Understanding the population structure of invasive sea lamprey (Petromyzon marinus) in the Great Lakes basin is essential for an effective control program. We review knowledge of lake connectivity, dispersal during the parasitic stage, and results from phenotypic, demographic, and genetic studies to evaluate how sea lamprey populations are structured. There is no evidence for contemporary movement between Lake Ontario and the Atlantic population, although it appears possible. Dispersal between Lake Ontario and the Finger Lakes is more likely, as is contemporary movement between Lakes Ontario and Erie via the Welland Canal, although neither has been directly observed. Downstream movement from Lake Erie to Lake Ontario via the Niagara River has been reported. Bidirectional movement between Lakes Erie and Huron has been observed, and movement of sea lamprey among the upper Great Lakes (especially between Lakes Huron and Michigan) is relatively common, although complete mixing likely does not occur. The maximum straight-line dispersal distance reported for a tagged sea lamprey was 628 km between the St. Marys River and western Lake Erie. Genetic population studies using a variety of molecular markers generally found weak but significant broad-scale population structure (e.g., between freshwater and anadromous populations, and among Lake Ontario, Lake Erie, and the upper Great Lakes), but finer-scale structure was rarely detected. Nevertheless, some within-basin structure is suggested by regional differences in phenotypic and demographic traits (e.g., sex ratio, body size). Further study will be important because management is most efficiently targeted when the geography of demographically independent populations is well-characterized.
The periodic application of chemical lampricides that selectively kill larval sea lampreys (Petromyzon marinus) in their nursery habitats remains a primary component of the Great Lakes Fishery Commission’s (GLFC) Sea Lamprey Control Program in the Laurentian Great Lakes. Lampricides include 3-trifluoromethyl-4-nitrophenol (TFM) and niclosamide, the 2-aminoethanol salt of 2′, 5-dichloro-4′-nitrosalicylanilide, which may be used as an additive to TFM during stream treatments, or alone in a granular, bottom-release formulation to target sea lamprey larvae in deepwater environments where dilution would render TFM ineffective. During the early 1990s, the GLFC identified lampricide reduction targets in response to societal concerns with pesticide use, rising lampricide costs, and promising research into alternative controls. By 1999, the GLFC’s control agents, Fisheries and Oceans Canada (DFO) and the U.S. Fish and Wildlife Service (USFWS), had reduced TFM use by 36%. However, without effective alternative methods to compensate for increasing larval and juvenile production, sea lamprey abundance and lake trout (Salvelinus namaycush) marking rates rose throughout the Great Lakes. Beginning in the early 2000s, the GLFC and its control agents responded to burgeoning sea lamprey populations by implementing measures to advance the use of lampricides, which included: 1) assessing and controlling sea lamprey larvae that survived treatment; 2) enhancing treatment efficacy; 3) developing new technology to effectively treat larval populations that inhabit deepwater environments; 4) increasing operational capacity to treat more tributaries and lentic areas at shorter intervals; and, 5) conducting large-scale and targeted treatment strategies. When comparing lampricide use between the decades of 1990–1999 and 2010–2019, significant increases occurred in the mean number of treatments and amounts of TFM and niclosamide applied annually. Concurrent with these actions, researchers undertook studies to identify factors that erode lampricide treatment efficiency, elucidate physiological mode of action, and investigate lethal and sub-lethal impacts of lampricide exposure on aquatic organisms. By integrating new operational tactics and strategies with advances in science and technology, the GLFC, DFO, and USFWS, with support from the U.S. Geological Survey and the U.S. Army Corps of Engineers, have achieved unprecedented suppression of sea lampreys and reduction in lake trout marking in the Great Lakes. However, emerging challenges potentially threaten the future use of lampricides.
Survival of adult fishes is critical to the conservation and management of wild populations, particularly for long-lived, slow to reproduce species. Most sturgeon species are of conservation concern, but their long lifespans and large ranges have made estimation of adult survival rates challenging. In this study, acoustic telemetry was used to track 205 lake sturgeon (Acipenser fulvescens) tagged in the St. Clair and Detroit rivers of the Laurentian Great Lakes over seven years (2012–2019). The objective of this study was to determine if annual survival was related to sex, size, tagging location (river), or year post-tagging using Cormack-Jolly-Seber (CJS) models. Annual survival was high among all seven years (range of point estimates: 95–99%) and did not differ based on sex, tagging year, size at time of tagging, or tagging location. Lake sturgeon detection probability on acoustic receivers was high each year (range of point estimates: 82–99%) and increased as the number of receivers in the system increased. High survival rates of lake sturgeon were consistent with levels thought required for lake sturgeon to be self-sustaining in the St. Clair – Detroit river system. Our application of acoustic telemetry detections as input to CJS models demonstrated the usefulness of this approach and should be considered for population assessment studies throughout the Great Lakes and beyond.
The collapse of Diporeia spp. and invasions of dreissenid mussels (zebra, Dreissena polymorpha; quagga, D. bugensis) and round goby (Neogobius melanostomus) have been associated with declines in abundance of native benthic fishes in the Great Lakes, including historically abundant slimy sculpin (Cottus cognatus). We hypothesized that as round goby colonized deeper habitat, slimy sculpin avoided habitat competition, predation, and aggression from round goby by shifting to deeper habitat. Accordingly, we predicted increased depth overlap of slimy sculpin with both round goby and deepwater sculpin (Myoxocephalus thompsonii) that resulted in habitat squeeze by both species. We used long-term bottom trawl data from Lakes Michigan, Huron, and Ontario to evaluate shifts in slimy sculpin depth and their depth overlap with round goby and deepwater sculpin. Lake Huron most supported our hypotheses as slimy sculpin shifted to deeper habitat coincident with the round goby invasion, and depth overlap between slimy sculpin and both species recently increased. Slimy sculpin depth trends in Lakes Michigan and Ontario suggest other ecological and environmental factors better predicted sculpin depth in these lakes.
No abstract available.
