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USGS2011

Fire frequency, area burned, and severity: A quantitative approach to defining a normal fire year

Fire frequency, area burned, and fire severity are important attributes of a fire regime, but few studies have quantified the interrelationships among them in evaluating a fire year. Although area burned is often used to summarize a fire season, burned area may not be well correlated with either the number or ecological effect of fires. Using the Landsat data archive, we examined all 148 wildland fires (prescribed fires and wildfires) >40 ha from 1984 through 2009 for the portion of the Sierra Nevada centered on Yosemite National Park, California, USA. We calculated mean fire frequency and mean annual area burned from a combination of field- and satellite-derived data. We used the continuous probability distribution of the differenced Normalized Burn Ratio (dNBR) values to describe fire severity. For fires >40 ha, fire frequency, annual area burned, and cumulative severity were consistent in only 13 of 26 years (50 %), but all pair-wise comparisons among these fire regime attributes were significant. Borrowing from long-established practice in climate science, we defined “fire normals” to be the 26 year means of fire frequency, annual area burned, and the area under the cumulative probability distribution of dNBR. Fire severity normals were significantly lower when they were aggregated by year compared to aggregation by area. Cumulative severity distributions for each year were best modeled with Weibull functions (all 26 years, r 2 ≥ 0.99; P < 0.001). Explicit modeling of the cumulative severity distributions may allow more comprehensive modeling of climate-severity and area-severity relationships. Together, the three metrics of number of fires, size of fires, and severity of fires provide land managers with a more comprehensive summary of a given fire year than any single metric.

Wyoming↗

USGS2010

Spatial models of Northern Bobwhite populations for conservation planning

Since 1980, northern bobwhite (Colinus virginianus) range-wide populations declined 3.9% annually. Within the West Gulf Coastal Plain Bird Conservation Region in the south-central United States, populations of this quail species have declined 6.8% annually. These declines sparked calls for land use change and prompted implementation of various conservation practices. However, to effectively reverse these declines and restore northern bobwhite to their former population levels, habitat conservation and management efforts must target establishment and maintenance of sustainable populations. To provide guidance for conservation and restoration of habitat capable of supporting sustainable northern bobwhite populations in the West Gulf Coastal Plain, we modeled their spatial distribution using landscape characteristics derived from 1992 National Land Cover Data and bird detections, from 1990 to 1994, along 10-stop Breeding Bird Survey route segments. Four landscape metrics influenced detections of northern bobwhite: detections were greater in areas with more grassland and increased aggregation of agricultural lands, but detections were reduced in areas with increased density of land cover edge and grassland edge. Using these landscape metrics, we projected the abundance and spatial distribution of northern bobwhite populations across the entire West Gulf Coastal Plain. Predicted populations closely approximated abundance estimates from a different cadre of concurrently collected data but model predictions did not accurately reflect bobwhite detections along species-specific call-count routes in Arkansas and Louisiana. Using similar methods, we also projected northern bobwhite population distribution circa 1980 based on Land Use Land Cover data and bird survey data from 1976 to 1984. We compared our 1980 spatial projections with our spatial estimate of 1992 populations to identify areas of population change. Additionally, we used our projection of the spatial distribution and abundance of bobwhite to predict areas of population sustainability. Our projections of population change and sustainability provide guidance for targeting habitat conservation and rehabilitation efforts for restoration of northern bobwhite populations in the West Gulf Coastal Plain.

