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At least 1,441 records · Page 80Linked to original sources
USGS2004

Two-dimensional hydrodynamic simulation of surface-water flow and transport to Florida Bay through the Southern Inland and Coastal Systems (SICS)

Successful restoration of the southern Florida ecosystem requires extensive knowledge of the physical characteristics and hydrologic processes controlling water flow and transport of constituents through extremely low-gradient freshwater marshes, shallow mangrove-fringed coastal creeks and tidal embayments, and near-shore marine waters. A sound, physically based numerical model can provide simulations of the differing hydrologic conditions that might result from various ecosystem restoration scenarios. Because hydrology and ecology are closely linked in southern Florida, hydrologic model results also can be used by ecologists to evaluate the degree of ecosystem restoration that could be achieved for various hydrologic conditions. A robust proven model, SWIFT2D, (Surface-Water Integrated Flow and Transport in Two Dimensions), was modified to simulate Southern Inland and Coastal Systems (SICS) hydrodynamics and transport conditions. Modifications include improvements to evapotranspiration and rainfall calculation and to the algorithms that describe flow through coastal creeks. Techniques used in this model should be applicable to other similar low-gradient marsh settings in southern Florida and elsewhere. Numerous investigations were conducted within the SICS area of southeastern Everglades National Park and northeastern Florida Bay to provide data and parameter values for model development and testing. The U.S. Geological Survey and the National Park Service supported investigations for quantification of evapotranspiration, vegetative resistance to flow, wind-induced flow, land elevations, vegetation classifications, salinity conditions, exchange of ground and surface waters, and flow and transport in coastal creeks and embayments. The good agreement that was achieved between measured and simulated water levels, flows, and salinities through minimal adjustment of empirical coefficients indicates that hydrologic processes within the SICS area are represented properly in the SWIFT2D model, and that the spatial and temporal resolution of these processes in the model is adequate. Sensitivity analyses were conducted to determine the effect of changes in boundary conditions and parameter values on simulation results, which aided in identifying areas of greatest uncertainty in the model. The parameter having the most uncertainty (most in need of further field study) was the flow coefficient for coastal creeks. Smaller uncertainties existed for wetlands frictional resistance and wind. Evapotranspiration and boundary inflows indicated the least uncertainty as determined by varying parameters used in their formulation and definition. Model results indicated that wind was important in reversing coastal creek flows. At Trout Creek (the major tributary connecting Taylor Slough wetlands with Florida Bay), flow in the landward direction was not simulated properly unless wind forcing was included in the simulation. Simulations also provided insight into the major influence that wind has on salinity mixing along the coast, the varying distribution of wetland flows at differing water levels, and the importance of topography in controlling flows to the coast. Slight topographic variations were shown to highly influence the routing of water. A multiple regression analysis was performed to relate inflows at the northern boundary of Taylor Slough bridge to a major pump station (S-332) north of the SICS model area. This analysis allows Taylor Slough bridge boundary conditions to be defined for the model from operating scenarios at S-332, which should facilitate use of the SICS model as an operational tool.

Florida↗
USGS2026

Spatially realistic dynamic N-mixture models

Dispersal is a complex ecological process that can be driven by the abiotic environment, density-dependent processes and species mobility. Traditionally, dispersal has been studied with capture-based data that are often limited in space and time. More recently, spatial dynamic N-mixture models (i.e. N-mixture models accounting for dispersal among local populations and changes in abundance over time) allow the study of dispersal with count data. However, current spatial dynamic N-mixture models focus mainly on distance-based dispersal, limiting our ability to evaluate realistic patterns and drivers of dispersal at relevant spatial and temporal scales. We developed a spatially realistic dynamic N-mixture model that allows dispersal to be driven by environmental conditions and population density. Using simulations, we evaluated the inferential performance of this model when large proportions of sites are unsurveyed and the survey period is short, situations that are typical of real-world studies. We then used two case studies to illustrate the applications of this model, one representing a species with limited mobility in fragmented habitat (Chiricahua Leopard Frogs, Lithobates chiricahuensis , in isolated ponds) and the other representing a species with great mobility in continuous heterogeneous habitat (Common Nighthawks, Chordeiles minor , in grasslands). Our simulation study showed that the model provides valid inference even when the number of surveyed sites is small (𝑛 =10) or when the survey period is short for dynamic models (5 years), indicating that the model could have great practical value in real-world studies. The case study of Chiricahua Leopard Frogs showed that the model is capable of revealing pond-type-specific dispersal and predicting dispersal among ponds. The case study of Common Nighthawks showed the ability of the model to reveal the effect of primary productivity on dispersal and to map dispersal across the study area. Our effort demonstrates the potential of using count data to gain insights about complex yet realistic dispersal processes. The model that we introduce is flexible and adaptable for a broad range of situations in population and conservation ecology

