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USGS2006

Preliminary integrated geologic map databases for the United States: Connecticut, Maine, Massachusetts, New Hampshire, New Jersey, Rhode Island and Vermont

The rapid growth in the use of Geographic Information Systems (GIS) has highlighted the need for regional and national scale digital geologic maps that have standardized information about geologic age and lithology. Such maps can be conveniently used to generate derivative maps for manifold special purposes such as mineral-resource assessment, metallogenic studies, tectonic studies, and environmental research. Although two digital geologic maps (Schruben and others, 1994; Reed and Bush, 2004) of the United States currently exist, their scales (1:2,500,000 and 1:5,000,000) are too general for many regional applications. Most states have digital geologic maps at scales of about 1:500,000, but the databases are not comparably structured and, thus, it is difficult to use the digital database for more than one state at a time. This report describes the result for a seven state region of an effort by the U.S. Geological Survey to produce a series of integrated and standardized state geologic map databases that cover the entire United States. In 1997, the United States Geological Survey's Mineral Resources Program initiated the National Surveys and Analysis (NSA) Project to develop national digital databases. One primary activity of this project was to compile a national digital geologic map database, utilizing state geologic maps, to support studies in the range of 1:250,000- to 1:1,000,000-scale. To accomplish this, state databases were prepared using a common standard for the database structure, fields, attribution, and data dictionaries. For Alaska and Hawaii new state maps are being prepared and the preliminary work for Alaska is being released as a series of 1:250,000 scale quadrangle reports. This document provides background information and documentation for the integrated geologic map databases of this report. This report is one of a series of such reports releasing preliminary standardized geologic map databases for the United States. The data products of the project consist of two main parts, the spatial databases and a set of supplemental tables relating to geologic map units. The datasets serve as a data resource to generate a variety of stratigraphic, age, and lithologic maps. This documentation is divided into four main sections: (1) description of the set of data files provided in this report, (2) specifications of the spatial databases, (3) specifications of the supplemental tables, and (4) an appendix containing the data dictionaries used to populate some fields of the spatial database and supplemental tables.

Connecticut, Maine, Massachusetts, New Hampshire, ↗

USGS2016

A multidimensional representation model of geographic features

A multidimensional model of geographic features has been developed and implemented with data from The National Map of the U.S. Geological Survey. The model, programmed in C++ and implemented as a feature library, was tested with data from the National Hydrography Dataset demonstrating the capability to handle changes in feature attributes, such as increases in chlorine concentration in a stream, and feature geometry, such as the changing shoreline of barrier islands over time. Data can be entered directly, from a comma separated file, or features with attributes and relationships can be automatically populated in the model from data in the Spatial Data Transfer Standard format.

Open-File Report↗

USGS2025

U.S. Geological Survey Pollinator Science Strategy, 2025–35—A Review and Look Forward

This “U.S. Geological Survey Pollinator Science Strategy, 2025–35—A Review and Look Forward” (“Pollinator Science Strategy”) describes the science vision of the U.S. Geological Survey (USGS) to support management, conservation, and policy decisions on animal pollinators and their habitats. As the science arm of the Department of the Interior, the USGS has a primary role in providing scientific information to natural resource managers and policymakers across the United States. This “Pollinator Science Strategy” was drafted by a team of USGS pollinator researchers and was further developed through feedback from Federal, State, Tribal, nongovernmental organizations, and industry partners. This “Pollinator Science Strategy” highlights the USGS’s role in the research to promote healthy pollinator populations and address partner information gaps so they can make more informed management decisions. By outlining the importance of USGS science in addressing the information needs of other agencies, organizations, and the public, the “Pollinator Science Strategy” reaffirms the USGS’s commitment to pollinator research and showcases our research priorities for 2025–35. With more than 300 research centers nationally, the USGS is equipped to address pollinator science across scales of complexity and geographic range. USGS pollinator science is organized according to the following five thematic areas: Assessing species ecology, distributions, and natural history requirements. Tracking species status and trends. Understanding species threats and stressors. Informing restoration and management actions. Developing novel methods for improving pollinator research, monitoring, and population outcomes that can benefit our Nation. Our pollinator information products and associated data are made widely available to the public to ensure scientific transparency and accessibility. This “Pollinator Science Strategy” concludes with several research goals that the USGS will work towards from 2025 to 2035, representing our vision for USGS science. These research goals include synthesizing and modernizing the latest information on pollinator threats, developing research that assists managers with habitat design and restoration, providing training to partners on native bee identification and monitoring design, and developing new technologies for assessing the status and trends of our nation’s pollinators.

