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Within the Gulf of Alaska, in the North Pacific Ocean, three major events - both natural and human-caused – resulted in large-scale ecosystem changes during the last 50 years.
At the nexus of the ocean and the land lies the nearshore ecosystem, which includes the intertidal zone, an area exposed during low tides and submerged during high tides. Species in the intertidal are adapted to a high level of environmental variability including high temperatures, waves, and salinity variability. Species’ tolerance to desiccation in part determines the elevation within the intertidal zone they occupy. Biological interactions also determine the presence and abundance of species. Predators like sea stars and competition for space can influence numbers of barnacles and mussels. As ocean and air temperatures continue to rise with climate change and marine heatwave are becoming more common intertidal species may have limited space to move vertically in response to sea level rise and many species are already living at the edge of their physiological tolerances for high temperatures.
Between 2014 and 2016, an extreme marine heatwave struck the North Pacific Ocean, affecting nearshore and pelagic (offshore, open ocean) ecosystems from southern California to Alaska. This unprecedented event, characterized by unusually warm ocean temperatures over a large area, was the longest-duration marine heatwave recorded to date. The Gulf of Alaska endured some of the most severe consequences of this heatwave, now known as the Pacific Marine Heatwave or “the Blob” (Fig. 1). Marine heatwaves, like the Blob, are increasing in frequency and intensity over time, and they can cause large-scale disruptions to marine ecosystems. The increased occurrence of these events across the world's oceans in recent decades necessitates an understanding of their impact on biological communities.
The U.S. Geological Survey (USGS) is a steward for over 130 years of rich, diverse natural science and information resources. We document one-of-a-kind observations of natural phenomena and cultural impacts on our changing world. In order for society to deal with national and global trends, the USGS must enable access and use of legacy, inaccessible information by including these data in our digital archives and databases. The USGS has conducted scientific assessments on the quality and quantity of the Nation's water resources, provided access to geospatial and natural resource data, and conducted multi-purpose natural science studies. All of these have generated records that need to be accessible and integrated in order to be examined for new information and interpretations that were never intended by the original collector. The Federal Records Act of 1950 mandates that the USGS preserve Federal records containing evidence of the agency's organization, functions, policies, decisions, procedures, and essential transactions. At the USGS, the goal of Open Government is to improve and increase access to scientific information. Therefore, it is incumbent upon the USGS to preserve, make available, and provide accountability for the data that it creates from our scientific projects.
Physics-based simulations are critical for understanding natural hazards. The increasing complexity of numerical codes requires benchmark exercises to verify that different computational methods yield consistent results when solving the same governing equations. Here, we present an open-access web platform designed for the verification of earthquake dynamic rupture, seismic cycle, and tsunami simulations. The platform architecture utilizes a modular, serverless backend on Amazon Web Services (AWS) to provide scalable file processing and visualization. A lightweight static web application provides a secure interface for uploading and managing results, while the browser-based data visualization enables interactive analysis of time series and surface grid data. By using structured JavaScript Object Notation (JSON) text files to define benchmark structures, the system remains fully extensible, allowing the addition of new scenarios without modifying the underlying software logic. The platform hosts the "The Tsunami Problem Versions" (TTPV) 1 & 2, two benchmarks for 3D fully coupled earthquake dynamic rupture and tsunami generation, and provides a framework for earthquake cycle models. This community resource aims to build trust in numerical simulations and facilitate long-term collaborative code verification as modeling software continues to evolve.
Introduction A number of different government-funded seismic data centers offer free open-access data (e.g., U.S. Geological Survey, National Earthquake Information Center, the Incorporated Research Institutions for Seismology (IRIS), and Data Management System), which can be freely downloaded and shared among different members of the community ( Lay, 2009 ). To efficiently share data, it is important that different data providers follow a common format. The Standard for the Exchange of Earthquake Data (SEED) provides one such format for storing seismic and other geophysical data. The SEED format is widely used in earthquake seismology; however, SEED and its structure can be difficult for many first-time users (ourselves included). Below is a quick tutorial that outlines the basic structure of SEED format. This write-up is in no way intended to replace the comprehensive SEED manual ( Ahern et al. , 2009 ), and instead of going into the details of any specific part of the SEED format we refer the reader to the manual for additional details. The goal of this write-up is to succinctly explain the basic structure of SEED format as well as the associated jargon, as most commonly used now, in a colloquial way so that novice users of SEED can become more familiar with the format and its application quickly. Our goal is to give the reader the necessary background so that when problems or questions about SEED format arise they will have some understanding of where they should look for more details or from where the problem might be stemming. As a secondary goal, we hope to help the reader become familiar with the SEED manual ( Ahern et al. , 2009 ), which contains detailed information about all aspects of the SEED format.