Arizona, Kansas↗
USGS2018

Estimating vegetation biomass and cover across large plots in shrub and grass dominated drylands using terrestrial lidar and machine learning

Terrestrial laser scanning (TLS) has been shown to enable an efficient, precise, and non-destructive inventory of vegetation structure at ranges up to hundreds of meters. We developed a method that leverages TLS collections with machine learning techniques to model and map canopy cover and biomass of several classes of short-stature vegetation across large plots. We collected high-definition TLS scans of 26 1-ha plots in desert grasslands and big sagebrush shrublands in southwest Idaho, USA. We used the Random Forests machine learning algorithm to develop decision tree models predicting the biomass and canopy cover of several vegetation classes from statistical descriptors of the aboveground heights of TLS points. Manual measurements of vegetation characteristics collected within each plot served as training and validation data. Models based on five or fewer TLS descriptors of vegetation heights were developed to predict the canopy cover fraction of shrubs (R 2 = 0.77, RMSE = 7%), annual grasses (R 2 = 0.70, RMSE = 21%), perennial grasses (R 2 = 0.36, RMSE = 12%), forbs (R 2 = 0.52, RMSE = 6%), bare earth or litter (R 2 = 0.49, RMSE = 19%), and the biomass of shrubs (R 2 = 0.71, RMSE = 175 g) and herbaceous vegetation (R 2 = 0.61, RMSE = 99 g) (all values reported are out-of-bag). Our models explained much of the variability between predictions and manual measurements, and yet we expect that future applications could produce even better results by reducing some of the methodological sources of error that we encountered. Our work demonstrates how TLS can be used efficiently to extend manual measurement of vegetation characteristics from small to large plots in grasslands and shrublands, with potential application to other similarly structured ecosystems. Our method shows that vegetation structural characteristics can be modeled without classifying and delineating individual plants, a challenging and time-consuming step common in previous methods applying TLS to vegetation inventory. Improving application of TLS to studies of shrub-steppe ecosystems will serve immediate management needs by enhancing vegetation inventories, environmental modeling studies, and the ability to train broader datasets collected from air and space.

Idaho↗
USGS2020

A multi-state occupancy modelling framework for robust estimation of disease prevalence in multi-tissue disease systems

Given the public health, economic and conservation implications of zoonotic diseases, their effective surveillance is of paramount importance. The traditional approach to estimating pathogen prevalence as the proportion of infected individuals in the population is biased because it fails to account for imperfect detection. A statistically robust way to reduce bias in prevalence estimates is to obtain repeated samples (or sample many tissues in multi‐tissue disease systems) and to apply statistical methods that account for imperfect detection and permit the interdependence of the infection process across multiple tissues. We developed a multi‐state occupancy modelling framework which considers two scenarios about the infection process, one where no assumptions about the dependencies among the tissues are made (general), and another where dependence among tissues is not permitted (constrained). We applied this framework to pseudorabies virus (PrV) DNA detection data obtained from whole blood; and oral, nasal and genital mucosa of 510 feral swine Sus scrofa during the years 2014–2016 in Florida, USA. The constrained model was better supported by data. PrV prevalence estimates varied among tissues and were higher than the naïve estimates, ranging from to 0.06 (CI: 0.02–0.14) in genital to 0.54 (CI: 0.14 ‐ 0.82) in nasal tissue. Probability of PrV detection ranged from 0.11 (CI: 0.06–0.18) in nasal to 0.51 (CI: 0.21–0.81) in genital tissue. PrV prevalence was not affected by the age or sex of the animal or the year of sampling, but prevalence increased as drought severity increased. The conditional probability of detecting PrV given infection in at least one tissue type within an individual was highest for nasal tissue, suggesting that nasal is the best tissue to sample for PrV surveillance if only one tissue can be sampled, at least for systems with tissue‐specific prevalence and detection probabilities similar to ours. Synthesis and applications . We focused on inferences about pathogen prevalence in multi‐tissue disease systems, dealing with both nondetection and potential dependencies among tissues in infection status. We found strong evidence of variation in both prevalence and detection probabilities among tissues. Our results emphasize the importance of sampling multiple tissues and of applying inference methods that account for imperfect detection in the surveillance of systemic diseases. The multi‐state modelling framework is broadly applicable to the surveillance of pathogens that infect multiple tissues and can be used even when the infection status of the pathogen in one tissue may depend on the infection status of the pathogen in other tissue(s).

