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At least 703 records · Page 39Linked to original sources
USGS2020

Relation of fish intersex to contaminants in riverine sport fishes

Endocrine active compounds (EACs) are pollutants that have been recognized as an emerging and widespread threat to aquatic ecosystems globally. Intersex, the presence of female germ cells within a predominantly male gonad, is considered a biomarker of endocrine disruption caused by EACs. We measured a suite of EACs and assessed their associated impacts on fish intersex occurrence and severity in a large, regulated river system in North Carolina and South Carolina, USA. Our specific objective was to determine the relationship of contaminants in water, sediment, and fish tissue with the occurrence and severity of the intersex condition in wild, adult black bass ( Micropterus ), sunfish ( Lepomis ), and catfish (Ictaluridae) species at 11 sites located on the Yadkin-Pee Dee River. Polycyclic aromatic hydrocarbons (PAHs), ethinylestradiol (EE2), and heavy metals were the most prevalent contaminants that exceeded effect levels for the protection of aquatic organisms. Fish intersex condition was most frequently observed and most severe in black basses and was less frequently detected and less severe in sunfishes and catfishes. The occurrence of the intersex condition in fish showed site-related effects, rather than increasing longitudinal trends from upstream to downstream. Mean black bass and catfish tissue contaminant concentrations were higher than that of sunfish, likely because of the latter's lower trophic position in the food web. Principal component analysis identified waterborne PAHs as the most correlated environmental contaminant with intersex occurrence and severity in black bass and sunfish. As indicated by the intersex condition, EACs have adverse but often variable effects on the health of wild sport fishes in this river, likely due to fluctuations in EAC inputs and the dynamic nature of the riverine system. These findings enhance the understanding of the relationship between contaminants and fish health and provide information to guide ecologically comprehensive conservation and management decisions.

North Carolina, South Carolina↗
USGS2009

Use of predictive models and rapid methods to nowcast bacteria levels at coastal beaches

The need for rapid assessments of recreational water quality to better protect public health is well accepted throughout the research and regulatory communities. Rapid analytical methods, such as quantitative polymerase chain reaction (qPCR) and immunomagnetic separation/adenosine triphosphate (ATP) analysis, are being tested but are not yet ready for widespread use. Another solution is the use of predictive models, wherein variable(s) that are easily and quickly measured are surrogates for concentrations of fecal-indicator bacteria. Rainfall-based alerts, the simplest type of model, have been used by several communities for a number of years. Deterministic models use mathematical representations of the processes that affect bacteria concentrations; this type of model is being used for beach-closure decisions at one location in the USA. Multivariable statistical models are being developed and tested in many areas of the USA; however, they are only used in three areas of the Great Lakes to aid in notifications of beach advisories or closings. These “operational” statistical models can result in more accurate assessments of recreational water quality than use of the previous day's Escherichia coli (E. coli) concentration as determined by traditional culture methods. The Ohio Nowcast, at Huntington Beach, Bay Village, Ohio, is described in this paper as an example of an operational statistical model. Because predictive modeling is a dynamic process, water-resource managers continue to collect additional data to improve the predictive ability of the nowcast and expand the nowcast to other Ohio beaches and a recreational river. Although predictive models have been shown to work well at some beaches and are becoming more widely accepted, implementation in many areas is limited by funding, lack of coordinated technical leadership, and lack of supporting epidemiological data.

Aquatic Ecosystem Health & Management↗
USGS2017

Using regional scale flow–ecology modeling to identify catchments where fish assemblages are most vulnerable to changes in water availability

