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At least 469 records · Page 26Linked to original sources

The soil physics contributions of Edgar Buckingham

During 1902 to 1906 as a soil physicist at the USDA Bureau of Soils (BOS), Edgar Buckingham originated the concepts of matric potential, soil–water retention curves, specific water capacity, and unsaturated hydraulic conductivity ( K ) as a distinct property of a soil. He applied a formula equivalent to Darcy's law (though without specific mention of Darcy's work) to unsaturated flow. He also contributed significant research on quasi-empirical formulas for K as a function of water content, water flow in capillary crevices and in thin films, and scaling. Buckingham's work on gas flow in soils produced paradigms that are consistent with our current understanding. His work on evaporation elucidated the concept of self-mulching and produced sound and sometimes paradoxical generalizations concerning conditions that favor or retard evaporation. Largely overshadowing those achievements, however, is that he launched a theory, still accepted today, that could predict transient water content as a function of time and space. Recently discovered documents reveal some of the arguments Buckingham had with BOS officials, including the text of a two-paragraph conclusion of his famous 1907 report on soil water, and the official letter documenting rejection of that text. Strained interpersonal relations motivated the departure of Buckingham and other brilliant physicists (N.E. Dorsey, F.H. King, and Lyman Briggs) from the BOS during 1903 to 1906. Given that Buckingham and his BOS colleagues had been rapidly developing the means of quantifying unsaturated flow, these strained relations probably slowed the advancement of unsaturated flow theory.

Soil Science Society of America Journal↗

The 1964 Great Alaska Earthquake and tsunamis: A modern perspective and enduring legacies

The magnitude 9.2 Great Alaska Earthquake that struck south-central Alaska at 5:36 p.m. on Friday, March 27, 1964, is the largest recorded earthquake in U.S. history and the second-largest earthquake recorded with modern instruments. The earthquake was felt throughout most of mainland Alaska, as far west as Dutch Harbor in the Aleutian Islands some 480 miles away, and at Seattle, Washington, more than 1,200 miles to the southeast of the fault rupture, where the Space Needle swayed perceptibly. The earthquake caused rivers, lakes, and other waterways to slosh as far away as the coasts of Texas and Louisiana. Water-level recorders in 47 states—the entire Nation except for Connecticut, Delaware, and Rhode Island— registered the earthquake. It was so large that it caused the entire Earth to ring like a bell: vibrations that were among the first of their kind ever recorded by modern instruments. The Great Alaska Earthquake spawned thousands of lesser aftershocks and hundreds of damaging landslides, submarine slumps, and other ground failures. Alaska’s largest city, Anchorage, located west of the fault rupture, sustained heavy property damage. Tsunamis produced by the earthquake resulted in deaths and damage as far away as Oregon and California. Altogether the earthquake and subsequent tsunamis caused 129 fatalities and an estimated $2.3 billion in property losses (in 2013 dollars). Most of the population of Alaska and its major transportation routes, ports, and infrastructure lie near the eastern segment of the Aleutian Trench that ruptured in the 1964 earthquake. Although the Great Alaska Earthquake was tragic because of the loss of life and property, it provided a wealth of data about subductionzone earthquakes and the hazards they pose. The leap in scientific understanding that followed the 1964 earthquake has led to major breakthroughs in earth science research worldwide over the past half century. This fact sheet commemorates Great Alaska Earthquake and examines the advances in knowledge and technology that have helped to improve earthquake preparation and response both in Alaska and around the world.

Alaska↗

Community for Data Integration 2017 annual report

The Community for Data Integration (CDI) is a group that helps members grow their expertise on all aspects of working with scientific data. The CDI’s activities advance data and information integration capabilities in the U.S. Geological Survey and in the wider Earth and biological sciences. This annual report describes the presentations, activities, collaboration areas, workshop, and other CDI-sponsored events in fiscal year 2017. The report also describes the objectives of the 11 CDI-funded projects in fiscal year 2017. The report shows how the CDI activities fulfill the strategic objective of the U.S. Geological Survey’s Core Science Systems Mission Area to develop a workplace model for interdisciplinary science.

