Light and flow regimes regulate the metabolism of rivers

Mean annual temperature and mean annual precipitation drive much of the variation in productivity across Earth's terrestrial ecosystems but do not explain variation in gross primary productivity (GPP) or ecosystem respiration (ER) in flowing waters. We document substantial variation in the magnitude and seasonality of GPP and ER across 222 US rivers. In contrast to their terrestrial counterparts, most river ecosystems respire far more carbon than they fix and have less pronounced and consistent seasonality in their metabolic rates. We find that variation in annual solar energy inputs and stability of flows are the primary drivers of GPP and ER across rivers. A classification schema based on these drivers advances river science and informs management.We thank Ted Stets, Jordan Read, Tom Battin, Sophia Bonjour, Marina Palta, and members of the Duke River Center for their help in developing these ideas. This work was supported by grants from the NSF 1442439 (to E.S.B. and J.W.H.), 1834679 (to R.O.H.), 1442451 (to R.O.H.), 2019528 (to R.O.H. and J.R.B.), 1442140 (to M.C.), 1442451 (to A.M.H.), 1442467 (to E.H.S.), 1442522 (to N.B.G.), 1624807 (to N.B.G.), and US Geological Survey funding for the working group was supported by the John Wesley Power Center for Analysis and Synthesis. Phil Savoy contributed as a postdoc- toral associate at Duke University and as a postdoctoral associate (contractor) at the US Geological Survey

A LOCATION-DEPENDENT RUNS-AND-GAPS MODEL FOR PREDICTING TCP PERFORMANCE OVER A UAV WIRELESS CHANNEL

In this paper, we use a finite-state model to predict the performance of the Transmission Control Protocol (TCP) over a varying wireless channel between an unmanned aerial vehicle (UAV) and ground nodes. As a UAV traverses its flight path, the wireless channel may experience periods of significant packet loss, successful packet delivery, and intermittent reception. By capturing packet run-length and gap-length statistics at various locations on the flight path, this locationdependent model can predict TCP throughput in spite of dynamically changing channel characteristics. We train the model by using packet traces from flight tests in the field and validate it by comparing TCP throughput distributions for model-generated traces against those for actual traces randomly sampled from field data. Our modeling methodology is general and can be applied to any UAV flight path. 1

At the Interfaces of the Hydrologic Sciences: Connecting Water, Elements, Ecosystems, and People Through the Major Contributions of Dr. Emily Bernhardt

In this paper, we describe the major contributions of Professor Emily Bernhardt to the hydrologic sciences. Dr. Bernhardt’s work addresses how carbon, nutrient, and contaminant dynamics respond to a wide range of environmental perturbations that alter hydrologic dynamics within and connectivity among ecosystems. Her research leverages intensive and extensive field sampling, experimental manipulations, macroscale data harmonization and exploration, and continental to global-scale synthesis activities to uncover key drivers and patterns of the impacts human perturbations have on water and elemental cycles. Dr. Bernhardt’s research program is defined by her ability to ask questions and use approaches that explicitly consider connectivity and interfaces in a variety of ways. Here, we highlight significant contributions from Dr. Bernhardt’s work, organized by connectivity, interfaces, and interactions among and across (1) elemental cycles, (2) ecosystems, (3) watersheds, (4) scales, and (5) disciplines. We conclude with a section on Dr. Bernhardt’s impact on the hydrologic sciences and beyond through her exceptional dedication to mentorship, engagement, and service

AEMON-J/DSOS Archive: "Hacking Limnology" Workshop + Virtual Summit in Data Science & Open Science in Aquatic Research

This OSF project is meant to serve as a long-term storage repository for presentations and workshop materials for the Aquatic Ecosystem Modeling-Junior (AEMON-J) and Virtual Summit: Incorporating Data Science and Open Science (DSOS) communities. Contributors in this repository include past presenters and workshop organizers. Contributors are only responsible for those individual presentations that are labeled with their surname