Coral reefs are iconic ecosystems that support diverse, productive communities in both shallow and deep waters. However, our incomplete knowledge of cold-water coral (CWC) niche space limits our understanding of their distribution and precludes a complete accounting of the ecosystem services they provide. Here, we present the results of recent surveys of the CWC mound province on the Blake Plateau off the U.S. east coast, an area of intense human activity including fisheries and naval operations, and potentially energy and mineral extraction. At one site, CWC mounds are arranged in lines that total over 150 km in length, making this one of the largest reef complexes discovered in the deep ocean. This site experiences rapid and extreme shifts in temperature between 4.3 and 10.7 °C, and currents approaching 1 m s−1. Carbon is transported to depth by mesopelagic micronekton and nutrient cycling on the reef results in some of the highest nitrate concentrations recorded in the region. Predictive models reveal expanded areas of highly suitable habitat that currently remain unexplored. Multidisciplinary exploration of this new site has expanded understanding of the cold-water coral niche, improved our accounting of the ecosystem services of the reef habitat, and emphasizes the importance of properly managing these systems.
Debris flows regularly traverse bedrock channels that dissect steep landscapes, but our understanding of bedrock erosion by debris flows and their impact on steepland morphology is still rudimentary. Quantitative models of steep bedrock channel networks are based on geomorphic transport laws designed to represent erosion by water-dominated flows. To quantify the impact of debris flow erosion on steep channel network form, it is first necessary to develop methods to estimate spatial variations in bulk debris flow properties (e.g., flow depth, velocity) throughout the channel network that can be integrated into landscape evolution models. Here, we propose and evaluate two methods to estimate spatial variations in bulk debris flow properties along the length of a channel profile. We incorporate both methods into a model designed to simulate the evolution of longitudinal channel profiles that evolve in response to debris flow and fluvial processes. To explore this model framework, we propose a general family of debris flow erosion laws where erosion rate is a function of debris flow depth and channel slope. Model results indicate that erosion by debris flows can explain the occurrence of a scaling break in the slope–area curve at low-drainage areas and that upper-network channel morphology may be useful for inferring catchment-averaged erosion rates in quasi-steady landscapes. Validating specific forms of a debris flow incision law, however, would require more detailed model–data comparisons in specific landscapes where input parameters and channel morphometry can be better constrained. Results improve our ability to interpret topographic signals within steep channel networks and identify observational targets critical for constraining a debris flow incision law.
Coral reefs are iconic ecosystems that support diverse, productive communities in both shallow and deep waters. However, our incomplete knowledge of cold-water coral (CWC) niche space limits our understanding of their distribution and precludes a complete accounting of the ecosystem services they provide. Here, we present the results of recent surveys of the CWC mound province on the Blake Plateau off the U.S. east coast, an area of intense human activity including fisheries and naval operations, and potentially energy and mineral extraction. At one site, CWC mounds are arranged in lines that total over 150 km in length, making this one of the largest reef complexes discovered in the deep ocean. This site experiences rapid and extreme shifts in temperature between 4.3 and 10.7 °C, and currents approaching 1 m s−1. Carbon is transported to depth by mesopelagic micronekton and nutrient cycling on the reef results in some of the highest nitrate concentrations recorded in the region. Predictive models reveal expanded areas of highly suitable habitat that currently remain unexplored. Multidisciplinary exploration of this new site has expanded understanding of the cold-water coral niche, improved our accounting of the ecosystem services of the reef habitat, and emphasizes the importance of properly managing these systems.
Eutrophication is one of the largest threats to aquatic ecosystems and chlorophyll a measurements are relevant indicators of trophic state and algal abundance. Many studies have modeled chlorophyll a in rivers but model development and testing has largely occurred at individual sites which hampers creating generalized models capable of making broad-scale predictions. To address this gap, we compiled a large data set of chlorophyll a concentrations matched to other water quality, meteorological, and reach characteristic data for a diverse set of 82 streams and rivers across the United States. We used this data set and extreme gradient boosting, a tree-based machine learning algorithm, to predict daily chlorophyll a concentrations. Furthermore, we tested several practical considerations of broad-scale models, such as making predictions at sites not included in model training or the utility of in situ water quality data versus universally available remotely estimated model inputs. Predictions were very strongly correlated to observations when compared against a randomly withheld subset of days; however, the model had lower accuracy when applied to completely novel sites withheld from model training. Turbidity and total nitrogen were the two most important variables for predicting chlorophyll a. Although in situ variables improved modeled estimates and were identified as more important during model interpretation, using only remote inputs still resulted in highly correlated predictions with small bias. Testing a model across many sites allowed for identification of common variables relevant to chlorophyll a and highlighted several challenges for applying data-driven models to new sites or at larger spatial scales.
Migratory waterfowl are an important resource for consumptive and non-consumptive users alike and provide tremendous economic value in North America. These birds rely on a complex matrix of public and private land for forage and roosting during migration and wintering periods, and substantial conservation effort focuses on increasing the amount and quality of target habitat. Yet, the value of habitat is a function not only of a site's resources but also of its geographic position and weather. To quantify this value, we used a continental-scale energetics-based model of daily dabbling duck movement to assess the marginal value of lands across the contiguous United States during the non-breeding period (September to May). We examined effects of eliminating each habitat node (32 × 32 km) in both a particularly cold and a particularly warm winter, asking which nodes had the largest effect on survival. The marginal value of habitat nodes for migrating dabbling ducks was a function of forage and roosting habitat but, more importantly, of geography (especially latitude and region). Irrespective of weather, nodes in the Southeast, central East Coast, and California made the largest positive contributions to survival. Conversely, nodes in the Midwest, Northeast, Florida, and the Pacific Northwest had consistent negative effects. Effects (positive and negative) of more northerly nodes occurred in late fall or early spring when climate was often severe and was most variable. Importance and effects of many nodes varied considerably between a cold and a warm winter. Much of the Midwest and central Great Plains benefited duck survival in a warm winter, and projected future warming may improve the value of lands in these regions, including many National Wildlife Refuges, for migrating dabbling ducks. Our results highlight the geographic variability in habitat value, as well as shifts that may occur in these values due to climate change.
