Director, Region 7 - Upper Colorado Basin
U.S. Geological Survey
Denver Federal Center, Bldg. 67
P.O. Box 25046, MS 911
Denver, CO 80225–0046
Species' response to rapid climate change can be measured through shifts in timing of recurring biological events, known as phenology. The Gulf of Maine is one of the most rapidly warming regions of the ocean, and thus an ideal system to study phenological and biological responses to climate change. A better understanding of climate-induced changes in phenology is needed to effectively and adaptively manage human-wildlife conflicts. Using data from a 20+ year marine mammal observation program, we tested the hypothesis that the phenology of large whale habitat use in Cape Cod Bay has changed and is related to regional-scale shifts in the thermal onset of spring. We used a multi-season occupancy model to measure phenological shifts and evaluate trends in the date of peak habitat use for North Atlantic right (Eubalaena glacialis), humpback (Megaptera novaeangliae), and fin (Balaenoptera physalus) whales. The date of peak habitat use shifted by +18.1 days (0.90 days/year) for right whales and +19.1 days (0.96 days/year) for humpback whales. We then evaluated interannual variability in peak habitat use relative to thermal spring transition dates (STD), and hypothesized that right whales, as planktivorous specialist feeders, would exhibit a stronger response to thermal phenology than fin and humpback whales, which are more generalist piscivorous feeders. There was a significant negative effect of western region STD on right whale habitat use, and a significant positive effect of eastern region STD on fin whale habitat use indicating differential responses to spatial seasonal conditions. Protections for threatened and endangered whales have been designed to align with expected phenology of habitat use. Our results show that whales are becoming mismatched with static seasonal management measures through shifts in their timing of habitat use, and they suggest that effective management strategies may need to alter protections as species adapt to climate change.
","language":"English","publisher":"Wiley","doi":"10.1111/gcb.16225","usgsCitation":"Pendleton, D., Tingley, M., Ganley, L., Friedland, K., Mayo, C., Brown, M., McKenna, B., Jordaan, A., and Staudinger, M., 2022, Decadal-scale phenology and seasonal climate drivers of migratory baleen whales in a rapidly warming marine ecosystem: Global Change Biology, v. 28, no. 16, p. 4989-5005, https://doi.org/10.1111/gcb.16225.","productDescription":"17 p.","startPage":"4989","endPage":"5005","ipdsId":"IP-135322","costCenters":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":447501,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/gcb.16225","text":"External Repository"},{"id":402267,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Cape Cod Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.6640625,\n 41.72213058512578\n ],\n [\n -70.02685546875,\n 41.72213058512578\n ],\n [\n -70.02685546875,\n 42.261049162113856\n ],\n [\n -70.6640625,\n 42.261049162113856\n ],\n [\n -70.6640625,\n 41.72213058512578\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"28","issue":"16","noUsgsAuthors":false,"publicationDate":"2022-06-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Pendleton, Dan","contributorId":292480,"corporation":false,"usgs":false,"family":"Pendleton","given":"Dan","email":"","affiliations":[{"id":48127,"text":"Anderson Cabot Center for Marine Life","active":true,"usgs":false}],"preferred":false,"id":844744,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tingley, Morgan","contributorId":292481,"corporation":false,"usgs":false,"family":"Tingley","given":"Morgan","affiliations":[],"preferred":false,"id":844745,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ganley, Laura","contributorId":292482,"corporation":false,"usgs":false,"family":"Ganley","given":"Laura","email":"","affiliations":[],"preferred":false,"id":844746,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Friedland, Kevin","contributorId":292483,"corporation":false,"usgs":false,"family":"Friedland","given":"Kevin","affiliations":[],"preferred":false,"id":844747,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mayo, Charlie","contributorId":292484,"corporation":false,"usgs":false,"family":"Mayo","given":"Charlie","email":"","affiliations":[],"preferred":false,"id":844748,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brown, Moria","contributorId":292485,"corporation":false,"usgs":false,"family":"Brown","given":"Moria","email":"","affiliations":[],"preferred":false,"id":844749,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McKenna, Brigid","contributorId":292486,"corporation":false,"usgs":false,"family":"McKenna","given":"Brigid","email":"","affiliations":[],"preferred":false,"id":844750,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jordaan, Adrian","contributorId":292487,"corporation":false,"usgs":false,"family":"Jordaan","given":"Adrian","affiliations":[],"preferred":false,"id":844751,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Staudinger, Michelle 0000-0002-4535-2005","orcid":"https://orcid.org/0000-0002-4535-2005","contributorId":205971,"corporation":false,"usgs":true,"family":"Staudinger","given":"Michelle","affiliations":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":844752,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70232145,"text":"70232145 - 2022 - Rub tree use and selection by American black bears and grizzly bears in northern Yellowstone National Park","interactions":[],"lastModifiedDate":"2022-06-08T11:47:45.607639","indexId":"70232145","displayToPublicDate":"2022-06-07T06:45:58","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3671,"text":"Ursus","active":true,"publicationSubtype":{"id":10}},"title":"Rub tree use and selection by American black bears and grizzly bears in northern Yellowstone National Park","docAbstract":"Several of the world's bear species exhibit tree-rubbing behavior, which is thought to be a form of scent-marking communication. Many aspects of this behavior remain unexplored, including differences in rub tree selection between sympatric bear species. We compiled rub tree data collected on Yellowstone National Park's Northern Range (USA) and compared rub tree selection of sympatric American black bears (Ursus americanus) and grizzly bears (U. arctos) at local and landscape scales. During 2017 and 2018, we identified 217 rub trees and detected black bears at 117 rub trees and grizzly bears at 18 rub trees, based on genetic analysis of collected hair samples. Rub trees generally were located in areas with gentle slopes and close to existing animal trails. Trees selected by black bears were typically in forested areas, whereas trees selected by grizzly bears were in forested and more open areas. Use of rub trees varied seasonally and between sexes for black bears, but seasonal data were inconclusive for grizzly bears. Black bears showed preferences for certain tree species for rubbing, but we did not find evidence that rub tree selection by grizzly bears differed among tree species. Both bear species selected trees that lacked branches on the lower portions of tree trunks and the maximum rub height was consistent with the body length of the bear species that used the tree. Although the sample size for grizzly bears was small, identifying the species and sex of bears based on genetic analysis enhanced interpretation of rub tree use and selection by bears. Scent-marking by black bears and grizzly bears on similar rub objects in well-traversed areas likely serves to enhance communication within and between the 2 species.
Under-representations of headwater channels in digital stream networks can result in uncertainty in the magnitude of headwater habitat loss, stream burial, and watershed function. Increased availability of high-resolution (<2 m) elevation data makes the delineation of headwater channels more attainable. In this study, elevation data derived from light detection and ranging was used to predict ephemeral stream networks across a forested and urban watershed in the Maryland Piedmont USA. A method was developed using topographic openness (TO) and wetness index to remotely predict the extent of stream networks. Predicted networks were compared against a comprehensive field survey of the ephemeral network in each watershed to evaluate performance. Comparisons were also made to the U.S. Geological Survey National Hydrography Dataset (NHD) and a flow accumulation approach where a single drainage area threshold defined channel initiation. Although the NHD and flow accumulation methods resulted in low commission errors, omission errors were highest in these networks. The TO-based networks detected a larger number of ephemeral channels, but with higher commission error. Small ephemeral channels with less defined banks or originating at groundwater seeps were difficult to detect in all methods. Comparisons between forested and urban watersheds also highlight the difficulty of identifying headwater channels using topographic attributes in human-modified landscapes.