Journal of Wildlife Management↗

USGS2014

Development of a spatially universal framework for classifying stream assemblages with application to conservation planning for Great Lakes lotic fish communities

Classifications are typically specific to particular issues or areas, leading to patchworks of subjectively defined spatial units. Stream conservation is hindered by the lack of a universal habitat classification system and would benefit from an independent hydrology-guided spatial framework of units encompassing all aquatic habitats at multiple spatial scales within large regions. We present a system that explicitly separates the spatial framework from any particular classification developed from the framework. The framework was constructed from landscape variables that are hydrologically and biologically relevant, covered all space within the study area, and was nested hierarchically and spatially related at scales ranging from the stream reach to the entire region; classifications may be developed from any subset of the 9 basins, 107 watersheds, 459 subwatersheds, or 10,000s of valley segments or stream reaches. To illustrate the advantages of this approach, we developed a fish-guided classification generated from a framework for the Great Lakes region that produced a mosaic of habitat units which, when aggregated, formed larger patches of more general conditions at progressively broader spatial scales. We identified greater than 1,200 distinct fish habitat types at the valley segment scale, most of which were rare. Comparisons of biodiversity and species assemblages are easily examined at any scale. This system can identify and quantify habitat types, evaluate habitat quality for conservation and/or restoration, and assist managers and policymakers with prioritization of protection and restoration efforts. Similar spatial frameworks and habitat classifications can be developed for any organism in any riverine ecosystem.

Michigan, Minnesota, New York, Ohio, Wisconsin↗

USGS2008

Limestone - A Crucial and Versatile Industrial Mineral Commodity

Limestone, as used by the minerals industry, is any rock composed mostly of calcium carbonate (CaCO3). Although limestone is common in many parts of the United States, it is critically absent from some. Limestone is used to produce Portland cement, as aggregate in concrete and asphalt, and in an enormous array of other products, making it a truly versatile commodity. Portland cement is essential to the building industry, but despite our Nation's abundance of limestone, there have been cement shortages in recent years. These have been caused in part by a need to find new areas suitable for quarrying operations. To help manage our Nation's resources of such essential mineral commodities, the U.S. Geological Survey (USGS) provides crucial data and scientific information to industry, policymakers, and the public.

Fact Sheet↗

USGS2003

Monitoring trends in bat populations of the United States and territories: Problems and prospects

Bats are ecologically and economically important mammals. The life histories of bats (particularly their low reproductive rates and the need for some species to gather in large aggregations at limited numbers of roosting sites) make their populations vulnerable to declines. Many of the species of bats in the United States (U.S.) and territories are categorized as endangered or threatened, have been candidates for such categories, or are considered species of concern. The importance and vulnerability of bat populations makes monitoring trends in their populations a goal for their future management. However, scientifically rigorous monitoring of bat populations requires well-planned, statistically defensible efforts. This volume reports findings of an expert workshop held to examine the topic of monitoring populations of bats. The workshop participants included leading experts in sampling and analysis of wildlife populations, as well as experts in the biology and conservation of bats. Findings are reported in this volume under two sections. Part I of the report presents contributed papers that provide overviews of past and current efforts at monitoring trends in populations of bats in the U.S. and territories. These papers consider current techniques and problems, and summarize what is known about the status and trends in populations of selected groups of bats. The contributed papers in Part I also include a description of the monitoring program developed for bat populations in the United Kingdom, a critique of monitoring programs in wildlife in general with recommendations for survey and sampling strategies, and a compilation and analysis of existing data on trends in bats of the U.S. and territories. Efforts directed at monitoring bat populations are piecemeal and have shortcomings. In Part II of the report, the workshop participants provide critical analyses of these problems and develop recommendations for improving methods, defining objectives and priorities, gaining mandates, and enhancing information exchange to facilitate future efforts for monitoring trends in U.S. bat populations.

Information and Technology Report↗

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↗

USGS2020

Grazing-induced changes to biological soil crust cover mediate hillslope erosion in a long-term exclosure experiment

