As the climate evolves over the next century, the interaction of accelerating sea level rise (SLR) and storms, combined with confining development and infrastructure, will place greater stresses on physical, ecological, and human systems along the ocean-land margin. Many of these valued coastal systems could reach “tipping points,” at which hazard exposure substantially increases and threatens the present-day form, function, and viability of communities, infrastructure, and ecosystems. Determining the timing and nature of these tipping points is essential for effective climate adaptation planning. Here we present a multidisciplinary case study from Santa Barbara, California (USA), to identify potential climate change-related tipping points for various coastal systems. This study integrates numerical and statistical models of the climate, ocean water levels, beach and cliff evolution, and two soft sediment ecosystems, sandy beaches and tidal wetlands. We find that tipping points for beaches and wetlands could be reached with just 0.25 m or less of SLR (~ 2050), with > 50% subsequent habitat loss that would degrade overall biodiversity and ecosystem function. In contrast, the largest projected changes in socioeconomic exposure to flooding for five communities in this region are not anticipated until SLR exceeds 0.75 m for daily flooding and 1.5 m for storm-driven flooding (~ 2100 or later). These changes are less acute relative to community totals and do not qualify as tipping points given the adaptive capacity of communities. Nonetheless, the natural and human built systems are interconnected such that the loss of natural system function could negatively impact the quality of life of residents and disrupt the local economy, resulting in indirect socioeconomic impacts long before built infrastructure is directly impacted by flooding.
Light is a primary constraint on primary production and drives many ecological processes in stream ecosystems, yet light regimes have received considerably less attention than other factors of the stream environment, such as hydrology or nutrient cycling. Light received by streams can be highly heterogeneous in both space and time resulting from changes in topography, channel characteristics, and riparian vegetation. Both the structure and phenology of riparian vegetation can be important determinants of the seasonality and magnitude of light reaching the stream surface, particularly in smaller forested streams. Despite the importance of riparian phenology on temporal patterns of stream light availability, existing models do not account for the seasonal dynamics of canopies. We developed a dynamic, biophysically based model (StreamLight) that incorporates canopy structure and phenology to predict light reaching the stream surface. We compared StreamLight to an existing model at 21 sites across the USA and found that, across sites, our biophysically based model produced light estimates that were more strongly correlated to observations and reduced the magnitude of errors in comparison to the existing model, particularly for streams that were relatively narrow compared to the height of riparian vegetation. Because smaller streams represent most global stream length, we expect that, in many smaller forested streams, the inclusion of canopy structure and phenology will enhance our ability to predict light regimes. We also used model simulations to examine the importance of controls on stream light environments and found that channel width was the strongest control on light environments. StreamLight represents an important incremental step forward in developing mechanistic models of river network productivity and in linking shifts in terrestrial vegetation structure and phenology to aquatic ecosystem productivity and thermal regimes.
Methane (CH4) emissions from natural landscapes constitute roughly half of global CH4 contributions to the atmosphere, yet large uncertainties remain in the absolute magnitude and the seasonality of emission quantities and drivers. Eddy covariance (EC) measurements of CH4 flux are ideal for constraining ecosystem-scale CH4 emissions due to quasi-continuous and high-temporal-resolution CH4 flux measurements, coincident carbon dioxide, water, and energy flux measurements, lack of ecosystem disturbance, and increased availability of datasets over the last decade. Here, we (1) describe the newly published dataset, FLUXNET-CH4 Version 1.0, the first open-source global dataset of CH4 EC measurements (available at https://fluxnet.org/data/fluxnet-ch4-community-product/, last access: 7 April 2021). FLUXNET-CH4 includes half-hourly and daily gap-filled and non-gap-filled aggregated CH4 fluxes and meteorological data from 79 sites globally: 42 freshwater wetlands, 6 brackish and saline wetlands, 7 formerly drained ecosystems, 7 rice paddy sites, 2 lakes, and 15 uplands. Then, we (2) evaluate FLUXNET-CH4 representativeness for freshwater wetland coverage globally because the majority of sites in FLUXNET-CH4 Version 1.0 are freshwater wetlands which are a substantial source of total atmospheric CH4 emissions; and (3) we provide the first global estimates of the seasonal variability and seasonality predictors of freshwater wetland CH4 fluxes. Our representativeness analysis suggests that the freshwater wetland sites in the dataset cover global wetland bioclimatic attributes (encompassing energy, moisture, and vegetation-related parameters) in arctic, boreal, and temperate regions but only sparsely cover humid tropical regions. Seasonality metrics of wetland CH4 emissions vary considerably across latitudinal bands. In freshwater wetlands (except those between 20∘ S to 20∘ N) the spring onset of elevated CH4 emissions starts 3 d earlier, and the CH4 emission season lasts 4 d longer, for each degree Celsius increase in mean annual air temperature. On average, the spring onset of increasing CH4 emissions lags behind soil warming by 1 month, with very few sites experiencing increased CH4 emissions prior to the onset of soil warming. In contrast, roughly half of these sites experience the spring onset of rising CH4 emissions prior to the spring increase in gross primary productivity (GPP). The timing of peak summer CH4 emissions does not correlate with the timing for either peak summer temperature or peak GPP. Our results provide seasonality parameters for CH4 modeling and highlight seasonality metrics that cannot be predicted by temperature or GPP (i.e., seasonality of CH4 peak). FLUXNET-CH4 is a powerful new resource for diagnosing and understanding the role of terrestrial ecosystems and climate drivers in the global CH4 cycle, and future additions of sites in tropical ecosystems and site years of data collection will provide added value to this database. All seasonality parameters are available at https://doi.org/10.5281/zenodo.4672601 (Delwiche et al., 2021). Additionally, raw FLUXNET-CH4 data used to extract seasonality parameters can be downloaded from https://fluxnet.org/data/fluxnet-ch4-community-product/ (last access: 7 April 2021), and a complete list of the 79 individual site data DOIs is provided in Table 2 of this paper.
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This outbreak led to the demise of over 50 million domestic birds and occurred mainly during the northward spring migration of adult avian populations.
There have been no experimental examinations of the pathogenesis, transmission, and population impacts of this virus in adult wild waterfowl with varying exposure histories—the most relevant age class.
We captured, housed, and challenged adult wild mallards (Anas platyrhynchos) with HPAIV H5N2 clade 2.3.4.4 and measured viral infection, viral excretion, and transmission to other mallards.
All inoculated birds became infected and excreted moderate amounts of virus, primarily orally, for up to 14 days. Cohoused, uninoculated birds also all became infected. Serological status had no effect on susceptibility. There were no obvious clinical signs of disease, and all birds survived to the end of the study (14 days).
Based on these results, adult mallards are viable hosts of HPAIV H5N2 regardless of prior exposure history and are capable of transporting the virus over short and long distances. These findings have implications for surveillance efforts. The capture and sampling of wild waterfowl in the spring, when most surveillance programs are not operating, are important to consider in the design of future HPAIV surveillance programs.