Streamflow is essential for maintaining healthy aquatic ecosystems and for supporting human water supply needs. Changes in climate, land use and water use practices may alter water availability. Understanding the potential effect of these changes on aquatic ecosystems is critical for long-term water management to maintain a balance between water for human consumption and ecosystem needs. Fish species data and streamflow estimates from a rainfall-runoff and flow routing model were used to develop boosted regression tree models to predict the relationship between streamflow and fish species richness (FSR) under plausible scenarios of (1) water withdrawal, (2) climate change and (3) increases in impervious surfaces in the Piedmont ecoregion of North Carolina, U.S.A. Maximum monthly flow, the fraction of total flow originating from impervious surface runoff, coefficient of monthly streamflow variability, and the specific river basin accounted for 50% of the variability in FSR. This model was used to predict FSR values for all twelve-digit Hydrological Unit Code catchments (HUC-12s) in the North Carolina Piedmont under current flow conditions and under water withdrawal, climate change and impervious surface scenarios. Flow–ecology modeling results indicate that predicted FSR declined significantly with increased water withdrawals. However, the magnitude of decline varied geographically. A “hot-spot” analysis was conducted based on predicted changes in FSR under each scenario to understand which HUC-12s were most likely to be affected by changes in water withdrawals, climate and impervious surfaces. Under the 20% withdrawal increase scenario, 413 of 886 (47%) HUC-12s in the study area were predicted to lose one or more species. HUC-12s in the Broad, Catawba, Yadkin and Cape Fear river basins were most susceptible to species loss. These findings may help decision making efforts by identifying catchments most vulnerable to changing water availability. Additionally, FSR-discharge modeling results can assist resource agencies, water managers and stakeholders in assessing the effect of water withdrawals in catchments to better support the protection and long-term conservation of species.

North Carolina↗
USGS2019

Towards common ground in the biodiversity–disease debate

The disease ecology community has struggled to come to consensus on whether biodiversity reduces or increases infectious disease risk, a question that directly affects policy decisions for biodiversity conservation and public health. Here, we summarize the primary points of contention regarding biodiversity–disease relationships and suggest that vector-borne, generalist wildlife and zoonotic pathogens are the types of parasites most likely to be affected by changes to biodiversity. One synthesis on this topic revealed a positive correlation between biodiversity and human disease burden across countries, but as biodiversity changed over time within these countries, this correlation became weaker and more variable. Another synthesis—a meta-analysis of generally smaller-scale experimental and field studies—revealed a negative correlation between biodiversity and infectious diseases (a dilution effect) in various host taxa. These results raise the question of whether biodiversity–disease relationships are more negative at smaller spatial scales. If so, biodiversity conservation at the appropriate scales might prevent wildlife and zoonotic diseases from increasing in prevalence or becoming problematic (general proactive approaches). Further, protecting natural areas from human incursion should reduce zoonotic disease spillover. By contrast, for some infectious diseases, managing particular species or habitats and targeted biomedical approaches (targeted reactive approaches) might outperform biodiversity conservation as a tool for disease control. Importantly, biodiversity conservation and management need to be considered alongside other disease management options. These suggested guiding principles should provide common ground that can enhance scientific and policy clarity for those interested in simultaneously improving wildlife and human health.

Nature Ecology & Evolution↗
USGS2024

Coyotes in the Great Basin desert do not exhibit a spatial response following the removal of anthropogenic water sources

Coyote ( Canis latrans ) range expansion into desert ecosystems has highlighted the role of anthropogenic water sources in arid ecosystems. Despite hypotheses that additional water facilitated this expansion, previous studies reported that coyotes did not exhibit a spatial or dietary response to removal of anthropogenic water. We used GPS data to examine if coyotes responded to water removal at a finer spatial scale than previously investigated. Our integrated step selection analysis did not find evidence that coyotes adjusted their distance to water following water removal. Vegetation was an important factor in habitat selection of coyotes, with riparian and agricultural areas being the most selected among vegetation types. Coyotes selected for locations where hunting and trapping was prohibited. Possibly the cause of increased coyote abundance in our study area was not due to the introduction of anthropogenic water sources but rather due to the cessation of regional lethal predator control programs. These two management decisions both occurred in the 1970s, therefore, their influences on the subsequent increase of coyote abundance may have been conflated. Our results, in combination with previous studies, provide evidence that coyotes are desert-adapted carnivores that do not rely on anthropogenic water sources.

