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At least 1,297 records · Page 72Linked to original sources

USGS2011

A Digital Hydrologic Network Supporting NAWQA MRB SPARROW Modeling--MRB_E2RF1WS

A digital hydrologic network was developed to support SPAtially Referenced Regression on Watershed attributes (SPARROW) models within selected regions of the United States. These regions correspond with the U.S. Geological Survey's National Water Quality Assessment (NAWQA) Program Major River Basin (MRB) study units 2, 3, 4, 5, and 7 (Preston and others, 2009). MRB2, covers the South Atlantic-Gulf and Tennessee River basins. MRB3, covers the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy River basins. MRB4, covers the Missouri River basins. MRB5, covers the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins. MRB7, covers the Pacific Northwest River basins. The digital hydrologic network described here represents surface-water pathways (MRB_E2RF1) and associated catchments (MRB_E2RF1WS). It serves as the fundamental framework to spatially reference and summarize explanatory information supporting nutrient SPARROW models (Brakebill and others, 2011; Wieczorek and LaMotte, 2011). The principal geospatial dataset used to support this regional effort was based on an enhanced version of a 1:500,000 scale digital stream-reach network (ERF1_2) (Nolan et al., 2002). Enhancements included associating over 3,500 water-quality monitoring sites to the reach network, improving physical locations of stream reaches at or near monitoring locations, and generating drainage catchments based on 100m elevation data. A unique number (MRB_ID) identifies each reach as a single unit. This unique number is also shared by the catchment area drained by the reach, thus spatially linking the hydrologically connected streams and the respective drainage area characteristics. In addition, other relevant physical, environmental, and monitoring information can be associated to the common network and accessed using the unique identification number.

Report↗

USGS2011

A Digital Hydrologic Network Supporting NAWQA MRB SPARROW Modeling--MRB_E2RF1WS

General Information↗

USGS2019

Competitive interactions among H, CU, and Zn ion moderate aqueous uptake of Cu and Zn by an aquatic insect

The absorption of aqueous copper (Cu) and zinc (Zn) by aquatic insects, a group widely used to assess water quality, is unresolved. This study examined interactions among Cu, Zn, and protons that potentially moderate Cu and Zn uptake by the acid-tolerant stonefly Zapada sp. Saturation uptake kinetics was imposed to identify competitive mechanisms. Decreasing pH reduced the maximum transport capacity, Jmax, in both metals, had little effect on the Cu dissociation constant, KD, and increased the Zn KD. Partial noncompetitive (Cu) and partial mixed competitive (Zn) inhibitor models most closely tracked the observed Cu and Zn influx across pH treatments. The estimated values for acid dissociation constants for the binary (proton-receptor) and ternary (proton-metal-receptor) complexes indicated the strong inhibitory effect of protons on Cu and Zn. In neutral pH water, Cu inhibited Zn uptake, but Zn had little effect on Cu uptake. The mechanism of Cu-Zn interaction was not identified. Results from separate Zn experiments suggested that the insect’s developmental stage may affect the apparent Jmax. The study underscores some of the challenges of modeling metal bioaccumulation and informs future research directions.

Environmental Pollution↗

USGS2006

Vegetation greenness impacts on maximum and minimum temperatures in northeast Colorado

The impact of vegetation on the microclimate has not been adequately considered in the analysis of temperature forecasting and modelling. To fill part of this gap, the following study was undertaken. A daily 850–700 mb layer mean temperature, computed from the National Center for Environmental Prediction-National Center for Atmospheric Research (NCEP-NCAR) reanalysis, and satellite-derived greenness values, as defined by NDVI (Normalised Difference Vegetation Index), were correlated with surface maximum and minimum temperatures at six sites in northeast Colorado for the years 1989–98. The NDVI values, representing landscape greenness, act as a proxy for latent heat partitioning via transpiration. These sites encompass a wide array of environments, from irrigated-urban to short-grass prairie. The explained variance (r 2 value) of surface maximum and minimum temperature by only the 850–700 mb layer mean temperature was subtracted from the corresponding explained variance by the 850–700 mb layer mean temperature and NDVI values. The subtraction shows that by including NDVI values in the analysis, the r 2 values, and thus the degree of explanation of the surface temperatures, increase by a mean of 6% for the maxima and 8% for the minima over the period March–October. At most sites, there is a seasonal dependence in the explained variance of the maximum temperatures because of the seasonal cycle of plant growth and senescence. Between individual sites, the highest increase in explained variance occurred at the site with the least amount of anthropogenic influence. This work suggests the vegetation state needs to be included as a factor in surface temperature forecasting, numerical modeling, and climate change assessments.

