Premise: Ceanothus (Rhamnaceae) is a large genus of shrubs that dominate California chaparral and are resilient to fires. Persistence is ensured by resprouting and/or seedling recruitment from dormant seed banks. Some species do both and others, the obligate seeders, are entirely dependent on seedling recruitment. The distribution of these two modes within the genus is poorly documented.
Methods: We used all available publications that document species responses to fire and filled most gaps in the literature based on extensive field studies of more than 60 recent wildfires in California.
Results: The genus is divided into two subgenera, Ceanothus and Cerastes. Ceanothus is widely considered to comprise mostly resprouting species and Cerastes to consist of only obligate seeders. The subgenus Ceanothus includes resprouting species throughout their range from the eastern United States and Midwest to western United States. Within the California Floristic Province (CFP), a few species are unique in producing massive lignotubers that develop from repeated fires; however, within the CFP, the majority of species in this subgenus do not resprout and are obligate seeders. Two have disjunct subspecies that are facultative seeders or obligate seeders.
Conclusions: Previously, speciation in this genus was contended to have occurred in the late Miocene within the CFP. The syndrome of obligate seeding is most strongly represented in this region, and we hypothesize that evolution of this syndrome was a response to increased predictability of fire driven by the Mediterranean climate and the long interval between fires.
","language":"English","publisher":"Botanical Society of America","doi":"10.1002/ajb2.16434","usgsCitation":"Keeley, J., Parker, V.T., Zedler, P., and Pratt, R., 2024, Ceanothus: Taxonomic patterns in life history responses to fire: American Journal of Botany, v. 111, no. 11, e16434, https://doi.org/10.1002/ajb2.16434.","productDescription":"e16434","ipdsId":"IP-163254","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":466783,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ajb2.16434","text":"Publisher Index Page"},{"id":464341,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Using remote sensing data and hydrological modeling, the 1-km runoff field simulated by VegET, and routed with mizuRoute, covers over 64,000 river segments in Africa. The VegET model simulates runoff based on vegetation and soil moisture dynamics, while mizuRoute processes this runoff through a detailed river network. Performance metrics show strong model reliability, with R² ranging from 0.5 to 0.9, NSE between 0.6 and 0.9, and KGE from 0.5 to 0.8. The total annual average discharge for Africa is quantified at 3238.1 km³.year-1, with contributions to various oceanic basins: 989.9 km³.year-1 to the North Atlantic, primarily from West African rivers like the Senegal, Gambia, Volta, and Niger; 1313.7 km³.year-1 to the South Atlantic, largely from the Congo River; 212.5 km³.year-1 to the Mediterranean Sea, predominantly from the Nile River; and 722.0 km³.year-1 to the Indian Ocean, with substantial inputs from rivers such as the Zambezi. This VegDischarge v1 is valuable for policymakers, stakeholders, and researchers to better understand water availability, its temporal and spatial variations, that impact water-related infrastructure planning, sustainable resource allocation, and the development of climate resilience mitigation strategies.
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The Adirondack Park in New York is a large, mountainous region with many low nutrient lakes. There is a gap in understanding regarding whether cyanoHAB reporting data are truly reflective of the susceptibility of lakes to develop bloom conditions. We evaluated lakes with and without documented cyanoHABs for cyanotoxin synthetase gene quantification, phytoplankton community composition, and akinete abundance to identify conditions associated with the observation of cyanoHABs. We analyzed: (1) contributions of cyanobacteria to the overall phytoplankton community; (2) differences in cyanobacterial communities and the presence of cyanotoxin synthetase genes; and (3) lake physical and geomorphological attributes as drivers of differences in cyanobacteria occurrence. Two sample types (water and sediment) were collected from two sample locations (nearshore and open water) in five lakes in 2021. We found cyanobacteria in all lakes and sample locations. Phytoplankton biovolume and cyanotoxin synthetase genes differed among lakes and by cyanoHAB history. Samples from lakes with documented blooms were associated with marginally higher total phosphorus. Non-metric multidimensional scaling was used to identify which environmental factors influenced community structure. Our study demonstrates the importance of multifaceted approaches to detect cyanobacteria that may only be apparent during ephemeral bloom events and the similarities among lakes with and without a history of bloom reports. This work contributes to a better understanding of cyanoHAB occurrence in Adirondack lakes, and conditions that may cause low nutrient lakes to be susceptible to cyanoHABs.","language":"English","publisher":"Taylor & Francis Online","doi":"10.1080/10402381.2024.2406283","usgsCitation":"Gorney, R.M., Nystrom, E.A., Stouder, M.D., St. Amand, A.E., Suave, C., Clark, D., Stelzer, E., Givens, C.E., and Graham, J.L., 2024, An evaluation of cyanobacterial occurrence and bloom development in Adirondack lakes: Lake and Reservoir Management, v. 40, no. 4, p. 373-389, https://doi.org/10.1080/10402381.2024.2406283.","productDescription":"17 p.","startPage":"373","endPage":"389","ipdsId":"IP-157540","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":466785,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/10402381.2024.2406283","text":"Publisher Index 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This tool also allows users to conduct a variety of analyses ranging from large-scale data processing and export to detailed and complex flow scenario manipulation around water rights and alternative climate futures.
","language":"English","publisher":"One Water Solutions Institute","doi":"10.25675/10217/239641","usgsCitation":"Wible, T., Holmquist-Johnson, C., Klingel, H., Morrison, R.R., Merritt, D., and Korsa, M., 2024, Environmental Flows for Riverine EcoSystem Habitats (E-FRESH) decision support tool user guide, 74 p., https://doi.org/10.25675/10217/239641.","productDescription":"74 p.","ipdsId":"IP-169441","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":464207,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wible, Tyler","contributorId":346297,"corporation":false,"usgs":false,"family":"Wible","given":"Tyler","email":"","affiliations":[{"id":82824,"text":"CSU One Water Solutions Institute","active":true,"usgs":false}],"preferred":false,"id":918610,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Holmquist-Johnson, Christopher 0000-0002-2782-7687","orcid":"https://orcid.org/0000-0002-2782-7687","contributorId":210644,"corporation":false,"usgs":true,"family":"Holmquist-Johnson","given":"Christopher","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":918611,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Klingel, Heidi","contributorId":346298,"corporation":false,"usgs":false,"family":"Klingel","given":"Heidi","email":"","affiliations":[{"id":36400,"text":"US Forest Service","active":true,"usgs":false}],"preferred":false,"id":918612,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Morrison, Ryan R.","contributorId":198245,"corporation":false,"usgs":false,"family":"Morrison","given":"Ryan","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":918613,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Merritt, David","contributorId":189308,"corporation":false,"usgs":false,"family":"Merritt","given":"David","affiliations":[],"preferred":false,"id":918614,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Korsa, Matthew","contributorId":346299,"corporation":false,"usgs":false,"family":"Korsa","given":"Matthew","email":"","affiliations":[{"id":82824,"text":"CSU One Water Solutions Institute","active":true,"usgs":false}],"preferred":false,"id":918615,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70265940,"text":"70265940 - 2024 - Long-term trends in abundance and potential drivers for eight species of coastal birds in the U.S. South Atlantic","interactions":[],"lastModifiedDate":"2025-04-22T17:18:09.018356","indexId":"70265940","displayToPublicDate":"2024-11-04T12:13:22","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5094,"text":"Regional Studies in Marine Science","onlineIssn":"2352-4855","active":true,"publicationSubtype":{"id":10}},"title":"Long-term trends in abundance and potential drivers for eight species of coastal birds in the U.S. South Atlantic","docAbstract":"The U.S. South Atlantic coastal region is used by many marine birds for foraging, reproduction, and migration. We developed standardized indices of relative abundance from long–term (1980–2016), semi-structured monitoring data (eBird) for eight species: Brown Pelican (Pelecanus occidentalis), Double-Crested Cormorant (Nannopterum auritum), White Ibis (Eudocimus albus), Wood Stork (Mycteria americana), Piping Plover (Charadrius melodus), American Oystercatcher (Haematopus palliatus), Clapper Rail (Rallus crepitans), and Northern Gannet (Morus bassanus). Following a period of stable or declining abundance from the 1980s through the 1990s, most species have shown stable or slightly upward trends through the late 2000s; Brown Pelican and Piping Plover have shown some evidence of recent declines. Species–specific correlations between abundance indices developed from presence/absence data and those developed from count data were positive for all species and ranged from 0.53 to 0.86. Dynamic factor analysis identified common trends in abundance among several species, in particular, Brown Pelican, Double–Crested Cormorant, and White Ibis. Model performance was improved with inclusion of an indicator of sea level rise, but not forage fish abundance or temperature, indicating habitat availability mediated by changing water levels may explain some of the underlying abundance trends. Our results provide baseline information on long–term trends for several important coastal birds that can help inform research, monitoring and conservation efforts in the U.S. South Atlantic region.