Journal of Arid Environments↗
USGS2020

Forage and habitat for pollinators in the northern Great Plains—Implications for U.S. Department of Agriculture conservation programs

Managed and wild pollinators are critical components of agricultural and natural systems. Despite the well-known value of insect pollinators to U.S. agriculture, Apis mellifera (Linnaeus, 1758; honey bees) and wild bees currently face numerous stressors that have resulted in declining health. These declines have engendered support for pollinator conservation efforts across all levels of government, private businesses, and nongovernmental organizations. In 2014, the U.S. Department of Agriculture (USDA) and the U.S. Geological Survey initiated an interagency agreement to evaluate honey bee forage across multiple States in the northern Great Plains and upper Midwest. The long-term goal of this study was to provide an empirical evaluation of floral resources used by honey bees, and the relative contribution of multiple land covers and USDA conservation programs to bee health and productivity. Our multi-State analysis of land-use change from 2006 to 2016 revealed loss of grassland and increases in corn and soybean area in North and South Dakota, representing a significant loss of bee-friendly land covers in areas that support the highest density of summer bee yards in the entire United States. Our landscape models demonstrate the importance of the Conservation Reserve Program in providing safe locations for beekeepers to keep honey bees during the summer and highlights how land use in the northern Great Plains has a lasting effect on the health of honey bee colonies during almond pollination the subsequent spring. Our multiseason, multi-State genetic analysis of honey bee-collected pollen revealed Melilotus spp., Asteraceae, Trifolium spp., Fabaceae, Sonchus arvensis , Symphyotrichum cordifolium , and Solidago spp. were the top taxa detected; Melilotus spp. represented 42 percent of all detected taxa. Symphyotrichum cordifolium , Solidago spp., and Grindelia spp. were the top native forbs detected in honey bee-collected pollen. We also conducted plant and bee surveys on private lands enrolled in the Conservation Reserve Program and Environmental Quality Incentives Program. In general, we found significant variability in floral resources and pollinator utilization across USDA programs and practices. On average, greater than 75 percent of honey bee flower observations on private lands enrolled in a USDA conservation program were on non-native forbs, whereas 33 percent of wild bee flower observations were on non-native forbs. Melilotus officinalis and Medicago sativa were the most visited by honey bees, wherease Medicago sativa and Helianthus maximiliani were the most visited by wild bees. Our analysis of nectar dearth periods in June and September for honey bees revealed that although Melilotus officinalis and Medicago sativa were highly visited, less common native forb species such as Ratibida columnifera , Agastache foeniculum , and Gaillardia aristata were preferred species. However, these preferred species were relatively rare on the landscape and are, therefore, unlikely to make up a sizable part of the honey bee diet. In addition to our empirical results, we also showcase how the U.S. Geological Survey Pollinator Library, a decision-support tool for natural resource managers, can be used to design cost-effective seeding mixes for pollinators. Collectively, the results of this research will assist USDA with maximizing the ecological impact and cost-effectiveness of their conservation programs on pollinators in the northern Great Plains.

Minnesota, North Dakota, South Dakota↗
USGS2012

Effects of climate change and population growth on the transboundary Santa Cruz aquifer

The USA and Mexico have initiated comprehensive assessment of 4 of the 18 aquifers underlying their 3000 km border. Binational management of groundwater is not currently proposed. University and agency researchers plus USA and Mexican federal, state, and local agency staff have collaboratively identified key challenges facing the Santa Cruz River Valley Aquifer located between the states of Arizona and Sonora. The aquifer is subject to recharge variability, which is compounded by climate change, and is experiencing growing urban demand for groundwater. In this paper, we briefly review past, current, and projected pressures on Santa Cruz groundwater. We undertake first-order approximation of the relative magnitude of climate change and human demand drivers on the Santa Cruz water balance. Global circulation model output for emissions scenarios A1B, B1, and A2 present mixed trends, with annual precipitation projected to vary by ±20% over the 21st century. Results of our analysis indicate that urban water use will experience greater percentage change than climate-induced recharge (which remains the largest single component of the water balance). In the Mexican portion of the Santa Cruz, up to half of future total water demand will need to be met from non-aquifer sources. In the absence of water importation and with agricultural water use and rights increasingly appropriated for urban demand, wastewater is increasingly seen as a resource to meet urban demand. We consider decision making on both sides of the border and conclude by identifying short- and longer-term opportunities for further binational collaboration on transboundary aquifer assessment.