Dryland ecosystems are particularly vulnerable to erosion generated by livestock grazing. Quantifying this risk across a variety of landscape settings is essential for successful adaptive management, particularly in light of a changing climate. In the Upper Colorado River Basin, there are nearly 25 000 km 2 of rangelands with underlying soils derived from Mancos Shale, an erodible and saline geologic parent material. Salinity is a major concern within the Colorado River watershed, much of which is attributed to runoff and leaching from Mancos Shale deposits. In a 60-yr paired-watershed experiment in western Colorado, we used silt fences to measure differences in saline hillslope erosion, including both total sediment yield and concentrations of primary saline constituents (Na and Se), in watersheds that were either exposed to grazing or where livestock was excluded. After accounting for the strong effects of soil type, slope, and antecedent precipitation, we found that grazing increased sediment loss by ≈50% across our 8-yr time series (0.1–1.5 tn ha −1 ), consistent with levels reported at the watershed scale in early published work from studies at the same location. Eroded sediment Se levels were low and unaffected by grazing history, but Na concentrations were significantly reduced on grazed hillslopes, likely due to depletion of surface Na in soils exposed to chronic soil disturbance by livestock. Variable selection and path analysis identified that biological soil crust (BSC) cover, more than any other variable, explained the differences in sediment yields between grazed and ungrazed watersheds, partially through the enhancement of soil aggregate stability. Our results suggest that BSC cover should be granted heightened consideration in rangeland decision support tools (e.g., state-and-transition models) and that measures to reduce surface disturbance from livestock such as altering the timing or intensity of grazing may be effective for reducing downstream impacts.

Colorado↗

USGS2016

Do we need demographic data to forecast plant population dynamics?

Rapid environmental change has generated growing interest in forecasts of future population trajectories. Traditional population models built with detailed demographic observations from one study site can address the impacts of environmental change at particular locations, but are difficult to scale up to the landscape and regional scales relevant to management decisions. An alternative is to build models using population-level data that are much easier to collect over broad spatial scales than individual-level data. However, it is unknown whether models built using population-level data adequately capture the effects of density-dependence and environmental forcing that are necessary to generate skillful forecasts. Here, we test the consequences of aggregating individual responses when forecasting the population states (percent cover) and trajectories of four perennial grass species in a semi-arid grassland in Montana, USA. We parameterized two population models for each species, one based on individual-level data (survival, growth and recruitment) and one on population-level data (percent cover), and compared their forecasting accuracy and forecast horizons with and without the inclusion of climate covariates. For both models, we used Bayesian ridge regression to weight the influence of climate covariates for optimal prediction. In the absence of climate effects, we found no significant difference between the forecast accuracy of models based on individual-level data and models based on population-level data. Climate effects were weak, but increased forecast accuracy for two species. Increases in accuracy with climate covariates were similar between model types. In our case study, percent cover models generated forecasts as accurate as those from a demographic model. For the goal of forecasting, models based on aggregated individual-level data may offer a practical alternative to data-intensive demographic models. Long time series of percent cover data already exist for many plant species. Modelers should exploit these data to predict the impacts of environmental change.

Methods in Ecology and Evolution↗

USGS2015

Efficient wetland surface water detection and monitoring via Landsat: Comparison with in situ data from the Everglades Depth Estimation Network

The U.S. Geological Survey is developing new Landsat science products. One, named Dynamic Surface Water Extent (DSWE), is focused on the representation of ground surface inundation as detected in cloud-/shadow-/snow-free pixels for scenes collected over the U.S. and its territories. Characterization of DSWE uncertainty to facilitate its appropriate use in science and resource management is a primary objective. A unique evaluation dataset developed from data made publicly available through the Everglades Depth Estimation Network (EDEN) was used to evaluate one candidate DSWE algorithm that is relatively simple, requires no scene-based calibration data, and is intended to detect inundation in the presence of marshland vegetation. A conceptual model of expected algorithm performance in vegetated wetland environments was postulated, tested and revised. Agreement scores were calculated at the level of scenes and vegetation communities, vegetation index classes, water depths, and individual EDEN gage sites for a variety of temporal aggregations. Landsat Archive cloud cover attribution errors were documented. Cloud cover had some effect on model performance. Error rates increased with vegetation cover. Relatively low error rates for locations of little/no vegetation were unexpectedly dominated by omission errors due to variable substrates and mixed pixel effects. Examined discrepancies between satellite and in situ modeled inundation demonstrated the utility of such comparisons for EDEN database improvement. Importantly, there seems no trend or bias in candidate algorithm performance as a function of time or general hydrologic conditions, an important finding for long-term monitoring. The developed database and knowledge gained from this analysis will be used for improved evaluation of candidate DSWE algorithms as well as other measurements made on Everglades surface inundation, surface water heights and vegetation using radar, lidar and hyperspectral instruments. Although no other sites have such an extensive in situ network or long-term records, the broader applicability of this and other candidate DSWE algorithms is being evaluated in other wetlands using this work as a guide. Continued interaction among DSWE producers and potential users will help determine whether the measured accuracies are adequate for practical utility in resource management.