Meteorological Applications↗

USGS2021

Conservation of northwestern and southwestern pond turtles: Threats, population size estimates, and population viability analysis

Accurate status assessments of long-lived, widely distributed taxa depend on the availability of long-term monitoring data from multiple populations. However, monitoring populations across large temporal and spatial scales is often beyond the scope of any one researcher or research group. Consequently, wildlife managers may be tasked with utilizing limited information from different sources to detect range-wide evidence of population declines and their causes. When assessments need to be made under such constraints, the research and management communities must determine how to extrapolate from variable population data to species-level inferences. Here, using three different approaches, we integrate and analyze data from the peer-reviewed literature and government agency reports to inform conservation for northwestern pond turtles (NPT) Actinemys marmorata and southwestern pond turtles (SPT) Actinemys pallida . Both NPT and SPT are long-lived freshwater turtles distributed along the west coast of the United States and Mexico. Conservation concerns exist for both species; however, SPT may face more severe threats and are thought to exist at lower densities throughout their range than NPT. For each species, we ranked the impacts of 13 potential threats, estimated population sizes, and modeled population viability with and without long-term droughts. Our results suggest that predation of hatchlings by invasive predators, such as American bullfrogs Lithobates catesbeianus and Largemouth Bass Micropterus salmoides, is a high-ranking threat for NPT and SPT. Southwestern pond turtles may also face more severe impacts associated with natural disasters (droughts, wildfires, and floods) than do NPT. Population size estimates from trapping surveys indicate that SPT have smaller population sizes on average than do NPT ( P = 0.0003), suggesting they may be at greater risk of local extirpation. Population viability analysis models revealed that long-term droughts are a key environmental parameter; as the frequency of severe droughts increases with climate change, the likelihood of population recovery decreases, especially when census sizes are low. Given current population trends and vulnerability to natural disasters throughout their range, we suggest that conservation and recovery actions first focus on SPT to prevent further population declines.

Journal of Fish and Wildlife Management↗

USGS1998

Models of metal binding structures in fulvic acid from the Suwannee River, Georgia

Fulvic acid, isolated from the Suwannee River, Georgia, was assessed for its ability to bind Ca2+, Cd2+, Cu2+, Ni2+, and Zn2+ ions at pH 6 before and after extensive fractionation that was designed to reveal the nature of metal binding functional groups. The binding constant for Ca2+ ion had the greatest increase of all the ions in a metal binding fraction that was selected for intensive characterization for the purpose of building quantitative average model structures. The 'metal binding' fraction was characterized by quantitative 13C NMR, 1H NMR, and FT-1R spectrometry and elemental, titrimetric, and molecular weight determinations. The characterization data revealed that carboxyl groups were clustered in short- chain aliphatic dibasic acid structures. The Ca2+ binding data suggested that ether-substituted oxysuccinic acid structures are good models for the metal binding sites at pH 6. Structural models were derived based upon oxidation and photolytic rearrangements of cutin, lignin, and tannin precursors. These structural models rich in substituted dibasic acid structures revealed polydentate binding sites with the potential for both inner-sphere and outer-sphere type binding. The majority of the fulvic acid molecule was involved with metal binding rather than a small substructural unit.Fulvic acid, isolated from the Suwannee River, Georgia, was assessed for its ability to bind Ca2+, Cd2+, Cu2+, Ni2+, and Zn2+ ions at pH 6 before and after extensive fractionation that was designed to reveal the nature of metal binding functional groups. The binding constant for Ca2+ ion had the greatest increase of all the ions in a metal binding fraction that was selected for intensive characterization for the purpose of building quantitative average model structures. The `metal binding' fraction was characterized by quantitative 13C NMR, 1H NMR, and FT-IR spectrometry and elemental, titrimetric, and molecular weight determinations. The characterization data revealed that carboxyl groups were clustered in short-chain aliphatic dibasic acid structures. The Ca2+ binding data suggested that ether-substituted oxysuccinic acid structures are good models for the metal binding sites at pH 6. Structural models were derived based upon oxidation and photolytic rearrangements of cutin, lignin, and tannin precursors. These structural models rich in substituted dibasic acid structures revealed polydentate binding sites with the potential for both inner-sphere and outer-sphere type binding. The majority of the fulvic acid molecule was involved with metal binding rather than a small substructural unit.