","language":"English","publisher":"University of Colorado, Boulder","collaboration":"University of Colorado, Boulder; Institute for Tribal Environmental Professionals; National Center for Atmospheric Research","usgsCitation":"Herman-Mercer, N.M., 2021, Guiding the Arctic Rivers Project Climate Model Development: Results from the Climate Information Survey, 27 p.","productDescription":"27 p.","ipdsId":"IP-134119","costCenters":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"links":[{"id":423511,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":423505,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.colorado.edu/research/arctic-rivers/sites/default/files/attached-files/arp_modelsurveyresults_report_final.pdf"}],"country":"Canada, United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -134.5522950063096,\n 59.87028426766375\n ],\n [\n -133.24373664299094,\n 61.28424546566808\n ],\n [\n -134.02887166098213,\n 63.05529254448754\n ],\n [\n -136.77684422395126,\n 65.05797812818923\n ],\n [\n -140.17909596857976,\n 66.66285098504187\n ],\n [\n -140.57166347757536,\n 69.21575646485616\n ],\n [\n -142.5345010225534,\n 70.03568521513193\n ],\n [\n -154.573237965085,\n 71.4172689598237\n ],\n [\n -160.59260643635076,\n 70.8674732710819\n ],\n [\n -166.35026323495282,\n 68.7464270445748\n ],\n [\n -166.08855156228913,\n 67.72775212396189\n ],\n [\n -164.91084903530233,\n 67.1758201951771\n ],\n [\n -166.8736865802803,\n 66.34986352746296\n ],\n [\n -167.65882159827146,\n 65.44146322228974\n ],\n [\n -165.56512821696163,\n 63.7581904273662\n ],\n [\n -165.95769572595722,\n 62.15218786087863\n ],\n [\n -166.6119749076166,\n 61.221310865102566\n ],\n [\n -164.91084903530233,\n 59.87028426766375\n ],\n [\n -161.6394531270057,\n 58.18719425432104\n ],\n [\n -158.6297688913728,\n 57.63105594029915\n ],\n [\n -155.88179632840357,\n 57.91020117337476\n ],\n [\n -151.43269789312018,\n 58.39353282771856\n ],\n [\n -146.7218877851731,\n 59.87028426766375\n ],\n [\n -143.84305938587198,\n 60.00139362894262\n ],\n [\n -140.83337515023914,\n 59.73865592328997\n ],\n [\n -138.4779700962655,\n 59.60650723894122\n ],\n [\n -137.16941173294686,\n 59.27385018786782\n ],\n [\n -134.5522950063096,\n 59.87028426766375\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Herman-Mercer, Nicole M. 0000-0001-5933-4978 nhmercer@usgs.gov","orcid":"https://orcid.org/0000-0001-5933-4978","contributorId":3927,"corporation":false,"usgs":true,"family":"Herman-Mercer","given":"Nicole","email":"nhmercer@usgs.gov","middleInitial":"M.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":890140,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70226844,"text":"70226844 - 2021 - Life-history attributes of Arctic-breeding birds drive uneven responses to environmental variability across different phases of the reproductive cycle","interactions":[],"lastModifiedDate":"2022-01-06T17:45:08.622262","indexId":"70226844","displayToPublicDate":"2021-12-13T06:45:34","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Life-history attributes of Arctic-breeding birds drive uneven responses to environmental variability across different phases of the reproductive cycle","docAbstract":"Animals exhibit varied life-history traits that reflect adaptive responses to their environments. For Arctic-breeding birds, traits related to diet, egg nutrient allocation, clutch size, and chick growth are predicted to be under increasing selection pressure due to rapid climate change and increasing environmental variability across high-latitude regions. We compared four migratory birds (black brant [Branta bernicla nigricans], lesser snow geese [Chen caerulescens caerulescens], semipalmated sandpipers [Calidris pusilla], and Lapland longspurs [Calcarius lapponicus]) with varied life histories at an Arctic site in Alaska, USA, to understand how life-history traits help moderate environmental variability across different phases of the reproductive cycle. We monitored aspects of reproductive performance related to the timing of breeding, reproductive investment, and chick growth from 2011 to 2018. In response to early snowmelt and warm temperatures, semipalmated sandpipers advanced their site arrival and bred in higher numbers, while brant and snow geese increased clutch sizes; all four species advanced their nest initiation dates. During chick rearing, longspur nestlings were relatively resilient to environmental variation, whereas warmer temperatures increased the growth rates of sandpiper chicks but reduced growth rates of snow goose goslings. These responses generally aligned with traits along the capital-income spectrum of nutrient acquisition and altricial–precocial modes of chick growth. Under a warming climate, the ability to mobilize endogenous reserves likely provides geese with relative flexibility to adjust the timing of breeding and the size of clutches. Higher temperatures, however, may negatively affect the quality of herbaceous foods and slow gosling growth. Species may possess traits that are beneficial during one phase of the reproductive cycle and others that may be detrimental at another phase, uneven responses that may be amplified with future climate warming. These results underscore the need to consider multiple phases of the reproductive cycle when assessing the effects of environmental variability on Arctic-breeding birds.
Lampreys (order: Petromyzontiformes) represent one of two extant groups of jawless fishes, also called cyclostomes. Lampreys have a variety of unique features that distinguish them from other fishes. Here we review the physiological features of lampreys that have contributed to their evolutionary and ecological success. The term physiology is used broadly to also include traits involving multiple levels of biological organization, like swimming performance, that have a strong but not exclusively physiological basis. We also provide examples of how sea lamprey traits are currently being used or investigated to control invasive populations in the Great Lakes, such as reduced capacity to detoxify lampricides, inability to surmount low barriers or dams, and sensitivity to several lamprey-specific chemosensory pheromones and alarm cues. Specific suggestions are also provided for how an improved knowledge of lamprey physiological traits could be exploited for more effective conservation of native lampreys and lead to the development of next generation sea lamprey control and conservation tools.
The lampricides TFM and niclosamide are added to streams to control invasive larval sea lamprey (Petromyzon marinus) populations in the Laurentian Great Lakes. Lampricide effectiveness depends upon TFM and niclosamide bioavailability which is influenced by both abiotic and biotic factors. For example, at lower pH, TFM bioavailability is higher because a greater proportion exists as un-ionized TFM (TFM-OH), which easily crosses the gills. At higher pH, however, the negatively charged ionized species of TFM (TFM-O−) predominates, which is less easily taken-up, meaning more TFM must be applied. Although water alkalinity does not directly affect TFM speciation, as a buffer it influences how much expired water crossing the gills is acidified by CO2 and metabolic acid excretion. In poorly buffered waters, greater acidification of the expired water increases TFM bioavailability in the gill microenvironment than in better buffered, higher alkalinity waters where more TFM must be applied. Hence, sea lamprey and non-target fishes such as lake sturgeon (Acipenser fulvescens) are more sensitive to lampricides in low pH, low alkalinity waters. Differences in gill structure and microenvironment acidification might also explain why TFM sensitivity of young-of-the-year lake sturgeon approaches or exceeds that of sea lamprey in higher alkalinity waters. Other biotic factors such as body size and metabolic rate also contribute to differences in lampricide sensitivity. We conclude that better understanding of the abiotic and biotic factors influencing lampricide bioavailability can be used to refine treatment protocols to improve lampricide effectiveness and to better protect non-target fishes from lampricide toxicity.