Circular↗

USGS2007

Geographic Analysis and Monitoring Program

The surface of the Earth is changing rapidly, at local, regional, national, and global scales, with significant repercussions for people, the economy, and the environment. Some changes have natural causes, such as wildland fires or hurricanes, while other changes on the land, such as resource extraction, agricultural practices, and urban growth, are human-induced processes. There are other types of changes that are a combination of natural and human-induced factors; landslides and floods, for example, are fundamentally natural processes that are often intensified or accelerated by human land use practices. Whatever their cause, land-surface changes can have profound environmental and economic impacts.

Fact Sheet↗

USGS2004

Urban growth in American cities : glimpses of U.S. urbanization

The Earth's surface is changing rapidly. Changes are local, regional, national, and even global in scope. Some changes have natural causes, such as earthquakes or drought. Other changes, such as urban expansion, agricultural intensification, resource extraction, and water resources development, are examples of human-induced change that have significant impact upon people, the economy, and resources. The consequences that result from these changes are often dramatic and widespread (Buchanan, Acevedo, and Zirbes, 2002) It is the role of the U.S. Geological Survey (USGS) to provide useful and relevant scientific information both to the agencies within the Department of the Interior and to the Nation in general. In an effort to comply with this task, USGS scientists are assessing the status of, and the trends in, the Nation's land surface. This assessment provides useful information for regional and national land use decisionmaking. This knowledge can be used to deal with issues of significance to the Nation, such as quality-of-life, ecology of urban environments, ecosystem health, ecological integrity, water quality and quantity concerns, resource availability, vulnerability to natural hazards, safeguards to human health, air and land quality, and accessibility to scientific information. Results of these assessments can also be analyzed to reveal rates and trends in land use change. Results from urban growth studies provide a firm foundation for continuing research that explores the consequences of human modification of the landscape. The USGS seeks to illustrate and explain the spatial history of urban growth and corresponding land use change. Scientists are studying urban environments from a regional perspective and a time scale of decades to measure the changes that have occurred in order to help understand the impact of anticipated changes in the future. Within this booklet are pairs of images of selected urbanized regions from across the Nation. These image pairs illustrate the transformation that these areas have undergone over two decades. Specifically, they depict changes in the extent of urban land. Each change pair is composed of one image from the 1970s and one image from the 1990s. Accompanying each image pair is a brief historical geography of factors that helped facilitate major changes that have occurred since the founding of the main city and the consequences and challenges of regional urban growth. The goal of this publication is to provide an illustration of urban change that is easily understood by a broad audience. The images used throughout this booklet were generated from land cover data developed by the USGS. The data sources include the Geographic Information Retrieval and Analysis System (GIRAS) for the 1970s images and the National Land Cover Dataset (NLCD) for the 1990s images. GIRAS digital maps are based on photointerpretations completed in the mid-1970s. The NLCD is a land cover dataset for the conterminous United States based on 1992 Landsat thematic mapper (TM) satellite imagery and supplemental data (fig. 1a and fig. 1b). The USGS distributes both of these land use and land cover digital datasets. The images were developed by using a geographic information system (GIS). The GIRAS and NLCD datasets were used to identify urban land within each region. In the final images all urban areas are shown in red. A shaded-relief map of each region was used to display the topographic context of the red polygon coverage. For all of these images, urban land is defined as areas transformed into a built-up environment for human use. It includes residential areas, commercial and industrial developments, transportation features, and institutions.