Georiga↗

USGS2017

Evaluation and use of U.S. Environmental Protection Agency Clean Watersheds Needs Survey data to quantify nutrient loads to surface water, 1978–2012

Changes in municipal and industrial point-source discharges over time have been an important factor affecting nutrient trends in many of the Nation’s streams and rivers. This report documents how three U.S. Environmental Protection Agency (EPA) national datasets—the Permit Compliance System, the Integrated Compliance Information System, and the Clean Watersheds Needs Survey—were evaluated for use in the U.S. Geological Survey National Water-Quality Assessment project to assess the causes of nutrient trends. This report also describes how a database of total nitrogen load and total phosphorous load was generated for select wastewater treatment facilities in the United States based on information reported in the EPA Clean Watersheds Needs Survey. Nutrient loads were calculated for the years 1978, 1980, 1982, 1984, 1986, 1988, 1990, 1992, 1996, 2000, 2004, 2008, and 2012 based on average nitrogen and phosphorous concentrations for reported treatment levels and on annual reported flow values. The EPA Permit Compliance System (PCS) and Integrated Compliance Information System (ICIS), which monitor point-source facility discharges, together are the Nation’s most spatially comprehensive dataset for nutrients released to surface waters. However, datasets for many individual facilities are incomplete, the PCS/ICIS historical data date back only to 1989, and historical data are available for only a limited number of facilities. Additionally, inconsistencies in facility reporting make it difficult to track or identify changes in nutrient discharges over time. Previous efforts made by the U.S. Geological Survey to “fill in” gaps in the PCS/ICIS data were based on statistical methods—missing data were filled in through the use of a statistical model based on the Standard Industrial Classification code, size, and flow class of the facility and on seasonal nutrient discharges of similar facilities. This approach was used to estimate point-source loads for a single point in time; it was not evaluated for use in generating a consistent data series over time. Another national EPA dataset that is available is the Clean Watersheds Needs Survey (CWNS), conducted every 4 years beginning 1973. The CWNS is an assessment of the capital needs of wastewater facilities to meet the water-quality goals set in the Clean Water Act. Data collected about these facilities include location and contact information for the facilities; population served; flow and treatment level of the facility; estimated capital needs to upgrade, repair, or improve facilities for water quality; and nonpoint-source best management practices. Total nitrogen and total phosphorous load calculations for each of the CWNS years were based on treatment level information and average annual outflow (in million gallons per day) from each of the facilities that had reported it. Treatment levels categories (such as Primary, Secondary, or Advanced) were substituted with average total nitrogen and total phosphorous concentrations for each treatment level based on those reported in literature. The CWNS dataset, like the PCS/ICIS dataset, has years where facilities did not report either a treatment level or an annual average outflow, or both. To fill in the data gaps, simple linear assumptions were made based on each facility’s responses to the survey in years bracketing the data gap or immediately before or after the data gap if open ended. Treatment level and flow data unique to each facility were used to complete the CWNS dataset for that facility.