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rsma.2024.103886","usgsCitation":"Craig, J., Siegfried, K., Cheshire, R., Karnauskas, M., and Jodice, P.G., 2024, Long-term trends in abundance and potential drivers for eight species of coastal birds in the U.S. South Atlantic: Regional Studies in Marine Science, v. 80, 103886, 14 p., https://doi.org/10.1016/j.rsma.2024.103886.","productDescription":"103886, 14 p.","ipdsId":"IP-159778","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":490995,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rsma.2024.103886","text":"Publisher Index Page"},{"id":484853,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida, Georgia, North Carolina, South Carolina","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -80.63812689012559,\n 24.981195366830136\n ],\n [\n -79.74779294326453,\n 26.53588076270711\n ],\n [\n -81.03973835977342,\n 29.95801011198671\n ],\n [\n -81.11631302916135,\n 31.396072044056297\n ],\n [\n -79.30822669011008,\n 33.150807571917255\n ],\n [\n -76.01718491915142,\n 34.68241756177868\n ],\n [\n -75.87971328976948,\n 36.709011056016635\n ],\n [\n -78.23890913908112,\n 36.73325180728209\n ],\n [\n -80.34864182194866,\n 34.55119531258265\n ],\n [\n -83.32101866451728,\n 32.39789594150341\n ],\n [\n -81.81661133200153,\n 28.946064586607065\n ],\n [\n -80.63812689012559,\n 24.981195366830136\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"80","noUsgsAuthors":false,"publicationDate":"2024-11-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Craig, J.K.","contributorId":353621,"corporation":false,"usgs":false,"family":"Craig","given":"J.K.","affiliations":[{"id":36612,"text":"National Marine Fisheries Service","active":true,"usgs":false}],"preferred":false,"id":934109,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Siegfried, K.I.","contributorId":353620,"corporation":false,"usgs":false,"family":"Siegfried","given":"K.I.","affiliations":[{"id":36612,"text":"National Marine Fisheries Service","active":true,"usgs":false}],"preferred":false,"id":934108,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cheshire, R.T.","contributorId":353622,"corporation":false,"usgs":false,"family":"Cheshire","given":"R.T.","affiliations":[{"id":36612,"text":"National Marine Fisheries Service","active":true,"usgs":false}],"preferred":false,"id":934110,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Karnauskas, M.","contributorId":353623,"corporation":false,"usgs":false,"family":"Karnauskas","given":"M.","affiliations":[{"id":36612,"text":"National Marine Fisheries Service","active":true,"usgs":false}],"preferred":false,"id":934111,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jodice, Patrick G.R. 0000-0001-8716-120X","orcid":"https://orcid.org/0000-0001-8716-120X","contributorId":219852,"corporation":false,"usgs":true,"family":"Jodice","given":"Patrick","middleInitial":"G.R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":934112,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70260490,"text":"70260490 - 2024 - The state of the science and practice of stream restoration in the Chesapeake: Lessons learned to inform better implementation, assessment and outcomes","interactions":[],"lastModifiedDate":"2024-11-05T16:47:15.828836","indexId":"70260490","displayToPublicDate":"2024-11-04T10:44:08","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"seriesTitle":{"id":17129,"text":"STAC Workshop Report","active":true,"publicationSubtype":{"id":3}},"seriesNumber":"24-006","title":"The state of the science and practice of stream restoration in the Chesapeake: Lessons learned to inform better implementation, assessment and outcomes","docAbstract":"The Chesapeake Bay Program’s (CBP) Science and Technical Advisory Committee (STAC) organized and led a workshop on the science and practice of stream restoration in order to summarize the state of knowledge in order to identify ways to improve stream restoration outcomes. The workshop identified a general framework for explaining the main factors leading to stream restoration outcomes: stream degradation has occurred, leading to regulatory and policy motivations that prioritize project goals, which leads to restoration approaches, assessment and monitoring efforts, and ultimately stream restoration outcomes. In the Chesapeake Bay watershed, stream restoration often occurs in response to Clean Water Act (CWA) mandates to reduce nitrogen, phosphorus, and sediment loads to the Bay. Reviews of stream restoration outcomes summarized at the workshop showed that, in general, stream restorations have led to minimal improvement to stream aquatic biota, effective ‘stabilization’ of channel form over time, moderate improvements to water quality, and short-term negative impacts to riparian vegetation. \n\n\nThe fundamental finding of the workshop was that often the primary goal of stream restoration projects is to improve geomorphic stability in the restored reach and downstream water quality, and not to improve local ecological conditions through ‘uplift’ (improvement of one or more ecosystem functions through a restorative activity; a term defined in Appendix D), and therefore these projects often do not improve aquatic macroinvertebrate or fish communities. This conflict in goals is a shortcoming of the currently most common regulatory driver for stream restoration (reducing downstream loads of N, P, and sediment) that could be addressed directly through diversifying goals to include biotic uplift, as biological benefit is an assumed condition for the permitting and crediting of stream restoration projects. It is also likely that current understanding of stressors and drivers of stream ecosystem health is insufficient, and that reach-scale restoration focused on geomorphic restoration is not removing the actual sources of stream health impairment that may arise in the upstream watershed. More science could help to identify how to improve the ecological condition of streams through management. The outcome of stream restoration monitoring has revealed that while geomorphic and hydrodynamic functions of stream restoration projects may be achieved, biotic stream function improvements remain elusive. As such, ensuring uplift may be achieved by avoiding restoration projects that risk resources in higher-quality streams and riparian corridors. Reach-scale restoration often does not effectively mitigate the watershed-scale stressors of stream ecosystems. If a desired outcome of stream restoration includes ecological uplift, then focusing efforts on improving stream ecology could help meet that goal.","language":"English","publisher":"Chesapeake Bay Program","collaboration":"Chesapeake Bay Program","usgsCitation":"Noe, G.E., Law, N., Berger, J., Filoso, S., Drescher, S., Fraley-McNeal, L., Hayes, B., Mayer, P., Ruck, C., Stack, B., Starr, R., Stranko, S., and Thompson, T., 2024, The state of the science and practice of stream restoration in the Chesapeake: Lessons learned to inform better implementation, assessment and outcomes: STAC Workshop Report 24-006, 96 p.","productDescription":"96 p.","ipdsId":"IP-169302","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":463690,"rank":1,"type":{"id":15,"text":"Index 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Tributary fidelity can benefit individual fish undergoing spawning migrations by reducing time and energy spent exploring new areas and leveraging previous experience, but anthropogenic activities that fragment or degrade these systems can eliminate those benefits. We used multistate models based on passive integrated transponder (PIT) detection data from 2013 to 2023 to estimate the proportion of flannelmouth suckers (Catostomus latipinnis) migrating to a tributary, McElmo Creek, from the mainstem San Juan River for spawning. Survival varied among years and among states. The top model for migration probability included sex, with males slightly more likely to migrate (0.93 vs 0.90), and the next model identified interannual variation in migration probability ranging from 0.875 to 0.999 across years, indicating high site fidelity. Individuals showed consistency in relative arrival timing across years, with the highest correlation generally during years with greater spring discharge and extended tributary residence time. Successful tributary spawning may be important for the maintenance of the mainstem San Juan River flannelmouth sucker population, but site fidelity may be maladaptive where tributaries are vulnerable to human alterations.
","language":"English","publisher":"Nature","doi":"10.1038/s41598-024-72273-7","usgsCitation":"Bonjour, S.M., Gido, K., Cathcart, C.N., and McKinstry, M.C., 2024, Individual return patterns of spawning flannelmouth sucker (Catostomus latipinnis) to a desert river tributary: Scientific Reports, v. 14, no. 1, 26690, 12 p., https://doi.org/10.1038/s41598-024-72273-7.","productDescription":"26690, 12 p.","ipdsId":"IP-166408","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":466786,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-024-72273-7","text":"Publisher Index Page"},{"id":463698,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Colorado, New Mexico, Utah","otherGeospatial":"Colorado River, McElmo Creek, San Juan River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -112,\n 38\n ],\n [\n -112,\n 36.5\n ],\n [\n -107,\n 36.5\n ],\n [\n -107,\n 38\n ],\n [\n -112,\n 38\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"14","issue":"1","noUsgsAuthors":false,"publicationDate":"2024-11-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Bonjour, Sophia Marie 0000-0003-3614-7023","orcid":"https://orcid.org/0000-0003-3614-7023","contributorId":335936,"corporation":false,"usgs":true,"family":"Bonjour","given":"Sophia","email":"","middleInitial":"Marie","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":917859,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gido, Keith B.","contributorId":341429,"corporation":false,"usgs":false,"family":"Gido","given":"Keith B.","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":917860,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cathcart, Charles N.","contributorId":317814,"corporation":false,"usgs":false,"family":"Cathcart","given":"Charles","email":"","middleInitial":"N.","affiliations":[{"id":7058,"text":"Alaska Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":917861,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McKinstry, Mark C.","contributorId":301155,"corporation":false,"usgs":false,"family":"McKinstry","given":"Mark","email":"","middleInitial":"C.","affiliations":[{"id":65322,"text":"Upper Colorado Regional Office","active":true,"usgs":false}],"preferred":false,"id":917862,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70261908,"text":"70261908 - 2024 - The LTAR cropland Common Experiment at Lower Chesapeake Bay","interactions":[],"lastModifiedDate":"2025-01-02T15:16:01.951758","indexId":"70261908","displayToPublicDate":"2024-11-04T09:04:43","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2262,"text":"Journal of Environmental Quality","active":true,"publicationSubtype":{"id":10}},"title":"The LTAR cropland Common Experiment at Lower Chesapeake Bay","docAbstract":"The Lower Chesapeake Bay (LCB) Long-Term Agroecosystem Research (LTAR) Common Experiment (CE) located in Beltsville, MD, focuses on research of concern to producers of the major regional crops, which are corn (Zea mays L.), soybean [Glycine max (L.) Merr.], wheat (Triticum aestivum L.), and various forage species. Livestock production in the region includes broiler and laying chickens (Gallus gallus domesticus L.) and dairy and beef cattle (Bos taurus L.). The LCB region is among the most heavily populated in the United States. Urban development pressure is high for both farms and natural areas. The need to restore Chesapeake Bay water quality is a major influence on regional agricultural practices. Conservation practices such as cover cropping, no-till agriculture, and nutrient management planning are more common in the region compared to nationally. However, farmers still face management challenges implementing practices that address water quality and the rise of herbicide-resistant weeds. Researchers at the LCB site recognize the need to protect the Chesapeake and Delaware Bays and maintain farmer profitability. The LCB CE compares a 3-year crop rotation system featuring alternative crop management (cover crop intensification, crop rotation diversification, and integrated weed management [IWM]) with a prevailing 2-year system (no cover crops and no IWM), both under continuous no-tillage, to identify the optimal balance to promote the sustainability of regional cropping systems. The LTAR LCB site provides data-driven tools and solutions to support farmers in the mid-Atlantic region.