Circular↗

USGS1991

Application and partial validation of a habitat model for moose in the Lake Superior region

A modified version of the dormant-season portion of a Habitat Suitability Index (HSI) model developed for assessing moose ( Alces alces ) habitat in the Lake Superior Region was incorporated in a Geographic Information System (GIS) for 490 km 2 of Minnesota's Superior National Forest. Moose locations (n=235) were plotted during aerial surveys conducted in December 1988 and January 1990-1991. Dormant-season forage and cover quality for 1,000-m, 500-m, and 200-m radii plots around random points and moose locations were compared using U.S. Forest Service stand examination data. Cover quality indices were lower than forage quality indices within all plots. The median value for the average cover quality index was greater (P=0.003) within 200-m plots around cow moose locations than for plots around random points for the most severe winter of the study. The proportion of highest-quality winter cover, such as mixed stands dominated by mid-age class white spruce ( Picea glauca ) and balsam fir ( Abies balsanea ), was greater within 500-m and 200-m plots around cow moose than within similar plots around random points during the two most severe winters. These results indicate that suboptimum ratings of winter habitat quality used in the GIS for dormant-season forage >100 m from cover, as suggested in the original HSI model, are reasonable. Integrating the habitat model with forest stand data using a GIS permitted analysis of moose habitat within a relatively large geographic area. Simulation of habitat quality indicated a potential shortage of late-winter cover in the study area. The effects of forest management actions on moose habitat quality can be simulated without collecting additional data.

Lake Superior region↗

USGS2016

Flood-inundation maps for a 12.5-mile reach of Big Papillion Creek at Omaha, Nebraska

Digital flood-inundation maps for a 12.5-mile reach of the Big Papillion Creek from 0.6 mile upstream from the State Street Bridge to the 72nd Street Bridge in Omaha, Nebraska, were created by the U.S. Geological Survey (USGS) in cooperation with the Papio-Missouri River Natural Resources District. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/ , depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage on the Big Papillion Creek at Fort Street at Omaha, Nebraska (station 06610732). Near-real-time stages at this streamgage may be obtained on the Internet from the USGS National Water Information System at http://waterdata.usgs.gov/ or the National Weather Service Advanced Hydrologic Prediction Service at http:/water.weather.gov/ahps/ , which also forecasts flood hydrographs at this site. Flood profiles were computed for the 12.5-mile reach by means of a one-dimensional step-backwater model. The model was calibrated by using the current (2015) stage-discharge relation at streamgages for the Big Papillion Creek at Fort Street at Omaha, Nebraska, and the Big Papillion Creek at Q Street at Omaha, Nebraska. The hydraulic model was then used to compute 15 water-surface profiles for flood stages at 1-foot (ft) intervals referenced to the streamgage datum for the Big Papillion Creek at Fort Street and ranging from 18 ft (or near bankfull) to 32 ft, which exceeds the “major flood stage” as defined by the National Weather Service. The simulated water-surface profiles were then combined with a Geographic Information System digital elevation model (derived from light detection and ranging data having a 1.18-ft vertical accuracy and 3.28-ft horizontal resolution) to delineate the area flooded at each flood stage (water level). The availability of these flood-inundation maps, along with Internet information regarding current stage from the USGS streamgage and forecasted high-flow stages from the National Weather Service, will provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, as well as for postflood recovery efforts.

Nebraska↗

USGS1998

Geospatial Technology Applications and Infrastructure in the Biological Resources Division