Open-File Report↗

Capacity assessment for Earth Monitoring, Analysis, and Prediction (EarthMAP) and future integrated monitoring and predictive science at the U.S. Geological Survey

Executive Summary Managers of our Nation’s resources face unprecedented challenges driven by the convergence of increasing, competing societal demands and a changing climate that affects the stability, vulnerability, and predictability of those resources. To help meet these challenges, the scientific community must take advantage of all available technologies, data, and integrative Earth systems modeling capacity to better inform resource and risk management decisions. This is the overarching goal of the U.S. Geological Survey (USGS) Earth Monitoring, Analysis, and Prediction (EarthMAP) vision: “By 2030, the USGS will deliver well integrated observations and predictions of the future state of natural systems—water, ecosystems, energy, minerals, hazards—at regional and national scales, working primarily with federal, state, and academic partners to develop and operate the capability” (U.S. Geological Survey, 2021). Providing more integrated Earth systems science and actionable information to decision makers, stakeholders, and the public requires a better understanding of the depth and distribution of existing capacity (capabilities, tools, and techniques) across the Bureau. Identifying existing capacity is also a critical first step toward gap analysis and targeted investments to increase capacity over time. The USGS formed a Capacity Assessment Team (CAT) and charged it with (1) conducting a Request for Information (RFI) to identify existing USGS expertise and activities supportive of integrated and predictive science to inform decision making, (2) developing a strategy and proof-of-concept for a continuously updated capacity assessment capability, and (3) identifying lessons learned to inform development of best practices for future capacity assessment efforts. The RFI took the form of a survey, with content guided by the science and technology needs identified in a USGS report titled “Grand Challenges for Integrated U.S. Geological Survey Science—A Workshop Report” (Jenni and others, 2017). The 44-question survey provided respondents the ability to rate their level of experience with a suite of priority disciplines, analysis and modeling approaches, technologies, and stakeholder engagement strategies and to enter optional narrative text for supporting context. An introductory portion focused on general science capacity assessment, followed by three sections targeting capabilities related to the foundational components of EarthMAP: (1) data and information integration, (2) integrated predictive science, and (3) actionable information. The survey results provided a high-level snapshot of USGS capacity in the targeted areas. Respondents (1,035 individuals) represented approximately 13 percent of the USGS across all mission areas and regions. Seventy-four percent of the respondents held a science-focused position title and the remainder had position titles in information technology, computer science, management, administrative, or other (contractors, volunteers, emeritus, and unknown). To provide greater insight into respondent capabilities and activities, information from the U.S. Department of the Interior and USGS enterprise information systems were used to further characterize topical expertise and organizational associations of survey respondents. To address the ongoing need to assess the Bureau’s capacity to address integrated predictive science priorities, the CAT developed a software-based proof-of-concept called the Integrated Science Assessment Information Database (iSAID) for assembling various information sources together toward making the full extent of USGS capabilities and scientific assets available for routine capacity assessment. This proof-of-concept is intended to serve as a catalyst for further development. The process of implementing the EarthMAP capacity assessment survey, analyzing survey responses, and developing the proof-of-concept resulted in lessons learned, findings, and recommendations. Example scenarios throughout the report demonstrate how capacity assessment data can inform science planning. Three overarching findings and recommendations are: (1) Finding: Capacity is limited in some critical disciplines, skills, and technology applications, but “sufficient” depends on the question and the need relative to availability at a given point in time. Recommendation: Develop an on-demand capacity assessment framework that enables rapid identification and evaluation of existing and available expertise to support decision needs as they arise. (2) Finding: Institutional barriers and lack of awareness constrain the ability of USGS staff to adopt new technologies, collaborate across administrative boundaries, and deliver actionable information to stakeholders in a timely manner. However, these barriers are not universally experienced. Recommendation: Pursue more targeted inquiries to clarify which institutional barriers are obstructing the adoption of new technologies and approaches or the sharing of expertise and equipment across organizational and regional boundaries. These inquiries should inform USGS leadership, mission areas, and regions whether policies can be revised or whether a lack of understanding is creating perceived obstacles. Highlight cases when staff have successfully adopted new technologies and approaches to advance EarthMAP priorities and provide actionable information in a timely manner to spread awareness of how perceived obstacles can be navigated and overcome when appropriate. (3) Finding: Examples of people and projects integrating across disciplines and scales and applying advanced approaches to meet complex stakeholder needs exist. Such examples provide transfer value across the spectrum from approach to decision making. Many projects, already underway, appear to meet elements of the EarthMAP vision, and the USGS has people who can provide leadership in multiple types of specific integrated science efforts. Recommendation: Use these findings as a starting point for near-term strategic planning for integrated science. Highlight, incentivize, and build on existing interdisciplinary predictive science and information delivery activities across the USGS to advance toward further realization of an EarthMAP capacity. The CAT efforts to develop and assess existing USGS capacity to advance the EarthMAP vision revealed a fundamental challenge for not only this effort but any effort to assess existing capacity: A considerable amount of thought, time, and effort is required to survey and assess capabilities and tools available to support a given need, yet best results are still likely to provide an incomplete assessment. To better meet the frequent need to assess capabilities, tools, products, and projects that address an expressed strategic priority, the CAT proposes the concept of an on-demand capacity assessment framework supported by a software package that dynamically pulls and integrates information from existing USGS information systems and public domain registries. Although existing USGS enterprise information systems currently lack the structure, cross-system consistency, interoperability, and stability to support a continuously updated capacity assessment capability, we identify reasonable near-term steps to improve the utility of information gathered on expertise and project capacity and to improve the consistency and completeness of information and the ability of USGS systems to share that information. The ability to search and characterize this information will make future assessments of capacity faster, more complete, more efficient, and more targeted. This approach would grow the Bureau’s capacity knowledge over time, iteratively improving the ability to access, leverage, and synthesize existing capabilities and assets as well as identify and fill critical gaps. The greatest promise for developing integrated science could lie in linking across existing projects and expertise to create a multi-project capacity for addressing large, complex environmental issues.

