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At least 631 records · Page 35Linked to original sources
USGS2018

Refining aging criteria for northern sea otters in Washington State

Measurement of skull ossification patterns is a standard method for aging various mammalian species and has been used to age sea otters Enhydra lutris from Russia, California, and Alaska. Cementum annuli counts have also been verified as an accurate aging method for sea otters in Alaska. In this study, we compared cementum annuli count results and skull ossification patterns as methods for aging the northern sea otter, E. l. kenyoni, in Washington State. We found significant agreement between the two methods, suggesting that either method could be used to age sea otters in Washington. We found that ossification of the squamosal–jugal suture at the ventral glenoid fossa can be used to differentiate male subadults from adults. To assist field biologists or others without access to cementum annuli or skull ossification analysis techniques, we analyzed a suite of morphologic, physiologic, and developmental characteristics to assess whether a set of these more easily accessible parameters could also predict age class. We identified tooth condition score, evidence of reproductive activity in females, and tooth eruption pattern as the most useful criteria for classifying sea otters in Washington. We created a simple decision tree based on characteristics accessible in the field or at necropsy, which can be used to reliably predict age class of Washington sea otters as determined by cementum annuli. These techniques offer field biologists and marine mammal stranding networks a replicable, cost-conscious methodology to gather useful biological information from sea otters.

Washington↗
USGS1983

Evaluating environmental and economic consequences of alternative pest management strategies: results of modeling workshops

The U.S. Environmental Protection Agency (EPA) needs a comprehensive method to evaluate the human health and environmental effects of alternative agricultural pest management strategies. This project explored the utility of Adaptive Environmental Assessment (AEA) techniques for meeting this need. The project objectives were to produce models for environmental impact analysis, improve communications, identify research needs and data requirements, and demonstrate a process for resolving conflicts. The project was structured around the construction (in an initial 2 1/2-day workshop) and examination (in a second 2 1/2-day workshop) of a simulation model of a corn agroecosystem. The model conceptualized at the first workshop simulates the effect of corn agrecosystem decisions on crop production, economic returns, and environmental indicators. The model is composed of five interacting submodels: 1) a Production Strategies submodel which makes decisions concerning tillage, planting, fertilizer and pesticide applications, and harvest; 2) a Hydrology/Chemical Transport submodel which represents soil hydrology, erosion, and concentrations of fertilizers and pesticides in the soil, runoff, surface waters, and percolation; 3) a Vegetation submodel which simulates growth of agricultural crops (corns and soybeans) and weeds; 4) a Pests submodel which calculates pest population levels and resulting crop damage; and 5) an Environmental Effects submodel which calculates indicators of potential fish kills, human health effects, and wildlife habitat. The most persistent data gaps encountered in quantifying the model were coefficients to relate environmental consequences to alternative pest management strategies. While the model developed in the project is not yet accurate enough to be used for real-world decisions about the use of pesticides on corn, it does contain the basic structure upon which such a model could be built. More importantly at this stage of development, the project has shown that very complex systems can be modeled in short periods of time and that the process of building such models increases understanding among disciplinary specialists and between diverse institutional interests. This process can be useful to EPA as the agency cooperates with other institutions to meet its responsibilities in less costly ways. Activities at the second 2 1/2-day workshop included a review of the model, incorporation of necessary corrections, simulation of policy scenarios, and examination of techniques to address remaining institutional conflicts. Participants were divided into three groups representing environmental, production or industry, and regulatory interests. Each group developed scenarios that would be most appealing to their particular interest and the scenarios were simulated by the agroecosystem computer model. Negotiators from each of the interest groups decided whether a hypothetical herbicide should be relabeled and if certain restrictions should be imposed on its use. Other participants functioned as experts and consultants on caucus teams. A solution to the hypothetical problem was successfully negotiated. Workshop participants and project staff agreed that the model and processes developed during the project should be used in training students, extension specialists, farmers, researchers, and chemical producers in collaborative problem solving methods. More productive research can be planned, and more realistic models of complex systems can be built in this way. More importantly, greater trust of decisionmakers in computer models, better understanding by technical experts about disciplines other than their own, and improved cooperation between institutional interests can be achieved. This trust, understanding, and cooperation are critical ingredients in solving problems that are too complex to be resolved by independent disciplinary activity and unilateral decision authority.

