The endangered Hawaiian hoary bat (Lasiurus semotus, Vespertilionidae, also known as Aeorestes semotus and ‘ōpe‘ape‘a) occurs on all the principal volcanic islands in Hawai‘i. Advances in acoustic bat monitoring techniques have contributed to the body of knowledge of bat activity and behavior in many areas of the State of Hawai‘i; however, there is still much that is unknown about the population and seasonal distribution of Hawaiian hoary bats on O‘ahu. A two-year acoustic survey for presence of Hawaiian hoary bats was conducted at 17 stations across four Marine Corps Base Hawaii (MCBH) properties on O‘ahu to document distribution, seasonal patterns, and foraging activity. Bats were confirmed present at all properties; MCBH Kaneohe Bay on Mōkapu Peninsula, Marine Corps Training Area Bellows (MCTAB) in Waimanalo, Camp H M Smith in Halawa Heights, and Puuloa Range Training Facility (RTF) on the ‘Ewa coastal plain. Hawaiian hoary bats were recorded in airspace at all four properties during important periods of Hawaiian hoary bat life history, including periods of pregnancy, lactation, and pup fledging; however, overall presence was low. Foraging activity as identified from characteristic feeding buzzes was very rare and was recorded on only three nights over the entire study. Within-night bat detection pooled for all nights and stations at each property showed that bat activity was mostly confined to the first several hours of the night at MCBH Kaneohe Bay and Puuloa RTF, whereas bat activity was spread throughout the night at Camp H M Smith and MCTAB. Overall, detection frequency was low (year 1 = 0.009, year 2 = 0.007, average = 0.008) at the study sites on O‘ahu compared to results from acoustic monitoring studies on the islands of Maui and Hawai‘i. However, the low rate of bat presence on MCBH properties is consistent with recent studies at other locations on the Island of O‘ahu. Monitoring the seasonal presence and distribution of Hawaiian hoary bats on MCBH facilities, especially at forest and wetland habitats, could contribute to the broader scientific understanding of islandwide distribution and behavior on O‘ahu, which is essential for species recovery planning and implementation of best management practices.
","language":"English","publisher":"Hawai‘i Cooperative Studies Unit, University of Hawai‘i at Hilo","collaboration":"HI/Dept. of Land and Nat. Resources; DOI/U.S. Fish and Wildlife; DoD/Marine Corps Base Hawaii; Hawai‘i Cooperative Studies Unit, University of Hawai‘i at Hilo","usgsCitation":"Pinzari, C., Montoya-Aiona, K., Gross, D., and Courtot, K., 2021, Hawaiian hoary bat acoustic surveys on Marine Corps Base Hawaii, 2019–2021: Technical Report 100, iv, 29 p.","productDescription":"iv, 29 p.","ipdsId":"IP-132851","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":393176,"type":{"id":15,"text":"Index Page"},"url":"https://hdl.handle.net/10790/6798"},{"id":393190,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"O'ahu","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -158.0108642578125,\n 21.220261047755002\n ],\n [\n -157.6318359375,\n 21.220261047755002\n ],\n [\n -157.6318359375,\n 21.54251136615996\n ],\n [\n -158.0108642578125,\n 21.54251136615996\n ],\n [\n -158.0108642578125,\n 21.220261047755002\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Pinzari, Corinna A. 0000-0001-9794-7564","orcid":"https://orcid.org/0000-0001-9794-7564","contributorId":208455,"corporation":false,"usgs":false,"family":"Pinzari","given":"Corinna A.","affiliations":[{"id":13341,"text":"Hawai‘i Cooperative Studies Unit, University of Hawai‘i at Hilo","active":true,"usgs":false}],"preferred":false,"id":828771,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Montoya-Aiona, Kristina 0000-0002-1776-5443 kmontoya-aiona@usgs.gov","orcid":"https://orcid.org/0000-0002-1776-5443","contributorId":5899,"corporation":false,"usgs":true,"family":"Montoya-Aiona","given":"Kristina","email":"kmontoya-aiona@usgs.gov","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":828772,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gross, Danielle","contributorId":218186,"corporation":false,"usgs":false,"family":"Gross","given":"Danielle","email":"","affiliations":[{"id":13341,"text":"Hawai‘i Cooperative Studies Unit, University of Hawai‘i at Hilo","active":true,"usgs":false}],"preferred":false,"id":828773,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Courtot, Karen 0000-0002-8849-4054 kcourtot@usgs.gov","orcid":"https://orcid.org/0000-0002-8849-4054","contributorId":140002,"corporation":false,"usgs":true,"family":"Courtot","given":"Karen","email":"kcourtot@usgs.gov","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":828774,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70229519,"text":"70229519 - 2021 - Mineral deposit discovery order and three-part quantitative assessments","interactions":[],"lastModifiedDate":"2022-03-11T13:08:11.334928","indexId":"70229519","displayToPublicDate":"2021-11-11T07:07:04","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2954,"text":"Ore Geology Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Mineral deposit discovery order and three-part quantitative assessments","docAbstract":"Larger oil pools tending to be discovered earlier in an exploration play suggests the same pattern might exist for mineral deposits and could be used in predicting sizes of undiscovered deposits in mineral assessments. The volume of individual petroleum pools is highly correlated with surface projection area of pools in basins. The gradual additions to individual oil pool reserves over time adds to the appearance of larger pools being discovered earlier.
Comparisons of surface projected areas of mineral deposits to their tonnages showed significant positive relationships in all 10 deposit types analyzed, suggesting that larger deposits should be discovered earlier than small deposits.
Analysis of deposits consistent with three-part mineral assessments identified 9 combinations of mineral deposit types in large regions each containing multiple geological permissive tracts showing negative and 1 positive relationships of deposit size with discovery date significant at the 1% level. Twenty other tests of regions containing multiple permissive settings had either negative or positive relationships, none significantly different from those that might occur by chance. The large regions are mostly based on political boundaries. These results suggest mineral deposit discovery order is not the same as observed in oil pool exploration.
The widely employed three-part quantitative mineral resource assessments are an obvious choice to benefit from patterns of declining deposit sizes with order of discovery. The 30 tests of relationships of discovery dates to deposit sizes demonstrated here were performed with deposits consistent with those in three-part assessments, but the large areas are not consistent with permissive tracts used in these assessments because they also contain substantial non-permissive geology.
In 100 permissive tracts assessed with three-part assessments of multiple deposit types located throughout the world, the median number of known well-explored deposits is 1 and 90 percent of tracts report less than 9 deposits. The number of well-explored deposits in three-part assessed tracts tends to be quite small, limiting any ability to recognize a discovery order versus size relationship.
In a three-part assessment of undiscovered porphyry copper deposits of South America, only 7 of 26 delineated tracts contained more than 2 known deposits and only 1 had a significant negative relationship between tonnage of known deposits and year of discovery (p = 0.04). Most predicted undiscovered deposits in this tract were expected to be under extensive unexplored post-mineralization cover, meaning the general grade and tonnage model should be applied because the discovery order process starts over. Projection of deposit sizes based on discovery order would provide a biased estimate of the undiscovered deposit sizes in this case. Thus, although a discovery order versus size relationship could exist in three-part mineral assessments, only rarely might the pattern be useful to predict sizes of undiscovered deposits.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.oregeorev.2021.104566","usgsCitation":"Singer, D., and Zientek, M., 2021, Mineral deposit discovery order and three-part quantitative assessments: Ore Geology Reviews, v. 139, no. Part B, 104566, 9 p., https://doi.org/10.1016/j.oregeorev.2021.104566.","productDescription":"104566, 9 p.","ipdsId":"IP-127845","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":467221,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.oregeorev.2021.104566","text":"Publisher Index Page"},{"id":397016,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":396983,"type":{"id":15,"text":"Index Page"},"url":"https://doi.org/10.1016/j.oregeorev.2021.104566"}],"volume":"139","issue":"Part B","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Singer, Donald A. 0000-0001-6812-6441","orcid":"https://orcid.org/0000-0001-6812-6441","contributorId":288318,"corporation":false,"usgs":false,"family":"Singer","given":"Donald A.","affiliations":[],"preferred":false,"id":837729,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zientek, Michael L. 0000-0002-8522-9626","orcid":"https://orcid.org/0000-0002-8522-9626","contributorId":210763,"corporation":false,"usgs":true,"family":"Zientek","given":"Michael L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":837728,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70225753,"text":"70225753 - 2021 - Exposure of predatory and scavenging birds to anticoagulant rodenticides in France: Exploration of data from French surveillance programs","interactions":[],"lastModifiedDate":"2022-01-25T17:12:08.987756","indexId":"70225753","displayToPublicDate":"2021-11-05T07:24:58","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Exposure of predatory and scavenging birds to anticoagulant rodenticides in France: Exploration of data from French surveillance programs","docAbstract":"Wild raptors are widely used to assess exposure to different environmental contaminants, including anticoagulant rodenticides (ARs). ARs are used on a global scale for rodent control, and act by disruption of the vitamin K cycle that results in haemorrhage usually accompanied by death within days. Some ARs are highly persistent and bioaccumulative, which can cause significant exposure of non-target species. We characterized AR exposure in a heterogeneous sample of dead raptors collected over 12 years (2008–2019) in south-eastern France. Residue analysis of 156 liver samples through LC-MS/MS revealed that 50% (78/156) were positive for ARs, with 13.5% (21/156) having summed second-generation AR (SGAR) concentrations >100 ng/g ww. While SGARs were commonly detected (97.4% of positive samples), first-generation ARs were rarely found (7.7% of positive samples). ARs were more frequently detected and at greater concentration in predators (prevalence: 82.5%) than in scavengers (38.8%). Exposure to multiple ARs was common (64.1% of positive samples). While chlorophacinone exposure decreased over time, an increasing exposure trend was observed for the SGAR brodifacoum, suggesting that public policies may not be efficient at mitigating risk of exposure for non-target species. Haemorrhage was observed in 88 birds, but AR toxicosis was suspected in only 2 of these individuals, and no difference in frequency of haemorrhage was apparent in birds displaying summed SGAR levels above or below 100 ng/g ww. As for other contaminants, 17.2% of liver samples (11/64) exhibited Pb levels compatible with sub-clinical poisoning (>6 μg/g dw), with 6.3% (4/64) above the threshold for severe/lethal poisoning (>30 μg/g dw). Nine individuals with Pb levels >6 μg/g dw also had AR residues, demonstrating exposure to multiple contaminants. Broad toxicological screening for other contaminants was positive for 18 of 126 individuals, with carbofuran and mevinphos exposure being the suspected cause of death of 17 birds. Our findings demonstrate lower but still substantial AR exposure of scavenging birds compared to predatory birds, and also illustrate the complexity of diagnosing AR toxicosis through forensic investigations.
