Volcanic eruptions are rare, but when they occur, they can profoundly affect nearby communities. In order to determine which communities are at risk, and in order for those communities to mitigate their risk, communities need to know whether they are in or near volcano hazard zones and have basic information about the hazards within those zones. In addition, individuals need to know whether they live in, work or go to school in, or cross volcano hazard zones as part of their routine so they can plan for what to do in the event of an eruption.
The purpose of this product is to serve as a starting point for dialogue with Indian Tribes of the Pacific Northwest who may be at risk from future volcanic eruptions. The map shows Tribal land boundaries and land-based volcano hazard zones, allowing Tribes to determine quickly if they are at risk from these hazards. A rose diagram in the map explanation shows typical Pacific Northwest wind directions and, hence, the most likely directions airborne material (tephra) from explosive eruptions will travel (primarily to the northeast, east, and southeast). We also provide basic information about the hazards and simple protective actions to take during unrest and eruptions, guidance for finding information about current volcanic activity and preparedness, and additional resources.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/gip209","collaboration":"Prepared in collaboration with the U.S. Geological Survey Office of Tribal Relations","usgsCitation":"Gardner, C.A., and Bard, J.A., 2021, How would a volcanic eruption affect your Tribe?: U.S. Geological Survey General Information Product 209, https://doi.org/10.3133/gip209.","productDescription":"1 Sheet: 66.00 x 36.00 inches","ipdsId":"IP-120998","costCenters":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":385548,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/gip/0209/covrthb.jpg"},{"id":385549,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/gip/0209/gip209.pdf","size":"17 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Oregon, Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -125.41992187499999,\n 41.902277040963696\n ],\n [\n -118.38867187500001,\n 41.902277040963696\n ],\n [\n -118.38867187500001,\n 48.980216985374994\n ],\n [\n -125.41992187499999,\n 48.980216985374994\n ],\n [\n -125.41992187499999,\n 41.902277040963696\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Volcano Hazards Program
Cascades Volcano Observatory
U.S. Geological Survey
1300 SE Cardinal Court
Vancouver, Washington, 98683-9589
Anthropogenic activities can lead to the loss, fragmentation, and alteration of wildlife habitats. I reviewed the recent literature (2014–2019) focused on the responses of avian, mammalian, and herpetofaunal species to oil and natural gas development, a widespread and still-expanding land use worldwide. My primary goals were to identify any generalities in species’ responses to development and summarize remaining gaps in knowledge. To do so, I evaluated the directionality of a wide variety of responses in relation to taxon, location, development type, development metric, habitat type, and spatiotemporal aspects.
Studies (n = 70) were restricted to the USA and Canada, and taxonomically biased towards birds and mammals. Longer studies, but not those incorporating multiple spatial scales, were more likely to detect significant responses. Negative responses of all types were present in relatively low frequencies across all taxa, locations, development types, and development metrics but were context-dependent. The directionality of responses by the same species often varied across studies or development metrics.
The state of knowledge about wildlife responses to oil and natural gas development has developed considerably, though many biases and gaps remain. Studies outside of North America and that focus on herpetofauna are lacking. Tests of mechanistic hypotheses for effects, long-term studies, assessment of response thresholds, and experimental designs that isolate the effects of different stimuli associated with development, remain critical. Moreover, tests of the efficacy of habitat mitigation efforts have been rare. Finally, investigations of the demographic effects of development across the full annual cycle were absent for non-game species and are critical for the estimation of population-level effects.
Due to high mortality in the first year or two of life, Lost River (Deltistes luxatus sp.) and Shortnose suckers (Chasmistes brevirostris sp.) in Upper Klamath Lake, Oregon rarely reach maturity. In 2015, the U.S. Fish and Wildlife Service began the Sucker Assisted Rearing Program (SARP) to improve early life survival before releasing the fish back into Upper Klamath Lake. Survival and growth rates were compared for fish in mesocosms among three potential release or in-lake rearing sites, and in a pond at the SARP rearing facility. Fish used in this study included a mix of Lost River, Shortnose, and Klamath largescale suckers reared at either U.S. Fish and Wildlife Service or Klamath Tribes fish rearing facilities. These sites were Shoalwater Bay (SWB), Rattlesnake Point (RPT), and Cove Point (CPT). Ninety-nine to 103 suckers tagged with passive integrated transponders (PIT) were placed into each mesocosm for up to 80 days and up to 103 days in the SARP pond. Cessation of movement, as determined by passive detection of tagged fish on remote antennas, indicated mortality. Dissolved-oxygen saturation, temperature, and pH were tracked hourly in each mesocosm. All the suckers placed into the SWB mesocosm died during an extreme hypoxia event. These fish were replaced with another 120 PIT-tagged and 2 untagged hatchery-reared Lost River suckers from the Klamath Tribes Fish Research Facility (KTFRF), of which, all but two died during a second extreme hypoxia event. It was determined that SWB was an unsuitable site for summertime release or rearing of juvenile suckers in 2018. The summer survival rate was ≥86 percent at CPT, RPT, and the SARP pond. Suckers in the SARP pond grew slightly slower and gained less weight relative to increases in length than suckers held at RPT and CPT. All suckers sampled at the start of the study from both the SARP facility and the KTFRF, when water temperatures averaged approximately 18–22 degrees Celsius (°C), were infected with low levels of the gill parasite Ichthyobodo sp. Ichthyobodo sp. was detected on only 1 of 16 suckers sampled from CPT, RPT, and the SARP pond in late September or early October when water temperatures were approximately 16–19 °C, indicating fish were able to shed the parasite in cooler temperatures. Water quality conditions at RPT and CPT were adequate for in-lake rearing of SARP suckers in 2018. Due to interannual differences in water quality conditions, these sites may not be suitable in all years. Future research focused on the suitability of RPT, CPT and other potential sites under in years with varying conditions would be beneficial for improving sucker in-lake rearing practices. Additional research could help to elucidate how size at entry into the mesocosms affects sucker survival.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211036","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Burdick, S.M., Conway, C.M., Ostberg, C.O., Bart, R.J., and Elliott, D.G., 2021, Survival and growth of suckers in mesocosms at three locations within Upper Klamath Lake, Oregon, 2018: U.S. Geological Survey Open-File Report 2021–1036, 18 p., https://doi.org/10.3133/ofr20211036.","productDescription":"v, 18 p.","onlineOnly":"Y","ipdsId":"IP-119761","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":385517,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1036/coverthb.jpg"},{"id":385518,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1036/ofr20211036.pdf","text":"Report","size":"2.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1036"}],"country":"United States","state":"Oregon","otherGeospatial":"Upper Klamath Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.79031372070312,\n 42.24478535602799\n ],\n [\n -121.79855346679686,\n 42.39810802339276\n ],\n [\n -121.95098876953125,\n 42.6147595985433\n ],\n [\n -122.12265014648438,\n 42.48627657532139\n ],\n [\n -121.96884155273436,\n 42.34129022434778\n ],\n [\n -121.9207763671875,\n 42.261049162113856\n ],\n [\n -121.81365966796874,\n 42.22139878761366\n ],\n [\n -121.79031372070312,\n 42.24478535602799\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016
Purpose of Review
Anthropogenic activities can lead to the loss, fragmentation, and alteration of wildlife habitats. I reviewed the recent literature (2014–2019) focused on the responses of avian, mammalian, and herpetofaunal species to oil and natural gas development, a widespread and still-expanding land use worldwide. My primary goals were to identify any generalities in species’ responses to development and summarize remaining gaps in knowledge. To do so, I evaluated the directionality of a wide variety of responses in relation to taxon, location, development type, development metric, habitat type, and spatiotemporal aspects.
Studies (n = 70) were restricted to the USA and Canada, and taxonomically biased towards birds and mammals. Longer studies, but not those incorporating multiple spatial scales, were more likely to detect significant responses. Negative responses of all types were present in relatively low frequencies across all taxa, locations, development types, and development metrics but were context-dependent. The directionality of responses by the same species often varied across studies or development metrics.
The state of knowledge about wildlife responses to oil and natural gas development has developed considerably, though many biases and gaps remain. Studies outside of North America and that focus on herpetofauna are lacking. Tests of mechanistic hypotheses for effects, long-term studies, assessment of response thresholds, and experimental designs that isolate the effects of different stimuli associated with development, remain critical. Moreover, tests of the efficacy of habitat mitigation efforts have been rare. Finally, investigations of the demographic effects of development across the full annual cycle were absent for non-game species and are critical for the estimation of population-level effects.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s40823-021-00065-0","usgsCitation":"Chalfoun, A.D., 2021, Responses of vertebrate wildlife to oil and natural gas development: Patterns and frontiers: Current Landscape Ecology Reports, v. 6, p. 71-84, https://doi.org/10.1007/s40823-021-00065-0.","productDescription":"14 p.","startPage":"71","endPage":"84","ipdsId":"IP-125857","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":488950,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s40823-021-00065-0","text":"Publisher Index Page"},{"id":486237,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana, North Dakota, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -115.99133325913138,\n 48.99530882529015\n ],\n [\n -115.94775136101576,\n 47.635070317007006\n ],\n [\n -114.71798520155821,\n 46.75535562272523\n ],\n [\n -114.49414972872306,\n 45.45998234056832\n ],\n [\n -113.96758226906417,\n 45.524482366283685\n ],\n [\n -113.60221411335195,\n 44.681702439031596\n ],\n [\n -111.32527287492972,\n 44.560953493263426\n ],\n [\n -110.95041014777493,\n 41.06914399002384\n ],\n [\n -103.87530651855269,\n 41.10554283282917\n ],\n [\n -103.94967923279542,\n 45.96760028626089\n ],\n [\n -96.46530149091419,\n 46.097634685465835\n ],\n [\n -97.09333137335523,\n 49.05935053469682\n ],\n [\n -115.99133325913138,\n 48.99530882529015\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"6","noUsgsAuthors":false,"publicationDate":"2021-05-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Chalfoun, Anna D. 0000-0002-0219-6006 achalfoun@usgs.gov","orcid":"https://orcid.org/0000-0002-0219-6006","contributorId":197589,"corporation":false,"usgs":true,"family":"Chalfoun","given":"Anna","email":"achalfoun@usgs.gov","middleInitial":"D.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":937676,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70220419,"text":"70220419 - 2021 - Differential susceptibility of Yukon River and Salish Sea stocks of Chinook salmon Oncorhynchus tshawytscha to ichthyophoniasis","interactions":[],"lastModifiedDate":"2021-05-13T12:23:33.882101","indexId":"70220419","displayToPublicDate":"2021-05-06T07:21:38","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1396,"text":"Diseases of Aquatic Organisms","active":true,"publicationSubtype":{"id":10}},"title":"Differential susceptibility of Yukon River and Salish Sea stocks of Chinook salmon Oncorhynchus tshawytscha to ichthyophoniasis","docAbstract":"Preliminary evidence suggests that Chinook salmon Oncorhynchus tshawytscha from the Yukon River may be more susceptible to Ichthyophonus sp. infections than Chinook from stocks further south. To investigate this hypothesis in a controlled environment, we experimentally challenged juvenile Chinook from the Yukon River and from the Salish Sea with Ichthyophonus sp. and evaluated mortality, infection prevalence and infection load over time. We found that juvenile Chinook salmon from a Yukon River stock were more susceptible to ichthyophoniasis than were those from a Salish Sea stock. After feeding with tissues from infected Pacific herring Clupea pallasii, Chinook salmon from both stocks became infected. The infection was persistent and progressive in Yukon River stock fish, where infections sometimes progressed to mortality, and histological examinations revealed parasite dissemination and proliferation throughout the host tissues. In Salish Sea-origin fish, however, infections were largely transient; host mortalities were rare, and parasite stages were largely cleared from most tissues after 3-4 wk. Susceptibility differences were evidenced by greater cumulative mortality, infection prevalence, parasite density, proportion of fish demonstrating a cellular response, and intensity of the cellular response among fish from the Yukon River stock. These observed differences between Chinook salmon stocks were consistent when parasite exposures occurred in both freshwater and seawater. These results support the hypothesis that a longer-standing host-pathogen relationship, resulting in decreased disease susceptibility, exists among Salish Sea Chinook salmon than among Yukon River conspecifics.