Report↗
USGS2022

Conflict of energies: Spatially modeling mule deer caloric expenditure in response to oil and gas development

Context Wildlife avoid human disturbances, including roads and development. Avoidance and displacement of wildlife into less suitable habitat due to human development can affect their energy expenditures and fitness. The heart rate and oxygen uptake of large mammals varies with both natural aspects of their habitat (terrain, climate, predators, etc.) and anthropogenic influence (noise, light, fragmentation, etc.). Although incorporating physiological analyses of energetics can inform the impacts of both development and conservation, management decisions rarely incorporate individuals’ energetic requirements when deciding on locations for potential development. Objectives We aimed to estimate the change in expected energy expenditure, numerically and spatially, for mule deer to traverse a landscape with varying levels of oil and gas development through time. Methods Using calculations of energy expenditure of mule deer ( Odocoileus hemionus ) by weight, in relation to physical terrain components, plus avoidance factors for anthropogenic disturbance, we developed a spatiotemporal model of the minimum energy required for mule deer to traverse a landscape. We compared expected energy expenditure across 12 study sites with increasing levels of oil and gas development and over time in our study area, on the northern Colorado Plateau of Utah. Results We found that energy expenditure can be increased by development, regardless of terrain, through increased travel distance associated with avoidance behavior. Maximum median energy expenditure to traverse a 1400 ha sample area rose from 1135 to 1935 kilocalories, a 70% increase in energy required of a mule deer. There was a significant relationship between energy expenditure and the size of oil and gas development (p < 0.001), its compactness (p < 0.05), and its ‘thinness’ (p < 0.001), but not terrain ruggedness (p = 0.25). Conclusion As the energy costs of movement correlate across multiple species of large mammals, our analysis of the energetic cost, for mule deer, associated with development can serve as a quantitative representative of the impacts of oil and gas development for multiple mammals—including threatened or endangered species. Our bioenergetic cost-distance model provides a means of delineating impediments to efficient movement and can be used to quantify the expected energetic costs of proposed future developments. As wildlife are exposed to increasing anthropogenic stressors which reduce fitness, it is important to make strategic siting decisions to reduce energetic costs imposed by human activities.

Utah↗
USGS2022

The Hawai'i groundwater recharge tool

This article discusses the design and implementation of the Hawai’i Groundwater Recharge Tool, an application for providing data and analyses of the impacts of land-cover modifications and changes in precipitation on groundwater-recharge rates for the island of O’ahu. This application uses simulation data based on a set of 29 land-cover types and 2 precipitation conditions to provide users with real-time recharge calculations for interactively defined land-cover modifications. The tool provides two visualizations, representing the land cover for the island and the resultant groundwater-recharge rates, and a set of metrics indicating the changes to groundwater recharge for relevant areas to present a set of easily interpretable outcomes based on user-defined scenarios. Users have varying degrees of control over the granularity of data input and output, allowing for the quick production of a roughly defined scenario, or more precise land-cover definitions. These modifications can be exported for further analysis. Heuristics are used to provide a responsive user interface and performant integration with the database containing the full set of simulation data. This tool is designed to provide user-friendly access to the information on the impacts of land-cover and precipitation changes on groundwater-recharge rates needed to assist in making data-driven decisions.

Hawai'i↗
USGS2015

Terrain parameters of glide snow avalanches and a simple spatial glide snow avalanche model

Glide snow avalanches are dangerous and difficult to predict. Despite substantial recent research there is still inadequate understanding regarding the controls of glide snow avalanche release. Glide snow avalanches often occur in similar terrain or the same locations annually, and repeat observations and prior work suggest that specific topography may be critical. Thus, to gain a better understanding of the terrain component of these types of avalanches we examined terrain parameters associated with the specific area of glide snow avalanche release in comparison to avalanche starting zones where no glide snow avalanches were observed (i.e. non-glide snow avalanche terrain). Glide snow avalanche occurrences visible from the Going-to-the-Sun Road corridor in Glacier National Park, Montana from 2003 to 2013 are investigated using a database of all avalanche occurrences derived of daily observations each year from 1 April to 1 June. This yielded 192 glide snow avalanches in 53 distinct avalanche paths. Each avalanche was digitized in a GIS using satellite, oblique, and aerial imagery as reference. A set of 117 non-glide snow avalanche starting zones were also selected in this manner. These were start zones with avalanche activity potential, but without glide avalanches observed. Topographical parameters such as area, slope, aspect, curvature, potential incoming solar radiation, distance from ridge, and elevation were then derived for the entire dataset utilizing tools with a GIS and a 10 m DEM. Ground class and a glide factor were calculated using a four level classification index with in-situ observations and a land surface type layer in a GIS. A total of 21 terrain variables were examined using a univariate analysis between areas where glide snow avalanches occurred and areas where glide snow avalanches were never observed, despite crack formation. Only two variables were not significantly different. The significantly different variables were then used to train a classification tree to distinguish between glide and non-glide snow avalanche terrain. A 10-fold cross validated tree resulted in four decision nodes to classify the data. The nodes split on glide factor, maximum slope angle, seasonal sum of incoming solar radiation, and maximum curvature to distinguish between glide snow avalanche and non-glide snow avalanche terrain with an unweighted average accuracy (RPC) of 0.95 and probability of detection of events (POD) of 0.99. Finally, the results of the cross-validated tree were used in a GIS to examine other areas, not used in the training dataset of the classification tree, of potential glide snow avalanche release within Glacier National Park. Using this understanding of the role of topographic parameters on glide snow avalanche activity, a spatial terrain based model was developed to identify other areas with high glide snow avalanche potential outside of the immediate observation area. This simple spatial model correctly classified 78 percent of actual glide snow avalanche terrain (pixel count) of a small test area of four independent observed glide snow avalanches.