Lake Ontario boasts a diverse fish community comprised of native and introduced species that support vibrant recreational, commercial and Indigenous fisheries. The effective delivery of a program to assess and control the sea lamprey (Petromyzon marinus) is crucial to achievement of Lake Ontario Fish Community Objectives of rehabilitating native fish stocks while protecting and maintaining the abundance of introduced salmonines. During 2000–2019, the Great Lakes Fishery Commission (GLFC) and its control agents, Fisheries and Oceans Canada (DFO) and the U. S. Fish and Wildlife Service (USFWS), delivered a consistent program of sea lamprey assessment and control. Beginning in 2004, rising sea lamprey abundance and marking rates on lake trout (Salvelinus namaycush) in Lake Ontario coincided with a decline of large lake trout in gillnet surveys. Efforts were undertaken to identify and control important sources of juvenile sea lampreys, including larvae that survived treatment, inhabited deepwater areas, or colonised previously uninhabited stream reaches and tributaries. A renewed reliance on proven conventional controls, including lampricide treatments and barriers, has resulted in consistent suppression of sea lamprey abundance and lake trout marking to prescribed targets in Lake Ontario during 2014–2019. This achievement is unprecedented in the 49-year history of Sea Lamprey Control Program delivery in Lake Ontario, and is attributable to the collaborative efforts of the GLFC, the control agents, and federal, provincial, state, and Indigenous partners.
Context: Camera trapping is increasingly used to collect information on wildlife occurrence and behaviour remotely. Not only does the technique provide insights into habitat use by species of interest, it also gathers information on non-target species.
Aims: We implemented ground-based camera trapping to investigate the behaviours of ground-dwelling birds, a technique that has largely been unutilised for studying birds, especially in wind-energy facilities.
Methods: We used camera traps to monitor activities of Agassiz’s desert tortoises (Gopherus agassizii) at their self-constructed burrows in a wind-energy facility near Palm Springs, California, USA. While doing so, we collected data on numerous burrow commensals, including birds.
Key results: Monitoring from late spring to mid-autumn in one year showed regular use of tortoise burrows and the immediate area by 12 species of birds, especially passerines. The most abundant species, as indicated by the number of photographs, but not necessarily individuals, was the rock wren (Salpinctes obsoletus), with a total of 1499 events. Birds appeared to use the interior or proximate vicinity of burrows for gathering nesting material, displaying, feeding, dust bathing and other activities. Of the bird species observed, 10 are known to be occasional casualties of turbine-blade strikes. The minimum known-age of a burrow had a positive relationship with bird counts.
Conclusions: Using camera traps focused at ground level can be a useful tool in avian conservation efforts because it is an effective technique for measuring bird presence, activity and behaviour in altered habitats such as wind farms, especially for those species that are low flyers or ground dwellers.
Implications: Acquiring data over the long term by using ground-based monitoring with camera traps could add to our understanding of avian behaviour and habitat use in relation to wind-energy infrastructure and operations, and help determine the vulnerability of avifauna that utilise the area.
","language":"English","publisher":"CSIRO Publishing","doi":"10.1071/WR21071","usgsCitation":"Puffer, S., Tennant, L.A., Lovich, J.E., Agha, M., Smith, A.L., Delaney, D., Arundel, T.R., Fleckenstein, L.J., Briggs, J., Walde, A., and Ennen, J., 2021, Birds not in flight: Using camera traps to observe ground use of birds at a wind-energy facility: Wildlife Research, v. 49, p. 283-294, https://doi.org/10.1071/WR21071.","productDescription":"12 p.","startPage":"283","endPage":"294","ipdsId":"IP-116087","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":393506,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Palm Springs","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.68167114257812,\n 33.668354044590075\n ],\n [\n -116.34246826171874,\n 33.668354044590075\n ],\n [\n -116.34246826171874,\n 34.02648590051866\n ],\n [\n -116.68167114257812,\n 34.02648590051866\n ],\n [\n -116.68167114257812,\n 33.668354044590075\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"49","noUsgsAuthors":false,"publicationDate":"2021-12-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Puffer, Shellie R. 0000-0003-4957-0963","orcid":"https://orcid.org/0000-0003-4957-0963","contributorId":193099,"corporation":false,"usgs":true,"family":"Puffer","given":"Shellie R.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":829326,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tennant, Laura A. 0000-0003-0062-7287 ltennant@usgs.gov","orcid":"https://orcid.org/0000-0003-0062-7287","contributorId":5984,"corporation":false,"usgs":true,"family":"Tennant","given":"Laura","email":"ltennant@usgs.gov","middleInitial":"A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":829327,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lovich, Jeffrey E. 0000-0002-7789-2831 jeffrey_lovich@usgs.gov","orcid":"https://orcid.org/0000-0002-7789-2831","contributorId":458,"corporation":false,"usgs":true,"family":"Lovich","given":"Jeffrey","email":"jeffrey_lovich@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":829328,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Agha, Mickey","contributorId":22235,"corporation":false,"usgs":false,"family":"Agha","given":"Mickey","email":"","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false},{"id":12425,"text":"University of Kentucky","active":true,"usgs":false}],"preferred":false,"id":829410,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smith, Amanda L. amandasmith@usgs.gov","contributorId":193098,"corporation":false,"usgs":true,"family":"Smith","given":"Amanda","email":"amandasmith@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":829411,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Delaney, David","contributorId":75444,"corporation":false,"usgs":true,"family":"Delaney","given":"David","affiliations":[],"preferred":false,"id":829412,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Arundel, Terence R. 0000-0003-0324-4249 tarundel@usgs.gov","orcid":"https://orcid.org/0000-0003-0324-4249","contributorId":139242,"corporation":false,"usgs":true,"family":"Arundel","given":"Terence","email":"tarundel@usgs.gov","middleInitial":"R.