","language":"English","publisher":"Inter-Research","doi":"10.3354/dao03577","usgsCitation":"Elliott, D.G., Conway, C.M., McKibben, C., MacKenzie, A., Hart, L., Groner, M., Purcell, M.K., Gregg, J.L., and Hershberger, P., 2021, Differential susceptibility of Yukon River and Salish Sea stocks of Chinook salmon Oncorhynchus tshawytscha to ichthyophoniasis: Diseases of Aquatic Organisms, v. 144, p. 123-131, https://doi.org/10.3354/dao03577.","productDescription":"9 p.","startPage":"123","endPage":"131","ipdsId":"IP-122128","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":385601,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"144","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Elliott, Diane G. 0000-0002-4809-6692 dgelliott@usgs.gov","orcid":"https://orcid.org/0000-0002-4809-6692","contributorId":2947,"corporation":false,"usgs":true,"family":"Elliott","given":"Diane","email":"dgelliott@usgs.gov","middleInitial":"G.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":815486,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conway, Carla M. 0000-0002-3851-3616 cmconway@usgs.gov","orcid":"https://orcid.org/0000-0002-3851-3616","contributorId":2946,"corporation":false,"usgs":true,"family":"Conway","given":"Carla","email":"cmconway@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":815487,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McKibben, Constance L.","contributorId":257993,"corporation":false,"usgs":false,"family":"McKibben","given":"Constance L.","affiliations":[{"id":52199,"text":"Previously USGS - Western Fisheries Research Center","active":true,"usgs":false}],"preferred":false,"id":815488,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"MacKenzie, Ashley 0000-0002-7402-7877 amackenzie@usgs.gov","orcid":"https://orcid.org/0000-0002-7402-7877","contributorId":150817,"corporation":false,"usgs":true,"family":"MacKenzie","given":"Ashley","email":"amackenzie@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":815489,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hart, Lucas M. 0000-0001-7035-8778","orcid":"https://orcid.org/0000-0001-7035-8778","contributorId":257994,"corporation":false,"usgs":false,"family":"Hart","given":"Lucas M.","affiliations":[{"id":52199,"text":"Previously USGS - Western Fisheries Research Center","active":true,"usgs":false}],"preferred":false,"id":815490,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Groner, Maya 0000-0002-3381-6415","orcid":"https://orcid.org/0000-0002-3381-6415","contributorId":220169,"corporation":false,"usgs":true,"family":"Groner","given":"Maya","email":"","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":815491,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Purcell, Maureen K. 0000-0003-0154-8433 mpurcell@usgs.gov","orcid":"https://orcid.org/0000-0003-0154-8433","contributorId":168475,"corporation":false,"usgs":true,"family":"Purcell","given":"Maureen","email":"mpurcell@usgs.gov","middleInitial":"K.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":815492,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gregg, Jacob L. 0000-0001-5328-5482 jgregg@usgs.gov","orcid":"https://orcid.org/0000-0001-5328-5482","contributorId":203912,"corporation":false,"usgs":true,"family":"Gregg","given":"Jacob","email":"jgregg@usgs.gov","middleInitial":"L.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":815493,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hershberger, Paul 0000-0002-2261-7760","orcid":"https://orcid.org/0000-0002-2261-7760","contributorId":203322,"corporation":false,"usgs":true,"family":"Hershberger","given":"Paul","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":815494,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70220372,"text":"70220372 - 2021 - The demographic and ecological factors shaping diversification among rare Astragalus species","interactions":[],"lastModifiedDate":"2021-08-03T14:23:15.719208","indexId":"70220372","displayToPublicDate":"2021-05-06T07:05:13","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1399,"text":"Diversity and Distributions","active":true,"publicationSubtype":{"id":10}},"displayTitle":"The demographic and ecological factors shaping diversification among rare Astragalus species","title":"The demographic and ecological factors shaping diversification among rare Astragalus species","docAbstract":"Evolutionary radiations are central to the origin and maintenance of biodiversity, yet we rarely understand how they are jointly shaped by demography and ecological opportunity. Astragalus is the largest plant genus in the world and is disproportionately comprised of rare species restricted to narrow geographic and ecological regions. Here, we explored the demographic and ecological mechanisms underlying patterns of diversification in a threatened Astragalus species complex endemic to a small desert region in the western United States.
Southeast Utah, USA.
We used high‐throughput DNA sequencing to infer genetic structure, genetic diversity, and demographic history (i.e., the timing of population divergence, effective population sizes and gene flow) among Astragalus taxa. We performed landscape genetic analyses to quantify the relationships between genetic differentiation, geographic distance, and ecological distance based on bioclimatic and soil variables. Finally, we identified putative adaptive loci that show higher genetic differentiation between taxa than expected based on our inferred neutral demographic model.
We found evidence of low gene flow between three highly differentiated taxa (currently delineated as A. iselyi, A. sabulosus var. sabulosus and A. sabulosus var. vehiculus) that rapidly diverged from a small ancestral population near the beginning of the last glacial period. Genomic signatures revealed long‐term effective population sizes are 2–10× larger than recent census sizes, perhaps due to the maintenance of standing genetic variation through seed banks. Consistent with limited dispersal and local adaptation, genome‐wide patterns of differentiation are shaped by geographic distance (isolation‐by‐distance) and climate and soil variation (isolation‐by‐environment). Taxon‐specific adaptation is further supported by uncovering putative adaptive loci.
Our findings suggest that interactions between demography (i.e., dispersal limitations and seeds banks) and ecological opportunity (i.e., spatial and temporal environmental heterogeneity) may promote diversification, endemism, and rarity among closely related Astragalus species and similar plant clades distributed across complex landscapes.