","language":"English","publisher":"Wiley","doi":"10.1111/irv.12886","usgsCitation":"Hall, J.S., Grear, D.A., Krauss, S., Seiler, P., Dusek, R.J., Nashold, S., and Webster, R., 2021, Highly pathogenic avian influenza virus H5N2 (Clade 2.3.4.4) challenge of mallards age appropriate to the 2015 midwestern poultry outbreak: Influenza and Other Respiratory Viruses, v. 15, no. 6, p. 767-777, https://doi.org/10.1111/irv.12886.","productDescription":"11 p.","startPage":"767","endPage":"777","ipdsId":"IP-126988","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":451359,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/irv.12886","text":"External Repository"},{"id":387814,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Horicon National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.70361328125,\n 43.52465500687185\n ],\n [\n -88.5779571533203,\n 43.526148603236294\n ],\n [\n -88.56834411621094,\n 43.542077996722796\n ],\n [\n -88.6102294921875,\n 43.59133291164543\n ],\n [\n -88.60061645507812,\n 43.628620426937886\n ],\n [\n -88.62876892089844,\n 43.65197548731187\n ],\n [\n -88.66584777832031,\n 43.64949133795468\n ],\n [\n -88.69194030761719,\n 43.625141236940564\n ],\n [\n -88.70361328125,\n 43.58635949637695\n ],\n [\n -88.69194030761719,\n 43.557007981627656\n ],\n [\n -88.68438720703125,\n 43.531624806844356\n ],\n [\n -88.70361328125,\n 43.52465500687185\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"15","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-07-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Hall, Jeffrey S. 0000-0001-5599-2826 jshall@usgs.gov","orcid":"https://orcid.org/0000-0001-5599-2826","contributorId":2254,"corporation":false,"usgs":true,"family":"Hall","given":"Jeffrey","email":"jshall@usgs.gov","middleInitial":"S.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":820847,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grear, Daniel A. 0000-0002-5478-1549 dgrear@usgs.gov","orcid":"https://orcid.org/0000-0002-5478-1549","contributorId":189819,"corporation":false,"usgs":true,"family":"Grear","given":"Daniel","email":"dgrear@usgs.gov","middleInitial":"A.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":820848,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Krauss, Scott","contributorId":190854,"corporation":false,"usgs":false,"family":"Krauss","given":"Scott","email":"","affiliations":[],"preferred":false,"id":820849,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Seiler, Patrick","contributorId":263433,"corporation":false,"usgs":false,"family":"Seiler","given":"Patrick","email":"","affiliations":[{"id":53983,"text":"St. Jude Children’s Research Hospital, Memphis, Tennessee","active":true,"usgs":false}],"preferred":false,"id":820850,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dusek, Robert J. 0000-0001-6177-7479 rdusek@usgs.gov","orcid":"https://orcid.org/0000-0001-6177-7479","contributorId":174374,"corporation":false,"usgs":true,"family":"Dusek","given":"Robert","email":"rdusek@usgs.gov","middleInitial":"J.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":820851,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nashold, Sean 0000-0002-8869-6633","orcid":"https://orcid.org/0000-0002-8869-6633","contributorId":214978,"corporation":false,"usgs":true,"family":"Nashold","given":"Sean","email":"","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":820852,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Webster, Robert G.","contributorId":263434,"corporation":false,"usgs":false,"family":"Webster","given":"Robert G.","affiliations":[{"id":53983,"text":"St. Jude Children’s Research Hospital, Memphis, Tennessee","active":true,"usgs":false}],"preferred":false,"id":820853,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70236722,"text":"70236722 - 2021 - Late Holocene slip rate of the Mojave section of the San Andreas Fault near Palmdale, California","interactions":[],"lastModifiedDate":"2022-09-16T12:28:22.314471","indexId":"70236722","displayToPublicDate":"2021-07-29T07:25:02","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Late Holocene slip rate of the Mojave section of the San Andreas Fault near Palmdale, California","docAbstract":"The geologic slip rate on the Mojave section of the San Andreas fault is poorly constrained, despite its importance for understanding earthquake hazard, apparent discrepancies between geologic and geodetic slip rates along this fault section, and long‐term fault interactions in southern California. Here, we use surficial geologic mapping, excavations, and radiocarbon and luminescence dating to quantify the displacements and ages of late Holocene landforms offset by the fault at three sites. At the Ranch Center site, the slip rate is determined using the base of a fan marking incision and deflection of an ephemeral channel. At the adjacent Key Slide site, the margin of a landslide deposited on indigenous fire hearths provides a minimum rate. At the X‐12 site, the slip rate is determined from a channel that incised into a broad fan surface, and is deflected and beheaded by the fault. We use maximum–minimum bounds on both the displacement and age of each offset feature to calculate slip rate for each site independently. Overlap of the three independent rate ranges yields a rate of 33–39 mm/yr over the last 3 ka, under the assumption that the sites share a common history, given their proximity. Considered in sequence, site‐level epistemic uncertainties in the data permit but do not require a rate increase since ∼1200 cal B.P. Modest rate changes can be explained by aleatory variability in earthquake timing and magnitude; larger changes could suggest a shared regional variation with the Garlock and other faults. The new late Holocene slip rates are consistent with geodetic model estimates that include a viscoelastic crust and earthquake cycle effects. The geologic slip rates also provide average slip over dozens of earthquake cycles—a key constraint for long‐term earthquake rupture forecasts.
The Everglades vulnerability analysis (EVA) is a project led by the U.S. Geological Survey in cooperation with the National Park Service and U.S. Army Corps of Engineers to accomplish one of the science goals of Restoration Coordination & Verification (RECOVER), a multiagency group responsible for providing scientific and technical evaluations and assessments for improving the ability of the Comprehensive Everglades Restoration Plan to restore, preserve, and protect the south Florida ecosystem while providing for the region’s other water-related needs. In 2016, RECOVER acknowledged the need for a tool that could synthesize the decades of Everglades ecosystem science and identify areas vulnerable to changing conditions on the landscape. The EVA tool answers this need through a landscape-scale modeling framework that provides annual responses and relative vulnerability for a suite of indicators of Everglades ecosystem health.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20213033","collaboration":"Prepared in cooperation with the National Park Service and U.S. Army Corps of Engineers","usgsCitation":"D’Acunto, L.E., Romañach, S.S., Haider, S.M., Hackett, C.E., Nestler, J.H., Shinde, D., and Pearlstine, L.G., 2021, The Everglades vulnerability analysis—Integrating ecological models and addressing uncertainty: U.S. Geological Survey Fact Sheet 2021–3033, 4 p., https://doi.org/10.3133/fs20213033.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"Y","ipdsId":"IP-127682","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":387501,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2021/3033/coverthb.jpg"},{"id":387502,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2021/3033/fs20213033.pdf","text":"Report","size":"1.05 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2021–3033"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.859130859375,\n 25.90864446329127\n ],\n [\n -81.49658203125,\n 25.224820176765036\n ],\n [\n -80.88134765625,\n 24.956180020055925\n ],\n [\n -80.2880859375,\n 25.005972656239187\n ],\n [\n -79.815673828125,\n 26.578702269100557\n ],\n [\n -81.968994140625,\n 26.578702269100557\n ],\n [\n -81.859130859375,\n 25.90864446329127\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.694580078125,\n 25.839449402063185\n ],\n [\n -80.68359375,\n 25.839449402063185\n ],\n [\n -80.68359375,\n 25.859223554761407\n ],\n [\n -80.694580078125,\n 25.859223554761407\n ],\n [\n -80.694580078125,\n 25.839449402063185\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Wetland and Aquatic Research Center
U.S. Geological Survey
7920 NW 71st St.
Gainesville, FL 32653
Group-size variation is common in colonially breeding species, including seabirds, whose breeding colonies can vary in size by several orders of magnitude. Seabirds are some of the most threatened marine taxa and understanding the drivers of colony size variation is more important than ever. Reproductive success is an important demographic parameter that can impact colony size, and it varies in association with a number of factors, including nesting habitat quality. Within colonies, seabirds often aggregate into distinct groups or subcolonies that may vary in quality. We used data from two colonies of Adélie penguins 73 km apart on Ross Island, Antarctica, one large and one small to investigate (1) How subcolony habitat characteristics influence reproductive success and (2) How these relationships differ at a small (Cape Royds) and large (Cape Crozier) colony with different terrain characteristics. Subcolonies were characterized using terrain attributes (elevation, slope aspect, slope steepness, wind shelter, flow accumulation), as well group characteristics (area/size, perimeter-to-area ratio, and proximity to nest predators). Reproductive success was higher and less variable at the larger colony while subcolony characteristics explained more of the variance in reproductive success at the small colony. The most important variable influencing subcolony quality at both colonies was perimeter-to-area ratio, likely reflecting the importance of nest predation by south polar skuas along subcolony edges. The small colony contained a higher proportion of edge nests thus higher potential impact from skua nest predation. Stochastic environmental events may facilitate smaller colonies becoming “trapped” by nest predation: a rapid decline in the number of breeding individuals may increase the proportion of edge nests, leading to higher relative nest predation and hindering population recovery. Several terrain covariates were retained in the final models but which variables, the shapes of the relationships, and importance varied between colonies.