Diffusion chronometry is now a widely applied methodology for determining the rates and timescales of geologic processes from the chemical zoning observed in minerals. Despite the popularity of the method, several challenges still remain during its application, including: (1) the random sectioning of minerals either in thin sections or grain mounts in which both off-center and oblique sections contribute substantial uncertainty to modeled timescales and (2) diffusion anisotropy needs to be accounted for in models, which generally requires determining the principal crystallographic axes of the mineral using electron backscatter diffraction, a technique that is both challenging and limiting because few scanning electron microscopes have an electron backscatter detector. This guide developed by the U.S. Geological Survey focuses on a step-by-step methodology for mounting individually oriented minerals that are sectioned through their cores prior to polishing for analytical work. Using this technique, one can significantly reduce the uncertainties associated with off-center sections and minimize or completely remove the need for determining crystallographic orientation via electron backscatter diffraction analyses. This report is presented as a guide for using the technique on olivine crystals but can be applied to any minerals that can be extracted for analysis. Two variations of the methodology are included here: (1) The individual crystal method that entails mounting individually sectioned single crystals and crystal groups and (2) the whole mount method in which multiple single crystals or crystal clusters are mounted and sectioned at the same time.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm5D5","programNote":"Volcano Hazards Program","usgsCitation":"Lynn, K.J., and DeSmither, L.G., 2023, Creating oriented and precisely sectioned mineral mounts for in situ chemical analyses—An example using olivine for diffusion chronometry studies: U.S. Geological Survey Techniques and Methods, book 5, chap. D5, 36 p., https://doi.org/10.3133/tm5D5.","productDescription":"ix, 36 p.","numberOfPages":"36","onlineOnly":"Y","ipdsId":"IP-142373","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":422457,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/05/d5/covrthb.jpg"},{"id":422458,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/05/d5/tm5d5.pdf","text":"Report","size":"12 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":422459,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/tm/05/d5/tm5d5.xml"},{"id":422460,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/tm/05/d5/images"},{"id":422461,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/tm5D5/full"}],"contact":"Director,
Volcano Science Center
U.S. Geological Survey
1300 SE Cardinal Court
Vancouver, WA 38683
Human development has major implications for wildlife populations. Urban-exploiter species can benefit from human subsidized resources, whereas urban-avoider species can vanish from wildlife communities in highly developed areas. Therefore, understanding how the density of different species varies in response to landcover changes associated with human development can provide important insight into how wildlife communities are likely to change and provide a starting point for predicting the consequences of those changes. Here, we estimated the population density of five common mesocarnivore species (coyote (Canis latrans), bobcat (Lynx rufus), red fox (Vulpes vulpes), raccoon (Procyon lotor), and Virginia opossum (Didelphis virginiana)) at 12 study sites along an urban to rural gradient in the greater Fayetteville Area, Northwest Arkansas, USA between November 2021, and March 2022. At each study site, we applied the Random Encounter Model (REM) to data from camera traps to calculate the density of five focal species. Coyote density ranged from 0.5 to 0.93 individuals/km2. Raccoon density ranged from 0.19 to 20.25 individuals/km2. Bobcat density ranged from 0 to 1.06 individuals/km2. Opossum density ranged from 0 to 3.43 individuals/km2. Red fox density ranged from 0 to 0.10 individuals/km2. Coyote and raccoon density showed a positive relationship with anthropogenic noise. Opossum density increased with HUD. Red Fox and bobcat density showed a negative relationship with forest area and a positive relationship with distance to water respectively, however confidence intervals for both species overlapped zero. The density estimates we report based on camera trap data of unmarked animals were consistent with reports from the literature for these same species derived from traditional methods, providing additional support to the REM as a viable, non-invasive method to calculate density of unmarked species. Our second analysis consisted of taking camera level density estimates and treating them as detection rates corrected for camera viewshed and animal movement. Coyote and raccoon detection rate showed a positive relationship with anthropogenic noise. Red Fox detection rate was positively related to developed open space, and negatively related to distance to water. Similarly to red fox, opossums detection rate was higher in areas with more developed open space. We found no evidence that bobcat density or detection rate varied with any of the landcover or anthropogenic variables we measured.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.gecco.2023.e02716","usgsCitation":"McTigue, L., and DeGregorio, B.A., 2023, Effects of landcover on mesocarnivore density and detection rate along an urban to rural gradient: Global Ecology and Conservation, v. 48, e02716, 14 p., https://doi.org/10.1016/j.gecco.2023.e02716.","productDescription":"e02716, 14 p.","ipdsId":"IP-149643","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":441657,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gecco.2023.e02716","text":"Publisher Index Page"},{"id":432148,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas","city":"Fayetteville","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -94.703264661285,\n 36.581012567484365\n ],\n [\n -94.703264661285,\n 35.69179592709919\n ],\n [\n -93.38479477781208,\n 35.69179592709919\n ],\n [\n -93.38479477781208,\n 36.581012567484365\n ],\n [\n -94.703264661285,\n 36.581012567484365\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"48","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McTigue, Leah","contributorId":310420,"corporation":false,"usgs":false,"family":"McTigue","given":"Leah","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":907388,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DeGregorio, Brett Alexander 0000-0002-5273-049X","orcid":"https://orcid.org/0000-0002-5273-049X","contributorId":243214,"corporation":false,"usgs":true,"family":"DeGregorio","given":"Brett","email":"","middleInitial":"Alexander","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":907389,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70250113,"text":"70250113 - 2023 - Shifted sediment-transport regimes by climate change and amplified hydrological variability in cryosphere-fed rivers","interactions":[],"lastModifiedDate":"2023-11-20T15:15:03.789762","indexId":"70250113","displayToPublicDate":"2023-11-08T09:10:21","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5010,"text":"Science Advances","active":true,"publicationSubtype":{"id":10}},"title":"Shifted sediment-transport regimes by climate change and amplified hydrological variability in cryosphere-fed rivers","docAbstract":"Climate change affects cryosphere-fed rivers and alters seasonal sediment dynamics, affecting cyclical fluvial material supply and year-round water-food-energy provisions to downstream communities. Here, we demonstrate seasonal sediment-transport regime shifts from the 1960s to 2000s in four cryosphere-fed rivers characterized by glacial, nival, pluvial, and mixed regimes, respectively. Spring sees a shift toward pluvial-dominated sediment transport due to less snowmelt and more erosive rainfall. Summer is characterized by intensified glacier meltwater pulses and pluvial events that exceptionally increase sediment fluxes. Our study highlights that the increases in hydroclimatic extremes and cryosphere degradation lead to amplified variability in fluvial fluxes and higher summer sediment peaks, which can threaten downstream river infrastructure safety and ecosystems and worsen glacial/pluvial floods. We further offer a monthly-scale sediment-availability-transport model that can reproduce such regime shifts and thus help facilitate sustainable reservoir operation and river management in wider cryospheric regions under future climate and hydrological change.