","language":"English","publisher":"Wiley","doi":"10.1111/ddi.13288","usgsCitation":"Jones, M.R., Winkler, D.E., and Massatti, R., 2021, The demographic and ecological factors shaping diversification among rare Astragalus species: Diversity and Distributions, v. 27, no. 8, p. 1407-1421, https://doi.org/10.1111/ddi.13288.","productDescription":"15 p.","startPage":"1407","endPage":"1421","ipdsId":"IP-119600","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":452394,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ddi.13288","text":"Publisher Index Page"},{"id":436380,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93SRC7M","text":"USGS data release","linkHelpText":"Astragalus species complex genetic data from southeast Utah (Grand County and San Juan County), USA"},{"id":385525,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.58837890625,\n 38.229550455326134\n ],\n [\n -109.072265625,\n 38.229550455326134\n ],\n [\n -109.072265625,\n 39.59722324495565\n ],\n [\n -110.58837890625,\n 39.59722324495565\n ],\n [\n -110.58837890625,\n 38.229550455326134\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"27","issue":"8","noUsgsAuthors":false,"publicationDate":"2021-05-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Jones, Matthew Richard 0000-0002-4822-157X","orcid":"https://orcid.org/0000-0002-4822-157X","contributorId":257921,"corporation":false,"usgs":true,"family":"Jones","given":"Matthew","email":"","middleInitial":"Richard","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":815282,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Winkler, Daniel E. 0000-0003-4825-9073","orcid":"https://orcid.org/0000-0003-4825-9073","contributorId":206786,"corporation":false,"usgs":true,"family":"Winkler","given":"Daniel","email":"","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":815283,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Massatti, Robert 0000-0001-5854-5597","orcid":"https://orcid.org/0000-0001-5854-5597","contributorId":207294,"corporation":false,"usgs":true,"family":"Massatti","given":"Robert","email":"","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":815284,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70221398,"text":"70221398 - 2021 - Refining the coarse filter approach: Using habitat-based species models to identify rarity and vulnerabilities in the protection of U.S. biodiversity","interactions":[],"lastModifiedDate":"2021-06-15T10:28:49.88002","indexId":"70221398","displayToPublicDate":"2021-05-03T07:59:13","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3871,"text":"Global Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Refining the coarse filter approach: Using habitat-based species models to identify rarity and vulnerabilities in the protection of U.S. biodiversity","docAbstract":"Preserving biodiversity and its many components is a priority of conservation science and how to efficiently allocate resources to preserve healthy populations of as many species, habitats, and ecosystems as possible. We used the U.S. Geological Survey (USGS) Gap Analysis Project (GAP) species models released in 2018, which identify predicted habitats for terrestrial vertebrates in the conterminous United States, to illustrate hotspots of biodiversity for the major taxonomic groups. This collection represents the first complete compilation of terrestrial vertebrate species models for the conterminous United States (U.S. Geological Survey (USGS), 2018a). We used the species models but not the available subspecies models; this resulted in the inclusion of 282 amphibian models, 621 bird models, 365 mammal models, and 322 reptiles in our analysis. We also used population trend information and made spatial queries to characterize species in three dimensions: geographic range (small or large), habitat breadth (narrow or wide), and population trend (decreasing vs stable or increasing). This characterization allowed us to divide the species into eight groups (A-H) with similar characteristics. Group A species (large geographic range, wide habitat breadth, and stable or increasing population trend) are species that are common now with no indication of becoming rare. Species B-H have theoretical or known characteristics that could lead them to become rare with the H species exhibiting small geographic range, narrow habitat breadth, and decreasing population trend. Finally, we evaluated the prevalence of mapped habitat on protected lands for each species, exploring the patterns of representation in the rare species groups by ecoregion. The species we identified with population and habitat use characteristics that potentially predispose them to being or becoming rare represented a large percentage of each taxon. Potentially rare species were widely distributed among ecoregions. Of the 20 ecoregions in the country, 14 have a greater number of rare species than the national average for at least one taxon. Protection of the habitat for the majority of these rare species is below that recommended (17% of available habitat) by the Convention on Biological Diversity (CBD). The Everglades ecoregion was the only ecoregion that protected more than half of its rare or potentially rare species.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.gecco.2021.e01598","usgsCitation":"Davidson, A., Dunn, L., Gergely, K., McKerrow, A., Williams, S.G., and Case, M., 2021, Refining the coarse filter approach: Using habitat-based species models to identify rarity and vulnerabilities in the protection of U.S. biodiversity: Global Ecology and Conservation, v. 28, e01598, 19 p., https://doi.org/10.1016/j.gecco.2021.e01598.","productDescription":"e01598, 19 p.","ipdsId":"IP-101927","costCenters":[{"id":38128,"text":"Science Analytics and Synthesis","active":true,"usgs":true}],"links":[{"id":452441,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gecco.2021.e01598","text":"Publisher Index Page"},{"id":386468,"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 -127.61718749999999,\n 25.16517336866393\n ],\n [\n -63.984375,\n 25.16517336866393\n ],\n [\n -63.984375,\n 51.83577752045248\n ],\n [\n -127.61718749999999,\n 51.83577752045248\n ],\n [\n -127.61718749999999,\n 25.16517336866393\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"28","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Davidson, Anne","contributorId":197967,"corporation":false,"usgs":false,"family":"Davidson","given":"Anne","email":"","affiliations":[],"preferred":false,"id":817517,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dunn, Leah","contributorId":217944,"corporation":false,"usgs":false,"family":"Dunn","given":"Leah","email":"","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":817518,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gergely, Kevin 0000-0002-4379-2189","orcid":"https://orcid.org/0000-0002-4379-2189","contributorId":208371,"corporation":false,"usgs":true,"family":"Gergely","given":"Kevin","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":817519,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McKerrow, Alexa 0000-0002-8312-2905 amckerrow@usgs.gov","orcid":"https://orcid.org/0000-0002-8312-2905","contributorId":127753,"corporation":false,"usgs":true,"family":"McKerrow","given":"Alexa","email":"amckerrow@usgs.gov","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":817520,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Williams, Steven G. 0000-0003-3760-6818","orcid":"https://orcid.org/0000-0003-3760-6818","contributorId":215501,"corporation":false,"usgs":false,"family":"Williams","given":"Steven","email":"","middleInitial":"G.","affiliations":[{"id":39268,"text":"North Carolina State University, NC Cooperative Fish & Wildlife Research Unit","active":true,"usgs":false}],"preferred":false,"id":817521,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Case, Mackenzie 0000-0002-5657-9133","orcid":"https://orcid.org/0000-0002-5657-9133","contributorId":260200,"corporation":false,"usgs":false,"family":"Case","given":"Mackenzie","email":"","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":817522,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70223879,"text":"70223879 - 2021 - Intact landscape promotes gene flow and low genetic structuring in the threatened Eastern Massasauga Rattlesnake","interactions":[],"lastModifiedDate":"2021-09-13T13:20:31.409068","indexId":"70223879","displayToPublicDate":"2021-05-02T08:10:01","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Intact landscape promotes gene flow and low genetic structuring in the threatened Eastern Massasauga Rattlesnake","docAbstract":"Genetic structuring of wild populations is dependent on environmental, ecological, and life-history factors. The specific role environmental context plays in genetic structuring is important to conservation practitioners working with rare species across areas with varying degrees of fragmentation. We investigated fine-scale genetic patterns of the federally threatened Eastern Massasauga Rattlesnake (Sistrurus catenatus) on a relatively undisturbed island in northern Michigan, USA. This species often persists in habitat islands throughout much of its distribution due to extensive habitat loss and distance-limited dispersal. We found that the entire island population exhibited weak genetic structuring with spatially segregated variation in effective migration and genetic diversity. The low level of genetic structuring contrasts with previous studies in the southern part of the species’ range at comparable fine scales (~7 km), in which much higher levels of structuring were documented. The island population's genetic structuring more closely resembles that of populations from Ontario, Canada, that occupy similarly intact habitats. Intrapopulation variation in effective migration and genetic diversity likely corresponds to the presence of large inland lakes acting as barriers and more human activity in the southern portion of the island. The observed genetic structuring in this intact landscape suggests that the Eastern Massasauga is capable of sufficient interpatch movements to reduce overall genetic structuring and colonize new habitats. Landscape mosaics with multiple habitat patches and localized barriers (e.g., large water bodies or roads) will promote gene flow and natural colonization for this declining species.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.7480","usgsCitation":"Kudla, N., McCluskey, E.M., Lulla, V., Grundel, R., and Moore, J.A., 2021, Intact landscape promotes gene flow and low genetic structuring in the threatened Eastern Massasauga Rattlesnake: Ecology and Evolution, v. 11, no. 11, p. 6276-6288, https://doi.org/10.1002/ece3.7480.","productDescription":"13 p.","startPage":"6276","endPage":"6288","ipdsId":"IP-120488","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":452455,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.7480","text":"Publisher Index Page"},{"id":436385,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HJW59U","text":"USGS data release","linkHelpText":"Genotype Data for Eastern Massasauga Rattlesnakes (Sistrurus catenatus) from Bois Blanc Island, Michigan at 15 Microsatellite DNA Loci"},{"id":389141,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan","otherGeospatial":"Bois Blanc Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.39697265625,\n 45.72152152227954\n ],\n [\n -84.34890747070312,\n 45.774707263032546\n ],\n [\n -84.40177917480469,\n 45.78907308856107\n ],\n [\n -84.42649841308594,\n 45.81827218518002\n ],\n [\n -84.42924499511719,\n 45.807743127853776\n ],\n [\n -84.4244384765625,\n 45.79338211440398\n ],\n [\n -84.43267822265625,\n 45.79003067864973\n ],\n [\n -84.49928283691406,\n 45.81157210628936\n ],\n [\n -84.51507568359375,\n 45.81300790534134\n ],\n [\n -84.53361511230469,\n 45.80965764997408\n ],\n [\n -84.58786010742188,\n 45.821621922335794\n ],\n [\n -84.59609985351562,\n 45.80917902561322\n ],\n [\n -84.57344055175781,\n 45.79816953017265\n ],\n [\n -84.54391479492188,\n 45.77901739936284\n ],\n [\n -84.5240020751953,\n 45.754109791149894\n ],\n [\n -84.51576232910155,\n 45.74883944887109\n ],\n [\n -84.50065612792967,\n 45.72583576754234\n ],\n [\n -84.43611145019531,\n 45.7205627558654\n ],\n [\n -84.41688537597656,\n 45.71480981187499\n ],\n [\n -84.39697265625,\n 45.72152152227954\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"11","noUsgsAuthors":false,"publicationDate":"2021-05-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Kudla, Nathan","contributorId":265592,"corporation":false,"usgs":false,"family":"Kudla","given":"Nathan","email":"","affiliations":[{"id":15305,"text":"Grand Valley State University","active":true,"usgs":false}],"preferred":false,"id":823068,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCluskey, Eric M.","contributorId":265593,"corporation":false,"usgs":false,"family":"McCluskey","given":"Eric","email":"","middleInitial":"M.","affiliations":[{"id":15305,"text":"Grand Valley State University","active":true,"usgs":false}],"preferred":false,"id":823069,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lulla, Vijay","contributorId":265594,"corporation":false,"usgs":false,"family":"Lulla","given":"Vijay","email":"","affiliations":[{"id":54727,"text":"Indiana University Purdue University Indianapolis","active":true,"usgs":false}],"preferred":false,"id":823070,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Grundel, Ralph 0000-0002-2949-7087 rgrundel@usgs.gov","orcid":"https://orcid.org/0000-0002-2949-7087","contributorId":2444,"corporation":false,"usgs":true,"family":"Grundel","given":"Ralph","email":"rgrundel@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":823071,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Moore, Jennifer A.","contributorId":265595,"corporation":false,"usgs":false,"family":"Moore","given":"Jennifer","email":"","middleInitial":"A.","affiliations":[{"id":15305,"text":"Grand Valley State University","active":true,"usgs":false}],"preferred":false,"id":823072,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70211230,"text":"70211230 - 2021 - Current activity on the Martian surface: A key subject for future exploration","interactions":[],"lastModifiedDate":"2021-10-12T15:08:55.173485","indexId":"70211230","displayToPublicDate":"2021-04-30T10:05:48","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":9373,"text":"Bulletin of the AAS","active":true,"publicationSubtype":{"id":1}},"title":"Current activity on the Martian surface: A key subject for future exploration","docAbstract":"One of the fundamental discoveries in Mars science in the last decade has been the extent and importance of current surface activity. Recent results have shifted our view of Mars from a world where the most interesting geologic events were in the distant past (similar to the Moon) to a world that undergoes active evolution and one where understanding the present is key to deciphering the planet’s history. When input was requested for the last Planetary Science Decadal Survey, some observations of surface changes had been published, but the number of detections was small and their significance not fully appreciated. Since that time, detections have proliferated, driven primarily by the long-term operation of the Mars Reconnaissance Orbiter (MRO) and the High Resolution Imaging Science Experiment (HiRISE) as well as landed observations of aeolian activity. In addition to observed changes, theory suggests that additional important surface processes are likely active but not yet observed because orbital data are limited in space and time and landed studies are rare.