","language":"English","publisher":"Nature Publications","doi":"10.1038/s41598-021-94861-7","usgsCitation":"Schmidt, A.E., Ballard, G., Lescroël, A., Dugger, K., Jongsomjit, D., Elrod, M.L., and Ainley, D., 2021, The influence of subcolony-scale nesting habitat on the reproductive success of Adélie penguins: Scientific Reports, v. 11, 15380, 15 p., https://doi.org/10.1038/s41598-021-94861-7.","productDescription":"15380, 15 p.","ipdsId":"IP-105335","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":451374,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-021-94861-7","text":"Publisher Index Page"},{"id":388881,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Antarctica, Cape Crozier, Cape Royds, Ross Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 160.1806640625,\n -78.56048828398782\n ],\n [\n 173.32031249999997,\n -78.56048828398782\n ],\n [\n 173.32031249999997,\n -75.28657817848102\n ],\n [\n 160.1806640625,\n -75.28657817848102\n ],\n [\n 160.1806640625,\n -78.56048828398782\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","noUsgsAuthors":false,"publicationDate":"2021-07-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Schmidt, Annie E.","contributorId":265338,"corporation":false,"usgs":false,"family":"Schmidt","given":"Annie","email":"","middleInitial":"E.","affiliations":[{"id":48619,"text":"pbcs","active":true,"usgs":false}],"preferred":false,"id":822578,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ballard, Grant","contributorId":265339,"corporation":false,"usgs":false,"family":"Ballard","given":"Grant","affiliations":[{"id":48619,"text":"pbcs","active":true,"usgs":false}],"preferred":false,"id":822579,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lescroël, Amélie","contributorId":265340,"corporation":false,"usgs":false,"family":"Lescroël","given":"Amélie","affiliations":[{"id":48619,"text":"pbcs","active":true,"usgs":false}],"preferred":false,"id":822580,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dugger, Katie M. 0000-0002-4148-246X cdugger@usgs.gov","orcid":"https://orcid.org/0000-0002-4148-246X","contributorId":4399,"corporation":false,"usgs":true,"family":"Dugger","given":"Katie","email":"cdugger@usgs.gov","middleInitial":"M.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":822577,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jongsomjit, Dennis","contributorId":265341,"corporation":false,"usgs":false,"family":"Jongsomjit","given":"Dennis","affiliations":[{"id":48619,"text":"pbcs","active":true,"usgs":false}],"preferred":false,"id":822581,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Elrod, Megan L.","contributorId":265342,"corporation":false,"usgs":false,"family":"Elrod","given":"Megan","email":"","middleInitial":"L.","affiliations":[{"id":48619,"text":"pbcs","active":true,"usgs":false}],"preferred":false,"id":822582,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ainley, David G.","contributorId":265343,"corporation":false,"usgs":false,"family":"Ainley","given":"David G.","affiliations":[],"preferred":false,"id":822583,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70222467,"text":"70222467 - 2021 - Timing and hydrological conditions associated with bigheaded carp movement past navigation dams on the upper Mississippi river","interactions":[],"lastModifiedDate":"2021-10-18T14:20:02.027547","indexId":"70222467","displayToPublicDate":"2021-07-28T08:40:45","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Timing and hydrological conditions associated with bigheaded carp movement past navigation dams on the upper Mississippi river","docAbstract":"As the range of non-native bigheaded carps (Hypophthalmichthys spp.) continues to expand throughout river systems of the United States, managers are tasked with preventing or slowing the spread of these invasive species. Main stem navigation dams on the upper Mississippi River, long considered a deterrent to fish migration, may slow or prevent the spread of invasive fish species. As discharge increases, hydraulic head (i.e., difference between upstream elevation and downstream elevation) at these navigation dams decreases, which is believed to allow for easier fish passage. We used acoustic telemetry to investigate the occurrence, frequency, and timing of bigheaded carp passage of upper Mississippi River dams, along with factors related to successful dam passage. During 2013 through 2017, adult silver carp (H. molitrix), bighead carp (H. nobilis) and their hybrids (N = 358) were tracked throughout the upper Mississippi River. A total of 1078 dam passages by bigheaded carps (N = 158) were observed past 15 dams. Seventy-eight percent of dam passages occurred during April through July. Cox proportional hazards regression models indicated that both upstream and downstream dam passages by these species were strongly affected by hydraulic head height at the dam and water temperature, with dam passages increasing as hydraulic head decreased and water temperature increased. A few dams rarely experience low hydraulic head and passages of those dams by bigheaded carps were rare. This information can be used by managers to develop strategies (e.g., placement of deterrent technologies, targeted removal efforts) to slow the spread of these invasive species.
Seismic instruments are highly sensitive and capable of recording a large range of different Earth signals. The high sensitivity of these instruments also makes them prone to various failures. Although many failures are very obvious, such as a dead channel, there are other more subtle failures that easily go unnoticed by both network operators and data users. This work documents several different types of failure modes in which the instrument is no longer faithfully recording ground‐motion data. Although some of these failure modes make the data completely unusable, there are also a number of failures in which the data can still be used for certain applications. Of course, the ideal situation is to identify as soon as possible when data become compromised and to have the network operator fix the station. However, knowing how the data became compromised can also help data users to identify if the data can still be used for their particular application. This work in no way attempts to exhaustively document recording failures but rather to communicate examples and equip the reader with ways of identifying failure modes.
Long-term environmental management to prevent waterfowl population declines is informed by ecology, movement behavior and habitat use patterns. Extrinsic factors, such as human-induced disturbance, can cause behavioral changes which may influence movement and resource needs, driving variation that affects management efficacy. To better understand the relationship between human-based disturbance and animal movement and habitat use, and their potential effects on management, we GPS tracked 15 dabbling ducks in California over ~4-weeks before, during and after the start of a recreational hunting season in October/November 2018. We recorded locations at 2-min intervals across three separate 24-h tracking phases: Phase 1) two weeks before the start of the hunting season (control (undisturbed) movement); Phase 2) the hunting season opening weekend; and Phase 3) a hunting weekend two weeks after opening weekend. We used GLMM models to analyze variation in movement and habitat use under hunting pressure compared with ‘normal’ observed patterns prior to commencement of hunting. We also compared responses to differing levels of disturbance related to the time of day (high - shooting/~daytime); moderate - non-lethal (~crepuscular); and low - night). During opening weekend flight (% time and distance) more than doubled during moderate and low disturbance and increased by ~50% during high disturbance compared with the pre-season weekend. Sanctuary use tripled during moderate and low disturbance and increased ~50% during high disturbance. Two weeks later flight decreased in all disturbance levels but was only less than the pre-season levels during high disturbance. In contrast, sanctuary use only decreased at night, although not to pre-season levels, while daytime doubled from ~45% to >80%. Birds adjust rapidly to disturbance and our results have implications for energetics models that estimate population food requirements. Management would benefit from reassessing the juxtaposition of essential sanctuary and feeding habitats to optimize wetland management for waterfowl.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2021.113170","usgsCitation":"McDuie, F., Lorenz, A., Klinger, R.C., Overton, C.T., Feldheim, C.L., Ackerman, J.T., and Casazza, M.L., 2021, Informing wetland management with waterfowl movement and sanctuary use responses to human-induced disturbance: Journal of Environmental Management, v. 297, 113170, 10 p., https://doi.org/10.1016/j.jenvman.2021.113170.","productDescription":"113170, 10 p.","ipdsId":"IP-124117","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":451383,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jenvman.2021.113170","text":"Publisher Index Page"},{"id":436261,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92N1BBF","text":"USGS data release","linkHelpText":"Waterfowl Disturbance in California and Nevada (2018)"},{"id":387500,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"297","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McDuie, Fiona 0000-0002-1948-5613","orcid":"https://orcid.org/0000-0002-1948-5613","contributorId":222936,"corporation":false,"usgs":true,"family":"McDuie","given":"Fiona","email":"","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":819986,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lorenz, Austen 0000-0003-3657-5941","orcid":"https://orcid.org/0000-0003-3657-5941","contributorId":222610,"corporation":false,"usgs":true,"family":"Lorenz","given":"Austen","email":"","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":819987,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Klinger, Robert C. 0000-0003-3193-3199 rcklinger@usgs.gov","orcid":"https://orcid.org/0000-0003-3193-3199","contributorId":5395,"corporation":false,"usgs":true,"family":"Klinger","given":"Robert","email":"rcklinger@usgs.gov","middleInitial":"C.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":819988,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Overton, Cory T. 0000-0002-5060-7447 coverton@usgs.gov","orcid":"https://orcid.org/0000-0002-5060-7447","contributorId":3262,"corporation":false,"usgs":true,"family":"Overton","given":"Cory","email":"coverton@usgs.gov","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":819989,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Feldheim, Cliff L.","contributorId":206561,"corporation":false,"usgs":false,"family":"Feldheim","given":"Cliff","email":"","middleInitial":"L.","affiliations":[{"id":37342,"text":"California Department of Water Resources","active":true,"usgs":false}],"preferred":false,"id":819990,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":202848,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":819991,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":819992,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70222358,"text":"fs20213041 - 2021 - Water priorities for the Nation—USGS Integrated Water Science basins","interactions":[],"lastModifiedDate":"2021-07-28T11:39:06.407293","indexId":"fs20213041","displayToPublicDate":"2021-07-27T14:40:00","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-3041","displayTitle":"Water Priorities for the Nation—USGS Integrated Water Science Basins","title":"Water priorities for the Nation—USGS Integrated Water Science basins","docAbstract":"The United States faces growing challenges to its water supply, infrastructure, and aquatic ecosystems because of population growth, climate change, floods, and droughts. To help address these challenges, the U.S. Geological Survey Water Resources Mission Area is integrating recent advances in monitoring, research, and modeling to improve assessments of water availability throughout the United States. A key part of this effort is the intensive study of 10 Integrated Water Science (IWS) basins across the Nation between 2019 and 2028.