The Willamette River, Oregon, is home to two salmonid species listed as threatened under the Endangered Species Act, Upper WIllamette River spring Chinook salmon (Oncorhynchus tshawytscha) and Upper Willamette River winter steelhead (O. mykiss). Streamflow in the Willamette River is regulated by upstream dams, 13 of which are operated by the U.S. Army Corps of Engineers (USACE) as part of the Willamette Valley Project. In 2008, these dams were determined to have a deleterious effect on Endangered Species Act-listed salmonids, resulting in USACE taking actions to mitigate those effects. Mitigation actions included setting seasonal streamflow targets at various locations along the river to improve survival and migration of juvenile salmonids. Although these targets were established with the best available information at the time, recent data and models have advanced understanding of Willamette River bathymetric, hydraulic, and thermal conditions, allowing for a more robust analysis of the effect of streamflow on downstream habitat. This study integrates those recent advances to build high-resolution models of usable habitat for juvenile Chinook salmon and steelhead to assess variation in spatial and seasonal patterns of habitat availability. Specifically, this study develops detailed maps of habitat availability for juvenile Chinook salmon and steelhead for two size classes (fry and pre-smolt). Habitat availability is modeled in a three-step process whereby (1) two-dimensional hydraulic models are paired with literature-supplied data on habitat preferences to create spatially explicit maps of rearing habitats for a wide range of streamflows; (2) reach-specific relations between streamflow and habitat area are developed and paired with streamgage records to create habitat time series for 2011, 2015, and 2016, which reflect “cool and wet,” “hot and dry,” and “warm but average precipitation” conditions, respectively; (3) temperature models are coupled with literature-based thermal thresholds to determine time periods and locations along the river corridor when rearing habitat has optimal, harmful, or lethal temperature conditions; (4) finally, habitat availability is summarized at several spatial scales to characterize longitudinal and seasonal patterns.
Findings show that modeled area of rearing habitat for Chinook salmon and steelhead responds non-uniformly to streamflow, where habitat in some reaches of the Willamette River consistently increase with additional streamflow, while in other reaches, habitat area decreases when streamflows increase from low to moderate flows. Modeled differences in flow-habitat relations are primarily explained by local geomorphology in each reach and resulting hydraulic conditions that arise with different streamflows. These are most pronounced when comparing laterally active, multi-channel reaches upstream from Corvallis with downstream reaches that are laterally stable with single-channel planforms. The reaches upstream from Corvallis generally have more habitat available per unit stream distance than downstream reaches, but all reaches display greatest amounts of habitat at the highest streamflows. Finally, results show that warm water temperature in summer greatly decreases the utility of habitat available to the focal species, particularly downstream from Corvallis. Together, these findings serve to inform flow management by characterizing spatial and seasonal patterns of habitat availability for juvenile spring Chinook salmon and winter steelhead and provide a quantitative assessment of the effects of streamflow on rearing habitat.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225034","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"White, J.S., Peterson, J.T., Stratton Garvin, L.E., Kock, T.J., and Wallick, J.R., 2022, Assessment of habitat availability for juvenile Chinook salmon (Oncorhynchus tshawytscha) and steelhead (O. mykiss) in the Willamette River, Oregon: U.S. Geological Survey Scientific Investigations Report 2022–5034, 44 p., https://doi.org/10.3133/sir20225034.","productDescription":"viii, 44 p.","onlineOnly":"Y","ipdsId":"IP-130018","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":401758,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5034/coverthb.jpg"},{"id":401759,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5034/sir20225034.pdf","text":"Report","size":"13.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5034"}],"country":"United States","state":"Oregon","otherGeospatial":"Willamette River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.40942382812501,\n 44.05995928349327\n ],\n [\n -122.2943115234375,\n 44.05995928349327\n ],\n [\n -122.2943115234375,\n 45.66780526567164\n ],\n [\n -123.40942382812501,\n 45.66780526567164\n ],\n [\n -123.40942382812501,\n 44.05995928349327\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
Mechanistic river models capable of simulating hydrodynamics and stream temperature are valuable tools for investigating thermal conditions and their relation to streamflow in river basins where upstream water storage and management decisions have an important influence on river reaches with threatened fish populations. In the Willamette River Basin in northwestern Oregon, a two-dimensional, hydrodynamic water-quality model (CE‑QUAL‑W2) has been used to investigate the downstream effects of dam operations and other anthropogenic influences on stream temperature. By simulating the managed releases of water and various temperatures from the large Willamette Valley Project dams upstream of the modeling domain, these models can be used to investigate riverine temperature conditions and their relation to streamflow to determine where and when conditions are most challenging for threatened fish populations and how dam operations and flow management can affect and optimize thermal conditions in the river.
The original models were initially developed to simulate conditions in spring–autumn of 2001 and 2002. This report documents (1) the upgrade of the river models to CE‑QUAL‑W2 version 4.2 and (2) the update of those models to simulate conditions that occurred from March through October of 2011, 2015, and 2016. These years were selected to represent a range of climatic and hydrologic conditions in the Willamette River Basin, including a “cool, wet” year (2011), a “hot, dry” year (2015), and a “normal” year (2016). Six submodels comprise the modeling system updated in this report; each submodel can be run independently or run with the others as a system. These models include the Coast Fork and Middle Fork Willamette River submodel, which includes the Coast Fork and Middle Fork Willamette Rivers, the Row River, and Fall Creek; the McKenzie River submodel, which includes the South Fork McKenzie River downstream of Cougar Dam and the McKenzie River from its confluence with the South Fork McKenzie River to its mouth; the South Santiam River submodel, which comprises the South Santiam River from Foster Dam to the Santiam River; the North Santiam and Santiam River submodel, which includes the Santiam River and the North Santiam River downstream of Big Cliff Dam; the Upper Willamette River submodel, which includes the Willamette River from Eugene to Salem; and the Middle Willamette River submodel, which includes the Willamette River from Salem to Willamette Falls near Oregon City.
The models included in this report were originally developed, calibrated, and documented by other researchers. As part of the model updates described here, some model parameters were adjusted to improve stability and decrease runtime. Boundary conditions including meteorological, hydrologic, and thermal parameters were developed and updated for model years 2011, 2015, and 2016. In many cases, the data sources used to drive the 2001 and 2002 models were no longer available, which required the use of new data sources, the determination of a proxy record, or the development of appropriate estimation techniques. Goodness-of-fit statistics for the updated models show a good model fit, with the models simulating subdaily water temperatures at most comparable locations with a mean absolute error of generally less than 1 °C and often nearing 0.5 °C, depending on the individual submodel, and a reasonably low bias. The subdaily mean error for the South Santiam River submodel produced the highest bias of any of the submodels. Goodness-of-fit statistics indicate that the results may be biased cool (ranging from -0.43 °C in 2016 to -0.80 °C in 2011 for subdaily results), but the only water temperature data available for comparison on the South Santiam River is itself estimated, and those estimates are known to be too high in summer. Depending on future modeling needs, that submodel may warrant further refinement, along with additional data collection to properly define and minimize any model bias.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221017","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Portland District","usgsCitation":"Stratton Garvin, L.E., Rounds, S.A., and Buccola, N.L., 2022, Updates to models of streamflow and water temperature for 2011, 2015, and 2016 in rivers of the Willamette River Basin, Oregon: U.S. Geological Survey Open-File Report 2022–1017, 73 p., https://doi.org/10.3133/ofr20221017.","productDescription":"Report: x, 73 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-119723","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":401872,"rank":8,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1017/ofr20221017.XML"},{"id":401871,"rank":7,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1017/images"},{"id":401815,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20225035","text":"SIR 2022-5035 —","linkHelpText":"The thermal landscape of the Willamette River—Patterns and controls on stream temperature and implications for flow management and cold-water salmonids"},{"id":401814,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20225034","text":"SIR 2022-5034 —","linkHelpText":"Assessment of habitat availability for juvenile Chinook salmon (Oncorhynchus tshawytscha) and steelhead (O. mykiss) in the Willamette River, Oregon"},{"id":501762,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113157.htm","linkFileType":{"id":5,"text":"html"}},{"id":401754,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1017/coverthb.jpg"},{"id":401755,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1017/ofr20221017.pdf","text":"Report","size":"10.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1017"},{"id":401756,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P908DXKH","text":"USGS data release","description":"USGS data release","linkHelpText":"CE-QUAL-W2 models for the Willamette River and major tributaries below U.S. Army Corps of Engineers dams—2011, 2015, and 2016"},{"id":401813,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20225006","text":"SIR 2022-5006 —","linkHelpText":"Tracking heat in the Willamette River system, Oregon"}],"country":"United States","state":"Oregon","otherGeospatial":"Willamette River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.134765625,\n 42.779275360241904\n ],\n [\n -120.673828125,\n 42.779275360241904\n ],\n [\n -120.673828125,\n 45.9511496866914\n ],\n [\n -123.134765625,\n 45.9511496866914\n ],\n [\n -123.134765625,\n 42.779275360241904\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
The Stibnite mining area, as used herein, is bounded by the map extent that includes the Yellow Pine, West End, and Hangar Flats ore bodies. Other ore bodies are nearby, but the purpose of this map is to offer a detailed (1:8,000 scale) geologic map with new cross sections in the immediate area of Stibnite, Idaho. This geologic map is very similar to the Stibnite quadrangle map (Stewart and others, 2016) particularly the units and structure descriptions, because of the overlap of map extent. The new work by the author includes: (1) the topographic lines generated from the LiDAR base (courtesy of Midas Gold Corporation); (2) additional structural measurements; (3) revision of geologic unit contact placements particular around West End and Stibnite pits among other locations; and (4) seven new cross sections. New structural measurements from field work account for 20 percent of measurements shown with the remaining from Midas Gold Corp., Smitherman (1985), and the Stibnite quadrangle map (Stewart and others, 2016). Locations of many shallow features in the cross sections are controlled by core logs of 48 drillholes provided by Midas Gold Corp. The logs include dike placement, dike to plutonic bodies relationships, metasedimentary body localities, and dips of stratigraphic units. The law of sines was used to calculate dip of contacts between metasedimentary units for each cross section. Other features at depth in the cross sections are schematic based on nearby surface features and overall geologic interpretation.