Understanding current Martian surface processes is a fundamental science question in itself, as it provides a test for physical and terrestrial analog-based models of specific geological processes acting under non-Earth planetary and environmental conditions. It is also an essential step for reading Mars’ geologic history and providing input to climate models: without understanding current dynamic processes, we cannot understand how they have varied during recent climate cycles, nor how they are reflected in ancient rock or modern ice records. Understanding the rates and types of current surface activity is also highly relevant to selecting geological samples, setting Planetary Protection rules, and understanding the hazards and environment that would be experienced by future human explorers.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Planetary science and astrobiology decadal survey 2023-2032","largerWorkSubtype":{"id":1,"text":"Federal Government Series"},"language":"English","publisher":"National Academy of Sciences","doi":"10.3847/25c2cfeb.72861191","usgsCitation":"Dundas, C.M., Byrne, S., Chojnacki, M., Diniega, S., Daubar, I.J., Hamilton, C.W., Hansen, C.J., McEwen, A.S., Portyankina, G., and Sizemore, H.G., 2021, Current activity on the Martian surface: A key subject for future exploration: Bulletin of the AAS, v. 53, no. 4, Whitepaper #157, 8 p., https://doi.org/10.3847/25c2cfeb.72861191.","productDescription":"Whitepaper #157, 8 p.","startPage":"2023","endPage":"2032","ipdsId":"IP-119571","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":452513,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3847/25c2cfeb.72861191","text":"Publisher Index Page"},{"id":390419,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Mars","volume":"53","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-03-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Dundas, Colin M. 0000-0003-2343-7224 cdundas@usgs.gov","orcid":"https://orcid.org/0000-0003-2343-7224","contributorId":2937,"corporation":false,"usgs":true,"family":"Dundas","given":"Colin","email":"cdundas@usgs.gov","middleInitial":"M.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":793282,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Byrne, Shane","contributorId":53513,"corporation":false,"usgs":false,"family":"Byrne","given":"Shane","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":793283,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chojnacki, Matthew","contributorId":201621,"corporation":false,"usgs":false,"family":"Chojnacki","given":"Matthew","affiliations":[{"id":27205,"text":"U. Arizona","active":true,"usgs":false}],"preferred":false,"id":793284,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Diniega, Serina","contributorId":212017,"corporation":false,"usgs":false,"family":"Diniega","given":"Serina","email":"","affiliations":[{"id":36276,"text":"JPL","active":true,"usgs":false}],"preferred":false,"id":793285,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Daubar, Ingrid J.","contributorId":204233,"corporation":false,"usgs":false,"family":"Daubar","given":"Ingrid","email":"","middleInitial":"J.","affiliations":[{"id":7023,"text":"Jet Propulsion Laboratory, California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":793286,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hamilton, Christopher W.","contributorId":196266,"corporation":false,"usgs":false,"family":"Hamilton","given":"Christopher","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":793287,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hansen, Candice J.","contributorId":70235,"corporation":false,"usgs":false,"family":"Hansen","given":"Candice","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":793288,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McEwen, Alfred S.","contributorId":61657,"corporation":false,"usgs":false,"family":"McEwen","given":"Alfred","email":"","middleInitial":"S.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":793289,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Portyankina, Ganna","contributorId":200703,"corporation":false,"usgs":false,"family":"Portyankina","given":"Ganna","email":"","affiliations":[],"preferred":false,"id":793290,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Sizemore, Hanna G 0000-0002-6641-2388","orcid":"https://orcid.org/0000-0002-6641-2388","contributorId":229472,"corporation":false,"usgs":false,"family":"Sizemore","given":"Hanna","email":"","middleInitial":"G","affiliations":[{"id":24584,"text":"PSI","active":true,"usgs":false}],"preferred":false,"id":793291,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70220242,"text":"fs20213025 - 2021 - Storms and floods of July 30, 2016, and May 27, 2018, in Ellicott City, Howard County, Maryland","interactions":[],"lastModifiedDate":"2021-04-29T17:07:33.658702","indexId":"fs20213025","displayToPublicDate":"2021-04-29T10:30:00","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-3025","displayTitle":"Storms and Floods of July 30, 2016, and May 27, 2018, in Ellicott City, Howard County, Maryland","title":"Storms and floods of July 30, 2016, and May 27, 2018, in Ellicott City, Howard County, Maryland","docAbstract":"On July 30, 2016, and May 27, 2018, the downtown area of Ellicott City, Maryland (fig. 1), was severely flooded by intense, short-duration rainfall that resulted in loss of life; significant damage to buildings, roads, infrastructure; and hundreds of vehicles washed away. Precipitation from the 2016 event totaled 6.60 inches in 3 hours (National Oceanic and Atmospheric Administration, 2016). Precipitation from the 2018 storm totaled 6.56 inches in 3 hours (National Oceanic and Atmospheric Administration, 2018).
In the aftermath of both storms, personnel from the U.S. Geological Survey (USGS) performed indirect discharge measurements to determine peak flow on the three streams that drain through the downtown area of Ellicott City and empty into the Patapsco River. High-water marks were flagged on selected reaches of three streams, Hudson Branch (station 01589017), Tiber Branch (station 01589019), and New Cut Branch (station 01589021) (fig. 2). Peak flows were computed using flow-through-culvert techniques with road overflow for Hudson Branch and slope-area techniques for Tiber Branch and New Cut Branch.
This fact sheet describes the basin characteristics, hydrologic characteristics, and flood history of the Ellicott City, Maryland, area. The storms and flood characteristics for July 30, 2016, and May 27, 2018, are described. Peak discharges computed from the indirect discharge measurements for Hudson Branch, Tiber Branch, and New Cut Branch are presented for the storms and floods of July 30, 2016, and May 27, 2018. To provide historical perspective on these floods in Ellicott City, results from the indirect discharge measurement computations were compared to peak flows from 75 USGS streamgages and 6 miscellaneous sites in Maryland and Delaware that resulted from intense storms in August and September 1971 (Carpenter, 1974). The findings indicate that although the Ellicott City storms and floods from July 30, 2016, and May 27, 2018, are considered very rare in terms of their probability of occurrence, other storms have occurred in the Maryland and Delaware regions in the past that have produced comparable runoff characteristics relative to drainage-area magnitude.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20213025","usgsCitation":"Doheny, E.J., and Nealen, C.W., 2021, Storms and floods of July 30, 2016, and May 27, 2018, in Ellicott City, Howard County, Maryland: U.S. Geological Survey Fact Sheet 2021–3025, 6 p., https://doi.org/10.3133/fs20213025.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-114401","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":385345,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2021/3025/coverthb.jpg"},{"id":385346,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2021/3025/fs20213025.pdf","text":"Report","size":"10.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2021-3025"}],"country":"United States","state":"Maryland","county":"Howard 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Maryland-Delaware-D.C. Water Science Center
U.S. Geological Survey
5522 Research Park Drive
Catonsville, MD 21228
A cloudburst on 7 August 2018 in the coastal bluffs of the Atlantic Highlands, New Jersey, induced flooding, erosion and multiple shallow slope failures that adversely affected the surrounding hillside residential area. Historically, short-duration deluges are rare in the New York Bay region, with only eight cloudbursts of greater magnitude documented since 1948. The coastal bluffs consist of a variably thick, sandy surficial material overlying flat-lying, mostly non-indurated Cretaceous and Tertiary sediments, including some low-permeability glauconitic units. The bluffs have been affected by both historical deep-seated and shallow landslide movement, the latter typically related to heavy, relatively long-duration rainfall associated with tropical cyclones and nor'easters. The shallow hydrological response during the rare cloudburst was captured at two hydrological monitoring sites and yielded insights into rapidly changing moisture conditions resulting in slope failure. Additional information is provided on historical cloudbursts that have affected the region, antecedent moisture conditions, and documented landslide types and processes.
","language":"English","publisher":"Geological Society of America","doi":"10.1144/qjegh2020-127","usgsCitation":"Ashland, F., Reilly, P.A., and Fiore, A.R., 2021, Capturing the transient hydrological response in sandy soils during a rare cloudburst associated with shallow slope failures; A case study in the Atlantic Highlands, New Jersey, USA: Quarterly Journal of Engineering Geology and Hydrogeology, v. 54, no. 4, qjegh2020-127, 10 p., https://doi.org/10.1144/qjegh2020-127.","productDescription":"qjegh2020-127, 10 p.","ipdsId":"IP-113986","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":436389,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9A601HC","text":"USGS data release","linkHelpText":"Hydrologic, slope movement, and soil property data from the coastal bluffs of the Atlantic Highlands, New Jersey, 2016-2018"},{"id":387111,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Jersey","otherGeospatial":"Atlantic Highlands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.1851806640625,\n 40.250184183819854\n ],\n [\n -73.8226318359375,\n 40.250184183819854\n ],\n [\n -73.8226318359375,\n 40.48873742102282\n ],\n [\n -74.1851806640625,\n 40.48873742102282\n ],\n [\n -74.1851806640625,\n 40.250184183819854\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"54","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-04-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Ashland, Francis 0000-0001-9948-0195 fashland@usgs.gov","orcid":"https://orcid.org/0000-0001-9948-0195","contributorId":198587,"corporation":false,"usgs":true,"family":"Ashland","given":"Francis","email":"fashland@usgs.gov","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":819186,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reilly, Pamela A. 0000-0002-2937-4490 jankowsk@usgs.gov","orcid":"https://orcid.org/0000-0002-2937-4490","contributorId":653,"corporation":false,"usgs":true,"family":"Reilly","given":"Pamela","email":"jankowsk@usgs.gov","middleInitial":"A.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":819187,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fiore, Alex R. 0000-0002-0986-5225 afiore@usgs.gov","orcid":"https://orcid.org/0000-0002-0986-5225","contributorId":4977,"corporation":false,"usgs":true,"family":"Fiore","given":"Alex","email":"afiore@usgs.gov","middleInitial":"R.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":819188,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70222120,"text":"70222120 - 2021 - Sagebrush recovery patterns after fuel treatments mediated by disturbance type and plant functional group interactions","interactions":[],"lastModifiedDate":"2021-07-20T11:46:05.454447","indexId":"70222120","displayToPublicDate":"2021-04-23T06:43:23","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Sagebrush recovery patterns after fuel treatments mediated by disturbance type and plant functional group interactions","docAbstract":"Fire and fuel management is a high priority in North American sagebrush ecosystems where the expansion of piñon and juniper trees and the invasion of nonnative annual grasses are altering fire regimes and resulting in loss of sagebrush species and habitat. We evaluated 10-yr effects of woody fuel treatments on sagebrush recruitment and plant functional group interactions using Sagebrush Steppe Treatment Evaluation Project data. We used mixed-effects ANOVAs to examine treatment effects on sagebrush density and cover and perennial and annual grass cover in expansion woodlands (prescribed fire and cut-and-leave) and annual grass invasion areas (prescribed fire, mowing, tebuthiuron herbicide application). We used piecewise structural equation models to evaluate interactions among sagebrush seedling density, juvenile and adult density, and cover and perennial and annual grass cover. Fuel treatments were equated to pulse or press disturbances varying in resource release and subsequent intra- and interspecific interactions. Prescribed fire, a high magnitude pulse disturbance with more severe effects in warm and dry sites, reduced sagebrush cover and decoupled associations among sagebrush seedlings, juvenile and adult density, and cover indicating changed population structure. Cutting and leaving trees, a low magnitude pulse disturbance in cooler and moister woodlands, increased sagebrush density and cover and generally had lesser effects on sagebrush intraspecific associations. Mowing, a moderate magnitude pulse disturbance, and tebuthiuron herbicide application, a multiyear press disturbance, reduced sagebrush cover and disrupted intraspecific relationships. Competitive release increased cover of perennial grass in all treatments but tebuthiuron. Annual grass increased in all treatments, especially prescribed fire and tebuthiuron. Annual and perennial grass interactions with sagebrush were generally rare, but in woodland treatments perennial grass suppressed annual grass through year 6. Treatments in cooler and moister woodland sites had more positive effects on sagebrush recruitment and perennial grass cover, less negative effects on sagebrush intraspecific interactions, and smaller increases in annual grass cover indicating potential increases in resilience to fire. In warmer and drier invasion sites, reductions in woody fuels resulted in lack of sagebrush recruitment, disruption of sagebrush intraspecific interactions, and progressive increases in annual grass indicating reduced resilience to fire and resistance to invaders.