Scientific Investigations Report↗

USGS2026

Compounding of 100-year coastal floods by rainfall in an urban environment

Coastal and pluvial flooding are both becoming more prevalent and severe due to climate change and urbanization in floodplains. The co-occurrence of these flood drivers is generally assumed to exacerbate the resulting flood impacts, a result referred to as compound flooding. However, few observational or modeling studies have investigated the circumstances under which this occurs. Here, we study the impacts of these combined flood drivers and evaluate the implicit hypothesis of official flood maps, which is that rainfall has a negligible impact on the flood depth and flooded area due to a 100 year coastal flood. A coastal system model, configured to capture coastal and pluvial flood drivers, is used. We evaluate the flooding for different urban landform types, including coastal landfill (human-made land), convergent areas (topographic depressions) and other urban terrain, within a model domain covering the Jamaica Bay watershed of New York City. A scenario-based strategy is adopted with a 100 year coastal flood as a control simulation, to which we add a set of realistic scenarios of rainfall data from historical tropical cyclones. We also apply a joint probability analysis framework with historical data to evaluate the probability of these compound coastal-pluvial scenarios. Results reveal cases where the pluvial driver compounds the coastal flood through expansion of the flood zone, with a 17% chance of rainfall increasing the flood area by 6%–38%, and a 5% chance of an increase of 61%–73%. It is rare that floods are significantly deepened but when deepening occurs, it is more common for the convergent zone than for the coastal landfill. These findings quantitatively assess the potential of the pluvial driver to exacerbate flooding, which may influence emergency management strategies such as evacuation plans, shelter arrangements, and related preparedness measures.

New York↗

USGS2015

Managing habitat to slow or reverse population declines of the Columbia spotted frog in the Northern Great Basin

Evaluating the effectiveness of habitat management actions is critical to adaptive management strategies for conservation of imperiled species. We quantified the response of a Great Basin population of the Columbia spotted frog ( Rana luteiventris ) to multiple habitat improvement actions aimed to reduce threats and reverse population declines. We used mark-recapture data for 1,394 adult frogs that had been marked by state, federal, and university biologists in 9 ponds representing a single population over a 16-year period from 1997 to 2012. With the use of demographic models, we assessed population-level effects of 1) a grazing exclosure constructed around 6 stock ponds that had been used to water livestock for decades before being fully fenced in 2003, and 2) the construction of 3 new stock ponds in 2003 to provide alternative water sources for livestock and, secondarily, to provide additional frog habitat. These management actions were implemented in response to a decline of more than 80% in population size from 1997 to 2002. We found evidence that excluding cattle from ponds and surrounding riparian habitats resulted in higher levels of frog production (more egg masses), higher adult frog recruitment and survival, and higher population growth rate. We also found that frogs colonized the newly constructed stock ponds within 3 years and frogs began breeding in 2 of them after 5 years. The positive effects of the cattle exclosure and additional production from the new ponds, although notable, did not result in full recovery of the population even 9 years later. This slow recovery may be partly explained by the effects of weather on recruitment rates, particularly the negative effects of harsher winters with late springs and higher fall temperatures. Although our findings point to potential successes of habitat management aimed at slowing or reversing rapidly declining frog populations, our study also suggests that recovering from severe population declines can take many years because of demographic and environmental processes.

Idaho↗

USGS2013

A comprehensive change detection method for updating the National Land Cover Database to circa 2011

