Aim
Biogeography seeks to identify and explain the spatial distributions of species and has become an important tool used by conservationists to protect and manage aquatic organisms. Texas, located in the southwestern United States, is home to 52 species of freshwater mussels, 9 of which are endemic to Texas and 7 that are endemic to Texas and neighboring states or countries. There have been two major attempts to classify this fauna into biogeographical provinces; however, both efforts relied on limited distribution information and outdated taxonomy. To address both issues, we set out to delineate biogeographic provinces for freshwater mussels in Texas by using a comprehensive distributional dataset of >28,000 records and molecular information.
Location
Southwestern United States.
Methods
We compiled community and molecular data for 48 of the 52 freshwater mussel species that occur in Texas. We performed algorithmic hierarchal cluster analysis (HCA) and nonmetric multidimensional scaling (NMDS) based on Euclidean distance to identify biogeographic groupings. We conducted a similar analysis using molecular sequence data for our target species.
Results
Based on the results from community and molecular data, we identified seven biogeographic provinces for freshwater mussels in Texas: Great Plains, Mississippi Embayment, Sabine-Neches, Trinity-San Jacinto, Central Texas, Rio Grande and Coastal. However, the Coastal and Great Plains provinces were not included in our analysis and were recognized based on previous work.
Main conclusions
Our approach integrating community and molecular datasets provides a comprehensive assessment of the biogeography of freshwater mussels in Texas, which serves as a model for future biogeographic studies. Our findings also shed light on the ecological, evolutionary and geologic processes shaping freshwater mussel communities in Texas, which is important for the conservation of remaining biodiversity in the state.
","language":"English","publisher":"John Wiley & Sons, Inc.","doi":"10.1111/ddi.13555","usgsCitation":"de Moulpied, M., Smith, C.H., Robertson, C.R., Johnson, N., Lopez, R., and Randklev, C.R., 2022, Biogeography of freshwater mussels (Bivalvia: Unionida) in Texas and implications on conservation biology: Diversity and Distributions, v. 28, no. 7, p. 1458-1474, https://doi.org/10.1111/ddi.13555.","productDescription":"17 p.","startPage":"1458","endPage":"1474","ipdsId":"IP-132849","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":447553,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ddi.13555","text":"Publisher Index Page"},{"id":401680,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"28","issue":"7","noUsgsAuthors":false,"publicationDate":"2022-05-30","publicationStatus":"PW","contributors":{"authors":[{"text":"de Moulpied, Michael 0000-0002-4007-7550","orcid":"https://orcid.org/0000-0002-4007-7550","contributorId":292219,"corporation":false,"usgs":false,"family":"de Moulpied","given":"Michael","email":"","affiliations":[{"id":36313,"text":"Texas A&M","active":true,"usgs":false}],"preferred":false,"id":844093,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Chase H. 0000-0002-1499-0311","orcid":"https://orcid.org/0000-0002-1499-0311","contributorId":225140,"corporation":false,"usgs":false,"family":"Smith","given":"Chase","email":"","middleInitial":"H.","affiliations":[{"id":13716,"text":"Baylor University","active":true,"usgs":false}],"preferred":false,"id":844094,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Robertson, Clint R.","contributorId":292221,"corporation":false,"usgs":false,"family":"Robertson","given":"Clint","email":"","middleInitial":"R.","affiliations":[{"id":27442,"text":"Texas parks and Wildlife Department","active":true,"usgs":false}],"preferred":false,"id":844095,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Nathan 0000-0001-5167-1988","orcid":"https://orcid.org/0000-0001-5167-1988","contributorId":210319,"corporation":false,"usgs":true,"family":"Johnson","given":"Nathan","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":844096,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lopez, Roel","contributorId":206218,"corporation":false,"usgs":false,"family":"Lopez","given":"Roel","affiliations":[{"id":36313,"text":"Texas A&M","active":true,"usgs":false}],"preferred":false,"id":844097,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Randklev, Charles R.","contributorId":202530,"corporation":false,"usgs":false,"family":"Randklev","given":"Charles","email":"","middleInitial":"R.","affiliations":[{"id":36313,"text":"Texas A&M","active":true,"usgs":false}],"preferred":false,"id":844098,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70231907,"text":"70231907 - 2022 - Structured decision making to rank North American Wetland Conservation Act proposals within joint venture regions","interactions":[],"lastModifiedDate":"2023-01-18T15:51:07.526101","indexId":"70231907","displayToPublicDate":"2022-06-03T08:32:14","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Structured decision making to rank North American Wetland Conservation Act proposals within joint venture regions","docAbstract":"The North American Wetlands Conservation Act (16 U.S.C. 4401-4412) provided funding and administration for wetland management and conservation projects. The North American Wetland Conservation Fund, enabled in 1989 with the Act, provides financial resources. Resource allocation decisions are based, in part, on regional experts, particularly migratory bird Joint Ventures (JVs) (i.e., partnerships for cooperative planning and coordinated management of the continent’s waterfowl populations and habitats). The JVs evaluate funding proposals submitted with their respective regions each year and make funding recommendations to decision makers. Proposal evaluation procedures differ among JVs, however, it could be helpful to consider a transparent, repeatable, and data-driven framework for prioritization within regions. We used structured decision making and linear additive value models for ranking proposals within JV regions. We used two JVs as case studies and constructed two different value models using JV-specific objectives and weights. The framework was developed through a collaborative process with JV staff and stakeholders. Models were written in Microsoft Excel. To test these models, we used six NAWCA proposals submitted to the Upper Mississippi / Great Lakes Joint Venture in 2016 and seven proposals submitted to the Gulf Coast Joint Venture in 2017. We compared proposal ranks assigned by the value model to ranks assigned by each JV’s management board. Ranks assigned by the value model differed from ranks assigned by the board for the Upper Mississippi / Great Lakes Joint Venture, but not for the Gulf Coast Joint Venture. However, ranks from the value model could change markedly with different objective weights and value functions. The weighted linear value model was beneficial for ranking NAWCA proposals because it allows JVs to treat the ranking as a multiple objective problem and tailor the ranking to their specific regional concerns. We believe a structured decision making approach could be adapted by JV staff to facilitate a systematic and transparent process for proposal ranking by their management boards.
","language":"English","publisher":"U. S. 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J.","contributorId":172329,"corporation":false,"usgs":false,"family":"Soulliere","given":"Gregory","email":"","middleInitial":"J.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":844087,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Coluccy, John M.","contributorId":111382,"corporation":false,"usgs":true,"family":"Coluccy","given":"John","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":844088,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wilson, Barry C.","contributorId":12968,"corporation":false,"usgs":true,"family":"Wilson","given":"Barry","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":844089,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brasher, Michael G.","contributorId":214393,"corporation":false,"usgs":false,"family":"Brasher","given":"Michael","email":"","middleInitial":"G.","affiliations":[{"id":36215,"text":"Ducks Unlimited","active":true,"usgs":false}],"preferred":false,"id":844090,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Al-Saffar, Mohammed A","contributorId":292215,"corporation":false,"usgs":false,"family":"Al-Saffar","given":"Mohammed","email":"","middleInitial":"A","affiliations":[{"id":62842,"text":"USWFS","active":true,"usgs":false}],"preferred":false,"id":844091,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Humburg, Dale D.","contributorId":79357,"corporation":false,"usgs":false,"family":"Humburg","given":"Dale","email":"","middleInitial":"D.","affiliations":[{"id":13073,"text":"Ducks Unlimited, Inc.","active":true,"usgs":false}],"preferred":false,"id":844092,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70231934,"text":"70231934 - 2022 - Can coastal habitats rise to the challenge? Resilience of estuarine habitats, carbon accumulation, and economic value to sea-level rise in a Puget Sound estuary","interactions":[],"lastModifiedDate":"2022-10-31T14:24:53.776047","indexId":"70231934","displayToPublicDate":"2022-06-03T08:09:47","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"Can coastal habitats rise to the challenge? Resilience of estuarine habitats, carbon accumulation, and economic value to sea-level rise in a Puget Sound estuary","docAbstract":"Sea-level rise (SLR) and obstructions to sediment delivery pose challenges to the persistence of estuarine habitats and the ecosystem services they provide. Restoration actions and sediment management strategies may help mitigate such challenges by encouraging the vertical accretion of sediment in and horizontal migration of tidal forests and marshes. We used a process-based soil accretion model (Coastal Wetland Equilibrium Model) combined with a habitat classification model (MOSAICS) to estimate the effects of SLR, suspended sediment, and inland habitat migration on estuarine habitats, soil carbon accumulation, and economic value of climate change mitigation of carbon accumulation (social cost of carbon dioxide) in a macrotidal estuary in the northwest USA over 100 years (2011 to 2110). Under present-day sediment levels, we projected that after 100 years, most high salt marsh would remain with < 100 cm SLR, but substantial area converted to transitional (low) salt marsh and mudflat with ≥ 100 cm SLR. Increasing sediment availability increased the projected resilience of transitional salt marsh to SLR but did not prevent declines in high marsh area. Projected total carbon accumulation plateaued or declined with ≥ 100 cm SLR, yet the economic value of carbon accumulation continued to rise over time, suggesting that the value of this ecosystem service was resilient to SLR. Doubling or tripling sediment availability increased projected carbon accumulation up to 7.69 and 14.2 kg m−2 and increased total economic value up to $373,000 and $710,000, respectively. Allowing marsh migration supported conversion of upland to freshwater marsh, with slight increases in carbon accumulation. These results inform climate adaptation planning for wetland managers seeking to understand the resilience of estuarine habitats and ecosystem services to SLR under multiple management strategies.