","language":"English","publisher":"Wiley","doi":"10.1002/ecs2.3450","usgsCitation":"Chambers, J., Urza, A.K., Board, D.I., Miller, R.F., Pyke, D.A., Roundy, B.A., Schupp, E.W., and Tausch, R.J., 2021, Sagebrush recovery patterns after fuel treatments mediated by disturbance type and plant functional group interactions: Ecosphere, v. 12, no. 4, e03450, 22 p., https://doi.org/10.1002/ecs2.3450.","productDescription":"e03450, 22 p.","ipdsId":"IP-123790","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":489091,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.3450","text":"Publisher Index Page"},{"id":387283,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-04-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Chambers, Jeanne C.","contributorId":75889,"corporation":false,"usgs":false,"family":"Chambers","given":"Jeanne C.","affiliations":[],"preferred":false,"id":819607,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Urza, Alexandra K. 0000-0001-9795-6735","orcid":"https://orcid.org/0000-0001-9795-6735","contributorId":261259,"corporation":false,"usgs":false,"family":"Urza","given":"Alexandra","email":"","middleInitial":"K.","affiliations":[{"id":16848,"text":"USDA Forest Service, Rocky Mountain Research Station","active":true,"usgs":false}],"preferred":false,"id":819608,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Board, David I.","contributorId":261260,"corporation":false,"usgs":false,"family":"Board","given":"David","email":"","middleInitial":"I.","affiliations":[{"id":16848,"text":"USDA Forest Service, Rocky Mountain Research Station","active":true,"usgs":false}],"preferred":false,"id":819609,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, Richard F.","contributorId":178258,"corporation":false,"usgs":false,"family":"Miller","given":"Richard","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":819610,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pyke, David A. 0000-0002-4578-8335 david_a_pyke@usgs.gov","orcid":"https://orcid.org/0000-0002-4578-8335","contributorId":3118,"corporation":false,"usgs":true,"family":"Pyke","given":"David","email":"david_a_pyke@usgs.gov","middleInitial":"A.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":819611,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Roundy, Bruce A.","contributorId":178261,"corporation":false,"usgs":false,"family":"Roundy","given":"Bruce","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":819612,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schupp, Eugene W.","contributorId":178262,"corporation":false,"usgs":false,"family":"Schupp","given":"Eugene","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":819613,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Tausch, Robin J.","contributorId":213637,"corporation":false,"usgs":false,"family":"Tausch","given":"Robin","email":"","middleInitial":"J.","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":819614,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70220316,"text":"70220316 - 2021 - Long‐term surveys support declines in early‐season forest plants used by bumblebees","interactions":[],"lastModifiedDate":"2021-08-03T14:08:51.128094","indexId":"70220316","displayToPublicDate":"2021-04-18T06:58:09","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Long‐term surveys support declines in early‐season forest plants used by bumblebees","docAbstract":"The potential for widespread landslides is generally increased when extraordinary wet periods occur during times of elevated subsurface hydrologic conditions. A series of storms in early 2018 in Pittsburgh, Pennsylvania, overlapped with a period of increased shallow soil moisture and rising bedrock groundwater levels resulting from seasonally diminished evapotranspiration and induced widespread landslides in the region. Most of the landslides were shallow slope failures in colluvium, landslide deposits, and/or fill. However, deep-seated landslide activity also occurred and corresponded with record cumulative precipitation from late February to April and bedrock groundwater levels rising to an annual high. Landslides blocked or damaged roads, adversely affected multiple houses, disrupted electrical service, crushed vehicles, and resulted in considerable economic losses. The initial landslides occurred during or immediately after a rare period of three successive days of heavy rain that began on February 14. Subsequent landslides between late February and April were induced by multiday storms with smaller rainfall totals. As shallow soil moisture at a monitoring site rose above a volumetric water content of 32%, the mean rainfall intensities necessary to induce slope failure in colluvium and other surficial deposits decreased. Deep-seated landslide movement occurred in the region mostly when the groundwater level in a bedrock observation well was shallower than 1.7 m. The availability of hydrologic and landslide movement monitoring data during this extraordinary series of storms highlighted the evolution of the landslide hazard with changing moisture conditions and yielded insights into potential hydrologic criteria for anticipating future widespread landslides in the region.
","language":"English","publisher":"Springer","doi":"10.1007/s10346-021-01665-x","usgsCitation":"Ashland, F., 2021, Critical shallow and deep hydrologic conditions associated with widespread landslides during a series of storms between February and April 2018 in Pittsburgh and vicinity, western Pennsylvania, USA: Landslides, v. 18, no. 6, p. 2159-2174, https://doi.org/10.1007/s10346-021-01665-x.","productDescription":"16 p.","startPage":"2159","endPage":"2174","ipdsId":"IP-099724","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":436408,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9BHFXFS","text":"USGS data release","linkHelpText":"Monitoring data from the Aleppo rockslide, Allegheny County, Pennsylvania, November 2013 - December 2018"},{"id":387112,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","county":"Allegheny County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.15625,\n 40.07807142745009\n ],\n [\n -79.2333984375,\n 40.07807142745009\n ],\n [\n -79.2333984375,\n 40.68063802521456\n ],\n [\n -80.15625,\n 40.68063802521456\n ],\n [\n -80.15625,\n 40.07807142745009\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"18","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-04-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Ashland, Francis 0000-0001-9948-0195 fashland@usgs.gov","orcid":"https://orcid.org/0000-0001-9948-0195","contributorId":198587,"corporation":false,"usgs":true,"family":"Ashland","given":"Francis","email":"fashland@usgs.gov","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":819177,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70228923,"text":"70228923 - 2021 - Hibernation behavior of a federally-threatened ground squirrel: Climate change and habitat selection implications","interactions":[],"lastModifiedDate":"2022-02-24T20:20:54.364557","indexId":"70228923","displayToPublicDate":"2021-04-13T13:51:24","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2373,"text":"Journal of Mammalogy","onlineIssn":"1545-1542","printIssn":"0022-2372","active":true,"publicationSubtype":{"id":10}},"title":"Hibernation behavior of a federally-threatened ground squirrel: Climate change and habitat selection implications","docAbstract":"Hibernation is an adaptation to survive periods of stress, from food limitation or harsh thermal conditions. A key question in contemporary ecology is whether rare, range-restricted species can change their behavior in response to climate change (i.e., through behavioral plasticity). The northern Idaho ground squirrel, Urocitellus brunneus (A. H. Howell, 1928), is a federally threatened species that hibernates for approximately 8 months per year within the bounds of its small range in central Idaho, USA. Changes in temperature, snow accumulation, and summer precipitation, all brought about as a result of climate change, may reduce survival or fecundity of northern Idaho ground squirrels if they cannot adapt to these climate changes. Hibernating species can respond to climate-change-induced thermal challenges in two ways: change their hibernation physiology and behavior (i.e., emergence date or number of torpor bouts) or alter their environment (i.e., change hibernacula depth or location). We explored a suite of intrinsic and extrinsic factors to document the extent to which they influenced hibernation behavior of northern Idaho ground squirrels. Emergence date was positively associated with snowpack and negatively associated with mean winter temperature. Mean minimum skin temperature was negatively associated with canopy closure and slope of a squirrel’s hibernaculum. Duration of the heterothermal period, number of euthermic bouts, and total time spent euthermic were positively associated with body mass. Immergence date and duration of the longest torpor bout were negatively associated with body mass. Warmer temperatures and less snow accumulation in the winter—caused by climate change—likely will cause altered emergence dates. Our results suggest that any future climate-induced changes in snowfall, ambient temperature, food availability, or habitat likely will impact survival of this rare ground squirrel, because such changes will cause changes in hibernation behavior, percent mass loss during hibernation, and duration of the active season when small mammals are more susceptible to predation.