The goal is to study 10 IWS basins that are representative of large geographic regions across the United States and that encompass a variety of potential threats to the amount and quality of water across the Nation. Lessons learned from these smaller IWS basins (10,000–20,000 square miles in size) about the interactions among climate, human effects, surface water, groundwater, water quality, and water supply and demand will be used to help quantify and forecast water availability in the larger regions and ultimately the Nation.
","language":"English","publisher":"U.S Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20213041","usgsCitation":"Miller, M.P., Eberts, S.M., and Sprague, L.A., 2021, Water priorities for the Nation—USGS Integrated Water Science basins: U.S. Geological Survey Fact Sheet 2021–3041, 2 p., https://doi.org/10.3133/fs20213041.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-124528","costCenters":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true},{"id":38131,"text":"WMA - Office of Planning and Programming","active":true,"usgs":true}],"links":[{"id":387381,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2021/3041/coverthb.jpg"},{"id":387382,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2021/3041/fs20213041.pdf","text":"Report","size":"1.49 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 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12201 Sunrise Valley Drive
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Deep-sea polymetallic nodule mining research activity has substantially increased in recent years, but the expected level of environmental impact is still being established. One environmental concern is the discharge of a sediment plume into the midwater column. We performed a dedicated field study using sediment from the Clarion Clipperton Fracture Zone. The plume was monitored and tracked using both established and novel instrumentation, including acoustic and turbulence measurements. Our field studies reveal that modeling can reliably predict the properties of a midwater plume in the vicinity of the discharge and that sediment aggregation effects are not significant. The plume model is used to drive a numerical simulation of a commercial-scale operation in the Clarion Clipperton Fracture Zone. Key takeaways are that the scale of impact of the plume is notably influenced by the values of environmentally acceptable threshold levels, the quantity of discharged sediment, and the turbulent diffusivity in the Clarion Clipperton Fracture Zone.
Climate change is altering the spatial distribution of many species around the world. In response, we need to identify and protect suitable areas for a large proportion of the fauna so that they persist through time. This exercise must also evaluate the ability of existing protected areas to provide safe havens for species in the context of climate change. Here, we combined passive acoustic monitoring, semi-automatic species identification models, and species distribution models of 21 bird and frog species based on past (1980–1989), present (2005–2014), and future (2040–2060) climate scenarios to determine how species distributions relate to the current distribution of protected areas in Puerto Rico. Species detection/non-detection data were acquired across ~ 700 sampling sites. We developed always-suitable maps that characterized suitable habitats in all three time periods for each species and overlaid these maps to identify regions with high species co-occurrence. These distributions were then compared with the distribution of existing protected areas. We show that Puerto Rico is projected to become dryer by 2040–2060, and precipitation in the warmest quarter was among the most important variables affecting bird and frog distributions. A large portion of always-suitable areas (ASA) is outside of protected areas (> 80%), and the percent of protected areas that overlaps with always-suitable areas is larger for bird (75%) than frog (39%) species. Our results indicate that present protected areas will not suffice to safeguard bird and frog species under climate change; however, the establishment of larger protected areas, buffer zones, and connectivity between protected areas may allow species to find suitable niches to withstand environmental changes.
","language":"English","publisher":"Springer Link","doi":"10.1007/s10531-021-02258-9","usgsCitation":"Campos-Cerqueira, M., Terando, A., Murray, B., Collazo, J.A., and Aide, M., 2021, Climate change is creating a mismatch between protected areas and suitable habitats for frogs and birds in Puerto Rico: Biological Conservation, v. 30, p. 3509-3528, https://doi.org/10.1007/s10531-021-02258-9.","productDescription":"20 p.","startPage":"3509","endPage":"3528","ipdsId":"IP-123023","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":40926,"text":"Southeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":451394,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10531-021-02258-9","text":"Publisher Index Page"},{"id":387778,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Puerto Rico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -67.3077392578125,\n 17.913409288694826\n ],\n [\n -65.58837890625,\n 17.913409288694826\n ],\n [\n -65.58837890625,\n 18.552532366385577\n ],\n [\n -67.3077392578125,\n 18.552532366385577\n ],\n [\n -67.3077392578125,\n 17.913409288694826\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"30","noUsgsAuthors":false,"publicationDate":"2021-07-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Campos-Cerqueira, Marconi","contributorId":261906,"corporation":false,"usgs":false,"family":"Campos-Cerqueira","given":"Marconi","email":"","affiliations":[{"id":53077,"text":"Rainforest Connection","active":true,"usgs":false}],"preferred":false,"id":820742,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Terando, Adam 0000-0002-9280-043X","orcid":"https://orcid.org/0000-0002-9280-043X","contributorId":205908,"corporation":false,"usgs":true,"family":"Terando","given":"Adam","affiliations":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":820743,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Murray, Brent","contributorId":261907,"corporation":false,"usgs":false,"family":"Murray","given":"Brent","email":"","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":820744,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Collazo, Jaime A. 0000-0002-1816-7744","orcid":"https://orcid.org/0000-0002-1816-7744","contributorId":217287,"corporation":false,"usgs":true,"family":"Collazo","given":"Jaime","email":"","middleInitial":"A.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":820745,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Aide, Mitchell","contributorId":261908,"corporation":false,"usgs":false,"family":"Aide","given":"Mitchell","email":"","affiliations":[{"id":38462,"text":"University of Puerto Rico","active":true,"usgs":false}],"preferred":false,"id":820746,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70223149,"text":"70223149 - 2021 - Evaluation of a modified rapid viability-polymerase chain reaction method for Bacillus atrophaeus spores in water matrices","interactions":[],"lastModifiedDate":"2021-08-12T12:33:45.714578","indexId":"70223149","displayToPublicDate":"2021-07-27T07:32:46","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2390,"text":"Journal of Microbiological Methods","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of a modified rapid viability-polymerase chain reaction method for Bacillus atrophaeus spores in water matrices","docAbstract":"A rapid method that provides information on the viability of organisms is needed to protect public health and ensure that remediation efforts following a release of a biological agent are effective. The rapid viability-polymerase chain reaction (RV-PCR) method combines broth culture and molecular methods to provide results on whether viable organisms are present in less than 15 h. In this study, a modified RV-PCR (mRV-PCR) method was compared to a membrane-filtration culture method for the detection of viable Bacillus spores in water matrices. Samples included small and large volumes of chlorine and non‑chlorine treated tap water. Large volume water samples (up to 100 L), were processed by ultrafiltration using a semi-automated waterborne pathogen concentrator, followed by centrifugation as a secondary concentration technique. The concentrated samples were analyzed by mRV-PCR and culture methods. The overall agreement between the mRV-PCR and culture methods when seed concentrations were greater than 10 spores per sample volume analyzed was 96%. The total time from the start of sample processing to the final sample result for the mRV-PCR method was decreased by approximately 2 h, in comparison to the previously published RV-PCR method because of the incorporation of shorter, more efficient primary and secondary concentration steps and a shorter DNA extraction technique. Overall, this study confirmed that RV-PCR is a promising approach for identifying viable Bacillus spores in small- and large-volume water samples and for producing results in less time than traditional culture methods.