Florida↗

USGS2024

Leveraging local wildlife surveys for robust occupancy trend estimation

Natural resource agencies are frequently tasked with monitoring populations of at-risk species to ensure management activities do not negatively affect the viability of wildlife populations. Typically, these monitoring efforts evaluate trends in a population’s abundance, occupancy, or geographic distribution. Often, surveys provide local information, but results are generally not incorporated into broad-scale monitoring efforts that focus on range-wide population changes due to their variable nature in both spatial extent and effort. We investigated whether aggregating these local (hereafter “variable”) surveys can generate enough statistical power to estimate broad-scale population trends using simulations of declining populations of fishers ( Pekania pennati ) over a 10-year time horizon. Our simulations included three population sizes which we refer to as abundant, common, and rare ( N 0 = 700, 350, and 100 individuals, respectively) with each declining at a rapid and moderate pace ( λ = 0.933, and 0.977, respectively). For each population, we simulated variable surveys using an occupancy framework to subsample the population with parameters that mimic combining multiple independent monitoring efforts which vary annually in location, and effort. Regardless of spatial consistency of annual sampling, there was minimal variation in statistical power under both high and low detection probability simulations. However, when sampling effort varied each year, statistical power was lower for most populations and sampling scenarios when compared to consistent sampling effort unless some baseline level of sampling effort was reliably achieved in all years. In many cases, adding low-level consistent baseline sampling to variable surveys resulted in statistical power close to that of consistent sampling efforts. Our results suggest statistical power is driven by annual consistency in the proportion of landscape sampled rather than spatial consistency in sampling locations. This result indicates that current variable surveys could be leveraged and combined to detect population declines for at-risk species at broad-scales if a baseline proportion of landscape is robustly sampled. The level of baseline sampling is highly dependent on population size and magnitudes of population change. In simulations with a common or abundant population experiencing a rapid decline, a baseline survey effort of at least 5% of the landscape in combination with variable surveys resulted in statistical power consistently above the standard threshold of 0.80 for occupancy monitoring. Leveraging existing local efforts to achieve high detection probability and baseline sampling would reduce financial and logistical burdens of broad-scale wildlife monitoring efforts.

Idaho, Montana↗

USGS2025

Water depth, position within the nesting colony, and nearest neighbor density affect nest survival in Aechmophorus occidentalis (Western Grebe)

Aechmophorus occidentalis (Western Grebe) are colonial nesting waterbirds that have experienced population declines. We located and monitored 709 grebe nests using a drone within Lake Cascade, the largest grebe breeding colony in Idaho. We conducted 6 flights between June 20, 2018 and July 11, 2018 and used the photographs from each flight to create an orthomosaic image that we then digitized and georeferenced. The resolution of the images allowed for visualization of each nest, nest contents, and adult grebes on each flight. Using the georeferenced images, we created nest histories and estimated nest fate for the 709 grebe nests. We also collected data on the following covariates to assess whether any of them affected nest survival: distance of the nest to the center of the colony; distance of the nest to the edge of the colony; distance of the nest to deep water habitat; water depth at the nest; nearest neighbor distance, and an aggregation index (mean distance to the 5 nearest nests). The orthomosaics from repeated drone flights allowed us to estimate nesting success without disturbing the colony; 51.2% of nests survived until hatching. The daily survival probability of grebe nests was positively correlated with the aggregation index and water depth at the nest (albeit only slightly). Daily survival probabilities were negatively correlated with distance between the nest and the colony center and distance to deep water (i.e., foraging habitat). The results of this study can be used to inform conservation efforts by identifying areas of the Lake Cascade grebe colony that are most vulnerable to nest failures and formulating explicit management actions that could be implemented to increase nest survival such as changes in timing of water drawdowns and habitat management to ensure habitat suitable for grebe nesting is in close proximity to deep water foraging areas. Moreover, grebes are not the only waterbird that makes use of managed reservoirs; other waterbirds may benefit from the findings of this study to implement more informed management practices.