Montana↗
USGS2017

Coupling ecological and social network models to assess “transmission” and “contagion” of an aquatic invasive species

Network analysis is used to address diverse ecological, social, economic, and epidemiological questions, but few efforts have been made to combine these field-specific analyses into interdisciplinary approaches that effectively address how complex systems are interdependent and connected to one another. Identifying and understanding these cross-boundary connections improves natural resource management and promotes proactive, rather than reactive, decisions. This research had two main objectives; first, adapt the framework and approach of infectious disease network modeling so that it may be applied to the socio-ecological problem of spreading aquatic invasive species, and second, use this new coupled model to simulate the spread of the invasive Chinese mystery snail ( Bellamya chinensis ) in a reservoir network in Southeastern Nebraska, USA. The coupled model integrates an existing social network model of how anglers move on the landscape with new reservoir-specific ecological network models. This approach allowed us to identify 1) how angler movement among reservoirs aids in the spread of B . chinensis , 2) how B . chinensis alters energy flows within individual-reservoir food webs, and 3) a new method for assessing the spread of any number of non-native or invasive species within complex, social-ecological systems.

Journal of Environmental Management↗
USGS2024

Analysis and review of fishery-dependent data for Hawaiian nearshore noncommercial fisheries

Noncommercial, shore-based fisheries provide economic, social, and cultural services to communities throughout the Hawaiian Islands. The State of Hawai‘i Department of Land and Natural Resources (DLNR), Division of Aquatic Resources (DAR) routinely conducts surveys to monitor noncommercial fisheries such that estimates of fishing effort and catch by gear type can be generated and used to implement more sustainable management practices. DAR executes both the Hawai‘i Marine Recreational Fishery Survey (HMRFS), a nationally standardized survey that focuses on intercepting fishers at access points (i.e., boat ramps) across the main Hawaiian Islands, and a set of roving creel surveys on O‘ahu, Maui Nui, and Kaua‘i that observe and intercept fishers at locations along the shoreline outside of those targeted by HMRFS. The latter set of creel surveys were designed to complement HMRFS by expanding its geographic coverage and thus providing a more representative picture of noncommercial fishing in Hawai‘i. Sustainable management priorities set by DAR rely on the availability of statewide, fishery- dependent data. Thus, we collate information from island-based roving creel surveys into a cohesive Statewide Creel Survey Database. Further, we provide preliminary analyses and describe ways that surveys could be streamlined to improve future data collection, analysis, and utility. In so doing, we synthesize the most detailed information to-date about noncommercial shore-based fisheries of Hawai‘i. The unprecedented spatial and temporal coverage of DAR’s dataset reveals the value of their survey efforts over the last decade to address fishery management needs. Our primary objectives, results, and conclusions are summarized below: 1) Integrate DAR roving creel survey data from different islands into a single Statewide Creel Survey Dataset (Chapter II). We describe the collation of creel survey data from O‘ahu, Maui Nui, and Kaua‘i into a statewide dataset. We also offer ways in which these surveys could be streamlined to meet the needs of managers and decision makers. Briefly, these are to create a statewide strategic plan, standardize the execution of standard operating procedures, centralize the creel survey database and associated metadata, and consider using technology that improves the data pipeline, including transitioning from paper-based to electronic systems for data entry and processing. 2) Assess whether the new Statewide Creel Survey Dataset can provide inputs for length-based stock assessments (Chapter III). Only on Maui were interviews conducted with associated catch data. There was reasonably high taxonomic coverage (42 species from 186 interviews with 310 fishers), but low sample sizes for nearly all species precluded the development of length-based stock assessments. We provide summary statistics from the existing data and briefly discuss how technologies could be used to automate analysis of images of noncommercial catch. 3) Analyze the Statewide Creel Survey Dataset for spatial and temporal patterns in fishing effort (Chapter IV): a. Visualizing noncommercial fishing pressure . We found that fishing effort (mean number of fishers observed per survey event at a site) on O'ahu was over three times greater than that recorded during similar surveys conducted on Maui or Kaua'i. We create maps that display the distribution of angling and spearfishing effort around each of the three islands. b. Factors that predict fishing “hotspots” around Maui . Fishing effort on Maui was associated with areas with more wave power and less parking availability. There were half as many fishers in areas with parking lots than in areas with parking on the road shoulder only. c. Changes in fishing effort during the COVID-19 pandemic . There was no change in