A functional definition to distinguish ponds from lakes and wetlands

Ponds are often identified by their small size and shallow depths, but the lack of a universal evidence-based definition hampers science and weakens legal protection. Here, we compile existing pond definitions, compare ecosystem metrics (e.g., metabolism, nutrient concentrations, and gas fluxes) among ponds, wetlands, and lakes, and propose an evidence-based pond definition. Compiled definitions often mentioned surface area and depth, but were largely qualitative and variable. Government legislation rarely defined ponds, despite commonly using the term. Ponds, as defined in published studies, varied in origin and hydroperiod and were often distinct from lakes and wetlands in water chemistry. We also compared how ecosystem metrics related to three variables often seen in waterbody definitions: waterbody size, maximum depth, and emergent vegetation cover. Most ecosystem metrics (e.g., water chemistry, gas fluxes, and metabolism) exhibited nonlinear relationships with these variables, with average threshold changes at 3.7 ± 1.8 ha (median: 1.5 ha) in surface area, 5.8 ± 2.5 m (median: 5.2 m) in depth, and 13.4 ± 6.3% (median: 8.2%) emergent vegetation cover. We use this evidence and prior definitions to define ponds as waterbodies that are small (< 5 ha), shallow (< 5 m), with < 30% emergent vegetation and we highlight areas for further study near these boundaries. This definition will inform the science, policy, and management of globally abundant and ecologically significant pond ecosystems.Fil: Richardson, David C.. State University of New York at New Paltz; Estados UnidosFil: Holgerson, Meredith A.. Cornell University; Estados UnidosFil: Farragher, Matthew J.. University of Maine; Estados UnidosFil: Hoffman, Kathryn K.. No especifíca;Fil: King, Katelyn B. S.. Michigan State University; Estados UnidosFil: Alfonso, María Belén. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto Argentino de Oceanografía. Universidad Nacional del Sur. Instituto Argentino de Oceanografía; ArgentinaFil: Andersen, Mikkel R.. No especifíca;Fil: Cheruveil, Kendra Spence. Michigan State University; Estados UnidosFil: Coleman, Kristen A.. University of York; Reino UnidoFil: Farruggia, Mary Jade. University of California at Davis; Estados UnidosFil: Fernandez, Rocio Luz. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Hondula, Kelly L.. No especifíca;Fil: López Moreira Mazacotte, Gregorio A.. Leibniz - Institute of Freshwater Ecology and Inland Fisheries; AlemaniaFil: Paul, Katherine. No especifíca;Fil: Peierls, Benjamin L.. No especifíca;Fil: Rabaey, Joseph S.. University of Minnesota; Estados UnidosFil: Sadro, Steven. University of California at Davis; Estados UnidosFil: Sánchez, María Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Ecología, Genética y Evolución de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Ecología, Genética y Evolución de Buenos Aires; ArgentinaFil: Smyth, Robyn L.. No especifíca;Fil: Sweetman, Jon N.. State University of Pennsylvania; Estados Unido

High Frequency Oxygen Data from Eight Shallow Prairie Pothole Lakes, 2009-2013

This dataset includes high frequency oxygen measurements from 8 shallow lakes. Each lake has a separate data file of oxygen measurements from the study period. Also included are data files of water chemistry, macrophyte biomass, and calculated metabolism values which include all lakes.Dissolved oxygen controls important processes in lakes, from chemical reactions to organism community structure and metabolism. In shallow lakes, small volumes allow for large fluctuations in dissolved oxygen concentrations, and the oxygen regime can greatly affect ecosystem-scale processes. This data includes high frequency dissolved oxygen measurements that we used to examine differences in oxygen regimes between two alternative stable states that occur in shallow lakes. We compared annual oxygen regimes in four macrophyte-dominated, clear state lakes to four phytoplankton-dominated, turbid state lakes by quantifying oxygen concentrations, anoxia frequency, and measures of whole-lake metabolism. Oxygen regimes were not significantly different between lake states throughout the year except for during the winter under-ice period. During winter, clear lakes had less oxygen, higher frequency of anoxic periods, and higher oxygen depletion rates. Oxygen depletion rates correlated positively with peak summer macrophyte biomass. Due to lower levels of oxygen, clear shallow lakes may experience anoxia more often and for longer duration during the winter, increasing the likelihood of experiencing fish winterkill. These observations have important implications for shallow lake management, which typically focuses efforts on maintaining the clearwater state.National Science Foundation (NSF): DEB-0919095; National Science Foundation (NSF): DEB-091907

Performance aware tasking for environmentally powered sensor networks

The use of environmental energy is now emerging as a feasible energy source for embedded and wireless computing systems such as sensor networks where manual recharging or replacement of batteries is not practical. However, energy supply from environmental sources is highly variable with time. Further, for a distributed system, the energy available at its various locations will be different. These variations strongly influence the way in which environmental energy is used. We present a harvesting theory for determining performance in such systems. First we present a model for characterizing environmental sources. Second, we state and prove two harvesting theorems that help determine the sustainable performance level from a particular source. This theory leads to practical techniques for scheduling processes in energy harvesting systems. Third, we present our implementation of a real embedded system that runs on solar energy and uses our harvesting techniques. The system adjusts its performance level in response to available resources. Fourth, we propose a localized algorithm for increasing the performance of a distributed system by adapting the process scheduling to the spatio-temporal characteristics of the environmental energy in the distributed system. While our theoretical intuition is based on certain abstractions, all the scheduling methods we present are motivated solely from the experimental behavior and resource constraints of practical sensor networking systems

Better Together: Early Career Aquatic Scientists Forge New Connections at Eco‐DAS XV

A sense of kuleana (personal responsibility) in caring for the land and sea. An appreciation for laulima (many hands cooperating). An understanding of aloha 'āina (love of the land). The University of Hawai'i at Manoa hosted the 2023 Ecological Dissertations in Aquatic Sciences (Eco-DAS) program, which fostered each of these intentions by bringing together a team of early career aquatic ecologists for a week of networking and collaborative, interdisciplinary project developmen