","language":"English","publisher":"Springer","doi":"10.1007/s12237-022-01087-5","usgsCitation":"Moritsch, M.M., Byrd, K.B., Davis, M.J., Good, A.J., Drexler, J.Z., Morris, J.T., Woo, I., Windham-Myers, L., Grossman, E.E., Nakai, G., Poppe, K.L., and Rybczyk, J.M., 2022, Can coastal habitats rise to the challenge? Resilience of estuarine habitats, carbon accumulation, and economic value to sea-level rise in a Puget Sound estuary: Estuaries and Coasts, v. 45, p. 2293-2309, https://doi.org/10.1007/s12237-022-01087-5.","productDescription":"17 p.","startPage":"2293","endPage":"2309","ipdsId":"IP-134918","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":447559,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s12237-022-01087-5","text":"Publisher Index Page"},{"id":435828,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ONIUCK","text":"USGS data release","linkHelpText":"Projected future habitat, elevation change, and carbon accumulation of coastal wetlands in the Nisqually River Delta, Washington"},{"id":401676,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Nisqually River Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.72981643676756,\n 47.05269803965603\n ],\n [\n -122.67969131469727,\n 47.05515408550348\n ],\n [\n -122.68999099731445,\n 47.06521099790879\n ],\n [\n -122.6905059814453,\n 47.07526601334617\n ],\n [\n -122.67539978027342,\n 47.089760603235646\n ],\n [\n -122.67127990722655,\n 47.1067049202684\n ],\n [\n -122.7366828918457,\n 47.10647124222482\n ],\n [\n -122.7385711669922,\n 47.10647124222482\n ],\n [\n -122.7389144897461,\n 47.07175866526645\n ],\n [\n -122.7344512939453,\n 47.06684799015446\n ],\n [\n -122.72981643676756,\n 47.05269803965603\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"45","noUsgsAuthors":false,"publicationDate":"2022-05-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Moritsch, Monica Mei Jeen 0000-0002-3890-1264","orcid":"https://orcid.org/0000-0002-3890-1264","contributorId":225210,"corporation":false,"usgs":true,"family":"Moritsch","given":"Monica","email":"","middleInitial":"Mei Jeen","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":844144,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Byrd, Kristin B. 0000-0002-5725-7486 kbyrd@usgs.gov","orcid":"https://orcid.org/0000-0002-5725-7486","contributorId":3814,"corporation":false,"usgs":true,"family":"Byrd","given":"Kristin","email":"kbyrd@usgs.gov","middleInitial":"B.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":844145,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Davis, Melanie J. 0000-0003-1734-7177","orcid":"https://orcid.org/0000-0003-1734-7177","contributorId":202773,"corporation":false,"usgs":true,"family":"Davis","given":"Melanie","email":"","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":844146,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Good, Anthony J. 0000-0002-0276-136X","orcid":"https://orcid.org/0000-0002-0276-136X","contributorId":203553,"corporation":false,"usgs":true,"family":"Good","given":"Anthony","email":"","middleInitial":"J.","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":true,"id":844147,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Drexler, Judith Z. 0000-0002-0127-3866 jdrexler@usgs.gov","orcid":"https://orcid.org/0000-0002-0127-3866","contributorId":167492,"corporation":false,"usgs":true,"family":"Drexler","given":"Judith","email":"jdrexler@usgs.gov","middleInitial":"Z.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":844148,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Morris, James T.","contributorId":29118,"corporation":false,"usgs":true,"family":"Morris","given":"James","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":844149,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Woo, Isa 0000-0002-8447-9236 iwoo@usgs.gov","orcid":"https://orcid.org/0000-0002-8447-9236","contributorId":2524,"corporation":false,"usgs":true,"family":"Woo","given":"Isa","email":"iwoo@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":844150,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Windham-Myers, Lisamarie 0000-0003-0281-9581 lwindham-myers@usgs.gov","orcid":"https://orcid.org/0000-0003-0281-9581","contributorId":2449,"corporation":false,"usgs":true,"family":"Windham-Myers","given":"Lisamarie","email":"lwindham-myers@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":844151,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Grossman, Eric E. 0000-0003-0269-6307 egrossman@usgs.gov","orcid":"https://orcid.org/0000-0003-0269-6307","contributorId":196610,"corporation":false,"usgs":true,"family":"Grossman","given":"Eric","email":"egrossman@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":844152,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Nakai, Glynnis","contributorId":172123,"corporation":false,"usgs":false,"family":"Nakai","given":"Glynnis","email":"","affiliations":[{"id":26986,"text":"US Fish and Wildlife Service, Nisqually Nat'l Wildlife Refuge, Olympia, WA","active":true,"usgs":false}],"preferred":false,"id":844153,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Poppe, Katrina L. 0000-0003-2830-4578","orcid":"https://orcid.org/0000-0003-2830-4578","contributorId":292257,"corporation":false,"usgs":false,"family":"Poppe","given":"Katrina","email":"","middleInitial":"L.","affiliations":[{"id":62851,"text":"Western Washington University, Department of Environmental Sciences","active":true,"usgs":false}],"preferred":false,"id":844154,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Rybczyk, John M.","contributorId":89794,"corporation":false,"usgs":true,"family":"Rybczyk","given":"John","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":844155,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70231846,"text":"sir20215113 - 2022 - Long-term groundwater availability in the Waihe‘e, ‘Īao, and Waikapū aquifer systems, Maui, Hawai‘i","interactions":[],"lastModifiedDate":"2026-04-02T19:46:57.445783","indexId":"sir20215113","displayToPublicDate":"2022-06-03T08:07:20","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5113","displayTitle":"Long-Term Groundwater Availability in the Waihe‘e, ‘Īao, and Waikapū Aquifer Systems, Maui, Hawai‘i","title":"Long-term groundwater availability in the Waihe‘e, ‘Īao, and Waikapū aquifer systems, Maui, Hawai‘i","docAbstract":"Groundwater levels have declined since the 1940s in the Wailuku area of central Maui, Hawai‘i, on the eastern flank of West Maui volcano, mainly in response to increased groundwater withdrawals. Available data since the 1980s also indicate a thinning of the freshwater lens and an increase in chloride concentrations of pumped water from production wells. These trends, combined with projected increases in demand for groundwater in central Maui, have led to concerns over groundwater availability and have highlighted a need to improve general understanding of the hydrologic effects of proposed groundwater withdrawals in the Waihe‘e, ‘Īao, and Waikapū areas of central Maui.
A numerical groundwater model was constructed to simulate the flow and salinity of groundwater in central Maui. The model simulates the effects of changes in groundwater withdrawals and recharge on water levels, freshwater-lens thicknesses, and chloride concentrations of pumped water from production wells. The model incorporates updated water-budget estimates of groundwater recharge from infiltration and direct recharge, seepage in stream channels, and inflow from inland areas. Mean annual groundwater recharge from infiltration and direct recharge was estimated using a daily water-budget model and the most current data, including the distributions of monthly rainfall and potential evapotranspiration, for the study area for nine historical periods from 1926 through 2012: 1926–69, 1970–79, 1980–84, 1985–89, 1990–94, 1995–99, 2000–04, 2005–09, and 2010–12. The water-budget model also estimated groundwater recharge based on one hypothetical scenario that used 1980–2010 rainfall and 2017 land cover. For the nine historical periods, estimated recharge from infiltration and direct recharge within the area of the groundwater model ranged from 30.4 million gallons per day (Mgal/d) during 2010–12 to 98.7 Mgal/d during 1926–69. Variability in recharge during these periods mainly reflects changes in rainfall and irrigation over time. Between 2010 and 2014, streamflow restoration in previously diverted streams resulted in an estimated increase in recharge from seepage in stream channels of about 12.5 Mgal/d. Average groundwater inflow of about 39.6 Mgal/d from inland, dike-intruded areas to the main area of interest was estimated from an existing island-wide numerical groundwater-flow model, which is at a larger scale and incorporates a greater number of simplifying assumptions.
The numerical groundwater model developed for this study was calibrated to 1926–2012 transient water levels, vertical salinity profiles, and chloride concentrations of water pumped by production wells in the study area. The model was then used to evaluate one future recharge and six selected withdrawal scenarios, developed in consultation with the Maui Department of Water Supply, in terms of long-term changes in water level and 50-percent ocean-water salinity surface. The groundwater model was also used to simulate the future salinity of water withdrawn by existing and proposed production wells. The simulations were run to steady-state conditions, providing an estimate of the long-term effects of changes in withdrawal and recharge on the groundwater resource. Results of the simulated future withdrawal scenarios indicate that, relative to 2017–18 rates, the scenarios’ long-term effect of increased withdrawals ultimately leads to lower water levels and a higher 50-percent ocean-water salinity surface indicating a thinning of the freshwater lens. Results also indicate that the increased withdrawals produce some groundwater with chloride concentration below 250 milligrams per liter and some groundwater with higher chloride concentration. The amount of drawdown near production wells and the quality of water withdrawn from production wells is dependent on the rate and spatial distribution of the withdrawals.
The model was also used to evaluate how groundwater availability may be affected for a drier recharge scenario based on a published study of future climate. Model results of the future recharge scenario indicate that the rate of groundwater recharge is a controlling factor for (1) water levels, (2) the 50-percent ocean-water salinity surface, and (3) the quality of water withdrawn from production wells in the Wailuku area. Coupled with reduced groundwater recharge (with all other factors remaining equal), the modeled future withdrawals in the scenario would tend to cause lower water levels, a higher 50-percent ocean-water salinity surface, and increased salinity of water withdrawn from production wells.
The three-dimensional numerical groundwater model developed for this study utilizes the latest available hydrologic and geologic information and is a useful tool for understanding the long-term hydrologic effects of additional groundwater withdrawals in central Maui. The model has several limitations, including its non-uniqueness and inability to account for local-scale heterogeneities. Short-term effects of changes in recharge and withdrawals—and optimization of pumping rates to meet increased demand for water with acceptable salinity—are possible conditions for future simulation analyses.