fishing effort on O‘ahu during the first year of the pandemic, but there was a 20% decline in year 2 and a 33% decline in year 3, both in comparison to pre-pandemic levels. Pre-pandemic creel survey data were unavailable for Maui and Kaua‘i, but fishing effort on these islands also declined as the pandemic progressed at similar or greater rates than those observed on O‘ahu. 4) Quantify potential bias in survey methods by experimentally deriving fisher detection probabilities of shore-based and drone-based surveys (Chapter V): a. Shore-based surveys . We conducted roving creel surveys for four months at three locations around Hilo Bay, designed to emulate and estimate the efficacy of DAR standard operating procedures. There was high agreement between paired observers in counting fishers, leading to near-perfect detection probabilities of both anglers (94%) and spearfishers (97%), but relatively low agreement and detection probabilities of other fishers (throw net, ‘opihi picking, etc.) (52%). b. Drone-based surveys . We used an unmanned aerial vehicle (UAV; operated by DAR staff) to collect imagery of fishers along the Hilo Bay shoreline. We used still images and video clips (with known fishing activity) to build an online survey that was distributed to DAR and HCFRU personnel, asking them to count and categorize resource users as a snorkeler, spearfisher, angler, or other fisher. Only 40.0% of the responses correctly counted and categorized resource users in the image. Anglers were correctly identified and enumerated in 90.0% of the responses, but the correct response rates of the other three user categories ranged from 67.8% – 79.4%. Snorkelers and anglers tended to be undercounted while spearfishers and other fishers were overcounted. 5) Review the potential for incorporating emerging technologies that will improve, augment, and evolve creel survey data collection, especially for spearfishing (Chapter VI). Within the context of monitoring shore-based noncommercial fishing, we review the use of electronic data entry/processing systems with geospatial and image capabilities, field cameras, drones, smart buoys, citizen science apps, data mining social media, artificial intelligence and machine learning. We highlight several of the challenges and considerations when implementing these technologies into creel surveys and provide a synthesis of options that could be used to better estimate spearfishing. The general conclusion of this assessment is that the DAR roving creel survey program is collecting valuable data that supplement the existing HMRFS efforts. However, there are a number of areas that could be improved to make these efforts a more effective tool for decision-making processes in resource management and conservation: 1) Establishment of clear statewide and island objectives for the Statewide Creel Survey Dataset. Currently, data collection efforts are focused towards addressing a very broad purpose – supplementing the HMRFS data collection efforts. However, the results of the preliminary analyses conducted as part of this project suggest that the data could be used to address other areas of need if these objectives were clearly defined. Further, the design of the creel survey would benefit from greater standardization of survey protocols between islands and an effort to define a) the acceptable margins of error associated with the estimates generated by these data and b) the minimum level of change that the surveys would need to detect to be useful to managers. 2) Centralization of data entry, data quality assessment, and data accessibility. Currently, each DAR office manages data entry, checks the data for errors, and is responsible for managing and storing the data. Instituting a centralized data entry system, particularly an online database that can receive survey data from tablets or smartphones running a standardized data collection application would improve efficiency, reduce data entry errors, and accelerate the availability of data to managers. A substantial amount of time and effort from the project described in this report was devoted to checking the dataset for errors. The development and application of data quality assurance protocols would ensure that the data are reliable and available in a timely fashion to support management decisions. 3) Address lingering questions regarding the efficacy of current survey protocols to capture and characterize the spearfishing component of the noncommercial fishery. The results presented in the report suggest that the current creel survey protocols do a good job detecting spearfishers when present but are not capturing sufficient data about their catch or total effort. There are also questions remaining as to whether the survey times and sites are sufficiently capturing the behavior of spearfishers in Hawai‘i. A more thorough assessment – whether through additional research, alteration of survey design, or review of data by representatives of the spearfishing community – would provide insight on how to use the Statewide Creel Survey Database to inform management of spearfishing. 4) Investigate the integration of technological advancements into the creel survey methods. As priorities and needs are developed and formalized, it would be valuable to consider how various technological advancements might enhance and streamline data collection or open new avenues of inquiry.