Journal of Applied Ecology↗
USGS2023

A novel assembly pipeline and functional annotations for targeted sequencing: A case study on the globally threatened Margaritiferidae (Bivalvia: Unionida)

The proliferation of genomic sequencing approaches has significantly impacted the field of phylogenetics. Target capture approaches provide a cost-effective, fast and easily applied strategy for phylogenetic inference of non-model organisms. However, several existing target capture processing pipelines are incapable of incorporating whole genome sequencing (WGS). Here, we develop a new pipeline for capture and de novo assembly of the targeted regions using whole genome re-sequencing reads. This new pipeline captured targeted loci accurately, and given its unbiased nature, can be used with any target capture probe set. Moreover, due to its low computational demand, this new pipeline may be ideal for users with limited resources and when high-coverage sequencing outputs are required. We demonstrate the utility of our approach by incorporating WGS data into the first comprehensive phylogenomic reconstruction of the freshwater mussel family Margaritiferidae. We also provide a catalogue of well-curated functional annotations of these previously uncharacterized freshwater mussel-specific target regions, representing a complementary tool for scrutinizing phylogenetic inferences while expanding future applications of the probe set.

Molecular Ecology Resources↗
USGS2016

A trans-national monarch butterfly population model and implications for regional conservation priorities

1. The monarch has undergone considerable population declines over the past decade, and the governments of Mexico, Canada, and the United States have agreed to work together to conserve the species. 2. Given limited resources, understanding where to focus conservation action is key for widespread species like monarchs. To support planning for continental-scale monarch habitat restoration, we address the question of where restoration efforts are likely to have the largest impacts on monarch butterfly ( Danaus plexippus Linn.) population growth rates. 3. We present a spatially explicit demographic model simulating the multi-generational annual cycle of the eastern monarch population, and use the model to examine management scenarios, some of which focus on particular regions of North America. 4. Improving the monarch habitat in the north central or southern parts of the monarch range yields a slightly greater increase in the population growth rate than restoration in other regions. However, combining restoration efforts across multiple regions yields population growth rates above 1 with smaller simulated improvements in habitat per region than single-region strategies. 5. S ynthesis and applications: These findings suggest that conservation investment in projects across the full monarch range will be more effective than focusing on one or a few regions, and will require international cooperation across many land use categories.

Ecological Entomology↗
USGS2014

Dynamic hyporheic exchange at intermediate timescales: testing the relative importance of evapotranspiration and flood pulses

Hyporheic fluxes influence ecological processes across a continuum of timescales. However, few studies have been able to characterize hyporheic fluxes and residence time distributions (RTDs) over timescales of days to years, during which evapotranspiration (ET) and seasonal flood pulses create unsteady forcing. Here we present a data-driven, particle-tracking piston model that characterizes hyporheic fluxes and RTDs based on measured vertical head differences. We used the model to test the relative influence of ET and seasonal flood pulses in the Everglades (FL, USA), in a manner applicable to other low-energy floodplains or broad, shallow streams. We found that over the multiyear timescale, flood pulses that drive relatively deep (∼1 m) flow paths had the dominant influence on hyporheic fluxes and residence times but that ET effects were discernible at shorter timescales (weeks to months) as a break in RTDs. Cumulative RTDs on either side of the break were generally well represented by lognormal functions, except for when ET was strong and none of the standard distributions applied to the shorter timescale. At the monthly timescale, ET increased hyporheic fluxes by 1–2 orders of magnitude; it also decreased 6 year mean residence times by 53–87%. Long, slow flow paths driven by flood pulses increased 6 year hyporheic fluxes by another 1–2 orders of magnitude, to a level comparable to that induced over the short term by shear flow in streams. Results suggest that models of intermediate-timescale processes should include at least two-storage zones with different RTDs, and that supporting field data collection occur over 3–4 years.