In a world where invasive alien species (IAS) are recognised as one of the major threats to biodiversity, leading scientists from five continents have come together to propose the concept of developing an international association for open knowledge and open data on IAS—termed “INVASIVESNET”. This new association will facilitate greater understanding and improved management of invasive alien species (IAS) and biological invasions globally, by developing a sustainable network of networks for effective knowledge exchange. In addition to their inclusion in the CBD Strategic Plan for Biodiversity, the increasing ecological, social, cultural and economic impacts associated with IAS have driven the development of multiple legal instruments and policies. This increases the need for greater co-ordination, co-operation, and information exchange among scientists, management, the community of practice and the public. INVASIVESNET will be formed by linking new and existing networks of interested stakeholders including international and national expert working groups and initiatives, individual scientists, database managers, thematic open access journals, environmental agencies, practitioners, managers, industry, non-government organisations, citizens and educational bodies. The association will develop technical tools and cyberinfrastructure for the collection, management and dissemination of data and information on IAS; create an effective communication platform for global stakeholders; and promote coordination and collaboration through international meetings, workshops, education, training and outreach. To date, the sustainability of many strategic national and international initiatives on IAS have unfortunately been hampered by time-limited grants or funding cycles. Recognising that IAS initiatives need to be globally coordinated and ongoing, we aim to develop a sustainable knowledge sharing association to connect the outputs of IAS research and to inform the consequential management and societal challenges arising from IAS introductions. INVASIVESNET will provide a dynamic and enduring network of networks to ensure the continuity of connections among the IAS community of practice, science and management.
Management of water resources in the transboundary Rio Grande/Río Bravo Basin (the Basin) presents challenges for state and Federal entities in the United States and Mexico making management decisions on shared water resources. Damming, channelization, water availability, and allocation are governed by water rights and water-sharing agreements. Data and information sharing are important aspects of transboundary cooperation, but differences in format, content, spatial and temporal resolution, and language hinder collaboration. In addition, data on the kinds and geographic distribution of water governance and management institutions across the Basin have not been consistently documented. Existing data disparities parallel the hydrological and social fragmentation of the Basin. Seeking to underscore the interdependence between social and environmental processes in the Basin, anthropologists and modelers collaborated to develop a socio-environmental geodatabase. This geodatabase is a first step in modeling the social components of decision making and their connectivity to environmental processes across the Basin. The geodatabase is available in an open-access domain and contains geospatial data related to water and land governance, hydrology, water use and hydraulic infrastructure, socioeconomics, and the biophysical environment necessary to advance the understanding of basin dynamics. Having these data documented and compiled in a central location serves as a resource to help decision makers better understand upstream and downstream social-environmental characteristics. This knowledge is useful for developing sustainable water management policies in a region where water resources are increasingly under pressure from climatic, environmental, and human-related changes.
On-line geoscience bibliographic citations and access points to citations are exponentially increasing as commercial, non-profit, and government agencies worldwide publish materials electronically. On-line bibliographic tools capture cited works, and open access content allows for freely obtained citations and documents. For this newsletter, citations from the numerous journals and books listed in the "Recent Papers" section of the EXPLORE newsletters from 2008-2011 were used to provide freely-accessible web sites to determine the availability of bibliographic information.
This paper presents research on the semantics of topographic data for triples and ontologies to blend the capabilities of the Semantic Web and The National Map of the U.S. Geological Survey. Automated conversion of relational topographic data of several geographic sample areas to the triple data model standard resulted in relatively poor semantic associations. Further research employed vocabularies of feature type and spatial relation terms. A user interface was designed to model the capture of non-standard terms relevant to public users and to map those terms to existing data models of The National Map through the use of ontology. Server access for the study area triple stores was made publicly available, illustrating how the development of linked data may transform institutional policies to open government data resources to the public. This paper presents these data conversion and research techniques that were tested as open linked data concepts leveraged through a user-centered interface and open USGS server access to the public.