Hawaii↗
USGS2023

Incorporating uncertainty in susceptibility criteria into probabilistic liquefaction hazard analysis

Most conventional approaches for assessing liquefaction triggering hazards generally rely on simplified procedures that involve identifying liquefaction susceptible layers and calculating a factor of safety against liquefaction (FSL) in each layer. Such procedures utilize deterministic semi-empirical models for standard penetration test (SPT), cone penetrometer test (CPT), or shear wave velocity (Vs)-based subsurface data. This general approach largely neglects considerable uncertainties in ground shaking, as well as aleatory variabilities and epistemic uncertainties inherent to liquefaction susceptibility and triggering prediction. A more robust methodology introduced by Kramer and Mayfield (2007) is known as probabilistic liquefaction hazard analysis (PLHA), which integrates the full ground motion hazard space with probabilistic forms of liquefaction triggering models (e.g., Boulanger and Idriss 2014), resulting in the computation of FSL profiles with consistent return periods. Multiple PLHA computational platforms have been developed over the years, with the computational framework from Makdisi (2021) serving as the basis for a new Liquefaction Hazard Tool under development at the U.S. Geologic Survey (USGS). Despite significant improvements in recent years to the availability of seismic hazard data and probabilistic triggering and effects models, the issue of incorporating uncertainty in characterizing liquefaction susceptibility remains a challenge. Most compositional susceptibility criteria (i.e., whether or not the soil exhibits sand-like behavior) currently in use are presented as deterministic bounds based on in-situ or laboratory test data; similarly, determination of soil saturation is often based on a single groundwater level from in-situ testing. As a result, the same types of binary decisions must be made in PLHA as in more conventional methods. With the expansion and availability of field and laboratory data pertaining to liquefaction through resources such as the Next Generation Liquefaction (NGL) project, there exists the potential for an improved set of susceptibility models for CPT, SPT, and Vs-based applications. Presented here is a brief discussion on how probabilistic susceptibility modeling can be accommodated in PLHA calculations, as well as how the use of multiple models can be leveraged within a logic tree to improve the representation of epistemic uncertainty in liquefaction hazard analysis.

Conference Paper↗
USGS2013

Detection of tamarisk defoliation by the northern tamarisk beetle based on multitemporal Landsat 5 thematic mapper imagery.

The spread of tamarisk ( Tamarix spp., also known as saltcedar) is a significant ecological disturbance in western North America and has long been targeted for control, leading to the importation of the northern tamarisk beetle ( Diorhabda carinulata ) as a biological control agent. Following its initial release along the Colorado River near Moab, Utah in 2004, the beetle has successfully established and defoliated tamarisk across much of the upper Colorado River Basin. However, the spatial distribution and seasonal timing of defoliation are complex and difficult to quantify over large areas. To address this challenge, we tested and compared two remote sensing approaches to mapping tamarisk defoliation: Disturbance Index (DI) and a decision tree method called Random Forest (RF). Based on multitemporal Landsat 5 TM imagery for 2006-2010, changes in DI and defoliation probability from RF were calculated to detect tamarisk defoliation along the banks of Green, Colorado, Dolores and San Juan rivers within the Colorado Plateau area. Defoliation mapping accuracy was assessed based on field surveys partitioned into 10 km sections of river and on regions of interest created for continuous riparian vegetation. The DI method detected 3711 ha of defoliated area in 2007, 7350 ha in 2008, 10,457 ha in 2009 and 5898 ha in 2010. The RF method detected much smaller areas of defoliation but proved to have higher accuracy, as demonstrated by accuracy assessment and sensitivity analysis, with 784 ha in 2007, 960 ha in 2008, 934 ha in 2009, and 1008 ha in 2010. Results indicate that remote sensing approaches are likely to be useful for studying spatiotemporal patterns of tamarisk defoliation as the tamarisk leaf beetle spreads throughout the western United States.

Arizona, Colorado, New Mexico, Utah, Wyoming↗
USGS2012

Guidelines for a graph-theoretic implementation of structural equation modeling

Structural equation modeling (SEM) is increasingly being chosen by researchers as a framework for gaining scientific insights from the quantitative analyses of data. New ideas and methods emerging from the study of causality, influences from the field of graphical modeling, and advances in statistics are expanding the rigor, capability, and even purpose of SEM. Guidelines for implementing the expanded capabilities of SEM are currently lacking. In this paper we describe new developments in SEM that we believe constitute a third-generation of the methodology. Most characteristic of this new approach is the generalization of the structural equation model as a causal graph. In this generalization, analyses are based on graph theoretic principles rather than analyses of matrices. Also, new devices such as metamodels and causal diagrams, as well as an increased emphasis on queries and probabilistic reasoning, are now included. Estimation under a graph theory framework permits the use of Bayesian or likelihood methods. The guidelines presented start from a declaration of the goals of the analysis. We then discuss how theory frames the modeling process, requirements for causal interpretation, model specification choices, selection of estimation method, model evaluation options, and use of queries, both to summarize retrospective results and for prospective analyses. The illustrative example presented involves monitoring data from wetlands on Mount Desert Island, home of Acadia National Park. Our presentation walks through the decision process involved in developing and evaluating models, as well as drawing inferences from the resulting prediction equations. In addition to evaluating hypotheses about the connections between human activities and biotic responses, we illustrate how the structural equation (SE) model can be queried to understand how interventions might take advantage of an environmental threshold to limit Typha invasions. The guidelines presented provide for an updated definition of the SEM process that subsumes the historical matrix approach under a graph-theory implementation. The implementation is also designed to permit complex specifications and to be compatible with various estimation methods. Finally, they are meant to foster the use of probabilistic reasoning in both retrospective and prospective considerations of the quantitative implications of the results.