The map area contains metamorphosed sediments of Neoproterozoic and Paleozoic age within the Stibnite roof pendant. This rock package is open to tightly folded and reached lower amphibolite facies metamorphism during the Cretaceous Period. Most of the metasedimentary rocks are nearly vertical to overturned and young to the southwest, except on the southwestern flank of the Garnet Creek syncline. Pulses of the Idaho batholith granitoids intruded the metasedimentary units found in the Stibnite roof pendant. Faulting with apparent reverse, normal, and/or strike-slip offset are all present within the map area. Mineralization is largely fault controlled with some stratigraphic control. Volumetrically minor dikes, sills, and small intrusions are of Eocene age, and these intrusions are mostly depicted on the cross sections. Quaternary surficial deposits occur in stream beds and glaciated areas.
Field work was conducted during the summers of 2013, 2015, and 2016. For consistency with recent research, most of the Stibnite quadrangle geologic map units (Stewart and others, 2016) are used for this geologic map. Intrusive units Kqd and Tba are new. The additional geologic mapping by the authors and compilation of detailed geologic maps from Midas Gold Corp. enhanced resolution. Cross sections incorporated drill core data including rock type, unit thickness, and oriented structural measurements offering detailed subsurface control. Data access was courtesy of Midas Gold Corp. Reed S. Lewis, Russell V. Di Fiori, and Claudio Berti provided constructive reviews that significantly improved this maps and cross sections. Previous studies that focus on mineralization include Schrader and Ross (1925), Currier (1935), White (1940), Cooper (1951), Cookro and others (1988), and more recently Gillerman and others (2019). Digital map files are available online (Wintzer, 2022).
","language":"English","publisher":"Idaho Geological Survey","usgsCitation":"Wintzer, N.E., 2022, Geologic map of the Stibnite mining area, Valley County, Idaho: Technical Report T-22-03, 2 Plates: 45.48 x 30.06 inches and 49.17 x 36.00 inches.","productDescription":"2 Plates: 45.48 x 30.06 inches and 49.17 x 36.00 inches","ipdsId":"IP-135563","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":402158,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":401908,"type":{"id":15,"text":"Index Page"},"url":"https://idahogeology.org/product/T-22-03","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Idaho","otherGeospatial":"Stibnite mining area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.3,\n 44.9\n ],\n [\n -115.341667,\n 44.9\n ],\n [\n -115.341667,\n 44.936111\n ],\n [\n -115.3,\n 44.936111\n ],\n [\n -115.3,\n 44.9\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wintzer, Niki E. 0000-0003-3085-435X nwintzer@usgs.gov","orcid":"https://orcid.org/0000-0003-3085-435X","contributorId":5297,"corporation":false,"usgs":true,"family":"Wintzer","given":"Niki","email":"nwintzer@usgs.gov","middleInitial":"E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":844339,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70232530,"text":"70232530 - 2022 - Subspecies differentiation and range-wide genetic structure are driven by climate in the California gnatcatcher, a flagship species for coastal sage scrub conservation","interactions":[],"lastModifiedDate":"2022-08-02T15:07:24.562089","indexId":"70232530","displayToPublicDate":"2022-06-06T07:19:52","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1601,"text":"Evolutionary Applications","active":true,"publicationSubtype":{"id":10}},"title":"Subspecies differentiation and range-wide genetic structure are driven by climate in the California gnatcatcher, a flagship species for coastal sage scrub conservation","docAbstract":"Understanding genetic structure and diversity within species can uncover associations with environmental and geographic attributes that highlight adaptive potential and inform conservation and management. The California gnatcatcher, Polioptila californica, is a small songbird found in desert and coastal scrub habitats from the southern end of Baja California Sur to Ventura County, California. Lack of congruence among morphological subspecies hypotheses and lack of measurable genetic structure found in a few genetic markers led to questions about the validity of subspecies within P. californica and the listing status of the coastal California gnatcatcher, P. c. californica. As a U.S. federally threatened subspecies, P. c. californica is recognized as a flagship for coastal sage scrub conservation throughout southern California. We used restriction site-associated DNA sequencing to develop a genomic dataset for the California gnatcatcher. We sampled throughout the species' range, examined genetic structure, gene–environment associations, and demographic history, and tested for concordance between genetic structure and morphological subspecies groups. Our data support two distinct genetic groups with evidence of restricted movement and gene flow near the U.S.- Mexico international border. We found that climate-associated outlier loci were more strongly differentiated than climate neutral loci, suggesting that local climate adaptation may have helped to drive differentiation after Holocene range expansions. Patterns of habitat loss and fragmentation are also concordant with genetic substructure throughout the southern California portion of the range. Finally, our genetic data supported the morphologically defined P. c. californica as a distinct group, but there was little evidence of genetic differentiation among other previously hypothesized subspecies in Baja California. Our data suggest that retaining and restoring connectivity, and protecting populations, particularly at the northern range edge, could help preserve existing adaptive potential to allow for future range expansion and long-term persistence of the California gnatcatcher.
Director, Northern Prairie Wildlife Research Center
U.S. Geological Survey
8711 37th Street Southeast
Jamestown, ND 58401
Human activities (e.g., shipping, tourism, oil, gas development) have increased in the Chukchi Sea because of declining sea ice. The declining sea ice itself and these activities may affect Pacific walrus (Odobenus rosmarus divergens) abundance; however, previous walrus abundance estimates have been notably imprecise. When sea ice is absent from the eastern Chukchi Sea, walruses in waters of the United States usually rest together onshore at a single Alaska coastal haulout, where they can be surveyed more easily than when they rest on dispersed offshore ice floes. We estimated the number of walruses on land (herd size) at this haulout from 13 unoccupied aircraft system (UAS) surveys flown within a 10-day period in each of 2018 and 2019. We estimated population size of walruses using the haulout over the course of the surveys by combining herd size data with data from satellite-linked transmitters that indicated whether tagged walruses were in or out of water during each survey. Our estimates of the population size of walruses using the haulout during each year's survey period were similar to each other and more precise than historical walrus abundance estimates: posterior means (95% credibility intervals) were 166,000 (133,000–201,000) for 2018 and 189,000 (135,000–251,000) for 2019. Auxiliary observations support using these estimates to represent the size of the population using the eastern Chukchi Sea in autumn during the surveyed years. Our study site was the only substantial Chukchi Sea coastal haulout in the United States during the survey periods and study-specific tracking data (consistent with known distribution and movement patterns) indicated tagged walruses remained in eastern Chukchi waters during the survey periods. In addition, the imagery, telemetry, and analytical methods developed for this study advance the prospect for precise range-wide walrus population size estimates.