","language":"English","publisher":"American Association for the Advancement of Science","doi":"10.1126/sciadv.adi5019","usgsCitation":"Zhang, T., Li, D., East, A.E., Kettner, A.J., Best, J., Ni, J., and Lu, X., 2023, Shifted sediment-transport regimes by climate change and amplified hydrological variability in cryosphere-fed rivers: Science Advances, v. 9, no. 45, eadi5019, 12 p., https://doi.org/10.1126/sciadv.adi5019.","productDescription":"eadi5019, 12 p.","ipdsId":"IP-147639","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":441660,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1126/sciadv.adi5019","text":"Publisher Index Page"},{"id":422725,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"45","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Zhang, Tinghu","contributorId":210005,"corporation":false,"usgs":false,"family":"Zhang","given":"Tinghu","email":"","affiliations":[],"preferred":false,"id":888409,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Li, Dongfeng","contributorId":297068,"corporation":false,"usgs":false,"family":"Li","given":"Dongfeng","email":"","affiliations":[{"id":64287,"text":"National University of Singapore","active":true,"usgs":false}],"preferred":false,"id":888410,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"East, Amy E. 0000-0002-9567-9460 aeast@usgs.gov","orcid":"https://orcid.org/0000-0002-9567-9460","contributorId":196364,"corporation":false,"usgs":true,"family":"East","given":"Amy","email":"aeast@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":888411,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kettner, Albert J.","contributorId":331669,"corporation":false,"usgs":false,"family":"Kettner","given":"Albert","email":"","middleInitial":"J.","affiliations":[{"id":36627,"text":"University of Colorado, Boulder","active":true,"usgs":false}],"preferred":false,"id":888412,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Best, James L.","contributorId":331670,"corporation":false,"usgs":false,"family":"Best","given":"James L.","affiliations":[{"id":35161,"text":"University of Illinois, Urbana-Champaign","active":true,"usgs":false}],"preferred":false,"id":888413,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ni, Jinren","contributorId":331671,"corporation":false,"usgs":false,"family":"Ni","given":"Jinren","email":"","affiliations":[{"id":79261,"text":"Peking University, Beijing, China","active":true,"usgs":false}],"preferred":false,"id":888414,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lu, Xixi","contributorId":298889,"corporation":false,"usgs":false,"family":"Lu","given":"Xixi","email":"","affiliations":[{"id":64287,"text":"National University of Singapore","active":true,"usgs":false}],"preferred":false,"id":888415,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70250689,"text":"70250689 - 2023 - Response of lake metabolism to catchment inputs inferred using high-frequency lake and stream data from across the northern hemisphere","interactions":[],"lastModifiedDate":"2023-12-27T12:49:16.223157","indexId":"70250689","displayToPublicDate":"2023-11-08T06:46:31","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7120,"text":"Limnology & Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Response of lake metabolism to catchment inputs inferred using high-frequency lake and stream data from across the northern hemisphere","docAbstract":"In lakes, the rates of gross primary production (GPP), ecosystem respiration (R), and net ecosystem production (NEP) are often controlled by resource availability. Herein, we explore how catchment vs. within lake predictors of metabolism compare using data from 16 lakes spanning 39°N to 64°N, a range of inflowing streams, and trophic status. For each lake, we combined stream loads of dissolved organic carbon (DOC), total nitrogen (TN), and total phosphorus (TP) with lake DOC, TN, and TP concentrations and high frequency in situ monitoring of dissolved oxygen. We found that stream load stoichiometry indicated lake stoichiometry for C : N and C : P (r2 = 0.74 and r2 = 0.84, respectively), but not for N : P (r2 = 0.04). As we found a strong positive correlation between TN and TP, we only used TP in our statistical models. For the catchment model, GPP and R were best predicted by DOC load, TP load, and load N : P (R2 = 0.85 and R2 = 0.82, respectively). For the lake model, GPP and R were best predicted by TP concentrations (R2 = 0.86 and R2 = 0.67, respectively). The inclusion of N : P in the catchment model, but not the lake model, suggests that both N and P regulate metabolism and that organisms may be responding more strongly to catchment inputs than lake resources. Our models predicted NEP poorly, though it is unclear why. Overall, our work stresses the importance of characterizing lake catchment loads to predict metabolic rates, a result that may be particularly important in catchments experiencing changing hydrologic regimes related to global environmental change.