Director,
Pacific Islands Water Science Center
U.S. Geological Survey
Inouye Regional Center
1845 Wasp Blvd., B176
Honolulu, HI 96818
Successful migration of Chinook Salmon (Oncorhynchus tshawytscha) smolts seaward in the Sacramento – San Joaquin River Delta (hereafter, Delta) requires navigating a network of numerous branching channels. Within the Delta, several key junctions route smolts either towards more direct paths to the ocean or towards the interior Delta, an area associated with decreased survival. Movements within these junctions that determine route choice can be influenced by numerous behavioral and environmental factors, including the complex interplay between tidal and riverine hydraulics. Here, we apply continuous time multistate Markov models to examine the influence of tidal and riverine hydraulics, behavioral factors, and management actions on smolt movements. These models incorporate more information from acoustic telemetry data compared with previous approaches to modeling smolt movements in the Delta. By decomposing modeled flows into tidal and net flow signals we elucidate how each component influences movements into and out of distributary channels. Increasing net flows generally increased movement rates, while flood tides decreased seaward movement rates. Similarly, ebb tides increased downstream movements as fish go with the flow. We found less support for diel movement behaviors compared to flow metrics. Additionally, we quantify the effects of a large management action, the placement of a physical barrier, which was effective at decreasing entrainment into the interior Delta. Together, these results help inform management of Chinook Salmon and increase our understanding of the major factors driving smolt movements within these key junctions.
","language":"English","publisher":"Springer","doi":"10.1007/s10641-022-01273-1","usgsCitation":"Dodrill, M., Perry, R., Pope, A., and Wang, X., 2022, Quantifying the effects of tides, river flow, and barriers on movements of Chinook Salmon smolts at junctions in the Sacramento–San Joaquin River Delta using multistate models: Environmental Biology of Fishes, v. 105, p. 2065-2082, https://doi.org/10.1007/s10641-022-01273-1.","productDescription":"18 p.","startPage":"2065","endPage":"2082","ipdsId":"IP-133966","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":401641,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento-San-Joaquin River Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.6513671875,\n 37.86618078529668\n ],\n [\n -122.56347656249999,\n 37.779398571318765\n ],\n [\n -122.55249023437501,\n 37.54022177661216\n ],\n [\n -122.0745849609375,\n 37.21720611325497\n ],\n [\n -121.541748046875,\n 37.020098201368114\n ],\n [\n -120.9210205078125,\n 37.24782120155428\n ],\n [\n -120.5804443359375,\n 37.4356124041315\n ],\n [\n -120.62988281249999,\n 37.63163475580643\n ],\n [\n -121.1846923828125,\n 37.896530447543\n ],\n [\n -121.31103515625,\n 38.052416771864834\n ],\n [\n -121.38244628906251,\n 38.268375880204744\n ],\n [\n -121.42639160156249,\n 38.45789034424927\n ],\n [\n -121.56921386718751,\n 38.70265930723801\n ],\n [\n -122.01416015625,\n 38.31149091244452\n ],\n [\n -122.61291503906249,\n 38.238180119798635\n ],\n [\n -122.6513671875,\n 37.86618078529668\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"105","noUsgsAuthors":false,"publicationDate":"2022-05-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Dodrill, Michael J. 0000-0002-7038-7170","orcid":"https://orcid.org/0000-0002-7038-7170","contributorId":206439,"corporation":false,"usgs":true,"family":"Dodrill","given":"Michael","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":844058,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perry, Russell 0000-0003-4110-8619","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":220189,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":844059,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pope, Adam C. 0000-0002-7253-2247","orcid":"https://orcid.org/0000-0002-7253-2247","contributorId":223237,"corporation":false,"usgs":true,"family":"Pope","given":"Adam","middleInitial":"C.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":844060,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wang, Xiaochun","contributorId":225264,"corporation":false,"usgs":false,"family":"Wang","given":"Xiaochun","email":"","affiliations":[{"id":41085,"text":"California Department of Water Resources, Sacramento, CA, 95819","active":true,"usgs":false}],"preferred":false,"id":844061,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70231905,"text":"70231905 - 2022 - Dynamic sensitivity to resource availability influences population responses to mismatches in a shorebird","interactions":[],"lastModifiedDate":"2022-09-01T14:36:44.26282","indexId":"70231905","displayToPublicDate":"2022-06-02T09:46:27","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Dynamic sensitivity to resource availability influences population responses to mismatches in a shorebird","docAbstract":"Climate change has caused shifts in seasonally recurring biological events leading to the temporal decoupling of consumer-resource pairs – i.e., phenological mismatching. Although mismatches often affect individual fitness, they do not invariably scale up to affect populations, making it difficult to assess the risk they pose. Individual variation may contribute to this inconsistency, with changes in resource availability and consumer needs leading mismatches to have different outcomes over time. Nevertheless, most models estimate a consumer’s match from a single timepoint, potentially obscuring when mismatches matter to populations. We analyzed how the effects of mismatches varied over time by studying precocial Hudsonian godwit (Limosa haemastica) chicks and their invertebrate prey from 2009 to 2019. We developed individual and population level models to determine how age-specific variation affect the relationship between godwits and resource availability. We found that periods with abundant resources led to higher growth and survival of godwit chicks, but also that chick survival was increasingly related to the availability of larger prey as chicks aged. At the population level, estimates of mismatches using age-structured consumer demand explained more variation in annual godwit fledging rates than more commonly used alternatives. Our study suggests that modeling the effects of mismatches as the disrupted interaction between dynamic consumer needs and resource availability clarifies when mismatches matter to both individuals and populations.
","language":"English","publisher":"Wiley","doi":"10.1002/ecy.3743","usgsCitation":"Wilde, L.R., Simmons, J.E., Swift, R.J., and Senner, N.R., 2022, Dynamic sensitivity to resource availability influences population responses to mismatches in a shorebird: Ecology, v. 103, no. 9, e3743, 14 p., https://doi.org/10.1002/ecy.3743.","productDescription":"e3743, 14 p.","ipdsId":"IP-125364","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":447562,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/ecy.3743","text":"External Repository"},{"id":401639,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Beluga River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -151.11968994140625,\n 61.18992667218288\n ],\n [\n -150.91506958007812,\n 61.18992667218288\n ],\n [\n -150.91506958007812,\n 61.264621333832146\n ],\n [\n -151.11968994140625,\n 61.264621333832146\n ],\n [\n -151.11968994140625,\n 61.18992667218288\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"103","issue":"9","noUsgsAuthors":false,"publicationDate":"2022-06-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Wilde, Luke R.","contributorId":291481,"corporation":false,"usgs":false,"family":"Wilde","given":"Luke","email":"","middleInitial":"R.","affiliations":[{"id":62717,"text":"Dept. of Biological Sciences, University of South Carolina","active":true,"usgs":false}],"preferred":false,"id":844068,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Simmons, Josiah E.","contributorId":292206,"corporation":false,"usgs":false,"family":"Simmons","given":"Josiah","email":"","middleInitial":"E.","affiliations":[{"id":62841,"text":"Division of Biological Sciences, University of Montana","active":true,"usgs":false}],"preferred":false,"id":844069,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Swift, Rose J. 0000-0001-7044-6196","orcid":"https://orcid.org/0000-0001-7044-6196","contributorId":212082,"corporation":false,"usgs":true,"family":"Swift","given":"Rose","email":"","middleInitial":"J.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":844070,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Senner, Nathan R.","contributorId":140465,"corporation":false,"usgs":false,"family":"Senner","given":"Nathan","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":844071,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70231900,"text":"fs20223039 - 2022 - Georgia and Landsat","interactions":[],"lastModifiedDate":"2025-03-20T14:27:39.867136","indexId":"fs20223039","displayToPublicDate":"2022-06-02T09:16:18","publicationYear":"2022","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":"2022-3039","displayTitle":"Georgia and Landsat","title":"Georgia and Landsat","docAbstract":"Georgia’s nickname is “The Peach State” for its fruitful production, but it also could be called “The State of Abundance.” Georgia ranks in the top 10 States for population, at more than 10 million residents, and 6 million residents are in the greater Atlanta area. Georgia also ranks in the top 10 States for forest areas with 24 million acres, or about two-thirds of the State. Its trees vary from deciduous hardwoods and pines to cypress and magnolias.
Georgia has diverse ecosystems, from the Blue Ridge Mountains in the northeast to the hilly, populous Piedmont region in the middle to the vast Coastal Plains that cover the southern half of the State with farms, forests, and wetlands. The State’s 14 major river basins, including the Chattahoochee and the Savannah, ultimately drain to the Atlantic Ocean or the Gulf of America. Millions of acres of wetlands include floodplain wetlands, freshwater swamps such as the Okefenokee Swamp, and coastal marshes. More than a dozen barrier islands lie off Georgia’s coastline. Wildlife in these myriad habitats include black bears, alligators, armadillos, manatees, sea turtles, and more than 40 species of snakes.
The Landsat satellite imagery scale and its 50-year record of Earth observations make Landsat ideal for monitoring changes in these diverse environments and supporting decision-making by government officials and land managers. Here are several ways Landsat has benefited Georgia.
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\"}}]}","edition":"Version 1.0: June 2, 2022; Version 1.1: March 19, 2025","contact":"Program Coordinator, National Land Imaging Program
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
Volcano monitoring, eruption response, and hazard assessment at volcanoes in the United States of America (US) fall under the mandate of five regional volcano observatories covering 161 active volcanoes. Working in a wide range of volcanic and geographic settings, US observatories must learn from and apply new knowledge and techniques to a great variety of scientific and hazard communication problems in volcanology. Over the past decade, experience during volcanic crises, such as the landmark 2018 eruption of Kīlauea, Hawaiʻi, has combined with investments and advances in research and technology, and the changing needs of partner agencies and the public, to transform the operations, science, and communication programs of US volcano observatories. Scientific and operational lessons from the past decade now guide new research and growing inter-observatory and external communication networks to meet new challenges and improve detection, forecasting, and response to volcanic eruptions in the US and around the world.