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":829413,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fleckenstein, Leo J.","contributorId":196259,"corporation":false,"usgs":false,"family":"Fleckenstein","given":"Leo","email":"","middleInitial":"J.","affiliations":[{"id":13019,"text":"Department of Forestry, University of Kentucky","active":true,"usgs":false}],"preferred":false,"id":829414,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Briggs, Jessica","contributorId":22691,"corporation":false,"usgs":true,"family":"Briggs","given":"Jessica","affiliations":[],"preferred":false,"id":829415,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Walde, Andrew","contributorId":212741,"corporation":false,"usgs":false,"family":"Walde","given":"Andrew","affiliations":[],"preferred":false,"id":829416,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Ennen, Joshua","contributorId":72691,"corporation":false,"usgs":true,"family":"Ennen","given":"Joshua","affiliations":[],"preferred":false,"id":829417,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70227044,"text":"70227044 - 2021 - Asynchronous flowering patterns in saguaro cacti (Carnegiea gigantea)","interactions":[],"lastModifiedDate":"2021-12-28T15:15:27.886637","indexId":"70227044","displayToPublicDate":"2021-12-12T09:13:00","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Asynchronous flowering patterns in saguaro cacti (Carnegiea gigantea)","docAbstract":"The saguaro cactus (Carnegiea gigantea [Engelm.] Britton & Rose) is a keystone species endemic to the Sonoran Desert of northern Mexico and the southwestern United States. The saguaro produces large white flowers near its stem apex (crown) during April–June, which bloom at night and close the following day. In 1924, Duncan Johnson reported that saguaro floral buds are likely to have an asymmetrical distribution in which buds occur in higher densities on the eastern half of a plant's crown. Using technology not available to Johnson, we tested his observations to determine whether flowers are asymmetrically distributed using repeat photography. We also tested whether there is a seasonal pattern of flowering that may explain Johnson’s observations. We tracked intra-individual flowering phenology of 20 saguaros and measured 2372 flowers across two reproductive seasons in Saguaro National Park, Tucson, Arizona. Flowers first appeared on the east side of all saguaro crowns at the start of the reproductive season, and then spread radially in a counterclockwise direction as the season progressed. In contrast to previous reports, saguaro flowers were consistently more abundant on the northern part of the crown than in the eastern part. To our knowledge, this study is the first to document a seasonal, counterclockwise pattern of asynchronous flowering in saguaro or any angiosperm. We discuss potential drivers of this phenomenon as well as implications for saguaros responding to climate change.
Dispersal is a critical life history strategy that has important conservation implications, particularly for at-risk species with active recovery efforts and migratory species. Both natal and breeding dispersal are driven by numerous selection pressures, including conspecific competition, individual characteristics, reproductive success, and spatiotemporal variation in habitat. Most studies focus on dispersal probabilities, but the distance traveled can affect survival, fitness, and even metapopulation dynamics.
We examined sources of variation in dispersal distances with 275 natal dispersal and 1335 interannual breeding events for piping plovers (Charadrius melodus) breeding in the Northern Great Plains between 2014 and 2019.
Natal dispersal was on average longer (mean: 81.0 km, median: 53 km) than adult breeding movements (mean: 23.7 km, median: 1 km). Individuals moved the shortest distances when hatched, previously nested, or settling on river habitats. When more habitat was available on their natal area than in the year prior, hatch-year birds moved shorter distances to their first breeding location. Similarly, adults also moved shorter distances when more habitat was available at the settling site and when in closer proximity to other known nesting areas. Additionally, adult movement distance was shorter when successfully hatching a nest the year prior, retaining a mate, or initiating a current nest earlier.
Habitat availability appears to be associated with dispersal distance for both hatch-year and adult piping plovers. Conservation efforts that integrate dispersal distances may benefit from maintaining nesting habitat within close proximity to other areas for adults and a network of clustered sites spread out across a larger landscape for natal dispersal.
","language":"English","publisher":"BMC","doi":"10.1186/s40462-021-00293-3","usgsCitation":"Swift, R.J., Anteau, M.J., Ellis, K.S., Ring, M., Sherfy, M.H., and Toy, D.L., 2021, Dispersal distance is driven by habitat availability and reproductive success in Northern Great Plains piping plovers: Movement Ecology, v. 9, 59, 14 p., https://doi.org/10.1186/s40462-021-00293-3.","productDescription":"59, 14 p.","ipdsId":"IP-123182","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":450043,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40462-021-00293-3","text":"Publisher Index Page"},{"id":396477,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana, North Dakota, South Dakota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.4248046875,\n 43.51668853502906\n ],\n [\n -97.2509765625,\n 43.51668853502906\n ],\n [\n -97.2509765625,\n 48.86471476180277\n ],\n [\n -105.4248046875,\n 48.86471476180277\n ],\n [\n -105.4248046875,\n 43.51668853502906\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","noUsgsAuthors":false,"publicationDate":"2021-12-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Swift, Rose J. 0000-0001-7044-6196","orcid":"https://orcid.org/0000-0001-7044-6196","contributorId":212082,"corporation":false,"usgs":true,"family":"Swift","given":"Rose","email":"","middleInitial":"J.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":836031,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anteau, Michael J. 0000-0002-5173-5870 manteau@usgs.gov","orcid":"https://orcid.org/0000-0002-5173-5870","contributorId":3427,"corporation":false,"usgs":true,"family":"Anteau","given":"Michael","email":"manteau@usgs.gov","middleInitial":"J.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":836032,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ellis, Kristen S. 0000-0003-2759-3670","orcid":"https://orcid.org/0000-0003-2759-3670","contributorId":251877,"corporation":false,"usgs":true,"family":"Ellis","given":"Kristen","email":"","middleInitial":"S.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":836033,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ring, Megan M. 0000-0001-8331-8492","orcid":"https://orcid.org/0000-0001-8331-8492","contributorId":225026,"corporation":false,"usgs":true,"family":"Ring","given":"Megan M.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":836034,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sherfy, Mark H. 0000-0003-3016-4105 msherfy@usgs.gov","orcid":"https://orcid.org/0000-0003-3016-4105","contributorId":125,"corporation":false,"usgs":true,"family":"Sherfy","given":"Mark","email":"msherfy@usgs.gov","middleInitial":"H.