","language":"English","publisher":"Wiley","doi":"10.1002/jeq2.20650","usgsCitation":"Bagley, G., Ackroyd, V., Cavagielli, M., White, K.E., Schomberg, H., Law, E., Bejleri, K., Hively, W.D., Fischel, M., Maul, J., Hapeman, C., McCarty, G.W., Dulaney, W., Timlin, D., and Mirsky, S., 2024, The LTAR cropland Common Experiment at Lower Chesapeake Bay: Journal of Environmental Quality, v. 53, no. 6, p. 814-822, https://doi.org/10.1002/jeq2.20650.","productDescription":"9 p.","startPage":"814","endPage":"822","ipdsId":"IP-165197","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":498257,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jeq2.20650","text":"Publisher Index Page"},{"id":465609,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, Maryland, New Jersey, Pennsylvania, Virginia","otherGeospatial":"Lower Chesapeake Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -73.9556764775082,\n 40.46153259662566\n ],\n [\n -74.48383881348687,\n 41.10110823458638\n ],\n [\n -75.02078942979834,\n 41.711418167779954\n ],\n [\n -76.9982529856057,\n 39.663312203537316\n ],\n [\n -78.15055555483706,\n 39.27537696005348\n ],\n [\n -79.51486618297113,\n 36.93865143986331\n ],\n [\n -75.88636033588946,\n 36.784474162430556\n ],\n [\n -75.05876660779819,\n 38.620227507492245\n ],\n [\n -74.4488327943047,\n 39.51207480207262\n ],\n [\n -73.9556764775082,\n 40.46153259662566\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"53","issue":"6","noUsgsAuthors":false,"publicationDate":"2024-11-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Bagley, Gwen","contributorId":347693,"corporation":false,"usgs":false,"family":"Bagley","given":"Gwen","affiliations":[{"id":62785,"text":"USDA-ARS Sustainable Agricultural Systems Laboratory","active":true,"usgs":false}],"preferred":false,"id":922233,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ackroyd, Victoria E.P.","contributorId":347696,"corporation":false,"usgs":false,"family":"Ackroyd","given":"Victoria E.P.","affiliations":[{"id":62785,"text":"USDA-ARS Sustainable Agricultural Systems Laboratory","active":true,"usgs":false}],"preferred":false,"id":922236,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cavagielli, Michelle A.","contributorId":347694,"corporation":false,"usgs":false,"family":"Cavagielli","given":"Michelle A.","affiliations":[{"id":62785,"text":"USDA-ARS Sustainable Agricultural Systems Laboratory","active":true,"usgs":false}],"preferred":false,"id":922234,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"White, K. 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Dean 0000-0002-5383-8064","orcid":"https://orcid.org/0000-0002-5383-8064","contributorId":201565,"corporation":false,"usgs":true,"family":"Hively","given":"W.","email":"","middleInitial":"Dean","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":922240,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Fischel, M.H.H.","contributorId":347698,"corporation":false,"usgs":false,"family":"Fischel","given":"M.H.H.","affiliations":[{"id":62785,"text":"USDA-ARS Sustainable Agricultural Systems Laboratory","active":true,"usgs":false}],"preferred":false,"id":922238,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Maul, Jude E.","contributorId":347699,"corporation":false,"usgs":false,"family":"Maul","given":"Jude E.","affiliations":[{"id":62785,"text":"USDA-ARS Sustainable Agricultural Systems Laboratory","active":true,"usgs":false}],"preferred":false,"id":922239,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Hapeman, Cathleen J.","contributorId":347700,"corporation":false,"usgs":false,"family":"Hapeman","given":"Cathleen J.","affiliations":[{"id":65190,"text":"USDA-ARS Hydrology and Remote Sensing Laboratory","active":true,"usgs":false}],"preferred":false,"id":922241,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"McCarty, Gregory W.","contributorId":192367,"corporation":false,"usgs":false,"family":"McCarty","given":"Gregory","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":922242,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Dulaney, Wayne","contributorId":333592,"corporation":false,"usgs":false,"family":"Dulaney","given":"Wayne","email":"","affiliations":[{"id":65190,"text":"USDA-ARS Hydrology and Remote Sensing Laboratory","active":true,"usgs":false}],"preferred":false,"id":922243,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Timlin, Dennis J.","contributorId":347701,"corporation":false,"usgs":false,"family":"Timlin","given":"Dennis J.","affiliations":[{"id":62785,"text":"USDA-ARS Sustainable Agricultural Systems Laboratory","active":true,"usgs":false}],"preferred":false,"id":922244,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Mirsky, Steven B.","contributorId":347702,"corporation":false,"usgs":false,"family":"Mirsky","given":"Steven B.","affiliations":[{"id":62785,"text":"USDA-ARS Sustainable Agricultural Systems Laboratory","active":true,"usgs":false}],"preferred":false,"id":922245,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70265637,"text":"70265637 - 2024 - A new water temperature modeling approach to predict thermal habitat suitability for nonnative cichlids in Florida rivers","interactions":[],"lastModifiedDate":"2025-04-14T15:41:33.931061","indexId":"70265637","displayToPublicDate":"2024-11-03T10:37:41","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2299,"text":"Journal of Freshwater Ecology","active":true,"publicationSubtype":{"id":10}},"title":"A new water temperature modeling approach to predict thermal habitat suitability for nonnative cichlids in Florida rivers","docAbstract":"As global temperatures increase, the spatiotemporal arrangement of thermal habitats in Florida rivers may shift, creating the potential for greater dispersal and establishment of nonnative tropical freshwater fishes. To understand how water temperature changes may affect the spatial distribution of these nonnative species, more effective water temperature prediction models are necessary. Currently, most models employ either a generalized air–water temperature relationship or require expensive and complicated tools to measure hydrometeorological factors (e.g. groundwater input). Thus, we developed a novel modeling approach that is accurate, accessible, and cost-effective in allowing fisheries managers to project water temperatures in rivers across Central and North Florida. To characterize the potential for nonnative fishes to spread northward, we evaluated two hardy and abundant species currently found primarily in South Florida: Mayan Cichlid (Mayaheros urophthalmus) and Oscar (Astronotus ocellatus). Our results show an increase in thermally suitable winter days for both species in 10 of 11 rivers studied, consistent with predicted water temperature warming under 16 climate-change scenarios spanning different levels of air temperature warming (+1 °C, +2 °C, +3 °C, +4 °C) and precipitation/groundwater thermal sensitivity (0, 0.33, 0.66, 1). Considering resource limitations, fisheries managers can use our water temperature modeling approach to predict effects of climate change on Mayan Cichlid and Oscar survival, growth, and dispersal and take actions to manage potential northward movement of these species.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/02705060.2024.2405721","usgsCitation":"Scott, A., and Carlson, A.K., 2024, A new water temperature modeling approach to predict thermal habitat suitability for nonnative cichlids in Florida rivers: Journal of Freshwater Ecology, v. 39, no. 1, 2405721, 24 p., https://doi.org/10.1080/02705060.2024.2405721.","productDescription":"2405721, 24 p.","ipdsId":"IP-166869","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":488211,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/02705060.2024.2405721","text":"Publisher Index Page"},{"id":484504,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"39","issue":"1","noUsgsAuthors":false,"publicationDate":"2024-11-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Scott, Alexandra M.","contributorId":353193,"corporation":false,"usgs":false,"family":"Scott","given":"Alexandra M.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":933153,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carlson, Andrew Kenneth 0000-0002-6681-0853","orcid":"https://orcid.org/0000-0002-6681-0853","contributorId":340581,"corporation":false,"usgs":true,"family":"Carlson","given":"Andrew","email":"","middleInitial":"Kenneth","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":933154,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70260841,"text":"70260841 - 2024 - The chlorine evolution of arc magmas and the crustal water filter","interactions":[],"lastModifiedDate":"2024-11-12T15:23:22.565635","indexId":"70260841","displayToPublicDate":"2024-11-02T09:20:52","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"The chlorine evolution of arc magmas and the crustal water filter","docAbstract":"Degassing of water from magmatic systems is key to transporting metals from magmas to form ore deposits, but elements like chlorine, through the formation of anion complexes, can be important in solubilizing and mobilizing these metals into water-rich fluids. Reconstructing the Cl systematics of evolving magmas is thus an important step towards understanding the origins of ore deposits, but the magmatic record is not well preserved because Cl can be lost during degassing. Here, we reconstruct the pre-degassing history of Cl in subduction zone (arc) magmas through amphiboles, which incorporate Cl directly into their crystal structures, preserving pre-eruptive magmatic signatures. Amphibole-reconstructed Cl contents indicate that magmatic differentiation can lead to a 4-fold increase in concentration due to Cl's incompatible behavior. The amphibole-reconstructed Cl contents of arc magmas are also significantly higher than values reported from melt inclusions, suggesting that many melt inclusions may have been trapped after magmas had already lost some Cl. We show that such Cl loss is likely associated with preferential partitioning of Cl into hydrous fluids degassed from the magma during crustal storage or ascent. The extent of Cl depletion can thus be used to estimate how much water was lost during early degassing. If Cl is important to certain ore deposits, magmatic water content may play an indirect role. Magmas too rich in water will lose water and hence Cl at greater depths, rendering such magmas less able to transport metals to the upper crust. By contrast, drier magmas may not produce enough Cl-rich fluids to mobilize metals. Thus, magmas with intermediate water contents may produce enough Cl-rich fluids at the right depths for certain types of ore deposits.