","language":"English","publisher":"Springer","doi":"10.1007/s00445-022-01567-3","usgsCitation":"Dietterich, H., and Neal, C.A., 2022, A look ahead to the next decade at US volcano observatories: Bulletin of Volcanology, v. 84, 63, 8 p., https://doi.org/10.1007/s00445-022-01567-3.","productDescription":"63, 8 p.","ipdsId":"IP-133974","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":447565,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00445-022-01567-3","text":"Publisher Index Page"},{"id":401677,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Federated States of Micronesia, United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -179.9,\n 50.28933925329178\n ],\n [\n -146.25,\n 50.28933925329178\n ],\n [\n -146.25,\n 62.75472592723178\n ],\n [\n -179.9,\n 62.75472592723178\n ],\n [\n -179.9,\n 50.28933925329178\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.8046875,\n 35.460669951495305\n ],\n [\n -106.171875,\n 35.460669951495305\n ],\n [\n -106.171875,\n 48.69096039092549\n ],\n [\n -124.8046875,\n 48.69096039092549\n ],\n [\n -124.8046875,\n 35.460669951495305\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -160.75195312499997,\n 18.22935133838668\n ],\n [\n -153.544921875,\n 18.22935133838668\n ],\n [\n -153.544921875,\n 22.59372606392931\n ],\n [\n -160.75195312499997,\n 22.59372606392931\n ],\n [\n -160.75195312499997,\n 18.22935133838668\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 144.228515625,\n 12.693932935851421\n ],\n [\n 146.65649414062497,\n 12.693932935851421\n ],\n [\n 146.65649414062497,\n 16.804541076383455\n ],\n [\n 144.228515625,\n 16.804541076383455\n ],\n [\n 144.228515625,\n 12.693932935851421\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 172.177734375,\n 49.49667452747045\n ],\n [\n 179.9,\n 49.49667452747045\n ],\n [\n 179.9,\n 54.470037612805754\n ],\n [\n 172.177734375,\n 54.470037612805754\n ],\n [\n 172.177734375,\n 49.49667452747045\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"84","noUsgsAuthors":false,"publicationDate":"2022-06-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Dietterich, Hannah R. 0000-0001-7898-4343","orcid":"https://orcid.org/0000-0001-7898-4343","contributorId":212771,"corporation":false,"usgs":true,"family":"Dietterich","given":"Hannah R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":844142,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Neal, Christina A. 0000-0002-7697-7825 tneal@usgs.gov","orcid":"https://orcid.org/0000-0002-7697-7825","contributorId":131135,"corporation":false,"usgs":true,"family":"Neal","given":"Christina","email":"tneal@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":844143,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70241557,"text":"70241557 - 2022 - Taking the leap: A binational translocation effort to close the 420-km gap in the Baja California lineage of the California red-legged frog (Rana draytonii)","interactions":[],"lastModifiedDate":"2023-03-23T13:31:20.828552","indexId":"70241557","displayToPublicDate":"2022-06-02T08:19:22","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9319,"text":"Frontiers in Conservation Science","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Taking the leap: A binational translocation effort to close the 420-km gap in the Baja California lineage of the California red-legged frog (Rana draytonii)","title":"Taking the leap: A binational translocation effort to close the 420-km gap in the Baja California lineage of the California red-legged frog (Rana draytonii)","docAbstract":"Conservation translocations, the human-mediated movement and release of a living organism for a conservation benefit, are increasingly recommended in species’ recovery plans as a technique for mitigating population declines or augmenting genetic diversity. However, translocation protocols for species with broad distributions may require regionally specific considerations to increase success, as environmental gradients may pose different constraints on population establishment and persistence in different parts of the range. Here we report on ongoing, genetically informed translocations of a threatened amphibian, California red-legged frog (Rana draytonii), from Baja California, México, to extirpated parts of the range in southern California in the United States, where contemporary stressors related to urbanization, invasive species, and aridification add to the natural environmental challenges already present for amphibians at this ‘warm edge’ of the range. We describe the collaborative binational planning required to jumpstart the effort, the fine-tuning of protocols for collection, transport, headstarting, and release of individuals, and results of multiple translocations, where time will tell whether the successes to date have reached their full potential. The steps outlined in this paper can serve as a template to inform future conservation translocations of imperiled amphibians across the U.S./México border, where the phylogenetics, historical biogeography and future habitat availability of a focal species are blind to political boundaries and critical to guiding recovery actions across the range.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fcosc.2022.908929","usgsCitation":"North, S., Richmond, J.Q., Santana, F.E., Peralta-García, A., Gallegos, E., Backlin, A.R., Hitchcock, C.J., Hollingsworth, B., Valdez-Villavicencio, J.H., Principe, Z., Fisher, R., and Winchell, C.S., 2022, Taking the leap: A binational translocation effort to close the 420-km gap in the Baja California lineage of the California red-legged frog (Rana draytonii): Frontiers in Conservation Science, v. 3, 908929, 12 p., https://doi.org/10.3389/fcosc.2022.908929.","productDescription":"908929, 12 p.","ipdsId":"IP-141339","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":447567,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fcosc.2022.908929","text":"Publisher Index 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Bradford","contributorId":202768,"corporation":false,"usgs":false,"family":"Hollingsworth","given":"Bradford","affiliations":[{"id":36525,"text":"San Diego Museum of Natural History","active":true,"usgs":false}],"preferred":false,"id":867305,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Valdez-Villavicencio, Jorge H.","contributorId":169076,"corporation":false,"usgs":false,"family":"Valdez-Villavicencio","given":"Jorge","email":"","middleInitial":"H.","affiliations":[{"id":25411,"text":"Conservacion de Fauna del Roroeste, Ensenada, Baja California, Mexico","active":true,"usgs":false}],"preferred":false,"id":867306,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Principe, Zachary","contributorId":303348,"corporation":false,"usgs":false,"family":"Principe","given":"Zachary","email":"","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":867307,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Fisher, Robert N. 0000-0002-2956-3240","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":51675,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":867308,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Winchell, Clark S.","contributorId":207769,"corporation":false,"usgs":false,"family":"Winchell","given":"Clark","email":"","middleInitial":"S.","affiliations":[{"id":37632,"text":"USFWS -- Carlsbad FWO","active":true,"usgs":false}],"preferred":false,"id":867309,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70246620,"text":"70246620 - 2022 - Chew-cards can accurately index invasive rat densities in Mariana Island forests","interactions":[],"lastModifiedDate":"2023-07-11T12:20:09.04227","indexId":"70246620","displayToPublicDate":"2022-06-02T07:16:37","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5071,"text":"NeoBiota","active":true,"publicationSubtype":{"id":10}},"title":"Chew-cards can accurately index invasive rat densities in Mariana Island forests","docAbstract":"Rats (Rattus spp.) are likely established on 80–90% of the world’s islands and represent one of the most damaging and expensive biological invaders. Effective rat control tools exist but require accurate population density estimates or indices to inform treatment timing and effort and to assess treatment efficacy. Capture-mark-recapture data are frequently used to produce robust density estimates, but collecting these data can be expensive, time-consuming, and labor-intensive. We tested a potentially cheaper and easier alternative, chew-cards, as a count-based (quantitative) index of invasive rat densities in tropical forests in the Mariana Islands, an archipelago in the western North Pacific Ocean. We trialed chew-cards in nine forest grids on two Mariana Islands by comparing the proportion of cards chewed to capture-mark-recapture density estimates and manipulated rat densities to test whether the relationship was retained. Chew-card counts were positively correlated with rat capture-mark-recapture density estimates across a range of rat densities found in the region. Additionally, the correlation between the two sampling methods increased with the number of days chew-cards were deployed. Specifically, when chew-cards were deployed for five nights, a 10% increase in the proportion of cards chewed equated to an estimated increase in rat density of approximately 2.4 individuals per ha (R2 = 0.74). Chew-cards can provide a valid index of rat densities in Mariana Island forests and are a cheaper alternative to capture-mark-recapture sampling when relative differences in density are of primary interest. New cost-effective monitoring tools can enhance our understanding and management of invaded islands while stretching limited resources further than some conventional approaches, thus improving invasive species management on islands.
We present and demonstrate a recursive-estimation framework to infer groundwater/surface-water exchange based on temperature time series collected at different vertical depths below the sediment/water interface. We formulate the heat-transport problem as a state-space model (SSM), in which the spatial derivatives in the convection/conduction equation are approximated using finite differences. The SSM is calibrated to estimate time-varying specific discharge using the Extended Kalman Filter (EKF) and Extended Rauch-Tung-Striebel Smoother (ERTSS). Whereas the EKF is suited to real-time (“online”) applications and uses only the past and current measurements for estimation (filtering), the ERTSS is intended for near-real time or batch-processing (“offline”) applications and uses a window of data for batch estimation (smoothing). The two algorithms are demonstrated with synthetic and field-experimental data and are shown to be efficient and rapid for the estimation of time-varying flux over seasonal periods; further, the recursive approaches are effective in the presence of rapidly changing flux and (or) nonperiodic thermal boundary conditions, both of which are problematic for existing approaches to heat tracing of time-varying groundwater/surface-water exchange.
No abstract available.