Open-File Report↗

Advances in recreational water quality monitoring at Indiana Dunes National Lakeshore

Indiana Dunes has improved its ability to protect the health of swimmers through better science-based management and increased understanding of contaminants. Most research has focused on Escherichia coli and its nature, sources, and distribution because it is widely accepted as an indicator of potential pathogens. Though research on E. coli and recreational water quality is continually generating new information, public beach managers may gain valuable insight into this management issue from our experience at Indiana Dunes. This article reviews one of the longest maintained indicator bacteria monitoring programs in the National Park System, highlights lessons learned, and summarizes research findings that may be of interest to public beach managers.

Park Science↗

Past, present, and future of Mars Polar Science: Outcomes and outlook from the 7th International Conference on Mars Polar Science and Exploration

Mars Polar Science is a subfield of Mars science that encompasses all studies of the cryosphere of Mars and its interaction with the Martian environment. Every 4 yr, the community of scientists dedicated to this subfield meets to discuss new findings and debate open issues in the International Conference on Mars Polar Science and Exploration (ICMPSE). This paper summarizes the proceedings of the seventh ICMPSE and the progress made since the sixth edition. We highlight the most important advances and present the most salient open questions in the field today, as discussed and agreed upon by the participants of the conference. We also feature agreed-upon suggestions for future methods, measurements, instruments, and missions that would be essential to answering the main open questions presented. This work is thus an overview of the current status of Mars Polar Science and is intended to serve as a road map for the direction of the field during the next 4 yr and beyond, helping to shape its contribution within the larger context of planetary science and exploration.

The Planetary Science Journal↗

Interpretation of dye tracing data collected November 13–December 2, 2017, at the Savoy Experimental Watershed as part of the Advanced Groundwater Field Techniques in Karst Terrains course, Savoy, Arkansas

The first course on the use of advanced groundwater field techniques for karst aquifers was conducted November 13–17, 2017, at the University of Arkansas Savoy Experimental Watershed (SEW), which is located on pastures for beef livestock research conducted by the Department of Animal Sciences at the University of Arkansas at Savoy, Arkansas. The SEW is an interdisciplinary, collaborative, long-term research site for the study of animal-waste management in a mantled karst setting. The course focused on advanced field activities appropriate for karst aquifer studies: dye tracing, groundwater/surface-water interactions, geophysical methods, and geochemistry. This report summarizes the data collected and interpreted from the dye tracing part of the November 2017 course, other USGS field courses, and past dye tracing investigations conducted by University of Arkansas students.