Executive Summary -- Automated spatial processing technology such as geographic information systems (GIS), telemetry, and satellite-based remote sensing are some of the more recent developments in the long history of geographic inquiry. For millennia, humankind has endeavored to map the Earth's surface and identify spatial relationships. But the precision with which we can locate geographic features has increased exponentially with satellite positioning systems. Remote sensing, GIS, thematic mapping, telemetry, and satellite positioning systems such as the Global Positioning System (GPS) are tools that greatly enhance the quality and rapidity of analysis of biological resources. These technologies allow researchers, planners, and managers to more quickly and accurately determine appropriate strategies and actions. Researchers and managers can view information from new and varying perspectives using GIS and remote sensing, and GPS receivers allow the researcher or manager to identify the exact location of interest. These geospatial technologies support the mission of the U.S. Geological Survey (USGS) Biological Resources Division (BRD) and the Strategic Science Plan (BRD 1996) by providing a cost-effective and efficient method for collection, analysis, and display of information. The BRD mission is 'to work with others to provide the scientific understanding and technologies needed to support the sound management and conservation of our Nation's biological resources.' A major responsibility of the BRD is to develop and employ advanced technologies needed to synthesize, analyze, and disseminate biological and ecological information. As the Strategic Science Plan (BRD 1996) states, 'fulfilling this mission depends on effectively balancing the immediate need for information to guide management of biological resources with the need for technical assistance and long-range, strategic information to understand and predict emerging patterns and trends in ecological systems.' Information sharing plays a key role in nearly everything BRD does. The Strategic Science Plan discusses the need to (1) develop tools and standards for information transfer, (2) disseminate information, and (3) facilitate effective use of information. This effort centers around the National Biological Information Infrastructure (NBII) and the National Spatial Data Infrastructure (NSDI), components of the National Information Infrastructure. The NBII and NSDI are distributed electronic networks of biological and geographical data and information, as well as tools to help users around the world easily find and retrieve the biological and geographical data and information they need. The BRD is responsible for developing scientifically and statistically reliable methods and protocols to assess the status and trends of the Nation's biological resources. Scientists also conduct important inventory and monitoring studies to maintain baseline information on these same resources. Research on those species for which the Department of the Interior (DOI) has trust responsibilities (including endangered species and migratory species) involves laboratory and field studies of individual animals and the environments in which they live. Researchboth tactical and strategicis conducted at the BRD's 17 science centers and 81 field stations, 54 Cooperative Fish and Wildlife Research Units in 40 states, and at 11 former Cooperative Park Study Units. Studies encompass fish, birds, mammals, and plants, as well as their ecosystems and the surrounding landscape. Biological Resources Division researchers use a variety of scientific tools in their endeavors to understand the causes of biological and ecological trends. Research results are used by managers to predict environmental changes and to help them take appropriate measures to manage resources effectively. The BRD Geospatial Technology Program facilitates the collection, analysis, and dissemination of data and informat

Information and Technology Report↗

USGS2022

Spatial social value distributions for multiple user groups in a coastal national park

Managing public lands to maximize societal benefits requires spatially explicit understanding of societal valuation, and public participation geographic information systems (PPGIS) are increasingly used in coastal settings to accomplish this task. Social Values for Ecosystem Services (SolVES), a PPGIS tool that systematizes the mapping and modeling of social values and cultural ecosystem services, is promising for use in coastal settings but has seen relatively limited applications relative to other PPGIS approaches; it has also, to our knowledge, not yet been applied in a barrier island setting. In this study, we surveyed two visitor groups and residents living near Cape Lookout National Seashore (North Carolina, USA) to understand their social values in the context of the park's management needs. We developed social-value models to evaluate differences between three user groups (fall visitors, summer visitors, and residents) and to evaluate how respondents' experiences, attitudes, and recreational activities influence the locations they value and their most strongly held value types, which included aesthetic, recreation, biodiversity, future, therapeutic, and historic values. We found that accessibility, user types and the seasonality of major recreational activities, and the linear configuration of the barrier island system at Cape Lookout are important influences on the social values held by visitors and residents. The modeling results provide information relevant to management at Cape Lookout and can inform the design of future PPGIS studies in coastal and marine settings.

North Carolina↗

USGS1990

Catalog of US GeoData

The development of geographic information systems (GIS) is a rapidly growing industry that supports natural resources, studies, land management, environmental analysis, and urban and transporation planning. The increasing use of computers for storing and analyzing earth science information has greatly expanded the demand for digital cartographic and geographic data. Digital cartography involves the collection, storage, processing, analysis, and display of map data with the aid of computers. The U.S. Geological Survey (USGS), the Nation's largest earth science research agency, through its National Mapping Program, has expanded digital cartography operations to include the collection of elevation, planimetric, land use and land cover, and geographic names information in digital form. This digital information is available on 9-track magnetic tapes and, in the case of 1:2,000,000-scale planimetric digital line graph data, in Compact Disc Read Only Memory (CD-ROM) format. Digital information can be used with all types of geographic and land information systems.