Fault friction is central to understanding earthquakes, yet laboratory rock mechanics experiments are restricted to, at most, meter scale. Questions thus remain as to the applicability of measured frictional properties to faulting in situ. In particular, the slip-weakening distance
This article develops global models of damping scaling factors (DSFs) for subduction zone earthquakes that are functions of the damping ratio, spectral period, earthquake magnitude, and distance. The Next Generation Attenuation for subduction earthquakes (NGA-Sub) project has developed the largest uniformly processed database of recorded ground motions to date from seven subduction regions: Alaska, Cascadia, Central America and Mexico, South America, Japan, Taiwan, and New Zealand. NGA-Sub used this database to develop new ground motion models (GMMs) at a reference 5% damping ratio. We worked with the NGA-Sub project team to develop an extended database that includes pseudo-spectral accelerations (PSA) for 11 damping ratios between 0.5% and 30%. We use this database to develop parametric models of DSF for both interface and intraslab subduction earthquakes that can be used to adjust any subduction GMM from a reference 5% damping ratio to other damping ratios. The DSF is strongly influenced by the response spectral shape and the duration of motion; therefore, in addition to the damping ratio, the median DSF model uses spectral period, magnitude, and distance as surrogate predictor variables to capture the effects of the spectral shape and the duration of motion. We also develop parametric models for the standard deviation of DSF. The models presented in this article are for the RotD50 horizontal component of PSA and are compared with the models for shallow crustal earthquakes in active tectonic regions. Some noticeable differences arise from the considerably longer duration of interface records for very large magnitude events and the enriched high-frequency content of intraslab records, compared with shallow crustal earthquakes. Regional differences are discussed by comparing the proposed global models with the data from each subduction region along with recommendations on the applicability of the models.
Understanding interfacial reactions that occur between the active layer and charge-transport layers can extend the stability of perovskite solar cells. In this study, the exposure of methylammonium lead iodide (CH3NH3PbI3) thin films prepared on poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS)-coated glass to 70% relative humidity (R.H.) leads to a perovskite crystal structure change from tetragonal to cubic within 2 days. Interface-sensitive photoluminescence measurements indicate that the structural change originates at the PEDOT:PSS/perovskite interface. During exposure to 30% R.H., the same structural change occurs over a much longer time scale (>200 days), and a reflection consistent with the presence of (CH3)2NH2PbI3 is detected to coexist with the cubic phase by X-ray diffraction pattern. The authors propose that chemical interactions at the PEDOT:PSS/perovskite interface, facilitated by humidity, promote the formation of dimethylammonium, (CH3)2NH2+. The partial A-site substitution of CH3NH3+ for (CH3)2NH2+ to produce a cubic (CH3NH3)1−x[(CH3)2NH2]xPbI3 phase explains the structural change from tetragonal to cubic during short-term humidity exposure. When (CH3)2NH2+ content exceeds its solubility limit in the perovskite during longer humidity exposures, a (CH3)2NH2+-rich, hexagonal phase of (CH3NH3)1−x[(CH3)2NH2]xPbI3 emerges. These interfacial interactions may have consequences for device stability and performance beyond CH3NH3PbI3 model systems and merit close attention from the perovskite research community.
This report addresses system characterization of Planet’s Dove Classic satellites and is part of a series of system characterization reports produced and delivered by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence. These reports present and detail the methodology and procedures for characterization; present technical and operational information about the specific sensing system being evaluated; and provide a summary of test measurements, data retention practices, data analysis results, and conclusions.
Since 2013, Planet has launched more than 360 Dove 3U CubeSats, where U stands for 10-centimeter (cm) x 10-cm x 10-cm stowed dimensions, each weighing about 5 kilograms. Since 2015, all Dove satellites have had four-band imagers with about a 4-meter (m) pixel ground sample distance. Since 2016, all Doves have been launched into Sun-synchronous orbits varying from 474 to 524 kilometers, with inclinations between 97 and 98 degrees. The Dove series satellites do not have orbit maintenance capabilities; thus, their orbits decay slowly over time, contributing to shorter lifetimes of about 3 years. More information on Planet satellites and sensors is available in the “2020 Joint Agency Commercial Imagery Evaluation—Remote Sensing Satellite Compendium” and from the manufacturer at https://www.planet.com/.
The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team completed data analyses to characterize the geometric (interior and exterior), radiometric, and spatial performances. Results of these analyses indicate that Dove Classic has an interior geometric performance in the range of −0.218 (−0.073 pixel) to −0.037 m (−0.012 pixel) in easting and −0.167 (−0.056 pixel) to −0.111 m (−0.037 pixel) in northing in band-to-band registration, an exterior geometric error of −6.841 (−2.280 pixels) in easting and −6.235 m (−2.078 pixels) in northing offset in comparison to Landsat 8 Operational Land Imager, a radiometric performance in the range of −0.057 to −0.010 in offset and 0.963 to 1.298 in slope, and a spatial performance in the range of 2.77 to 3.35 pixels for full width at half maximum, with a modulation transfer function at a Nyquist frequency in the range of 0.003 to 0.010.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211030C","usgsCitation":"Kim, M., Park, S., Anderson, C., and Stensaas, G.L., 2021, System characterization report on Planet’s Dove Classic, chap. C of Ramaseri Chandra, S.N., comp., System characterization of Earth observation sensors: U.S. Geological Survey Open-File Report 2021–1030, 28 p., https://doi.org/10.3133/ofr20211030C.","productDescription":"v, 28 p.","numberOfPages":"38","onlineOnly":"Y","ipdsId":"IP-126677","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":387443,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1030/c/ofr20211030c.pdf","text":"Report","size":"31.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021–1030C"},{"id":387442,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1030/c/coverthb.jpg"}],"contact":"Director, Earth Resources Observation and Science Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
A study was conducted during June–October 2020 to evaluate factors affecting the migration success of adult sockeye salmon (Oncorhynchus nerka) in the Yakima River, Washington. A total of 144 adult sockeye salmon were tagged and released during the study. Most fish (112 fish) were collected, tagged with passive integrated transponder (PIT), and released at the mouth of the Yakima River. The remaining fish were tagged with a radio transmitter and PIT tag: 13 fish were collected, tagged, and released at Prosser Dam; 13 fish were collected and tagged at Prosser Dam, transported downstream, and released at the mouth of the Yakima River; and 6 fish were collected, tagged, and released at the mouth of the Yakima River. Radio-tagged fish released at Prosser Dam initially moved upstream and spread out in the river reach between Prosser and Sunnyside Dams, but all fish stopped moving and several transmitters were recovered. Detection records and temperature data from recovered transmitters were the basis for inferring that avian predators consumed at least 6 of the 13 fish. Fifteen of the 19 radio-tagged sockeye salmon released at the mouth of the Yakima River moved upstream in the Columbia River and were detected at Johnson Island in the Hanford Reach, or at Priest Rapids Dam. Two of these fish, tagged on August 7, eventually moved back downstream and entered the Yakima River when water temperatures in the lower Yakima River were 16–18 degrees Celsius (°C). One fish moved upstream to Sunnyside Dam where its tag was later recovered. The other fish moved farther upstream and was detected at Prosser Dam, but eventually moved downstream and its tag was recovered near Benton City, Washington. None of the recovered tags were found near a carcass. More than one-half of the sockeye salmon that were collected, tagged, and released at the mouth of the Yakima River were subsequently detected, and the greatest proportion of fish from groups released during June, July, and August entered the Yakima River. This finding suggests that adult sockeye salmon are present at the mouth of the Yakima River throughout the summer. Detection records for tagged fish at monitoring sites located near cool water inputs in the lower Yakima River suggest that sockeye salmon do not spend a substantial amount of time at these locations. Fish count data at Prosser Dam fish ladders showed that sockeye salmon had a bi-modal pattern of upstream migration with peaks in late June/early July and September when water temperature in the lower Yakima River was 20 °C or less. Sixty-one percent of PIT-tagged sockeye salmon detected at Prosser Dam were eventually collected at the adult fish trapping facility at Roza Dam where fish are collected and transported upstream to Cle Elum Reservoir. These data, in conjunction with results from other studies, suggest that a substantial proportion of Yakima River sockeye salmon fail to arrive at Roza Dam. Additional research will be required to better understand factors affecting Yakima River sockeye salmon.