Arkansas↗

Introduction: Special issue on advances in topobathymetric mapping, models, and applications

Detailed knowledge of near-shore topography and bathymetry is required for many geospatial data applications in the coastal environment. New data sources and processing methods are facilitating development of seamless, regional-scale topobathymetric digital elevation models. These elevation models integrate disparate multi-sensor, multi-temporal topographic and bathymetric datasets to provide a coherent base layer for coastal science applications such as wetlands mapping and monitoring, sea-level rise assessment, benthic habitat mapping, erosion monitoring, and storm impact assessment. The focus of this special issue is on recent advances in the source data, data processing and integration methods, and applications of topobathymetric datasets.

Journal of Coastal Research↗

A look ahead to the next decade at US volcano observatories

Volcano monitoring, eruption response, and hazard assessment at volcanoes in the United States of America (US) fall under the mandate of five regional volcano observatories covering 161 active volcanoes. Working in a wide range of volcanic and geographic settings, US observatories must learn from and apply new knowledge and techniques to a great variety of scientific and hazard communication problems in volcanology. Over the past decade, experience during volcanic crises, such as the landmark 2018 eruption of Kīlauea, Hawaiʻi, has combined with investments and advances in research and technology, and the changing needs of partner agencies and the public, to transform the operations, science, and communication programs of US volcano observatories. Scientific and operational lessons from the past decade now guide new research and growing inter-observatory and external communication networks to meet new challenges and improve detection, forecasting, and response to volcanic eruptions in the US and around the world.

Bulletin of Volcanology↗

Leveraging artificial intelligence and machine learning to advance Chesapeake Bay research and management: A review of status, challenges, and opportunities

The Chesapeake Bay and its watershed (hereafter “Chesapeake Bay region”) have been the focus of extensive restoration efforts for several decades. These restoration efforts are guided by the Chesapeake Bay Watershed Agreement (Chesapeake Executive Council 2014) which outlines 10 goals and 31 measurable outcomes. The Chesapeake Bay is globally recognized as a model for coastal restoration due to long-term investments in monitoring, modeling, implementation and research by the Chesapeake Bay Program (CBP) partnership. These monitoring network spans tidal and non-tidal regions and provides data across multiple scales. Artificial intelligence (AI), particularly machine-learning (ML) and deep learning (DL), has emerged as a powerful tool for analyzing large, complex datasets. These techniques have gained widespread adoption across various disciplines, including ecology, hydrology, and environmental science. In the Bay context, AI/ML is increasingly being used to explore drivers of environmental change, analyze system dynamics, and predict conditions in areas with limited monitoring. The CBP partnership, particularly its Scientific and Technical Advisory Committee (STAC), has increasingly recognized the growing role of AI/ML in watershed and estuarine management. Recent Chesapeake Community Research Symposium sessions and initiatives such as the Chesapeake Global Collaboratory highlight increasing regional momentum to apply big data and AI/ML for environmental solutions. Together, these developments underscore the timely need to explore how AI/ML can help advance Chesapeake Bay restoration and management. This STAC workshop, titled “Leveraging Artificial Intelligence and Machine learning to Advance Chesapeake Bay Research and Management: A review of status, challenges, and opportunities,” was held from February 24-25, 2025, in Edgewater, Maryland to bring together over 50 federal, state, and academic scientists and partners to synthesize the current state of AI/ML applications and identify research gaps in Chesapeake Bay research and management. The workshop focused on three main objectives: 1. Summarize recent AI/ML applications and lessons learned in both tidal and nontidal areas of the Chesapeake Bay region. 2. Identify challenges and gaps in applying AI/ML approaches to Chesapeake Bay data. Such challenges and gaps may include data limitations, harmonization issues, ineffective communication of AI/ML insights, and a lack of coordination among research and management institutions. 3. Develop recommendations and identify opportunities for leveraging AI/ML to address issues across the Chesapeake Bay region. Key areas of focus may include generating new information to support watershed management, delivering AI/MLgenerated insights to managers in a clear and actionable way, and fostering greater collaboration among stakeholders within the CBP Partnership. Workshop participants engaged in science presentations and breakout sessions to develop recommendations for advancing the integration of AI/ML techniques into research and management across the Chesapeake Bay region. By synthesizing current applications, identifying challenges, and exploring new opportunities, the workshop has provided valuable insights and recommendations for better leveraging AI/ML approaches to support the success of Bay restoration efforts. Together, these recommendations provide a roadmap for enhancing data-driven, science-based decision making aligned with the goals and outcomes of the Chesapeake Bay Watershed Agreement.