Santa Cruz Aquifer↗
USGS2005

Natural attenuation software (NAS): Assessing remedial strategies and estimating timeframes

Natural Attenuation Software (NAS) is a screening tool to estimate remediation timeframes for monitored natural attenuation (MNA) and to assist in decision-making on the level of source zone treatment in conjunction with MNA using site-specific remediation objectives. Natural attenuation processes that NAS models include are advection, dispersion, sorption, non-aqueous phase liquid (NAPL) dissolution, and biodegradation of either petroleum hydrocarbons or chlorinated ethylenes. Newly-implemented enhancements to NAS designed to maximize the utility of NAS for site managers were observed. NAS has expanded source contaminant specification options to include chlorinated ethanes and chlorinated methanes, and to allow for the analysis of any other user-defined contaminants that may be subject to microbially-mediated transformations (heavy metals, radioisotopes, etc.). Included is the capability to model co-mingled plumes, with constituents from multiple contaminant categories. To enable comparison of remediation timeframe estimates between MNA and specific engineered remedial actions , NAS was modified to incorporate an estimation technique for timeframes associated with pump-and-treat remediation technology for comparison to MNA. This is an abstract of a paper presented at the 8th International In Situ and On-Site Bioremediation Symposium (Baltimore, MD 6/6-9/2005).

Conference Paper↗
USGS2022

Evaluating sources of bias in pedigree-based estimates of breeding population size

Applications of genetic-based estimates of population size are expanding, especially for species for which traditional demographic estimation methods are intractable due to the rarity of adult encounters. Estimates of breeding population size ( N S ) are particularly amenable to genetic-based approaches as the parameter can be estimated using pedigrees reconstructed from genetic data gathered from discrete juvenile cohorts, therefore eliminating the need to sample adults in the population. However, a critical evaluation of how genotyping and sampling effort influence bias in pedigree reconstruction, and how these biases subsequently influence estimates of N S , is needed to evaluate the efficacy of the approach under a range of scenarios. We simulated a model system to understand the interactive effects of genotyping and sampling effort on error in genetic pedigrees reconstructed from the program COLONY . We then evaluated how errors in pedigree reconstruction influenced bias and precision in estimates of N S using three different rarefaction estimators. Results indicated that pedigree error can be minimal when adequate genetic data are available, such as when juvenile sample sizes are large and/or individuals are genotyped at many informative loci. However, even in cases for which data are limited, using results of the simulation analysis to understand the magnitude and sources of bias in reconstructed pedigrees can still be informative when estimating N S . We applied results of the simulation analysis to evaluate Nˆ S for a population of federally endangered Atlantic sturgeon ( Acipenser oxyrinchus oxyrinchus ) in the Delaware River, USA. Our results indicated that N S is likely to be three orders of magnitude lower compared with historic breeding population sizes, which is a considerable advancement in our understanding of the population status of Atlantic sturgeon in the Delaware River. Our analyses are broadly applicable in the design and interpretation of studies seeking to estimate N S and can help to guide conservation decisions when ecological uncertainty is high. The utility of these results is expected to grow as rapid advances in genetic technologies increase the popularity of genetic population monitoring and estimation.