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":836035,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Toy, Dustin L. 0000-0001-5390-5784 dtoy@usgs.gov","orcid":"https://orcid.org/0000-0001-5390-5784","contributorId":5150,"corporation":false,"usgs":true,"family":"Toy","given":"Dustin","email":"dtoy@usgs.gov","middleInitial":"L.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":836036,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70236523,"text":"70236523 - 2021 - Influence of antecedent geology on the Holocene formation and evolution of Horn Island, Mississippi, USA","interactions":[],"lastModifiedDate":"2022-09-09T12:28:43.889046","indexId":"70236523","displayToPublicDate":"2021-12-11T07:25:11","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2667,"text":"Marine Geology","active":true,"publicationSubtype":{"id":10}},"title":"Influence of antecedent geology on the Holocene formation and evolution of Horn Island, Mississippi, USA","docAbstract":"Horn Island, one of the two most stable barriers along the Mississippi-Alabama chain (Cat, East and West Ship, Horn, West Petit Bois, Petit Bois, and Dauphin), provides critical habitat, helps regulate estuarine conditions in the Mississippi Sound, and reduces wave energy and storm surge before they reach the mainland shore. However, important details of the formation and evolution of the island in response to sea-level rise, storms, and antecedent geology remain unclear. This study integrates 2200 km of high-resolution geophysical data, 35 sediment cores, and 18 radiocarbon ages to better understand the geologic history of the island. Incised valleys of the Biloxi and Pascagoula Rivers underlie Horn Island and played a profound role in the evolution of the system. Within the incised valleys, sandy paleochannel deposits represent potential sediment sources during island development. Scour associated with wave and tidal ravinement processes liberated sand from the paleochannels and along with numerous other sizable sand sources on the shelf contributed to the formation and continued maintenance of Horn Island. Based on radiocarbon ages, transgressive ephemeral islands/shoals with no preserved shoreface existed at least 8000 cal yr BP and were frequently overwashed when sea-level rise rates were ~ 4–5 mm/yr. Approximately 5000 cal yr BP, coinciding with a deceleration in sea-level rise to about 1.4 mm/yr and attendant increased sand supply, radiocarbon ages associated with Horn Island's barrier complex and lower shoreface indicate a period of island stabilization. Seismic and sediment core data show a long history of westward lateral migration by longshore currents through tidal ravinement and inlet fill. Subsurface sand packages associated with tidal inlet fill and paleochannels are available for ravinement and may be important sand sources for Horn Island to maintain subaerial exposure with the expected accelerated future sea-level rise.
Transgression into adjacent uplands is an important global response of coastal wetlands to accelerated rates of sea level rise. “Ghost forests” mark a signature characteristic of marsh transgression on the landscape, as changes in tidal inundation and salinity cause bordering upland tree mortality, increase light availability, and the emergence of tidal marsh species due to reduced competition. To investigate these mechanisms of the marsh migration process, we conducted a field experiment to simulate a natural disturbance event (e.g., storm-induced flooding) by inducing the death of established trees (coastal loblolly pine, Pinus taeda) at the marsh-upland forest ecotone. After this simulated disturbance in 2014, we monitored changes in vegetation along an elevation gradient in control and treatment areas to determine if disturbance can lead to an ecosystem shift from forested upland to wetland vegetation. Light availability initially increased in the disturbed area, leading to an increase in biodiversity of vegetation with early successional grass and shrub species. However, over the course of this 5-year experiment, there was no increase in inundation in the disturbed areas relative to the control and pine trees recolonized becoming the dominant plant cover in the disturbed study areas. Thus, in the 5 years since the disturbance, there has been no overall shift in species composition toward more hydrophytic vegetation that would be indicative of marsh transgression with the removal of trees. These findings suggest that disturbance is necessary but not sufficient alone for transgression to occur. Unless hydrological characteristics suppress tree re-growth within a period of several years following disturbance, the regenerating trees will shade and outcompete any migrating wetland vegetation species. Our results suggest that complex interactions between disturbance, biotic resistance, and slope help determine the potential for marsh transgression.
Using diagnostic data and contemporary sampling efforts, we conducted surveillance for a diversity of pathogens, toxicants, and diseases of muskrats (Ondatra zibethicus). Between 1977 and 2019, 26 diagnostic cases were examined from Kansas and throughout the Southeast and Mid-Atlantic, USA. We identified multiple causes of mortality in muskrats, but trauma (8/26), Tyzzer’s disease (5/6), and cysticercosis (5/26) were the most common. We also conducted necropsies, during November 2018—January 2019 Pennsylvania muskrat trapping season, on 380 trapper-harvested muskrat carcasses after the pelt was removed. Tissue samples and exudate were tested for presence of or exposure to a suite of pathogens and contaminants. Gastrointestinal tracts were examined for helminths. Intestinal helminths were present in 39.2% of necropsied muskrats, with Hymenolepis spp. (62%) and echinostome spp. (44%) being the most common Molecular testing identified a low prevalence of infection with Clostridium piliforme in the feces and Sarcocystis spp. in the heart. We detected a low seroprevalence to Toxoplasma gondii (1/380). No muskrats were positive for Francisella tularensis or Babesia spp. Cysticercosis was detected in 20% (5/26) of diagnostic cases and 15% (57/380) of our trapper-harvested muskrats. Toxic concentrations of arsenic, cadmium, lead, or mercury were not detected in tested liver samples. Copper, molybdenum, and zinc concentrations were detected at acceptable levels comparative to previous studies. Parasite intensity and abundance were typical of historic reports; however, younger muskrats had higher intensity of infection than older muskrats which is contradictory to what has been previously reported. A diversity of pathogens and contaminants have been reported from muskrats, but the associated disease impacts are poorly understood. Our data are consistent with historic reports and highlight the wide range of parasites, pathogens and contaminants harbored by muskrats in Pennsylvania. The data collected are a critical component in assessing overall muskrat health and serve as a basis for understanding the impacts of disease on recent muskrat population declines.