Florida↗
USGS2018

On the development of a magnetic susceptibility‐based tracer for aeolian sediment transport research

Aeolian processes — the erosion, transport, and deposition of sediment by wind — play important geomorphological and ecological roles in drylands. These processes are known to impact the spatial patterns of soil, nutrients, plant‐available water, and vegetation in many dryland ecosystems. Tracers, such as rare earth elements and stable isotopes have been successfully used to quantify the transport and redistribution of sediment by aeolian processes in these ecosystems. However, many of the existing tracer techniques are labor‐intensive and cost‐prohibitive, and hence simpler alternative approaches are needed to track aeolian redistribution of sediments. To address this methodological gap, we test the applicability of a novel metal tracer‐based methodology for estimating post‐fire aeolian sediment redistribution, using spatio‐temporal measurements of low‐field magnetic susceptibility (MS). We applied magnetic metal tracers on soil microsites beneath shrub vegetation in recently burned and control treatments in a heterogeneous landscape in the Chihuahuan desert (New Mexico, USA). Our results indicate a spatially homogeneous distribution of the magnetic tracers on the landscape after post‐burn wind erosion events. MS decreased after wind erosion events on the burned shrub microsites, indicating that these areas functioned as sediment sources following the wildfire, whereas they are known to be sediment sinks in the undisturbed (e.g., not recently burned) ecosystem. This experiment represents the first step toward the development of a cost‐effective and non‐destructive tracer‐based approach to estimate the transport and redistribution of sediment by aeolian processes.

Earth Surface Processes and Landforms↗
USGS2024

Fish bioenergetics modeling

A bioenergetics model for a fish is defined as a quantitative description of the fish's energy budget. Bioenergetics modeling can be applied to free-ranging fish in rivers, lakes, and oceans to estimate annual food consumption by fish populations; such applications have proven useful in managing fisheries. In addition, bioenergetics models have been used to better understand fish growth and consumption in ecosystems, to guide conservation management of endangered or threatened fish populations, to determine the importance of the role of fish in cycling nutrients within ecosystems, to predict fish growth and consumption under climate change , and to identify the important factors regulating contaminant accumulation in free-ranging fish. Over the past 60 years, fish bioenergetics modeling has led to significant advancements in both aquatic ecology, especially fish ecology, and fisheries management.

Book chapter↗
USGS2015

Book review: Restoring paradise: Rethinking and rebuilding nature in Hawaii

The native ecosystems of Hawai‘i have been severely degraded by the introduction of herbivorous mammals and a myriad of invasive plant species. Left unmanaged, most natural areas would continue along a trajectory towards domination by nonnative species; however, several projects have undertaken the daunting task of ecological restoration, four of which are the subject of Restoring Paradise by Robert Cabin: Hakalau Forest National Wildlife Refuge; Hawai‘i Volcanoes National Park; the Auwahi dryland forest, Maui and Limahuli Garden and Preserve, Kaua‘i. After an introductory section discussing the setting and factors that have contributed to so much of the degradation and extinction of Hawai‘i’s native biota, Cabin outlines two different views of restoration in two central sections of the book: ad hoc, trial-and-error approaches versus the careful application of science to direct restoration. The time-tested methods of fence construction, ungulate removal, weed control, and replanting native species with the help of numerous volunteers and community support are presented in marked contrast to inconsistent applications of science in guiding restoration, and illustrated by some of the author’s unsuccessful research. The book is largely presented as a non-technical first-person account of travels and meetings with key personalities driving restoration projects. The philosophies of restoration practitioners are embedded in passages from interviews. Setbacks, obstacles, logistical constraints, and successes are narrated in between as Cabin revisits each of the restoration sites. The utility of science in restoration is frequently questioned by the author and sometimes abandoned by practitioners in favour of a ‘let-nature-take-its-course’ approach. Review info: Restoring Paradise: Rethinking and Rebuilding Nature in Hawaii . By Robert J. Cabin, 2013. ISBN: 978-0822836931, 236 pp.

