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Potential cheatgrass abundance within lightly invaded areas of the Great Basin
ContextAnticipating where an invasive species could become abundant can help guide prevention and control efforts aimed at reducing invasion impacts. Information on potential abundance can be combined with information on the current status of an invasion to guide management towards currently uninvaded locations where the threat of invasion is high.ObjectivesWe aimed to support management by develo
Authors
Helen Sofaer, Catherine S. Jarnevich, Erin K. Buchholtz, Brian S. Cade, John T. Abatzoglou, Cameron L. Aldridge, Patrick Comer, Daniel Manier, Lauren E. Parker, Julie A. Heinrichs
Explainable machine learning improves interpretability in the predictive modeling of biological stream conditions in the Chesapeake Bay Watershed, USA
Anthropogenic alterations have resulted in widespread degradation of stream conditions. To aid in stream restoration and management, baseline estimates of conditions and improved explanation of factors driving their degradation are needed. We used random forests to model biological conditions using a benthic macroinvertebrate index of biotic integrity for small, non-tidal streams (upstream area ≤2
Authors
Kelly O. Maloney, Claire Buchanan, Rikke Jepsen, Kevin P. Krause, Matthew Joseph Cashman, Benjamin Paul Gressler, John A. Young, Matthias Schmid
Evaluating the effect of nuclear inclusion X (NIX) infections on Pacific razor clam populations
ABSTRACT: Nuclear inclusion X (NIX), the etiological agent of bacterial gill disease in Pacific razor clams Siliqua patula, was associated with host mortality events in coastal Washington State, USA, during the mid-1980s. Ongoing observations of truncated razor clam size distributions in Kalaloch Beach, Washington, raised concerns that NIX continues to impact populations. We conducted a series of
Authors
Maya Groner, Paul Hershberger, Steven C. Fradkin, Carla M. Conway, Aine C. Hawthorn, Maureen K. Purcell
Exploring metapopulation-scale suppression alternatives for a global invader in a river network experiencing climate change
Invasive species can dramatically alter ecosystems, but eradication is difficult, and suppression is expensive once they are established. Uncertainties in the potential for expansion and impacts by an invader can lead to delayed and inadequate suppression, allowing for establishment. Metapopulation viability models can aid in planning strategies to improve responses to invaders and lessen invasive
Authors
Brian D. Healy, Phaedra E. Budy, Charles Yackulic, Brendan P. Murphy, Robert C. Schelly, Mark C. McKinstry
Causality guided machine learning model on wetland CH4 emissions across global wetlands
Wetland CH4 emissions are among the most uncertain components of the global CH4 budget. The complex nature of wetland CH4 processes makes it challenging to identify causal relationships for improving our understanding and predictability of CH4 emissions. In this study, we used the flux measurements of CH4 from eddy covariance towers (30 sites from 4 wetlands types: bog, fen, marsh, and wet tundra)
Authors
Kunxiaojia Yuan, Qing Zhu, Fa Li, William J. Riley, Margaret Torn, Housen Chu, Gavin McNicol, Mingshu Chen, Sara Knox, Kyle B. Delwiche, Huayi Wu, Dennis Baldocchi, Hongxu Ma, Ankur R. Desai, Jiquan Chen, Torsten Sachs, Masahito Ueyama, Oliver Sonnentag, Manuel Helbig, Eeva-Stiina Tuittila, Gerald Jurasinski, Franziska Koebsch, David I. Campbell, Hans Peter Schmid, Annalea Lohila, Mathias Goeckede, Mats B. Nilsson, Thomas Friborg, Joachim Jansen, Donatella Zona, Eugenie S. Euskirchen, Eric Ward, Gil Bohrer, Zhenong Jin, Licheng Liu, Hiroki Iwata, Jordan P. Goodrich, Robert B. Jackson
Evaluation of machine learning approaches for predicting streamflow metrics across the conterminous United States
Few regional or national scale studies have evaluated machine learning approaches for predicting streamflow metrics at ungaged locations. Most such studies are limited by the number of dimensions of the streamflow regime investigated. This study, in contrast, provides a comprehensive evaluation of the streamflow regime based on three widely available machine learning approaches (support vector reg