The Rainy-Lake of the Woods Basin covers 70,000 square kilometers in mid-central North America and is contained within the Provinces of Ontario and Manitoba in Canada and the State of Minnesota in the United States. This basin contains natural wilderness areas, national parks, and thousands of lakes that bring outdoor enthusiasts from around the world for hunting, fishing, backpacking, boating, and other forms of recreation. However, trade, commerce, visitors, and wildlife can inadvertently transport hitchhiking exotic invasive species that affect the functioning of natural systems by displacing native organisms, introducing diseases, and modifying predator/prey relations. In cooperation with the International Joint Commission, the U.S. Geological Survey evaluated the aquatic invasive species that pose a possible threat to North America. The outcome of this project is a set of lists of invasive species that have traits amenable or proximity to the Rainy-Lake of the Woods Basin. These lists can be referenced to further evaluate known and potential nonindigenous invasive species. The lists were derived by evaluating more than 1,500 species from several online sources including Non-Indigenous Aquatic Species, Great Lakes Aquatic Nonindigenous Species Information System, Biodiversity Information Serving Our Nation, and other State, Provincial, and Federal lists in the United States and Canada. The purpose of these lists is to be a coarse filter to determine which species pose the greatest risk to the Rainy-Lake of the Woods Basin. Using this filter, seven categories of risk assessment priorities were developed: Very High-Approaching, Very High-Present, High-Approaching, High-Present, Moderate, Low, and Native. These categories can be used by the International Rainy-Lake of the Woods Multi-Agency Arrangement Aquatic Invasive Species Subcommittee to prioritize which species will be evaluated further focusing on five risk factors: arrival risk, vulnerability assessment, ecological impact, socioeconomic impact, and beneficial impact. Based on proximity, ease of transport or introduction, and known impact to Rainy-Lake of the Woods or other impacted ecosystems, this project identified the following 10 species that could be prioritized first for risk evaluations: Bythotrephes longimanus (spiny waterflea), Faxonius rusticus (rusty crayfish), Neogobius melanostomus (round goby), Dreissena polymorpha (zebra mussel), Bithynia tentaculata (mud Bithynia or faucet snail), Potamopyrgus antipodarum (New Zealand mud snail), Butomus umbellatus (flowering rush), Nitellopsis obtusa (starry stonewort), Myriophyllum spicatum (Eurasian watermilfoil), and Phragmites australis australis (common reed).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221070","collaboration":"Prepared in cooperation with the International Joint Commission","usgsCitation":"Bell, A.H., Katona, L.R., and Vellequette, N.M., 2023, Development and application of a risk assessment tool for aquatic invasive species in the international Rainy-Lake of the Woods Basin, United States and Canada: U.S. Geological Survey Open-File Report 2022–1070, 26 p., https://doi.org/10.3133/ofr20221070.","productDescription":"Report: vi, 26 p.; 3 Datasets","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-127028","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":499719,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115587.htm","linkFileType":{"id":5,"text":"html"}},{"id":422425,"rank":8,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221070/full"},{"id":422424,"rank":7,"type":{"id":28,"text":"Dataset"},"url":"https://bison.usgs.gov/","text":"USGS database","linkHelpText":"—Biodiversity Information Serving Our Nation (BISON)"},{"id":422421,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1070/images/"},{"id":422418,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1070/coverthb.jpg"},{"id":422420,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1070/ofr20221070.XML"},{"id":422419,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1070/ofr20221070.pdf","text":"Report","size":"1.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022–1070"},{"id":422422,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://www.glerl.noaa.gov/glansis/riskAssessment.html","text":"NOAA database","linkHelpText":"—Great Lake Aquatic Nonindigenous Species Information System (GLANSIS) Risk Assessment Clearinghouse"},{"id":422423,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://nas.er.usgs.gov/","text":"USGS database","linkHelpText":"—NAS—Nonindigenous Aquatic Species"}],"country":"Canada, United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -95.7568318410593,\n 50.39164460188181\n ],\n [\n -95.7568318410593,\n 47.02962883799128\n ],\n [\n -90.08788652855912,\n 47.02962883799128\n ],\n [\n -90.08788652855912,\n 50.39164460188181\n ],\n [\n -95.7568318410593,\n 50.39164460188181\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
1 Gifford Pinchot Drive
Madison, WI 53726
The Karner blue butterfly (Lycaeides melissa samuelis, or Kbb), a federally endangered species under the U.S. Endangered Species Act in decline due to habitat loss, can be further threatened by climate change. Evaluating how climate shapes the population trend of the Kbb can help in the development of adaptive management plans. Current demographic models for the Kbb incorporate in either a density-dependent or density-independent manner. We instead created mixed density-dependent and -independent (hereafter “endo-exogenous”) models for Kbbs based on long-term count data of five isolated populations in the upper Midwest, United States during two flight periods (May to June and July to August) to understand how the growth rates were related to previous population densities and abiotic environmental conditions, including various macro- and micro-climatic variables. Our endo-exogenous extinction risk models showed that both density-dependent and -independent components were vital drivers of the historical population trends. However, climate change impacts were not always detrimental to Kbbs. Despite the decrease of population growth rate with higher overwinter temperatures and spring precipitations in the first generation, the growth rate increased with higher summer temperatures and precipitations in the second generation. We concluded that finer spatiotemporally scaled models could be more rewarding in guiding the decision-making process of Kbb restoration under climate change.
Accurate estimates of current and future habitat suitability are needed for species that may require assistance in tracking a shifting climate. Standard species distribution models (SDMs) based on occurrence data are the most common approach for evaluating climatic suitability, but these may suffer from inaccuracies stemming from disequilibrium dynamics and/or an inability to identify suitable climate regions that have no analogues within the current range. An alternative approach is to test performance with experimental introductions, and model suitability from the empirical results. We used this method with the Haleakalā silversword (Argyroxiphium sandwicense subsp. macrocephalum), using a network of out-plant plots across the top of Haleakalā volcano, Hawaiʻi. Over a ~ 5-year period, survival varied strongly across this network and was effectively explained by a simple model including mean rainfall and air temperature. We then applied this model to estimate current climatic suitability for restoration or translocation activities, to define trends in suitability over the past three decades, and to project future suitability through 2051. This empirical approach indicated that much of the current range has low suitability for long-term successful restoration, but also identified areas of high climatic suitability in a region where plants do not currently occur. These patterns contrast strongly with projections obtained with a standard SDM, which predicted continued suitability throughout the current range. Under continued climatic shifts, these results caution against the common SDM presumption of equilibrium between species’ distributions and their environment, even for long-established native species.