","language":"English","publisher":"PLoS","doi":"10.1371/journal.pone.0260987","usgsCitation":"Ganoe, L., Brown, J., Lovallo, M., Yabsley, M., Garrett, K., Thompson, A., Poppenga, R., Ruder, M., and Walter, W., 2021, Surveillance for diseases, pathogens, and toxicants of muskrat (Ondatra zibethicus) in Pennsylvania and surrounding regions: PLoS ONE, v. 16, no. 12, e0260987, 21 p., https://doi.org/10.1371/journal.pone.0260987.","productDescription":"e0260987, 21 p.","ipdsId":"IP-132458","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":467218,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0260987","text":"Publisher Index Page"},{"id":466438,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -80.85632156110431,\n 42.2858130455985\n ],\n [\n -80.85632156110431,\n 39.57662331387951\n ],\n [\n -74.27817658513136,\n 39.57662331387951\n ],\n [\n -74.27817658513136,\n 42.2858130455985\n ],\n [\n -80.85632156110431,\n 42.2858130455985\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"16","issue":"12","noUsgsAuthors":false,"publicationDate":"2021-12-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Ganoe, Laken S.","contributorId":348374,"corporation":false,"usgs":false,"family":"Ganoe","given":"Laken S.","affiliations":[{"id":83355,"text":"Pennsylvania Cooperative Fish and Wildlife Research Unit","active":true,"usgs":false}],"preferred":false,"id":923410,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brown, Justin D.","contributorId":348375,"corporation":false,"usgs":false,"family":"Brown","given":"Justin D.","affiliations":[{"id":83356,"text":"Department of Veterinary and Biomedical Sciences","active":true,"usgs":false}],"preferred":false,"id":923411,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lovallo, Matthew J.","contributorId":348376,"corporation":false,"usgs":false,"family":"Lovallo","given":"Matthew J.","affiliations":[{"id":83357,"text":"Bureau of Wildlife Management","active":true,"usgs":false}],"preferred":false,"id":923412,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yabsley, Michael J.","contributorId":348377,"corporation":false,"usgs":false,"family":"Yabsley","given":"Michael J.","affiliations":[{"id":39308,"text":"Southeastern Cooperative Wildlife Disease Study","active":true,"usgs":false}],"preferred":false,"id":923413,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Garrett, Kayla B.","contributorId":348378,"corporation":false,"usgs":false,"family":"Garrett","given":"Kayla B.","affiliations":[{"id":81749,"text":"Warnell School of Forestry and Natural Resources","active":true,"usgs":false}],"preferred":false,"id":923414,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Thompson, Alec T.","contributorId":348379,"corporation":false,"usgs":false,"family":"Thompson","given":"Alec T.","affiliations":[{"id":39308,"text":"Southeastern Cooperative Wildlife Disease Study","active":true,"usgs":false}],"preferred":false,"id":923415,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Poppenga, Robert H.","contributorId":348380,"corporation":false,"usgs":false,"family":"Poppenga","given":"Robert H.","affiliations":[{"id":36526,"text":"California Animal Health and Food Safety Laboratory","active":true,"usgs":false}],"preferred":false,"id":923416,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ruder, Mark G.","contributorId":348381,"corporation":false,"usgs":false,"family":"Ruder","given":"Mark G.","affiliations":[{"id":39308,"text":"Southeastern Cooperative Wildlife Disease Study","active":true,"usgs":false}],"preferred":false,"id":923417,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Walter, W. David 0000-0003-3068-1073","orcid":"https://orcid.org/0000-0003-3068-1073","contributorId":219540,"corporation":false,"usgs":true,"family":"Walter","given":"W. 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Biocrusts may influence the availability and nature of safe sites for plant recruitment and the susceptibility of an area to invasion by non-native species. Therefore, to investigate the potential role of biocrusts in invasive species management, we sought to determine whether native and non-native grass recruitments in two North American deserts were differentially affected by biocrusts. We conducted a series of coordinated experiments in field, semi-controlled, and controlled environment settings in the Colorado Plateau and Sonoran Desert using contrasting biocrust and grass functional types. Experiments in field environments focused on early establishment of grass seedlings whereas controlled environment experiments focused on seedling emergence. Within each experiment, we compared responses (frequency, magnitude, and timing of emergence/establishment) both across species (biocrust types pooled) and across species and levels of biocrust development. Native grasses varied by experiment and included Aristida purpurea, A. purpurea var. longiseta, Bouteloua gracilis, and Vulpia octoflora. Emergence of non-native Bromus tectorum was similar to that of native grasses on the Colorado Plateau. Differences in emergence of native vs. non-native grasses in the Sonoran Desert were species- and response-specific. Emergence of the non-native Bromus rubens was comparable to that of native grasses whereas emergence frequency and magnitude of the non-native Pennisetum ciliare was lower compared with two of four native species. Within a grass species, emergence was higher and faster on bare soil compared with biocrusts in the Sonoran Desert semi-controlled and greenhouse environment experiments. However, the pattern was not consistent across other experiments. When comparing across Colorado Plateau and Sonoran Desert biocrusts in greenhouse experiments, we found that emergence of native grasses was higher on Colorado Plateau biocrusts. Based on the lack of consistent results across our experiments, grass recruitment on biocrusts appears to be driven more by species-specific traits than species provenance. Our greenhouse experiments suggest that biocrust topographic relief is an important safe site trait influencing plant recruitment.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.3841","usgsCitation":"McIntyre, C., Archer, S.R., Predick, K., and Belnap, J., 2021, Biocrusts do not differentially influence emergence and early establishment of native and non-native grasses: Ecosphere, v. 12, no. 12, e03841, 18 p., https://doi.org/10.1002/ecs2.3841.","productDescription":"e03841, 18 p.","ipdsId":"IP-125741","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":488350,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.3841","text":"Publisher Index Page"},{"id":393588,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Utah","otherGeospatial":"Colorado Plateau, Sonoran Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.05804443359375,\n 31.884554393746278\n ],\n [\n -110.86715698242186,\n 31.884554393746278\n ],\n [\n -110.86715698242186,\n 32.013898345577914\n ],\n [\n -111.05804443359375,\n 32.013898345577914\n ],\n [\n -111.05804443359375,\n 31.884554393746278\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.62570190429688,\n 38.155077102180655\n ],\n [\n -109.2974853515625,\n 38.155077102180655\n ],\n [\n -109.2974853515625,\n 38.371808917147554\n ],\n [\n -109.62570190429688,\n 38.371808917147554\n ],\n [\n -109.62570190429688,\n 38.155077102180655\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"12","noUsgsAuthors":false,"publicationDate":"2021-12-09","publicationStatus":"PW","contributors":{"authors":[{"text":"McIntyre, Cheryl","contributorId":270544,"corporation":false,"usgs":false,"family":"McIntyre","given":"Cheryl","email":"","affiliations":[{"id":56180,"text":"School of Natural Resources and the Environment, The University of Arizona, 1064 East Lowell Street, Tucson, AZ, 85719, USA;National Park Service, Chihuahuan Desert Network, 12661 E Broadway Blvd., Tucson, AZ, 85748, USA","active":true,"usgs":false}],"preferred":false,"id":829545,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Archer, Steven