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2024.119048","usgsCitation":"Borchardt, J.S., and Lee, C., 2024, The chlorine evolution of arc magmas and the crustal water filter: Earth and Planetary Science Letters, v. 648, 119048, 9 p., https://doi.org/10.1016/j.epsl.2024.119048.","productDescription":"119048, 9 p.","ipdsId":"IP-167774","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":489865,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.epsl.2024.119048","text":"Publisher Index Page"},{"id":463871,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"648","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Borchardt, Jackson Stone 0000-0001-6891-3314","orcid":"https://orcid.org/0000-0001-6891-3314","contributorId":346157,"corporation":false,"usgs":true,"family":"Borchardt","given":"Jackson","email":"","middleInitial":"Stone","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":918266,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lee, Cin-Ty","contributorId":346158,"corporation":false,"usgs":false,"family":"Lee","given":"Cin-Ty","email":"","affiliations":[{"id":7173,"text":"Rice University","active":true,"usgs":false}],"preferred":false,"id":918267,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70263176,"text":"70263176 - 2024 - Exploring the dynamic interactions between the Southern San Andreas Fault and a normal fault under the Salton Sea","interactions":[],"lastModifiedDate":"2025-01-31T15:08:50.504738","indexId":"70263176","displayToPublicDate":"2024-11-02T08:00:40","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6453,"text":"Journal of Geophysical Research Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Exploring the dynamic interactions between the Southern San Andreas Fault and a normal fault under the Salton Sea","docAbstract":"We investigate the dynamic interactions between the Southern San Andreas Fault (SSAF) and a proximal normal fault (NF) beneath the Salton Sea in southern California. The NF, positioned near the SSAF terminus at Bombay Beach, exhibits 11–15 displacement events across 14 stratigraphic sequences, with a range of 0.2–1.4 m of vertical offset since ∼2–3 ka. Notably, four of these events may align temporally with SSAF earthquakes, raising questions about the possible interplay between the two faults. Utilizing dynamic rupture models, we analyze the coseismic interactions between the SSAF and NF, addressing under what conditions the SSAF induces slip on the NF. Our findings reveal that a suite of SSAF ruptures, particularly those propagating from north to south, can trigger slip on the normal fault and replicate observed vertical offsets. If the SSAF extends beneath the Salton Sea, earthquakes originating south of the NF intersection are less likely to trigger normal fault slip, although we cannot exclude this possibility. Some SSAF ruptures do not trigger discernible slip on the NF, rendering such events undetectable in the stratigraphic record. Our research contributes toward discussions regarding the seismic hazard in southern California, shedding light on the interplay between the SSAF and NF.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2023JB028621","usgsCitation":"Flores, L., Kyriakopoulos, C., Oglesby, D., Meltzner, A., Rockwell, T., Fletcher, J., and Brothers, D., 2024, Exploring the dynamic interactions between the Southern San Andreas Fault and a normal fault under the Salton Sea: Journal of Geophysical Research Solid Earth, v. 129, no. 11, e2023JB028621, 27 p., https://doi.org/10.1029/2023JB028621.","productDescription":"e2023JB028621, 27 p.","ipdsId":"IP-167490","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":481545,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Salton Sea, Southern San Andreas Fault","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.65460420209196,\n 33.84881697934365\n ],\n [\n -115.60752481012484,\n 32.705792541668316\n ],\n [\n -115.09341127848316,\n 32.71621614794114\n ],\n [\n -116.0942650348575,\n 33.93798453809697\n ],\n [\n -116.65460420209196,\n 33.84881697934365\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"129","issue":"11","noUsgsAuthors":false,"publicationDate":"2024-11-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Flores, Luis Ivan Bazan","contributorId":350339,"corporation":false,"usgs":false,"family":"Flores","given":"Luis Ivan Bazan","affiliations":[{"id":17864,"text":"University of Memphis","active":true,"usgs":false}],"preferred":false,"id":925784,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kyriakopoulos, Christodoulos","contributorId":350340,"corporation":false,"usgs":false,"family":"Kyriakopoulos","given":"Christodoulos","affiliations":[{"id":17864,"text":"University of Memphis","active":true,"usgs":false}],"preferred":false,"id":925785,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Oglesby, David D.","contributorId":350341,"corporation":false,"usgs":false,"family":"Oglesby","given":"David D.","affiliations":[{"id":12655,"text":"University of California, Riverside","active":true,"usgs":false}],"preferred":false,"id":925786,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Meltzner, Aron J.","contributorId":350342,"corporation":false,"usgs":false,"family":"Meltzner","given":"Aron J.","affiliations":[{"id":16631,"text":"Nanyang Technological University","active":true,"usgs":false}],"preferred":false,"id":925787,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rockwell, Thomas K.","contributorId":350343,"corporation":false,"usgs":false,"family":"Rockwell","given":"Thomas K.","affiliations":[{"id":6608,"text":"San Diego State University","active":true,"usgs":false}],"preferred":false,"id":925788,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fletcher, John M.","contributorId":350344,"corporation":false,"usgs":false,"family":"Fletcher","given":"John M.","affiliations":[{"id":82505,"text":"Centro de Investigación Científica y de Educación Superior de Ensenada","active":true,"usgs":false}],"preferred":false,"id":925789,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Brothers, Daniel S. 0000-0001-7702-157X","orcid":"https://orcid.org/0000-0001-7702-157X","contributorId":210199,"corporation":false,"usgs":true,"family":"Brothers","given":"Daniel S.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":925790,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70260170,"text":"sim3521 - 2024 - Geologic map of the southern Stillwater Range, Nevada","interactions":[],"lastModifiedDate":"2025-07-23T16:57:56.517005","indexId":"sim3521","displayToPublicDate":"2024-11-01T14:25:00","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3521","displayTitle":"Geologic Map of the Southern Stillwater Range, Nevada","title":"Geologic map of the southern Stillwater Range, Nevada","docAbstract":"The southern Stillwater Range in west-central Nevada contains the western part of the Oligocene Stillwater-Clan Alpine caldera complex, which extends about 55 kilometers (km) east from the west side of the Stillwater Range to the northwestern Desatoya Mountains. The complex consists of at least seven nested ignimbrite calderas and subjacent plutonic rocks emplaced into a complex basement composed of Mesozoic metasedimentary and metavolcanic rocks and Cretaceous granitic plutons. The calderas formed during large-volume (100s to greater than (>) 2,500 cubic kilometers [km3]) eruptions of silicic ignimbrites between about 30.4 and 25.1 million years before present (Ma). The Job Canyon and Poco Canyon calderas and the western part of the much larger Elevenmile Canyon caldera, and their plutonic roots, are exposed in the southern Stillwater Range. There, the caldera complex was steeply tilted during large-magnitude crustal extension in the middle Miocene, and further exhumed during the late Miocene to Holocene Basin and Range extension that formed the modern Stillwater Range. This tilted crustal section affords an exceptional opportunity to view structural cross sections of ignimbrite calderas and their plutonic roots to paleodepths as much as 9–10 km.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sim3521","collaboration":"Prepared in cooperation with the Nevada Bureau of Mines and Geology","programNote":"National Cooperative Geologic Mapping Program","usgsCitation":"John, D.A., Colgan, J.P., Berry, M.E., Henry, C.D., and Silberling, N.J., 2024, Geologic map of the southern Stillwater Range, Nevada: U.S. Geological Survey Scientific Investigations Map 3521, 2 sheets, scale 1:24,000, 39-p. pamphlet, https://doi.org/10.3133/sim3521.","productDescription":"Report: iv, 39 p.; 3 Sheets: 42.23 x 64.92 inches or smaller; 2 Data Releases","ipdsId":"IP-123012","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":463560,"rank":9,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sim/3521/sim3521.xml"},{"id":463559,"rank":8,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sim/3521/images"},{"id":463384,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7P26X2V","text":"USGS data release","linkHelpText":"Geochemical and geochronologic data from the Stillwater Range, Clan Alpine, and Desatoya Mountains, Nevada (ver. 3.0, December 2023)"},{"id":463383,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WW1EUF","text":"USGS data release","linkHelpText":"Digital database of the geologic map of the southern Stillwater Range, Nevada"},{"id":463382,"rank":5,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3521/sim3521_sheet2.pdf","text":"Sheet 2—Correlation and list of map units and explanation of map symbols","size":"524 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Sheet 2"},{"id":463381,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3521/sim3521_sheet1-geospatial.pdf","text":"Sheet 1— Georeferenced geologic map","size":"16.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3521 sheet 1 geospatial"},{"id":463380,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3521/sim3521_sheet1.pdf","text":"Sheet 1—Geologic map","size":"15.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3521 sheet 1"},{"id":463379,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3521/sim3521_pamphlet.pdf","text":"Pamphlet","size":"2.74 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3521 pamphlet"},{"id":483247,"rank":10,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sim/3521/versionHist.txt","text":"Version History","size":"4.0 KB","linkFileType":{"id":2,"text":"txt"},"description":"SIM 3521 version history"},{"id":463378,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3521/coverthb2.jpg"},{"id":492781,"rank":11,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117751.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Nevada","otherGeospatial":"Southern Stillwater Range","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -118.5,\n 39.75\n ],\n [\n -118.5,\n 39.375\n ],\n [\n -118,\n 39.375\n ],\n [\n -118,\n 39.75\n ],\n [\n -118.5,\n 39.75\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Version 1.0: November 1, 2024; Version 1.1: March 12, 2025","contact":"Director, Geosciences and Environmental Change Science Center
U.S. Geological Survey
Box 25046, MS-980
Denver, CO 80225-0046
More than 2 million Californians rely on groundwater from privately owned domestic wells for drinking-water supply. This report summarizes a water-quality survey of domestic and small-system drinking-water supply wells in the eastern Sacramento Valley and adjacent foothills where more than 25,000 residents are estimated to use privately owned domestic wells. Study results show that inorganic and organic constituents in groundwater were present above regulatory (maximum contaminant level, MCL) benchmarks for public drinking-water quality in 8 and 3 percent, respectively, of the aquifer area used for domestic drinking-water supply (herein, “domestic groundwater resources”; fig. 1).