Authors
Ken Eng, David M. Wolock
What did they just say? Building a Rosetta stone for geoscience and machine learning
Modern advancements in science and engineering are built upon multidisciplinary projects that bring experts together from different fields. Within their respective disciplines, researchers rely on precise terminology for specific ideas, principles, methods, and theories. Hence, the potential for miscommunication is substantial, especially when common words have been adopted by one (or both) group(
Authors
Stanley Paul Mordensky, John Lipor, Erick R. Burns, Cary Ruth Lindsey
A synthesis of coral reef research at Buck Island Reef National Monument and Salt River Bay National Historical Park and Ecological Preserve, St. Croix, U.S. Virgin Islands: 1961 to 2022
This synthesis focuses on the history of research on coral reefs within two U.S. National Park Service units in St. Croix, U.S. Virgin Islands: Buck Island Reef National Monument (from 1961 to 2022) and Salt River Bay National Historical Park and Ecological Preserve (from 1980 to 2022). Buck Island Reef National Monument (BUIS) is off the north shore of the island of St. Croix, in the U.S. Virgin
Authors
Caroline Rogers
Scaling-up deep learning predictions of hydrography from IfSAR data in Alaska
The United States National Hydrography Dataset (NHD) is a database of vector features representing the surface water features for the country. The NHD was originally compiled from hydrographic content on U.S. Geological Survey topographic maps but is being updated with higher quality feature representations through flow-routing techniques that derive hydrography from high-resolution elevation data
Authors
Larry Stanislawski, Ethan J. Shavers, Alexander Duffy, Philip T. Thiem, Nattapon Jaroenchai, Shaowen Wang, Zhe Jiang, Barry J. Kronenfeld, Barbara P. Buttenfield
Upper Rio Grande Basin water-resource status and trends: Focus area study review and synthesis
The Upper Rio Grande Basin (URGB) is a critical international water resource under pressure from a myriad of climatic, ecological, infrastructural, water-use, and legal constraints. The objective of this study is to provide a comprehensive assessment of the spatial distribution and temporal trends of selected water-budget components (snow processes, evapotranspiration (ET), streamflow processes, a
Authors
Kyle R. Douglas-Mankin, Christine Rumsey, Graham A. Sexstone, Tamara I. Ivahnenko, Natalie Houston, Shaleene Chavarria, Gabriel B. Senay, Linzy K. Foster, Jonathan V. Thomas, Allison K. Flickinger, Amy E. Galanter, C. David Moeser, Toby L. Welborn, Diana E. Pedraza, Patrick M. Lambert, Michael Scott Johnson
ECCOE Landsat Quarterly Calibration and Validation report—Quarter 1, 2022
Executive SummaryThe U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Calibration and Validation (Cal/Val) Center of Excellence (ECCOE) focuses on improving the accuracy, precision, calibration, and product quality of remote-sensing data, leveraging years of multiscale optical system geometric and radiometric calibration and characterization experience. The ECCOE Landsa
Authors
Md Obaidul Haque, Rajagopalan Rengarajan, Mark Lubke, Md Nahid Hasan, Fatima Tuz Zafrin Tuli, Jerad L. Shaw, Alex Denevan, Shannon Franks, Esad Micijevic, Michael J. Choate, Cody Anderson, Brian Markham, Kurt Thome, Ed Kaita, Julia Barsi, Raviv Levy, Lawrence Ong
A RADical approach to conservation in Alaska: Rapid climate change requires a new perspective
In Alaska, conservation areas are managed to promote the persistence of wild species, habitats, cultural resources, visitor experiences, and ecosystem services. Many conservation areas are managed by federal or state agencies, and have specific boundaries, missions, and legislative mandates. Many are also the domains of Indigenous and local people who derive livelihoods and cultural identity from
Authors
Jeremy Littell, Gregor W. Schuurman, Joel H. Reynolds, John M. Morton, Nicole Schmitt