R.","contributorId":139043,"corporation":false,"usgs":false,"family":"Archer","given":"Steven","email":"","middleInitial":"R.","affiliations":[{"id":12625,"text":"School of Natural Resources and the Environment, University of Arizona, Tucson, AZ, 85721, USA","active":true,"usgs":false}],"preferred":false,"id":829546,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Predick, Katie","contributorId":270545,"corporation":false,"usgs":false,"family":"Predick","given":"Katie","email":"","affiliations":[{"id":56181,"text":"School of Natural Resources and the Environment, The University of Arizona, 1064 East Lowell Street, Tucson, AZ, 85719, USA","active":true,"usgs":false}],"preferred":false,"id":829548,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Belnap, Jayne 0000-0001-7471-2279 jayne_belnap@usgs.gov","orcid":"https://orcid.org/0000-0001-7471-2279","contributorId":1332,"corporation":false,"usgs":true,"family":"Belnap","given":"Jayne","email":"jayne_belnap@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":829547,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70226873,"text":"70226873 - 2021 - Ten simple rules for creating a scientific web application","interactions":[],"lastModifiedDate":"2021-12-17T14:58:45.469602","indexId":"70226873","displayToPublicDate":"2021-12-09T08:53:24","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5727,"text":"PLOS Computational Biology","active":true,"publicationSubtype":{"id":10}},"title":"Ten simple rules for creating a scientific web application","docAbstract":"The use of scientific web applications (SWApps) across biological and environmental sciences has grown exponentially over the past decade or so. Although quantitative evidence for such increased use in practice is scant, collectively, we have observed that these tools become more commonplace in teaching, outreach, and in science coproduction (e.g., as decision support tools). Despite the increased popularity of SWApps, researchers often receive little or no training in creating such tools. Although rolling out SWApps can be a relatively simple and quick process using modern, popular platforms like R shiny apps or Tableau dashboards, making them useful, usable, and sustainable is not. These 10 simple rules for creating a SWApp provide a foundation upon which researchers with little to no experience in web application design and development can consider, plan, and carry out SWApp projects.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pcbi.1009574","usgsCitation":"Burnett, J.L., Dale, R., Hou, C.Y., Palomo-Munoz, G., Stack-Whitney, K., Aulenbach, S., Bristol, R.S., Valle, D., and Wellman, T., 2021, Ten simple rules for creating a scientific web application: PLOS Computational Biology, v. 17, no. 12, e1009574, 12, https://doi.org/10.1371/journal.pcbi.1009574.","productDescription":"e1009574, 12","ipdsId":"IP-124888","costCenters":[{"id":38128,"text":"Science Analytics and Synthesis","active":true,"usgs":true}],"links":[{"id":450052,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pcbi.1009574","text":"Publisher Index Page"},{"id":393048,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"17","issue":"12","noUsgsAuthors":false,"publicationDate":"2021-12-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Burnett, Jessica Leigh 0000-0002-0896-5099","orcid":"https://orcid.org/0000-0002-0896-5099","contributorId":248195,"corporation":false,"usgs":true,"family":"Burnett","given":"Jessica","email":"","middleInitial":"Leigh","affiliations":[{"id":38128,"text":"Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":828562,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dale, Renee 0000-0002-1674-1247","orcid":"https://orcid.org/0000-0002-1674-1247","contributorId":270163,"corporation":false,"usgs":false,"family":"Dale","given":"Renee","email":"","affiliations":[{"id":56103,"text":"Donald Danforth Plant Science Center","active":true,"usgs":false}],"preferred":false,"id":828563,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hou, Chung Yi 0000-0002-8087-1775","orcid":"https://orcid.org/0000-0002-8087-1775","contributorId":270164,"corporation":false,"usgs":false,"family":"Hou","given":"Chung","email":"","middleInitial":"Yi","affiliations":[{"id":37768,"text":"USGS Contractor","active":true,"usgs":false}],"preferred":false,"id":828564,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Palomo-Munoz, Gabriela","contributorId":248196,"corporation":false,"usgs":false,"family":"Palomo-Munoz","given":"Gabriela","email":"","affiliations":[{"id":16610,"text":"University of Nebraska-Lincoln","active":true,"usgs":false}],"preferred":false,"id":828605,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stack-Whitney, Kaitlin 0000-0002-0815-5037","orcid":"https://orcid.org/0000-0002-0815-5037","contributorId":270165,"corporation":false,"usgs":false,"family":"Stack-Whitney","given":"Kaitlin","email":"","affiliations":[{"id":32390,"text":"Rochester Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":828567,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Aulenbach, Steven 0000-0002-0172-6538","orcid":"https://orcid.org/0000-0002-0172-6538","contributorId":261331,"corporation":false,"usgs":true,"family":"Aulenbach","given":"Steven","email":"","affiliations":[{"id":207,"text":"Core Research Center","active":true,"usgs":true}],"preferred":true,"id":828565,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bristol, R. Sky 0000-0003-1682-4031 sbristol@usgs.gov","orcid":"https://orcid.org/0000-0003-1682-4031","contributorId":3585,"corporation":false,"usgs":true,"family":"Bristol","given":"R.","email":"sbristol@usgs.gov","middleInitial":"Sky","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":false,"id":828566,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Valle, Denis 0000-0002-9830-8876","orcid":"https://orcid.org/0000-0002-9830-8876","contributorId":270166,"corporation":false,"usgs":false,"family":"Valle","given":"Denis","email":"","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":828569,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wellman, Tristan 0000-0003-3049-6214 twellman@usgs.gov","orcid":"https://orcid.org/0000-0003-3049-6214","contributorId":2166,"corporation":false,"usgs":true,"family":"Wellman","given":"Tristan","email":"twellman@usgs.gov","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":828568,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70227327,"text":"70227327 - 2021 - Dam removal and river restoration","interactions":[],"lastModifiedDate":"2022-01-10T14:39:37.546875","indexId":"70227327","displayToPublicDate":"2021-12-09T08:38:25","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Dam removal and river restoration","docAbstract":"The removal of dams from rivers has become a common and widespread practice in the United States and Europe. Although often initiated by factors like economics and safety, ecosystem restoration is often a desired benefit and outcome of dam removal. We describe the physical and ecological effects that the placement and removal of dams have on rivers. We then focus on the drivers of dam removal, present considerations for undertaking a dam removal project, and discuss case-studies and recent syntheses describing the ecological outcomes of dam removal.