The importance of characterizing, quantifying, and monitoring land cover, land use, and their changes has been widely recognized by global and environmental change studies. Since the early 1990s, three U.S. National Land Cover Database (NLCD) products (circa 1992, 2001, and 2006) have been released as free downloads for users. The NLCD 2006 also provides land cover change products between 2001 and 2006. To continue providing updated national land cover and change datasets, a new initiative in developing NLCD 2011 is currently underway. We present a new Comprehensive Change Detection Method (CCDM) designed as a key component for the development of NLCD 2011 and the research results from two exemplar studies. The CCDM integrates spectral-based change detection algorithms including a Multi-Index Integrated Change Analysis (MIICA) model and a novel change model called Zone, which extracts change information from two Landsat image pairs. The MIICA model is the core module of the change detection strategy and uses four spectral indices (CV, RCVMAX, dNBR, and dNDVI) to obtain the changes that occurred between two image dates. The CCDM also includes a knowledge-based system, which uses critical information on historical and current land cover conditions and trends and the likelihood of land cover change, to combine the changes from MIICA and Zone. For NLCD 2011, the improved and enhanced change products obtained from the CCDM provide critical information on location, magnitude, and direction of potential change areas and serve as a basis for further characterizing land cover changes for the nation. An accuracy assessment from the two study areas show 100% agreement between CCDM mapped no-change class with reference dataset, and 18% and 82% disagreement for the change class for WRS path/row p22r39 and p33r33, respectively. The strength of the CCDM is that the method is simple, easy to operate, widely applicable, and capable of capturing a variety of natural and anthropogenic disturbances potentially associated with land cover changes on different landscapes.

Remote Sensing of Environment↗

USGS2020

Efficient mammal biodiversity surveys for ecological restoration monitoring

Efficient biodiversity surveys are critical for successful restoration monitoring and management. We studied the effect of varying sampling effort on the observed species richness of surveys of small mammals (trapping transects), bats (passive acoustic detection), and medium to large mammals (trail cameras). Field studies provided mammalian biodiversity data for 4 bottomland hardwood restoration sites in northeastern Indiana. Subsampled data were used to simulate monitoring surveys with a range of levels of effort. We then used hierarchical Bayesian nonlinear mixed models to analyze how different components of sampling effort affected observed species richness, a key monitoring outcome. We found that observed small mammal richness increased with the increased number of transects in a survey, while observed bat and medium to large mammal richness increased with the increased duration of sampling. Variation between sites was important for the observed richness of small mammals and bats but not for medium to large mammals. The key driver of richness observed in simulated surveys was related to the spatial scale at which target fauna interact with the habitat, with decreasing richness accompanied by a greater spatial scale of animal–habitat interactions. Our findings suggest taxon-specific recommendations for efficiently quantifying the mammalian diversity of managed sites.

Indiana↗

USGS2017

Local and cross-seasonal associations of climate and land use with abundance of monarch butterflies Danaus plexippus

Quantifying how climate and land use factors drive population dynamics at regional scales is complex because it depends on the extent of spatial and temporal synchrony among local populations, and the integration of population processes throughout a species’ annual cycle. We modeled weekly, site-specific summer abundance (1994–2013) of monarch butterflies Danaus plexippus at sites across Illinois, USA to assess relative associations of monarch abundance with climate and land use variables during the winter, spring, and summer stages of their annual cycle. We developed negative binomial regression models to estimate monarch abundance during recruitment in Illinois as a function of local climate, site-specific crop cover, and county-level herbicide (glyphosate) application. We also incorporated cross-seasonal covariates, including annual abundance of wintering monarchs in Mexico and climate conditions during spring migration and breeding in Texas, USA. We provide the first empirical evidence of a negative association between county-level glyphosate application and local abundance of adult monarchs, particularly in areas of concentrated agriculture. However, this association was only evident during the initial years of the adoption of herbicide-resistant crops (1994–2003). We also found that wetter and, to a lesser degree, cooler springs in Texas were associated with higher summer abundances in Illinois, as were relatively cool local summer temperatures in Illinois. Site-specific abundance of monarchs averaged approximately one fewer per site from 2004–2013 than during the previous decade, suggesting a recent decline in local abundance of monarch butterflies on their summer breeding grounds in Illinois. Our results demonstrate that seasonal climate and land use are associated with trends in adult monarch abundance, and our approach highlights the value of considering fine-resolution temporal fluctuations in population-level responses to environmental conditions when inferring the dynamics of migratory species.