The production and accessibility of geospatial information including Earth observation is changing greatly both technically and in terms of human participation. Advances in technology have changed the way that geospatial data are produced and accessed, resulting in more efficient processes and greater accessibility than ever before. Improved technology has also created opportunities for increased participation in the gathering and interpretation of data through crowdsourcing and citizen science efforts. Increased accessibility has resulted in greater participation in the use of data as prices for Government-produced data have fallen and barriers to access have been reduced. The increase in participation in the production and in the use of data, defined as data democracy for this workshop, are having great impacts on economics and more generally on society. There is also a strong drive by governments around the world, as shown by the G8 Declaration in June 2013, to make public sector information and scientific data more widely accessible. These are respectively termed “open data” and “open research data.” This report summarizes discussion at the Workshop on Assessing the Impact and Value of Open Geospatial Information held at George Washington University in Washington, D.C. in October 2014. Workshop participants examined the consequences of expanding data democracy with a focus on its socioeconomic impacts. Evaluations were presented of state-of-the-art methods to assess these socioeconomic impacts, which included position papers and remarks by discussants. The workshop included discussions about the following topics: (1) increased and expanded information sources; (2) societal impacts, including approaches to economics assessments; (3) constraints to open access, including the demands for return on investment, specifications of intellectual property rights, and privacy issues; and (4) learning from the experiences of other data-rich domains, such as environmental management, internet businesses, health, and transportation. The workshop was a working meeting with strong participant engagement, leading to recommendations for action. The meeting included five topic-driven sessions and keynote presentations. Precirculated position papers for each panel session facilitated preparation and remarks by discussants. After the position papers are updated following the discussants’ remarks, it is planned to submit them for publication. The workshop included 68 participants coming from international organizations, the U.S. public and private sectors, nongovernmental organizations, and academia. Participants included policy makers and analysts, financial analysts, economists, information scientists, geospatial practitioners, and other discipline experts.
The Landsat program has been collecting and archiving moderate resolution earth imagery since 1972. The number of Landsat users and uses has increased exponentially since the enactment of a free and open data policy in 2008, which made data available free of charge to all users. Benefits from the information Landsat data provides vary from improving environmental quality to protecting public health and safety and informing decision makers such as consumers and producers, government officials and the public at large. Although some studies have been conducted, little is known about the total benefit provided by open access Landsat imagery. This report contains a set of case studies focused on the uses and benefits of Landsat imagery. The purpose of these is to shed more light on the benefits accrued from Landsat imagery and to gain a better understanding of the program’s value. The case studies tell a story of how Landsat imagery is used and what its value is to different private and public entities. Most of the case studies focus on the use of Landsat in water resource management, although some other content areas are included.
The U.S. Geological Survey (USGS) is the primary U.S. Government agency for water data collection and dissemination. In this role, the USGS has recently created and deployed a National Water Census Data Portal (NWC-DP) which provides access to streamflow, evapotransporation, precipitation, aquatic biology and other data at the national level. Recognizing the value of these data sets for hydrologic science education, this paper presents an effort to bridge the gap between pencil–and-paper-based hydrology curriculum and the USGS NWC-DP resource. Specifically, we have developed an R package, National Water Census Education (NWCEd), and five associated laboratory exercises that integrate R- and web-services-based access to the NWC-DP data sets. Using custom functions built into the NWCEd, students are able to access unprecedented amounts of hydrologic data from the NWC-DP, which can be applied to current hydrology curriculum and analyzed using NWCEd and a number of other open-source R tools.
The Outer Continental Shelf Lands Act of 1953, as amended in 1978 (43 U.S.C. 1331 et seq.), grants to the Secretary of the Interior the authority to issue leases for minerals on the U.S. Outer Continental Shelf (OCS). It provides the authority and guidelines which the Secretary utilizes fo7 expeditious exploration and development of the OCS while ensuring timely access to information by affected states and local governments in order that appropriate planning will anticipate and ameliorate impacts from such OCS activities.
Magnetotellurics (MT) is a passive electromagnetic geophysical method that measures variations in subsurface electrical resistivity. MT data are collected in the time domain and processed in the frequency domain to produce estimates of a transfer function representing the Earth’s electrical structure. Unfortunately, the MT community lacks metadata and data standards for time series data. As the community grows and findability, accessibility, interoperability, and reuse of digital assets (FAIR) data principles are enforced by government and funding agencies, a standard is needed for time series data. Presented here is a hierarchical data format (MTH5) that is logically formatted to how MT data are collected. Open-source Python packages are also described to read, write, and manipulate MTH5 files. These include a package to deal with metadata ( mt_metadata ) based on standards developed by the Working Group for Magnetotelluric Data Handling and Software assembled by the Incorporated Research Institutions for Seismology (IRIS), and mth5 : a package to interact with MTH5 files that uses mt_metadata . Example code and workflows are presented.