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Encyclopedia of Inland Waters","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-12-819166-8.00101-8","usgsCitation":"Duda, J.J., and Bellmore, J.R., 2021, Dam removal and river restoration, chap. of Encyclopedia of Inland Waters, HTML Document, https://doi.org/10.1016/B978-0-12-819166-8.00101-8.","productDescription":"HTML Document","ipdsId":"IP-126235","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":394100,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Duda, Jeffrey J. 0000-0001-7431-8634 jduda@usgs.gov","orcid":"https://orcid.org/0000-0001-7431-8634","contributorId":148954,"corporation":false,"usgs":true,"family":"Duda","given":"Jeffrey","email":"jduda@usgs.gov","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":830478,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bellmore, J. Ryan","contributorId":271034,"corporation":false,"usgs":false,"family":"Bellmore","given":"J.","email":"","middleInitial":"Ryan","affiliations":[{"id":56260,"text":"U.S. Forest Service, Pacific Northwest Research Station, 11175 Auke Lake Way, Juneau, Alaska, 99801","active":true,"usgs":false}],"preferred":false,"id":830479,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70241613,"text":"70241613 - 2021 - Subsurface temperature properties for three types of permeable pavements in cold weather climates and implications for deicer reduction","interactions":[],"lastModifiedDate":"2023-03-24T12:29:30.894323","indexId":"70241613","displayToPublicDate":"2021-12-09T07:23:08","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Subsurface temperature properties for three types of permeable pavements in cold weather climates and implications for deicer reduction","docAbstract":"An information-theoretic approach was used to evaluate non-native freshwater fish species introduced to insular habitats of Hawaii and Guam comparing successful establishments vs. failures. Since the late 1800s, as many as 81 non-native freshwater fish species have been recorded as introduced to Hawaii and Guam (combined) and 50 (62%) of these are documented as having one or more established populations. We examined eleven independent variables to investigate establishment success by creating 21 a priori logistic regression models ranked using Akaike's Information Criterion adjusted for small sample size. An additional eight post-hoc models were included that comprised the best a priori model and various combinations of individual variables. The best overall model of establishment probability included effects of taxonomic affinity (family membership), prior establishment success on other tropical islands, and hypoxia tolerance. Establishment success in Hawaii and Guam was highest for those species established on many other islands, and according to our best model air-breathing fishes were more likely to become established. Six fish families, each with from three to 18 species introduced to Pacific islands, were highly successful at establishment: Cichlidae (16 established of 18 species introduced), Poeciliidae (seven of eight), Cyprinidae (four of seven), Centrarchidae (four of four), Clariidae (three of three), and Loricariidae (three of four). Those that successfully established include both small and moderately large-bodied taxa, while representing a diverse array of other morphological and life-history traits. Pathways and motives associated with fish introductions in the Pacific have been linked to desires to develop aquaculture, enhance wild stocks of food, sport, and bait fishes, for use as biological control agents, or are linked to the ornamental fish trade. We found that many established species were introduced via multiple pathways (up to eight) and our analyses suggest that the combination of prior establishment success on other tropical islands and presence of non-native fishes in multiple pathways was indicative of high propagule pressure. Our study results and conclusions on Pacific tropical island introductions are in general agreement with previous studies on non-native freshwater fishes in other regions of the world and similar to observations in continental ecosystems and temperate zones.
In the face of climate change, wind energy represents an important alternative to oil and gas extraction to meet increasing energy demands, but it has the potential to disrupt wildlife populations. Because behavioral adjustments, such as altered habitat selection, are a primary way that long-lived species respond to novel disturbances, we evaluated effects of wind energy development on pronghorn (Antilocapra americana) space use and habitat selection. Using data from GPS-collared female pronghorn in the Shirley Basin of south-central Wyoming, USA, we tested four potential effects of wind turbines on pronghorn space use during the summer and winter: (1) displacement away from wind turbines, (2) increase in size of home ranges, (3) short-term avoidance behavior within home ranges, and (4) changes in avoidance behavior within home ranges over time. We monitored 166 individuals over five summers (2010, 2011, 2018, 2019, and 2020) and 142 individuals over five winters (2009/2010, 2010/2011, 2011/2012, 2018/2019, and 2019/2020) and used resource selection functions to evaluate selection relative to turbines after controlling for other habitat factors, such as snow depth. Although a lack of consistent negative effects of wind turbines on pronghorn across years suggested that wind energy development may have less severe and more intermittent effects on pronghorn than oil and gas development has had on other ungulates, there was a trend toward increased displacement during the study and behavioral avoidance was apparent for individuals in close proximity to turbines. However, pronghorn were highly variable in their fine-scale habitat selection, across both individuals and years, which could make effects of wind energy development difficult to detect. Nevertheless, some individuals, particularly those close to wind-energy facilities, did avoid turbines, which could translate to population-level behavioral or demographic changes over time and affect the resilience and stability of the population. Over time, the accumulation of development, including wind turbines, roads, and fences, can both limit movement and fragment habitat, potentially reaching a critical threshold beyond which populations are negatively impacted.
Spatial organization plays prominent roles in disease transmission, genetics, and demography of wildlife populations and is therefore an important consideration not only for wildlife management, but also for inference about populations and processes. We used hierarchical agglomerative clustering of a spatial graph network to partition Wind Cave National Park (WICA) into five regions used by 163 female elk (Cervus elaphus) marked with global positioning system collars during 2005–08 and 2011–13. We grouped elk based on differential use of the five regions, developed a priori models for inter-group variation in the occurrence of chronic wasting disease (CWD), and used Akaike's information criterion to compare models and stratify regions. Previous descriptions of elk population structure, which have been based on social contact or overlap of individual ranges, have distinguished spatially disjunct population subsets. Constructing hierarchical partitions of the landscape enabled us to also discern and describe overlapping and nested subsets. During 2016–18, apparent park-wide prevalence of CWD was 0.18 (90% CI = [0.146, 0.182]); however, prevalence within three spatial strata used primarily by different elk ranged from 0.03 ([0.008, 0.074]) to 0.29 ([0.211, 0.375]). In context with published estimates of recruitment, predation, and anthropogenic mortality, such differences in prevalence equate to increasing local abundance of elk in southwestern WICA, stable to declining abundance in the west/northwest, and rapidly declining abundance in the east. Despite the modest size of WICA (11,357 ha), park-wide averages conflate effects of elk distribution and disease, obscuring spatial patterns with profound implications for study and management of elk and CWD. Graph networks have been used widely in ecology to describe such phenomena as social relationships, connectivity of habitat patches, animal movements, and the spread of disease. Extension to partitioning of geographic range is straightforward but entails different considerations. We discuss allocation of sampling effort, construction of an initial partition, specification of a model for graph cohesion, selection of a clustering algorithm, and identification of useful partitions.