Illinois↗

USGS2012

Strategic directions for U.S. Geological Survey water science, 2012-2022 - Observing, understanding, predicting, and delivering water science to the Nation

Executive Summary This report expands the Water Science Strategy that was begun in the USGS Science Strategy, “Facing Tomorrow’s Challenges—U.S. Geological Survey Science in the Decade 2007–2017” (U.S. Geological Survey, 2007). The report looks at the relevant issues facing society and develops a strategy built around observing, understanding, predicting, and delivering water science for the next 5 to 10 years by building new capabilities, tools, and delivery systems to meet the Nation’s water-resource needs. This report begins by presenting the vision of water science for the USGS and the societal issues that are influenced by, and in turn influence, the water resources of our Nation. The essence of the Water Strategic Science Plan is built on the concept of “water availability,” defined as spatial and temporal distribution of water quantity and quality, as related to human and ecosystem needs, as affected by human and natural influences . The report also describes the core capabilities of the USGS in water science—the strengths, partnerships, and science integrity that the USGS has built over its 130-year history. Nine priority actions are presented in the report, which combine and elevate the numerous specific strategic actions listed throughout the report. Priority actions were developed as a means of providing the audience of this report with a list for focused attention, even if resources and time limit the ability of managers to address all of the strategic actions in the report. Priority actions focus on the following: Improve integrated science planning for water. Expand and enhance water-resource monitoring networks. Characterize the water cycle through development of state-of-the-art 3-D/4-D hydrogeologic framework models at multiple scales. Clarify the linkage between human water use (engineered hydrology) and the water cycle (natural hydrology). Advance ecological flow science. Provide flood-inundation science and information. Develop rapid deployment teams for water-related emergencies. Conduct integrated watershed assessment, research, and modeling. Deliver water data and analyses to the Nation. The body of the report is presented as a hierarchal set of 5 goals, 14 objectives, and 27 strategic actions that the USGS should undertake to advance water science through year 2022. The goals deal with: Providing society the information it needs regarding the amount and quality of water in all components of the water cycle at high temporal and spatial resolution, nationwide; Advancing our understanding of processes that determine water availability; Predicting changes in the quantity and quality of water resources in response to changing climate, population, land use, and management scenarios; Anticipating and responding to water-related emergencies and conflicts; and Delivering timely hydrologic data, analyses, and decision-support tools seamlessly across the Nation to support water-resource decisions. Scientific information produced on water resources would be without value if it were not communicated to society in a fashion that can inform decisions and actions. Therefore, the chapter following the goals describes how the USGS should inform, involve, and educate society about the science it produces. This includes discussions on local outreach and the use of social media for effective communication. This report concludes with a chapter devoted to the crosscutting science issues of the Water Mission Area with the other USGS Mission Areas: Climate and Land Use Change, Core Science Systems, Ecosystems, Energy and Minerals, Environmental Health Science, and Natural Hazards. Not one of these Mission Areas stands alone—all must work together and integrate their actions to fulfill the USGS science mission for the future. This final chapter identifies the important linkages that must be realized and maintained for this integration to occur.

Open-File Report↗

USGS2016

Sediment acoustic index method for computing continuous suspended-sediment concentrations