Delaware, New Jersey, Pennsylvania↗
USGS2016

Scale-dependent habitat selection and size-based dominance in adult male American alligators

Habitat selection is an active behavioral process that may vary across spatial and temporal scales. Animals choose an area of primary utilization (i.e., home range) then make decisions focused on resource needs within patches. Dominance may affect the spatial distribution of conspecifics and concomitant habitat selection. Size-dependent social dominance hierarchies have been documented in captive alligators, but evidence is lacking from wild populations. We studied habitat selection for adult male American alligators ( Alligator mississippiensis ; n = 17) on the Pearl River in central Mississippi, USA, to test whether habitat selection was scale-dependent and individual resource selectivity was a function of conspecific body size. We used K-select analysis to quantify selection at the home range scale and patches within the home range to determine selection congruency and important habitat variables. In addition, we used linear models to determine if body size was related to selection patterns and strengths. Our results indicated habitat selection of adult male alligators was a scale-dependent process. Alligators demonstrated greater overall selection for habitat variables at the patch level and less at the home range level, suggesting resources may not be limited when selecting a home range for animals in our study area. Further, diurnal habitat selection patterns may depend on thermoregulatory needs. There was no relationship between resource selection or home range size and body size, suggesting size-dependent dominance hierarchies may not have influenced alligator resource selection or space use in our sample. Though apparent habitat suitability and low alligator density did not manifest in an observed dominance hierarchy, we hypothesize that a change in either could increase intraspecific interactions, facilitating a dominance hierarchy. Due to the broad and diverse ecological roles of alligators, understanding the factors that influence their social dominance and space use can provide great insight into their functional role in the ecosystem.

Mississippi↗
USGS2011

MODFLOW-CDSS, a version of MODFLOW-2005 with modifications for Colorado Decision Support Systems

MODFLOW-CDSS is a three-dimensional, finite-difference groundwater-flow model based on MODFLOW-2005, with two modifications. The first modification is the introduction of a Partition Stress Boundaries capability, which enables the user to partition a selected subset of MODFLOW's stress-boundary packages, with each partition defined by a separate input file. Volumetric water-budget components of each partition are tracked and listed separately in the volumetric water-budget tables. The second modification enables the user to specify that execution of a simulation should continue despite failure of the solver to satisfy convergence criteria. This modification is particularly intended to be used in conjunction with automated model-analysis software; its use is not recommended for other purposes.

Open-File Report↗
USGS2021

Peak-flow variability, peak-flow informational needs, and consideration of regional regression analyses in managing the crest-stage gage network in Montana

The U.S. Geological Survey (USGS), in cooperation with the Montana Department of Transportation (MDT), has operated a crest-stage gage (CSG) network in Montana to collect peak-flow data since 1955. The CSG network is vital to collecting peak-flow data on small drainage basins that typically are not addressed by continuous streamflow operations. Discussions between USGS and MDT identified a need for evaluating the CSG network to allow for better decision making in the management of the network. The purpose of this report is to (1) generally describe peak-flow variability in Montana, (2) assess peak-flow informational needs relevant to MDT activities, and (3) consider the characteristics of the active CSG network in relation to addressing the informational needs. The evaluation of the CSG network is intended to assist in prioritization for discontinuation of CSGs and other activities involving changes to the CSG network. Peak-flow variability was investigated by analysis of selected peak-flow characteristics of 659 unregulated streamgages in or near Montana. A generalized peak-flow variability index ( PFVI ) was developed to provide large-scale representation of peak-flow variability in Montana. For unregulated Montana streamgages, PFVI generally monotonically decreases with increasing drainage area, although there is somewhat large (but generally consistent) variability about the locally weighted scatterplot smooth line. Presumably, highly variable small-scale hydroclimatic processes are integrated with increasing drainage area such that variability in many hydrologic characteristics is reduced. PFVI also decreases with increasing mean basin elevation and mean annual precipitation. Presumably, higher elevation and wetter hydroclimatic settings in Montana contribute to reduced variability in hydrologic characteristics. Intuitively, PFVI might be expected to generally decrease with increasing years of record because the standard deviation might typically be expected to decrease with increasing sample size. However, relations among PFVI and years of record are more complex and variable than drainage area, elevation, and precipitation. PFVI variably increases from 10 to about 40 years of record and then generally monotonically decreases from about 40 to about 105 years of record. Relations among PFVI and the years of record might be confounded by effects of drainage area because streamgages with long periods of record (greater than about 60 years) generally have large drainage areas (greater than about 100 square miles). The relations between PFVI and drainage area, mean basin elevation, mean annual precipitation, and years of record substantially differ among the eight hydrologic regions in Montana. As such, the PFVI relations were further investigated within each hydrologic region. A major use of peak-flow information by MDT is for design of road and highway infrastructure, including bridges, culverts, and roadside drainage ditches. As such, basin characteristics (including drainage area, mean basin elevation, and mean annual precipitation) of the Montana streamgage network (735 regulated and unregulated streamgages) were statistically investigated in relation to basin characteristics of 12,639 road and stream intersections in Montana. Both regulated and unregulated streamgages were investigated because the road and stream intersections are on both regulated and unregulated streams. Exploratory analyses indicated that the various relations substantially differ among the hydrologic regions. As such, the relations between the Montana streamgage network and the road and stream intersections were further investigated within each hydrologic region. An important objective of the CSG network is to provide data for developing regional regression equations (RREs) for estimating frequencies at ungaged sites in Montana. Various characteristics of the RREs substantially differ among the eight hydrologic regions in Montana. As such, the RRE characteristics were further investigated within each hydrologic region. For each of the eight hydrologic regions, various characteristics of peak-flow variability, peak-flow informational needs, and regional regression analyses were investigated in detail. Possible shortcomings of the streamgage network in each hydrologic region are identified and possible future improvements to the CSG network are presented.