General Information Product↗

USGS2010

Mineral and Vegetation Maps of the Bodie Hills, Sweetwater Mountains, and Wassuk Range, California/Nevada, Generated from ASTER Satellite Data

Multispectral remote sensing data acquired by the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) were analyzed to identify and map minerals, vegetation groups, and volatiles (water and snow) in support of geologic studies of the Bodie Hills, Sweetwater Mountains, and Wassuk Range, California/Nevada. Digital mineral and vegetation mapping results are presented in both portable document format (PDF) and ERDAS Imagine format (.img). The ERDAS-format files are suitable for integration with other geospatial data in Geographic Information Systems (GIS) such as ArcGIS. The ERDAS files showing occurrence of 1) iron-bearing minerals, vegetation, and water, and 2) clay, sulfate, mica, carbonate, Mg-OH, and hydrous quartz minerals have been attributed according to identified material, so that the material detected in a pixel can be queried with the interactive attribute identification tools of GIS and image processing software packages (for example, the Identify Tool of ArcMap and the Inquire Cursor Tool of ERDAS Imagine). All raster data have been orthorectified to the Universal Transverse Mercator (UTM) projection using a projective transform with ground-control points selected from orthorectified Landsat Thematic Mapper data and a digital elevation model from the U.S. Geological Survey (USGS) National Elevation Dataset (1/3 arc second, 10 m resolution). Metadata compliant with Federal Geographic Data Committee (FGDC) standards for all ERDAS-format files have been included, and contain important information regarding geographic coordinate systems, attributes, and cross-references. Documentation regarding spectral analysis methodologies employed to make the maps is included in these cross-references.

Scientific Investigations Map↗

USGS2021

USGS National Water Quality Monitoring Network

What is the U.S. Geological Survey National Water Quality Monitoring Network? Understanding the water quality of U.S. streams and rivers requires consistent data collection and analysis over decades. The U.S. Geological Survey’s (USGS) National Water Quality Network (NWQN) was established to facilitate national-scale understanding of surface-water quality conditions through the collection of comparable data in large rivers and small streams in different geographic and land-use settings. Data collected by the NWQN support the needs of Federal, State, and local stakeholders tasked with managing our Nation’s water resources.

Fact Sheet↗

USGS2011

Topographic mapping data semantics through data conversion and enhancement

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.

Book chapter↗

USGS2019

Flood-inundation maps for Nimishillen Creek near North Industry, Ohio, 2019

Digital flood-inundation maps for a 4-mile reach of Nimishillen Creek near North Industry, Ohio, were created by the U.S. Geological Survey (USGS) in cooperation with the Muskingum Watershed Conservancy District, Ohio, and the Stark County Board of Commissioners. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping (FIM) Program website at https://water.usgs.gov/osw/flood_inundation/ , depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage on Nimishillen Creek at North Industry, Ohio (station number 03118500). Near-real-time stages at this streamgage can be obtained on the internet from the USGS National Water Information System at https://waterdata.usgs.gov/ or the National Weather Service Advanced Hydrologic Prediction Service at https://water.weather.gov/ahps/ , which also forecasts flood hydrographs at this site. Flood profiles were computed for the stream reach by means of a one-dimensional step-backwater model. The model was calibrated to the current stage-discharge relation at the streamgage on Nimishillen Creek at North Industry and documented high-water marks from the flood of January 12, 2017. The hydraulic model was then used to compute seven water-surface profiles for flood stages at 1-foot (ft) intervals referenced to the streamgage datum and ranging from 8 to 14 ft, which is from “action stage” to above “major flood stage” as reported by the National Weather Service. The simulated water-surface profiles were then used in combination with a geographic information system (GIS) digital elevation model derived from light detection and ranging data to delineate the areas flooded at each water level. The availability of these maps, along with internet information regarding current stage from the USGS streamgage and forecasted high-flow stages from the National Weather Service, will provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, as well as for postflood recovery efforts. Forecasts for the USGS streamgage on Nimishillen Creek at North Industry, Ohio are issued as needed during times of high water, but are not routinely available (National Weather Service, 2017).