The only inorganic constituent detected above regulatory benchmarks was arsenic. The only organic constituent exceeding regulatory benchmarks was the fumigant 1,2,3-trichloropropane (1,2,3-TCP). Three additional organic constituents—the disinfection by-product chloroform, the gasoline oxygenate methyl tert-butyl ether (MTBE), and the solvent tetrachloroethene (PCE)—were detected at low concentrations below one-tenth of regulatory benchmarks in 34, 10, and 10 percent of domestic groundwater resources, respectively. Total dissolved solids (TDS), iron, and manganese exceeded non-regulatory aesthetic guidelines for drinking water in 5, 10, and 26 percent of domestic groundwater resources, respectively. Per- and polyfluoroalkyl substances (PFASs) were detected in 29 percent of domestic groundwater resources,with 5 percent exceeding the recently enacted (April 2024) U.S. Environmental Protection Agency MCLs. Total coliform and enterococci bacteria were detected in 13 and 8 percent of domestic groundwater resources, respectively.
Redox sensitive constituents in this study included arsenic, manganese, nitrate, and iron. In the lower elevation portions of the eastern Sacramento Valley study area, reducing conditions in groundwater aquifers promote elevated arsenic, iron, and manganese, and conversely lower concentrations of nitrate. The presence of the volatile organic compound (VOC) 1,2,3-TCP was related to its past history in select agricultural land uses (on orchards or vineyards) in the Sacramento Valley; however, unlike in the San Joaquin Valley where orchards and vineyards are more common, its detection frequency was low (only detected in one well in this study). Chloroform was frequently detected in this study at low levels. Chloroform is a disinfection byproduct commonly found in domestic wells treated by shock chlorination. The solvent PCE is among the most frequently detected VOCs in groundwater, which is primarily related to its long history of use and its persistence in groundwater in oxic conditions. The gasoline oxygenate MTBE was a contaminant introduced to groundwater through atmospheric exchange when it was used as a fuel additive to decrease smog inducing emissions from vehicles. Its occurrence in groundwater at low levels is expected and makes it a potentially useful tracer of relatively recent recharge water being withdrawn from wells. The PFASs are anthropogenic chemicals with hundreds of uses, and they have been incorporated into many different products, processes, and applications worldwide. Like MTBE, the occurrence of PFASs in groundwater may be in part due to atmospheric exchange, but there are several other pathways that contribute PFASs to the environment.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241061","collaboration":"Prepared in cooperation with California State Water Resources Control Board","usgsCitation":"Bennett, G.L., V, 2024, Quality of groundwater used for domestic supply in the eastern Sacramento Valley and adjacent foothills, California: U.S. Geological Survey Open-File Report 2024–1061, 15 p., https://doi.org/10.3133/ofr20241061.","productDescription":"15 p.","numberOfPages":"15","onlineOnly":"Y","ipdsId":"IP-150528","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":497891,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117769.htm","linkFileType":{"id":5,"text":"html"}},{"id":463494,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1061/images"},{"id":463493,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1061/ofr20241061.xml"},{"id":463495,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241061/full"},{"id":463492,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1061/ofr20241061.pdf","text":"Report","size":"10 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":463491,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1061/covrthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Eastern Sacramento Valley and adjacent foothills","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.25,\n 40\n ],\n [\n -122.25,\n 38.666\n ],\n [\n -120.5,\n 38.666\n ],\n [\n -120.5,\n 40\n ],\n [\n -122.25,\n 40\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
Context
Soil resource heterogeneity drives plant species diversity patterns at local and landscape scales. In drylands, biocrusts are patchily distributed and contribute to soil resource heterogeneity important for plant establishment and growth. Yet, we have a limited understanding of how such heterogeneity may relate to patterns of plant diversity and community structure.
Objectives
We explored relationships between biocrust-associated soil cover heterogeneity and plant diversity patterns in a cool desert ecosystem. We asked: (1) does biocrust-associated soil cover heterogeneity predict plant diversity and community composition? and (2) can we use high-resolution remote sensing data to calculate soil cover heterogeneity metrics that could be used to extrapolate these patterns across landscapes?
Methods
We tested associations among field-based measures of plant diversity and soil cover heterogeneity. We then used a Support Vector Machine classification to map soil, plant and biocrust cover from sub-centimeter resolution Unoccupied Aerial System (UAS) imagery and compared the mapped results to field-based measures.
Results
Field-based soil cover heterogeneity and biocrust cover were positively associated with plant diversity and predicted community composition. The accuracy of UAS-mapped soil cover classes varied across sites due to variation in timing and quality of image collections, but the overall results suggest that UAS are a promising data source for generating detailed, spatially explicit soil cover heterogeneity metrics.
Conclusions
Results improve understanding of relationships between biocrust-associated soil cover heterogeneity and plant diversity and highlight the promise of high-resolution UAS data to extrapolate these patterns over larger landscapes which could improve conservation planning and predictions of dryland responses to soil degradation under global change.
Since the onset of the COVID-19 pandemic in early 2020, people have experienced food insecurity challenges because of increased prices of staple food commodities and loss of income or livelihood. Globally, countries with limited capacity to adapt have struggled to recover from pandemic-related disruptions and are further challenged to address adverse effects of climate change on agricultural production (United Nations [UN], 2022). Ukraine, a key agricultural exporter of staple food commodities, has a vital role in contributing to global food security, in particular through its wheat exports to countries in the Middle East, North Africa, and Europe (Martyshev and others, 2023). However, Ukraine’s role as a stable source of global wheat has been disrupted by the ongoing Russia-Ukraine war—a conflict which began in February of 2022.
Given the fragile state of global and local markets and food systems, and the increasing risk climate change poses to agricultural production globally, Ukraine has prioritized adopting efficient agricultural practices to contribute to stabilizing crop yields and to increase its capacity to export wheat and other staple crops. According to Ukraine’s Ministry of Agrarian Policy and Food (MINAGRO), along with addressing climate change, a contributing driver for this prioritization is the desire to join the European Union (EU) and the need to meet the requirements for the EU’s Common Agricultural Policy (CAP) for acceptance as a union member state (Markiyan Dmytrasevych, a former deputy minister of MINAGRO, oral commun., 2023). As a result, MINAGRO is considering climate-smart agricultural practices to secure future crop yields and build resilience within its agricultural sector, especially as the war has impeded millions of tons of crops from reaching domestic and global markets. This report employs the climate-smart agriculture framework to provide Ukrainian agricultural policy- and decision makers and others in technical and development assistance roles with an overview of relevant climate, environmental, and agricultural policy and market factors, and projections on climate and environmental resources that could influence the implementation of climate-smart agricultural practices in Ukraine, and aid Ukraine in successfully joining the EU.
","language":"English","publisher":"Department of Interior International Technical Assistance Program (DOI ITAP)","usgsCitation":"Romero, V., Schultz, A.R., Powlen, K., and Shah, S.D., 2024, Climate-smart agriculture for Ukraine: Winter wheat breeding for food security and climate adaptation, 62 p.","productDescription":"62 p.","ipdsId":"IP-160321","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":465376,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.doi.gov/media/document/report-agriculture-ukraine-winter-wheat-breeding-food-security-and-climate"},{"id":465406,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Ukraine","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[31.786,52.10168],[32.15941,52.06127],[32.41206,52.28869],[32.71576,52.23847],[33.7527,52.33507],[34.39173,51.76888],[34.14198,51.56641],[34.22482,51.25599],[35.02218,51.20757],[35.37792,50.77396],[35.35612,50.5772],[36.62617,50.22559],[37.39346,50.38395],[38.01063,49.91566],[38.59499,49.92646],[40.06906,49.60106],[40.08079,49.30743],[39.67466,48.78382],[39.89563,48.23241],[39.73828,47.89894],[38.77058,47.82561],[38.25511,47.5464],[38.22354,47.10219],[37.42514,47.02222],[36.75985,46.6987],[35.82368,46.64596],[34.96234,46.2732],[35.02079,45.65122],[35.51001,45.40999],[36.53,45.46999],[36.33471,45.11322],[35.24,44.94],[33.88251,44.36148],[33.32642,44.56488],[33.54692,45.03477],[32.45417,45.32747],[32.6308,45.51919],[33.58816,45.85157],[33.29857,46.0806],[31.74414,46.33335],[31.67531,46.70625],[30.74875,46.5831],[30.37761,46.03241],[29.60329,45.29331],[29.14972,45.46493],[28.67978,45.30403],[28.23355,45.48828],[28.48527,45.59691],[28.65999,45.93999],[28.93372,46.25883],[28.86297,46.43789],[29.07211,46.51768],[29.17065,46.37926],[29.75997,46.34999],[30.02466,46.42394],[29.83821,46.52533],[29.90885,46.67436],[29.55967,46.92858],[29.41514,47.34665],[29.05087,47.51023],[29.1227,47.8491],[28.67089,48.11815],[28.25955,48.15556],[27.52254,48.46712],[26.85782,48.36821],[26.61934,48.22073],[26.19745,48.22088],[25.94594,47.98715],[25.20774,47.89106],[24.86632,47.73753],[24.40206,47.98188],[23.76096,47.9856],[23.14224,48.09634],[22.71053,47.88219],[22.64082,48.15024],[22.08561,48.42226],[22.28084,48.82539],[22.55814,49.08574],[22.77642,49.0274],[22.51845,49.47677],[23.42651,50.30851],[23.92276,50.42488],[24.02999,50.70541],[23.52707,51.57845],[24.00508,51.61744],[24.55311,51.88846],[25.32779,51.91066],[26.33796,51.83229],[27.45407,51.5923],[28.24162,51.57223],[28.61761,51.42771],[28.99284,51.60204],[29.25494,51.36823],[30.15736,51.41614],[30.55512,51.3195],[30.61945,51.82281],[30.92755,52.04235],[31.786,52.10168]]]},\"properties\":{\"name\":\"Ukraine\"}}]}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Romero, Veronica 0000-0002-8124-4386","orcid":"https://orcid.org/0000-0002-8124-4386","contributorId":302660,"corporation":false,"usgs":true,"family":"Romero","given":"Veronica","email":"","affiliations":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":921606,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schultz, August Raleigh 0000-0002-5016-827X","orcid":"https://orcid.org/0000-0002-5016-827X","contributorId":302948,"corporation":false,"usgs":true,"family":"Schultz","given":"August","email":"","middleInitial":"Raleigh","affiliations":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":921607,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Powlen, Kathryn 0000-0002-9685-0063","orcid":"https://orcid.org/0000-0002-9685-0063","contributorId":328833,"corporation":false,"usgs":true,"family":"Powlen","given":"Kathryn","email":"","affiliations":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":921608,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shah, Sachin D. 0000-0002-5440-5535 sdshah@usgs.gov","orcid":"https://orcid.org/0000-0002-5440-5535","contributorId":194450,"corporation":false,"usgs":true,"family":"Shah","given":"Sachin","email":"sdshah@usgs.gov","middleInitial":"D.