The Anza-Cahuilla groundwater basin located mainly in the semi-arid headwaters of the Santa Margarita River watershed in southern California is the principle source of groundwater for a rural disadvantaged community and two Native American Tribes, the Ramona Band of Cahuilla and the Cahuilla. Groundwater in the study area is derived entirely from precipitation and managing groundwater sustainably requires an accurate assessment of the water balance components, yet long-term estimates do not exist. Demand for groundwater in the region has increased and groundwater quality has decreased due to population growth and increased irrigated cropland. To characterize monthly long-term natural recharge and runoff estimates, a physically-based water balance model (Basin Characterization Model) was locally calibrated and validated using nearby streamgages and published estimates of climatic and hydrologic variables. The average modeled annual recharge and runoff from 1981 to 2010 was 5.4 × 106 and 1.2 × 107 m3, respectively, for the study area. Recharge and runoff do not reliably occur in large amounts every year and recharge rarely occurs in the groundwater basin footprint. These long-term estimates can be used by water managers, stakeholders, and Native American Tribes to develop plans for sustainable management of future water resources, and as inputs to a three-dimensional groundwater model.
","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12971","usgsCitation":"Stern, M.A., Flint, L.E., Flint, A.L., and Christensen, A.H., 2021, A basin-scale approach to estimating recharge in the desert: Anza-Cahuilla groundwater basin, CA: Journal of the American Water Resources Association, v. 57, no. 6, p. 990-1003, https://doi.org/10.1111/1752-1688.12971.","productDescription":"14 p.","startPage":"990","endPage":"1003","ipdsId":"IP-119217","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":450287,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1752-1688.12971","text":"Publisher Index Page"},{"id":436125,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9BAMCP4","text":"USGS data release","linkHelpText":"Basin Characterization Model (BCMv8) monthly recharge and runoff for the Anza-Cahuilla Groundwater Basin, California"},{"id":391385,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Anza-Cahuilla groundwater basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.9166,\n 33.3333\n ],\n [\n -116.25,\n 33.3333\n ],\n [\n -116.25,\n 33.75\n ],\n [\n -116.9166,\n 33.75\n ],\n [\n -116.9166,\n 33.3333\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"57","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-11-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Stern, Michelle A. 0000-0003-3030-7065 mstern@usgs.gov","orcid":"https://orcid.org/0000-0003-3030-7065","contributorId":4244,"corporation":false,"usgs":true,"family":"Stern","given":"Michelle","email":"mstern@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":826392,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flint, Lorraine E. 0000-0002-7868-441X lflint@usgs.gov","orcid":"https://orcid.org/0000-0002-7868-441X","contributorId":1184,"corporation":false,"usgs":true,"family":"Flint","given":"Lorraine","email":"lflint@usgs.gov","middleInitial":"E.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":826393,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Flint, Alan L. 0000-0002-5118-751X aflint@usgs.gov","orcid":"https://orcid.org/0000-0002-5118-751X","contributorId":1492,"corporation":false,"usgs":true,"family":"Flint","given":"Alan","email":"aflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":826394,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Christensen, Allen H. 0000-0002-7061-5591 ahchrist@usgs.gov","orcid":"https://orcid.org/0000-0002-7061-5591","contributorId":1510,"corporation":false,"usgs":true,"family":"Christensen","given":"Allen","email":"ahchrist@usgs.gov","middleInitial":"H.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":826395,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70225732,"text":"70225732 - 2021 - Evidence of glacial activity during MIS 4 in the Rocky Mountains, Colorado, USA","interactions":[],"lastModifiedDate":"2025-04-28T15:22:06.512155","indexId":"70225732","displayToPublicDate":"2021-11-02T06:32:52","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":899,"text":"Arctic, Antarctic, and Alpine Research","active":true,"publicationSubtype":{"id":10}},"title":"Evidence of glacial activity during MIS 4 in the Rocky Mountains, Colorado, USA","docAbstract":"The Ziegler Reservoir fossil site near Snowmass Village, Colorado, provides a rare opportunity to examine environmental conditions in the Rocky Mountains during marine isotope stage (MIS) 4 (71–57 ka). Although recognized as a global-scale cold event, MIS 4 is typically absent from Rocky Mountain glacial chronologies because the geologic evidence was covered or destroyed during the subsequent, and more extensive, MIS 2 (Pinedale; 29–14 ka) glaciation. Ziegler Reservoir lies beyond the Pinedale glacial extent, which allowed for the preservation of a long-lived sequence of eolian sediments deposited in a lacustrine environment that spans from late MIS 6 (ca. 140 ka) through early MIS 3 (ca. 55 ka). Sediments dating to MIS 4 exhibit a significant increase in clay-sized particles, suggesting that the source areas, most likely nearby glacio-fluvial deposits, were enriched with fine-grained material at that time. We hypothesize that the elevated clay content was the result of rock flour production by nearby valley glaciers that were active in the Rocky Mountains during MIS 4. The results of our study illustrate how recognizing indirect evidence of glacial activity can result in a more complete record of past climate conditions than what could be achieved by the study of moraines alone.
In the San Francisco Estuary (SFE), the effects of freshwater flow on the aquatic ecosystem have been studied extensively over the years and remains a contentious management issue. It is especially contentious with regards to the Delta Smelt (Hypomesus transpacificus), a species endemic to the SFE that has been listed as threatened under the Federal Endangered Species Act and endangered by the State of California. Early studies of Delta Smelt distribution within the SFE suggested that Delta Smelt habitat is determined largely by freshwater flow; however, the exact mechanisms and processes producing such benefits remained unclear. In the summer of 2017, the Flow Alteration Management, Analysis, and Synthesis Team (FLOAT-MAST) was established to analyze, synthesize, and summarize the data collected from the various flow-related monitoring and special studies occurring in 2017(see Table Intro 4). This report will focus on the 2017 summer-fall status of Delta Smelt and its habitat following a record wet year.
There has been a long-term decline in the abundance of Delta Smelt associated with a decline in other pelagic fishes. Investigators concluded that the decline has likely been caused by the interactive effects of several causes, including changes in both physical and biotic habitats, many of which are tied to amount and timing of freshwater flow. For this report, we formulated a number of basic predictions about the likely effects of high flows in 2017 on Delta Smelt and their habitat (Table 3). We use a qualitative weight of evidence approach to evaluate whether these predictions were supported by available data. Data sources included a variety of long-term monitoring surveys conducted by Interagency Ecological Program (IEP) agencies, as well as model outputs.
Delta Smelt population, health, and life history metrics rarely responded as predicted. Water temperature appears to have a stronger effect on Delta Smelt growth rate and some metrics of life history diversity than outflow or X2 position. Other life history diversity attributes varied but did not appear to be driven by outflow or temperature. Health status was difficult to interpret. Low prevalence of lesions and improved nutritional condition during the drought was contradicted by declining overall population levels. Because of the sparse catches of Delta Smelt in the post-POD years, we consider the data insufficient to reach firm conclusions about the predictions concerning range and distribution of Delta Smelt, especially in the fall. The prediction of high survival was not supported. The 2017 Delta Smelt year class began with poor recruitment in spring of 2017 and below average survival for spring to summer and summer to fall. Thus, low production and low survival led to low abundance of all life stages. During the fall to winter period survival improved, yet the resulting adults were low in number. Foraging success of the fish captured, as measured by stomach fullness, was high for juveniles and adults in 2017 relative to recent years associated with the higher densities of common zooplankton prey that occurred in 2017.
Northern bobwhite Colinus virginianus populations have been rapidly declining in the eastern, central, and southern United States for decades. Land use change and an incompatibility between northern bobwhite resource needs and human land use practices have driven declines. Here, we applied occupancy analyses on two spatial scales (state level and ecoregion level) to more than 5,000 northern bobwhite surveys conducted over 6 y across the entire state of Arkansas to explore patterns in occupancy and land use variables, and to identify priority areas for management and conservation. At the state level, northern bobwhite occupied 29% of sites and northern bobwhite were most likely to occur in areas with a high percentage of early successional habitat (grassland, pasture, and shrubland). The statewide model predicted that northern bobwhite were likely to occur (≥ 75% predicted occupancy) in < 20% of the state. Arkansas is comprised of five distinct ecoregions, and analyses at the ecoregion spatial scale showed that habitat associations of northern bobwhite could vary between ecoregions. For example, early successional habitat best predicted northern bobwhite occupancy in both the Arkansas River Valley and Ozark Mountains ecoregions, and other habitat associations such as the proportion of herbaceous habitat and hay-pasture habitat, respectively, further refined predictions. Contrastingly, richness of land cover classes alone best predicted northern bobwhite occupancy in the Ouachita Mountains ecoregion. Ecoregion-level models were thus more discerning than the state-level model and should be more helpful to managers in identifying priority conservation areas. However, in two of five ecoregions, surveys too rarely encountered northern bobwhite to accurately predict their occurrence. We found that likely occupied northern bobwhite habitat lay primarily on private properties (95%), but that numerous public entities own and manage land identified as suitable or likely occupied. We conclude that management of northern bobwhite in Arkansas could benefit from cooperation among state, federal, and military partners, as well as surrounding private landowners and that ecoregion-specific models may be more useful in identifying priority areas for management. Our approach incorporates multiple landscape scales when using remote sensing technology in conjunction with monitoring data and could have important application for the management of northern bobwhite and other grassland bird species.