Ecosphere↗
USGS2023

Guide for benthic invertebrate studies in support of Natural Resource Damage Assessment and Restoration

This guide is intended to assist with characterizing injury to freshwater benthic macroinvertebrates (BMIs) in Natural Resource Damage Assessment and Restoration (NRDAR) cases. The contents are narrowly focused on insects, crustaceans, snails, and other invertebrate fauna that are typically considered part of BMI communities and are not intended to address studies of injury to larger benthic taxa such as freshwater mussels, crayfish, or benthic fishes or amphibians. Although some percentage of the community functions as predators, BMIs are predominantly primary consumers (for example, scrapers, shredders, and filterer/gatherer feeding groups) that play an essential role in converting carbon and nitrogen from plant tissues into animal biomass for higher-order consumers, especially in flowing waters. Aquatic contaminants can disrupt the quantity and quality of energy transferred (ecosystem function) by reducing invertebrate biomass and diversity. Additionally, the accumulation of toxic residues in invertebrate tissues may be a source of exposure leading to adverse effects in higher trophic levels. The goal of NRDAR BMI assessments is to establish direct linkages of contaminant exposure to injuries reflected by changes in community structure (for example, reduced density and taxa richness) or by effects at the individual population level (for example, survival, growth, and reproduction). BMIs are infrequently the U.S. Department of Interior (DOI)-managed resource in a NRDAR case, with managed resources more frequently including migratory birds, fish, or other insectivorous vertebrates. Therefore, it is critical to have clearly defined objectives for evaluating BMIs and an understanding of how invertebrate data relate to the quantification of injuries to the DOI-managed resource. This guide is intended to assist decisions on whether or not to proceed with BMI studies, use of existing information and data for screening purposes, and what types of studies can support a BMI-injury determination. This document is intended to provide general considerations and best practices for assessing BMIs. Relevant guidance and references are listed throughout the report as sources for specific methods and analysis.

Open-File Report↗
USGS2020

Analysis of aquifer framework and hydraulic properties of Lovelock Valley, Lovelock, Nevada

Multiple aquifer tests were conducted in Lovelock, Nevada, to determine hydraulic conductivity and storage properties to be used with the numerical groundwater flow model of the lower Humboldt River Basin while accounting for the influence of surface features with a modeling component. The numerical model will ultimately provide the Nevada Division of Water Resources (NDWR) with information regarding the impacts of groundwater pumping on the Humboldt River, allowing the Nevada State Engineer to make informed decisions in the conjunctive management of the State’s groundwater and surface water resources. Seven slug tests, one single-well pumping test, and two multi-well pumping tests were conducted to evaluate properties of shallow Lahontan clays and silts; shallow fluvial deposits; and coarser, water-bearing deposits of the younger alluvium. Aquifer tests were conducted between March 2017 and April 2018. Results indicate aquifers in the Lovelock Valley have transmissivity ranging between 0.0001 and 95,000 feet squared per day (ft 2 /day). The results of these tests provide constraints on hydraulic properties for a numerical groundwater flow model being developed for a capture study in the lower Humboldt River Basin.

Nevada↗
USGS2025

Climate consideration in environmental effects analyses on federal public lands in the United States

Effects of a changing climate, including drought, wildfire, and invasive species encroachment, are evident on public lands across the United States. Decision making on Federal public lands requires analyses under the National Environmental Policy Act (NEPA), and there are guidelines for considering climate in NEPA analyses. To better understand how climate most recently has been considered, we analyzed a stratified random sample of 130 environmental assessments (EAs) completed by the Bureau of Land Management (BLM) from 2021 to 2023 across the contiguous United States. We assessed whether EAs considered (1) potential effects of the proposed action on climate (2) potential climate effects on the proposed action, and (3) potential climate effects on resources of concern. We also identified whether EAs included data and science about climate or greenhouse gas emissions, and which datasets and documents were cited. We used two approaches: automated keyword searches and document analysis. Thirty-seven percent of EAs considered the potential effects of the proposed action on climate, 8% considered the potential effects of climate on the proposed action, and 4% of individual resource analyses considered the potential effects of climate on the resource. EAs in the ‘oil and gas development,’ ‘renewable energy,’ and ‘forestry and timber management’ proposed action categories most frequently considered the potential effects of climate and used climate data and science. Our findings suggest an opportunity for scientists to work more closely with public land managers to identify available data and science for considering climate in environmental effects analyses and to provide science delivery mechanisms that can facilitate the consideration and use of climate science in decision making.