Delaware, Maryland, Virginia↗

Research and development program; Conservation Division Outer Continental Shelf oil and gas operations; Technical report 1981

As a result of recommendations several years ago from the National Academy of Sciences, the University of Oklahoma, and the National Aeronautics and Space Administration (NASA), the U.S. Geological Survey has embarked upon a program of research and development to provide the technological insights needed for its regulatory operations offshore—operations which provide assurances to the public for safety and for the prevention of pollution in oil and gas drilling and production. These clear objectives are, therefore, those of the research program, not the economics of operations, which are of concern to industry. The Program is a contract research program and is an integral part of the Conservation Division. It is a focal point for deriving possible solutions from the university community, private industry, and the Federal laboratory system for identified offshore operational problems. This vast interdisciplinary body of science and technology provides the kind of research needed by the Division in its Outer Continental Shelf (OCS) operations which involve such problematic areas as structural dynamics, fluid flow, and geotechnology. The Program encourages innovation and creativity which can be accomplished only by talented scientists and engineers who are dedicated to man's endeavor to make breakthroughs in science and technology. Because the Division's mission is operational, in a sense like the U.S. Navy, the R&D Program must progress in a timely manner even though technological advances cannot really be scheduled. As the Navy's Office of Naval Research (ONR) has so successfully coped with the seeming dichotomy of anticipating the occurrence of innovations, so must the Conservation Division. Thus, USGS, like ONR, makes use of the unsolicited proposal and the best effort contract to accomplish its objectives. Good science and technology can only be accomplished when several variables converge: a talented investigator doing his own research, which happens to coincide with our needs, availability of resources, time scales, etc. Our task is to "beat the bushes" so that these people come to us with their innovative ideas and concepts. They have done so by learning of our interests through announcements of the Program in the Federal Register, reading reports which emanate from the Program, and by attending our seminars.

Open-File Report↗

The Great Lakes Geologic Mapping Coalition—Working collaboratively to understand the geology of the Great Lakes Region