","language":"English","publisher":"U.S. Fish and Wildlife Service","doi":"10.3996/JFWM-21-002","usgsCitation":"Lassiter, E.V., Asher, M., Christie, G., Gale, C., Massey, A., Massery, C., MIddaugh, C., Veon, J., and DeGregorio, B.A., 2021, Northern bobwhite occupancy patterns on multiple spatial scales across Arkansas: Journal of Fish and Wildlife Management, v. 12, no. 2, p. 502-512, https://doi.org/10.3996/JFWM-21-002.","productDescription":"11 p.","startPage":"502","endPage":"512","ipdsId":"IP-125981","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":450328,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/jfwm-21-002","text":"Publisher Index Page"},{"id":396907,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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R.","contributorId":288241,"corporation":false,"usgs":false,"family":"MIddaugh","given":"C. R.","affiliations":[{"id":37007,"text":"Arkansas Game and Fish Commission","active":true,"usgs":false}],"preferred":false,"id":837584,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Veon, J.","contributorId":288245,"corporation":false,"usgs":false,"family":"Veon","given":"J.","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":837585,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"DeGregorio, Brett Alexander 0000-0002-5273-049X","orcid":"https://orcid.org/0000-0002-5273-049X","contributorId":243214,"corporation":false,"usgs":true,"family":"DeGregorio","given":"Brett","email":"","middleInitial":"Alexander","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":837586,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70225688,"text":"70225688 - 2021 - Sustaining transmission in different host species: The emblematic case of Sarcoptes scabiei","interactions":[],"lastModifiedDate":"2021-11-03T13:01:38.761509","indexId":"70225688","displayToPublicDate":"2021-10-27T08:00:04","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":997,"text":"BioScience","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Sustaining transmission in different host species: The emblematic case of Sarcoptes scabiei","title":"Sustaining transmission in different host species: The emblematic case of Sarcoptes scabiei","docAbstract":"Some pathogens sustain transmission in multiple different host species, but how this epidemiologically important feat is achieved remains enigmatic. Sarcoptes scabiei is among the most host generalist and successful of mammalian parasites. We synthesize pathogen and host traits that mediate sustained transmission and present cases illustrating three transmission mechanisms (direct, indirect, and combined). The pathogen traits that explain the success of S. scabiei include immune response modulation, on-host movement capacity, off-host seeking behaviors, and environmental persistence. Sociality and host density appear to be key for hosts in which direct transmission dominates, whereas in solitary hosts, the use of shared environments is important for indirect transmission. In social den-using species, combined direct and indirect transmission appears likely. Empirical research rarely considers the mechanisms enabling S. scabiei to become endemic in host species—more often focusing on outbreaks. Our review may illuminate parasites’ adaptation strategies to sustain transmission through varied mechanisms across host species.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/biosci/biab106","usgsCitation":"Browne, E., Driessen, M., Cross, P., Escobar, L.E., Foley, J.E., , L., Niedringhaus, K., Rossi, L., and Carver, S., 2021, Sustaining transmission in different host species: The emblematic case of Sarcoptes scabiei: BioScience, biab106, 11 p., https://doi.org/10.1093/biosci/biab106.","productDescription":"biab106, 11 p.","ipdsId":"IP-128884","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":450343,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1093/biosci/biab106","text":"External Repository"},{"id":391312,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2021-10-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Browne, E","contributorId":268241,"corporation":false,"usgs":false,"family":"Browne","given":"E","email":"","affiliations":[{"id":16141,"text":"University of Tasmania","active":true,"usgs":false}],"preferred":false,"id":826258,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Driessen, MM","contributorId":268242,"corporation":false,"usgs":false,"family":"Driessen","given":"MM","email":"","affiliations":[{"id":55606,"text":"Department of Primary Industries, Parks, Water and Environment, Tasmanian Government.","active":true,"usgs":false}],"preferred":false,"id":826259,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cross, Paul C. 0000-0001-8045-5213","orcid":"https://orcid.org/0000-0001-8045-5213","contributorId":204814,"corporation":false,"usgs":true,"family":"Cross","given":"Paul C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":826260,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Escobar, L. E. 0000-0001-5735-2750","orcid":"https://orcid.org/0000-0001-5735-2750","contributorId":260844,"corporation":false,"usgs":false,"family":"Escobar","given":"L.","email":"","middleInitial":"E.","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":826261,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Foley, Janet E.","contributorId":148029,"corporation":false,"usgs":false,"family":"Foley","given":"Janet","email":"","middleInitial":"E.","affiliations":[{"id":16975,"text":"University of California Davis","active":true,"usgs":false}],"preferred":false,"id":826262,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":" Lopez-Olvera","contributorId":268245,"corporation":false,"usgs":false,"given":"Lopez-Olvera","email":"","affiliations":[{"id":55608,"text":"Universitat Autònoma de Barcelona","active":true,"usgs":false}],"preferred":false,"id":826263,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Niedringhaus, KD","contributorId":268246,"corporation":false,"usgs":false,"family":"Niedringhaus","given":"KD","email":"","affiliations":[{"id":39308,"text":"Southeastern Cooperative Wildlife Disease Study","active":true,"usgs":false}],"preferred":false,"id":826264,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rossi, Liza","contributorId":267849,"corporation":false,"usgs":false,"family":"Rossi","given":"Liza","email":"","affiliations":[{"id":39887,"text":"Colorado Parks and Wildlife","active":true,"usgs":false}],"preferred":false,"id":826265,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Carver, Scott 0000-0002-3579-7588","orcid":"https://orcid.org/0000-0002-3579-7588","contributorId":197456,"corporation":false,"usgs":false,"family":"Carver","given":"Scott","email":"","affiliations":[],"preferred":false,"id":826266,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70246522,"text":"70246522 - 2021 - Diagenetic barite-pyrite-wurtzite formation and redox signatures in Triassic mudstone, Brooks Range, northern Alaska","interactions":[],"lastModifiedDate":"2023-07-10T13:20:53.475537","indexId":"70246522","displayToPublicDate":"2021-10-27T06:37:35","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1213,"text":"Chemical Geology","active":true,"publicationSubtype":{"id":10}},"title":"Diagenetic barite-pyrite-wurtzite formation and redox signatures in Triassic mudstone, Brooks Range, northern Alaska","docAbstract":"Mineralogical and geochemical studies of interbedded black and gray mudstones in the Triassic part of the Triassic-Jurassic Otuk Formation (northern Alaska) document locally abundant barite and pyrite plus diverse redox signatures. These strata, deposited in an outer shelf setting at paleolatitudes of ~45 to 60°N, show widespread sedimentological evidence for bioturbation. Barite occurs preferentially in black mudstones (TOC = 0.93–6.46 wt%), forming displacive euhedral crystals with pyrite inclusions and rims, and late albite inclusions or intergrowths. Pyrite also occurs as small (3–20 μm) framboids, discontinuous laminae, euhedral and anhedral crystals, and replacements of barite and fossils (mainly radiolarians). Paragenetically early wurtzite is present as clusters of very small (1–3 μm) aggregates of radiating crystals 0.5 to 1.0 μm long with cores of organic matter that overgrow framboidal pyrite; later wurtzite forms 10- to 30-μm bladed crystals. Equant grains (3–30 μm) and small (20 μm) angular clusters of zinc sulfide that include <1-μm-long, comb-like structures are sphalerite or wurtzite, or both. Minor siderite forms euhedral crystals intergrown with albite that enclose wurtzite and barite. Illite shows intergrowths with sphalerite; rare K-feldspar is intergrown with barite. Formation of these minerals and assemblages is attributed to early diagenetic processes.
Whole-rock geochemical data for 15 samples show large ranges in redox proxies including Post Archean Average Shale (PAAS)-normalized enrichment factors (EFs) for V, U, Mo, and Re, and Al-normalized ratios for V, U, and Mo. Results for most black mudstones, with or without abundant barite and/or pyrite, suggest deposition within an oxygen minimum zone. Cerium anomalies, PAAS-normalized and calculated on a detrital-free basis, range widely from 0.49 to 0.96 and may reflect diagenetic overprinting by Ce-depleted fluids. Considering data for both black and gray mudstones, the overall geochemical pattern together with evidence from pyrite framboid sizes suggest that redox conditions fluctuated greatly from euxinic to oxic, like the redox profiles reported for modern shelf sediments offshore Peru and Namibia. The euxinic redox signatures in some Otuk black mudstones may correlate with widespread Early to Middle Triassic ocean anoxic events proposed for other regions.
Calculations of median EFs for trace elements in Otuk black mudstones reveal both enrichments and depletions. Normalizations to the median composition of the three least-mineralized black mudstones show that barite- and/or pyrite-rich samples display large (>50%) positive changes for Li (+80.4%), V (+75.6%), Sr (+75.9%), Ba (+790%), Cu (+92.1%), Ni (+169%), Ag (+156%), Au (+3091%), As (+109%), Sb (+476%), and Se (+205%); Zn shows a moderate positive change of +42.1%. Moderate negative changes are evident only for Ge (−47.2%) and W (−30.6%). The local enrichments may reflect one or more factors including redox variations in bottom waters and pore fluids, element mobility during diagenesis, and selective fractionation into minerals such as barite, pyrite, and wurtzite. Anomalously low U/Al and UEF values, compared to those for other modern and ancient organic-rich sediments and sedimentary rocks, are attributed to increased solubility and loss of U during bioturbation-related oxygenation in the subsurface.