Suspended-sediment characteristics can be computed using acoustic indices derived from acoustic Doppler velocity meter (ADVM) backscatter data. The sediment acoustic index method applied in these types of studies can be used to more accurately and cost-effectively provide time-series estimates of suspended-sediment concentration and load, which is essential for informed solutions to many sediment-related environmental, engineering, and agricultural concerns. Advantages of this approach over other sediment surrogate methods include: (1) better representation of cross-sectional conditions from large measurement volumes, compared to other surrogate instruments that measure data at a single point; (2) high temporal resolution of collected data; (3) data integrity when biofouling is present; and (4) less rating curve hysteresis compared to streamflow as a surrogate. An additional advantage of this technique is the potential expansion of monitoring suspended-sediment concentrations at sites with existing ADVMs used in streamflow velocity monitoring. This report provides much-needed standard techniques for sediment acoustic index methods to help ensure accurate and comparable documented results. A sediment acoustic index gage is used to collect continuous acoustic backscatter data, using an ADVM deployed in a fixed location, which are related to results from discrete suspended-sediment samples. The raw ADVM backscatter data are adjusted for variables affecting backscatter other than the sediment concentration to compute the sediment-corrected backscatter ( SCB ) and sediment attenuation coefficient ( SAC ). The sediment acoustic index rating (rating) is then developed by relating the sediment characteristics from the periodic samples to the SCB and (or) SAC and other explanatory variables in a site-specific, instrument-specific, simple or multiple linear regression model. The rating is reviewed and checked to ensure the technique has been applied appropriately. This review includes an assessment of the theoretical soundness, the adequacy of the model calibration dataset, and the quality of the regression model and regression diagnostics. The rating can then be applied to the acoustic surrogates and other explanatory variables to obtain continuous records of computed suspended-sediment concentration. The estimates of suspended-sediment concentration can then be paired with streamflow data, if available, to compute continuous records of suspended-sediment load. Once developed, sediment acoustic index ratings must be validated with additional suspended-sediment samples, beyond the period of record used in the rating development, to verify that the regression model continues to adequately represent sediment conditions within the stream. Changes in ADVM configuration or installation, or replacement with another ADVM, may require development of a new rating. The best practices described in this report can be used to develop continuous estimates of suspended-sediment concentration and load using sediment acoustic surrogates to enable more informed and accurate responses to diverse sedimentation issues.

Techniques and Methods↗

USGS2000

Monitoring beach morphology changes using small-format aerial photography and digital softcopy photogrammetry

Current methods of monitoring beach morphology changes commonly involve the establishment of Global Positioning System profiles that are surveyed on a regular basis. Although this method produces precise measurements of coastal topography, it is costly in time and effort and may result in large data gaps between profiles. Much of our understanding of coastal dynamics is thus limited by profile spacing and survey frequency. Softcopy photogrammetry is increasingly being used as an alternative to assess shoreline change and study beach morphodynamics. This method of producing three-dimensional topographic models and orthophotographs from digitized aerial photography can aid in filling in the gaps between established profiles. A limiting factor to this technology is the cost of obtaining high-resolution aerial photography. We have developed an aerial mapping system designed to collect data in an efficient and cost-effective way. We use a small-format aerial photography system that can be mounted on a variety of small aircraft on short notice. After a flight, the photographs are scanned, and softcopy photogrammetry software is used to create both DTMs (Digital Terrain Models) and orthophotographs. The DTMs can be compared with existing profiles for accuracy, and volumetric changes can be computed. The orthophotos are used to make precise measurements of the position and morphology of shoreline features. This aerial mapping system is advantageous over previous methods of beach morphology change monitoring because it allows for rapid response to storm events and provides a cost-effective method of establishing a continual monitoring program in erosion hazard areas.

Environmental Geosciences↗

USGS2020

Influence of sediment and stream transport on detecting a source of environmental DNA

Environmental DNA (eDNA) can be used for early detection, population estimations, and assessment of potential spread of invasive species, but questions remain about factors that influence eDNA detection results. Efforts are being made to understand how physical, chemical, and biological factors—settling, resuspension, dispersion, eDNA stability/decay—influence eDNA estimations and potentially population abundance. In a series of field and controlled mesocosm experiments, we examined the detection and accumulation of eDNA in sediment and water and the transport of eDNA in a small stream in the Lake Michigan watershed, using the invasive round goby fish ( Neogobius melanostomus ) as a DNA source. Experiment 1: caged fish (average n = 44) were placed in a stream devoid of round goby; water was collected over 24 hours along 120-m of stream, including a simultaneous sampling event at 7 distances from DNA source; stream monitoring continued for 24 hours after fish were removed. Experiment 2: round goby were placed in laboratory tanks; water and sediment were collected over 14 days and for another 150 days post-fish removal to calculate eDNA shedding and decay rates for water and sediment. For samples from both experiments, DNA was extracted, and qPCR targeted a cytochrome oxidase I gene (COI) fragment specific to round goby. Results indicated that eDNA accumulated and decayed more slowly in sediment than water. In the stream, DNA shedding was markedly lower than calculated in the laboratory, but models indicate eDNA could potentially travel long distances (up to 50 km) under certain circumstances. Collectively, these findings show that the interactive effects of ambient conditions (e.g., eDNA stability and decay, hydrology, settling-resuspension) are important to consider when developing comprehensive models. Results of this study can help resource managers target representative sites downstream of potential invasion sites, thereby maximizing resource use.