","language":"English","publisher":"Society for Study of Amphibians and Reptiles","usgsCitation":"Reed, R., Liske-Clark, J., and Liske-Clark, S., 2022, Emoia atrocostata (tidepool skink, mangrove skink). USA Commonwealth of the Northern Mariana Islands: Saipan Island: Herpetological Review, v. 53, no. 2, p. 262-263.","productDescription":"2 p.","startPage":"262","endPage":"263","ipdsId":"IP-120647","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":420639,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://ssarherps.org/herpetological-review-pdfs/","linkFileType":{"id":5,"text":"html"}},{"id":420640,"type":{"id":24,"text":"Thumbnail"},"url":"http://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Commonwealth of the Northern Marianas Islands, Saipan Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 145.74964043722963,\n 15.0898311971863\n ],\n [\n 145.75737318842783,\n 15.121450044553143\n ],\n [\n 145.74236255375018,\n 15.1372577008961\n ],\n [\n 145.7587377915803,\n 15.161845043266041\n ],\n [\n 145.78011657430176,\n 15.14955172917007\n ],\n [\n 145.78966879636937,\n 15.149990788403187\n ],\n [\n 145.79512720897935,\n 15.16711338769295\n ],\n [\n 145.77875197114935,\n 15.19345313930694\n ],\n [\n 145.83333609724968,\n 15.268503375244052\n ],\n [\n 145.8124121822451,\n 15.293514165126581\n ],\n [\n 145.78193604517287,\n 15.2632375658403\n ],\n [\n 145.71461562298305,\n 15.218472857919991\n ],\n [\n 145.68641382449727,\n 15.123206509036578\n ],\n [\n 145.70551826863243,\n 15.104323753533805\n ],\n [\n 145.74964043722963,\n 15.0898311971863\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"53","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Reed, Robert 0000-0001-8349-6168","orcid":"https://orcid.org/0000-0001-8349-6168","contributorId":267796,"corporation":false,"usgs":true,"family":"Reed","given":"Robert","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":882049,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liske-Clark, Jill","contributorId":216449,"corporation":false,"usgs":false,"family":"Liske-Clark","given":"Jill","email":"","affiliations":[{"id":39432,"text":"Division of Fish & Wildlife, Commonwealth of the Northern Marianas, Lower Base, Saipan Commonwealth of the Northern Mariana Islands","active":true,"usgs":false}],"preferred":false,"id":882050,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Liske-Clark, Samantha","contributorId":329355,"corporation":false,"usgs":false,"family":"Liske-Clark","given":"Samantha","email":"","affiliations":[{"id":78573,"text":"Saipan International School","active":true,"usgs":false}],"preferred":false,"id":882051,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70236670,"text":"70236670 - 2022 - Spout Run temperature study revisited- Part II: New insights for trout habitat from TU & USGS collaboration 2022","interactions":[],"lastModifiedDate":"2022-09-15T16:53:08.222861","indexId":"70236670","displayToPublicDate":"2022-06-01T11:41:56","publicationYear":"2022","noYear":false,"publicationType":{"id":25,"text":"Newsletter"},"publicationSubtype":{"id":30,"text":"Newsletter"},"seriesTitle":{"id":12588,"text":"Lateral Lines","active":true,"publicationSubtype":{"id":30}},"title":"Spout Run temperature study revisited- Part II: New insights for trout habitat from TU & USGS collaboration 2022","docAbstract":"The Winchester TU Chapter partnered with US Geological Survey scientists to forecast habitat conditions for brook trout in Virginia. The results can be viewed here: https://chesapeake.usgs.gov/fishforecast/
TU members deployed stream temperature gages within several streams across the region: Dry River, Passage Creek, Spout Run, Beaver Creek, Mossy Creek. The USGS then used the temperature data to evaluate current and future conditions for brook trout.
","language":"English","publisher":"Trout Unlimited, Winchester Chapter #638","usgsCitation":"Hitt, N.P., 2022, Spout Run temperature study revisited- Part II: New insights for trout habitat from TU & USGS collaboration 2022: Lateral Lines, no. June 2022, p. 8-9.","productDescription":"2 p.","startPage":"8","endPage":"9","ipdsId":"IP-141316","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":406771,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":406769,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://winchestertu.org/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Virginia","otherGeospatial":"Spout Run","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.12721252441406,\n 39.03\n ],\n [\n -78,\n 39.03\n ],\n [\n -78,\n 39.144972625112224\n ],\n [\n -78.12721252441406,\n 39.144972625112224\n ],\n [\n -78.12721252441406,\n 39.03\n ]\n ]\n ]\n }\n }\n ]\n}","issue":"June 2022","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hitt, Nathaniel P. 0000-0002-1046-4568","orcid":"https://orcid.org/0000-0002-1046-4568","contributorId":238185,"corporation":false,"usgs":true,"family":"Hitt","given":"Nathaniel","email":"","middleInitial":"P.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":851822,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70246621,"text":"70246621 - 2022 - New state and county records of introduced amphibians and reptiles of Georgia, USA.","interactions":[],"lastModifiedDate":"2023-07-19T16:42:06.960625","indexId":"70246621","displayToPublicDate":"2022-06-01T11:36:22","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1898,"text":"Herpetological Review","active":true,"publicationSubtype":{"id":10}},"title":"New state and county records of introduced amphibians and reptiles of Georgia, USA.","docAbstract":"Recent efforts to eradicate the invasive Argentine Giant Tegu (Salvator merianae) has led to the discovery of several county records of this introduced lizard as well as several other potentially invasive amphibian and reptile species in the state of Georgia, USA. New records were determined using a database of county records maintained by the Georgia Department of Natural Resources. All specimens and photographic records are stored at the Georgia Southern University – Savannah Science Museum Herpetology Collection (GSU) and were collected under the Georgia scientific collection permit number 1000545737 and IACUC permit number I18020 and I21010. All coordinates are presented in WGS 84. We report 14 new county records consisting of two anurans and 11 squamates in Georgia.
","language":"English","publisher":"Society for the Study of Amphibians and Reptiles","usgsCitation":"Brennan, M., McBrayer, L., Carroll, J., Krysko, K.L., and Yackel Adams, A.A., 2022, New state and county records of introduced amphibians and reptiles of Georgia, USA.: Herpetological Review, v. 53, no. 2, p. 272-273.","productDescription":"2 p.","startPage":"272","endPage":"273","ipdsId":"IP-130578","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":419155,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":418850,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://ssarherps.org/publications/herpetological-review/","linkFileType":{"id":5,"text":"html"}}],"country":"United 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University","active":true,"usgs":false}],"preferred":false,"id":877404,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Krysko, Kenneth L.","contributorId":200646,"corporation":false,"usgs":false,"family":"Krysko","given":"Kenneth","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":877405,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Yackel Adams, Amy A. 0000-0002-7044-8447 yackela@usgs.gov","orcid":"https://orcid.org/0000-0002-7044-8447","contributorId":3116,"corporation":false,"usgs":true,"family":"Yackel Adams","given":"Amy","email":"yackela@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":877406,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70231845,"text":"ofr20221013 - 2022 - Water-budget accounting for tropical regions model (WATRMod) documentation","interactions":[],"lastModifiedDate":"2026-03-27T19:49:35.907978","indexId":"ofr20221013","displayToPublicDate":"2022-06-01T11:17:20","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-1013","displayTitle":"Water-Budget Accounting for Tropical Regions Model (WATRMod) Documentation","title":"Water-budget accounting for tropical regions model (WATRMod) documentation","docAbstract":"Regional groundwater recharge commonly is estimated using a threshold-type water-budget approach in which groundwater recharge is assumed to occur when water in the plant-root zone exceeds the soil’s moisture storage capacity. A water budget of the plant-soil system accounts for water inputs (rainfall, fog interception, irrigation, septic-system leachate, and other inputs), water outputs (runoff, evaporation, transpiration, and recharge), and changes in stored water during a specified time interval. Water budgets can be computed on any desired interval, including annual, monthly, daily, and subdaily intervals. In general, uncertainty in recharge estimates is expected to be lower using daily or subdaily intervals relative to monthly and annual intervals. Average recharge rates computed over a period of a year or multiple years are commonly determined from water budgets computed using a daily computation interval capable of capturing rainfall and land-cover changes during the period.
This report documents the Water-budget Accounting for Tropical Regions Model, or WATRMod, code that can be used to estimate spatially variable, daily water-budget components in tropical-island and other appropriate settings. The purpose of this report is to provide descriptions of WATRMod’s (1) approach to computing a daily water budget, (2) represented processes, (3) limitations, and (4) execution procedure, input requirements, output files, and example files. The model computes a daily water budget for each hydrologically independent subarea within the overall study area. A subarea is defined by its climatic, soil, land-cover, and human-related (for example, adding irrigation or other water) characteristics. The water-budget model can represent processes including rainfall, fog interception, irrigation, septic-system leachate, direct recharge that bypasses the plant-soil system, runoff, canopy evaporation in forested areas, evapotranspiration, and groundwater recharge. The water-budget model can represent either one of the following different accounting orders: (1) accounting for loss of water by evapotranspiration before accounting for recharge, and (2) accounting for recharge before accounting for evapotranspiration. WATRMod’s limitations include: (1) uncharacterized, subdaily transient changes in water inputs and outputs from the plant-soil system, (2) unrepresented precipitation in the form of snow and sublimation, and (3) routing runoff from one subarea to an adjacent subarea that is not directly represented.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221013","usgsCitation":"Oki, D.S., 2022, Water-budget accounting for tropical regions model (WATRMod) documentation: U.S. Geological Survey Open-File Report 2022-1013, 77 p., https://doi.org/10.3133/ofr20221013.","productDescription":"Report: viii, 77 p.; Data Release","numberOfPages":"77","onlineOnly":"Y","ipdsId":"IP-126805","costCenters":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"links":[{"id":501758,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113077.htm","linkFileType":{"id":5,"text":"html"}},{"id":401381,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VPAY41","text":"WATRMod, a Water-budget accounting for tropical regions model—source code, executable file, and example files","description":"Oki, D.S., 2022, WATRMod, a Water-budget accounting for tropical regions model—source code, executable file, and example files: U.S. Geological Survey data release, https://doi.org/10.5066/P9VPAY41."},{"id":401379,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1013/covrthb.jpg"},{"id":401380,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1013/ofr20221013.pdf","text":"Report","size":"3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Open-File Report 2022-1013"}],"country":"United States","state":"Hawaii","otherGeospatial":"Island of Maui","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -156.3848876953125,\n 20.555652403773365\n ],\n [\n -156.0003662109375,\n 20.6379249854131\n ],\n [\n -155.9454345703125,\n 20.776659051878816\n ],\n [\n -156.26678466796875,\n 20.964004409178308\n ],\n [\n -156.47003173828125,\n 20.925527866647226\n ],\n [\n -156.610107421875,\n 21.056307701901847\n ],\n [\n -156.72271728515625,\n 20.94604992010052\n ],\n [\n -156.67327880859375,\n 20.822875478868443\n ],\n [\n -156.55792236328122,\n 20.761250430919652\n ],\n [\n -156.48651123046875,\n 20.771523019513364\n ],\n [\n -156.4617919921875,\n 20.622502259344817\n ],\n [\n -156.3848876953125,\n 20.555652403773365\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Pacific Islands Water Science Center
U.S. Geological Survey
Inouye Regional Center
1845 Wasp Blvd., B176
Honolulu, HI 96818
The annual Lake Ontario April bottom trawl survey and Alewife, Alosa pseudoharengus, population assessment provide science to inform management decisions related to predator-prey balance and fish community dynamics. The 2022 survey was conducted from March 31 to April 26, included 235 trawls in the main lake and embayments, and sampled depths from 5 to 219 m (16 – 723 ft). The survey captured 311,770 fish from 30 species with a total weight of 7,740 kg (17,028 lbs.). Alewife were 85% of the catch by number while Rainbow Smelt, Osmerus mordax, Round Goby, Neogobius melanostomus, and Deepwater Sculpin, Myoxocephalus thompsonii, comprised 6%, 4%, and 4% of the catch, respectively. The 2022 biomass index for Rainbow Smelt decreased 80% relative to the high values observed in 2021 as did the value for Cisco, Coregonus artedi, (46% decline). Emerald Shiner, Notropis atherinoides, biomass index increased in 2021 and Threespine Stickleback, Gasterosteus aculeatus, biomass remained low. No Bloater, Coregonus hoyi, were captured during the 2022 survey.