Physicochemical constraints on barite, pyrite, and wurtzite formation are informed by use of a pH-fO2 plot constructed at 10 °C. Based on paragenetic evidence for multistage deposition of these three minerals, together with the presence of illite intergrown with ZnS and K-feldspar with barite, proposed diagenetic trends involve an increase in pH and fO2 related to the ingress of sulfate-rich pore fluids during bioturbation, followed by a return to lower then higher pH and fO2 conditions linked to carbon, sulfur, barium, and iron cycling during diagenesis. Labile Ba of marine pelagic origin was mobilized from organic-rich sediment upward to the sulfate-methane transition zone where barite precipitated during the interaction of reduced Ba- and CH4-rich fluids with sulfate-bearing pore fluids. The formation of paragenetically early wurtzite (ZnS) crystals, as well as locally high EF values for Cu, Ni, Ag, and Au, is attributed to metal enrichment of pore fluids, with sources being derived in part from water-column deposition from hydrothermal plumes related to coeval Triassic seafloor vent systems including a volcanogenic massive sulfide deposit in British Columbia and the Wrangellia Large Igneous Province in Alaska.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.chemgeo.2021.120568","usgsCitation":"Slack, J.F., McAleer, R.J., Shanks, W., and Dumoulin, J.A., 2021, Diagenetic barite-pyrite-wurtzite formation and redox signatures in Triassic mudstone, Brooks Range, northern Alaska: Chemical Geology, v. 585, 120568, 22 p., https://doi.org/10.1016/j.chemgeo.2021.120568.","productDescription":"120568, 22 p.","ipdsId":"IP-130237","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":450344,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.chemgeo.2021.120568","text":"Publisher Index Page"},{"id":418739,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -168.604267717169,\n 71.70733094087223\n ],\n [\n -168.604267717169,\n 67.12370451837805\n ],\n [\n -140.49132965188403,\n 67.12370451837805\n ],\n [\n -140.49132965188403,\n 71.70733094087223\n ],\n [\n -168.604267717169,\n 71.70733094087223\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"585","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Slack, John F. 0000-0001-6600-3130 jfslack@usgs.gov","orcid":"https://orcid.org/0000-0001-6600-3130","contributorId":1032,"corporation":false,"usgs":true,"family":"Slack","given":"John","email":"jfslack@usgs.gov","middleInitial":"F.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":877040,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McAleer, Ryan J. 0000-0003-3801-7441 rmcaleer@usgs.gov","orcid":"https://orcid.org/0000-0003-3801-7441","contributorId":215498,"corporation":false,"usgs":true,"family":"McAleer","given":"Ryan","email":"rmcaleer@usgs.gov","middleInitial":"J.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":877041,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shanks, Wayne (Pat)","contributorId":240838,"corporation":false,"usgs":true,"family":"Shanks","given":"Wayne (Pat)","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":877042,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dumoulin, Julie A. 0000-0003-1754-1287 dumoulin@usgs.gov","orcid":"https://orcid.org/0000-0003-1754-1287","contributorId":203209,"corporation":false,"usgs":true,"family":"Dumoulin","given":"Julie","email":"dumoulin@usgs.gov","middleInitial":"A.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":877043,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70226161,"text":"70226161 - 2021 - Pb-Pb and U-Pb dating of cassiterite by in situ LA-ICPMS: Examples spanning ~1.85 Ga to ~100 Ma in Russia and implications for dating Proterozoic to Phanerozoic tin deposits.","interactions":[],"lastModifiedDate":"2021-11-15T15:20:09.143105","indexId":"70226161","displayToPublicDate":"2021-10-22T09:17:45","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5207,"text":"Minerals","active":true,"publicationSubtype":{"id":10}},"title":"Pb-Pb and U-Pb dating of cassiterite by in situ LA-ICPMS: Examples spanning ~1.85 Ga to ~100 Ma in Russia and implications for dating Proterozoic to Phanerozoic tin deposits.","docAbstract":"This paper investigates applicability of cassiterite to dating ore deposits in a wide age range. We report in situ LA-ICPMS U-Pb and Pb-Pb dating results (n = 15) of cassiterite from six ore deposits in Russia ranging in age from ~1.85 Ga to 93 Ma. The two oldest deposits dated at ~1.83–1.86 Ga are rare metal Vishnyakovskoe located in the East Sayan pegmatite belt and tin deposits within the Tuyukan ore region in the Baikal folded region. Rare metal skarn deposits of Pitkäranta ore field in the Ladoga region, Fennoscandian Shield are dated at ~1.54 Ga. Cassiterite from the Mokhovoe porphyry tin deposit located in western Transbaikalia is 810 ± 20 Ma. The youngest cassiterite was dated from the deposits Valkumei (Russian North East, 108 ± 2 Ma) and Merek (Russian Far East, 93 ± 2 Ma). Three methods of age calculations, including 208Pb/206Pb-207Pb/206Pb inverse isochron age, Tera-Wasserburg Concordia lower intercept age, and 207Pb-corrected 206Pb*/238U age were used and the comparison of the results is discussed. In all cases, the dated cassiterite from the ore deposits agreed, within error, with the established period of magmatism of the associated granitic rock
","language":"English","publisher":"MDPI","doi":"10.3390/min11111166","usgsCitation":"Neymark, L., Larin, A.M., and Moscati, R.J., 2021, Pb-Pb and U-Pb dating of cassiterite by in situ LA-ICPMS: Examples spanning ~1.85 Ga to ~100 Ma in Russia and implications for dating Proterozoic to Phanerozoic tin deposits.: Minerals, v. 11, 1166, 30 p., https://doi.org/10.3390/min11111166.","productDescription":"1166, 30 p.","ipdsId":"IP-132675","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":450377,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/min11111166","text":"Publisher Index Page"},{"id":436137,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HK0RL5","text":"USGS data release","linkHelpText":"Pb-Pb and U-Pb data of Proterozoic to Phanerozoic cassiterite deposits in Russia"},{"id":391681,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Russia","otherGeospatial":"Chuya-Kodar complex, East Sayan belt, Merek Greisen tin ore deposit, Mokhovoe Porphyry tin deposit, Pitkaranta Mining District, Valkumei silicate-sulfide vein tin deposit","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 97.5,\n 52\n ],\n [\n 104,\n 52\n ],\n [\n 104,\n 55.37286814115173\n ],\n [\n 97.5,\n 55.37286814115173\n ],\n [\n 97.5,\n 52\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 112.5,\n 58\n ],\n [\n 115,\n 58\n ],\n [\n 115,\n 59\n ],\n [\n 112.5,\n 59\n ],\n [\n 112.5,\n 58\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 31,\n 61\n ],\n [\n 33,\n 61\n ],\n [\n 33,\n 62\n ],\n [\n 31,\n 62\n ],\n [\n 31,\n 61\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 114.5,\n 55.333\n ],\n [\n 115,\n 55.333\n ],\n [\n 115,\n 56\n ],\n [\n 114.5,\n 56\n ],\n [\n 114.5,\n 55.333\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 170,\n 68.75\n ],\n [\n 173,\n 68.75\n ],\n [\n 173,\n 70\n ],\n [\n 170,\n 70\n ],\n [\n 170,\n 68.75\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 130,\n 42\n ],\n [\n 142,\n 42\n ],\n [\n 142,\n 52\n ],\n [\n 130,\n 52\n ],\n [\n 130,\n 42\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","noUsgsAuthors":false,"publicationDate":"2021-10-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Neymark, Leonid A. 0000-0003-4190-0278 lneymark@usgs.gov","orcid":"https://orcid.org/0000-0003-4190-0278","contributorId":140338,"corporation":false,"usgs":true,"family":"Neymark","given":"Leonid A.","email":"lneymark@usgs.gov","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":826692,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Larin, Anatoly M. 0000-0001-5677-7415","orcid":"https://orcid.org/0000-0001-5677-7415","contributorId":268799,"corporation":false,"usgs":false,"family":"Larin","given":"Anatoly","email":"","middleInitial":"M.","affiliations":[{"id":55670,"text":"IPGG, RAS","active":true,"usgs":false}],"preferred":false,"id":826693,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moscati, Richard J. 0000-0002-0818-4401 rmoscati@usgs.gov","orcid":"https://orcid.org/0000-0002-0818-4401","contributorId":2462,"corporation":false,"usgs":true,"family":"Moscati","given":"Richard","email":"rmoscati@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":826694,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70225698,"text":"70225698 - 2021 - Hierarchical clustering for paired watershed experiments: Case study in southeastern Arizona, U.S.A.","interactions":[],"lastModifiedDate":"2021-11-03T12:50:00.117476","indexId":"70225698","displayToPublicDate":"2021-10-20T07:46:25","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":"Hierarchical clustering for paired watershed experiments: Case study in southeastern Arizona, U.S.A.","docAbstract":"Masting, the intermittent and synchronous production of large seed crops, can have profound consequences for plant populations and the food webs that are built on their seeds. For centuries, people have recorded mast crops because of their importance in managing wildlife populations. In the past 30 years, we have begun to recognize the importance of masting in conserving and managing many other aspects of the environment: promoting the regeneration of forests following fire or other disturbance, conserving rare plants, conscientiously developing the use of edible seeds as non-timber forest products, coping with the consequences of extinctions on seed dispersal, reducing the impacts of plant invasions with biological control, suppressing zoonotic diseases and preventing depredation of endemic fauna. We summarize current instances and future possibilities of a broad set of applications of masting. By exploring in detail several case studies, we develop new perspectives on how solutions to pressing conservation and land management problems may benefit by better understanding the dynamics of seed production. A lesson common to these examples is that masting can be used to time management, and often, to do this effectively, we need models that explicitly forecast masting and the dynamics of seed-eating animals into the near-term future.
","language":"English","publisher":"The Royal Society","doi":"10.1098/rstb.2020.0383","usgsCitation":"Pearse, I.S., Wion, A., Gonzalez, A., and Pesendorfer, M.B., 2021, Understanding mast seeding for conservation and land management: Philosophical Transactions of the Royal Society B: Biological Sciences, v. 376, no. 1839, https://doi.org/10.1098/rstb.2020.0383.","ipdsId":"IP-126922","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":450431,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8520776","text":"External Repository"},{"id":391735,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"376","issue":"1839","noUsgsAuthors":false,"publicationDate":"2021-10-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Pearse, Ian S. 0000-0001-7098-0495","orcid":"https://orcid.org/0000-0001-7098-0495","contributorId":216680,"corporation":false,"usgs":true,"family":"Pearse","given":"Ian","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":826820,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wion, Andreas","contributorId":225092,"corporation":false,"usgs":false,"family":"Wion","given":"Andreas","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":826821,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gonzalez, Angela","contributorId":268856,"corporation":false,"usgs":false,"family":"Gonzalez","given":"Angela","email":"","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":826822,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pesendorfer, Mario B.","contributorId":201187,"corporation":false,"usgs":false,"family":"Pesendorfer","given":"Mario","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":826823,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70227403,"text":"70227403 - 2021 - Similarities and differences between two deadly Caribbean coral diseases: White plague and stony coral tissue loss disease","interactions":[],"lastModifiedDate":"2022-01-13T12:47:15.078084","indexId":"70227403","displayToPublicDate":"2021-10-18T06:41:55","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3912,"text":"Frontiers in Marine Science","onlineIssn":"2296-7745","active":true,"publicationSubtype":{"id":10}},"title":"Similarities and differences between two deadly Caribbean coral diseases: White plague and stony coral tissue loss disease","docAbstract":"For several decades, white plagues (WPDs: WPD-I, II and III) and more recently, stony coral tissue loss disease (SCTLD) have significantly impacted Caribbean corals. These diseases are often difficult to separate in the field as they produce similar gross signs. Here we aimed to compare what we know about WPD and SCTLD in terms of: (1) pathology, (2) etiology, and (3) epizootiology. We reviewed over 114 peer-reviewed publications from 1973 to 2021. Overall, WPD and SCTLD resemble each other macroscopically, mainly due to the rapid tissue loss they produce in their hosts, however, SCTLD has a more concise case definition. Multiple-coalescent lesions are often observed in colonies with SCTLD and rarely in WPD. A unique diagnostic sign of SCTLD is the presence of bleached circular areas when SCTLD lesions are first appearing in the colony. The paucity of histopathologic archives for WPDs for multiple species across geographies makes it impossible to tell if WPD is the same as SCTLD. Both diseases alter the coral microbiome. WPD is controversially regarded as a bacterial infection and more recently a viral infection, whereas for SCTLD the etiology has not been identified, but the putative pathogen, likely to be a virus, has not been confirmed yet. Most striking differences between WPD and SCTLD have been related to duration and phases of epizootic events and mortality rates. While both diseases may become highly prevalent on reefs, SCTLD seems to be more persistent even throughout years. Both transmit directly (contact) and horizontally (waterborne), but organism-mediated transmission is only proven for WPD-II. Given the differences and similarities between these diseases, more detailed information is needed for a better comparison. Specifically, it is important to focus on: (1) tagging colonies to look at disease progression and tissue mortality rates, (2) tracking the fate of the epizootic event by looking at initial coral species affected, the features of lesions and how they spread over colonies and to a wider range of hosts, (3) persistence across years, and (4) repetitive sampling to look at changes in the microbiome as the disease progresses. Our review shows that WPDs and SCTLD are the major causes of coral tissue loss recorded in the Caribbean.