Informed population monitoring efforts are essential for sound management of harvested species, and adaptive strategies that provide detailed information to monitoring efforts often require data inputs from complimentary sources. Movement ecology information is seldom directly incorporated into population monitoring or adaptive harvest management strategies, yet can provide valuable information on species distributions, emigration and immigration rates, and aid in determining optimal population monitoring timing. The Rocky Mountain Population (RMP) of Sandhill Cranes is a harvested population subject to a stringent adaptive harvest management framework and an annual aerial survey to estimate population abundance, but movements of Sandhill Cranes during survey windows, and subsequent changes to harvest quotas based on their movement and distribution have not been investigated. We used seven years of GPS tracking data to estimate state-specific emigration and immigration rates, using a Bayesian multi-state capture-recapture model, among states within the RMP distribution to understand how seasonal crane movements may influence optimal aerial survey timing. We then leveraged these transition probabilities in conjunction with aerial survey count data to model how changes in aerial survey timing and movement-informed crane distribution would influence the current RMP Sandhill Crane adaptive harvest management model resulting in estimated changes to harvest allocation among states based on Sandhill Crane movement. We found that Sandhill Crane emigration from northern states began to increase the week of the aerial survey in late September, and continued to increase as autumn migration progressed into October. As expected, immigration to southern states began as emigration from northern states increased. Importantly, little movement among states occurred prior to the current aerial survey design timing. Overall, we found that current survey timing and shortly thereafter (∼1 week) did not greatly influence estimates of Sandhill Crane distribution, and did not greatly influence the harvest reallocation to each state until mid to late October (range of −42–+52 tag allocation change), much later than the current survey design would allow. Using GPS locations, we found that optimal population monitoring efforts could be improved to account for both detection and seasonal movements, while minimally influencing current adaptive harvest management strategies to stakeholders. Linking movement ecology with population monitoring efforts and subsequently adaptive harvest management strategies yields insightful information that can be beneficial for conservation planning, decision-making, and optimal species management of a migratory bird.
The Federal Highway Administration and State departments of transportation nationwide need an efficient method to assess potential adverse effects of highway stormwater runoff on receiving waters to optimize stormwater-treatment decisions. To this end, the U.S. Geological Survey, in cooperation with the Federal Highway Administration and the North Carolina Department of Transportation (NCDOT), developed a decision-support software tool based on a statewide version of the Stochastic Empirical Loading and Dilution Model (SELDM). This decision-support tool is designed to identify potential adverse effects of highway runoff by using a criterion based on a measurable change in water quality from a surrogate pollutant. The NCDOT worked with the North Carolina Department of Environmental Quality to select a 25-percent change in suspended sediment concentration as the decision-rule criterion for identifying measurable downstream water-quality change; this selection was based on available data and widely accepted stormwater monitoring uncertainties. Development of the statewide tool and its application to the Piedmont ecoregion are described in this report. Because SELDM can be applied to build a similar decision-support tool in any State, this report describes practice-ready methods that other State departments of transportation and municipal permittees can use to streamline environmental permitting and project delivery while protecting the environment.
Hydraulic design engineers can use this decision-support tool to establish stormwater-treatment goals for highway construction or improvement projects without having to learn SELDM or interpret its statistical output. The tool is a spreadsheet that determines if a selected highway segment can directly discharge highway runoff, if the highway segment can discharge runoff following treatment using a basic vegetated conveyance best management practice (BMP), or if treatment using an advanced BMP is needed to minimize effects of discharges on downstream water quality. To use the tool, hydraulic design engineers obtain upstream-basin characteristics from the U.S. Geological Survey StreamStats application and highway-site characteristics from preliminary design plans. They then enter these characteristics in the decision-support tool, which identifies the necessary stormwater-treatment goal.
The Piedmont ecoregion was used as a case study to demonstrate the type of information the decision-support tool can provide. In this ecoregion, 100 percent of direct discharges meet the water-quality criterion when the drainage-area ratio is less than about 0.007 acres of highway per square mile of upstream basin. Advanced BMPs are needed in 100 percent of basins with drainage-area ratios greater than about 50 acres per square mile. Between these drainage-area ratios, the selection of direct discharge, a basic vegetated conveyance BMP, or an advanced BMP is a function of highway-site and upstream-basin properties.
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U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Iceland's exposure to major ocean current pathways of the central North Atlantic makes it a useful location for developing long-term proxy records of past marine climate. Such records provide more detailed understanding of the full range of past variability which is necessary to improve predictions of future changes. We constructed a 225-year (1791–2015 CE) master shell growth chronology from 29 shells of Arctica islandica collected at 100 m water depth in southwest Iceland (Faxaflói). The growth chronology provides a robust age model for shell oxygen isotope (δ18Oshell) data produced at annual resolution for 251 years (1765–2015 CE). The temperature reconstruction derived from δ18Oshell shows coherence with May–October local surface temperature records and sea surface temperatures in the North Atlantic region, suggesting it is a useful proxy indicator of water temperature variability at 100 m depth within Faxaflói. Field correlations between the shell-based records and gridded sea surface temperature data reveal strong positive correlations between the 1-year lagged shell growth and temperatures within the subpolar gyre post-1972, suggesting a delayed influence of subpolar gyre dynamics on ecological indicators in southwest Iceland in recent decades. However, the shell growth chronology and δ18Oshell record generally show relatively weak and insignificant correlations with larger region climate indices including the Atlantic Multidecadal Variability, North Atlantic Oscillation, and East Atlantic pattern. Therefore the interannual variations in the newly produced shell-based records appear to reflect more local to regional dynamics around southwest Iceland than large-scale modes of climate variability.
Inland flooding, sea-level rise, and pollution pose challenges for Maine’s infrastructure and natural resources. A highly detailed, three-dimensional (3D) model of the Earth’s surface is allowing the State of Maine to address these challenges in an increasingly comprehensive and timely manner. In addition, highly accurate elevation data facilitate land development, forest management, agricultural practices, and wildlife conservation, all of which are key pillars of Maine’s economy. Critical applications that meet the State’s management needs depend on light detection and ranging (lidar) data that provide a highly detailed 3D model of the Earth’s surface and aboveground features.