In 2022, Alewife biomass in U.S. waters (58.1 kilograms per hectare, kg·ha-1) was substantially higher than Canadian waters (26.3 kg·ha-1). The 2022 Alewife biomass index (41.6 kg·ha-1) decreased 10% from 2021 while the 2022 density index decreased 62% from 2021. Prediction modeling indicated the growth of the abundant 2020 Alewife year class, sampled as age-1 fish in 2021, would cause the adult Alewife biomass to increase in 2022. Although the adult Alewife biomass did increase relative to 2021 (61%), the increase was lower than predicted. The difference between the predictions and observations was because survival of age-1 fish from 2021 to 2022 was lower than had previously been observed. In the three previous years of observations the proportion of age-1 Alewife surviving to age 2 ranged from 0.33 to 0.53; however, that proportion was only 0.21 from 2021 to 2022. Survival estimates of Alewife age-5 through age-8 were higher than previously observed, possibly because salmonid predation focused on the abundant younger Alewife. The catch of age-1 Alewife in 2022, which is a measure of reproductive success in 2021, was below average and similar to the abundances of the 2018 and 2019 year classes. Simulation modeling results indicated the adult Alewife biomass is likely to increase slightly in 2023, whereas predictions for 2024 are less certain.
Hydroacoustic sampling was used to estimate prey fish densities in open-water, pelagic habitats not sampled by the bottom trawl. Bottom trawl-based densities from the lake bottom were at least 25 times greater than densities of prey fish in the water column above the trawl. These results support the idea that, in April, when the warmest, most dense water is on the lake bottom, Alewife and most other pelagic prey fish primarily inhabit deep, near bottom habitats and can be effectively sampled with bottom trawling.
","language":"English","publisher":"Great Lakes Fishery Commission","collaboration":"NYSDEC, OMNRF","usgsCitation":"Weidel, B., Gutowsky, L.F., Goretzke, J., Holden, J., and Minihkeim, S.P., 2022, Lake Ontario April prey fish survey results and Alewife assessment, 2022, 11 p.","productDescription":"11 p.","ipdsId":"IP-144324","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":406900,"type":{"id":15,"text":"Index Page"},"url":"https://www.glfc.org/lake-ontario-committee.php"},{"id":406974,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Lake Ontario","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.925537109375,\n 43.265206318396025\n ],\n [\n -79.8101806640625,\n 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Jessica","contributorId":268339,"corporation":false,"usgs":false,"family":"Goretzke","given":"Jessica","affiliations":[{"id":13678,"text":"New York State Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":852089,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Holden, Jeremy","contributorId":139654,"corporation":false,"usgs":false,"family":"Holden","given":"Jeremy","affiliations":[{"id":12864,"text":"OMNRF","active":true,"usgs":false}],"preferred":false,"id":852090,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Minihkeim, Scott P. 0000-0003-4958-2462","orcid":"https://orcid.org/0000-0003-4958-2462","contributorId":265808,"corporation":false,"usgs":true,"family":"Minihkeim","given":"Scott","email":"","middleInitial":"P.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":852091,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70248097,"text":"70248097 - 2022 - 2021 National park visitor spending effects: Economic contributions to local communities, states, and the nation","interactions":[],"lastModifiedDate":"2023-09-05T15:55:29.98934","indexId":"70248097","displayToPublicDate":"2022-06-01T10:53:59","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":53,"text":"Natural Resource Report","active":false,"publicationSubtype":{"id":1}},"seriesNumber":"NPS/NRSS/EQD/NRR-2022/2395","title":"2021 National park visitor spending effects: Economic contributions to local communities, states, and the nation","docAbstract":"The National Park Service (NPS) manages the Nation’s most iconic destinations that attract millions of visitors from across the Nation and around the world. Trip-related spending by NPS visitors generates and supports economic activity within park gateway communities. This report summarizes the annual economic contribution analysis that measures how NPS visitor spending cycles through local economies, generating business sales and supporting jobs and income.\nIn 2021, the National Park System received over 297 million recreation visits (up 25% from 2020). Visitors to national parks spent an estimated $20.5 billion in local gateway regions (up 41% from 2020). The estimated contribution of this spending to the national economy was 322,600 jobs, $14.6 billion in labor income, $24.3 billion in value added, and $42.5 billion in economic output. The lodging sector saw the highest direct effects, with $7 billion in economic output directly contributed to this sector nationally. The restaurants sector saw the next greatest effects, with $4.2 billion in economic output directly contributed to this sector nationally.\nResults from the Visitor Spending Effects report series are available online via an interactive tool. Users can view year-by-year trend data and explore current year visitor spending, jobs, labor income, value added, and economic output effects by sector for national, state, and local economies. The interactive tool is available at https://www.nps.gov/subjects/socialscience/vse.htm.","language":"English","publisher":"National Park Service","usgsCitation":"Cullinane Thomas, C., Flyr, M., and Koontz, L., 2022, 2021 National park visitor spending effects: Economic contributions to local communities, states, and the nation: Natural Resource Report NPS/NRSS/EQD/NRR-2022/2395, v, 63 p.","productDescription":"v, 63 p.","ipdsId":"IP-139225","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":420493,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://www.nps.gov/nature/customcf/NPS_Data_Visualization/docs/NPS_2021_Visitor_Spending_Effects.pdf"},{"id":420494,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Cullinane Thomas, Catherine M. 0000-0001-8168-1271","orcid":"https://orcid.org/0000-0001-8168-1271","contributorId":328910,"corporation":false,"usgs":true,"family":"Cullinane Thomas","given":"Catherine M.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":881839,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flyr, Matthew 0000-0002-4723-3763","orcid":"https://orcid.org/0000-0002-4723-3763","contributorId":291828,"corporation":false,"usgs":false,"family":"Flyr","given":"Matthew","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":881840,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Koontz, Lynne koontzl@usgs.gov","contributorId":2174,"corporation":false,"usgs":false,"family":"Koontz","given":"Lynne","email":"koontzl@usgs.gov","affiliations":[{"id":7016,"text":"Environmental Quality Division, National Park Service, Fort Collins, Colorado","active":true,"usgs":false}],"preferred":false,"id":881841,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70237855,"text":"70237855 - 2022 - The population genetics of the causative agent of snake fungal disease indicate recent introductions to the USA","interactions":[],"lastModifiedDate":"2022-10-27T15:51:09.02612","indexId":"70237855","displayToPublicDate":"2022-06-01T10:44:00","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2979,"text":"PLoS Biology","active":true,"publicationSubtype":{"id":10}},"title":"The population genetics of the causative agent of snake fungal disease indicate recent introductions to the USA","docAbstract":"Snake fungal disease (SFD; ophidiomycosis), caused by the pathogen Ophidiomyces ophiodiicola (Oo), has been documented in wild snakes in North America and Eurasia, and is considered an emerging disease in the eastern United States of America. However, a lack of historical disease data has made it challenging to determine whether Oo is a recent arrival to the USA or whether SFD emergence is due to other factors. Here, we examined the genomes of 82 Oo strains to determine the pathogen’s history in the eastern USA. Oo strains from the USA formed a clade (Clade II) distinct from European strains (Clade I), and molecular dating indicated that these clades diverged too recently (approximately 2,000 years ago) for transcontinental dispersal of Oo to have occurred via natural snake movements across Beringia. A lack of nonrecombinant intermediates between clonal lineages in Clade II indicates that Oo has actually been introduced multiple times to North America from an unsampled source population, and molecular dating indicates that several of these introductions occurred within the last few hundred years. Molecular dating also indicated that the most common Clade II clonal lineages have expanded recently in the USA, with time of most recent common ancestor mean estimates ranging from 1985 to 2007 CE. The presence of Clade II in captive snakes worldwide demonstrates a potential mechanism of introduction and highlights that additional incursions are likely unless action is taken to reduce the risk of pathogen translocation and spillover into wild snake populations.
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It was also the setting for events like the Wright Brothers’ famous first flight of a powered aircraft, called “Wright Flyer,” which took place in Kitty Hawk in 1903. Today, North Carolina license plates proudly proclaim the State as “First in Flight.”