Most invasive species are not studied during their initial colonization of ecosystems to which they were recently introduced. Rather, research is typically performed after invasive species are well established and causing harm to the native biodiversity. Thus, novel adaptations of invasive species during their initial invasions are rarely identified. The California kingsnake (Lampropeltis californiae) is an invasive species in the Canary Islands that originated via escape or release from captive populations. Previous studies have demonstrated several morphological differences between the native California population and the invasive populations on Gran Canaria Island, particularly in regard to color pattern and body mass. In this study, we assessed the reproductive condition of 1,538 museum specimens of L. californiae from the native range, and 668 from Gran Canaria. Our results show that 57.1% of female L. californiae from Gran Canaria were gravid versus 13.4% of those from California. Moreover, average follicle size and clutch size were both greater in the invasive range (20.3 and 65%). In addition, there was a marked phenological shift in the invasive populations, among which follicles appeared 60 days sooner than in the native range. These differences can possibly be attributed to a larger body mass in the invasive populations, a lack of interspecific competition, origination from the pet trade, increased selection for large clutch sizes, and/or increased climate suitability in the invaded habitats. Overall, these reproductive and phenological attributes appear to constitute advantages for L. californiae during the invasion of this newly encountered ecosystem. The phenomenon of reproductive plasticity might generally be advantageous for rapid irruption of snakes on islands.
Owls are important avian predators in forested systems, but little is known about landscape use by most forest-adapted owl species in environments impacted by mixed-severity wildfire. To better understand species-specific patterns of post-wildfire landscape use within an owl guild, we used passive acoustic monitoring using autonomous recording units. The technology is effective for multi-species surveys, especially if some species are rare, nocturnal, or difficult to detect by traditional means. In 2017, we surveyed the interior and adjacent unburned areas of a 10,700-ha mixed-severity wildfire that burned in 2015 in southwest Oregon. We used occupancy modeling to identify patterns of landscape use by five species of forest owls: barred owls (Strix varia), great horned owls (Bubo virginianus), western screech-owls (Megascops kennicottii), northern pygmy-owls (Glaucidium gnoma), and northern saw-whet owls (Aegolius acadicus). Our results showed a positive relationship between increasing fire severity and probability of use by western screech-owls and a similar but somewhat weaker relationship for northern pygmy-owls. Barred owls were rarely detected in severely burned areas and their use decreased with increased fire severity. We observed generally low landscape use for great horned owls, which decreased with increased fire severity and at higher elevations. Thus, four out of the five species appeared to use recently burned forests at different levels, with only northern saw-whet owls showing near-complete avoidance of the burned area. These findings increase our understanding of the basic ecology of each species and highlight the varied use of burned areas within this community. These previously undocumented patterns of landscape use in burned landscapes should provide insights to managers and policymakers in the Pacific Northwest as climate shifts, and fires may increase in size, frequency, and severity.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.3770","usgsCitation":"Leila S. Duchac, Lesmeister, D., Dugger, K., and Davis, R., 2021, Differential landscape use by forest owls two years after a mixed-severity wildfire: Ecosphere, v. 12, no. 10, e03770, 20 p., https://doi.org/10.1002/ecs2.3770.","productDescription":"e03770, 20 p.","ipdsId":"IP-120447","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":489751,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.3770","text":"Publisher Index Page"},{"id":486234,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Klamath Mountains, southwestern Cascade Range","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.15473942336051,\n 42.979349859959285\n ],\n [\n -123.15473942336051,\n 42.74219443185612\n ],\n [\n -122.70304770341082,\n 42.74219443185612\n ],\n [\n -122.70304770341082,\n 42.979349859959285\n ],\n [\n -123.15473942336051,\n 42.979349859959285\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"12","issue":"10","noUsgsAuthors":false,"publicationDate":"2021-10-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Leila S. Duchac","contributorId":355573,"corporation":false,"usgs":false,"family":"Leila S. Duchac","affiliations":[{"id":56194,"text":"fs","active":true,"usgs":false}],"preferred":false,"id":937670,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lesmeister, Damon B.","contributorId":355574,"corporation":false,"usgs":false,"family":"Lesmeister","given":"Damon B.","affiliations":[{"id":56194,"text":"fs","active":true,"usgs":false}],"preferred":false,"id":937671,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dugger, Katie M. 0000-0002-4148-246X cdugger@usgs.gov","orcid":"https://orcid.org/0000-0002-4148-246X","contributorId":4399,"corporation":false,"usgs":true,"family":"Dugger","given":"Katie","email":"cdugger@usgs.gov","middleInitial":"M.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":937669,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Davis, Raymond J.","contributorId":355575,"corporation":false,"usgs":false,"family":"Davis","given":"Raymond J.","affiliations":[{"id":56194,"text":"fs","active":true,"usgs":false}],"preferred":false,"id":937672,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70224963,"text":"70224963 - 2021 - The climate envelope of Alaska’s northern treelines: Implications for controlling factors and future treeline advance","interactions":[],"lastModifiedDate":"2021-11-16T15:50:54.193537","indexId":"70224963","displayToPublicDate":"2021-10-08T10:43:13","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1445,"text":"Ecography","active":true,"publicationSubtype":{"id":10}},"title":"The climate envelope of Alaska’s northern treelines: Implications for controlling factors and future treeline advance","docAbstract":"Understanding the key mechanisms that control northern treelines is important to accurately predict biome shifts and terrestrial feedbacks to climate. At a global scale, it has long been observed that elevational and latitudinal treelines occur at similar mean growing season air temperature (GSAT) isotherms, inspiring the growth limitation hypothesis (GLH) that cold GSAT limits aboveground growth of treeline trees, with mean treeline GSAT ~6–7°C. Treelines with mean GSAT warmer than 6–7°C may indicate other limiting factors. Many treelines globally are not advancing despite warming, and other climate variables are rarely considered at broad scales. Our goals were to test whether current boreal treelines in northern Alaska correspond with the GLH isotherm, determine which environmental factors are most predictive of treeline presence, and identify areas beyond the current treeline where advance is most likely. We digitized ~12 400 km of treelines (>26 K points) and computed seasonal climate variables across northern Alaska. We then built a generalized additive model predicting treeline presence to identify key factors determining treeline. Two metrics of mean GSAT at Alaska's northern treelines were consistently warmer than the 6–7°C isotherm (means of 8.5°C and 9.3°C), indicating that direct physiological limitation from low GSAT is unlikely to explain the position of treelines in northern Alaska. Our final model included cumulative growing degree-days, near-surface (≤1 m) permafrost probability and growing season total precipitation, which together may represent the importance of soil temperature. Our results indicate that mean GSAT may not be the primary driver of treeline in northern Alaska or that its effect is mediated by other more proximate, and possibly non-climatic, controls. Our model predicts treeline potential in several areas beyond current treelines, pointing to possible routes of treeline advance if unconstrained by non-climatic factors.
","language":"English","publisher":"Wiley","doi":"10.1111/ecog.05597","usgsCitation":"Maher, C.T., Dial, R.J., Pastick, N.J., Hewitt, R.E., Jorgenson, M., and Sullivan, P., 2021, The climate envelope of Alaska’s northern treelines: Implications for controlling factors and future treeline advance: Ecography, v. 44, no. 11, p. 1710-1722, https://doi.org/10.1111/ecog.05597.","productDescription":"13 p.","startPage":"1710","endPage":"1722","ipdsId":"IP-129005","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":450505,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ecog.05597","text":"Publisher Index Page"},{"id":390390,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -163.65234374999997,\n 66\n ],\n [\n -141.15234374999997,\n 66\n ],\n [\n -141.064453125,\n 69.71810669906763\n ],\n [\n -148.88671874999997,\n 70.4367988185464\n ],\n [\n -156.4453125,\n 71.38514208411495\n ],\n [\n -163.037109375,\n 70.22974449563027\n ],\n [\n -166.904296875,\n 68.78414378041504\n ],\n [\n -165.9375,\n 67.64267630796034\n ],\n [\n -163.65234374999997,\n 66\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"44","issue":"11","noUsgsAuthors":false,"publicationDate":"2021-10-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Maher, Colin T.","contributorId":267273,"corporation":false,"usgs":false,"family":"Maher","given":"Colin","email":"","middleInitial":"T.","affiliations":[{"id":55458,"text":"University of Alaska, Anchorage","active":true,"usgs":false}],"preferred":false,"id":824887,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dial, Roman J.","contributorId":267274,"corporation":false,"usgs":false,"family":"Dial","given":"Roman","email":"","middleInitial":"J.","affiliations":[{"id":12915,"text":"Alaska Pacific University","active":true,"usgs":false}],"preferred":false,"id":824888,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pastick, Neal J. 0000-0002-4321-6739","orcid":"https://orcid.org/0000-0002-4321-6739","contributorId":267275,"corporation":false,"usgs":false,"family":"Pastick","given":"Neal","middleInitial":"J.","affiliations":[{"id":54490,"text":"KBR, Inc., under contract to USGS","active":true,"usgs":false}],"preferred":false,"id":824889,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hewitt, Rebecca E.","contributorId":267276,"corporation":false,"usgs":false,"family":"Hewitt","given":"Rebecca","email":"","middleInitial":"E.","affiliations":[{"id":12698,"text":"Northern Arizona University","active":true,"usgs":false}],"preferred":false,"id":824890,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jorgenson, M. Torre","contributorId":267277,"corporation":false,"usgs":false,"family":"Jorgenson","given":"M. Torre","affiliations":[{"id":13506,"text":"Alaska Ecoscience","active":true,"usgs":false}],"preferred":false,"id":824891,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sullivan, Patrick F.","contributorId":267278,"corporation":false,"usgs":false,"family":"Sullivan","given":"Patrick F.","affiliations":[{"id":55458,"text":"University of Alaska, Anchorage","active":true,"usgs":false}],"preferred":false,"id":824892,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70240963,"text":"70240963 - 2021 - Zirconium-bearing accessory minerals in UK Paleogene granites: Textural, compositional, and paragenetic relationships","interactions":[],"lastModifiedDate":"2023-03-02T16:41:52.991683","indexId":"70240963","displayToPublicDate":"2021-09-23T10:35:50","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1593,"text":"European Journal of Mineralogy","active":true,"publicationSubtype":{"id":10}},"title":"Zirconium-bearing accessory minerals in UK Paleogene granites: Textural, compositional, and paragenetic relationships","docAbstract":"The mineral occurrences, parageneses, textures, and compositions of Zr-bearing accessory minerals in a suite of UK Paleogene granites from Scotland and Northern Ireland are described. Baddeleyite, zirconolite, and zircon, in that sequence, formed in hornblende + biotite granites (type 1) and hedenbergite–fayalite granites (type 2). The peralkaline microgranite (type 3) of Ailsa Craig contains zircon, dalyite, a eudialyte-group mineral, a fibrous phase which is possibly lemoynite, and Zr-bearing aegirine. Hydrothermal zircon is also present in all three granite types and documents the transition from a silicate-melt environment to an incompatible element-rich aqueous-dominated fluid. No textures indicative of inherited zircon were observed. The minerals crystallized in stages from magmatic through late-magmatic to hydrothermal. The zirconolite and eudialyte-group mineral are notably Y+REE-rich (REE signifies rare earth element). The crystallization sequence of the minerals may have been related to the activities of Si and Ca, to melt peralkalinity, and to local disequilibrium.