Environmental Management↗
USGS2023

Identifying demographic and environmental drivers of population dynamics and viability in an endangered top predator using an integrated model

Knowledge about the demographic and environmental factors underlying population dynamics is fundamental to designing effective conservation measures to recover depleted wildlife populations. However, sparse monitoring data or persistent knowledge gaps about threats make it difficult to identify the drivers of population dynamics. In situations where small, declining, or depleted populations show continued evidence of decline for unknown reasons, integrated population models can make efficient use of available data to improve our understanding of demography, provide fundamental insights into factors that may be limiting recovery, and support conservation decisions. We used mark-resight and aerial survey data from 2004 to 2018 to build a Bayesian integrated population model for the Cook Inlet population of beluga whales ( Delphinapterus leucas ), which is listed as endangered under the U.S. Endangered Species Act. We examined the effects of prey availability and oceanographic conditions on beluga vital rates and conducted a population viability analysis to predict extinction risk across a range of hypothetical changes in beluga survival and reproduction. Our results indicated that while the survival of breeding females (0.97; 95% CI: 0.95–0.99) and young calves (0.92; 0.80–0.98) was relatively high, the survival of nonbreeders (0.94; 0.91–0.97) and fecundity (0.28; 0.22–0.36) may be depressed. Furthermore, our analysis indicates that the population will likely continue to decline, with a 17–32% probability of extinction in 150 years. Our model highlights the utility of integrated population modeling for maximizing the usefulness of available data and identifying factors contributing to the failure of protected populations to recover. This framework can be used to evaluate proposed conservation and recovery efforts for this and other endangered species.

Animal Conservation↗
USGS2014

Operational earthquake forecasting can enhance earthquake preparedness

We cannot yet predict large earthquakes in the short term with much reliability and skill, but the strong clustering exhibited in seismic sequences tells us that earthquake probabilities are not constant in time; they generally rise and fall over periods of days to years in correlation with nearby seismic activity. Operational earthquake forecasting (OEF) is the dissemination of authoritative information about these time‐dependent probabilities to help communities prepare for potentially destructive earthquakes. The goal of OEF is to inform the decisions that people and organizations must continually make to mitigate seismic risk and prepare for potentially destructive earthquakes on time scales from days to decades. To fulfill this role, OEF must provide a complete description of the seismic hazard—ground‐motion exceedance probabilities as well as short‐term rupture probabilities—in concert with the long‐term forecasts of probabilistic seismic‐hazard analysis (PSHA).

Seismological Research Letters↗
USGS2018

A statement of common ground regarding the role of wildfire in forested landscapes of the western United States

For millennia, wildfires have markedly influenced forests and non-forested landscapes of the western United States (US), and they are increasingly seen as having substantial impacts on society and nature. There is growing concern over what kinds and amounts of fire will achieve desirable outcomes and limit harmful effects on people and nature. Moreover, the increasing complexity surrounding cost and management of wildfires suggests that science should play a more prominent role in informing decisions about the need for fire in nature, and the need for society to adapt to the inevitable occurrence of different kinds and amounts of fire and smoke. Scientists widely view the natural wildfire regime as essential to western US forest ecosystem functioning. However, debates continue over how much low-, moderate-, and high severity fire is “natural” or desirable in these forests. Ongoing disagreement centers on the characteristics and importance of historical proportions and patch size distributions of low-, moderate-, and high-severity fires of dry, moist, and cold forests, and on the ecological consequences of changing fire-patch patterns and relative abundances. Scientists also debate the relative importance of climate and extreme weather versus fuel as drivers of high-severity fire, as well as the effectiveness and value of fuel treatments for reducing risks of undesired fire effects. Climate research shows that we should expect shifting future climates in all ecoregions. These expected changes make it difficult for scientists, land managers, and decision-makers to know the degree to which future forest management should be informed by historical conditions. There also is disagreement about how to make western forests more resilient to future disruptions in both climatic and fire regimes. To complicate matters, areas of scientific agreement -- the “common ground” shared by those in the research community -- are poorly articulated. Thus, the focus of the Fire Research Consensus (FRC) project has been to identify common ground among scientists, and provide a summary that can inform management. Land and fire managers are one audience for this report, as are stakeholders and the interested public. Our analysis, which results from extensive scientific literature reviews and questionnaires sent to western fire scientists and land managers, is summarized in nine key topics: A. Fire history and fire ecology vary with geography. B. Human impacts and management history vary with geography. C. Fire is a keystone process, which occurs in almost all western US forest types. D. Knowledge of historical range of variability (HRV) is useful but does not dictate land management goals. E. Forest structure, composition, and fuels have changed, affecting burn severity and fire extent. F. Climate and fuels both influence current fire sizes and their severities. G. The role of changing climatic conditions is increasingly important. H. Multiple fire ecology and fire history research approaches can be useful for characterizing fire regimes. I. Many existing fire management tools and strategies can be useful moving forward. We found much common ground that will be useful to scientists, managers, citizens, and policy decision-makers. For example, there is wide agreement among scientists that fire is one of the most essential influences on western forests and that more fire is needed on most landscapes, but not all wildfire behavior or extent will do. Fires can produce more positive benefits and fewer negative impacts when they burn with an ecologically appropriate mix and pattern of low, moderate, and high severity. Managers will need assistance and funding to create landscape conditions that favor more desirable fire behavior at broad spatial scales. Note that much societal impact from western wildfires occurs in non-forested landscapes that are not covered in this report, where findings would differ from those reported here for forested landscapes. We summarize additional key points below.