Pacific Conservation Biology↗
USGS2003

A strategy for mapping mid-scale existing vegetation in support of national fire fuel assessment

Geospatial distribution of natural vegetation is among the very important environmental parameters required for applications ranging from global climate change to monitoring of natural hazards, monitoring of ecosystem vitality, and fire management practices. Increasingly sophisticated applications require vegetation datasets to cover large areas at a suitable scale and provide sufficiently detailed information. In this paper, we describe a research effort to develop a remote sensing methodology capable of producing 30-meter resolution, wall-to-wall coverage of existing vegetation types and structure variables in support of a multi-agency fire fuels and fire risks assessment project. Success of this remote sensing research effort is dependent on improved sensor and data qualities, a thorough understanding of regional and local vegetation ecology, successful integration of remote sensing with a large amount of field plot data, and flexible mapping algorithms. Preliminary results produced in the Wasatch Range and Uinta Mountains of central Utah include 28 vegetation types with an overall accuracy of 60% (average by life forms), percent canopy density (sub-pixel density) of forest, shrub, and herbaceous cover (correlation coefficient of 89, 60, and 55% respectively), and average top canopy height of forest, shrub, and herbaceous cover (correlation coefficient of 73, 50, 20% respectively). Techniques to improve the first-round results are discussed, including refinements of mapping models and use of relevant environmental gradients and potential vegetation classification associated with actual vegetation types.

Conference Paper↗
USGS2019

Conducting and interpreting fish telemetry studies: Considerations for researchers and resource managers

Telemetry is an increasingly common tool for studying the ecology of wild fish, with great potential to provide valuable information for management and conservation. For researchers to conduct a robust telemetry study, many essential considerations exist related to selecting the appropriate tag type, fish capture and tagging methods, tracking protocol, data processing and analyses, and interpretation of findings. For telemetry-derived knowledge to be relevant to managers and policy makers, the research approach must consider management information needs for decision-making, while end users require an understanding of telemetry technology (capabilities and limitations), its application to fisheries research and monitoring (study design), and proper interpretation of results and conclusions (considering the potential for biases and proper recognition of associated uncertainties). To help bridge this gap, we provide a set of considerations and a checklist for researchers to guide them in conducting reliable and management-relevant telemetry studies, and for managers to evaluate the reliability and relevance of telemetry studies so as to better integrate findings into management plans. These considerations include implicit assumptions, technical limitations, ethical and biological realities, analytical merits, and the relevance of study findings to decision-making processes.

Reviews in Fish Biology and Fisheries↗
USGS2019

Thin-layer sediment addition to an existing salt marsh to combat sea-level rise and improve endangered species habitat in California, USA

Current tidal marsh elevations and their accretion rates are important predictors of vulnerability to sea-level rise. When tidal marshes are at risk, adaptation measures, such as sediment addition to increase elevations, can be implemented to prevent degradation and loss. In 2016, wildlife managers prescribed a thin-layer sediment addition of locally sourced dredged material from Anaheim Bay to mitigate plausible future impacts of sea-level rise to Seal Beach National Wildlife Refuge, an urbanized, subsiding, sediment limited, and low elevation tidal marsh in southern California, USA. In this study, our objectives were to determine how suspended sediment concentrations (SSC) and fluxes associated with sediment application affected an adjacent eelgrass bed and a more distant deep tidal channel at different time periods throughout the project and how sediment application affected tidal marsh elevation. Due to the sediment addition the tidal marsh elevation increased by 25.4 cm across 3.06 ha. Mean SSC levels at the eelgrass site increased from 4 mg/L during pre-augmentation to 16 mg/L during sediment application. SSC levels also increased up to 40 mg/L with the installation of sediment barriers. Winter storms during construction also had an influence on SSC, with an extreme storm event increasing SSC from 9 mg/L pre-storm levels to 16 mg/L during the storm. However, SSC at the deep site remained constant during all time periods with a mean of 7 mg/L. Our results show that little to zero sediment was exported out of Anaheim Bay during the study period, illustrating that any impacts were localized to the application area. These findings suggest that although long-range export of applied dredge material is unlikely from future thin-layer sediment application at this site, adjacent habitats could experience impacts if erosion control measures are not implemented effectively. Future projects will benefit from similar pre- and post-addition monitoring to establish the long-term efficacy of sea-level rise adaptation measures.