","language":"English","publisher":"Copernicus Publications","doi":"10.5194/ejm-33-537-2021","usgsCitation":"Belkin, H.E., and MacDonald, R., 2021, Zirconium-bearing accessory minerals in UK Paleogene granites: Textural, compositional, and paragenetic relationships: European Journal of Mineralogy, v. 37, p. 537-570, https://doi.org/10.5194/ejm-33-537-2021.","productDescription":"34 p.","startPage":"537","endPage":"570","ipdsId":"IP-124385","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":450702,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/ejm-33-537-2021","text":"Publisher Index Page"},{"id":413625,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Northern Ireland, Scotland","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -4.371029936775869,\n 57.27175687671797\n ],\n [\n -7.259167863003029,\n 57.27175687671797\n ],\n [\n -7.259167863003029,\n 54.061864482791236\n ],\n [\n -4.371029936775869,\n 54.061864482791236\n ],\n [\n -4.371029936775869,\n 57.27175687671797\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"37","noUsgsAuthors":false,"publicationDate":"2021-09-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Belkin, Harvey E. 0000-0001-7879-6529 hbelkin@usgs.gov","orcid":"https://orcid.org/0000-0001-7879-6529","contributorId":581,"corporation":false,"usgs":true,"family":"Belkin","given":"Harvey","email":"hbelkin@usgs.gov","middleInitial":"E.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":865503,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"MacDonald, Ray","contributorId":9704,"corporation":false,"usgs":true,"family":"MacDonald","given":"Ray","email":"","affiliations":[],"preferred":false,"id":865504,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70230404,"text":"70230404 - 2021 - Informing future condition scenario planning for habitat specialists of the imperiled pine rockland ecosystem of South Florida","interactions":[],"lastModifiedDate":"2022-04-12T13:20:09.477273","indexId":"70230404","displayToPublicDate":"2021-09-23T08:12:11","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":7504,"text":"Final Report","active":true,"publicationSubtype":{"id":1}},"title":"Informing future condition scenario planning for habitat specialists of the imperiled pine rockland ecosystem of South Florida","docAbstract":"This project evaluated habitat conditions for two species found in the imperiled pine rockland ecosystem—the Rim Rock Crowned Snake (Tantilla oolitica) and the Key Ring-Necked Snake (Diadophis punctatus acricus). The Rim Rock Crowned Snake historically occurred in eastern Miami-Dade County (hereafter, mainland) as well as throughout the Florida Keys, whereas the Key Ring-Necked Snake occurs only in lower Florida Keys (Enge et al. 2004; Mays and Enge 2016). Both species are very elusive, small (< 20 cm in length) and primarily fossorial. Pine rockland habitat is rapidly disappearing in South Florida, with < 3 percent of its original extent remaining. Saltwater intrusion from hurricanes and sea-level rise (SLR), and human development pose the greatest threats to the longevity of this ecosystem which, in turn, places species that are endemic to this unique habitat at risk of extinction.
The Rim Rock Crowned Snake and the Key Ringed-Necked Snake are being considered for listing by the U.S. Fish and Wildlife Service (USFWS). To aid the agency’s decision, it must be able to forecast species’ responses to potential future environmental conditions, as well as to different conservation and management actions. Yet, the information needed to complete these forecasts—such as population trends, life history traits, habitat use, and future land use and climate conditions—is often lacking for most rare species. This is especially problematic for assessments of species resiliency to changes in climate and land use.
When these types of data are lacking, information on habitat quality can be used to help determine how a species will respond to change. First, this project gathered current and historical records for both species from various sources such as museum specimens, inventories, and other personal account. Then, we identified potential future changes in habitat that could result from different management actions, such as habitat acquisition or restoration, and environmental conditions, such as changes in the frequency and intensity of tropical storms and rates of SLR. Researchers then explored the potential impacts of these habitat condition changes on the Rim Rock Crowned Snake and Key Ring-Necked Snake.
This information can be used by the USFWS to help make decisions about the need to protect these species under the Endangered Species Act and could inform the conservation, management, and recovery of other at-risk species found in the pine rockland ecosystem. This work supports the Secretary of Interior’s priority to create a conservation stewardship legacy by using science to identify best practices to manage land and water resource and adapt to changes in the environment.
","language":"English","publisher":"Southeast Climate Adaptation Science Center","usgsCitation":"Walls, S.C., 2021, Informing future condition scenario planning for habitat specialists of the imperiled pine rockland ecosystem of South Florida: Final Report, 18 p.","productDescription":"18 p.","ipdsId":"IP-129367","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":398537,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":398518,"type":{"id":15,"text":"Index Page"},"url":"https://secasc.ncsu.edu/science/pine-rocklands/"}],"country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.0458984375,\n 24.287026865376436\n ],\n [\n -79.9365234375,\n 24.287026865376436\n ],\n [\n -79.9365234375,\n 26.244156283890756\n ],\n [\n -82.0458984375,\n 26.244156283890756\n ],\n [\n -82.0458984375,\n 24.287026865376436\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Walls, Susan C. 0000-0001-7391-9155 swalls@usgs.gov","orcid":"https://orcid.org/0000-0001-7391-9155","contributorId":138952,"corporation":false,"usgs":true,"family":"Walls","given":"Susan","email":"swalls@usgs.gov","middleInitial":"C.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":840331,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70221220,"text":"sir20215053 - 2021 - Analysis of Escherichia coli, total recoverable iron, and dissolved selenium concentrations, loading, and identifying data gaps for selected 303(d) listed streams, Grand Valley, western Colorado, 1980–2018","interactions":[],"lastModifiedDate":"2021-09-13T16:54:19.222516","indexId":"sir20215053","displayToPublicDate":"2021-09-13T11:30:00","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5053","displayTitle":"Analysis of Escherichia coli, Total Recoverable Iron, and Dissolved Selenium Concentrations, Loading, and Identifying Data Gaps for Selected 303(d) Listed Streams, Grand Valley, Western Colorado, 1980–2018","title":"Analysis of Escherichia coli, total recoverable iron, and dissolved selenium concentrations, loading, and identifying data gaps for selected 303(d) listed streams, Grand Valley, western Colorado, 1980–2018","docAbstract":"Tributaries to the Colorado River in the Grand Valley in western Colorado (segment COLCLC13b) have been placed on the State of Colorado 303(d) list as impaired for Escherichia coli (E. coli), total recoverable iron, and dissolved selenium. The Colorado Department of Public Health and Environment Water Quality Control Division is required to develop total maximum daily loads for these constituents in these tributaries. The U.S. Geological Survey, in cooperation with the Grand Valley Drainage District and Colorado Water Conservation Board, conducted a study to (1) characterize concentrations, loads, and load reductions for E. coli, total recoverable iron, and dissolved selenium using existing data and (2) identify water-quality data gaps to inform future monitoring strategies. This study analyzed water-quality and streamflow data for 3 main-stem sites (2 sites along the Colorado River and 1 site along the Gunnison River) and 29 selected sites on tributaries to the Colorado River.
Sample data were available at five sites along Adobe Creek and at six sites along Leach Creek, the two tributaries in the study area that are impaired for E. coli. All geometric mean E. coli concentrations at sites along Adobe Creek and Leach Creek exceeded the State recreational use standard of 126 colony forming units per 100 milliliters (CFU/100 mL). In Adobe Creek, E. coli concentrations in samples ranged from 45.7 to more than 2,420 CFU/100 mL (method upper reporting limit for undiluted samples), and geometric mean concentrations at sites ranged from 301 to 1,180 CFU/100 mL. The E. coli concentrations generally increased in the downstream direction in Adobe Creek; however, increases were not seen between all sites. The largest downstream increase in E. coli concentration was measured between the two most upstream sites. In Leach Creek, concentrations of E. coli in samples ranged from 25.9 to more than 2,420 CFU/100 mL, and geometric mean concentrations at sites ranged from 160 to 259 CFU/100 mL. The E. coli concentrations showed no consistent downgradient increase in Leach Creek. In fact, some of the highest E. coli concentrations were measured at the most upstream site, Leach Creek at Summer Hill Drive.
Total recoverable iron concentrations and loads were evaluated at 15 tributary sites for samples collected from August 1993 to February 2018. Median total recoverable iron concentrations ranged from 211 to 4,670 micrograms per liter (µg/L). The chronic aquatic-life water-quality standard (1,000 µg/L) was exceeded in most irrigation season (April through October) samples but was rarely exceeded in nonirrigation season (November through March) samples. Concentrations were often an order of magnitude higher in samples collected during irrigation season than in samples collected during nonirrigation season. None of the sites had enough concurrent total recoverable iron and streamflow data to compute annual loads. As with E. coli, the lack of concurrent total recoverable iron and streamflow information represents a data gap, which needs to be addressed to compute annual loads.