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211075","collaboration":"Prepared in cooperation with Bureau of Reclamation, Yakama Nation Fisheries, and Washington Department of Fish and Wildlife","usgsCitation":"Kock, T.J., Hansen, A.C., Evans, S.D., Visser, R., Saluskin, B., Matala, A., and Hoffarth, P., 2021, Evaluation of factors affecting migration success of adult sockeye salmon (Oncorhynchus nerka) in the Yakima River, Washington, 2020: U.S. Geological Survey Open-File Report 2021–1075, 30 p., https://doi.org/10.3133/ofr20211075.","productDescription":"vi, 30 p.","onlineOnly":"Y","ipdsId":"IP-128700","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":387441,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1075/ofr20211075.pdf","text":"Report","size":"5.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1075"},{"id":387440,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1075/coverthb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Yakima River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.8770751953125,\n 45.96642454131025\n ],\n [\n -118.67431640625,\n 45.96642454131025\n ],\n [\n -118.67431640625,\n 46.916503267244835\n ],\n [\n -120.8770751953125,\n 46.916503267244835\n ],\n [\n -120.8770751953125,\n 45.96642454131025\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016
1. Migratory waterfowl facilitate long distance dispersal of zoonotic pathogens and are increasingly recognized as contributing to the geographic spread of avian influenza viruses (AIV). AIV are globally distributed and have the potential to produce highly contagious poultry disease, economically impact both large-scale and backyard poultry producers, and raise the specter of epidemics and pandemics in human populations.
2. Because migratory waterfowl behavior varies across multiple spatial and temporal scales, the timing and distribution of wild bird AIV introductions to poultry are also heterogeneous in time and space. To help reduce economic impacts to the poultry industry and enable poultry producers to better anticipate when and where poultry outbreaks may occur, it is critically important to consider the movement ecology of the waterfowl species transporting and transmitting AIV.
3. We used telemetry for a geographically widespread and common AIV host, blue-winged teal (Spatula discors; BWTE), to model reservoir host movement states with respect to backyard and commercial poultry facilities in the United States. Our modeling framework enabled us to estimate wild bird proximity to poultry facilities while concurrently assessing the influence of poultry facilities on BWTE movement state transition. Our primary objective was to estimate the likelihood of duck and poultry overlap by estimating when and where BWTE were geographically closest to poultry.
4. Synthesis and applications. Migratory waterfowl facilitate dispersal of the avian influenza viruses that cause highly contagious poultry disease. Movement analysis of blue-winged teal indicates that spatio-temporal overlap between wild birds and poultry facilities varies by season, the poultry type produced (e.g., turkey, chicken), and if the facility is a commercial or backyard operation. These findings are broadly applicable to disease ecology research and can be applied by poultry producers to improve bio-security, enhance poultry management, and prioritize disease surveillance efforts.
","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2664.13963","usgsCitation":"Humphreys, J.M., Douglas, D.C., Ramey, A.M., Mullinax, J.M., Soos, C., Link, P.T., Walther, P., and Prosser, D., 2021, The spatial-temporal relationship of blue-winged teal to domestic poultry: Movement state modeling of a highly mobile avian influenza host: Journal of Applied Ecology, v. 58, no. 10, p. 2040-2052, https://doi.org/10.1111/1365-2664.13963.","productDescription":"13 p.","startPage":"2040","endPage":"2052","ipdsId":"IP-118863","costCenters":[{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":451405,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2664.13963","text":"Publisher Index Page"},{"id":387599,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"58","issue":"10","noUsgsAuthors":false,"publicationDate":"2021-08-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Humphreys, John M.","contributorId":217932,"corporation":false,"usgs":false,"family":"Humphreys","given":"John","email":"","middleInitial":"M.","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":820044,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Douglas, David C. 0000-0003-0186-1104 ddouglas@usgs.gov","orcid":"https://orcid.org/0000-0003-0186-1104","contributorId":2388,"corporation":false,"usgs":true,"family":"Douglas","given":"David","email":"ddouglas@usgs.gov","middleInitial":"C.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":820046,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ramey, Andrew M. 0000-0002-3601-8400 aramey@usgs.gov","orcid":"https://orcid.org/0000-0002-3601-8400","contributorId":1872,"corporation":false,"usgs":true,"family":"Ramey","given":"Andrew","email":"aramey@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":820045,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mullinax, Jennifer M.","contributorId":221170,"corporation":false,"usgs":false,"family":"Mullinax","given":"Jennifer","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":820047,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Soos, Catherine","contributorId":177909,"corporation":false,"usgs":false,"family":"Soos","given":"Catherine","email":"","affiliations":[],"preferred":false,"id":820048,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Link, Paul T.","contributorId":53611,"corporation":false,"usgs":false,"family":"Link","given":"Paul","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":820049,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Walther, Patrick","contributorId":213915,"corporation":false,"usgs":false,"family":"Walther","given":"Patrick","email":"","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":820050,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Prosser, Diann 0000-0002-5251-1799","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":217931,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":820051,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70223325,"text":"70223325 - 2021 - Modeling the bioavailability of nickel and zinc to Ceriodaphnia dubia and Neocloeon triangulifer in toxicity tests with Natural Waters","interactions":[],"lastModifiedDate":"2021-11-01T15:53:57.560018","indexId":"70223325","displayToPublicDate":"2021-07-23T17:43:28","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Modeling the bioavailability of nickel and zinc to Ceriodaphnia dubia and Neocloeon triangulifer in toxicity tests with Natural Waters","title":"Modeling the bioavailability of nickel and zinc to Ceriodaphnia dubia and Neocloeon triangulifer in toxicity tests with Natural Waters","docAbstract":"We studied biotic ligand model (BLM) predictions of toxicity of nickel (Ni) and zinc (Zn) in natural waters from Illinois and Minnesota USA which had combinations of pH, hardness, and dissolved organic carbon (DOC) more extreme than 99.7% of waters in a nationwide database. We conducted 7-d chronic tests with Ceriodaphnia dubia, and 96-hr acute test and 14-d chronic tests with Neocloeon triangulifer, and estimated LC50s and EC20s for both species. Toxicity of Ni and Zn to both species differed among test waters by factors from 8 (Zn tests with C. dubia) to 35 (Zn tests with N. triangulifer). For both species and metals, tests with Minnesota waters (low pH and hardness, high DOC) showed lower toxicity than Illinois waters (high pH, high hardness, low DOC). Recalibration of the Ni BLM to be more responsive to pH-related changes improved predictions of Ni toxicity, especially for C. dubia. We compared several input data scenarios for the Zn BLM, which generally had minor effects on Model Performance Scores (MPS). A scenario that included inputs of modeled dissolved inorganic carbon and measured Al and Fe(III) produced highest MPS values for tests with both C. dubia and N. triangulifer. Overall, the BLM framework successfully modeled variation in toxicity for both Zn and Ni across wide ranges of water chemistry in tests with both standard and novel test organisms.
