasin. Indeed, the conceptual model of Wondzell (2011) predicts systematicvariation in river corridor exchange as a function of (1) variation inbaseflow over time atmore »a fixed location, (2) variation in discharge withlocation in the river network, and (3) local geomorphic setting. To testthis conceptual model we conducted more than 60 solute tracer studiesincluding a synoptic campaign in the 5th-order river network of the H. J. Andrews Experimental Forest (Oregon, USA) and replicate-in-time experimentsin four watersheds. We interpret the data using a series of metricsdescribing river corridor exchange and solute transport, testing forconsistent direction and magnitude of relationships relating these metricsto discharge and local geomorphic setting. We confirmed systematic decreasein river corridor exchange space through the river networks, from headwatersto the larger main stem. However, we did not find systematic variation withchanges in discharge through time or with local geomorphic setting. Whileinterpretation of our results is complicated by problems with the analyticalmethods, the results are sufficiently robust for us to conclude that space-for-timeand time-for-space substitutions are not appropriate in our study system.Finally, we suggest two strategies that will improve the interpretability oftracer test results and help the hyporheic community develop robust datasets that will enable comparisons across multiple sites and/or dischargeconditions.« less