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":921609,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70274748,"text":"70274748 - 2024 - Converting non-standard data to standardized data","interactions":[],"lastModifiedDate":"2026-04-08T15:46:07.107982","indexId":"70274748","displayToPublicDate":"2024-11-01T10:45:22","publicationYear":"2024","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"16","title":"Converting non-standard data to standardized data","docAbstract":"Fishery biologists spend considerable effort over multiple years collecting data on fish population and community status using a particular sampling method or set of methods. However, new (and often more effective) sampling methods and technologies are continuously being developed. To incorporate these new sampling techniques, fishery biologists need a means for converting fish sampling data collected using old methods so that they can be compared with data collected using new sampling methods. Similarly, fishery biologists often need a means to compare fish sampling data collected using the same method over time (e.g., from year to year) and space (e.g., between sample sites). If fish abundance, species presence, or richness are estimated using an unbiased statistical estimator (e.g., occupancy estimation, capture-recapture estimation), the estimates can be validly compared even if the fish sample data were collected with different methods. However, if unbiased statistical estimators were not used, biologists need methods for adjusting fish sampling data collected using different methods or using the same method collected under different sampling conditions. In this chapter, we describe and provide examples of statistical techniques for converting nonstandard fish sampling data to American Fisheries Society (AFS) standardized data and for making comparisons of fish sampling data collected at different times or at different locations. We define standard fish sampling data as data collected using the standardized fish sampling methods described throughout this book. Any other sampling methods and associated data are thus defined as nonstandard. Before delving into the details of the techniques that can be used to convert data, we describe the nature of fish sample data, their uses, and their limitations.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Standard methods for sampling North American freshwater fishes","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"American Fisheries Society","doi":"10.47886/9781934874769.ch16","usgsCitation":"Peterson, J.T., de Kerckhove, D.T., Giacomini, H.C., and Paukert, C., 2024, Converting non-standard data to standardized data, chap. 16 of Standard methods for sampling North American freshwater fishes, https://doi.org/10.47886/9781934874769.ch16.","ipdsId":"IP-132428","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":502279,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Peterson, James T. 0000-0002-7709-8590 james_peterson@usgs.gov","orcid":"https://orcid.org/0000-0002-7709-8590","contributorId":2111,"corporation":false,"usgs":true,"family":"Peterson","given":"James","email":"james_peterson@usgs.gov","middleInitial":"T.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":958909,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"de Kerckhove, Derrick T.","contributorId":369387,"corporation":false,"usgs":false,"family":"de Kerckhove","given":"Derrick","middleInitial":"T.","affiliations":[{"id":16762,"text":"Ontario Ministry of Natural Resources and Forestry","active":true,"usgs":false}],"preferred":false,"id":958910,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Giacomini, Henrique C.","contributorId":369388,"corporation":false,"usgs":false,"family":"Giacomini","given":"Henrique","middleInitial":"C.","affiliations":[{"id":16762,"text":"Ontario Ministry of Natural Resources and Forestry","active":true,"usgs":false}],"preferred":false,"id":958911,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Paukert, Craig 0000-0002-9369-8545","orcid":"https://orcid.org/0000-0002-9369-8545","contributorId":268045,"corporation":false,"usgs":true,"family":"Paukert","given":"Craig","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":958912,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70274732,"text":"70274732 - 2024 - Coldwater fish in wadeable streams","interactions":[],"lastModifiedDate":"2026-04-09T13:35:34.103086","indexId":"70274732","displayToPublicDate":"2024-11-01T10:29:27","publicationYear":"2024","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"8","title":"Coldwater fish in wadeable streams","docAbstract":"Although we are consistent with the past edition of this volume regarding standard sampling techniques for wadeable, coldwater streams, this edition reflects recent literature, advances in calibrating numbers, and obtaining lengths of fish collected and provides additional clarity regarding effort. We also specify a minimum of two netters and one electrofisher operator for backpack electrofishing to allow capture of fish that “roll” downstream without surfacing (e.g., fish like sculpins, which lack swim bladders); however, as in the past edition, a minimum of one netter and one operator may be used on studies focused on fish with swim bladders, like salmonids (salmons and trouts). Finally, this chapter mentions specifically what factors should lead to standard adjustments to techniques to account for the range of habitat features typically encountered in headwater streams.
Small, wadeable streams comprise most habitats available to fish in fluvial networks. Wadeable streams are generally less than 1 m deep, and fish can be sampled without the use of float craft. Cold waters are generally defined as having mean 7-d summer maximum water temperatures less than 20°C, providing habitat for coldwater fishes.
Fish fauna of small, coldwater North American streams typically include salmonids, sculpins, minnows, sticklebacks, suckers, or lampreys (Hocutt and Wiley 1986). Standard sampling protocols provided herein apply most readily to salmonids because of their sport and commercial values (Johnson et al. 2007). Salmonids also have cultural values, are well studied and widely distributed, and act as predators, competitors, and prey (Lee et al. 1997). However, many of these methods can also be applied effectively to sample nonsalmonids. As interest in nonsalmonid species grows, further development and investigation of sampling methods for a broader diversity of species is expected (see section 8.5).
","language":"English","publisher":"American Fisheries Society","doi":"10.47886/9781934874769.ch8","usgsCitation":"Falke, J.A., Dunham, J., Rosenberger, A.E., Thurow, R.F., Dolloff, A., Howell, P.J., and Saunders, W.C., 2024, Coldwater fish in wadeable streams, https://doi.org/10.47886/9781934874769.ch8.","ipdsId":"IP-135033","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":502277,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Falke, Jeffrey A. 0000-0002-6670-8250 jfalke@usgs.gov","orcid":"https://orcid.org/0000-0002-6670-8250","contributorId":5195,"corporation":false,"usgs":true,"family":"Falke","given":"Jeffrey","email":"jfalke@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":958875,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dunham, Jason 0000-0002-6268-0633","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":220078,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":958876,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rosenberger, Amanda E. 0000-0002-5520-8349 arosenberger@usgs.gov","orcid":"https://orcid.org/0000-0002-5520-8349","contributorId":5581,"corporation":false,"usgs":true,"family":"Rosenberger","given":"Amanda","email":"arosenberger@usgs.gov","middleInitial":"E.","affiliations":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":958877,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thurow, Russell F.","contributorId":369327,"corporation":false,"usgs":false,"family":"Thurow","given":"Russell","middleInitial":"F.","affiliations":[{"id":36226,"text":"U.S. Department of Agriculture Forest Service","active":true,"usgs":false}],"preferred":false,"id":958878,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dolloff, Andrew","contributorId":369328,"corporation":false,"usgs":false,"family":"Dolloff","given":"Andrew","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":958879,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Howell, Philip J.","contributorId":369329,"corporation":false,"usgs":false,"family":"Howell","given":"Philip","middleInitial":"J.","affiliations":[{"id":36226,"text":"U.S. Department of Agriculture Forest Service","active":true,"usgs":false}],"preferred":false,"id":958880,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Saunders, W. Carl","contributorId":369330,"corporation":false,"usgs":false,"family":"Saunders","given":"W.","middleInitial":"Carl","affiliations":[{"id":36226,"text":"U.S. Department of Agriculture Forest Service","active":true,"usgs":false}],"preferred":false,"id":958881,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70274726,"text":"70274726 - 2024 - An introduction to standardized sampling","interactions":[],"lastModifiedDate":"2026-04-08T15:23:31.605172","indexId":"70274726","displayToPublicDate":"2024-11-01T10:18:25","publicationYear":"2024","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"1","title":"An introduction to standardized sampling","docAbstract":"In 2009, the first edition of Standard Methods for Sampling North American Freshwater Fishes was published. This was the first time in the history of fisheries science that standardization of methods and equipment had taken place on such a large geographic scale. Since its publication, the methods have been used extensively across North America by local, state, and federal agencies, organizations, and universities who have seen the advantages of large-scale data comparison. Authors have been invited to present these methods in other locations around the world to help with standard sampling programs on other continents. Now, with large-scale issues such as human-caused climate change, effects of landscape-scale regulations, and effects of habitat degradation continuing to increase in importance, the ability to compare data across wide regions and political boundaries, compare data over time, and collect data with improved accuracy and precision is more important than ever. This new edition of Standard Methods is sponsored by the American Fisheries Society (AFS), the U.S. Fish and Wildlife Service, and the Association of Fish and Wildlife Agencies (AFWA), with contributions by numerous state, provincial and federal agencies, and numerous academic institutions and nongovernmental organizations (NGOs). It is authored by over 100 experts in fisheries sampling from across Canada, Mexico, and the United States. Most techniques for water body types addressed in the first edition have been kept the same-in the interest of standardization over time; however, many important additions have been made.