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/jmammal/gyab021","usgsCitation":"Goldberg, A., and Conway, C.J., 2021, Hibernation behavior of a federally-threatened ground squirrel: Climate change and habitat selection implications: Journal of Mammalogy, v. 102, no. 2, p. 574-587, https://doi.org/10.1093/jmammal/gyab021.","productDescription":"14 p.","startPage":"574","endPage":"587","ipdsId":"IP-119242","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":452691,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/jmammal/gyab021","text":"Publisher Index Page"},{"id":396450,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","county":"Adams 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Amanda R.","contributorId":280029,"corporation":false,"usgs":false,"family":"Goldberg","given":"Amanda R.","affiliations":[{"id":39599,"text":"ui","active":true,"usgs":false}],"preferred":false,"id":835912,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conway, Courtney J. 0000-0003-0492-2953 cconway@usgs.gov","orcid":"https://orcid.org/0000-0003-0492-2953","contributorId":2951,"corporation":false,"usgs":true,"family":"Conway","given":"Courtney","email":"cconway@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":835911,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70219571,"text":"70219571 - 2021 - Abundance of a recently discovered Alaskan rhodolith bed in a shallow, seagrass-dominated lagoon","interactions":[],"lastModifiedDate":"2021-05-13T15:47:15.589885","indexId":"70219571","displayToPublicDate":"2021-04-12T06:48:30","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1069,"text":"Botanica Marina","active":true,"publicationSubtype":{"id":10}},"title":"Abundance of a recently discovered Alaskan rhodolith bed in a shallow, seagrass-dominated lagoon","docAbstract":"Rhodoliths are important foundation species of the benthic photic zone but are poorly known and rarely studied in Alaska. A bed of Lithothamnion soriferum rhodoliths was discovered in 2008 in Kinzarof Lagoon, Alaska, a shallow-water embayment dominated by eelgrass (Zostera marina). Rhodolith presence and biomass were estimated to assess trends and environmental factors that may influence rhodolith distribution and abundance during 4 years spread over a 12-year period (2008–2010, and 2019). Rhodolith presence and biomass were positively associated with percent seaweed cover, as most rhodoliths and seaweeds occurred in subtidal areas, and negatively associated with percent eelgrass cover. Rhodoliths occurred in two primary areas of the lagoon, a 182-ha core area in a shallow water (mean tide depth of -0.03 m MLLW) tidal channel with low eelgrass density, and a 22-ha outlying area at shallower water depths (>0.2 m MLLW) with moderate to high eelgrass cover. There was no apparent trend in rhodolith biomass over the study period despite wide variation in mean annual estimates. This study establishes a baseline for continued investigations and monitoring of this important benthic resource in Alaska.","language":"English","publisher":"Walter de Gruyter","doi":"10.1515/bot-2020-0072","usgsCitation":"Ward, D.H., Amundson, C., Fitzmorris, P., Menning, D.M., Markis, J., Sowl, K.M., and Lindstrom, S.C., 2021, Abundance of a recently discovered Alaskan rhodolith bed in a shallow, seagrass-dominated lagoon: Botanica Marina, v. 64, no. 2, p. 119-127, https://doi.org/10.1515/bot-2020-0072.","productDescription":"9 p.","startPage":"119","endPage":"127","ipdsId":"IP-120006","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":385073,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Kinzarof Lagoon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -162.6328468322754,\n 55.27403067982278\n ],\n [\n -162.56675720214844,\n 55.27921306663861\n ],\n [\n -162.5598907470703,\n 55.28683874542267\n ],\n [\n -162.56298065185547,\n 55.30013129739357\n ],\n [\n -162.58855819702148,\n 55.30110851519261\n ],\n [\n -162.60984420776367,\n 55.30335602478241\n ],\n [\n -162.63782501220703,\n 55.30648278283089\n ],\n [\n -162.6687240600586,\n 55.29680857682341\n ],\n [\n -162.69515991210938,\n 55.27383510481281\n ],\n [\n -162.6858901977539,\n 55.27315058469293\n ],\n [\n -162.6328468322754,\n 55.27403067982278\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"64","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-04-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Ward, David H. 0000-0002-5242-2526 dward@usgs.gov","orcid":"https://orcid.org/0000-0002-5242-2526","contributorId":3247,"corporation":false,"usgs":true,"family":"Ward","given":"David","email":"dward@usgs.gov","middleInitial":"H.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":814206,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Amundson, Courtney","contributorId":257417,"corporation":false,"usgs":false,"family":"Amundson","given":"Courtney","affiliations":[{"id":40349,"text":"USGS Alaska Science Center (former employee)","active":true,"usgs":false}],"preferred":false,"id":814207,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fitzmorris, Patrick","contributorId":222725,"corporation":false,"usgs":false,"family":"Fitzmorris","given":"Patrick","email":"","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":814208,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Menning, Damian M. 0000-0003-3547-3062 dmenning@usgs.gov","orcid":"https://orcid.org/0000-0003-3547-3062","contributorId":205131,"corporation":false,"usgs":true,"family":"Menning","given":"Damian","email":"dmenning@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":814209,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Markis, Joel","contributorId":257418,"corporation":false,"usgs":false,"family":"Markis","given":"Joel","email":"","affiliations":[{"id":16298,"text":"University of Alaska Southeast","active":true,"usgs":false}],"preferred":false,"id":814210,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sowl, Kristine M.","contributorId":60372,"corporation":false,"usgs":false,"family":"Sowl","given":"Kristine","email":"","middleInitial":"M.","affiliations":[{"id":12598,"text":"Izembek National Wildlife Refuge","active":true,"usgs":false}],"preferred":false,"id":814211,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lindstrom, Sandra C.","contributorId":242967,"corporation":false,"usgs":false,"family":"Lindstrom","given":"Sandra","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":814212,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70219605,"text":"70219605 - 2021 - 3-D geologic controls of hydrothermal fluid flow at Brady geothermal field, Nevada, USA","interactions":[],"lastModifiedDate":"2021-04-15T12:22:10.257428","indexId":"70219605","displayToPublicDate":"2021-04-10T07:16:28","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1828,"text":"Geothermics","active":true,"publicationSubtype":{"id":10}},"title":"3-D geologic controls of hydrothermal fluid flow at Brady geothermal field, Nevada, USA","docAbstract":"In many hydrothermal systems, fracture permeability along faults provides pathways for groundwater to transport heat from depth. Faulting generates a range of deformation styles that cross-cut heterogeneous geology, resulting in complex patterns of permeability, porosity, and hydraulic conductivity. Vertical connectivity (a throughgoing network of permeable areas that allows advection of heat from depth to the shallow subsurface) is rare and is confined to relatively small volumes that have highly variable spatial distribution. This local compartmentalization of connectivity represents a significant challenge to understanding hydrothermal circulation and for exploring, developing, and managing hydrothermal resources. Here, we present an evaluation of the geologic characteristics that control this compartmentalization in hydrothermal systems through 3-D analysis of the Brady geothermal field in western Nevada. A published 3-D geologic map of the Brady area is used as a basis to develop structural and geological variables that are hypothesized to control or effect permeability or connectivity. The 3-D distribution of these variables is compared to the distribution of productive and non-productive fluid flow intervals along production wells and non-productive wells via principal component analysis (PCA). This comparison elucidates which geologic and structural variables are most closely associated with productive fluid flow intervals. Results indicate that production intervals at Brady are located: (1) within or near to known and stress-loaded macro-scale faults, and (2) in areas of high fault and fracture density.
Surficial mass wasting events are a hazard worldwide. Seismic and acoustic signals from these often remote processes, combined with other geophysical observations, can provide key information for monitoring and rapid response efforts and enhance our understanding of event dynamics. Here, we present seismoacoustic data and analyses for two very large ice–rock avalanches occurring on Iliamna Volcano, Alaska (USA), on 22 May 2016 and 21 June 2019. Iliamna is a glacier-mantled stratovolcano located in the Cook Inlet, ∼200 km from Anchorage, Alaska. The volcano experiences massive, quasi-annual slope failures due to glacial instabilities and hydrothermal alteration of volcanic rocks near its summit. The May 2016 and June 2019 avalanches were particularly large and generated energetic seismic and infrasound signals which were recorded at numerous stations at ranges from ∼9 to over 600 km. Both avalanches initiated in the same location near the head of Iliamna's east-facing Red Glacier, and their ∼8 km long runout shapes are nearly identical. This repeatability – which is rare for large and rapid mass movements – provides an excellent opportunity for comparison and validation of seismoacoustic source characteristics. For both events, we invert long-period (15–80 s) seismic signals to obtain a force-time representation of the source. We model the avalanche as a sliding block which exerts a spatially static point force on the Earth. We use this force-time function to derive constraints on avalanche acceleration, velocity, and directionality, which are compatible with satellite imagery and observed terrain features. Our inversion results suggest that the avalanches reached speeds exceeding 70 m s−1, consistent with numerical modeling from previous Iliamna studies. We lack sufficient local infrasound data to test an acoustic source model for these processes. However, the acoustic data suggest that infrasound from these avalanches is produced after the mass movement regime transitions from cohesive block-type failure to granular and turbulent flow – little to no infrasound is generated by the initial failure. At Iliamna, synthesis of advanced numerical flow models and more detailed ground observations combined with increased geophysical station coverage could yield significant gains in our understanding of these events.