Cataloguing damage and its correlation with hazard intensity is one of the key components needed to robustly assess future risk and plan for mitigation as it provides important empirical data. Damage assessments following volcanic eruptions have been conducted for buildings and other structures following hazards such as tephra fall, pyroclastic density currents, and lahars. However, there are relatively limited quantitative descriptions of the damage caused by lava flows, despite the number of communities that have been devastated by lava flows in recent decades (e.g., Cumbre Vieja, La Palma, 2021; Nyiragongo, Democratic Republic of Congo, 2002 and 2021; Fogo, Cape Verde, 2014–2015). The 2018 lower East Rift Zone (LERZ) lava flows of Kīlauea volcano, Hawaiʻi, inundated 32.4 km2 of land in the Puna District, including residential properties, infrastructure, and farmland. During and after the eruption, US Geological Survey scientists and collaborators took over 8000 aerial and ground photographs and videos of the eruption processes, deposits, and impacts. This reconnaissance created one of the largest available impact datasets documenting an effusive eruption and provided a unique opportunity to conduct a comprehensive damage assessment. Drawing on this georeferenced dataset, satellite imagery, and 2019 ground-based damage surveys, we assessed the pre-event typology and post-event condition of structures within and adjacent to the area inundated by lava flows during the 2018 LERZ eruption. We created a database of damage: each structure was assigned a newly developed damage state and data quality category value. We assessed 3165 structures within the Puna District and classified 1839 structures (58%) as destroyed, 90 structures (3%) as damaged, and 1236 (39%) as unaffected. We observed a range of damage states, affected by the structural typology and hazard characteristics. Our study reveals that structures may be damaged or destroyed beyond the lava flow margin, due to thermal effects from the lava flow, fire spread, or from exposure to a range of hazards associated with fissure eruptions, such as steam, volcanic gases, or tephra fall. This study provides a major contribution to the currently limited evidence base required to forecast future lava flow impacts and assess risk.
Food insecurity continues to grow in Sub-Saharan Africa (SSA). In 2019, chronically malnourished people numbered nearly 240 million, or 20% of the population in SSA. Globally, numerous efforts have been made to anticipate potential droughts, crop conditions, and food shortages in order to improve early warning and risk management for food insecurity. To support this goal, we develop an Earth Observation (EO) and machine-learning-based operational, subnational maize yield forecast system and evaluate its out-of-sample forecast skills during the growing seasons for Kenya, Somalia, Malawi, and Burkina Faso. In general, forecast skills improve substantially during the vegetative growth period (VP) and gradually during the reproductive development period (RP). Thus, mid-season assessment can provide effective early warning months before harvest. Skillful forecasts (Nash Sutcliffe Efficiency (NSE) > 0.6 and Mean Absolute Percentage Error (MAPE) < 20%) appear approximately two dekads after the VP; for example, skillful forecasts appear in May in Kenya and Somalia, January in Malawi, and July in Burkina Faso. During model development, effective EO features are also identified, such as precipitation and available water during VP, and dry days and extreme temperatures in early VP. Compared to monthly standard EO features, sub-monthly (dekadal), non-standard, and serial EO features significantly improve forecast skills by ＋ 0.3 NSE and -10% of MAPE, demonstrating the ability to precisely and effectively capture favorable or detrimental crop development conditions. Finally, skillful forecasts and practical utility are demonstrated in the recent normal and dry years in each region. Overall, the developed yield forecasting system can provide skillful predictions during the growing season, supporting regional and international agricultural decision-making processes, including informing food-security planning and management, thereby helping to mitigate food shortages caused by unfavorable climate conditions.
Temperate-breeding Canada Goose (Branta canadensis maxima) abundance has increased to previously unrecorded levels, providing social, ecological, and economic value. However, there are also costs associated with abundant Canada Geese. Although hunter harvest is a valued, sustainable use of Canada Geese, the adaptability of geese to urban areas may result in lower susceptibility of geese to hunters, potentially reducing the contribution of hunter harvest to conflict reduction. Our goal was to compare movement of geese marked in urban and rural areas to assess efficacy of hunter harvest in managing urban goose populations. We marked 71 adult female Canada Geese during brood-rearing with GPS-GSM transmitters in urban (n = 45) and rural (n = 26) locations in Iowa, USA to monitor movement during the 2018-19 and 2019-20 Mississippi Flyway goose hunting season frameworks. We estimated the mean proportion of locations each group was available for hunter harvest and examined factors affecting home range areas using generalized linear mixed models. Additionally, we estimated habitat selection of urban- and rural-marked geese using a step-selection analysis. Urban geese had a lower proportion of locations in areas available to hunters (0.07 [95% CI: 0.04-0.13]) than rural geese (0.56 [95% CI: 0.34-0.76]), but median home range area was similar for each group and decreased in size from autumn to late winter. Canada Geese marked in urban areas were more likely to select developed areas and less likely to select wetlands than rural geese, and they had high selection of agricultural fields within city limits during goose hunting seasons. Although Canada Geese breeding in urban areas may be less available for hunter harvest, movement data show when and where opportunity exists to increase harvest susceptibility. Canada Goose management could require actions in addition to hunter harvest to achieve goals in urban areas.
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\"}}]}","volume":"17","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Luukkonen, Benjamin Z.","contributorId":348730,"corporation":false,"usgs":false,"family":"Luukkonen","given":"Benjamin Z.","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":923723,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Klaver, Robert W. 0000-0002-3263-9701 bklaver@usgs.gov","orcid":"https://orcid.org/0000-0002-3263-9701","contributorId":3285,"corporation":false,"usgs":true,"family":"Klaver","given":"Robert","email":"bklaver@usgs.gov","middleInitial":"W.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":923724,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jones III, Orrin E.","contributorId":348731,"corporation":false,"usgs":false,"family":"Jones III","given":"Orrin E.","affiliations":[{"id":24495,"text":"Iowa Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":923725,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70236537,"text":"70236537 - 2022 - Evidence of alternative trophic pathways for fish consumers in a large river system in the face of invasion","interactions":[],"lastModifiedDate":"2022-09-09T12:08:10.245228","indexId":"70236537","displayToPublicDate":"2022-06-05T07:06:10","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Evidence of alternative trophic pathways for fish consumers in a large river system in the face of invasion","docAbstract":"Large rivers are susceptible to anthropogenic alteration, which can result in drastic changes to their functional ecology. We evaluated spatial–temporal changes in the functional fish communities of the Upper Mississippi River System (UMRS) using data from six study reaches. Species were classified into one of 14 feeding guilds and mass per unit effort (MPUE) was then calculated for each feeding guild annually per gear type. MPUE was standardized using the multigear mean standardization method (MGMS) and log-transformed. Both ANOSIM and Chi-square tests were used to determine differences in MPUE among reaches. We then estimated functional diversity by calculating the number of functional groups (N), Margalef's d, Pielou's J′, Shannon's Diversity, and Simpson's Diversity Index. An AR(1) time series model was used to investigate proportional changes in each guild over 25 years. To evaluate the effect of invasive Carp species in invaded reaches, a Chow test was applied to observations between 2000 and 2005. Analyses revealed differences in the functional fish community among reaches. We found differences in functional diversity metrics among study reaches, but there was little evidence that this differed between invaded and non-invaded reaches. Results determined that invertivore/detritivores have been consistently declining system-wide, with few groups showing a net change. There was also little evidence that invasion altered the proportion of any functional guild. Evaluating the spatial–temporal patterns of functional communities is beneficial to understanding the resilience of a system and can provide further insight into its trophic needs when considering future restoration initiatives.