Ohio↗

USGS2009

Vegetation classification and distribution mapping report: Mesa Verde National Park

The classification and distribution mapping of the vegetation of Mesa Verde National Park (MEVE) and surrounding environment was achieved through a multi-agency effort between 2004 and 2007. The National Park Service’s Southern Colorado Plateau Network facilitated the team that conducted the work, which comprised the U.S. Geological Survey’s Southwest Biological Science Center, Fort Collins Research Center, and Rocky Mountain Geographic Science Center; Northern Arizona University; Prescott College; and NatureServe. The project team described 47 plant communities for MEVE, 34 of which were described from quantitative classification based on f eld-relevé data collected in 1993 and 2004. The team derived 13 additional plant communities from field observations during the photointerpretation phase of the project. The National Vegetation Classification Standard served as a framework for classifying these plant communities to the alliance and association level. Eleven of the 47 plant communities were classified as “park specials;” that is, plant communities with insufficient data to describe them as new alliances or associations. The project team also developed a spatial vegetation map database representing MEVE, with three different map-class schemas: base, group, and management map classes. The base map classes represent the fi nest level of spatial detail. Initial polygons were developed using Definiens Professional (at the time of our use, this software was called eCognition), assisted by interpretation of 1:12,000 true-color digital orthophoto quarter quadrangles (DOQQs). These polygons (base map classes) were labeled using manual photo interpretation of the DOQQs and 1:12,000 true-color aerial photography. Field visits verified interpretation concepts. The vegetation map database includes 46 base map classes, which consist of associations, alliances, and park specials classified with quantitative analysis, additional associations and park specials noted during photointerpretation, and non-vegetated land cover, such as infrastructure, land use, and geological land cover. The base map classes consist of 5,007 polygons in the project area. A field-based accuracy assessment of the base map classes showed overall accuracy to be 43.5%. Seven map classes comprise 89.1% of the park vegetated land cover. The group map classes represent aggregations of the base map classes, approximating the group level of the National Vegetation Classification Standard, version 2 (Federal Geographic Data Committee 2007), and reflecting physiognomy and floristics. Terrestrial ecological systems, as described by NatureServe (Comer et al. 2003), were used as the fi rst approximation of the group level. The project team identified 14 group map classes for this project. The overall accuracy of the group map classes was determined using the same accuracy assessment data as for the base map classes. The overall accuracy of the group representation of vegetation was 80.3%. In consultation with park staff , the team developed management map classes, consisting of park-defined groupings of base map classes intended to represent a balance between maintaining required accuracy and providing a focus on vegetation of particular interest or import to park managers. The 23 management map classes had an overall accuracy of 73.3%. While the main products of this project are the vegetation classification and the vegetation map database, a number of ancillary digital geographic information system and database products were also produced that can be used independently or to augment the main products. These products include shapefiles of the locations of field-collected data and relational databases of field-collected data.

Mesa Verde National Park↗

USGS2026

A geographic dataset of rocky reefs habitat areas of particular concern for the United States West Coast

The United States National Marine Fisheries Service determines “essential fish habitat (EFH)” for federally managed species in coordination with regional fishery management councils, considers adverse effects to those habitats, and provides information to further habitat conservation and enhancement. Identifying discrete subsets of EFH as “habitat areas of particular concern (HAPC)” can help focus conservation, management, and research efforts. In 2006, the Pacific Fishery Management Council designated rocky reefs along the United States (U.S.) West Coast as HAPCs for groundfishes because of their ecological significance, sensitivity to human impacts, and relative rarity. To better understand where rocky reefs occur, we (1) located rocky reef areas that were not included in the 2006 rocky reef dataset, and (2) incorporated best available data into a refined geographic dataset that enables visualization. Our update shows that rocky reefs are distributed throughout the U.S. West Coast continental margin, are patchier than previously known, and comprise 8% of the extent of all data inputs. This updated dataset will inform resource management decisions in coastal and marine environments.

California, Oregon, Washington↗

USGS2026

Whatever it takes— Shaping the L&O Letters Early Career Publication Honor to deliver true benefit