Western United States↗
USGS2020

Expert-informed habitat suitability analysis for at-risk species assessment and conservation planning

The U.S. Fish and Wildlife Service (USFWS) is responsible for reviewing the biological status of hundreds of species to determine federal status designations under the Endangered Species Act. The longleaf pine Pinus palustris ecological system supports many priority at-risk species designated for review, including five species of herpetofauna: gopher tortoise Gopherus polyphemus , southern hognose snake Heterodon simus , Florida pine snake Pituophis melanoleucus mugitus , gopher frog Lithobates ( Rana ) capito , and striped newt Notophthalmus perstriatus . To inform status decisions and conservation planning, we developed habitat suitability models to 1) identify habitat features that best predict species presence and 2) estimate the amount and distribution of suitable habitat across each species' range under current conditions. We incorporated expert judgment from federal, state, and other partners to capture variation in ecological settings across species' ranges, prioritize predictor variables to test in models, mitigate data limitations by informing the selection of pseudoabsence points, qualitatively evaluate model estimates, and improve the likelihood that experts will trust and use model predictions for conservation. Soil characteristics, land cover, and fire interval strongly influenced habitat suitability for all species. Suitable habitat was distributed on known species strongholds, as well as private lands without known species records. Between 4.7% (gopher frog) and 14.6% (gopher tortoise) of the area in a species' range was classified as suitable habitat, and between 28.1% (southern hognose snake) and 47.5% (gopher frog) of suitable habitat was located in patches larger than 1 km 2 (100 ha) on publicly owned lands. By overlaying predictions for each species, we identified areas of suitable habitat for multiple species on protected and unprotected lands. These results have direct applications to management and conservation planning: partners can tailor site-level management based on attributes associated with high habitat suitability for species of concern; allocate survey effort in areas with suitable habitat but no known species records; and identify priority areas for management, land acquisitions, or other strategies based on the distribution of species records, suitable habitat, and land protection status. These results can aid regional partners in implementing effective conservation strategies and inform status designation decisions of the USFWS.

Alabama, Florida, Georgia, Louisiana, Mississippi,↗
USGS2010

Using airborne geophysical surveys to improve groundwater resource management models

Increasingly, groundwater management requires more accurate hydrogeologic frameworks for groundwater models. These complex issues have created the demand for innovative approaches to data collection. In complicated terrains, groundwater modelers benefit from continuous high‐resolution geologic maps and their related hydrogeologic‐parameter estimates. The USGS and its partners have collaborated to use airborne geophysical surveys for near‐continuous coverage of areas of the North Platte River valley in western Nebraska. The survey objectives were to map the aquifers and bedrock topography of the area to help improve the understanding of groundwater‐surface‐water relationships, leading to improved water management decisions. Frequency‐domain heliborne electromagnetic surveys were completed, using a unique survey design to collect resistivity data that can be related to lithologic information to refine groundwater model inputs. To render the geophysical data useful to multidimensional groundwater models, numerical inversion is necessary to convert the measured data into a depth‐dependent subsurface resistivity model. This inverted model, in conjunction with sensitivity analysis, geological ground truth (boreholes and surface geology maps), and geological interpretation, is used to characterize hydrogeologic features. Interpreted two‐ and three‐dimensional data coverage provides the groundwater modeler with a high‐resolution hydrogeologic framework and a quantitative estimate of framework uncertainty. This method of creating hydrogeologic frameworks improved the understanding of flow path orientation by redefining the location of the paleochannels and associated bedrock highs. The improved models reflect actual hydrogeology at a level of accuracy not achievable using previous data sets.

Conference Paper↗