Grass carp, bighead carp, and silver carp spawn in flowing water. Their eggs, and then larvae, develop while drifting. Hydraulic conditions and water temperature control spawning locations, egg survival, and the downstream distance traveled before the hatched larvae can swim for low velocity nursery habitats. Existing egg drift models simulate the fluvial transport of carp eggs but have limitations in capturing the effect of localized turbulence on egg transport due to inadequate dimensions of hydrodynamics and/or empirical parameterization of river dispersion. We present a three-dimensional Lagrangian particle tracking model that uses fully resolved river hydrodynamics and a continuous random walk algorithm driven by local turbulent kinetic energy and its dissipation rate. We incorporate a new set of equations to compute evolving egg characteristics with fully resolved 3-D hydrodynamics. To demonstrate the performance of the model, we conducted a case study in an eight-kilometer reach of the Missouri River at the discharge of approximately 25% daily flow exceedance. Three-dimensional river hydrodynamics was modeled, calibrated, and evaluated with measurement data. Egg drift was modeled and compared using fully three-dimensional, depth-averaged two-dimensional, and zone-averaged one-dimensional hydrodynamics. The comparison shows a generally good agreement among models of downstream egg transport due to advection but a different dispersion pattern of eggs in the river, as a result of turbulent diffusion and shear induced dispersion.
Although carbonatites are the primary source of the world’s rare earth elements (REEs), the processes responsible for ore-grade REE enrichment in carbonatites are still poorly understood. In this study, we present a petrologic, geochemical, and isotopic evaluation of the Elk Creek carbonatite in southeast Nebraska to constrain the origin of REE mineralization. The Elk Creek carbonatite is a multilithologic carbonatite comprised of an early apatite-dolomite carbonatite, a middle/heavy REE-enriched magnetite-dolomite carbonatite, and a late-stage light REE-enriched, barite-dolomite carbonatite, as well as a suite of breccias. Neodymium, strontium, and carbon isotopic data from the early apatite-dolomite carbonatite, εNd(T) = 2.3 to 3.4, 87Sr/86Sr(i) = 0.702704 to 0.702857, and δ13C = −3.3 to −3.4, indicate that the parental magma and REEs were derived from the mantle, and textural and chemical data suggest that hydrothermal processes played an important role in reaching ore-grade enrichment. Higher initial 87Sr/86Sr values (∼0.7041) of REE-mineralized lithologies are evidence that these fluids were derived, in part, from meteoric water that interacted with the country rock. Modeling of the C-O isotopic data reveals that some of the isotopic variation results from closed-system Rayleigh fractionation of an evolving carbonatitic magma between 300 and 500 °C, but an excursion to heavier δ18O is likely the result of interaction with H2O-CO2-fluids at temperatures from 400 to 100 °C. Hydrothermal dolomite has higher 87Sr/86Sr values than early-formed magmatic dolomite, consistent with metasomatism by fluids derived, in part, from a more radiogenic source such as the Precambrian-age wall rock. Rare earth element mineralization occurs primarily in fine-grained, cavity filling minerals including monazite, bastnäsite, parisite, and synchysite along with barite, dolomite, quartz, and iron oxides. We interpret the LREE enrichment at Elk Creek to be the product of hydrothermal fluids derived from the evolving carbonatite magma and fluids from the wall rock. The REEs likely became enriched in late-stage fluids from the evolving magma as well as being remobilization by the dissolution of earlier formed minerals. Middle/heavy REE-enrichment in the magnetite-dolomite carbonatite is hosted in hydrothermal dolomite and is attributed to variations in the composition of hydrothermal fluids.
Populations of amphibians that breed in isolated, ephemeral wetlands may be particularly sensitive to breeding and recruitment rates, which can be influenced by dynamic and difficult-to-predict extrinsic factors. The gopher frog Rana capito is a declining species currently proposed for listing under the U.S. Endangered Species Act, as well as one of many pond-breeding amphibians of conservation concern in the southeastern United States. To represent gopher frog breeding dynamics, we applied an occupancy modeling framework that integrated multiple data sets collected across the species' range to 1) estimate the influence of climate, habitat, and other factors on wetland-specific seasonal breeding probabilities; and 2) use those estimates to characterize seasonal, annual, and regional breeding patterns over a 10-y period. Breeding probability at a wetland was positively influenced by seasonal precipitation (Standardized Precipitation Index) and negatively influenced by fish presence. We found some evidence that the amount of suitable habitat surrounding a wetland was positively correlated with breeding probability during drought conditions. The percentage of sampled wetlands (N = 192) predicted to have breeding varied seasonally, annually, and regionally across the study. Within-year temporal patterns of breeding differed across the range: in most locations north of Florida, peaks of breeding occurred in winter and spring months; whereas breeding was more dispersed throughout the year in Florida. Peaks of breeding across the 10-y period often occurred during or in the season following high rainfall events (e.g., hurricanes). These results have direct applications for site-level management that aims to increase successful breeding opportunities of gopher frogs and other associated pond-breeding amphibians, including monitoring protocol and intensity, removal of fish, and improving terrestrial habitat conditions surrounding wetlands (e.g., via tree or shrub removal and prescribed fire). The results also have implications for better-informed management through the closer alignment of breeding activity monitoring with predicted seasonal peaks. Furthermore, estimates of breeding frequency can be incorporated into population viability analyses to inform forthcoming assessments of extinction risk and designation of the species' conservation status by the U.S. Fish and Wildlife Service.
","language":"English","publisher":"Allen Press","doi":"10.3996/JFWM-21-076","usgsCitation":"Crawford, B., Farmer, A.L., Enge, K.M., Greene, A.H., Diaz, L., Maerz, J., and Moore, C.T., 2022, Breeding dynamics of gopher frog metapopulations over 10 years: Journal of Fish and Wildlife Management, v. 13, no. 2, p. 422-436, https://doi.org/10.3996/JFWM-21-076.","productDescription":"15 p.","startPage":"422","endPage":"436","ipdsId":"IP-132970","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":447552,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/jfwm-21-076","text":"Publisher Index Page"},{"id":433319,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama, Florida, Georgia, North Carolina, South Carolina","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -76.37623620146309,\n 35.01905610973961\n ],\n [\n -79.58387829875939,\n 35.765474175904856\n ],\n [\n -84.05790907036402,\n 32.71553184084284\n ],\n [\n -86.95743456481551,\n 31.313371252353505\n ],\n [\n -87.97753689244945,\n 31.255714516567366\n ],\n [\n -87.90062766475464,\n 30.410921928153\n ],\n [\n -87.59693089405745,\n 30.192182652668805\n ],\n [\n -86.47166028094222,\n 30.256647398203384\n ],\n [\n -85.28363865323925,\n 29.70795105375852\n ],\n [\n -84.92300860524551,\n 29.589227662420754\n ],\n [\n -84.08074545620036,\n 30.02565465245405\n ],\n [\n -83.15740795176218,\n 29.317339522650897\n ],\n [\n -82.63768115979533,\n 28.69410108060019\n ],\n [\n -82.92151914429557,\n 27.84487915072812\n ],\n [\n -82.2486913639156,\n 26.57820345742978\n ],\n [\n -80.14666967814253,\n 27.38909651326503\n ],\n [\n -81.36572255738787,\n 30.46066646132182\n ],\n [\n -80.96075675824606,\n 31.903583611808543\n ],\n [\n -79.10275245779792,\n 33.184671689061005\n ],\n [\n -78.85784463476865,\n 33.722973799123594\n ],\n [\n -77.88573955862327,\n 33.91871952883908\n ],\n [\n -76.37623620146309,\n 35.01905610973961\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"13","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-06-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Crawford, Brian A.","contributorId":341519,"corporation":false,"usgs":false,"family":"Crawford","given":"Brian A.","affiliations":[{"id":81748,"text":"Georgia Cooperative Fish and Wildlife Research Unit","active":true,"usgs":false}],"preferred":false,"id":908553,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Farmer, Anna L.","contributorId":341520,"corporation":false,"usgs":false,"family":"Farmer","given":"Anna","email":"","middleInitial":"L.","affiliations":[{"id":36335,"text":"Fish and Wildlife Research Institute","active":true,"usgs":false}],"preferred":false,"id":908554,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Enge, Kevin M","contributorId":177669,"corporation":false,"usgs":false,"family":"Enge","given":"Kevin","email":"","middleInitial":"M","affiliations":[],"preferred":false,"id":908555,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Greene, Aubrey Heupel","contributorId":341522,"corporation":false,"usgs":false,"family":"Greene","given":"Aubrey","email":"","middleInitial":"Heupel","affiliations":[{"id":36335,"text":"Fish and Wildlife Research Institute","active":true,"usgs":false}],"preferred":false,"id":908556,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Diaz, Lauren","contributorId":341523,"corporation":false,"usgs":false,"family":"Diaz","given":"Lauren","email":"","affiliations":[{"id":36335,"text":"Fish and Wildlife Research Institute","active":true,"usgs":false}],"preferred":false,"id":908557,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Maerz, John C.","contributorId":341524,"corporation":false,"usgs":false,"family":"Maerz","given":"John C.","affiliations":[{"id":81749,"text":"Warnell School of Forestry and Natural Resources","active":true,"usgs":false}],"preferred":false,"id":908558,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Moore, Clinton T. 0000-0002-6053-2880 cmoore@usgs.gov","orcid":"https://orcid.org/0000-0002-6053-2880","contributorId":3643,"corporation":false,"usgs":true,"family":"Moore","given":"Clinton","email":"cmoore@usgs.gov","middleInitial":"T.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908559,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70231909,"text":"70231909 - 2022 - Biogeography of freshwater mussels (Bivalvia: Unionida) in Texas and implications on conservation biology","interactions":[],"lastModifiedDate":"2022-07-08T13:38:13.520477","indexId":"70231909","displayToPublicDate":"2022-06-03T08:43:05","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1399,"text":"Diversity and Distributions","active":true,"publicationSubtype":{"id":10}},"title":"Biogeography of freshwater mussels (Bivalvia: Unionida) in Texas and implications on conservation biology","docAbstract":"Aim
Biogeography seeks to identify and explain the spatial distributions of species and has become an important tool used by conservationists to protect and manage aquatic organisms. Texas, located in the southwestern United States, is home to 52 species of freshwater mussels, 9 of which are endemic to Texas and 7 that are endemic to Texas and neighboring states or countries. There have been two major attempts to classify this fauna into biogeographical provinces; however, both efforts relied on limited distribution information and outdated taxonomy. To address both issues, we set out to delineate biogeographic provinces for freshwater mussels in Texas by using a comprehensive distributional dataset of >28,000 records and molecular information.