Dissolved selenium concentrations and loads were evaluated at 20 tributary sites using discrete water-quality data collected 1991–2018. Dissolved selenium concentrations were higher during nonirrigation season than during irrigation season at tributary sites. However, irrigation season dissolved selenium loads were generally higher than nonirrigation selenium loads, because streamflows were higher during irrigation season. Regression analysis was used to estimate daily dissolved selenium concentrations and loads at three main-stem sites for water years (WYs) 1980–2018 (Gunnison River near Grand Junction and Colorado River near Colorado-Utah State Line) and WYs 2002–18 (Colorado River near Cameo). A trend analysis of dissolved selenium concentrations and loads was completed for these sites from the same respective starting dates but ending in 2017. A continuing downward trend in dissolved selenium concentration was observed at all sites and across all seasonal designations of the analysis. The dissolved selenium concentration decreased by 0.12 µg/L from WY 2002 to 2017 at Colorado River near Cameo, representing an 18-percent decrease during the time period. The dissolved selenium concentration at Gunnison River near Grand Junction decreased by 4.2 µg/L from WY 1980 to 2017, representing a 56-percent decrease overall. During the same time period, dissolved selenium concentration at Colorado River near Colorado-Utah State Line decreased by 3.8 µg/L, representing a 56-percent decrease overall. A downward trend in dissolved selenium load was also observed at all sites and across all seasonal designations of the analysis. The relative contribution of dissolved selenium from the Grand Valley near Grand Junction was estimated by comparing loads at main-stem sites bracketing the study area. The two upstream sites, Colorado River near Cameo and Gunnison River near Grand Junction, contributed 60,300 cumulative pounds and 251,000 cumulative pounds, respectively, during WYs 2002–18. At the furthest downstream site, Colorado River near Colorado-Utah State Line, 490,000 cumulative pounds were estimated during the same time period, indicating that the region between Whitewater and State line contributed approximately 179,000 cumulative pounds or a mean annual load of 10,500 lb/yr. Grand Valley dissolved selenium contributions appear to be stable during WYs 2002–18.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215053","collaboration":"Prepared in cooperation with the Grand Valley Drainage District and the Colorado Water Conservation Board","usgsCitation":"Miller, L.D., Gidley, R.G., Day, N.K., and Thomas, J.C., 2021, Analysis of Escherichia coli, total recoverable iron, and dissolved selenium concentrations, loading, and identifying data gaps for selected 303(d) listed streams, Grand Valley, western Colorado, 1980–2018 (ver. 1.1, September 2021): U.S. Geological Survey Scientific Investigations Report 2021-5053, 37 p., https://doi.org/10.3133/sir20215053.","productDescription":"Report: vii, 37 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-106948","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":386290,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5053/sir20215053.pdf","text":"Report","size":"2.19 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5053"},{"id":386289,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5053/coverthb3.jpg"},{"id":388012,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2021/5053/versionHist.txt","size":"8.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"Version history"},{"id":386291,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9P6WI44","text":"USGS data release","linkHelpText":"Analysis of Escherichia coli, total recoverable iron, and dissolved selenium concentrations and loads for selected 303(d) listed segments in the Grand Valley, western Colorado, 1980–2018 (ver. 3.0, August 2021)"}],"country":"United States","state":"Colorado","otherGeospatial":"Grand Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.083251953125,\n 38.736946065676\n ],\n [\n -107.99560546875,\n 38.736946065676\n ],\n [\n -107.99560546875,\n 39.470125122358176\n ],\n [\n -109.083251953125,\n 39.470125122358176\n ],\n [\n -109.083251953125,\n 38.736946065676\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: June 9, 2021; Version 1.1: September 13, 2021","contact":"Director, Colorado Water Science Center
U.S. Geological Survey
Box 25046, MS-415
Denver, CO 80225-0046
Siliceous sinter is formed by biogenic and abiogenic opal deposition around hot springs and geysers. Using Structure-from-Motion photogrammetry we generated three-dimensional models of Giant and Castle Geysers from the Upper Geyser Basin of Yellowstone National Park. We use these models to calculate an approximate mass of sinter for each (~2 and ~ 5 kton, respectively) and estimate a range of plausible long-term deposition rates for Castle Geyser (470 to 940 kg·yr−1). We estimate ~2% of the silica discharged from Castle Geyser is deposited as sinter in the cone and proximal terraces. We collected 15 sinter samples following the stratigraphy of each geyser from an older terrace to a younger cone and examined them using a variety of analytical methods. We find that young opaline sinter with a water content of <12 wt% (from loss on ignition) contains higher concentrations of major and trace elements, notably As, Sb, Rb, Ga and Cs, relative to older dehydrated sinter. Rare earth element (REE) concentrations in sinter are 2–3 orders of magnitude higher than in the thermal water from which they are deposited. Sinter deposits are enriched in light REE, Gd and Yb when normalized to concentrations in thermal water and enriched in Eu, Tm, and Yb when normalized to the underlying rhyolite. Sinter samples with the highest REE concentrations are also enriched in organic material, implying either microbial uptake of REE, or that organic molecules are efficient ligands that form metal complexes.
Critical mineral resources titanium, zirconium, and rare earth elements occur in placer deposits over vast parts of the U.S. Atlantic Coastal Plain. Key questions regarding provenance, pathways of minerals to deposit sites, and relations to geologic features remain unexplained. As part of a national effort to collect data over regions prospective for critical minerals, the first public high-resolution aeroradiometric survey over the U.S. Atlantic Coastal Plain was conducted over Quaternary sediments in South Carolina. The new data provide an unprecedented view of potential deposits by imaging Th-bearing minerals in the heavy mineral assemblage. Sand ridges show the highest radiometric Th values with localized, linear anomalies, especially along the shoreface and in areas reworked by multiple processes and/or during multiple episodes. Estuarine areas with finer-grained sediments show lower, distributed Th anomalies. Th values averaged over geologic unit areas are similar for both environments, suggesting that heavy minerals are present but have not been locally concentrated in the lower-energy estuarine environments. Radiometric K highlights immature minerals such as mica and potassium feldspar. K is elevated within shallow sediments younger than ca. 130 ka, an attribute that persists in regional data from northern South Carolina to northern Florida. Both K and Th are elevated over the floodplains of the Santee River and other rivers with headwaters in the igneous and metamorphic Piedmont Terrane. The persistence of K anomalies for distances of more than 100 km from the Santee River floodplain suggests that heavy minerals are delivered from the Piedmont to offshore areas by major rivers, transported along the coast by the longshore current, and redeposited onshore by marine processes.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/GSATG512A.1","usgsCitation":"Shah, A.K., Morrow, R., Pace, M., Harris, M., and Doar, W., 2021, Mapping critical minerals from the sky: GSA Today, v. 31, 7 p., https://doi.org/10.1130/GSATG512A.1.","productDescription":"7 p.","ipdsId":"IP-122675","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":450884,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/gsatg512a.1","text":"Publisher Index Page"},{"id":389590,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida, Georgia, South Carolina","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.189453125,\n 34.288991865037524\n ],\n [\n -80.4638671875,\n 33.90689555128866\n ],\n [\n -81.58447265624999,\n 32.861132322810946\n ],\n [\n -82.11181640625,\n 31.93351676190369\n ],\n [\n -82.28759765625,\n 30.95876857077987\n ],\n [\n -82.02392578125,\n 30.050076521698735\n ],\n [\n -81.6943359375,\n 29.286398892934763\n ],\n [\n -80.9912109375,\n 29.209713225868185\n ],\n [\n -80.7275390625,\n 29.592565403314087\n ],\n [\n -80.96923828125,\n 30.732392734006083\n ],\n [\n -80.35400390625,\n 31.914867503276223\n ],\n [\n -79.21142578125,\n 32.37996146435729\n ],\n [\n -78.24462890625,\n 33.119150226768866\n ],\n [\n -78.15673828125,\n 33.63291573870479\n ],\n [\n -79.013671875,\n 34.30714385628804\n ],\n [\n -79.189453125,\n 34.288991865037524\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"31","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Shah, Anjana K. 0000-0002-3198-081X ashah@usgs.gov","orcid":"https://orcid.org/0000-0002-3198-081X","contributorId":2297,"corporation":false,"usgs":true,"family":"Shah","given":"Anjana","email":"ashah@usgs.gov","middleInitial":"K.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":823741,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morrow, Robert 0000-0001-5282-2389","orcid":"https://orcid.org/0000-0001-5282-2389","contributorId":265921,"corporation":false,"usgs":false,"family":"Morrow","given":"Robert","email":"","affiliations":[{"id":54824,"text":"SC Geological Survey","active":true,"usgs":false}],"preferred":false,"id":823742,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pace, Michael 0000-0003-2770-5724","orcid":"https://orcid.org/0000-0003-2770-5724","contributorId":216678,"corporation":false,"usgs":true,"family":"Pace","given":"Michael","email":"","affiliations":[],"preferred":true,"id":823743,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harris, M.Scott 0000-0002-9220-788X","orcid":"https://orcid.org/0000-0002-9220-788X","contributorId":265922,"corporation":false,"usgs":false,"family":"Harris","given":"M.Scott","email":"","affiliations":[{"id":35839,"text":"College of Charleston","active":true,"usgs":false}],"preferred":false,"id":823744,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Doar, William 0000-0002-9895-8422","orcid":"https://orcid.org/0000-0002-9895-8422","contributorId":265923,"corporation":false,"usgs":false,"family":"Doar","given":"William","email":"","affiliations":[{"id":54824,"text":"SC Geological Survey","active":true,"usgs":false}],"preferred":false,"id":823745,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70223848,"text":"70223848 - 2021 - The application of metacommunity theory to the management of riverine ecosystems","interactions":[],"lastModifiedDate":"2021-10-18T15:04:59.504944","indexId":"70223848","displayToPublicDate":"2021-09-08T07:01:53","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5067,"text":"WIREs Water","active":true,"publicationSubtype":{"id":10}},"title":"The application of metacommunity theory to the management of riverine ecosystems","docAbstract":"River managers strive to use the best available science to sustain biodiversity and ecosystem function. To achieve this goal requires consideration of processes at different scales. Metacommunity theory describes how multiple species from different communities potentially interact with local-scale environmental drivers to influence population dynamics and community structure. However, this body of knowledge has only rarely been used to inform management practices for river ecosystems. In this article, we present a conceptual model outlining how the metacommunity processes of local niche sorting and dispersal can influence the outcomes of management interventions and provide a series of specific recommendations for applying these ideas as well as research needs. In all cases, we identify situations where traditional approaches to riverine management could be enhanced by incorporating an understanding of metacommunity dynamics. A common theme is developing guidelines for assessing the metacommunity context of a site or region, evaluating how that context may affect the desired outcome, and incorporating that understanding into the planning process and methods used. To maximize the effectiveness of management activities, scientists, and resource managers should update the toolbox of approaches to riverine management to reflect theoretical advances in metacommunity ecology.