California↗
USGS2006

Endocrine disrupting chemicals research program of the U.S. Environmental Protection Agency: summary of a peer-review report

At the request of the U.S. Environmental Protection Agency (EPA) Office of Research and Development, a subcommittee of the Board of Scientific Counselors Executive Committee conducted an independent and open peer review of the Endocrine Disrupting Chemicals Research Program (EDC Research Program) of the U.S. EPA. The subcommittee was charged with reviewing the design, relevance, progress, scientific leadership, and resources of the program. The subcommittee found that the long-term goals and science questions in the EDC Program are appropriate and represent an understandable and solid framework for setting research priorities, representing a combination of problem-driven and core research. Long-term goal (LTG) 1, dealing with the underlying science surrounding endocrine disruptors, provides a solid scientific foundation for conducting risk assessments and making risk management decisions. LTG 2, dealing with defining the extent of the impact of endocrine-disrupting chemicals (EDCs), has shown greater progress on ecologic effects of EDCs compared with that on human health effects. LTG 3, which involves support of the Endocrine Disruptor Screening and Testing Program of the U.S. EPA, has two mammalian tests already through a validation program and soon available for use. Despite good progress, we recommend that the U.S. EPA a ) strengthen their expertise in wildlife toxicology, b ) expedite validation of the Endocrine Disruptors Screening and Testing Advisory Committee tests, c ) continue dependable funding for the EDC Research Program, d ) take a leadership role in the application of “omics” technologies to address many of the science questions critical for evaluating environmental and human health effects of EDCs, and e ) continue to sponsor multidisciplinary intramural research and interagency collaborations.

Environmental Health Perspectives↗
USGS2020

Compounds of emerging concern detected in water samples from potable water and wastewater treatment plants and detected in water and bed-sediment samples from sites on the Trinity River, Dallas, Texas, 2009–13