Idaho↗

USGS2006

Distribution patterns of individually identifiable West Indian manatees ( Trichechus manatus ) in Florida

Photographs of distinctively scarred manatees ( Trichechus manatus ) were taken at aggregation sites throughout Florida and assembled into a catalog for identifying individuals. Resightings of known manatees in different years or at different locations enabled us to document site fidelity and long-distance movements. Of the 891 individuals included in the catalog as of August 1986, 470 (53%) were resighted at least once. We documented 219 cases of seasonal returns to specific aggregation sites and 98 instances of movements between areas. Movements in excess of 820 km were documented for individuals on the east coast of Florida. Rapid movements south during early winter, as well as northerly spring movements, verify a seasonal migration pattern for many individuals along Florida's east coast. The wide-ranging migratory habits of manatees in Florida must be considered if meaningful management strategies are to be developed and implemented.

Florida↗

USGS2014

Lesser prairie-chicken nest site selection, microclimate, and nest survival in association with vegetation response to a grassland restoration program

Climate models predict that the region of the Great Plains Landscape Conservation Cooperative (GPLCC) will experience increased maximum and minimum temperatures, reduced frequency but greater intensity of precipitation events, and earlier springs. These climate changes along with different landscape management techniques may influence the persistence of the lesser prairie-chicken (Tympanuchus pallidicinctus), a candidate for protection under the Endangered Species Act and a priority species under the GPLCC, in positive or negative ways. The objectives of this study were to conduct (1) a literature review of lesser prairie-chicken nesting phenology and ecology, (2) an analysis of thermal aspects of lesser prairie-chicken nest microclimate data, and (3) an analysis of nest site selection, nest survival, and vegetation response to 10 years of tebuthiuron and/or grazing treatments. We found few reports in the literature containing useful data on the nesting phenology of lesser prairie-chickens; therefore, managers must rely on short-term observations and measurements of parameters that provide some predictive insight into climate impacts on nesting ecology. Our field studies showed that prairie-chickens on nests were able to maintain relatively consistent average nest temperature of 31 °C and nest humidities of 56.8 percent whereas average external temperatures (20.3–35.0 °C) and humidities (35.2–74.9 percent) varied widely throughout the 24 hour (hr) cycle. Grazing and herbicide treatments within our experimental areas were designed to be less intensive than in common practice. We determined nest locations by radio-tagging hen lesser prairie-chickens captured at leks, which are display grounds at which male lesser prairie-chickens aggregate and attempt to attract a female for mating. Because nest locations selected by hen lesser prairie-chicken are strongly associated with the lek at which they were captured, we assessed nesting habitat use on the basis of hens captured at individual leks, and then for all leks pooled. There was no clear pattern of selection for treatment type for nest placement among hens associated with individual leks; however, when hens from all leks were pooled, we found nesting lesser prairie-chickens selected control plots for nesting over plots that were grazed, treated with tebuthiuron, or were both grazed and treated with tebuthiuron. Overall, the probability of a nest surviving the incubation period was 0.57 for this study and did not vary significantly among treatment types. In contrast to nesting preference for untreated habitats, lek use exhibited no noticeable selection of treatment type. Over the 10 years of the habitat management study, there was 91 percent less sand shinnery oak (Quercus havardii) in treated areas than untreated areas. The removal of sand shinnery oak made environmental soil moisture more available for grasses and forbs to germinate and grow. Grasses increased by 149 percent and forbs increased by 257 percent in treated areas as compared to untreated areas throughout the study period. Our combined results, including our habitat selection analysis at the individual lek level, indicated that reduced rates of herbicide and short-duration grazing treatments were not detrimental to nesting lesser prairie-chickens and that populations of lesser prairie-chickens in shrub-dominated ecosystems may benefit from reduced rates of herbicide application and short duration of grazing that results in increased habitat heterogeneity.

