Science Analytics and Synthesis (SAS)

Publications

Filter Total Items: 192
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Year Published: 2021

Data management and interactive visualizations for the evolving marine biodiversity observation network

Assessing the current state of and predicting change in the ocean’s biological and ecosystem resources requires observations and research to safeguard these valuable public assets. The Marine Biodiversity Observation Network (MBON) partnered with the Global Ocean Observing System Biology and Ecosystems Panel and the Ocean Biodiversity Information...

Benson, Abigail; Murray, Tylar; Canonico, Gabrielle; Montes, Enrique; Muller-Karger, Frank; Kavanaugh, Maria T.; Trinanes, Joaquin; deWitt, Lynn M.

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Year Published: 2021

Applying biodiversity metrics as surrogates to a habitat conservation plan

Unabated urbanization has led to environmental degradation and subsequent biodiversity loss across the globe. As an outcome of unmitigated land use, multi-jurisdictional agencies have developed land use plans that attempt to protect threatened or endangered species across selected areas by which some trade-offs between harm to species and...

Boykin, Kenneth G.; Kepner, William G.; McKerrow, Alexa J.

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Year Published: 2021

Leveraging existing technology: Developing a trusted digital repository for the U.S. Geological Survey

As Federal Government agencies in the United States pivot to increase access to scientific data (Sheehan, 2016), the U.S. Geological Survey (USGS) has made substantial progress (Kriesberg et al., 2017). USGS authors are required to make federally funded data publicly available in an approved data repository (USGS, 2016b). This type of public data...

Hutchison, Vivian B.; Norkin, Tamar; Langseth, Madison; Ignizio, Drew; Zolly, Lisa; McClees-Funinan, Ricardo; Liford, Amanda N.

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Year Published: 2021

Quantifying the representation of plant communities in the protected areas of the U.S.: An analysis based on the U.S. National Vegetation Classification Groups

Plant communities represent the integration of ecological and biological processes and they serve as an important component for the protection of biological diversity. To measure progress towards protection of ecosystems in the United States for various stated conservation targets we need datasets at the appropriate thematic, spatial, and temporal...

McKerrow, Alexa J.; Davidson, Anne; Rubino, Matthew; Faber-Langendoen, Don; Dockter, Daryn (Contractor)

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Year Published: 2021

Refining the coarse filter approach: Using habitat-based species models to identify rarity and vulnerabilities in the protection of U.S. biodiversity

Preserving biodiversity and its many components is a priority of conservation science and how to efficiently allocate resources to preserve healthy populations of as many species, habitats, and ecosystems as possible. We used the U.S. Geological Survey (USGS) Gap Analysis Project (GAP) species models released in 2018, which identify...

Davidson, Anne; Dunn, Leah; Gergely, Kevin; McKerrow, Alexa J.; Williams, Steven G.; Case, Mackenzie

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Year Published: 2021

Community for Data Integration 2019 annual report

The Community for Data Integration is a community of practice whose purpose is to advance the U.S. Geological Survey’s data integration capabilities. In fiscal year 2019, the Community for Data Integration held 9 monthly forums, facilitated 11 collaboration areas, held several workshops and training events, and funded 14 projects. The activities...

Hsu, Leslie; Liford, Amanda N.
Hsu, L., and Liford, A.N., 2021, Community for Data Integration 2019 Annual Report: U.S. Geological Survey Open-File Report 2021–1016, 19 p., https://doi.org/10.3133/ofr20211016.

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Year Published: 2021

U.S. Geological Survey wildland fire science strategic plan, 2021–26

The U.S. Geological Survey (USGS) Wildland Fire Science Strategic Plan defines critical, core fire science capabilities for understanding fire-related and fire-responsive earth system processes and patterns, and informing management decision making. Developed by USGS fire scientists and executive leadership, and informed by conversations with...

Steblein, Paul F.; Loehman, Rachel A.; Miller, Mark P.; Holomuzki, Joseph R.; Soileau, Suzanna C.; Brooks, Matthew L.; Drane-Maury, Mia; Hamilton, Hannah M.; Kean, Jason W.; Keeley, Jon E.; Mason, Robert R.; McKerrow, Alexa J.; Meldrum, James R.; Molder, Edmund B.; Murphy, Sheila F.; Peterson, Birgit; Plumlee, Geoffrey S.; Shinneman, Douglas J.; van Mantgem, Phillip J.; York, Alison
Steblein, P.F., Loehman, R.A., Miller, M.P., Holomuzki, J.R., Soileau, S.C., Brooks, M.L., Drane-Maury, M., Hamilton, H.M., Kean, J.W., Keeley, J.E., Mason, R.R., Jr., McKerrow, A., Meldrum, J.R., Molder, E.B., Murphy, S.F., Peterson, B., Plumlee, G.S., Shinneman, D.J., van Mantgem, P.J., and York, A., 2021, U.S. Geological Survey wildland fire science strategic plan, 2021–26: U.S. Geological Survey Circular 1471, 30 p., https://doi.org/10.3133/cir1471.