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\"}}]}","contact":"Director, National Geospatial Program
U.S. Geological Survey
12201 Sunrise Valley Drive, Mail Stop 511
Reston, VA 20192
Email: 3DEP@usgs.gov
","tableOfContents":"Alaska contains over 130 volcanoes and volcanic fields that have been active within the last 2 million years. Of these, roughly 90 have erupted during the Holocene, with many characterized by at least one large explosive eruption. These large tephra-producing eruptions (LTPEs) generate orders of magnitude more erupted material than a “typical” arc explosive eruption and distribute ash thousands of kilometers from their source. Because LTPEs occur infrequently, and the proximal explosive deposit record in Alaska is generally limited to the Holocene, we require a method that links distal deposits to a source volcano where the correlative proximal deposits from that eruption are no longer preserved. We present a model that accurately and confidently identifies LTPE volcanic sources in the Alaska-Aleutian arc using only in situ geochemistry. The model is a voting ensemble classifier comprised of six conceptually different machine learning algorithms trained on proximal tephra deposits that have had their source positively identified. We show that incompatible trace element ratios (e.g., Nb/U, Th/La, Rb/Sm) help produce a feature space that contains significantly more variance than one produced by major element concentrations, ultimately creating a model that can achieve high accuracy, precision, and recall on predicted volcanic sources, regardless of the perceived 2D data distribution (i.e., bimodal, uniform, normal) or composition (i.e., andesite, trachyte, rhyolite) of that source. Finally, we apply our model to unidentified distal marine tephra deposits in the region to better understand explosive volcanism in the Alaska-Aleutian arc, specifically its pre-Holocene spatiotemporal distribution.
The Cross-Hosgri slope is a bathymetric lineament that crosses the main strand of the Hosgri fault offshore Point Estero, central California. Recently collected chirp seismic reflection profiles and sediment cores provide the basis for a reassessment of Cross-Hosgri slope origin and the lateral slip rate of the Hosgri fault based on offset of the lower slope break of the Cross-Hosgri slope. The Cross-Hosgri slope is comprised of two distinct stratigraphic units. The lower unit (unit 1) overlies the post–Last Glacial Maximum transgressive erosion surface and is interpreted as a Younger Dryas (ca. 12.85–11.65 ka) shoreface deposit based on radiocarbon and optically stimulated luminescence (OSL) ages, Bayesian age modeling, seismic facies, sediment texture, sediment infauna, and heavy mineral component. The shoreface was abandoned and partly eroded during rapid sea-level rise from ca. 11.5 to 7 ka. Unit 2 consists of fine sand and silt deposited in a midshelf environment when the rate of sea-level rise slowed between ca. 7 ka and the present. Although unit 2 provides a thin, relatively uniform cover over the lower slope break of the older shoreface, this feature still represents a valuable piercing point, providing a Hosgri fault slip rate of 2.6 ± 0.8 mm/yr. Full-waveform processing of chirp data resulted in significantly higher resolution in coarser-grained strata, which are typically difficult to interpret with more traditional envelope processing. Our novel combination of offshore radiocarbon and OSL dating is the first application to offshore paleoseismic studies, and our results indicate the utility of this approach for future marine neotectonic investigations.
Context Tidal saline wetlands (TSWs) are highly threatened from climate-change effects of sea-level rise. Studies of TSWs along the East Coast U.S. and elsewhere suggest significant likely losses over coming decades but needed are analytic tools gauged to Pacific Coast U.S. wetlands.
Objectives We predict the impacts of sea-level rise (SLR) on the elevation capital (vertical) and migration potential (lateral) resilience of TSWs along the Pacific Coast U.S. over the period 2020 to 2150 under a 1.5-m SLR scenario, and identified TSWs at risk of most rapid loss of resilience. Here, we define vertical resilience as the amount of elevation capital and lateral resilience as the amount of TSW displacement area relative to existing area.
Methods We used Bayesian network (BN) modeling to predict changes in resilience of TSWs as probabilities which can be useful in risk analysis and risk management. We developed the model using a database sample of 26 TSWs with 147 sediment core samples, among 16 estuary drainage areas along coastal California, Oregon, and Washington.
Results We found that all TSW sites would lose at least 50% of their elevation capital resilience by 2060 to just before 2100, and 100% by 2070 to 2130, depending on the site. Under a 1.5-m sea-level rise scenario, nearly all sites in California will lose most or all of their lateral migration resilience. Resilience losses generally accelerated over time. In the BN model, elevation capital resilience is most sensitive to elevation capital at time t, mean tide level at time t, and change in sea level from time 0 to time t.
Conclusions All TSW sites were projected with declines in resilience. Our model can further aid decision-making such as prioritizing sites for potential management adaptation strategies. We also identified variables most influencing resilience predictions and thus those potentially prioritized for monitoring or development of strategies to prevent loss regionally.
","language":"English","publisher":"Springer","doi":"10.1007/s10980-023-01762-3","usgsCitation":"Marcot, B.G., Thorne, K., Carr, J., and Guntenspergen, G.R., 2023, Foundations of modeling resilience of tidal saline wetlands to sea-level rise along the U.S. Pacific Coast: Landscape Ecology, v. 38, p. 3061-3080, https://doi.org/10.1007/s10980-023-01762-3.","productDescription":"20 p.","startPage":"3061","endPage":"3080","ipdsId":"IP-148063","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":441704,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10980-023-01762-3","text":"Publisher Index Page"},{"id":422365,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Oregon, Washington","otherGeospatial":"Pacific Ocean","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.79508376826595,\n 32.6394986015149\n ],\n [\n -117.38046175678818,\n 33.634263181198776\n ],\n [\n -119.04924372825178,\n 34.47903231583611\n ],\n [\n -120.38379894663998,\n 34.68829360587419\n ],\n [\n -120.39855065841579,\n 35.33926414301449\n ],\n [\n -121.79626050797515,\n 36.460712237169574\n ],\n [\n -121.69218260053856,\n 36.794964571410546\n ],\n [\n -121.93473143542474,\n 37.099336500561904\n ],\n [\n -121.67841132759617,\n 37.4046675213457\n ],\n [\n -122.29904672509281,\n 38.299945698864775\n ],\n [\n -122.73038676825749,\n 38.20384318696074\n ],\n [\n -123.43481358189254,\n 39.0731465550509\n ],\n [\n -124.04491152385293,\n 40.344784634590496\n ],\n [\n -123.71975903545354,\n 41.393830664494715\n ],\n [\n -124.30182241974398,\n 42.756208502734836\n ],\n [\n -123.72352270756943,\n 43.87384063633678\n ],\n [\n -123.69957609415667,\n 46.20564287869419\n ],\n [\n -123.73190708914615,\n 47.01614568390107\n ],\n [\n -124.52407464804097,\n 48.44687072153897\n ],\n [\n -125.07770960477518,\n 48.56365821581798\n ],\n [\n -124.81324633275776,\n 47.69849413178119\n ],\n [\n -124.24511492723724,\n 46.407052517711605\n ],\n [\n -124.64743081974362,\n 43.59326210341467\n ],\n [\n -124.85817977876286,\n 42.61603559520387\n ],\n [\n -124.46177432494142,\n 41.15906667493712\n ],\n [\n -124.73844702893035,\n 40.16919745978089\n ],\n [\n -124.14464449468676,\n 39.63763990789823\n ],\n [\n -124.08963171928053,\n 38.73318027566873\n ],\n [\n -123.05064665424416,\n 37.68717586937068\n ],\n [\n -121.75049102805497,\n 35.902294376643596\n ],\n [\n -120.98156553638233,\n 35.198466337951686\n ],\n [\n -120.87397110810903,\n 34.31747679968289\n ],\n [\n -119.36572913414489,\n 34.05126341484619\n ],\n [\n -117.64709261279006,\n 33.1121239333127\n ],\n [\n -117.2603048744129,\n 32.509262003906\n ],\n [\n -116.79508376826595,\n 32.6394986015149\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"38","noUsgsAuthors":false,"publicationDate":"2023-10-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Marcot, Bruce G.","contributorId":140456,"corporation":false,"usgs":false,"family":"Marcot","given":"Bruce","email":"","middleInitial":"G.","affiliations":[{"id":12647,"text":"U.S. Forest Service, Pacific Northwest Research Station","active":true,"usgs":false}],"preferred":false,"id":887494,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thorne, Karen M. 0000-0002-1381-0657","orcid":"https://orcid.org/0000-0002-1381-0657","contributorId":204579,"corporation":false,"usgs":true,"family":"Thorne","given":"Karen M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":887495,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carr, Joel A. 0000-0002-9164-4156 jcarr@usgs.gov","orcid":"https://orcid.org/0000-0002-9164-4156","contributorId":168645,"corporation":false,"usgs":true,"family":"Carr","given":"Joel A.","email":"jcarr@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":887496,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Guntenspergen, Glenn R. 0000-0002-8593-0244 glenn_guntenspergen@usgs.gov","orcid":"https://orcid.org/0000-0002-8593-0244","contributorId":2885,"corporation":false,"usgs":true,"family":"Guntenspergen","given":"Glenn","email":"glenn_guntenspergen@usgs.gov","middleInitial":"R.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":887497,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70257377,"text":"70257377 - 2023 - Whole-lake acoustic telemetry to evaluate survival of stocked juvenile fish","interactions":[],"lastModifiedDate":"2024-08-21T16:13:36.214575","indexId":"70257377","displayToPublicDate":"2023-11-02T09:00:46","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Whole-lake acoustic telemetry to evaluate survival of stocked juvenile fish","docAbstract":"Estimates of juvenile survival are critical for informing population dynamics and the ecology of fish, yet these demographic parameters are difficult to measure. Here, we demonstrate that advances in animal tracking technology provide opportunities to evaluate survival of juvenile tagged fish. We implemented a whole-lake telemetry array in conjunction with small acoustic tags (including tags < 1.0 g) to track the fate of stocked juvenile cisco (Coregonus artedi) as part of a native species restoration effort in the Finger Lakes region of New York, USA. We used time-to-event modeling to characterize the survival function of stocked fish, where we infer mortality as the cessation of tag detections. Survival estimates revealed distinct stages of juvenile cisco mortality including high immediate post-release mortality, followed by a period of elevated mortality during an acclimation period. By characterizing mortality over time, the whole-lake biotelemetry effort provided information useful for adapting stocking practices that may improve survival of stocked fish, and ultimately the success of the species reintroduction effort. The combination of acoustic technology and time-to-event modeling to inform fish survival may have wide applicability across waterbodies where receiver arrays can be deployed at scale and where basic assumptions about population closure can be satisfied.
","language":"English","publisher":"Springer Nature","doi":"10.1038/s41598-023-46330-6","usgsCitation":"Koeberle, A., Pearsall, W., Hammers, B., Mulhall, D., McKenna Jr., J., Chalupnicki, M., and Sethi, S.A., 2023, Whole-lake acoustic telemetry to evaluate survival of stocked juvenile fish: Scientific Reports, v. 13, e18956, 12 p., https://doi.org/10.1038/s41598-023-46330-6.","productDescription":"e18956, 12 p.","ipdsId":"IP-152742","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":441707,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-023-46330-6","text":"Publisher Index Page"},{"id":433009,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Finger Lakes region, Keuka Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -77.25902648249861,\n 42.667712412436\n ],\n [\n -77.25902648249861,\n 42.40324220590065\n ],\n [\n -77.06119645246562,\n 42.40324220590065\n ],\n [\n -77.06119645246562,\n 42.667712412436\n ],\n [\n -77.25902648249861,\n 42.667712412436\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"13","noUsgsAuthors":false,"publicationDate":"2023-11-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Koeberle, Alexander","contributorId":342552,"corporation":false,"usgs":false,"family":"Koeberle","given":"Alexander","email":"","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":910186,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pearsall, Webster","contributorId":342553,"corporation":false,"usgs":false,"family":"Pearsall","given":"Webster","email":"","affiliations":[{"id":13678,"text":"New York State Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":910187,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hammers, Brad","contributorId":342555,"corporation":false,"usgs":false,"family":"Hammers","given":"Brad","email":"","affiliations":[{"id":13678,"text":"New York State Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":910188,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mulhall, Daniel","contributorId":342558,"corporation":false,"usgs":false,"family":"Mulhall","given":"Daniel","email":"","affiliations":[{"id":13678,"text":"New York State Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":910189,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McKenna Jr., James E. 0000-0002-1428-7597","orcid":"https://orcid.org/0000-0002-1428-7597","contributorId":342562,"corporation":false,"usgs":false,"family":"McKenna Jr.","given":"James E.","affiliations":[{"id":62863,"text":"Great Lakes Science Center","active":true,"usgs":false}],"preferred":false,"id":910190,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chalupnicki, Marc 0000-0002-3792-9345","orcid":"https://orcid.org/0000-0002-3792-9345","contributorId":242991,"corporation":false,"usgs":true,"family":"Chalupnicki","given":"Marc","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":910191,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sethi, Suresh Andrew 0000-0002-9369-487X ssethi@usgs.gov","orcid":"https://orcid.org/0000-0002-9369-487X","contributorId":252537,"corporation":false,"usgs":true,"family":"Sethi","given":"Suresh","email":"ssethi@usgs.gov","middleInitial":"Andrew","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":911332,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70249994,"text":"70249994 - 2023 - Field observations and long short-term memory modeling of spectral wave evolution at living shorelines in Chesapeake Bay, USA","interactions":[],"lastModifiedDate":"2023-11-12T13:51:58.025735","indexId":"70249994","displayToPublicDate":"2023-11-02T07:46:55","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5444,"text":"Applied Ocean Research","active":true,"publicationSubtype":{"id":10}},"title":"Field observations and long short-term memory modeling of spectral wave evolution at living shorelines in Chesapeake Bay, USA","docAbstract":"Living shorelines as a nature-based solution for climate change adaptation were constructed in many places around the world. The success of this type of projects requires long-term monitoring for adaptive management. The paper presents a novel framework leveraging scientific machine learning methods for accurate and rapid prediction of long-term hydrodynamic forcing impacting living shorelines using short-term measurements of water levels and wind waves in the largest estuary in the U.S. Different from existing data-driven wave prediction models focusing on significant wave heights, this study is focused on the prediction of wave energy spectra in shallow water using winds and tides as the input feature and short-term measurements of wave spectra and water depths as the label. Long Short-Term Memory (LSTM) models were developed using four-month wave measurements in the stormy seasons to predict integral wave parameters and energy spectra for multiple years. The developed models accurately predicted wave heights, peak periods, and energy spectra around the living shorelines, capturing complex wave dynamics, such as wave generation by wind, nonlinear wave-wave interactions, and depth-limited wave breaking in the shallow water of a large estuary. The validated models were then used to determine the long-term wave forcing impacting the living shorelines based on the modeled wave characteristics and spectra. Model results show that the surrogate models utilizing LSTM to predict wave spectra in the frequency domain enable long-term predictions of spectral wave evolution with a minimal computational cost. Our findings provide valuable insights into the efficacy of living shorelines in attenuating wave energy and demonstrate the utility of this approach in assessing the effectiveness of such living shoreline structures.
The 6 February 2023 Kahramanmaraş, Turkey (Türkiye), earthquake sequence produced > 500 km of surface rupture primarily on the left‐lateral East Anatolian (~345 km) and Çardak (~175 km) faults. Constraining the length and magnitude of surface displacement on the causative faults is critical for loss estimates, recovery efforts, rapid identification of impacted infrastructure, and fault displacement hazard analysis. To support these efforts, we rapidly mapped the surface rupture from satellite data with support from remote sensing and field teams, and released the results to the public in near‐real time. Detailed surface rupture mapping commenced on 7 February and continued as high‐resolution (< 1.0 m/pixel) optical images from WorldView satellites (2023 Maxar) became available. We interpreted the initial simplified rupture trace from subpixel offset fields derived from Advanced Land Observation Satellite2 and Sentinel‐1A synthetic aperture radar image pairs available on 8 and 10 February, respectively. The mapping was released publicly on 10 February, with frequent updates, and published in final form four months postearthquake (Reitman, Briggs, et al., 2023). This publicly available, rapid mapping helped guide fieldwork and constrained U.S. Geological Survey finite‐fault and loss estimate models, as well as stress change estimates and dynamic rupture models.
The James Tributary Summary outlines change over time for a suite of monitored tidal water quality parameters and associated potential drivers of those trends for the period 1985 – 2021 and provides a brief description of the current state of knowledge explaining these observed changes. Water quality parameters described include surface (above pycnocline) total nitrogen (TN), surface total phosphorus (TP), surface water temperature (WTEMP), spring and summer (June, July, August) surface chlorophyll a, summer bottom (below pycnocline) dissolved oxygen (DO) concentrations, and Secchi disk depth (a measure of water clarity). Results for annual bottom TP, bottom TN, surface ortho-phosphate (PO4), surface dissolved inorganic nitrogen (DIN), surface total suspended solids (TSS), and summer surface DO concentrations are provided in an Appendix. Drivers discussed include physiographic watershed characteristics, changes in TN, TP, and sediment loads from the watershed to tidal waters, expected effects of changing land use, and implementation of nutrient management and natural resource conservation practices. Factors internal to estuarine waters that also play a role as drivers are described including biogeochemical processes, physical forces such as wind-driven mixing of the water column and increase in rainfall intensity and volume, and biological factors such as phytoplankton biomass and the presence of submerged aquatic vegetation. Continuing to track water quality response and investigating these influencing factors are important steps to understanding water quality patterns and changes in the James River. The intended audiences for this report include, but are not limited to, 1) technical managers within jurisdictions who are looking at tidal water quality data and trying to understand why patterns are occurring, 2) local watershed organizations that are trying to understand these analyses and working to connect them to their local area(s), and 3) federal, state, and academic researchers. Figure 1 presents a conceptual model highlighting these intended audiences. Our goal is for the Tributary Summary documents to be sources of readily available background for change over time in tidal water quality observed with monitoring data. The intended purpose of the Tributary Summary documents is to help answer questions related to water quality, show how landscape factors drive water quality change over time, provide support for management decisions that may alter water quality trends and living resources conditions, and highlight where there may be information or knowledge gaps.
","language":"English","publisher":"Chesapeake Bay Program","usgsCitation":"Sullivan, B.M., Gootman, K., Gunnerson, A., Johnson, C., Mason, C.A., Perry, E., Bhatt, G., Keisman, J.L., Webber, J.S., Harcum, J., Lane, M., Devereux, O., Zhang, Q., Murphy, R., Karrh, R., Butler, T., Van Note, V., and Wei, Z., 2023, James Tributary summary: A summary of trends in tidal water quality and associated factors, 1985-2021, 77 p.","productDescription":"77 p.","ipdsId":"IP-155491","costCenters":[{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true},{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":422387,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://www.chesapeakebay.net/who/group/integrated-trends-analysis-team","linkFileType":{"id":5,"text":"html"}},{"id":422427,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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