The population in the Dallas-Fort Worth metropolitan area in northern Texas is rapidly growing, resulting in a rapid increase in the demand for potable water and an increase in the discharge of wastewater treatment plant effluent. An assessment of compounds of emerging concern (CECs) in samples collected at potable water and wastewater treatment plants in Dallas and downstream from Dallas in the Trinity River was completed by the U.S. Geological Survey in cooperation with the City of Dallas, Dallas Water Utilities. CECs are synthetic or naturally occurring chemicals that are not commonly monitored in the environment but can enter the environment and cause known or suspected adverse ecological or human health effects. CECs can enter the environment through nonpoint sources (for example, runoff) and point sources (for example, concentrated animal feeding operations and treated-effluent discharge from wastewater treatment plants), which can increase concentrations of CECs especially in highly populated areas. CECs include pharmaceuticals (prescription and nonprescription), steroidal hormones, stanols, sterols, detergents and detergent metabolites (hereinafter referred to as “detergents”), personal-use products, pesticides, polycyclic aromatic hydrocarbons (PAHs), flame retardants, plasticizers, and other organic compounds used in everyday domestic, agricultural, and industrial applications. The release of CECs to the environment went largely unrecognized until relatively recently. Increased loading of certain CECs to the environment, combined with advancements in laboratory analysis methods that resulted in appreciably lower detection levels, brought greater attention to the release of CECs. In addition, synthesis of new chemicals or changes in use and disposal of existing chemicals can create new sources of CECs. Some CECs are endocrine disrupting compounds (EDCs), which can elicit adverse effects on development, behavior, and reproduction of wildlife and can cause dysfunction of human and wildlife endocrine (hormone) systems. Results of studies in the United States and Europe indicate that CECs, their metabolites, and industrial, agricultural, and household wastewater products are present in the aquatic environment, water treatment plants, and septic systems. CECs, especially pharmaceuticals, are of interest because of their persistence, widespread use, and potential to cause adverse effects in humans and nontargeted organisms. There is also concern that some CECs and EDCs resist degradation of water treatment processes at potable water treatment plants (PWTPs) and wastewater treatment plants (WWTPs) and that treated-effluent discharge could contain compounds that negatively affect biota living in receiving waters. Therefore, CECs and EDCs are more likely to be detected in environmental samples collected near areas of high population density where treated effluent from WWTPs can contribute substantially to receiving waters. The U.S. Geological Survey, in cooperation with the City of Dallas, Dallas Water Utilities, evaluated the occurrence and concentrations of selected CECs in samples collected at PWTPs and WWTPs in Dallas and downstream from the Dallas-Fort Worth metropolitan area in the Trinity River, Texas, from August 2009 to December 2013. Water samples were collected at three PWTP sites, two WWTP sites, and five study sites on the Trinity River; all sites where samples were collected were in or downstream from Dallas. These water samples were analyzed for 120 CECs, including human-health pharmaceuticals (prescription and nonprescription), antibiotics, steroidal hormones, stanols, sterols, detergents, personal-use products (flavors and fragrances), pesticides and repellents, industrial wastewater compounds, disinfection compounds, PAHs, flame retardants, and plasticizers. Additionally, bed-sediment samples were collected at each of the five Trinity River sites. The bed-sediment samples were analyzed for 57 CECs. In general, the water treatment processes at PWTPs and WWTPs were effective at reducing detections and concentrations of CECs to undetectable levels or transforming the compounds into degradates that were not analyzed. There were 14 and 73 CECs detected in raw water and in untreated-influent water at PWTPs and WWTPs, respectively. Of these, 11 of the 14 CECs detected in raw-water samples and 44 of the 73 CECs detected in untreated-influent samples were not detected in finished water or in treated-effluent water samples, respectively, indicating that these compounds were removed or degraded to compounds that were not analyzed. Some CECs, however, are resistant to degradation and were detected in untreated and treated water at PWTPs and at WWTPs. The three CECs detected at PWTPs in raw-water and finished-water samples were tris(dichloroisopropyl)phosphate, benzophenone, and methyl salicylate. At WWTPs, 29 CECs were detected, including carbamazepine, sulfamethoxazole, 4-androstene-3,17- dione , 3-beta-coprostanol, acetyl-hexamethyl-tetrahydronaphthalene (AHTN), hexahydro-hexamethyl-cyclopenta-benzopyran (HHCB), 1,4-dichlorobenzene, tribromomethane, benzophenone, and tris(dichloroisopropyl)phosphate, in untreated and treated water, indicating that treatment processes likely did not remove or degrade these compounds. Of the 23 CECs detected in stream-water samples collected at 5 sites on the Trinity River in or near Dallas, 10 CECs (carbamazepine, sulfamethoxazole, caffeine, 3-beta-coprostanol, cholesterol, HHCB, benzophenone, triethyl citrate, tributyl phosphate, and tris(dichloroisopropyl)phosphate) were detected at all 5 sites. The 10 CECs detected in water samples collected at all 5 sites on the Trinity River were also detected in treated-effluent water at WWTPs. Eleven of the 57 targeted CECs were detected in bed-sediment samples collected at study sites on the Trinity River. Of these 11 CECs, only 2 (beta-sitosterol and cholesterol) were detected in bed-sediment samples at all 5 sites on the Trinity River. Nine of these 11 CECs were not detected in any water-column sample, likely because of the strong hydrophobic characteristics of these compounds. Results from water treatment plants indicate that the water treatment process is less effective for removing or degrading compounds that are engineered to be resistant to degradation. These results also indicate the presence of CECs and EDCs at locations upstream from PWTPs in Dallas. Results from Trinity River main-stem sites indicate that some compounds are naturally attenuated during transport, but a few are persistent throughout the study reach. Many CECs and EDCs are hydrophobic and were only detected in bed sediment, indicating multiple pathways through which CECs can persist in the environment. In general, concentrations of CECs in the Dallas-Fort Worth metropolitan area were similar to those found in metropolitan areas nationwide.