","language":"English","publisher":"Copernicus","doi":"10.5194/esurf-9-271-2021","usgsCitation":"Toney, L., Fee, D., Allstadt, K.E., Haney, M.M., and Matoza, R.S., 2021, Reconstructing the dynamics of the highly similar May 2016 and June 2019 Iliamna Volcano, Alaska ice–rock avalanches from seismoacoustic data: Earth Surface Dynamics, v. 9, p. 271-293, https://doi.org/10.5194/esurf-9-271-2021.","productDescription":"23 p.","startPage":"271","endPage":"293","ipdsId":"IP-122705","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":452741,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/esurf-9-271-2021","text":"Publisher Index Page"},{"id":385003,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Iliamna Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -156.26953125,\n 59.712097173322924\n ],\n [\n -144.8876953125,\n 59.712097173322924\n ],\n [\n -144.8876953125,\n 63.31268278043484\n ],\n [\n -156.26953125,\n 63.31268278043484\n ],\n [\n -156.26953125,\n 59.712097173322924\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","noUsgsAuthors":false,"publicationDate":"2021-04-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Toney, Liam 0000-0003-0167-9433","orcid":"https://orcid.org/0000-0003-0167-9433","contributorId":257264,"corporation":false,"usgs":true,"family":"Toney","given":"Liam","email":"","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":813940,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fee, David","contributorId":251816,"corporation":false,"usgs":false,"family":"Fee","given":"David","affiliations":[{"id":6695,"text":"UAF","active":true,"usgs":false}],"preferred":false,"id":813941,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Allstadt, Kate E. 0000-0003-4977-5248","orcid":"https://orcid.org/0000-0003-4977-5248","contributorId":138704,"corporation":false,"usgs":true,"family":"Allstadt","given":"Kate","email":"","middleInitial":"E.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":813942,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haney, Matthew M. 0000-0003-3317-7884 mhaney@usgs.gov","orcid":"https://orcid.org/0000-0003-3317-7884","contributorId":172948,"corporation":false,"usgs":true,"family":"Haney","given":"Matthew","email":"mhaney@usgs.gov","middleInitial":"M.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":813943,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Matoza, Robin S.","contributorId":257265,"corporation":false,"usgs":false,"family":"Matoza","given":"Robin","email":"","middleInitial":"S.","affiliations":[{"id":36524,"text":"University of California, Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":813944,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70228373,"text":"70228373 - 2021 - Embracing ensemble species distribution models to inform at-risk species status assessments","interactions":[],"lastModifiedDate":"2022-02-09T17:03:42.769248","indexId":"70228373","displayToPublicDate":"2021-04-01T10:56:58","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Embracing ensemble species distribution models to inform at-risk species status assessments","docAbstract":"Conservation planning depends on reliable information regarding the geographic distribution of species. However, our knowledge of species' distributions is often incomplete, especially when species are cryptic, difficult to survey, or rare. The use of species distribution models has increased in recent years and proven a valuable tool to evaluate habitat suitability for species. However, practitioners have yet to fully adopt the potential of species distribution models to inform conservation efforts for information-limited species. Here, we describe a species distribution modeling approach for at-risk species that could better inform U.S. Fish and Wildlife Service's species status assessments and help facilitate conservation decisions. We applied four modeling techniques (generalized additive, maximum entropy, generalized boosted, and weighted ensemble) to occurrence data for four at-risk species proposed for listing under the U.S. Endangered Species Act (Papaipema eryngii, Macbridea caroliniana, Scutellaria ocmulgee, and Balduina atropurpurea) in the Southeastern United States. The use of ensemble models reduced uncertainty caused by differences among modeling techniques, with a consequent improvement of predictive accuracy of fitted models. Incorporating an ensemble modeling approach into species status assessments and similar frameworks is likely to benefit survey efforts, inform recovery activities, and provide more robust status assessments for at-risk species. We emphasize that co-producing species distribution models in close collaboration with species experts has the potential to provide better calibration data and model refinements, which could ultimately improve reliance and use of model outputs.
","language":"English","publisher":"U.S. Fish and Wildlife Service","doi":"10.3996/JFWM-20-072","usgsCitation":"Ramirez-Reyes, C., Nazeri, M., Street, G., Jones-Ferrand, D.T., Vilella, F., and Evans, K.O., 2021, Embracing ensemble species distribution models to inform at-risk species status assessments: Journal of Fish and Wildlife Management, v. 12, no. 1, p. 98-111, https://doi.org/10.3996/JFWM-20-072.","productDescription":"14 p.","startPage":"98","endPage":"111","ipdsId":"IP-114759","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":452828,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/jfwm-20-072","text":"Publisher Index Page"},{"id":395684,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas, Florida, Georgia, Missouri, North Carolina, South Carolina","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.01074218749999,\n 33.063924198120645\n ],\n [\n -90.87890625,\n 34.125447565116126\n ],\n [\n -89.7802734375,\n 35.817813158696616\n ],\n [\n -89.3408203125,\n 36.80928470205937\n ],\n [\n -90.2197265625,\n 38.41055825094609\n ],\n [\n -90.2197265625,\n 38.89103282648846\n ],\n [\n -91.58203125,\n 40.38002840251183\n ],\n [\n -91.8017578125,\n 40.713955826286046\n ],\n [\n -95.9326171875,\n 40.613952441166596\n ],\n [\n -94.74609375,\n 39.33429742980725\n ],\n [\n -94.74609375,\n 37.92686760148135\n ],\n [\n -94.6142578125,\n 36.24427318493909\n ],\n [\n -94.658203125,\n 33.7243396617476\n ],\n [\n -93.8232421875,\n 33.247875947924385\n ],\n [\n -93.7353515625,\n 33.02708758002874\n ],\n [\n -91.01074218749999,\n 33.063924198120645\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.9375,\n 36.27970720524017\n ],\n [\n -81.7822265625,\n 36.4566360115962\n ],\n [\n -83.4521484375,\n 35.35321610123823\n ],\n [\n -83.5400390625,\n 34.92197103616377\n ],\n [\n -85.69335937499999,\n 34.95799531086792\n ],\n [\n -85.1220703125,\n 31.015278981711266\n ],\n [\n -86.66015624999999,\n 30.90222470517144\n ],\n [\n -86.30859375,\n 30.486550842588485\n ],\n [\n -85.1220703125,\n 29.649868677972304\n ],\n [\n -83.5400390625,\n 29.6880527498568\n ],\n [\n -82.6611328125,\n 27.644606381943326\n ],\n [\n -80.9033203125,\n 29.726222319395504\n ],\n [\n -81.2548828125,\n 31.42866311735861\n ],\n [\n -78.837890625,\n 33.32134852669881\n ],\n [\n -76.11328125,\n 34.59704151614417\n ],\n [\n -75.2783203125,\n 35.92464453144099\n ],\n [\n -75.9375,\n 36.27970720524017\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-04-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Ramirez-Reyes, C.","contributorId":275333,"corporation":false,"usgs":false,"family":"Ramirez-Reyes","given":"C.","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":834005,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nazeri, M.","contributorId":275334,"corporation":false,"usgs":false,"family":"Nazeri","given":"M.","email":"","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":834006,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Street, Garrett","contributorId":275335,"corporation":false,"usgs":false,"family":"Street","given":"Garrett","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":834007,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jones-Ferrand, D. T.","contributorId":275336,"corporation":false,"usgs":false,"family":"Jones-Ferrand","given":"D.","email":"","middleInitial":"T.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":834008,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vilella, Francisco 0000-0003-1552-9989 fvilella@usgs.gov","orcid":"https://orcid.org/0000-0003-1552-9989","contributorId":171363,"corporation":false,"usgs":true,"family":"Vilella","given":"Francisco","email":"fvilella@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":834009,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Evans, K. O.","contributorId":275337,"corporation":false,"usgs":false,"family":"Evans","given":"K.","email":"","middleInitial":"O.","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":834010,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70219585,"text":"70219585 - 2021 - Predicting the spatiotemporal exposure of aquatic species to intrusions of fire retardant in streams with limited data","interactions":[],"lastModifiedDate":"2021-04-15T12:51:24.287992","indexId":"70219585","displayToPublicDate":"2021-04-01T07:50:06","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":"Predicting the spatiotemporal exposure of aquatic species to intrusions of fire retardant in streams with limited data","docAbstract":"Because fire retardant can enter streams and harm aquatic species including endangered fish, agencies such as the U.S. Forest Service (USFS) must estimate the downstream extent of toxic effects every time fire retardant enters streams (denoted as an “intrusion”). A challenge in estimating the length of stream affected by the intrusion and the exposure time of species in the affected reach is the lack of data typically available on the stream's geometry and flow characteristics. Previously, the USFS estimated the affected reach length assuming instantaneous mixing of the retardant over the reach; however, this approach neglects key river mixing processes. An approach is described that accounts for advection and dispersion of the retardant as well as the downstream growth of the stream. Applied to 13 intrusions documented by the USFS, the new approach shows affected reach lengths range between 8.0 and 362 km; all 13 cases exceeded previous estimates from an instantaneous mixing model. The time that a stationary individual in the affected reach is exposed to concentrations above a pre-defined toxicity threshold (10% of 96-hour LC50, for example) ranges from 0.17 to 2.73 h, with all but one case having a maximum exposure time less than 1.5 h. Results from 1152 hypothetical intrusions provided by the USFS confirm that exposure times rarely exceed 5 h. This result suggests that 96-hour tests to determine toxicity (LC50) to various species should be reconsidered. Although the approach described can be improved in several ways, it provides a first estimate of the effects of fire retardant intrusions.
Investigators rely on brood surveys to estimate annual fecundity of game birds. However, investigators often do not account for factors that influence brood detection probability nor rarely document how much females and their broods are disturbed (flush rates) during surveys, which could lead to biased survival estimates. We used 45 radio-tagged female Greater Sage-Grouse (Centrocercus urophasianus) with broods to compare detection probabilities and document disturbance among four survey methods to allow future investigators to select the method that best meets their objectives. These methods included daytime flush, daytime visual, nocturnal spotlight, and fecal surveys at nocturnal roost sites, with the latter being a novel method. We used Cormack–Jolly–Seber (CJS) models to compare detection probability and daily survival estimates for visual and fecal surveys of broods 0–47 d post-hatch and a double-survey approach to compare detection probabilities among flush, fecal, and spotlight surveys ~42 d post-hatch when investigators often determine brood fate. From CJS models, detection probability for visual surveys increased with brood age (0.618–0.881), whereas detection probability for fecal surveys did not (0.748). Daily survival probability estimates increased with brood age and differed annually based on fecal surveys (2016: 0.978–1.000 and 2017: 0.839–0.998). We detected age-specific daily survival probability with visual surveys (0.956–0.997), but not annual differences. Based on the double-survey approach, detection probability was high (0.857–1.000) for all methods. We flushed ~310–750% fewer females and broods during fecal and spotlight surveys than during both types of daytime surveys. Our results highlight the need to account for detection probabilities among methods and document disturbance to hens and broods that can help investigators design surveys to minimize impacts to birds. Furthermore, our result suggest that actions to improve brood survival during the first week post-hatch may improve local recruitment.