Introduction The Great Lakes Geologic Mapping Coalition (GLGMC), commonly referred to as the “Coalition,” is a partnership between the U.S. Geological Survey (USGS), the U.S. States of Illinois, Indiana, Michigan, Minnesota, New York, Ohio, Pennsylvania, and Wisconsin and the Canadian province of Ontario. The member States receive funding for geologic mapping work from the USGS National Cooperative Geologic Mapping Program (NCGMP), whereas Ontario participates as a nonfunded partner. The mission of the GLGMC is to produce three-dimensional (3D) geologic maps that depict unconsolidated sediments and near-surface bedrock in the Great Lakes region of North America. Geologic maps are the basis of most earth science investigations and help support resource exploration (energy, minerals, groundwater), natural hazard mitigation, infrastructure development, and land-use planning, all of which can be used to advance economic development and strengthen national security in the Great Lakes region. During the last few million years, the Great Lakes region has experienced repeated glacial advances and retreats, leaving behind extensive sediments, abundant natural resources, and widespread effects on the underlying bedrock geology (Swezey and others, 2022). Linked by shared histories of past glaciations, industrial agriculture, and legacy automotive, coal, steel, and manufacturing industries, the GLGMC member States collaborate to improve the understanding of the 3D distribution of the sediments overlying the region’s bedrock (fig. 1). Developing a comprehensive subsurface 3D framework of this glaciated terrain can provide earth science data to policymakers at all levels. These insights facilitate informed decisions on the exploration, use, and protection of vital resources, such as critical minerals, industrial materials, and aquifers, thereby supporting economic prosperity and the well-being of the citizens of this region. Since its inception in 1998, the Coalition has completed more than 100 geologic mapping projects across the Great Lakes region. Each project aims to deliver geologic maps, 3D datasets, and other information that improves understanding of the geology of the Great Lakes region, with an emphasis on economic and water resources. Key deliverables include 3D geologic maps and models typically portraying sediment thickness, often derived from top-of-bedrock and borehole data. These products are developed through a combination of fieldwork, subsurface modeling, and the collection and analysis of rock and sediment cores. To support Coalition goals, member States collaborate with scientists working on related STATEMAP, EDMAP, and FEDMAP projects. Coalition scientists also engage with Tribal Nations in the Great Lakes region to ensure that Tribal interests pertaining to Coalition work are addressed. Through this collaboration, the Coalition unites the efforts of State, Federal, and Tribal Nation stakeholders to advance geologic data production and enhance understanding of the geologic resources of the Great Lakes region.

Illinois, Indiana, Michigan, Minnesota, New York, ↗

Tests of peak flow scaling in simulated self-similar river networks

The effect of linear flow routing incorporating attenuation and network topology on peak flow scaling exponent is investigated for an instantaneously applied uniform runoff on simulated deterministic and random self-similar channel networks. The flow routing is modelled by a linear mass conservation equation for a discrete set of channel links connected in parallel and series, and having the same topology as the channel network. A quasi-analytical solution for the unit hydrograph is obtained in terms of recursion relations. The analysis of this solution shows that the peak flow has an asymptotically scaling dependence on the drainage area for deterministic Mandelbrot-Vicsek (MV) and Peano networks, as well as for a subclass of random self-similar channel networks. However, the scaling exponent is shown to be different from that predicted by the scaling properties of the maxima of the width functions. ?? 2001 Elsevier Science Ltd. All rights reserved.

Advances in Water Resources↗

Holocene and latest Pleistocene glacial chronology, Glacier National Park, Montana.

Moraines of two different age groups have been identified fronting the present-day glaciers and snowfields in Glacier National Park, Montana. The subdued, vegetated moraines of the older group have been found at 25 sites, mainly in the central part of the Lewis Range. These older moraines are in places overlain by the Mazama ash. Although the exact age of the moraines has not been determined by radiocarbon dating, vegetative evidence and correlation with other pre-altithermal age moraines in the Rocky Mountains suggest that these older moraines date from 10 000 BP or earlier. Whether these moraines are the product of a separate advance after the end of the Wisconsin glaciation or are simply the product of the last advance or stillstand of Wisconsin glaciers before final deglaciation is not known.Moraines of the younger group, consisting of fresh bouldery rubble, are common throughout Glacier Park. Tree-ring analyses indicate that some of these younger moraines were deposited by advances that culminated during the mid-19th century. At that time there were more than 150 glaciers in Glacier Park. This episode of mid-19th century climatic cooling resulted in the most extensive glacial advance in this region since the end of the Wisconsin glaciation.Present-day glaciers have shrunk drastically from their mid-19th century positions; more than half the glaciers present during that time no longer exist. Much of this retreat occurred between 1920 and the mid-1940's, corresponding to a period of above-average summer temperatures and below-average annual precipitation in this region. Between 1966 and 1979, several of the larger glaciers in the Mount Jackson area of Glacier Park advanced as much as 100 m.