Like the first edition, these methods are designed for fish community assessments in North American aquatic systems (e.g., for this edition, lakes, ponds, rivers, and streams containing warmwater and coldwater species; the Great Lakes, wetlands, and cenotes). Although other methods may be available that better target a more specific size-group or species, these techniques were selected as most effective for general surveys of these systems and typically are the most effective for capturing the common fishes found in these waters.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Standard methods for sampling North American freshwater fishes","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"American Fisheries Society","doi":"10.47886/9781934874769.ch1","usgsCitation":"Bonar, S.A., Conroy, J.D., Contreras-Balderas, S., and Iles, A.C., 2024, An introduction to standardized sampling, chap. 1 of Standard methods for sampling North American freshwater fishes, p. 1-22, https://doi.org/10.47886/9781934874769.ch1.","productDescription":"22 p.","startPage":"1","endPage":"22","ipdsId":"IP-152853","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":502275,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"Second edition","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bonar, Scott A. 0000-0003-3532-4067 sbonar@usgs.gov","orcid":"https://orcid.org/0000-0003-3532-4067","contributorId":3712,"corporation":false,"usgs":true,"family":"Bonar","given":"Scott","email":"sbonar@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":958864,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conroy, Joseph D.","contributorId":145527,"corporation":false,"usgs":false,"family":"Conroy","given":"Joseph","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":958865,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Contreras-Balderas, Salvador","contributorId":35956,"corporation":false,"usgs":true,"family":"Contreras-Balderas","given":"Salvador","email":"","affiliations":[],"preferred":false,"id":958866,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Iles, Alison C.","contributorId":369326,"corporation":false,"usgs":false,"family":"Iles","given":"Alison","middleInitial":"C.","affiliations":[],"preferred":false,"id":958867,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70262576,"text":"70262576 - 2024 - A strategic and science-based framework for management of invasive annual grasses in the sagebrush biome","interactions":[],"lastModifiedDate":"2025-01-21T16:29:14.018355","indexId":"70262576","displayToPublicDate":"2024-11-01T10:12:36","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6002,"text":"Rangeland Ecology & Management","active":true,"publicationSubtype":{"id":10}},"title":"A strategic and science-based framework for management of invasive annual grasses in the sagebrush biome","docAbstract":"In the last 20 years, the North American sagebrush biome has lost over 500,000 ha of intact and largely intact sagebrush plant communities on an annual basis. Much of this loss has been associated with expansion and infilling of invasive annual grasses (IAGs). These species are highly competitive against native perennial grasses in disturbed environments, and create fuel conditions that increase both the likelihood of fire ignition and the ease of wildfire spread across large landscapes. Given the current rate of IAG expansion in both burned and unburned rangelands, ameliorating the IAG threat will involve a range-wide paradigm shift from opportunistic and reactive management, to a framework that spatially prioritizes maintenance of largely intact, uninvaded areas and improvement of invaded habitats in strategic locations. We created a framework accompanied by biome-wide priority maps using geospatial overlays that target areas to MAINTAIN large, uninvaded areas as natural resource anchors through activities to prevent IAGs and IMPROVE areas to reduce invasions with the highest potential for management efforts to succeed in restoring large, intact landscapes. We then offer three case studies to illustrate the use of these concepts and map products at multiple scales. Our map products operate at the biome scale using regional data sources but additional data sources may be needed to inform local conservation planning. However, the basic strategic management principles of a) maintaining the intact and uninvaded areas that we can least afford to lose to IAGs and b) improving areas where we have a higher likelihood of restoration success, is timely, relevant, and scalable from the biome to local levels.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rama.2024.08.019","usgsCitation":"Boyd, C.S., Creutzburg, M.K., Kumar, A.V., Smith, J., Doherty, K., Mealor, B.A., Bradford, J., Cahill, M., Copeland, S., Duquette, C., Garner, L., Holdrege, M., Sparklin, B., and Cross, T.B., 2024, A strategic and science-based framework for management of invasive annual grasses in the sagebrush biome: Rangeland Ecology & Management, v. 97, p. 61-72, https://doi.org/10.1016/j.rama.2024.08.019.","productDescription":"12 p.","startPage":"61","endPage":"72","ipdsId":"IP-164191","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":481051,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rama.2024.08.019","text":"Publisher Index Page"},{"id":480832,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.35998060853578,\n 48.72039589220637\n ],\n [\n -121.35998060853578,\n 32.36195983901993\n ],\n [\n -99.82677748353605,\n 32.36195983901993\n ],\n [\n -99.82677748353605,\n 48.72039589220637\n ],\n [\n -121.35998060853578,\n 48.72039589220637\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"97","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Boyd, Chad S.","contributorId":255106,"corporation":false,"usgs":false,"family":"Boyd","given":"Chad","email":"","middleInitial":"S.","affiliations":[{"id":51433,"text":"Eastern Oregon Agricultural Research Center, USDA Agricultural Research Service, Burns, OR 97720 USA","active":true,"usgs":false}],"preferred":false,"id":924587,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Creutzburg, Megan 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Center","active":true,"usgs":true}],"preferred":true,"id":924593,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cahill, Matthew","contributorId":245219,"corporation":false,"usgs":false,"family":"Cahill","given":"Matthew","email":"","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":924666,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Copeland, Stella M.","contributorId":196218,"corporation":false,"usgs":false,"family":"Copeland","given":"Stella M.","affiliations":[{"id":37009,"text":"USDA Agricultural Research Service","active":true,"usgs":false}],"preferred":false,"id":924595,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Duquette, Cameron A.","contributorId":349699,"corporation":false,"usgs":false,"family":"Duquette","given":"Cameron A.","affiliations":[{"id":83505,"text":"The Nature Conservancy, Eastern Oregon Agricultural Research Center, Burns, OR 97720","active":true,"usgs":false}],"preferred":false,"id":924596,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Garner, Lindy","contributorId":349700,"corporation":false,"usgs":false,"family":"Garner","given":"Lindy","affiliations":[{"id":83506,"text":"US Department of Interior, US Fish and Wildlife Service, Great Falls, MT 59405","active":true,"usgs":false}],"preferred":false,"id":924597,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Holdrege, Martin C. 0000-0003-4078-6012","orcid":"https://orcid.org/0000-0003-4078-6012","contributorId":295782,"corporation":false,"usgs":true,"family":"Holdrege","given":"Martin C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":924598,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Sparklin, Bill","contributorId":349701,"corporation":false,"usgs":false,"family":"Sparklin","given":"Bill","affiliations":[{"id":83506,"text":"US Department of Interior, US Fish and Wildlife Service, Great Falls, MT 59405","active":true,"usgs":false}],"preferred":false,"id":924599,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Cross, Todd B.","contributorId":189267,"corporation":false,"usgs":false,"family":"Cross","given":"Todd","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":924600,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70261872,"text":"70261872 - 2024 - Effect of invasive plant removal on the density of Peromyscus sonoriensis (western deer mice) in Point Reyes National Seashore, California, USA.","interactions":[],"lastModifiedDate":"2025-01-02T14:22:50.155687","indexId":"70261872","displayToPublicDate":"2024-11-01T10:11:30","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1462,"text":"Ecological Restoration","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Effect of invasive plant removal on the density of Peromyscus sonoriensis (western deer mice) in Point Reyes National Seashore, California, USA.","title":"Effect of invasive plant removal on the density of Peromyscus sonoriensis (western deer mice) in Point Reyes National Seashore, California, USA.","docAbstract":"Non-native plants can affect communities through direct competition, and by providing refuge to seed predators, creating apparent competition with native plants. Ammophila arenaria (European beachgrass) has been introduced to coastal dune habitats throughout the western United States where it forms dense monocultures, stabilizes dunes, and alters abiotic and biotic conditions. The dominance of European beachgrass has been linked to declines of Lupinus tidestromii (Tidestrom’s lupine), an herb endemic to coastal dune communities in central and northern California. Peromyscus sonoriensis (western deer mice), a native seed predator, use beachgrass as refuge from predators. Tidestrom’s lupine plants near European beachgrass stands experience greater predation pressure from deer mice. At Point Reyes National Seashore, California, USA (PRNS), mechanical removal, manual pulling, and herbicide treatment have been used to reduce the density of European beachgrass near Tidestrom’s lupine populations. We trapped deer mice at five sites in PRNS that experienced different management regimes and used spatially-explicit capture-recapture models to estimate deer mouse density as a function of site and habitat treatment. We found that deer mouse density was lowest in areas where European beachgrass was mechanically removed and in herbicide-treated foredunes, and highest in areas highly invaded by European beachgrass and Carpobrotus spp. (iceplant). The density of deer mice increased from 2021 to 2022 at every site except one that underwent extensive mechanical removal of European beachgrass from 2010-2011. This study shows enduring effects of European beachgrass removal on the density of a native seed predator and highlights the importance of habitat management for conservation of Tidestrom’s lupine.