Montana↗
USGS2024

Probabilistic assessment of postfire debris-flow inundation in response to forecast rainfall

Communities downstream of burned steep lands face increases in debris-flow hazards due to fire effects on soil and vegetation. Rapid postfire hazard assessments have traditionally focused on quantifying spatial variations in debris-flow likelihood and volume in response to design rainstorms. However, a methodology that provides estimates of debris-flow inundation downstream of burned areas based on forecast rainfall would provide decision-makers with information that directly addresses the potential for downstream impacts. We introduce a framework that integrates a 24 h lead-time ensemble precipitation forecast with debris-flow likelihood, volume, and runout models to produce probabilistic maps of debris-flow inundation. We applied this framework to simulate debris-flow inundation associated with the 9 January 2018 debris-flow event in Montecito, California, USA. When the observed debris-flow volumes were used to drive the probabilistic forecast model, analysis of the simulated inundation probabilities demonstrates that the model is both reliable and sharp. In the fully predictive model, however, in which debris-flow likelihood and volume were computed from the atmospheric model ensemble's predictions of peak 15 min rainfall intensity, I 15 , the model generally under-forecasted the inundation area. The observed peak I 15 lies in the upper tail of the atmospheric model ensemble spread; thus a large fraction of ensemble members forecast lower I 15 than observed. Using these I 15 values as input to the inundation model resulted in lower-than-observed flow volumes which translated into under-forecasting of the inundation area. Even so, approximately 94 % of the observed inundated area was forecast to have an inundation probability greater than 1 %, demonstrating that the observed extent of inundation was generally captured within the range of outcomes predicted by the model. Sensitivity analyses indicate that debris-flow volume and two parameters associated with debris-flow mobility exert significant influence on inundation predictions, but reducing uncertainty in postfire debris-flow volume predictions will have the largest impact on reducing inundation outcome uncertainty. This study represents a first step toward a near-real-time hazard assessment product that includes probabilistic estimates of debris-flow inundation and provides guidance for future improvements to this and similar model frameworks by identifying key sources of uncertainty.

California↗
USGS2017

Using object-based image analysis to conduct high-resolution conifer extraction at regional spatial scales