Location
Southwestern United States.
Methods
We compiled community and molecular data for 48 of the 52 freshwater mussel species that occur in Texas. We performed algorithmic hierarchal cluster analysis (HCA) and nonmetric multidimensional scaling (NMDS) based on Euclidean distance to identify biogeographic groupings. We conducted a similar analysis using molecular sequence data for our target species.
Results
Based on the results from community and molecular data, we identified seven biogeographic provinces for freshwater mussels in Texas: Great Plains, Mississippi Embayment, Sabine-Neches, Trinity-San Jacinto, Central Texas, Rio Grande and Coastal. However, the Coastal and Great Plains provinces were not included in our analysis and were recognized based on previous work.
Main conclusions
Our approach integrating community and molecular datasets provides a comprehensive assessment of the biogeography of freshwater mussels in Texas, which serves as a model for future biogeographic studies. Our findings also shed light on the ecological, evolutionary and geologic processes shaping freshwater mussel communities in Texas, which is important for the conservation of remaining biodiversity in the state.
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\"}}]}","volume":"28","issue":"7","noUsgsAuthors":false,"publicationDate":"2022-05-30","publicationStatus":"PW","contributors":{"authors":[{"text":"de Moulpied, Michael 0000-0002-4007-7550","orcid":"https://orcid.org/0000-0002-4007-7550","contributorId":292219,"corporation":false,"usgs":false,"family":"de Moulpied","given":"Michael","email":"","affiliations":[{"id":36313,"text":"Texas A&M","active":true,"usgs":false}],"preferred":false,"id":844093,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Chase H. 0000-0002-1499-0311","orcid":"https://orcid.org/0000-0002-1499-0311","contributorId":225140,"corporation":false,"usgs":false,"family":"Smith","given":"Chase","email":"","middleInitial":"H.","affiliations":[{"id":13716,"text":"Baylor University","active":true,"usgs":false}],"preferred":false,"id":844094,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Robertson, Clint R.","contributorId":292221,"corporation":false,"usgs":false,"family":"Robertson","given":"Clint","email":"","middleInitial":"R.","affiliations":[{"id":27442,"text":"Texas parks and Wildlife Department","active":true,"usgs":false}],"preferred":false,"id":844095,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Nathan 0000-0001-5167-1988","orcid":"https://orcid.org/0000-0001-5167-1988","contributorId":210319,"corporation":false,"usgs":true,"family":"Johnson","given":"Nathan","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":844096,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lopez, Roel","contributorId":206218,"corporation":false,"usgs":false,"family":"Lopez","given":"Roel","affiliations":[{"id":36313,"text":"Texas A&M","active":true,"usgs":false}],"preferred":false,"id":844097,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Randklev, Charles R.","contributorId":202530,"corporation":false,"usgs":false,"family":"Randklev","given":"Charles","email":"","middleInitial":"R.","affiliations":[{"id":36313,"text":"Texas A&M","active":true,"usgs":false}],"preferred":false,"id":844098,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70231907,"text":"70231907 - 2022 - Structured decision making to rank North American Wetland Conservation Act proposals within joint venture regions","interactions":[],"lastModifiedDate":"2023-01-18T15:51:07.526101","indexId":"70231907","displayToPublicDate":"2022-06-03T08:32:14","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Structured decision making to rank North American Wetland Conservation Act proposals within joint venture regions","docAbstract":"The North American Wetlands Conservation Act (16 U.S.C. 4401-4412) provided funding and administration for wetland management and conservation projects. The North American Wetland Conservation Fund, enabled in 1989 with the Act, provides financial resources. Resource allocation decisions are based, in part, on regional experts, particularly migratory bird Joint Ventures (JVs) (i.e., partnerships for cooperative planning and coordinated management of the continent’s waterfowl populations and habitats). The JVs evaluate funding proposals submitted with their respective regions each year and make funding recommendations to decision makers. Proposal evaluation procedures differ among JVs, however, it could be helpful to consider a transparent, repeatable, and data-driven framework for prioritization within regions. We used structured decision making and linear additive value models for ranking proposals within JV regions. We used two JVs as case studies and constructed two different value models using JV-specific objectives and weights. The framework was developed through a collaborative process with JV staff and stakeholders. Models were written in Microsoft Excel. To test these models, we used six NAWCA proposals submitted to the Upper Mississippi / Great Lakes Joint Venture in 2016 and seven proposals submitted to the Gulf Coast Joint Venture in 2017. We compared proposal ranks assigned by the value model to ranks assigned by each JV’s management board. Ranks assigned by the value model differed from ranks assigned by the board for the Upper Mississippi / Great Lakes Joint Venture, but not for the Gulf Coast Joint Venture. However, ranks from the value model could change markedly with different objective weights and value functions. The weighted linear value model was beneficial for ranking NAWCA proposals because it allows JVs to treat the ranking as a multiple objective problem and tailor the ranking to their specific regional concerns. We believe a structured decision making approach could be adapted by JV staff to facilitate a systematic and transparent process for proposal ranking by their management boards.