Montana↗

Cyanobacterial harmful algal blooms and U.S. Geological Survey science capabilities

Cyanobacterial harmful algal blooms (CyanoHABs) are increasingly a global concern because CyanoHABs pose a threat to human and aquatic ecosystem health and cause economic damages. Despite advances in scientific understanding of cyanobacteria and associated compounds, many unanswered questions remain about occurrence, environmental triggers for toxicity, and the ability to predict the timing, duration, and toxicity of CyanoHABs. U.S. Geological Survey (USGS) scientists are leading a diverse range of studies to address CyanoHAB issues in water bodies throughout the United States, using a combination of traditional methods and emerging technologies, and in collaboration with numerous partners. By providing practical applications of cutting edge CyanoHAB research, USGS studies have advanced scientific understanding, enabling the development of approaches to help protect ecological and human health.

Open-File Report↗

Geoinformatics 2007: data to knowledge

Geoinformatics is the term used to describe a variety of efforts to promote collaboration between the computer sciences and the geosciences to solve complex scientific questions. It refers to the distributed, integrated digital information system and working environment that provides innovative means for the study of the Earth systems, as well as other planets, through use of advanced information technologies. Geoinformatics activities range from major research and development efforts creating new technologies to provide high-quality, sustained production-level services for data discovery, integration and analysis, to small, discipline-specific efforts that develop earth science data collections and data analysis tools serving the needs of individual communities. The ultimate vision of Geoinformatics is a highly interconnected data system populated with high quality, freely available data, as well as, a robust set of software for analysis, visualization, and modeling.

Scientific Investigations Report↗

Geoinformatics 2008 - Data to Knowledge

Geoinformatics is the term used to describe a variety of efforts to promote collaboration between the computer sciences and the geosciences to solve complex scientific questions. It refers to the distributed, integrated digital information system and working environment that provides innovative means for the study of the Earth systems, as well as other planets, through use of advanced information technologies. Geoinformatics activities range from major research and development efforts creating new technologies to provide high-quality, sustained production-level services for data discovery, integration and analysis, to small, discipline-specific efforts that develop earth science data collections and data analysis tools serving the needs of individual communities. The ultimate vision of Geoinformatics is a highly interconnected data system populated with high quality, freely available data, as well as, a robust set of software for analysis, visualization, and modeling. This volume is a collection of extended abstracts for oral papers presented at the Geoinformatics 2008 conference, June 11 and 13, 2008, in Potsdam, Germany.

Scientific Investigations Report↗

AviList: A unified global bird checklist

Universally recognized scientific names for organisms are necessary for accurate and efficient communication. Incongruence in taxonomic treatments results in situations where one name is used for different entities or one entity is known by different names, with negative consequences for conservation, science, trade, legislation, law enforcement, and education, leading to discord among stakeholders and confusion among users. Within the ornithological community taxonomic incongruence among four widely adopted global bird checklists has led to calls for the development of a single unified global avian taxonomy or checklist. Here we introduce AviList, a comprehensive, collaborative and evolving effort towards developing a unified global avian taxonomy, spearheaded by representatives of most current global checklists and many major regional authorities, and supported by the International Ornithologists’ Union (IOU), BirdLife International and the Cornell Lab of Ornithology. AviList version 2025, the first version, was officially launched on 11 June 2025 and is available online as a comprehensive, searchable public-access database. It recognizes 11,131 bird species in 2376 genera, 252 families and 46 orders. This global effort has resolved over 1000 species-level taxonomic incongruences among existing checklists. With AviList’s launch, the IOC World Bird List and the Clements Checklist of Birds of the World have ceased any independent taxonomic updates, while BirdLife International is in the process of total alignment, leading to a harmonization in the classification underpinning a number of major bird projects, including eBird, Macaulay Library, Merlin Bird ID and the IUCN Red List. Adoption of AviList will improve inter-operability across global biodiversity, molecular, ecological and spatial databases (e.g. GBIF). Strong governance of AviList will ensure it is a “living” document that is regularly updated by a global community of bird taxonomists as new scientific advances are made, with positive impacts for conservation, academia and human society. It is hoped that AviList will support and encourage taxonomic science by identifying areas where further research is most needed, and that it will provide a blueprint for taxonomic authorities in other organismic groups endeavoring to achieve taxonomic harmonization.

Biodiversity and Conservation↗