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Soil cover heterogeneity associated with biocrusts predicts patch-level plant diversity patterns Soil cover heterogeneity associated with biocrusts predicts patch-level plant diversity patterns

Context Soil resource heterogeneity drives plant species diversity patterns at local and landscape scales. In drylands, biocrusts are patchily distributed and contribute to soil resource heterogeneity important for plant establishment and growth. Yet, we have a limited understanding of how such heterogeneity may relate to patterns of plant diversity and community structure. Objectives We...
Authors
Caroline A. Havrilla, Miguel L. Villarreal

Machine learning and new-generation spaceborne hyperspectral data advance crop type mapping Machine learning and new-generation spaceborne hyperspectral data advance crop type mapping

Hyperspectral sensors provide near-continuous spectral data that can facilitate advancements in agricultural crop classification and characterization, which are important for addressing global food and water security issues. We investigated two new-generation hyperspectral sensors, Germany’s Deutsches Zentrum für Luft‐ und Raumfahrt Earth Sensing Imaging Spectrometer (DESIS) and Italy’s...
Authors
Itiya P. Aneece, Prasad Thenkabail, Richard L. McCormick, Alifu Haireti, Daniel Foley, Adam Oliphant, Pardhasaradhi Teluguntla

Long-term communication of aftershock forecasts: The Canterbury earthquake sequence in New Zealand Long-term communication of aftershock forecasts: The Canterbury earthquake sequence in New Zealand

On 14 February 2016, a magnitude (M)5.7 earthquake struck in Christchurch New Zealand (Aotearoa in the Maori language). The shaking caused damage to historic facades, power outages, cliff collapses, rock falls, and liquefaction but no reported injuries or fatalities. This Valentine’s Day earthquake was an aftershock in the Canterbury earthquake sequence (CES), which began on 4 September...
Authors
Anne Wein, Sara K. McBride, Julia S. Becker, Annemarie Christophersen, Emma Hudson Doyle, Matthew Gerstenberger, Sally H. Potter

The feasibility of using national-scale datasets for classifying wetlands in Arizona with machine learning The feasibility of using national-scale datasets for classifying wetlands in Arizona with machine learning

The advent of machine learning techniques has led to a proliferation of landscape classification products. These approaches can fill gaps in wetland inventories across the United States (U.S.) provided that large reference datasets are available to develop accurate models. In this study, we tested the feasibility of expediting the classification process by sourcing requisite training and...
Authors
Christopher E. Soulard, Jessica J. Walker, Britt Windsor Smith, Jason R. Kreitler

Birdwatching preferences reveal synergies and tradeoffs among recreation, carbon, and fisheries ecosystem services in Pacific Northwest estuaries, USA Birdwatching preferences reveal synergies and tradeoffs among recreation, carbon, and fisheries ecosystem services in Pacific Northwest estuaries, USA

Coastal ecosystems provide multiple ecosystem services that are valued in diverse ways. The Nisqually River Delta (the Delta), an estuary in Puget Sound, Washington, U.S.A., is co-managed by the Nisqually Indian Tribe and the Billy Frank Jr. Nisqually National Wildlife Refuge. In an ecosystem services assessment, we used different service-appropriate methods including citizen science...
Authors
Kristin B. Byrd, Isa Woo, Laurie Anne Hall, Emily Pindilli, Monica Moritsch, Anthony Good, Susan E.W. De La Cruz, Melanie J. Davis, Glynnis Nakai

U.S. Geological Survey climate science plan—Future research directions U.S. Geological Survey climate science plan—Future research directions

Executive Summary Climate is the primary driver of environmental change and is a key consideration in defining science priorities conducted across all mission areas in the U.S. Geological Survey (USGS). Recognizing the importance of climate change to its future research agenda, the USGS’s Climate Science Steering Committee requested the development of a Climate Science Plan to identify...
Authors
Tamara Wilson, Ryan P. Boyles, Nicole DeCrappeo, Judith Z. Drexler, Kevin D. Kroeger, Rachel A. Loehman, John M. Pearce, Mark P. Waldrop, Peter D. Warwick, Anne M. Wein, Sara L. Zeigler, Beard