There are clear advantages for those who openly share their research. Publishing Open Access (OA) articles can increase author visibility (McCabe and Snyder 2014 ), improve productivity metrics (i.e., more diverse and higher citation rates; Huang et al. 2024 ; Piwowar et al. 2018 ), widen collaborative networks (Tai and Robinson 2018 ), and help secure future funding and/or comply with funder mandates (Herrmannova et al. 2019 ; Larivière and Sugimoto 2018 ; McKiernan et al. 2016 and references therein). These benefits can be vital for students and early career researchers (ECRs) trying to advance and thrive in academia. However, publishing papers in Gold OA journals such as L&O Letters comes at a notable financial cost, as these journals require that the corresponding author (or their organization or funder) pay a fee to make their published article immediately freely available to the public. These article processing charges can be prohibitively expensive (Fontúrbel and Vizentin-Bugoni 2021 ; Mekonnen et al. 2022 ; Ross-Hellauer et al. 2022 ). While Read and Publish agreements and waiver programs may be available to help cover these costs, these programs often exclude independent authors as well as those affiliated with ineligible or non-participating institutions (e.g., publisher waivers using the Research4Life eligibility criteria for access currently only allow authors from one of 13 South American countries/territories to publish free of charge). Besides the financial barrier, authors from underrepresented groups can also face a myriad of other publishing roadblocks, such as linguistic challenges (for speakers of English as a foreign language; Amano et al. 2023 ; Franco-Santos 2024 ; Ramírez-Castañeda 2020 ) and geopolitical-scientific bias (e.g., science conducted in the Global South being seen as less impactful and innovative than that conducted in the Global North; Ghosh 2022 ; Smits et al. 2025 ). For context, Global South (GS) and Global North (GN) are not geographic determinations (i.e., South and North hemispheres), but geopolitical classifications regarding a nation's level of development (underdeveloped, developing, or developed). For example: Australia and Brazil are both located in the southern hemisphere, but the former is considered as a Global North (developed) country and the latter as a Global South (underdeveloped or developing) country. When a subset of researchers is unable to openly publish their work, the diversity of voices represented in OA literature can decline (Williams et al. 2023 ). Loss of diversity is a loss to science, as diversity increases productivity, innovation, and scientific impact (refer to opening quote; Freeman and Huang 2014 ; AlShebli et al. 2018 ; Tomillo et al. 2022 ). To partially address the above-mentioned challenges and enable underfunded ECRs to publish their work in OA format, the biennial L&O Letters Early Career Publication Honor (ECPH) was established in 2020 by the ASLO Raelyn Cole Editorial (RCE) Fellows (Hotaling et al. 2022 ). Below we reflect on the benefits, outcomes, and scientific impact of the 2022 call and introduce the articles it helped publish in L&O Letters , which are bundled in this section of the ECPH Virtual Issue. Articles published in L&O Letters during other calls are available in their respective sections. We also refer the reader to six articles published by ECRs in other journals (not included in this Virtual Issue) whose content originally warranted their leading author an ECPH in 2022.

Limnology and Oceanography Letters↗

USGS2025

Comparative genomics of Bacillus anthracis A and B-clades reveals genetic variation in genes responsible for spore germination

Bacillus anthracis , the causative agent of anthrax, is composed of three genetic clades (A, B, and C). Clade-A is the most common and distributed worldwide, B-clade has a narrow geographic distribution, and C-clade is rare. South Africa's Kruger National Park (KNP) has high diversity of B. anthracis , with strains from A and B clades described from its northernmost region, Pafuri. We employed whole genome sequencing to investigate the genomic diversity of B. anthracis strains isolated from animal carcasses ( n = 34) during the 2012–2015 outbreaks. Whole-genome single-nucleotide polymorphism (wgSNP) analysis assigned the 2012–2015 B. anthracis genomes to the A-clade branch, distributed across the branch's two minor sub-clades A.Br.005/006. Additionally, pan-genomic analysis distinguished the A- and B-clade genomes, identifying unique accessory genes. Notable genetic differences include the biosynthetic spore cell wall genes; long-chain fatty acid CoA ligases ( FaD13 ), Bacillus collagen-like protein of anthracis (BclA) involved in the exosporium germination, as well as a truncated murein DD-endopeptidase ( mepH ) found in the pXO2 plasmid of the B-clade strains. The tryptophan synthase subunit alpha gene ( trpA ), which results in a pseudogene in B-clade genomes separates the A- and B-clade genomes. These differences in biosynthetic cell wall genes suggest variation in adaptability or cell growth of the B-clade strains in the environment, further influenced by the truncation of the trpA gene involved in spore germination. The A.Br.005/006-clade strains in KNP exhibit higher genetic diversity, which may enhance their resilience to environmental stressors. In contrast, the KNP B-clade (B.Br.001/002) strains show limited genetic variation, potentially reducing their adaptability. This pattern is evident through whole-genome SNP analysis and pan-genomics investigating the evolution of B. anthracis .

Kruger National Park↗