","language":"English","publisher":"U. S. Fish and Wildlife Service","doi":"10.3996/JFWM-21-089","usgsCitation":"Krainyk, A., Lyons, J.E., Soulliere, G.J., Coluccy, J.M., Wilson, B.C., Brasher, M.G., Al-Saffar, M.A., and Humburg, D.D., 2022, Structured decision making to rank North American Wetland Conservation Act proposals within joint venture regions: Journal of Fish and Wildlife Management, v. 13, no. 2, p. 375-395, https://doi.org/10.3996/JFWM-21-089.","productDescription":"21 p.","startPage":"375","endPage":"395","ipdsId":"IP-122603","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":447556,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/jfwm-21-089","text":"Publisher Index Page"},{"id":401678,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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States\"}}]}","volume":"13","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-05-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Krainyk, Anastasia 0000-0002-3100-9011","orcid":"https://orcid.org/0000-0002-3100-9011","contributorId":214391,"corporation":false,"usgs":true,"family":"Krainyk","given":"Anastasia","email":"","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":844085,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lyons, James E. 0000-0002-9810-8751","orcid":"https://orcid.org/0000-0002-9810-8751","contributorId":222844,"corporation":false,"usgs":true,"family":"Lyons","given":"James","email":"","middleInitial":"E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":844086,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Soulliere, Gregory J.","contributorId":172329,"corporation":false,"usgs":false,"family":"Soulliere","given":"Gregory","email":"","middleInitial":"J.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":844087,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Coluccy, John M.","contributorId":111382,"corporation":false,"usgs":true,"family":"Coluccy","given":"John","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":844088,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wilson, Barry C.","contributorId":12968,"corporation":false,"usgs":true,"family":"Wilson","given":"Barry","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":844089,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brasher, Michael G.","contributorId":214393,"corporation":false,"usgs":false,"family":"Brasher","given":"Michael","email":"","middleInitial":"G.","affiliations":[{"id":36215,"text":"Ducks Unlimited","active":true,"usgs":false}],"preferred":false,"id":844090,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Al-Saffar, Mohammed A","contributorId":292215,"corporation":false,"usgs":false,"family":"Al-Saffar","given":"Mohammed","email":"","middleInitial":"A","affiliations":[{"id":62842,"text":"USWFS","active":true,"usgs":false}],"preferred":false,"id":844091,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Humburg, Dale D.","contributorId":79357,"corporation":false,"usgs":false,"family":"Humburg","given":"Dale","email":"","middleInitial":"D.","affiliations":[{"id":13073,"text":"Ducks Unlimited, Inc.","active":true,"usgs":false}],"preferred":false,"id":844092,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70231846,"text":"sir20215113 - 2022 - Long-term groundwater availability in the Waihe‘e, ‘Īao, and Waikapū aquifer systems, Maui, Hawai‘i","interactions":[],"lastModifiedDate":"2026-04-02T19:46:57.445783","indexId":"sir20215113","displayToPublicDate":"2022-06-03T08:07:20","publicationYear":"2022","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":"2021-5113","displayTitle":"Long-Term Groundwater Availability in the Waihe‘e, ‘Īao, and Waikapū Aquifer Systems, Maui, Hawai‘i","title":"Long-term groundwater availability in the Waihe‘e, ‘Īao, and Waikapū aquifer systems, Maui, Hawai‘i","docAbstract":"Groundwater levels have declined since the 1940s in the Wailuku area of central Maui, Hawai‘i, on the eastern flank of West Maui volcano, mainly in response to increased groundwater withdrawals. Available data since the 1980s also indicate a thinning of the freshwater lens and an increase in chloride concentrations of pumped water from production wells. These trends, combined with projected increases in demand for groundwater in central Maui, have led to concerns over groundwater availability and have highlighted a need to improve general understanding of the hydrologic effects of proposed groundwater withdrawals in the Waihe‘e, ‘Īao, and Waikapū areas of central Maui.
A numerical groundwater model was constructed to simulate the flow and salinity of groundwater in central Maui. The model simulates the effects of changes in groundwater withdrawals and recharge on water levels, freshwater-lens thicknesses, and chloride concentrations of pumped water from production wells. The model incorporates updated water-budget estimates of groundwater recharge from infiltration and direct recharge, seepage in stream channels, and inflow from inland areas. Mean annual groundwater recharge from infiltration and direct recharge was estimated using a daily water-budget model and the most current data, including the distributions of monthly rainfall and potential evapotranspiration, for the study area for nine historical periods from 1926 through 2012: 1926–69, 1970–79, 1980–84, 1985–89, 1990–94, 1995–99, 2000–04, 2005–09, and 2010–12. The water-budget model also estimated groundwater recharge based on one hypothetical scenario that used 1980–2010 rainfall and 2017 land cover. For the nine historical periods, estimated recharge from infiltration and direct recharge within the area of the groundwater model ranged from 30.4 million gallons per day (Mgal/d) during 2010–12 to 98.7 Mgal/d during 1926–69. Variability in recharge during these periods mainly reflects changes in rainfall and irrigation over time. Between 2010 and 2014, streamflow restoration in previously diverted streams resulted in an estimated increase in recharge from seepage in stream channels of about 12.5 Mgal/d. Average groundwater inflow of about 39.6 Mgal/d from inland, dike-intruded areas to the main area of interest was estimated from an existing island-wide numerical groundwater-flow model, which is at a larger scale and incorporates a greater number of simplifying assumptions.
The numerical groundwater model developed for this study was calibrated to 1926–2012 transient water levels, vertical salinity profiles, and chloride concentrations of water pumped by production wells in the study area. The model was then used to evaluate one future recharge and six selected withdrawal scenarios, developed in consultation with the Maui Department of Water Supply, in terms of long-term changes in water level and 50-percent ocean-water salinity surface. The groundwater model was also used to simulate the future salinity of water withdrawn by existing and proposed production wells. The simulations were run to steady-state conditions, providing an estimate of the long-term effects of changes in withdrawal and recharge on the groundwater resource. Results of the simulated future withdrawal scenarios indicate that, relative to 2017–18 rates, the scenarios’ long-term effect of increased withdrawals ultimately leads to lower water levels and a higher 50-percent ocean-water salinity surface indicating a thinning of the freshwater lens. Results also indicate that the increased withdrawals produce some groundwater with chloride concentration below 250 milligrams per liter and some groundwater with higher chloride concentration. The amount of drawdown near production wells and the quality of water withdrawn from production wells is dependent on the rate and spatial distribution of the withdrawals.
The model was also used to evaluate how groundwater availability may be affected for a drier recharge scenario based on a published study of future climate. Model results of the future recharge scenario indicate that the rate of groundwater recharge is a controlling factor for (1) water levels, (2) the 50-percent ocean-water salinity surface, and (3) the quality of water withdrawn from production wells in the Wailuku area. Coupled with reduced groundwater recharge (with all other factors remaining equal), the modeled future withdrawals in the scenario would tend to cause lower water levels, a higher 50-percent ocean-water salinity surface, and increased salinity of water withdrawn from production wells.
The three-dimensional numerical groundwater model developed for this study utilizes the latest available hydrologic and geologic information and is a useful tool for understanding the long-term hydrologic effects of additional groundwater withdrawals in central Maui. The model has several limitations, including its non-uniqueness and inability to account for local-scale heterogeneities. Short-term effects of changes in recharge and withdrawals—and optimization of pumping rates to meet increased demand for water with acceptable salinity—are possible conditions for future simulation analyses.
Director,
Pacific Islands Water Science Center
U.S. Geological Survey
Inouye Regional Center
1845 Wasp Blvd., B176
Honolulu, HI 96818
Successful migration of Chinook Salmon (Oncorhynchus tshawytscha) smolts seaward in the Sacramento – San Joaquin River Delta (hereafter, Delta) requires navigating a network of numerous branching channels. Within the Delta, several key junctions route smolts either towards more direct paths to the ocean or towards the interior Delta, an area associated with decreased survival. Movements within these junctions that determine route choice can be influenced by numerous behavioral and environmental factors, including the complex interplay between tidal and riverine hydraulics. Here, we apply continuous time multistate Markov models to examine the influence of tidal and riverine hydraulics, behavioral factors, and management actions on smolt movements. These models incorporate more information from acoustic telemetry data compared with previous approaches to modeling smolt movements in the Delta. By decomposing modeled flows into tidal and net flow signals we elucidate how each component influences movements into and out of distributary channels. Increasing net flows generally increased movement rates, while flood tides decreased seaward movement rates. Similarly, ebb tides increased downstream movements as fish go with the flow. We found less support for diel movement behaviors compared to flow metrics. Additionally, we quantify the effects of a large management action, the placement of a physical barrier, which was effective at decreasing entrainment into the interior Delta. Together, these results help inform management of Chinook Salmon and increase our understanding of the major factors driving smolt movements within these key junctions.