","language":"English","publisher":"Society of Environmental Toxicology and Chemistry","doi":"10.1002/etc.5178","usgsCitation":"Besser, J.M., Ivey, C.D., Steevens, J.A., Cleveland, D.M., Soucek, D.J., Dickinson, A., Van Genderen, E.J., Ryan, A.C., Schlekat, C.E., Garman, E., Middleton, E., and Santore, R.C., 2021, Modeling the bioavailability of nickel and zinc to Ceriodaphnia dubia and Neocloeon triangulifer in toxicity tests with Natural Waters: Environmental Toxicology and Chemistry, v. 40, no. 11, p. 3049-3062, https://doi.org/10.1002/etc.5178.","productDescription":"14 p.","startPage":"3049","endPage":"3062","ipdsId":"IP-124650","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":436265,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9GWJRF3","text":"USGS data release","linkHelpText":"Survival, growth and reproduction of C. dubia and N. triangulifer to nickel and zinc exposure in natural waters"},{"id":388396,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois, Minnesota","otherGeospatial":"Keeley Creek, Spoon Creek, Spring Creek, St. Louis River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.2080078125,\n 47.100044694025215\n ],\n [\n -91.23046875,\n 47.100044694025215\n ],\n [\n -91.23046875,\n 48.1367666796927\n ],\n [\n -93.2080078125,\n 48.1367666796927\n ],\n [\n -93.2080078125,\n 47.100044694025215\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.8681640625,\n 40.38002840251183\n ],\n [\n -87.5390625,\n 40.38002840251183\n ],\n [\n -87.5390625,\n 41.541477666790286\n ],\n [\n -89.8681640625,\n 41.541477666790286\n ],\n [\n -89.8681640625,\n 40.38002840251183\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"40","issue":"11","noUsgsAuthors":false,"publicationDate":"2021-07-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Besser, John M. 0000-0002-9464-2244 jbesser@usgs.gov","orcid":"https://orcid.org/0000-0002-9464-2244","contributorId":2073,"corporation":false,"usgs":true,"family":"Besser","given":"John","email":"jbesser@usgs.gov","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":821744,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ivey, Chris D. 0000-0002-0485-7242 civey@usgs.gov","orcid":"https://orcid.org/0000-0002-0485-7242","contributorId":3308,"corporation":false,"usgs":true,"family":"Ivey","given":"Chris","email":"civey@usgs.gov","middleInitial":"D.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":821745,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Steevens, Jeffery A. 0000-0003-3946-1229","orcid":"https://orcid.org/0000-0003-3946-1229","contributorId":207511,"corporation":false,"usgs":true,"family":"Steevens","given":"Jeffery","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":821746,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cleveland, Danielle M. 0000-0003-3880-4584 dcleveland@usgs.gov","orcid":"https://orcid.org/0000-0003-3880-4584","contributorId":187471,"corporation":false,"usgs":true,"family":"Cleveland","given":"Danielle","email":"dcleveland@usgs.gov","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":821747,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Soucek, David J. 0000-0002-7741-0193","orcid":"https://orcid.org/0000-0002-7741-0193","contributorId":224591,"corporation":false,"usgs":false,"family":"Soucek","given":"David","email":"","middleInitial":"J.","affiliations":[{"id":40897,"text":"Illinois Natural History Survey, University of Illinois, Urbana-Champaign, IL","active":true,"usgs":false}],"preferred":false,"id":821748,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dickinson, Amy","contributorId":224592,"corporation":false,"usgs":false,"family":"Dickinson","given":"Amy","email":"","affiliations":[{"id":40897,"text":"Illinois Natural History Survey, University of Illinois, Urbana-Champaign, IL","active":true,"usgs":false}],"preferred":false,"id":821749,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Van Genderen, Eric J.","contributorId":264611,"corporation":false,"usgs":false,"family":"Van Genderen","given":"Eric","email":"","middleInitial":"J.","affiliations":[{"id":54515,"text":"International Zinc Association, Durham NC","active":true,"usgs":false}],"preferred":false,"id":821750,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ryan, Adam C.","contributorId":175564,"corporation":false,"usgs":false,"family":"Ryan","given":"Adam","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":821751,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Schlekat, Chris E.","contributorId":264612,"corporation":false,"usgs":false,"family":"Schlekat","given":"Chris","email":"","middleInitial":"E.","affiliations":[{"id":54516,"text":"NiPERA Inc, Durham NC","active":true,"usgs":false}],"preferred":false,"id":821752,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Garman, Emily R.","contributorId":264613,"corporation":false,"usgs":false,"family":"Garman","given":"Emily R.","affiliations":[{"id":54516,"text":"NiPERA Inc, Durham NC","active":true,"usgs":false}],"preferred":false,"id":821753,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Middleton, Elizabeth 0000-0002-4775-2774","orcid":"https://orcid.org/0000-0002-4775-2774","contributorId":264614,"corporation":false,"usgs":false,"family":"Middleton","given":"Elizabeth","email":"","affiliations":[{"id":54516,"text":"NiPERA Inc, Durham NC","active":true,"usgs":false}],"preferred":false,"id":821754,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Santore, Robert C.","contributorId":202449,"corporation":false,"usgs":false,"family":"Santore","given":"Robert","email":"","middleInitial":"C.","affiliations":[{"id":36447,"text":"Windward Environmental LLC, Syracuse, NY","active":true,"usgs":false}],"preferred":false,"id":821755,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70221896,"text":"sir20215026 - 2021 - Hydrogeology of the Susquehanna River valley-fill aquifer system in the towns of Conklin and Kirkwood, Broome County, New York","interactions":[],"lastModifiedDate":"2024-06-26T19:36:08.52945","indexId":"sir20215026","displayToPublicDate":"2021-07-23T10:10:00","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5026","displayTitle":"Hydrogeology of the Susquehanna River Valley-Fill Aquifer System in the Towns of Conklin and Kirkwood, Broome County, New York","title":"Hydrogeology of the Susquehanna River valley-fill aquifer system in the towns of Conklin and Kirkwood, Broome County, New York","docAbstract":"The hydrogeology of the Susquehanna River valley-fill aquifer system and adjacent areas in south-central Broome County, New York, was investigated in cooperation with the New York State Department of Environmental Conservation. The study area encompasses roughly 55.5 square miles and includes the towns of Conklin and Kirkwood. Multiple small, perhaps discontinuous, valley-fill aquifers of unknown extent and hydraulic interconnection underlie the Susquehanna River valley from easternmost Binghamton south to Riverside, New York, near the Pennsylvania border. The hydrogeologic framework of these aquifers is described in this report on the basis of existing descriptions of surficial materials, especially those related to deglaciation, and subsurface data extracted from well and boring logs. A compilation of surficial geology, the descriptions of the spatial distribution of confined and unconfined aquifers, hydrogeologic sections, and well locations is provided as an oversized map plate and in a U.S. Geological Survey data release.
Residential households are one of the principal consumers of groundwater in the study area. Approximately half of these households are served by public water-supply systems that obtain water from wells, chiefly from highly productive but small and likely discontinuous surficial deposits of sand and gravel, while others obtain water from sand-and-gravel aquifers beneath till and (or) fine-grained lacustrine deposits, and a few from bedrock. Residents outside the public-supply service areas rely on private wells. In till-mantled upland areas, nearly all private wells tap bedrock. Water-resource potential is likely greatest north of Kirkwood Center, New York, where the valley is narrowest, and local aquifers are in thick stratified glacial deposits. Well yields are highest in this part of the valley, and the local aquifer system is likely replenished through induced infiltration from the Susquehanna River and numerous small tributaries. The area between Langdon and Kirkwood is filled with a mixture of stratified and unstratified glacial sediments and contains one high-yield well. This area likely has moderate water-resource potential, but limited well data make this difficult to verify. Well yields from suitable stratified glacial sediments generally decrease southward toward Riverside, New York.