Will there be water? Climate change, housing needs, and future water demand in California Will there be water? Climate change, housing needs, and future water demand in California

Climate change in California is expected to alter future water availability, impacting water supplies needed to support future housing growth and agriculture demand. In groundwater-dependent regions like California's Central Coast, new land-use related water demand and decreasing recharge is already stressing depleted groundwater basins. We developed a spatially explicit state-and...
Authors
Tamara Wilson, Paul C. Selmants, Ryan M Boynton, James H. Thorne, Nathan D. Van Schmidt, Timothy Thomas

Hyperspectral imaging predicts differences in carbon and nitrogen status among representative biocrust functional groups of the Colorado Plateau Hyperspectral imaging predicts differences in carbon and nitrogen status among representative biocrust functional groups of the Colorado Plateau

Biological soil crusts (biocrusts) are widespread soil photosynthetic communities covering about 12% of Earth's land surface and play crucial roles in terrestrial carbon (C) and nitrogen (N) cycles, yet scalable quantifications of biocrusts and their biogeochemical contributions are notably lacking. While remote sensing has enormous potential to assess, scale, and contextualize biocrusts...
Authors
Dong Yan, Sasha C. Reed, William A. Rutherford, Mostafa Javadian, Robin H. Reibold, Miguel L. Villarreal, Benjamin Poulter, Shujun Song, William K. Smith

Crop type classification, trends, and patterns of central California agricultural fields from 2005 to 2020 Crop type classification, trends, and patterns of central California agricultural fields from 2005 to 2020

California produces many key agricultural products in the United States. Current geospatial agricultural datasets are limited in mapping accuracy, spatial context, or observation period. This study uses machine learning and high-resolution imagery to produce a time series of crop maps to assess crop type trends and patterns across central California from 2005 to 2020. National...
Authors
Britt Windsor Smith, Christopher E. Soulard, Jessica J. Walker

Oil and gas development influences potential for dust emission from the Upper Colorado River Basin, USA Oil and gas development influences potential for dust emission from the Upper Colorado River Basin, USA

Wind erosion and dust emission from drylands have large consequences for ecosystem function and human health. Wind erosion is naturally reduced by soil crusting and sheltering by non-erodible roughness elements such as plants. Land uses that reduce surface roughness and disturb the soil surface can dramatically increase dust emission. Extraction of oil and gas is a common and growing...
Authors
Gayle Loren Tyree, A. Chappell, Miguel L. Villarreal, S. Dhital, Michael C. Duniway, B.L. Edwards, A.M. Faist, T.W. Nauman, N.P. Webb

An ensemble mean method for remote sensing of actual evapotranspiration to estimate water budget response across a restoration landscape An ensemble mean method for remote sensing of actual evapotranspiration to estimate water budget response across a restoration landscape

Estimates of actual evapotranspiration (ETa) are valuable for effective monitoring and management of water resources. In areas that lack ground-based monitoring networks, remote sensing allows for accurate and consistent estimates of ETa across a broad scale—though each algorithm has limitations (i.e., ground-based validation, temporal consistency, spatial resolution). We developed an...
Authors
Roy E. Petrakis, Laura M. Norman, Miguel L. Villarreal, Gabriel B. Senay, MacKenzie Friedrichs, Florance Cassassuce, Florent Gomis, Pamela L. Nagler

Automated Cropland Fallow Algorithm (ACFA) for the Northern Great Plains of USA Automated Cropland Fallow Algorithm (ACFA) for the Northern Great Plains of USA

Cropland fallowing is choosing not to plant a crop during a season when a crop is normally planted. It is an important component of many crop rotations and can improve soil moisture and health. Knowing which fields are fallow is critical to assess crop productivity and crop water productivity, needed for food security assessments. The annual spatial extent of cropland fallows is poorly...
Authors
Adam Oliphant, Prasad Thenkabail, Pardhasaradhi Teluguntla, Itiya Aneece, Daniel Foley, Richard L. McCormick
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