PLoS ONE↗

USGS2009

Effects of experimental protocol on global vegetation model accuracy: a comparison of simulated and observed vegetation patterns for Asia

Prognostic vegetation models have been widely used to study the interactions between environmental change and biological systems. This study examines the sensitivity of vegetation model simulations to: (i) the selection of input climatologies representing different time periods and their associated atmospheric CO 2 concentrations, (ii) the choice of observed vegetation data for evaluating the model results, and (iii) the methods used to compare simulated and observed vegetation. We use vegetation simulated for Asia by the equilibrium vegetation model BIOME4 as a typical example of vegetation model output. BIOME4 was run using 19 different climatologies and their associated atmospheric CO 2 concentrations. The Kappa statistic, Fuzzy Kappa statistic and a newly developed map-comparison method, the Nomad index, were used to quantify the agreement between the biomes simulated under each scenario and the observed vegetation from three different global land- and tree-cover data sets: the global Potential Natural Vegetation data set (PNV), the Global Land Cover Characteristics data set (GLCC), and the Global Land Cover Facility data set (GLCF). The results indicate that the 30-year mean climatology (and its associated atmospheric CO 2 concentration) for the time period immediately preceding the collection date of the observed vegetation data produce the most accurate vegetation simulations when compared with all three observed vegetation data sets. The study also indicates that the BIOME4-simulated vegetation for Asia more closely matches the PNV data than the other two observed vegetation data sets. Given the same observed data, the accuracy assessments of the BIOME4 simulations made using the Kappa, Fuzzy Kappa and Nomad index map-comparison methods agree well when the compared vegetation types consist of a large number of spatially continuous grid cells. The results of this analysis can assist model users in designing experimental protocols for simulating vegetation.

Ecological Modelling↗

USGS2023

Ecological harm and economic damages of chemical contamination to linked aquatic-terrestrial food webs: A study-design tool for practitioners

Contamination of aquatic ecosystems can have cascading effects on terrestrial consumers by altering the availability and quality of aquatic insect prey. Comprehensive assessment of these indirect food-web effects of contaminants on natural resources and their associated services necessitates using both ecological and economic tools. In the present study we present an aquatic-terrestrial assessment tool (AT2), including ecological and economic decision trees, to aid practitioners and researchers in designing contaminant effect studies for linked aquatic-terrestrial insect-based food webs. The tool is tailored to address the development of legal claims by the US Department of the Interior's Natural Resource Damage Assessment and Restoration Program, which aims to restore natural resources injured by oil spills and hazardous substance releases into the environment. Such cases require establishing, through scientific inquiry, the existence of natural resource injury as well as the determination of the monetary or in-kind project-based damages required to restore this injury. However, this tool is also useful to researchers interested in questions involving the effects of contaminants on linked aquatic-terrestrial food webs. Stylized cases exemplify how application of AT2 can help practitioners and researchers design studies when the contaminants present at a site are likely to lead to injury of terrestrial aerial insectivores through loss of aquatic insect prey and/or dietary contaminant exposure. Designing such studies with ecological endpoints and economic modeling inputs in mind will increase the relevance and cost-effectiveness of studies, which can in turn improve the outcomes of cases and studies involving the ecological effects of contaminants on food webs.

Environmental Toxicology and Chemistry↗