Characterizing potential groundwater resources is also helpful for prioritizing source-water-protection efforts. Water resources throughout New York are at risk of contamination from commercial and industrial surface activities. As in many valley areas throughout the Susquehanna River watershed in south-central New York, valley wells with depths greater than roughly 100 to 150 feet are susceptible to contamination by naturally occurring saltwater and methane. New York currently has a moratorium on hydraulic fracturing, but the study area is underlain by rocks suitable for unconventional methods of gas production that would likely be initiated if the moratorium were to be lifted.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215026","collaboration":"Prepared in cooperation with the New York State Department of Environmental Conservation","usgsCitation":"Van Hoesen, J.G., Heisig, P.M., and Fisher, S.R., 2021, Hydrogeology of the Susquehanna River valley-fill aquifer system in the towns of Conklin and Kirkwood, Broome County, New York: U.S. Geological Survey Scientific Investigations Report 2021–5026, 29 p., 1 pl., https://doi.org/10.3133/sir20215026.","productDescription":"Report: vii, 29 p.; 1 Plate 30.25 x 31.25 inches; Data Release","numberOfPages":"29","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-118763","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":387155,"rank":4,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2021/5026/sir20215026_plate1.pdf","text":"Plate 1","size":"1.82 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Detailed aquifer mapping of the Susquehanna River valley in south-central Broome County, towns of Conklin and Kirkwood, New York"},{"id":387154,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9O1EAV7","text":"USGS data release","linkHelpText":"Digital datasets for the hydrogeology of the Susquehanna River Valley in south-central Broome County, towns of Conklin and Kirkwood, New York"},{"id":387153,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5026/sir20215026.pdf","text":"Report","size":"8.25 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5026"},{"id":387152,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5026/coverthb2.jpg"}],"country":"United States","state":"New York","county":"Broome County","otherGeospatial":"Susquehanna River Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.91690063476561,\n 42.001345689029755\n ],\n [\n -75.74970245361328,\n 42.001345689029755\n ],\n [\n -75.74970245361328,\n 42.08803181932636\n ],\n [\n -75.91690063476561,\n 42.08803181932636\n ],\n [\n -75.91690063476561,\n 42.001345689029755\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180–8349
Forest management guidelines are designed to protect water quality from unintended effects of land use changes such as timber harvest, mining, or forest road construction. Although streams that periodically cease to flow (nonperennial) drain the majority of forested areas, these streams are not consistently included in forest management guidelines. This paper reviews management guidelines for nonperennial (intermittent and ephemeral) streams draining temperate forests in the continental U.S., evaluates potential impacts of land use activities on ecosystem services provided by these streams, and identifies information needed to incorporate nonperennial streams into water quality protection practices. For federally administered lands, national management guidance is deliberately nonprescriptive, deferring to regional and forest-level recommendations for both perennial and nonperennial streams. Most state guidelines recommend riparian management zone (RMZ) protection for perennial streams (48/50 states) and intermittent streams (45/50 states), but only Alaska and West Virginia require RMZs around ephemeral streams. Based on the National Hydrography Dataset, an average of 58% of forested land area in the U.S. drains to nonperennial headwater streams, making these stream types the most common connectors between forested lands and the aquatic system. Land uses that modify flow regimes in these streams can affect sediment and organic matter transport and distribution, stream temperature dynamics, and biogeochemical processing. Nonperennial streams also provide material subsidies to downstream waters and serve as temporary habitats for some aquatic species. However, limited research has examined how forest land uses affect ecosystem services and biota in these streams. Therefore we highlight a set of key questions about nonperennial streams in forests, not the least of which is simply understanding where headwater stream channels are located and associated patterns of flow duration. Although many questions remain, we also note where recent advances in data collection, modeling and process-level research provide opportunities to resolve uncertainties around nonperennial streams in forested landscapes of the continental U.S.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2021.119523","usgsCitation":"Kampf, S.K., Dwyer, K., Fairchild, M.P., Dunham, J.B., Snyder, C.D., Jaeger, K.L., Luce, C., Hammond, J., Wilson, C., Zimmer, M., and Sidell, M., 2021, Managing nonperennial headwater streams in temperate forests of the United States: Forest Ecology and Management, v. 497, 119523, 16 p., https://doi.org/10.1016/j.foreco.2021.119523.","productDescription":"119523, 16 p.","ipdsId":"IP-128255","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":405997,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"geometry\": {\n \"type\": \"MultiPolygon\",\n \"coordinates\": [\n [\n [\n [\n -94.81758,\n 49.38905\n ],\n [\n -94.64,\n 48.84\n 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Kathleen","contributorId":296016,"corporation":false,"usgs":false,"family":"Dwyer","given":"Kathleen","email":"","affiliations":[{"id":16848,"text":"USDA Forest Service, Rocky Mountain Research Station","active":true,"usgs":false}],"preferred":false,"id":850389,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fairchild, Matthew P.","contributorId":196533,"corporation":false,"usgs":false,"family":"Fairchild","given":"Matthew","email":"","middleInitial":"P.","affiliations":[{"id":24595,"text":"USDA Forest Service, Fort Collins CO","active":true,"usgs":false}],"preferred":false,"id":850390,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dunham, Jason B. 0000-0002-6268-0633 jdunham@usgs.gov","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":147808,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","email":"jdunham@usgs.gov","middleInitial":"B.","affiliations":[{"id":365,"text":"Leetown Science 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Lab, Colorado State University","active":true,"usgs":false}],"preferred":false,"id":850396,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Zimmer, Margaret","contributorId":296022,"corporation":false,"usgs":false,"family":"Zimmer","given":"Margaret","affiliations":[{"id":27155,"text":"University of California Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":850397,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Sidell, Marielle","contributorId":296023,"corporation":false,"usgs":false,"family":"Sidell","given":"Marielle","email":"","affiliations":[{"id":63968,"text":"Department of Ecosystem Science and Sustainability, Colorado State University","active":true,"usgs":false}],"preferred":false,"id":850398,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70222612,"text":"70222612 - 2021 - Applying biodiversity metrics as surrogates to a habitat conservation plan","interactions":[],"lastModifiedDate":"2021-08-09T13:40:23.125976","indexId":"70222612","displayToPublicDate":"2021-07-23T08:27:41","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5021,"text":"Environments","active":true,"publicationSubtype":{"id":10}},"title":"Applying biodiversity metrics as surrogates to a habitat conservation plan","docAbstract":"Unabated urbanization has led to environmental degradation and subsequent biodiversity loss across the globe. As an outcome of unmitigated land use, multi-jurisdictional agencies have developed land use plans that attempt to protect threatened or endangered species across selected areas by which some trade-offs between harm to species and additional conservation approaches are allowed among the partnering organizations. Typical conservation plans can be created to focus on single or multiple species, and although they may protect a species or groups of species, they may not account for biodiversity or its protection across the given area. We applied an approach that clustered deductive habitat models for terrestrial vertebrates into metrics that serve as surrogates for biodiversity and relate to ecosystem services. In order to evaluate this process, we collaborated with the partnering agencies who are creating a Multi-Species Habitat Conservation Plan in southern California and compared it to the entire Mojave Desert Ecoregion. We focused on total terrestrial vertebrate species richness and taxon groupings representing amphibians, birds, mammals, and reptiles, and two special status species using the Normalized Index of Biodiversity (NIB). The conservation planning area had a lower NIB and was less species rich than the Mojave Desert Ecoregion, but the Mojave River riparian corridor had a higher NIB and was more species-rich, and while taxon analysis varied across the geographies, this pattern generally held. Additionally, we analyzed desert tortoise (Gopherus agassizii) and desert kit fox (Vulpes macrotis arsipus) as umbrella species and determined that both species are associated with increased NIB and large numbers of species for the conservation area. Our process provided the ability to incorporate value-added surrogate information into a formal land use planning process and used a metric, NIB, which allowed comparison of the various planning areas and geographic units. Although this process has been applied to Apple Valley, CA, and other geographies within the U.S., the approach has practical application for other global biodiversity initiatives.
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