The aerospace and defense sectors remain large players in the State’s economy to this day. Boeing, Lockheed Martin, General Electric Aviation, and others maintain a presence in the Tar Heel State, and military installations dot the landscape.
It is fitting, then, that North Carolinians rely upon a satellite system to monitor and study the health of their State’s vast and varied terrain: its coastal plain, the sweeping valleys and peaks of the Blue Ridge Mountains, and the fertile rolling plateau of the Piedmont ecoregion that separates the two. The U.S. Geological Survey Landsat satellite program’s unparalleled 50-year record of Earth surface change offers scientists, watershed and land managers, urban planners, and others insight into landscape change, both drastic and mild. Landsat observations document everything from posthurricane floods that push inland to subtle shifts in forest composition and coastal encroachment on urban and military infrastructure.
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U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
Faults and folds on the southern flank of the Ozark dome in northern Arkansas, USA, record flexural extension in a foreland area followed by shortening in response to the late Paleozoic Ouachita orogeny. Map-scale structures and an analysis of fault-slip data collected systematically during geologic mapping demonstrate that most deformation in the area accommodated north-south extension as the southern margin of Laurentia was flexed beneath the thrust load of the Ouachita belt, probably during Middle Pennsylvanian. Extension was concentrated in northeast- and west-northwest-trending structural zones having sets of discontinuous, often en echelon normal and strike-slip faults and associated monoclinal folds. Reactivation of basement weaknesses that underlie these zones is indicated by their close match to oblique-rift models in which both the proportions of normal and strike-slip faulting and the internal extension directions vary with orientation of the zones. Subsequent propagation of north-south Ouachita shortening into the foreland formed small-offset strike-slip and sparse reverse faults that overprinted older extensional structures. Strike-slip faults were concentrated in reactivated northeast-trending structural zones. In two areas, reverse faults and local anticlines were developed in the footwalls of older normal faults, both near intersections of northeast- and west-northwest-trending structural zones. These are interpreted as areas of incipient inversion due to compressional stress concentrations at fault-block corners. Spatial overlap of areas of north-south shortening and fluid flux marked by silicification or lead-zinc mineralization indicates that regional fluid flow of brines was coeval with and may have enhanced inversion during Late Pennsylvanian to early Permian.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021TC006706","usgsCitation":"Hudson, M., and Turner, K.J., 2022, Late Paleozoic flexural extension and overprinting shortening in the southern Ozark dome, Arkansas, USA: Evolving fault kinematics in the foreland of the Ouachita orogen: Tectonics, v. 41, e2021TC006706, 27 p., https://doi.org/10.1029/2021TC006706.","productDescription":"e2021TC006706, 27 p.","ipdsId":"IP-125523","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":447580,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2021tc006706","text":"Publisher Index Page"},{"id":435830,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92TLPU2","text":"USGS data release","linkHelpText":"Fault data collected between 1996 and 2019 from the Buffalo River watershed area, northern Arkansas"},{"id":402148,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas, Kansas, Missouri, Oklahoma","otherGeospatial":"Ozark dome","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.63623046875,\n 35.51434313431818\n ],\n [\n -92.83447265624999,\n 35.60371874069731\n ],\n [\n -92.30712890625,\n 35.71083783530009\n ],\n [\n -88.22021484375,\n 36.24427318493909\n ],\n [\n -88.3740234375,\n 37.055177106660814\n ],\n [\n -89.14306640625,\n 37.125286284966805\n ],\n [\n -89.5166015625,\n 37.71859032558816\n ],\n [\n -90.28564453124999,\n 38.09998264736481\n ],\n [\n -91.34033203125,\n 38.238180119798635\n ],\n [\n -92.0654296875,\n 38.34165619279595\n ],\n [\n -93.4716796875,\n 38.22091976683121\n ],\n [\n -94.52636718749999,\n 37.47485808497102\n ],\n [\n -94.9658203125,\n 37.23032838760387\n ],\n [\n -95.1416015625,\n 36.58024660149866\n ],\n [\n -95.361328125,\n 35.90684930677121\n ],\n [\n -94.89990234375,\n 35.496456056584165\n ],\n [\n -94.63623046875,\n 35.51434313431818\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"41","noUsgsAuthors":false,"publicationDate":"2022-06-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Hudson, Mark R. 0000-0003-0338-6079 mhudson@usgs.gov","orcid":"https://orcid.org/0000-0003-0338-6079","contributorId":1236,"corporation":false,"usgs":true,"family":"Hudson","given":"Mark R.","email":"mhudson@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":844677,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Turner, Kenzie J. 0000-0002-4940-3981 kturner@usgs.gov","orcid":"https://orcid.org/0000-0002-4940-3981","contributorId":496,"corporation":false,"usgs":true,"family":"Turner","given":"Kenzie","email":"kturner@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":844678,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70255746,"text":"70255746 - 2022 - Distribution of niclosamide following granular Bayluscide applications in lotic systems","interactions":[],"lastModifiedDate":"2024-07-03T14:03:07.647204","indexId":"70255746","displayToPublicDate":"2022-06-01T08:47:05","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"seriesTitle":{"id":7568,"text":"Project Completion Report","active":true,"publicationSubtype":{"id":3}},"title":"Distribution of niclosamide following granular Bayluscide applications in lotic systems","docAbstract":"The granular formulation of Bayluscide [Bayluscide 3.2% Granular Sea Lamprey Larvicide, granular Bayluscide (gB)] is applied in lentic and lotic systems to survey (assessment) and kill (treatment) larval sea lampreys (Petromyzon marinus; Linnaeus, 1758) in the Great Lakes basin. Granules are spread on the water surface, settle to the sediment surface, and dissolve. The potential risk of niclosamide exposure (2′,5-dichloro-4′-nitrosalicylanilide), the active ingredient of gB, to non-target organisms located downstream of survey plots, is a concern of partner agencies (state-level natural resource departments, U.S. Fish and Wildlife Service Ecological Services, and Fisheries and Oceans Canada Species at Risk Branch). Spatiotemporal distribution of niclosamide in the water column and sediment was evaluated in and downstream of five larval survey plots in two rivers following the application of gB. Water samples were collected at 0.25, 2, 4, 6, 8, and 24 h from three depths in the water column (10 cm above the sediment, ½ the water column depth, and the water surface) at three locations inside each survey plot, and 1 meter upstream from three sediment sample grids positioned 10, 30, and 100 m downstream. Sediment samples were collected from inside the grids at 0.25, 2, 4, 6, 8, and 24 h, and from inside the survey plots, 8 and 24 h after gB application. Niclosamide was detected in the sediment and water at all sample locations. From 2 to 24 h after application, average water concentrations 1) varied between study sites, 2) decreased from the survey plots to 100 m downstream, 3) varied by depth in the water column, and 4) decreased over time. Average sediment concentrations varied by distance downstream and time post-application, but not by study site or river. Data suggest there would be negligible exposure to non-target organisms downstream of a gB survey plot based on low niclosamide concentrations measured in the water and sediment. The depletion rate of niclosamide was also evaluated in St. Clair River sediment dosed at the field application rate. Niclosamide concentration decreased at a rate of 2.28% per hour over the 24 hours measured, equating to a half-life of 1.27 days. This indicates the length of time an organism in the sediment in a survey plot might be exposed. Underwater cameras were placed along the edge of two St. Clair River survey plots to document gB distribution on the sediment and any potential target and non-target effects. Video was inconclusive in tracking gB through the water column. Larval sea lamprey and non-target mortality were not observed. Additional video footage of one St. Clair River survey plot showed large areas of river bottom without gB.