The distribution and abundance of pinyon ( Pinus monophylla ) and juniper ( Juniperus osteosperma, J. occidentalis ) trees (hereinafter, "pinyon-juniper") in sagebrush ( Artemisia spp.) ecosystems of the Great Basin in the Western United States has increased substantially since the late 1800s. Distributional expansion and infill of pinyon-juniper into sagebrush ecosystems threatens the ecological function and economic viability of these ecosystems within the Great Basin, and is now a major contemporary challenge facing land and wildlife managers. Particularly, pinyon-juniper encroachment into intact sagebrush ecosystems has been identified as a primary threat facing populations of greater sage-grouse ( Centrocercus urophasianus ; hereinafter, "sage-grouse"), which is a sagebrush obligate species. Even seemingly innocuous scatterings of isolated pinyon-juniper in an otherwise intact sagebrush landscape can negatively affect survival and reproduction of sage-grouse. Therefore, accurate and high-resolution maps of pinyon-juniper distribution and abundance (indexed by canopy cover) across broad geographic extents would help guide land management decisions that better target areas for pinyon-juniper removal projects (for example, fuel reduction, habitat improvement for sage-grouse, and other sagebrush species) and facilitate science that further quantifies ecological effects of pinyon-juniper encroachment on sage-grouse populations and sagebrush ecosystem processes . Hence, we mapped pinyon-juniper (referred to as conifers for actual mapping) at a 1 × 1-meter (m) high resolution across the entire range of previously mapped sage-grouse habitat in Nevada and northeastern California. We used digital orthophoto quad tiles from National Agriculture Imagery Program (2010, 2013) as base imagery, and then classified conifers using automated feature extraction methodology with the program Feature Analyst ™ . This method relies on machine learning algorithms that extract features from imagery based on their spectral and spatial signatures. We classified conifers in 6,230 tiles and then tested for errors of omission and commission using confusion matrices. Accuracy ranged from 79.1 to 96.8, with an overall accuracy of 84.3 percent across all mapped areas. An estimated accuracy coefficient (kappa) indicated substantial to nearly perfect agreement, which varied across mapped areas. For this mapping process across the entire mapping extent, four sets of products are available at https://doi.org/10.5066/F7348HVC , including (1) a shapefile representing accuracy results linked to mapping subunits; (2) binary rasters representing conifer presence or absence at a 1 × 1 m resolution; (3) a 30 × 30 m resolution raster representing percentages of conifer canopy cover within each cell from 0 to 100; and (4) 1 × 1 m resolution canopy cover classification rasters derived from a 50-m-radius moving window analysis. The latter two products can be reclassified in a geographic information system (GIS) into user-specified bins to meet different objectives, which include approximations for phases of encroachment. These products complement, and in some cases improve upon, existing conifer maps in the Western United States, and will help facilitate sage-grouse habitat management and sagebrush ecosystem restoration.

California, Nevada↗
USGS2026

Combining branching processes and Allee effects into an integral projection model to assess invasion risk

Invasive species threaten both ecological systems and economies. Successful establishment is governed partly by demographic stochasticity, where random individual-level variation can significantly influence invasion dynamics. A critical factor is the Allee effect, which describes reduced population growth at low densities, potentially serving as a barrier to persistence. Size-dependent growth and survival further shape outcomes based on the size distribution of individuals within the population. To address these complexities, we developed a population-level model integrating an Integral Projection Model (IPM) for the expected size distribution with an Allee effect for recruitment dynamics and a branching process to account for demographic stochasticity. We applied this framework to Silver Carp ( Hypophthalmichthys molitrix ), a species established in the Upper Mississippi River system that poses significant risk of expanding into the Great Lakes. Our analysis compared temporal dynamics and population-size distributions under hypothetical introduction scenarios for large adult and smaller subadult fish. In both cases, initial population size relative to the Allee threshold was a critical determinant of establishment probability, with introductions below the threshold requiring stochastic growth across a critical biomass boundary before self-sustaining dynamics could take hold. Sensitivity analysis further indicated that per-spawner recruitment played a compounding role in invasion risk: higher recruitment rates reduced the critical introduction size for establishment and compressed the time to self-sustaining population size, jointly broadening the window of invasion risk. These findings highlight the framework’s potential for invasion assessments and offer insights into how Allee effects, size structure, and recruitment rates interact to govern establishment outcomes, while underscoring the need for species-specific parameter estimates before quantitative outputs can guide management decisions.