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Year Published: 2021

U.S. Geological Survey Community for Data Integration 2019 Workshop Proceedings—From big data to smart data

The U.S. Geological Survey (USGS) Community for Data Integration (CDI) Workshop was held during June 3–7, 2019, at Center Green in Boulder, Colo. The theme of the workshop was “From Big Data to Smart Data” with the purpose of bringing together the community to discuss current topics, shared challenges, and steps forward to advance twenty-first...

Hsu, Leslie
Hsu, L., 2021, U.S. Geological Survey Community for Data Integration 2019 Workshop Proceedings—From big data to smart data: U.S. Geological Survey Open-File Report 2020–1132, 48 p., https://doi.org/10.3133/ofr20201132.

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Year Published: 2020

New operational national satellite burned area product

Introduction Lack of consistent spatial and temporal fire information with relevant spatial resolution hinders land management and broad-scale assessments of fire activity, especially in the eastern United States and the Great Plains where fi re is important ecologically and culturally. Remote sensing can be used to monitor fi re activity, augment...

Hawbaker, Todd J.; Vanderhoof, Melanie K.; Schmidt, Gail L.; Beal, Yen-Ju G.; Picotte, Joshua J.; Takacs, Joshua; Falgout, Jeff T.; Dwyer, John L.

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Year Published: 2020

USGS enterprise tools for efficient and effective management of science data

The Science Data Management Branch (SDM) of the U.S. Geological Survey (USGS) provides data management expertise and leadership and develops guidance and tools to support the USGS in providing the nation with reliable scientific information on the basis of which to describe the Earth. The SDM suite of tools supports the USGS Data Management...

Hutchison, Vivian B.; Liford, Amanda; McClees-Funinan, Ricardo; Zolly, Lisa; Ignizio, Drew; Langseth, Madison; Serna, Brandon; Sellers, Elizabeth; Hsu, Leslie; Norkin, Tamar; McNiff, Marcia; Donovan, Grace
Hutchison, V.B., Liford, A.N., McClees-Funinan, Ricardo, Zolly, Lisa, Ignizio, D.A., Langseth, M.L., Serna, B.S., Sellers, E.A., Hsu, Leslie, Norkin, Tamar, McNiff, Marcia, Donovan, G.C., 2020, USGS enterprise tools for efficient and effective management of science data: U.S. Geological Survey Fact Sheet 2020–3041, 2 p., https://doi.org/10.3133/fs20203041.

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Year Published: 2020

Ecological forecasting—21st century science for 21st century management

Natural resource managers are coping with rapid changes in both environmental conditions and ecosystems. Enabled by recent advances in data collection and assimilation, short-term ecological forecasting may be a powerful tool to help resource managers anticipate impending near-term changes in ecosystem conditions or dynamics. Managers may use the...

Bradford, John B.; Weltzin, Jake; Mccormick, Molly; Baron, Jill; Bowen, Zack; Bristol, Sky; Carlisle, Daren; Crimmins, Theresa; Cross, Paul; DeVivo, Joe; Dietze, Mike; Freeman, Mary; Goldberg, Jason; Hooten, Mevin; Hsu, Leslie; Jenni, Karen; Keisman, Jennifer L.; Kennen, Jonathan; Lee, Kathy; Lesmes, David; Loftin, Keith; Miller, Brian W.; Murdoch, Peter S.; Newman, Jana; Prentice, Karen L.; Rangwala, Imtiaz; Read, Jordan; Sieracki, Jennifer; Sofaer, Helen; Thur, Steve; Toevs, Gordon; Werner, Francisco; White, C. LeAnn; White, Timothy; Wiltermuth, Mark
Bradford, J.B., Weltzin, J.F., McCormick, M., Baron, J., Bowen, Z., Bristol, S., Carlisle, D., Crimmins, T., Cross, P., DeVivo, J., Dietze, M., Freeman, M., Goldberg, J., Hooten, M., Hsu, L., Jenni, K., Keisman, J., Kennen, J., Lee, K., Lesmes, D., Loftin, K., Miller, B.W., Murdoch, P., Newman, J., Prentice, K.L., Rangwala, I., Read, J., Sieracki, J., Sofaer, H., Thur, S., Toevs, G., Werner, F., White, C.L., White, T., and Wiltermuth, M., 2020, Ecological forecasting—21st century science for 21st century management: U.S. Geological Survey Open-File Report 2020–1073, 54 p., https://doi.org/10.3133/ofr20201073.