","language":"English","publisher":"Great Lakes Fishery Commission","usgsCitation":"Kaye, C., Bernardy, J.A., Schueller, J., Schloesser, N., Henson, M., Andresen, C.K., and Kirkeeng, C., 2022, Distribution of niclosamide following granular Bayluscide applications in lotic systems: Project Completion Report, 51 p.","productDescription":"51 p.","ipdsId":"IP-124289","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":430758,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":430738,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.glfc.org/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Michigan","county":"Alger County, St. Clair County","otherGeospatial":"Au Train River, St. Clair River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.57645899273449,\n 42.61812499759989\n ],\n [\n -82.64420763126448,\n 42.60751672353578\n ],\n [\n -82.69105509407704,\n 42.5650651070078\n ],\n [\n -82.58510775509997,\n 42.58947764353198\n ],\n [\n -82.57645899273449,\n 42.61812499759989\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -86.85011260876064,\n 46.41879658960383\n ],\n [\n -86.81383102571745,\n 46.41879658960383\n ],\n [\n -86.81383102571745,\n 46.43674452905637\n ],\n [\n -86.85011260876064,\n 46.43674452905637\n ],\n [\n -86.85011260876064,\n 46.41879658960383\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kaye, Cheryl","contributorId":167292,"corporation":false,"usgs":false,"family":"Kaye","given":"Cheryl","affiliations":[{"id":6599,"text":"U.S. Fish and Wildlife Service, Marquette Biological Station","active":true,"usgs":false}],"preferred":false,"id":905523,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bernardy, Jeffry A 0000-0001-7443-1995","orcid":"https://orcid.org/0000-0001-7443-1995","contributorId":296763,"corporation":false,"usgs":false,"family":"Bernardy","given":"Jeffry","email":"","middleInitial":"A","affiliations":[{"id":64165,"text":"former USGS, UMESC employee (retired)","active":true,"usgs":false}],"preferred":false,"id":905524,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schueller, Justin R. 0000-0002-7102-3889","orcid":"https://orcid.org/0000-0002-7102-3889","contributorId":213527,"corporation":false,"usgs":true,"family":"Schueller","given":"Justin","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":905525,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schloesser, Nicholas 0000-0002-3815-5302","orcid":"https://orcid.org/0000-0002-3815-5302","contributorId":237025,"corporation":false,"usgs":true,"family":"Schloesser","given":"Nicholas","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":905526,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Henson, Mary P.","contributorId":339882,"corporation":false,"usgs":false,"family":"Henson","given":"Mary P.","affiliations":[{"id":81410,"text":"USFWS, Marquette Biological Station","active":true,"usgs":false}],"preferred":false,"id":905527,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Andresen, Chad K.","contributorId":335684,"corporation":false,"usgs":false,"family":"Andresen","given":"Chad","email":"","middleInitial":"K.","affiliations":[{"id":80467,"text":"Marquette Biological Station, US Fish and Wildlife Service, Marquette, Michigan, USA","active":true,"usgs":false}],"preferred":false,"id":905528,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kirkeeng, Courtney A. 0000-0002-7141-1216","orcid":"https://orcid.org/0000-0002-7141-1216","contributorId":237026,"corporation":false,"usgs":true,"family":"Kirkeeng","given":"Courtney","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":905529,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70237644,"text":"70237644 - 2022 - Using structured decision making to evaluate potential management responses to detection of dreissenid mussel (Dreissena spp.) environmental DNA","interactions":[],"lastModifiedDate":"2022-10-18T13:57:05.161824","indexId":"70237644","displayToPublicDate":"2022-06-01T08:44:40","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2655,"text":"Management of Biological Invasions","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Using structured decision making to evaluate potential management responses to detection of dreissenid mussel (Dreissena spp.) environmental DNA","title":"Using structured decision making to evaluate potential management responses to detection of dreissenid mussel (Dreissena spp.) environmental DNA","docAbstract":"Environmental (e)DNA tools are sensitive and cost-effective for early detection of invasive species. However, the uncertainty associated with the interpretation of positive eDNA detections makes it challenging to determine appropriate natural resource management responses. Multiple sources of error can give rise to positive detections of eDNA in a sample when individuals of that species are not present at the site or a widespread infestation is not imminent. Acting on an erroneous eDNA inference could result in needless costs or reductions in desirable resources. Alternatively, failure to rapidly act on eDNA results that truly indicate invader presence could compound negative impacts and lead to high, long-term costs to manage infestations. We used a structured decision making (SDM) process, which incorporates tradeoffs and uncertainties, to evaluate appropriate response actions following hypothetical eDNA detections of invasive dreissenid mussel (Dreissena spp.) eDNA in Jordanelle Reservoir, Utah (USA). We worked with decision-makers and stakeholders to identify objectives and discrete management action alternatives to assess consequences and tradeoffs. Alternatives ranged from no action to intensive and expensive control efforts. The best performing alternative was delayed containment described by immediate attempts to confirm the eDNA detections using non-molecular sampling techniques followed by mandatory watercraft exit inspections to prevent dreissenid mussel spread to regional water bodies. Non-molecular sampling increased public support for management by demonstrating a commitment to monitor the invasion state before action, whereas containment decreased likelihood of regional spread to other waters. Delayed containment had the lowest downside risk, and the highest upside gains relative to other alternative actions. Sensitivity analyses showed our results to be robust to parameter and outcome uncertainty.
","language":"English","publisher":"Regional Euro-Asian Biological Invasions Centre","doi":"10.3391/mbi.2022.13.2.06","usgsCitation":"Sepulveda, A., Smith, D.R., O'Donnell, K., Owens, N., White, B., Richter, C.A., Merkes, C.M., Wolf, S., Rau, M., Neilson, M., Daniel, W., Dumoulin, C.E., and Hunter, M., 2022, Using structured decision making to evaluate potential management responses to detection of dreissenid mussel (Dreissena spp.) environmental DNA: Management of Biological Invasions, v. 13, no. 2, p. 344-368, https://doi.org/10.3391/mbi.2022.13.2.06.","productDescription":"25 p.","startPage":"344","endPage":"368","ipdsId":"IP-133646","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":447583,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3391/mbi.2022.13.2.06","text":"Publisher Index Page"},{"id":435831,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Y2IQTS","text":"USGS data release","linkHelpText":"Predicted consequences of detecting dreissenid mussel eDNA in Jordanelle Reservoir Utah, 2021"},{"id":408476,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sepulveda, Adam 0000-0001-7621-7028 asepulveda@usgs.gov","orcid":"https://orcid.org/0000-0001-7621-7028","contributorId":4187,"corporation":false,"usgs":true,"family":"Sepulveda","given":"Adam","email":"asepulveda@usgs.gov","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":854796,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, David R. 0000-0001-6074-9257 drsmith@usgs.gov","orcid":"https://orcid.org/0000-0001-6074-9257","contributorId":168442,"corporation":false,"usgs":true,"family":"Smith","given":"David","email":"drsmith@usgs.gov","middleInitial":"R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":854797,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O'Donnell, Katherine M. 0000-0001-9023-174X","orcid":"https://orcid.org/0000-0001-9023-174X","contributorId":289575,"corporation":false,"usgs":false,"family":"O'Donnell","given":"Katherine M.","affiliations":[{"id":62192,"text":"Compass Resource Management","active":true,"usgs":false}],"preferred":false,"id":854798,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Owens, Nathan","contributorId":297990,"corporation":false,"usgs":false,"family":"Owens","given":"Nathan","email":"","affiliations":[],"preferred":false,"id":854799,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"White, Brittany","contributorId":297992,"corporation":false,"usgs":false,"family":"White","given":"Brittany","email":"","affiliations":[],"preferred":false,"id":854803,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Richter, Cathy A. 0000-0001-7322-4206 crichter@usgs.gov","orcid":"https://orcid.org/0000-0001-7322-4206","contributorId":1878,"corporation":false,"usgs":true,"family":"Richter","given":"Cathy","email":"crichter@usgs.gov","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":854801,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Merkes, Christopher M. 0000-0001-8191-627X cmerkes@usgs.gov","orcid":"https://orcid.org/0000-0001-8191-627X","contributorId":139516,"corporation":false,"usgs":true,"family":"Merkes","given":"Christopher","email":"cmerkes@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":854944,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wolf, Skylar","contributorId":279472,"corporation":false,"usgs":false,"family":"Wolf","given":"Skylar","affiliations":[{"id":36967,"text":"Virginia Tech University","active":true,"usgs":false}],"preferred":false,"id":854802,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rau, 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0000-0001-7587-9417","orcid":"https://orcid.org/0000-0001-7587-9417","contributorId":298038,"corporation":false,"usgs":true,"family":"Dumoulin","given":"Christine","email":"","middleInitial":"E.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":854943,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Hunter, Margaret 0000-0002-4760-9302","orcid":"https://orcid.org/0000-0002-4760-9302","contributorId":214742,"corporation":false,"usgs":true,"family":"Hunter","given":"Margaret","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":854800,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70237405,"text":"70237405 - 2022 - Overturning stereotypes: The fuzzy boundary between recreational and subsistence inland fisheries","interactions":[],"lastModifiedDate":"2022-10-12T13:52:58.684473","indexId":"70237405","displayToPublicDate":"2022-06-01T08:41:29","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1652,"text":"Fish and Fisheries","active":true,"publicationSubtype":{"id":10}},"title":"Overturning stereotypes: The fuzzy boundary between recreational and subsistence inland fisheries","docAbstract":"Inland recreational fisheries provide numerous socio- economic benefits to fishers, families and communities. Recreationally harvested fish are also frequently consumed and may provide affordable and sustainable but undervalued contributions to human nutrition. Quantifying the degree to which recreationally harvested fish contribute to food security and subsistence is impeded by lack of data on harvest and consumption and by the difficulty in differentiating among recreational and subsistence fisheries. Recreational harvest records tend to be limited to wealthy, food- secure countries and well- monitored fisheries with clear regulations or permitting systems. These records often neglect components of recreational harvest among food- insecure fishers who are potentially more likely to have consumption as a motivation. Here, we highlight the ‘fuzzy boundary’ that can exist between inland recreational and subsistence fisheries and argue that unreported consumption is likely to be a hidden contributor to food security in some populations. We draw on local case studies from around the world to highlight specific instances where recreationally harvested fish species contribute food and subsistence benefits to participating communities. We use these examples to highlight the diversity of ways that inland recreational fisheries contribute to human nutrition, knowledge gaps in understanding recreational fishing for food, and consequences of not accounting for them as food fisheries in policy and management. The aim of this paper is to draw the attention of resource managers and policy makers, create greater social awareness of the importance of recreational fisheries and bring to light this hidden contribution of inland fisheries to nutrition and subsistence.","language":"English","publisher":"Wiley","doi":"10.1111/faf.12688","usgsCitation":"Nyboer, E.A., Embke, H.S., Robertson, A., Arlinghaus, R., Bower, S., Baigun, C., Beard, T., Cooke, S.J., Cowx, I.G., Koehn, J.D., Lyach, R., Milardi, M., Potts, W.M., and Lynch, A., 2022, Overturning stereotypes: The fuzzy boundary between recreational and subsistence inland fisheries: Fish and Fisheries, v. 23, no. 6, p. 1282-1298, https://doi.org/10.1111/faf.12688.","productDescription":"17 p.","startPage":"1282","endPage":"1298","ipdsId":"IP-135314","costCenters":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":500571,"rank":0,"type":{"id":41,"text":"Open Access External Repository 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The core intent of this project was to provide evidence to support the Teton Area Wildfire Protection Coalition (TAWPC) and affiliated organizations in their wildfire mitigation and education programming. This report analyzes existing wildfire risk data collected in fall 2020 and pairs it with social data collected in the winter and spring of 2021, in order to better understand residents’ knowledge, experiences, and perceptions about wildfire risk. This greater understanding will help TAWPC focus its programs and outreach and ultimately promote increased mitigation and reduced wildfire risk in Teton County. The results of the wildfire risk assessment, covering 725 private residential properties in the study area, suggest that 89% face high, very high, or extreme risk of wildfire. In comparison, only 41% of residents estimated their risk of wildfire to be high, very high, or extreme. This suggests a “gap” between rapid assessment and survey estimates.
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