Science Analytics and Synthesis (SAS)

Home

Science Analytics and Synthesis (SAS) emphasizes a science data lifecycle approach to Earth systems data and information. We strive to accelerate research and decision making through data science, information delivery, advanced computing, and biodiversity analytics.

View All Programs and Activities

Gap Analysis Project Species Viewer

Gap Analysis Project Species Viewer

The Gap Analysis Project Species Viewer is focused on providing access to species range maps and predicted habitat distribution models for species within the continental U.S. through an interactive map, allowing the user to explore the data.

Viewer

Hawaii Waterfalls Linked to the National Hydrography Datasets

Hawaii Waterfalls Linked to the National Hydrography Datasets

Waterfall locations and estimated waterfall heights on five of the main Hawaiian Islands linked the NHD. Knowing waterfall locations and characteristics can aide in understanding species distributions and migration patterns across stream networks.

Get Data

Comprehensive List of Non-Native Species in AK-HI-L48, V2.0

Comprehensive List of Non-Native Species in AK-HI-L48, V2.0

A compilation and analysis of authoritative assertions of the nonindigenous status of taxa in Alaska, Hawaii, and the conterminous United States of America.

Get Data

News

Date published: August 21, 2020

Call for proposals: LTER Office Network (LNO) Award Registration Information for Synthesis Working Groups

NSF's Long Term Ecological Reaserach Network (LTER) is releasing a call for proposals for synthesis working groups.

Date published: February 13, 2020

Understanding and Predicting Wetland Methane Emissions

When: February 27, 2020 at 4 pm MT
Where: B218 E‐Conference Room, CSU Natural & Environmental Science Building (NESB)
Online: https://zoom.us/j/732190660
Who: Dr. Rob Jackson, Stanford University & members of the...

Publications

Publication Thumbnail
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.

Publication Thumbnail
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 F.; 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; Kennen, Jonathan; Lee, Kathy; Lesmes, David; Loftin, Keith; Miller, Brian W.; Murdoch, Peter; 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.

Publication Thumbnail
Year Published: 2020

Community for data integration 2018 funded project report

The U.S. Geological Survey Community for Data Integration annually funds small projects focusing on data integration for interdisciplinary research, innovative data management, and demonstration of new technologies. This report provides a summary of the 10 projects funded in fiscal year 2018, outlining their goals, activities, and accomplishments.

Hsu, Leslie; Andrews, Caitlin M.; Bradford, John B.; Buscombe, Daniel D.; Chase, Katherine J.; Daniel, Wesley M.; Jones, Jeanne M.; Fuller, Pam; Mirus, Benjamin B.; Neilson, Matthew E.; Vraga, Hans W.; Walker, Jessica J.; Walworth, Dennis H.; Warrick, Jonathan; Weltzin, Jake F.; Wieferich, Daniel J.; Wood, Nathan J.
Hsu, L., Andrews, C.M., Bradford, J.B., Buscombe, D.D., Chase, K.J., Daniel, W.M., Jones, J.M., Fuller, P., Mirus, B.B., Neilson, M.E., Vraga, H.W., Walker, J.J., Walworth, D.H., Warrick, J., Weltzin, J., Wieferich, D.J., and Wood, N.J., 2020, Community for Data Integration 2018 funded project report: U.S. Geological Survey Open-File Report 1062, 9 p., https://doi.org/10.3133/ofr20201062.