The increasing use of spatially explicit analyses of high-resolution spatially distributed data (imagery and point clouds) for the purposes of characterising spatial heterogeneity in geophysical phenomena necessitates the development of custom analytical and computational tools. In recent years, such analyses have become the basis of, for example, automated texture characterisation and segmentation, roughness and grain size calculation, and feature detection and classification, from a variety of data types. In this work, much use has been made of statistical descriptors of localised spatial variations in amplitude variance (roughness), however the horizontal scale (wavelength) and spacing of roughness elements is rarely considered. This is despite the fact that the ratio of characteristic vertical to horizontal scales is not constant and can yield important information about physical scaling relationships. Spectral analysis is a hitherto under-utilised but powerful means to acquire statistical information about relevant amplitude and wavelength scales, simultaneously and with computational efficiency. Further, quantifying spatially distributed data in the frequency domain lends itself to the development of stochastic models for probing the underlying mechanisms which govern the spatial distribution of geological and geophysical phenomena. The software package PySESA (Python program for Spatially Explicit Spectral Analysis) has been developed for generic analyses of spatially distributed data in both the spatial and frequency domains. Developed predominantly in Python , it accesses libraries written in Cython and C++ for efficiency. It is open source and modular, therefore readily incorporated into, and combined with, other data analysis tools and frameworks with particular utility for supporting research in the fields of geomorphology, geophysics, hydrography, photogrammetry and remote sensing. The analytical and computational structure of the toolbox is described, and its functionality illustrated with an example of a high-resolution bathymetric point cloud data collected with multibeam echosounder.
The U.S. Geological Survey (USGS) has long recognized the strategic importance and value of well-managed data assets as an integral component of scientific integrity and foundational to the advancement of scientific research, decision making, and public safety. The USGS investment in the science lifecycle, including collection of unbiased data assets, interpretation, peer review, interpretive publications, and data release, ultimately contributes to the transparency and availability of science. Foundational Government directives and laws, such as the Foundations for Evidence-Based Policymaking Act of 2018 (Public Law 115–435, 132 Stat. 5529) as well as Executive Order 13642, “Making Open and Machine Readable the New Default for Government Information,” provide a framework for addressing strategic data management. The USGS Data Strategy builds on that framework by outlining high-level goals and objectives that serve as a long-term, decadal guide toward achieving a broad, data-focused vision. Benefits of the USGS Data Strategy are many. The USGS will contribute to open science by increasing efficiencies in the consistent management of valuable data assets; driving innovation that results in modernized capabilities to ensure data are analysis ready; increasing data skills across the Bureau to enhance workforce data literacy; broadening capacity to understand and address needs of stakeholders; and measuring progress in producing findable, accessible, interoperable, and reusable (FAIR) data products. The major goals and objectives of the USGS Data Strategy promote maximizing the utility of USGS data based on stakeholder needs, promoting data innovation, coordinating common data practices, modernizing our USGS enterprise data architecture, and enhancing our data-centric culture. The goals and objectives in the strategy align with other Bureau strategic plans, guidance, and directives from the Department of the Interior and the Federal Government. This strategy is a key component to strengthen the Bureau’s data ecosystem to ensure a relevant, long-term capacity that supports internal needs and achieves its scientific mission in the most efficient and effective manner.
The National Uranium Resource Evaluation (NURE) program was conducted by the U.S. Government between 1974 and 1983. The NURE program was administered by the Grand Junction, CO, office of the Department of Energy. The program included airborne gamma-ray spectrometry and magnetic data collection as well as extensive geochemical sample collection and processing. Aeroradiometric and aeromagnetic surveys of 98 1° by 3° quadrangles were flown in Alaska between 1975 and 1980. The data were flown in 15 surveys by Texas Instruments (T.I.), Lockwood, Kessler, and Bartlett (LKB), and AeroServices (Aero) under contract to the U.S. Government. A series of contractor reports document the surveys on a quadrangle by quadrangle basis. We list references to these reports on the detailed survey index pages accessible through the Survey Irfo page.