Texas↗
USGS2021

Integrating socioecological suitability with human-wildlife conflict risk: Case study for translocation of a large ungulate

Translocations are essential for re-establishing wildlife populations. As they sometimes fail, it is critical to assess factors that influence their success pre-translocation. Socioecological suitability models (SESMs) integrate social acceptance and ecological suitability to enable identification of areas where wildlife populations will expand, which makes it likely that SESMs will also be useful for predicting translocation success. To inform site selection for potential elk Cervus canadensis reintroduction to north-eastern Minnesota, United States, we developed broadscale maps of social acceptance from surveys of local residents and landowners, animal use equivalence (AUE) from forage measured in the field and empirical conflict risk from geospatial data. Resulting SESMs integrated social acceptance favourability scores, AUE and conflict risk, and weighted SESMs showed the relative influences of acceptance and conflict. Social acceptance was positive for local residents and landowners (mean ≥ 5.4; scale of 1–7). AUE (scaled to an elk home range) ranged between 1 and 9 elk/16 km 2 during winter, and from 14 to 83 elk/16 km 2 during summer. Human–elk conflict risk was low (mean ≤ 0.10; scaled 0–1), increasing from north to south. Geographical distributions differed for social acceptance, AUE and conflict risk, and weighted SESMs revealed unsuitable areas that were otherwise obscured. Synthesis and applications . Integrating human–wildlife conflict risk into SESMs shows where social acceptance of translocated species is likely to erode, even where viewed favourably pre-translocation, to inform translocation planning by highlighting interactions between key factors. Such integrated models supplement existing reintroduction biology frameworks by supporting decision-making and knowledge development. In north-eastern Minnesota, natural resource managers who are considering elk reintroductions are using SESMs reported here to identify where human–elk conflict is unlikely to result in an isolated elk population and where addressing concerns for area residents about conflict risk is essential.

Minnesota↗
USGS2024

Using explainable machine learning methods to evaluate vulnerability and restoration potential of ecosystem state transitions

Ecosystem state transitions can be ecologically devastating or be a restoration success. State transitions are common within aquatic systems worldwide, especially considering human-mediated changes to land use and water use. We created a transferable conceptual framework to enable multiscale assessments of state resilience and early warnings of state transitions that can inform strategic restorations and avoid ecosystem collapse. The conceptual framework integrated machine learning predictions with ecosystem state concepts (e.g., state classification, gradients of vulnerability, and recovery potential leading to state transitions) and was devised to investigate possible environmental drivers. As an application of the framework, we generated prediction probabilities of submersed aquatic vegetation (SAV) presence at nearly 10,000 sites in the Upper Mississippi River (United States). Then, we used an interpretability method to explain model predictions to gain insights into possible environmental drivers and thresholds or linear responses of SAV presence and absence. Model accuracy was 89% without spatial bias. Average water depth, suspended solids, substrate, and distance to nearest SAV were the best predictors and likely environmental drivers of SAV habitat suitability. These environmental drivers exhibited nonlinear, threshold-type responses for SAV. All the results are also presented in an online dashboard to explore results at many spatial scales. The habitat suitability model outputs and prediction explanations from many spatial scales (4 m to 400 km of river reach) can inform research and restoration planning.

Conservation Biology↗
USGS2012

Assessing the vulnerability of human and biological communities to changing ecosystem services using a GIS-based multi-criteria decision support tool

In this paper we describe an application of a GIS-based multi-criteria decision support web tool that models and evaluates relative changes in ecosystem services to policy and land management decisions. The Santa Cruz Watershed Ecosystem Portfolio (SCWEPM) was designed to provide credible forecasts of responses to ecosystem drivers and stressors and to illustrate the role of land use decisions on spatial and temporal distributions of ecosystem services within a binational (U.S. and Mexico) watershed. We present two SCWEPM sub-models that when analyzed together address bidirectional relationships between social and ecological vulnerability and ecosystem services. The first model employs the Modified Socio-Environmental Vulnerability Index (M-SEVI), which assesses community vulnerability using information from U.S. and Mexico censuses on education, access to resources, migratory status, housing situation, and number of dependents. The second, relating land cover change to biodiversity (provisioning services), models changes in the distribution of terrestrial vertebrate habitat based on multitemporal vegetation and land cover maps, wildlife habitat relationships, and changes in land use/land cover patterns. When assessed concurrently, the models exposed some unexpected relationships between vulnerable communities and ecosystem services provisioning. For instance, the most species-rich habitat type in the watershed, Desert Riparian Forest, increased over time in areas occupied by the most vulnerable populations and declined in areas with less vulnerable populations. This type of information can be used to identify ecological conservation and restoration targets that enhance the livelihoods of people in vulnerable communities and promote biodiversity and ecosystem health.

Santa Cruz watershed↗