","language":"English","publisher":"Springer","doi":"10.1007/s10641-022-01273-1","usgsCitation":"Dodrill, M., Perry, R., Pope, A., and Wang, X., 2022, Quantifying the effects of tides, river flow, and barriers on movements of Chinook Salmon smolts at junctions in the Sacramento–San Joaquin River Delta using multistate models: Environmental Biology of Fishes, v. 105, p. 2065-2082, https://doi.org/10.1007/s10641-022-01273-1.","productDescription":"18 p.","startPage":"2065","endPage":"2082","ipdsId":"IP-133966","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":401641,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento-San-Joaquin River Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.6513671875,\n 37.86618078529668\n ],\n [\n -122.56347656249999,\n 37.779398571318765\n ],\n [\n -122.55249023437501,\n 37.54022177661216\n ],\n [\n -122.0745849609375,\n 37.21720611325497\n ],\n [\n -121.541748046875,\n 37.020098201368114\n ],\n [\n -120.9210205078125,\n 37.24782120155428\n ],\n [\n -120.5804443359375,\n 37.4356124041315\n ],\n [\n -120.62988281249999,\n 37.63163475580643\n ],\n [\n -121.1846923828125,\n 37.896530447543\n ],\n [\n -121.31103515625,\n 38.052416771864834\n ],\n [\n -121.38244628906251,\n 38.268375880204744\n ],\n [\n -121.42639160156249,\n 38.45789034424927\n ],\n [\n -121.56921386718751,\n 38.70265930723801\n ],\n [\n -122.01416015625,\n 38.31149091244452\n ],\n [\n -122.61291503906249,\n 38.238180119798635\n ],\n [\n -122.6513671875,\n 37.86618078529668\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"105","noUsgsAuthors":false,"publicationDate":"2022-05-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Dodrill, Michael J. 0000-0002-7038-7170","orcid":"https://orcid.org/0000-0002-7038-7170","contributorId":206439,"corporation":false,"usgs":true,"family":"Dodrill","given":"Michael","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":844058,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perry, Russell 0000-0003-4110-8619","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":220189,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":844059,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pope, Adam C. 0000-0002-7253-2247","orcid":"https://orcid.org/0000-0002-7253-2247","contributorId":223237,"corporation":false,"usgs":true,"family":"Pope","given":"Adam","middleInitial":"C.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":844060,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wang, Xiaochun","contributorId":225264,"corporation":false,"usgs":false,"family":"Wang","given":"Xiaochun","email":"","affiliations":[{"id":41085,"text":"California Department of Water Resources, Sacramento, CA, 95819","active":true,"usgs":false}],"preferred":false,"id":844061,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70246620,"text":"70246620 - 2022 - Chew-cards can accurately index invasive rat densities in Mariana Island forests","interactions":[],"lastModifiedDate":"2023-07-11T12:20:09.04227","indexId":"70246620","displayToPublicDate":"2022-06-02T07:16:37","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5071,"text":"NeoBiota","active":true,"publicationSubtype":{"id":10}},"title":"Chew-cards can accurately index invasive rat densities in Mariana Island forests","docAbstract":"Rats (Rattus spp.) are likely established on 80–90% of the world’s islands and represent one of the most damaging and expensive biological invaders. Effective rat control tools exist but require accurate population density estimates or indices to inform treatment timing and effort and to assess treatment efficacy. Capture-mark-recapture data are frequently used to produce robust density estimates, but collecting these data can be expensive, time-consuming, and labor-intensive. We tested a potentially cheaper and easier alternative, chew-cards, as a count-based (quantitative) index of invasive rat densities in tropical forests in the Mariana Islands, an archipelago in the western North Pacific Ocean. We trialed chew-cards in nine forest grids on two Mariana Islands by comparing the proportion of cards chewed to capture-mark-recapture density estimates and manipulated rat densities to test whether the relationship was retained. Chew-card counts were positively correlated with rat capture-mark-recapture density estimates across a range of rat densities found in the region. Additionally, the correlation between the two sampling methods increased with the number of days chew-cards were deployed. Specifically, when chew-cards were deployed for five nights, a 10% increase in the proportion of cards chewed equated to an estimated increase in rat density of approximately 2.4 individuals per ha (R2 = 0.74). Chew-cards can provide a valid index of rat densities in Mariana Island forests and are a cheaper alternative to capture-mark-recapture sampling when relative differences in density are of primary interest. New cost-effective monitoring tools can enhance our understanding and management of invaded islands while stretching limited resources further than some conventional approaches, thus improving invasive species management on islands.
We present and demonstrate a recursive-estimation framework to infer groundwater/surface-water exchange based on temperature time series collected at different vertical depths below the sediment/water interface. We formulate the heat-transport problem as a state-space model (SSM), in which the spatial derivatives in the convection/conduction equation are approximated using finite differences. The SSM is calibrated to estimate time-varying specific discharge using the Extended Kalman Filter (EKF) and Extended Rauch-Tung-Striebel Smoother (ERTSS). Whereas the EKF is suited to real-time (“online”) applications and uses only the past and current measurements for estimation (filtering), the ERTSS is intended for near-real time or batch-processing (“offline”) applications and uses a window of data for batch estimation (smoothing). The two algorithms are demonstrated with synthetic and field-experimental data and are shown to be efficient and rapid for the estimation of time-varying flux over seasonal periods; further, the recursive approaches are effective in the presence of rapidly changing flux and (or) nonperiodic thermal boundary conditions, both of which are problematic for existing approaches to heat tracing of time-varying groundwater/surface-water exchange.
The Winchester TU Chapter partnered with US Geological Survey scientists to forecast habitat conditions for brook trout in Virginia. The results can be viewed here: https://chesapeake.usgs.gov/fishforecast/
TU members deployed stream temperature gages within several streams across the region: Dry River, Passage Creek, Spout Run, Beaver Creek, Mossy Creek. The USGS then used the temperature data to evaluate current and future conditions for brook trout.
","language":"English","publisher":"Trout Unlimited, Winchester Chapter #638","usgsCitation":"Hitt, N.P., 2022, Spout Run temperature study revisited- Part II: New insights for trout habitat from TU & USGS collaboration 2022: Lateral Lines, no. June 2022, p. 8-9.","productDescription":"2 p.","startPage":"8","endPage":"9","ipdsId":"IP-141316","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":406771,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":406769,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://winchestertu.org/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Virginia","otherGeospatial":"Spout Run","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.12721252441406,\n 39.03\n ],\n [\n -78,\n 39.03\n ],\n [\n -78,\n 39.144972625112224\n ],\n [\n -78.12721252441406,\n 39.144972625112224\n ],\n [\n -78.12721252441406,\n 39.03\n ]\n ]\n ]\n }\n }\n ]\n}","issue":"June 2022","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hitt, Nathaniel P. 0000-0002-1046-4568","orcid":"https://orcid.org/0000-0002-1046-4568","contributorId":238185,"corporation":false,"usgs":true,"family":"Hitt","given":"Nathaniel","email":"","middleInitial":"P.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":851822,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70246621,"text":"70246621 - 2022 - New state and county records of introduced amphibians and reptiles of Georgia, USA.","interactions":[],"lastModifiedDate":"2023-07-19T16:42:06.960625","indexId":"70246621","displayToPublicDate":"2022-06-01T11:36:22","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1898,"text":"Herpetological Review","active":true,"publicationSubtype":{"id":10}},"title":"New state and county records of introduced amphibians and reptiles of Georgia, USA.","docAbstract":"Recent efforts to eradicate the invasive Argentine Giant Tegu (Salvator merianae) has led to the discovery of several county records of this introduced lizard as well as several other potentially invasive amphibian and reptile species in the state of Georgia, USA. New records were determined using a database of county records maintained by the Georgia Department of Natural Resources. All specimens and photographic records are stored at the Georgia Southern University – Savannah Science Museum Herpetology Collection (GSU) and were collected under the Georgia scientific collection permit number 1000545737 and IACUC permit number I18020 and I21010. All coordinates are presented in WGS 84. We report 14 new county records consisting of two anurans and 11 squamates in Georgia.
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