New Mexico;Texas↗

USGS2025

Public, bottled, and private drinking water: Shared contaminant-mixture exposures and effects challenge

BACKGROUND: Humans are primary drivers of environmental contaminant exposures worldwide, including in drinking-water (DW). In the United States (US), point-of-use DW (POU DW) is supplied via private tapwater (TW, predominantly private wells), public-supply TW, and bottled water (BW). Differences in management, monitoring, and messaging and lack of directly intercomparable exposure data influence the actual and perceived quality and safety of different DW supplies and directly impact consumer decision making. OBJECTIVES: The purpose of this paper is to provide a meta-analysis (quantitative synthesis) of POU DW contaminant mixture exposures and corresponding potential human health effects of private-TW, public-TW, and BW by aggregating exposure results and harmonizing apical health benchmark weighted and bioactivity weighted effects predictions across previous studies by this research group. DISCUSSION: Simultaneous exposures to multiple inorganic and organic contaminants of known or suspected human-health concern are common across all three DW supplies, with substantial variability observed in each and no systematic difference in predicted cumulative risk between supply chains. Differences in contaminant or contaminant class exposures (e.g., trace metals, disinfection byproducts), with important implications for DW quality improvements, were observed and attributed to corresponding differences in regulation and compliance monitoring. CONCLUSION: The results indicate that human-health risks from contaminant exposures are common to and comparable in all three DW supplies, including BW. Importantly, this study’s target analytical coverage, which exceeds that currently feasible for water purveyors or homeowners, nevertheless is a substantial underestimation of the full breadth of contaminant mixtures in the environment and potentially present in DW. Thus, the results emphasize the need for improved understanding of the adverse human-health implications of long-term exposures to low level inorganic /organic contaminant mixtures across all three distribution pipelines and do not support commercial messaging of BW as a systematically safer alternative to public-TW. Regardless of the supply, increased engagement in source-water protection and drinking-water treatment, including consumer point of use treatment, is necessary to reduce risks associated with long-term DW contaminant exposures, especially in vulnerable populations, and to reduce environmental waste and plastics contamination.

Environment International↗

USGS2021

Mineral resource inventory of North Dakota

Aside from construction aggregate materials, the value of nonfuel mineral commodities that have been produced in North Dakota is small, although there is potential for the existence of several mineral resource deposit types which are not economically viable at this time. In this report, we present a mineral resource inventory of the State of North Dakota, developed by the U.S. Geological Survey at the request the Bureau of Land Management. To set the stage for that inventory, we briefly outline the long and complex geologic history of North Dakota that extends back more than 3 billion years. Using several existing databases, we summarize the distribution of known mineral commodities and the results of commodity exploration over time. Using all available data, we discuss the potential for economic occurrences of 13 commodities in North Dakota, including some listed as Critical Minerals.