","language":"English","publisher":"Wiley","doi":"10.1002/wat2.1557","usgsCitation":"Patrick, C.J., Anderson, K.E., Brown, B.L., Hawkins, C.P., Metcalfe, A.N., Saffarinia, P., Siqueira, T., Swan, C.M., Tonkin, J.D., and Yuan, L.L., 2021, The application of metacommunity theory to the management of riverine ecosystems: WIREs Water, v. 8, no. 6, e1557, 21 p., https://doi.org/10.1002/wat2.1557.","productDescription":"e1557, 21 p.","ipdsId":"IP-119036","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":450888,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/wat2.1557","text":"Publisher Index Page"},{"id":389050,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-09-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Patrick, Christopher J.","contributorId":199778,"corporation":false,"usgs":false,"family":"Patrick","given":"Christopher","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":822932,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Kurt E.","contributorId":265545,"corporation":false,"usgs":false,"family":"Anderson","given":"Kurt","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":822933,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brown, Brown L.","contributorId":265546,"corporation":false,"usgs":false,"family":"Brown","given":"Brown","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":822934,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hawkins, Charles P.","contributorId":198331,"corporation":false,"usgs":false,"family":"Hawkins","given":"Charles","email":"","middleInitial":"P.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":822935,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Metcalfe, Anya N. 0000-0002-6286-4889 ametcalfe@usgs.gov","orcid":"https://orcid.org/0000-0002-6286-4889","contributorId":5271,"corporation":false,"usgs":true,"family":"Metcalfe","given":"Anya","email":"ametcalfe@usgs.gov","middleInitial":"N.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":822936,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Saffarinia, Parsa","contributorId":265547,"corporation":false,"usgs":false,"family":"Saffarinia","given":"Parsa","email":"","affiliations":[],"preferred":false,"id":822937,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Siqueira, Tadeu","contributorId":265548,"corporation":false,"usgs":false,"family":"Siqueira","given":"Tadeu","email":"","affiliations":[],"preferred":false,"id":822938,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Swan, Christopher M.","contributorId":265549,"corporation":false,"usgs":false,"family":"Swan","given":"Christopher","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":822939,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Tonkin, Jonathan D.","contributorId":260624,"corporation":false,"usgs":false,"family":"Tonkin","given":"Jonathan","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":822940,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Yuan, Lester L.","contributorId":198316,"corporation":false,"usgs":false,"family":"Yuan","given":"Lester","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":822941,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70223890,"text":"70223890 - 2021 - Demographic modeling informs functional connectivity and management interventions in Graham’s beardtongue","interactions":[],"lastModifiedDate":"2021-10-18T15:06:55.286746","indexId":"70223890","displayToPublicDate":"2021-09-04T08:08:54","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1324,"text":"Conservation Genetics","active":true,"publicationSubtype":{"id":10}},"title":"Demographic modeling informs functional connectivity and management interventions in Graham’s beardtongue","docAbstract":"Functional connectivity (i.e., the movement of individuals across a landscape) is essential for the maintenance of genetic variation and persistence of rare species. However, illuminating the processes influencing functional connectivity and ultimately translating this knowledge into management practice remains a fundamental challenge. Here, we combine various population structure analyses with pairwise, population-specific demographic modeling to investigate historical functional connectivity in Graham’s beardtongue (Penstemon grahamii), a rare plant narrowly distributed across a dryland region of the western US. While principal component and population structure analyses indicated an isolation-by-distance pattern of differentiation across the species’ range, spatial inferences of effective migration exposed an abrupt shift in population ancestry near the range center. To understand these seemingly conflicting patterns, we tested various models of historical gene flow and found evidence for recent admixture (~ 3400 generations ago) between populations near the range center. This historical perspective reconciles population structure patterns and suggests management efforts should focus on maintaining connectivity between these previously isolated lineages to promote the ongoing transfer of genetic variation. Beyond providing species-specific knowledge to inform management options, our study highlights how understanding demographic history may be critical to guide conservation efforts when interpreting population genetic patterns and inferring functional connectivity.
ABSTRACT: The deep ocean hosts a large diversity of azooxanthellate cold-water corals whose associated microbiomes remain to be described. While the bacterial genus Endozoicomonas has been widely identified as a dominant associate of tropical and temperate corals, it has rarely been detected in deep-sea corals. Determining microbial baselines for these cold-water corals is a critical first step to understanding the ecosystem services their microbiomes contribute, while providing a benchmark against which to measure responses to environmental change or anthropogenic effects. Samples of Acanthogorgia aspera, A. spissa, Desmophyllum dianthus, and D. pertusum (Lophelia pertusa) were collected from western Atlantic sites off the US east coast and from the northeastern Gulf of Mexico. Microbiomes were characterized by 16S rRNA gene amplicon surveys. Although D. dianthus and D. pertusum have recently been combined into a single genus due to their genetic similarity, their microbiomes were significantly different. The Acanthogorgia spp. were collected from submarine canyons in different regions, but their microbiomes were extremely similar and dominated by Endozoicomonas. This is the first report of coral microbiomes dominated by Endozoicomonas occurring below 1000 m, at temperatures near 4°C. D. pertusum from 2 Atlantic sites were also dominated by distinct Endozoicomonas, unlike D. pertusum from other sites described in previous studies, including the Gulf of Mexico, the Mediterranean Sea and a Norwegian fjord.
","language":"English","publisher":"Inter-Research","doi":"10.3354/meps13844","usgsCitation":"Kellogg, C.A., and Pratte, Z.A., 2021, Unexpected diversity of Endozoicomonas in deep-sea corals: Marine Ecology Progress Series, v. 673, p. 1-15, https://doi.org/10.3354/meps13844.","productDescription":"15 p.","startPage":"1","endPage":"15","ipdsId":"IP-126734","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":450959,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/meps13844","text":"Publisher Index Page"},{"id":436213,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Z1HPKR","text":"USGS data release","linkHelpText":"Cold-water Coral Microbiomes (Acanthogorgia spp. Desmophyllum dianthus, and Lophelia pertusa) from the Gulf of Mexico and Atlantic Ocean off the Southeast Coast of the United States-Raw Data"},{"id":388829,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.8828125,\n 37.405073750176925\n ],\n [\n -74.6630859375,\n 35.42486791930558\n ],\n [\n -75.673828125,\n 34.161818161230386\n ],\n [\n -78.046875,\n 33.247875947924385\n ],\n [\n -79.453125,\n 32.32427558887655\n ],\n [\n -79.4970703125,\n 31.541089879585808\n ],\n [\n -77.87109375,\n 31.316101383495624\n ],\n [\n -74.4873046875,\n 32.509761735919426\n ],\n [\n -71.71875,\n 34.77771580360469\n ],\n [\n -71.455078125,\n 36.4566360115962\n ],\n [\n -71.89453125,\n 37.405073750176925\n ],\n [\n -72.5537109375,\n 37.50972584293751\n ],\n [\n -73.47656249999999,\n 37.82280243352756\n ],\n [\n -74.1796875,\n 37.96152331396614\n ],\n [\n -74.8828125,\n 37.405073750176925\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"673","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kellogg, Christina A. 0000-0002-6492-9455 ckellogg@usgs.gov","orcid":"https://orcid.org/0000-0002-6492-9455","contributorId":391,"corporation":false,"usgs":true,"family":"Kellogg","given":"Christina","email":"ckellogg@usgs.gov","middleInitial":"A.","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":822526,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pratte, Zoe A.","contributorId":214260,"corporation":false,"usgs":false,"family":"Pratte","given":"Zoe","email":"","middleInitial":"A.","affiliations":[{"id":27526,"text":"Georgia Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":822527,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70239176,"text":"70239176 - 2021 - What do you mean by false positive?","interactions":[],"lastModifiedDate":"2023-01-02T19:01:30.374493","indexId":"70239176","displayToPublicDate":"2021-09-01T12:59:20","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5840,"text":"Environmental DNA","active":true,"publicationSubtype":{"id":10}},"title":"What do you mean by false positive?","docAbstract":"Misunderstandings regarding the term “false positive” present a significant hurdle to broad adoption of eDNA monitoring methods. Here, we identify three challenges to clear communication of false-positive error between scientists, managers, and the public. The first arises from a failure to distinguish between false-positive eDNA detection at the sample level and false-positive inference of taxa presence at the site level. The second is based on the large proportion of false positives that may occur when true-positive detections are likely to be rare, even when rates of contamination or other error are low. And the third misunderstanding occurs when conventional species detection approaches, often based on direct capture, are used to confirm eDNA approaches without acknowledging or quantifying the conventional approach's detection probability. The solutions to these issues include careful and consistent communication of error definitions, managing expectations of error rates, and providing a balanced discussion not only of alternative sources of species DNA, but also of the detection limitations of conventional methods. We argue that the benefit of addressing these misunderstandings will be increased confidence in the utility of eDNA methods and, ultimately, improved resource management using eDNA approaches.
","language":"English","publisher":"Wiley","doi":"10.1002/edn3.194","usgsCitation":"Darling, J., Jerde, C.L., and Sepulveda, A., 2021, What do you mean by false positive?: Environmental DNA, v. 3, no. 5, p. 879-883, https://doi.org/10.1002/edn3.194.","productDescription":"5 p.","startPage":"879","endPage":"883","ipdsId":"IP-124696","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":450967,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/edn3.194","text":"Publisher Index Page"},{"id":411273,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","issue":"5","noUsgsAuthors":false,"publicationDate":"2021-05-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Darling, John A. 0000-0002-4776-9533","orcid":"https://orcid.org/0000-0002-4776-9533","contributorId":260860,"corporation":false,"usgs":false,"family":"Darling","given":"John A.","affiliations":[{"id":37230,"text":"EPA","active":true,"usgs":false}],"preferred":false,"id":860685,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jerde, Christopher L. 0000-0002-8074-3466","orcid":"https://orcid.org/0000-0002-8074-3466","contributorId":210301,"corporation":false,"usgs":false,"family":"Jerde","given":"Christopher","email":"","middleInitial":"L.","affiliations":[{"id":16936,"text":"University of California Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":860686,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sepulveda, Adam 0000-0001-7621-7028 asepulveda@usgs.gov","orcid":"https://orcid.org/0000-0001-7621-7028","contributorId":4187,"corporation":false,"usgs":true,"family":"Sepulveda","given":"Adam","email":"asepulveda@usgs.gov","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":860687,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}