PLOS Ecosystems↗
USGS2010

Fort Collins Science Center- Policy Analysis and Science Assistance Branch : Integrating social, behavioral, economic and biological sciences

The Fort Collins Science Center's Policy Analysis and Science Assistance (PASA) Branch is a team of approximately 22 scientists, technicians, and graduate student researchers. PASA provides unique capabilities in the U.S. Geological Survey by leading projects that integrate social, behavioral, economic, and biological analyses in the context of human-natural resource interactions. Resource planners, managers, and policymakers in the U.S. Departments of the Interior (DOI) and Agriculture (USDA), State and local agencies, as well as international agencies use information from PASA studies to make informed natural resource management and policy decisions. PASA scientists' primary functions are to conduct both theoretical and applied social science research, provide technical assistance, and offer training to advance performance in policy relevant research areas. Management and research issues associated with human-resource interactions typically occur in a unique context, involve difficult to access populations, require knowledge of both natural/biological science in addition to social science, and require the skill to integrate multiple science disciplines. In response to these difficult contexts, PASA researchers apply traditional and state-of-the-art social science methods drawing from the fields of sociology, demography, economics, political science, communications, social-psychology, and applied industrial organization psychology. Social science methods work in concert with our rangeland/agricultural management, wildlife, ecology, and biology capabilities. The goal of PASA's research is to enhance natural resource management, agency functions, policies, and decision-making. Our research is organized into four broad areas of study.

Fact Sheet↗
USGS2021

Analysis of body condition indices reveals different ecotypes of the Antillean manatee

Assessing the body condition of wild animals is necessary to monitor the health of the population and is critical to defining a framework for conservation actions. Body condition indices (BCIs) are a non-invasive and relatively simple means to assess the health of individual animals, useful for addressing a wide variety of ecological, behavioral, and management questions. The Antillean manatee ( Trichechus manatus manatus ) is an endangered subspecies of the West Indian manatee, facing a wide variety of threats from mostly human-related origins. Our objective was to define specific BCIs for the subspecies that, coupled with additional health, genetic and demographic information, can be valuable to guide management decisions. Biometric measurements of 380 wild Antillean manatees captured in seven different locations within their range of distribution were obtained. From this information, we developed three BCIs (BCI 1 = UG/SL, BCI 2 = W/SL 3 , BCI 3 = W/(SL*UG 2 )). Linear models and two-way ANCOVA tests showed significant differences of the BCIs among sexes and locations. Although our three BCIs are suitable for Antillean manatees, BCI 1 is more practical as it does not require information about weight, which can be a metric logistically difficult to collect under particular circumstances. BCI 1 was significantly different among environments, revealing that the phenotypic plasticity of the subspecies have originated at least two ecotypes—coastal marine and riverine—of Antillean manatees.

Puerto Rico↗
USGS2009

Probability of Elevated Nitrate Concentrations in Groundwater in the Eagle River Watershed Valley-Fill Aquifer, Eagle County, North-Central Colorado, 2006-2007

This raster data set delineates the predicted probability of elevated nitrate concentrations in groundwater in the Eagle River watershed valley-fill aquifer, Eagle County, North-Central Colorado, 2006-2007. This data set was developed by a cooperative project between the U.S. Geological Survey, Eagle County, the Eagle River Water and Sanitation District, the Town of Eagle, the Town of Gypsum, and the Upper Eagle Regional Water Authority. This project was designed to evaluate potential land-development effects on groundwater and surface-water resources so that informed land-use and water management decisions can be made. This groundwater probability map and its associated probability maps was developed as follows: (1) A point data set of wells with groundwater quality and groundwater age data was overlaid with thematic layers of anthropogenic (related to human activities) and hydrogeologic data by using a geographic information system to assign each well values for depth to groundwater, distance to major streams and canals, distance to gypsum beds, precipitation, soils, and well depth. These data then were downloaded to a statistical software package for analysis by logistic regression. (2) Statistical models predicting the probability of elevated nitrate concentrations, the probability of unmixed young water (using chlorofluorocarbon-11 concentrations and tritium activities), and the probability of elevated volatile organic compound concentrations were developed using logistic regression techniques. (3) The statistical models were entered into a GIS and the probability map was constructed.

Data Series↗