Incorporating spatial and temporal scales into greater sage-grouse (Centrocercus urophasianus) population monitoring strategies is challenging and rarely implemented. Sage-grouse populations experience fluctuations in abundance that lead to temporal oscillations, making trend estimation difficult. Accounting for stochasticity is critical to reliably estimate population trends and investigate variation related to deterministic factors on the landscape, which are amenable to management action. Here, we describe a novel, range-wide hierarchical monitoring framework for sage-grouse centered on four objectives: (1) create a standardized database of lek counts, (2) develop spatial population structures by clustering leks, (3) estimate spatial trends at different temporal extents based on abundance nadirs (troughs), and (4) develop a targeted annual warning system to help inform management decisions. Using automated and repeatable methods (software), we compiled a lek database (as of 2019) that contained 262,744 counts and 8,421 unique lek locations from disparate state data. The hierarchical population units (clusters) included 13 nested levels, identifying biologically relevant units and population structure that minimized inter-cluster sage-grouse movements. With these products, we identified spatiotemporal variation in trends in population abundance using Bayesian state-space models. We estimated 37.0, 65.2, and 80.7-percent declines in abundance range-wide during short (17 years), medium (33 years), and long (53 years) temporal scales, respectively. However, some areas exhibited evidence of increasing trends in abundance in recent decades. Models predicted 12.3, 19.2, and 29.6 percent of populations (defined as clusters of neighboring leks) consisted of over 50-percent probability of extirpation at 19, 38, and 56-year projections from 2019, respectively, based on averaged annual rate of change in apparent abundance across two, four, and six oscillations (average period of oscillation is 9.4 years). At the lek level, models predicted 45.7, 60.1, and 78.0 percent of leks with over 50-percent extirpation probabilities over the same time periods, respectively, mostly located on the periphery of the species’ range. The targeted annual warning system automates annual identification of local populations exhibiting asynchronous decline relative to regional population patterns using simulated management actions and an optimization algorithm for evaluating range-wide stabilization of population abundance. In 2019, approximately 3.2 percent of leks and 2.0 percent of populations were identified by the targeted annual warning system for management intervention range-wide.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201154","collaboration":"Prepared in cooperation with the Western Association of Fish and Wildlife Agencies and the Bureau of Land Management","usgsCitation":"Coates, P.S., Prochazka, B.G., O’Donnell, M.S., Aldridge, C.L., Edmunds, D.R., Monroe, A.P., Ricca, M.A., Wann, G.T., Hanser, S.E., Wiechman, L.A., and Chenaille, M.P., 2021, Range-wide greater sage-grouse hierarchical monitoring framework—Implications for defining population boundaries, trend estimation, and a targeted annual warning system: U.S. Geological Survey Open-File Report 2020–1154, 243 p., https://doi.org/10.3133/ofr20201154.","productDescription":"Report: vi, 243 p.; 1 Table","numberOfPages":"243","onlineOnly":"Y","ipdsId":"IP-123421","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":384766,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2020/1154/ofr20201154_table8.csv","text":"Table 8","size":"80 KB","linkFileType":{"id":7,"text":"csv"}},{"id":384765,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2020/1154/ofr20201154_table8.xlsx","text":"Table 8","size":"60 KB","linkFileType":{"id":3,"text":"xlsx"}},{"id":384760,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1154/ofr20201154.pdf","text":"Report","size":"310 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":384759,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1154/covrthb.jpg"}],"country":"United States","state":"California, Colorado, Idaho, Montana, Nevada, North Dakota, Oregon, South Dakota, Utah, Washington, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.32226562500001,\n 35.67514743608467\n ],\n [\n -103.447265625,\n 35.67514743608467\n ],\n [\n -103.447265625,\n 48.69096039092549\n ],\n [\n -120.32226562500001,\n 48.69096039092549\n ],\n [\n -120.32226562500001,\n 35.67514743608467\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
Commercial forest plantations of fast-growing species have been established globally to meet increasing demands for timber, pulpwood, and other wood products. Industrial plantations may contribute to tropical forest conservation by reducing exploitation of primary and secondary natural forests. Whether such plantations can support critical elements of biodiversity, including provision of habitat and movement corridors for species of conservation concern, is an important question in Southeast Asia. Our objectives were to investigate relationships between habitat gradients and community attributes of medium-sized to large mammals in a mixed plantation mosaic in Bengkoka Peninsula, Sabah, East Malaysia. Data on mammals were collected using 59 remote camera stations deployed for a minimum of 21 days (24-hour sampling occasions) in three major land-use types: natural forest, Acacia plantations, and non-Acacia plantations (oil palm, rubber, young Eucalyptus pellita). We used sample-based rarefaction to evaluate variation in species richness with land use. We used generalized linear models and ordination analyses to evaluate whether variation in mammal detections and species composition was associated with habitat gradients. We recorded >22 mammal species over 1572 sampling occasions. Natural forest area was positively associated with mammal species richness and detections of threatened mammals. Overall detections of mammals increased with decreasing elevation, but decreased within, and close to, Acacia plantations. Detections of threatened mammals increased with greater proportions of natural forest and Acacia and increasing proximity to roads. Sample-based rarefaction indicated that species richness of mammals in Acacia and natural forest was considerably higher than observed. Both natural forest and Acacia plantations shared similar values for species richness and diversity, but non-Acacia plantations scored lower in both metrics. Mammal species composition differed among different types of land use. Smaller generalists used non-Acacia plantation forests. A variety of other mammals including some threatened species used natural forest, Acacia, or a combination of the two. Acacia plantations possess attributes supporting a diversity of mammal species, including those we defined as threatened based on IUCN criteria. However, this is likely a function of the habitat mosaic with natural forest in the study area and the mangrove forests on the fringes of the peninsula serving as refuges of mammal diversity. Retention and restoration of natural and mangrove forests may therefore enhance the conservation potential of industrial Acacia plantations. Additionally, controlled road access in conjunction with anti-poaching operations and strengthening public awareness are essential to reduce the threat of overexploitation.
A key assumption in species distribution modeling (SDM) with presence‐background (PB) methods is that sampling of occurrence localities is unbiased and that any sampling bias is proportional to the background distribution of environmental covariates. This assumption is rarely met when SDM practitioners rely on federated museum records from natural history collections for geo‐located occurrences due to inherent sampling bias found in these collections. We use a simulation approach to explore the effectiveness of three methods developed to account for sampling bias in SDM with PB frameworks. Two of the methods rely on careful filtering of observation data—geographic thinning (G‐Filter) and environmental thinning (E‐Filter)—while a third, FactorBiasOut, creates selection weights for background data to bias locations toward areas where the observation dataset was sampled. While these methods have been assessed previously, evaluation has emphasized spatial predictions of habitat potential. Here, we dig deeper into the effectiveness of these methods by exploring how sampling bias not only affects predictions of habitat potential, but also our understanding of niche characteristics such as which explanatory variables and response curves best represent species–environment relationships. We simulate 100 virtual species ranging from generalist to specialist in their habitat preferences and introduce geographic and environmental bias at three intensity levels to measure the effectiveness of each correction method to (1) predict true probability of occurrence across a study area, (2) recover true species–environment relationships, and (3) identify true explanatory variables. We find that the FactorBiasOut most often showed the greatest improvement in recreating known distributions but did no better at correctly identifying environmental covariates or recreating species–environment relationships than G‐Filter or E‐Filter methods. Narrow niche species are most problematic for biased calibration datasets, such that correction methods can, in some cases, make predictions worse.
A multi-component geochemical dataset was collected from groundwater and surface-water bodies associated with the urban Fountain Creek alluvial aquifer, Colorado, USA, to facilitate analysis of recharge sources, geochemical interactions, and groundwater-residence times. Results indicate that groundwater can be separated into three distinct geochemical zones based on location within the flow system and proximity to surface water, and these zones can be used to infer sources of recharge and groundwater movement through the aquifer. Rare-earth-element concentrations and detections of wastewater-indicator compounds indicate the presence of effluent from wastewater-treatment plants in both groundwater and surface water. Effluent presence in groundwater indicates that streams in the area lose to groundwater in some seasons and are a source of focused groundwater recharge. Distributions of pharmaceuticals and wastewater-indicator compounds also inform an understanding of groundwater–surface-water interactions. Noble-gas isotopes corroborate rare-earth-element data in indicating geochemical evolution within the aquifer from recharge area to discharge area and qualitatively indicate variable groundwater-residence times and mixing with pre-modern groundwater. Quantitative groundwater-residence times calculated from 3H/3He, SF6, and lumped-parameter modeling generally are less than 20 years, but the presence of mixing with older groundwater of an unknown age is also indicated at selected locations. Future investigations would benefit by including groundwater-age tracers suited to quantification of mixing for both young (years to decades) and old (centuries and millennia) groundwater. This multi-faceted analysis facilitated development of a conceptual model for the investigated groundwater-flow system and illustrates the application of an encompassing suite of analytes in exploring hydrologic and geochemical interactions in complex systems.
","language":"English","publisher":"MDPI","doi":"10.3390/w13060871","usgsCitation":"Newman, C.P., Paschke, S.S., and Keith, G.L., 2021, Natural and anthropogenic geochemical tracers to investigate residence times and groundwater–surface-water interactions in an urban alluvial aquifer: Water, v. 13, no. 6, 30 p., https://doi.org/10.3390/w13060871.","productDescription":"30 p.","ipdsId":"IP-118155","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":452974,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w13060871","text":"Publisher Index Page"},{"id":436443,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P99SPQM2","text":"USGS data release","linkHelpText":"Environmental-tracer modeling to support hydrogeochemical evaluation of the Fountain Creek Alluvial Aquifer, El Paso County, Colorado, 2018-2019"},{"id":384712,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","city":"Colorado Springs","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.2490234375,\n 38.61687046392973\n ],\n [\n -104.1888427734375,\n 38.61687046392973\n ],\n [\n -104.1888427734375,\n 39.16839998800286\n ],\n [\n -105.2490234375,\n 39.16839998800286\n ],\n [\n -105.2490234375,\n 38.61687046392973\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-03-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Newman, Connor P. 0000-0002-6978-3440","orcid":"https://orcid.org/0000-0002-6978-3440","contributorId":222596,"corporation":false,"usgs":true,"family":"Newman","given":"Connor","email":"","middleInitial":"P.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":813075,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Paschke, Suzanne S. 0000-0002-3471-4242 spaschke@usgs.gov","orcid":"https://orcid.org/0000-0002-3471-4242","contributorId":1347,"corporation":false,"usgs":true,"family":"Paschke","given":"Suzanne","email":"spaschke@usgs.gov","middleInitial":"S.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":813076,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Keith, Gabrielle L. 0000-0002-2304-8504 gkeith@usgs.gov","orcid":"https://orcid.org/0000-0002-2304-8504","contributorId":256699,"corporation":false,"usgs":true,"family":"Keith","given":"Gabrielle","email":"gkeith@usgs.gov","middleInitial":"L.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":813077,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}