North Dakota↗

USGS2024

Deposited sediment influences occurrence of functional traits of stream fishes

To better understand stream-fish sensitivity to fine sediment, we documented assemblage-wide responses by selected traits along a sedimentation gradient. We then discuss the management implications of these ‘dose–response’ relations in the contexts of biotic assessments and conservation of sediment-sensitive species. We identified a spatial gradient in sediment deposition among streams within the upper Piedmont of the Roanoke River basin in North Carolina and Virginia. We assessed fine-sediment sensitivity of 81 species based on eight species traits stratified by four attributes: food preference, feeding location, spawning substrate and spawning behaviour. We then ranked each trait and scored each species with respect to its sediment sensitivity. Using data from electrofishing surveys during 2018–2019, we calculated proportional abundances of traits observed at 30 sites throughout the study area and grouped species by their aggregate sensitivity scores. We assessed relations between embeddedness and silt cover and occurrences of species and traits using a combination of regression and ordination approaches. All traits tested responded to embeddedness or silt cover, or both. Feeding traits exhibited the strongest responses to embeddedness, while reproductive traits exhibited the strongest responses to silt cover. Our findings indicate that negative responses of the probability of presence for high-sensitivity traits to embeddedness and silt cover were linear, with no apparent thresholds. Additionally, proportional abundances of species with multiple high-sensitivity traits were inversely related to embeddedness and silt cover. Overall, our findings regarding population-level responses to sedimentation were consistent with our findings for trait-specific responses. Our analysis of species sensitivity to fine sediment corroborated the patterns we saw in our trait-specific analyses, indicating that population responses to sedimentation can be predicted from combinations of species traits. The ‘dose–response’ relations we documented may be applicable to managing sediment impacts on fishes, especially in the contexts of biotic assessments and conservation of sediment-sensitive species.

North Carolina, Virginia↗

USGS2010

A likelihood framework for joint estimation of salmon abundance and migratory timing using telemetric mark-recapture

Many fisheries for Pacific salmon Oncorhynchus spp. are actively managed to meet escapement goal objectives. In fisheries where the demand for surplus production is high, an extensive assessment program is needed to achieve the opposing objectives of allowing adequate escapement and fully exploiting the available surplus. Knowledge of abundance is a critical element of such assessment programs. Abundance estimation using mark—recapture experiments in combination with telemetry has become common in recent years, particularly within Alaskan river systems. Fish are typically captured and marked in the lower river while migrating in aggregations of individuals from multiple populations. Recapture data are obtained using telemetry receivers that are co-located with abundance assessment projects near spawning areas, which provide large sample sizes and information on population-specific mark rates. When recapture data are obtained from multiple populations, unequal mark rates may reflect a violation of the assumption of homogeneous capture probabilities. A common analytical strategy is to test the hypothesis that mark rates are homogeneous and combine all recapture data if the test is not significant. However, mark rates are often low, and a test of homogeneity may lack sufficient power to detect meaningful differences among populations. In addition, differences among mark rates may provide information that could be exploited during parameter estimation. We present a temporally stratified mark—recapture model that permits capture probabilities and migratory timing through the capture area to vary among strata. Abundance information obtained from a subset of populations after the populations have segregated for spawning is jointly modeled with telemetry distribution data by use of a likelihood function. Maximization of the likelihood produces estimates of the abundance and timing of individual populations migrating through the capture area, thus yielding substantially more information than the total abundance estimate provided by the conventional approach. The utility of the model is illustrated with data for coho salmon O. kisutch from the Kasilof River in south-central Alaska.

North American Journal of Fisheries Management↗

USGS2024

State of the data: Assessing the FAIRness of USGS data

In response to recent shifts towards open science that emphasize transparency, reproducibility, and access to research data, the US Geological Survey (USGS) conducted a study to assess the degree to which USGS data assets meet the FAIR data principles (Findable, Accessible, Interoperable, and Reusable). The USGS designed and applied a methodology for quantitative analysis of FAIR characteristics. A new rubric was derived from a crosswalk of existing FAIR evaluation frameworks and customized for the USGS. The rubric, consisting of 62 yes/no questions, was applied to 392 metadata records of USGS data products published between 1987 and 2022. Results were analyzed to show which FAIR characteristics were most and least present in the metadata and how these scores changed after the implementation of data policy requirements in 2016. Aggregated scores showed specific areas of strength and needed improvements. The greatest increases in FAIR scores over time were for elements that were required by new data policies, especially in the ‘Findable’ category. Based on the results, this paper presents strategies to further improve USGS alignment with FAIR. The suggested strategies are organized in four key areas: USGS data repository characteristics, training and communities of practice, data management policy considerations, and metadata standards, tools, and best practices.

Data Science Journal↗