","language":"English","publisher":"University of Wisconsin Press","doi":"10.3368/er.42.4.271","usgsCitation":"Rose, J.P., Parsons, L., Kleeman, P.M., and Halstead, B., 2024, Effect of invasive plant removal on the density of Peromyscus sonoriensis (western deer mice) in Point Reyes National Seashore, California, USA.: Ecological Restoration, v. 42, no. 4, p. 271-283, https://doi.org/10.3368/er.42.4.271.","productDescription":"14 p.","startPage":"271","endPage":"283","ipdsId":"IP-157736","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":498258,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3368/er.42.4.271","text":"Publisher Index Page"},{"id":465573,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Point Reyes National Seashore","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.13596190950221,\n 38.24285655590538\n ],\n [\n -123.13596190950221,\n 37.89014364527141\n ],\n [\n -122.65921084771676,\n 37.89014364527141\n ],\n [\n -122.65921084771676,\n 38.24285655590538\n ],\n [\n -123.13596190950221,\n 38.24285655590538\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"42","issue":"4","noUsgsAuthors":false,"publicationDate":"2024-12-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Rose, Jonathan P. 0000-0003-0874-9166 jprose@usgs.gov","orcid":"https://orcid.org/0000-0003-0874-9166","contributorId":199339,"corporation":false,"usgs":true,"family":"Rose","given":"Jonathan","email":"jprose@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":922103,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Parsons, Lorraine S 0000-0003-1943-037X","orcid":"https://orcid.org/0000-0003-1943-037X","contributorId":333962,"corporation":false,"usgs":false,"family":"Parsons","given":"Lorraine S","affiliations":[{"id":80025,"text":"NPS - Point Reyes National Seashore - PORE","active":true,"usgs":false}],"preferred":false,"id":922104,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kleeman, Patrick M. 0000-0001-6567-3239 pkleeman@usgs.gov","orcid":"https://orcid.org/0000-0001-6567-3239","contributorId":3948,"corporation":false,"usgs":true,"family":"Kleeman","given":"Patrick","email":"pkleeman@usgs.gov","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":922105,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Halstead, Brian J. 0000-0002-5535-6528 bhalstead@usgs.gov","orcid":"https://orcid.org/0000-0002-5535-6528","contributorId":3051,"corporation":false,"usgs":true,"family":"Halstead","given":"Brian J.","email":"bhalstead@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":922106,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70260412,"text":"sim3527 - 2024 - Geomorphic map of the Umatilla River corridor, Oregon","interactions":[],"lastModifiedDate":"2025-12-22T20:27:56.574752","indexId":"sim3527","displayToPublicDate":"2024-11-01T10:05:11","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3527","title":"Geomorphic map of the Umatilla River corridor, Oregon","docAbstract":"This map portrays the distribution of landforms along the Umatilla River in northeastern Oregon and covers a corridor 127 kilometers long from the confluence of the Umatilla River with the Columbia River upstream to Meacham Creek. The map encompasses the valley bottom and extends about 1 kilometer up the adjoining hillslopes. Map data are intended to support water quality and fisheries enhancement efforts pursuant to the First Foods, a resource-management approach that focuses on traditionally gathered foods including water, fish, big game, roots, and berries and calls attention to the reciprocity between people and the foods upon which humans depend.
The Umatilla River drains about 6,300 square kilometers on the northwest slope of the Blue Mountains in northeast Oregon. Most of the drainage basin is underlain by Miocene basalt flows of the Columbia River Basalt Group. Younger, weakly lithified, late Miocene and early Pliocene gravel deposits of local origin (for example, McKay Formation) are mapped in a few places. Upland surfaces are mantled with windborne silt (loess) correlative with deposits elsewhere known as the Palouse Formation. Surfaces below an elevation of about 340 meters were inundated repeatedly by large Pleistocene glacial outburst floods, most emanating from glacial Lake Missoula in western Montana. In backflooded areas such as the lower Umatilla River valley, Missoula floods deposited extensive slack-water silt.
Areas mapped as open water, active channel and tie channel, flood basin, valley bottom, and modified land constitute the geomorphic floodplain: the area subject to occasional inundation by the Umatilla River. Deposits and landforms within the floodplain are inset into Missoula flood deposits and hence postdate the 20–15-kilo-annum Missoula floods. Some floodplain deposits are no more than a few centuries old, as indicated by substantial erosion and deposition during the Umatilla River flood of February 2020, the largest since systematic measurements began in October 1903. Deposits and landforms of the floodplain are transient features within the longer-term incision of the Umatilla River into mid-Miocene flood basalts and younger gravel of the McKay Formation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3527","collaboration":"Prepared in cooperation with the Confederated Tribes of the Umatilla Indian Reservation","usgsCitation":"Yuh, I.P., Haugerud, R.A., O'Connor, J.E., and O'Daniel, S.J., 2024, Geomorphic map of the Umatilla River corridor, Oregon: U.S. Geological Survey Scientific Investigation Map 3527, scale 1:12,000, 6 sheets, https://doi.org/10.3133/sim3527.","productDescription":"6 Sheets: 60.00 x 22.00 inches or smaller; Data Release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-158910","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":497889,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117653.htm","linkFileType":{"id":5,"text":"html"}},{"id":463503,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13OOE7Q","description":"Yuh, I.P., Haugerud, R.A., O’Connor, J.E., and O’Daniel, S.J., 2024, Geospatial database for the geomorphic map of the Umatilla River corridor, Oregon: U.S. Geological Survey data release, https://doi.org/10.5066/P13OOE7Q.","linkHelpText":"Geospatial database for the geomorphic map of the Umatilla River corridor, Oregon"},{"id":463502,"rank":7,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3527/sim3527_sheet06.pdf","text":"Sheet 6","size":"14 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":463501,"rank":6,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3527/sim3527_sheet05.pdf","text":"Sheet 5","size":"14 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":463500,"rank":5,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3527/sim3527_sheet04.pdf","text":"Sheet 4","size":"17 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":463499,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3527/sim3527_sheet03.pdf","text":"Sheet 3","size":"15 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":463498,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3527/sim3527_sheet02.pdf","text":"Sheet 2","size":"13 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":463497,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3527/sim3527_sheet01.pdf","text":"Sheet 1","size":"11 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":463496,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3527/covrthb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Umatilla River corridor","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -118.33321833933547,\n 45.68071824192785\n ],\n [\n -118.3561230993523,\n 45.730645505488894\n ],\n [\n -118.68247351832258,\n 45.7153349524672\n ],\n [\n -118.92979975453633,\n 45.69914300966221\n ],\n [\n -119.0766497072885,\n 45.72208021102742\n ],\n [\n -119.23122860492205,\n 45.82720081569687\n ],\n [\n -119.31238252617953,\n 45.9495910938214\n ],\n [\n -119.37228184901241,\n 45.932123278858995\n ],\n [\n -119.33556936082459,\n 45.81912165021458\n ],\n [\n -119.34329830570641,\n 45.7652305840443\n ],\n [\n -119.05732734508436,\n 45.64513599220672\n ],\n [\n -118.76555967580092,\n 45.630274925778025\n ],\n [\n -118.33238843274466,\n 45.66767113997548\n ],\n [\n -118.33321833933547,\n 45.68071824192785\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Geology, Minerals, Energy, & Geophysics Science Center
U.S. Geological Survey
350 N. Akron Rd.
Moffett Field, CA 94035
Effective monitoring of populations is critical for assessing the efficacy of conservation and management activities, determining the conservation status of a species, and examining trends over time. However, far too often, monitoring efforts fall short of adequately describing the population. Poorly defined problems and objectives, a lack of standard operating procedures, a poor selection of attributes to monitor (We define attributes as characteristics such as presence-absence, relative abundance, size structure, body condition, and age structure data), inadequate survey designs (e.g., low survey effort or statistical power), a lack of consistency due to budget shortages or staffing turnover, and a lack of rigorous analyses of the data focused on improving monitoring methods are the causes of ineffective monitoring (Lindenmayer and Likens 2010; Reynolds 2012). Many of these issues can be addressed prior to implementing a monitoring program by defining clear objectives, developing a formal protocol with specific instructions on how to conduct the survey, analyzing historical data to estimate the required sample size, exploring collaborations between biologists and statisticians, and instituting a formal goal to regularly analyze the data collected to improve the monitoring process (Lindenmayer and Likens 2010). The goal of this chapter is to provide an overview of defining the sampling frame, site selection from the sampling frame, sample size estimation, data summarization and analysis techniques, parameter estimation, and hypothesis testing, as well as recognizing when a monitoring program is unlikely to produce the desired results.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Standard methods for sampling North American freshwater fishes","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"American Fisheries Society","doi":"10.47886/9781934874769.ch14","usgsCitation":"Stewart, D.R., Broms, K.M., Gerow, K.G., Allen, M.A., and Quist, M., 2024, Statistical analysis, chap. of Standard methods for sampling North American freshwater fishes, p. 285-338, https://doi.org/10.47886/9781934874769.ch14.","productDescription":"54 p.","startPage":"285","endPage":"338","ipdsId":"IP-134392","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":502273,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"Second edition","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Stewart, David R","contributorId":369391,"corporation":false,"usgs":false,"family":"Stewart","given":"David","middleInitial":"R","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":958913,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Broms, Kristin M","contributorId":369392,"corporation":false,"usgs":false,"family":"Broms","given":"Kristin","middleInitial":"M","affiliations":[{"id":64975,"text":"Neptune and Company","active":true,"usgs":false}],"preferred":false,"id":958914,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gerow, Ken G","contributorId":369393,"corporation":false,"usgs":false,"family":"Gerow","given":"Ken","middleInitial":"G","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":958915,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Allen, Micheal A","contributorId":369394,"corporation":false,"usgs":false,"family":"Allen","given":"Micheal","middleInitial":"A","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":958916,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Quist, Michael C. 0000-0001-8268-1839","orcid":"https://orcid.org/0000-0001-8268-1839","contributorId":272016,"corporation":false,"usgs":true,"family":"Quist","given":"Michael C.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":958917,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70240993,"text":"70240993 - 2024 - Standard data management practices","interactions":[],"lastModifiedDate":"2026-04-08T14:56:35.897833","indexId":"70240993","displayToPublicDate":"2024-11-01T10:04:06","publicationYear":"2024","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"15","title":"Standard data management practices","docAbstract":"Accomplishing data management in a standardized and practical way begins with an understanding of what data management is. The Data Management Association defines data management as “the development, execution, and supervision of plans, policies, programs, and practices that deliver, control, protect, and enhance the value of data and information assets throughout their lifecycles” (Earley 2017). In this chapter, we present the tenets of data management in the context of fisheries for our target audience: fisheries biologists who may have limited formal training in data science. Experienced data managers may also benefit from the contents of this chapter, but the authors’ goal is to enhance and improve those activities that produce data, from project planning to acquiring data through field sampling, to cataloging and analyzing data, to sharing and archiving data.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Standard methods for sampling North American freshwater fishes, second edition","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"American Fisheries Society","doi":"10.47886/9781934874769.ch15","usgsCitation":"Krogman, R., Bayer, J.M., Cooper, A., Kopaska, J., Leonard, N., Pritt, J., Roe, C., Tracy, E., Venturelli, P.A., Wieferich, D.J., and Infante, D.M., 2024, Standard data management practices, chap. 15 of Standard methods for sampling North American freshwater fishes, second edition, p. 339-368, https://doi.org/10.47886/9781934874769.ch15.","productDescription":"30 p.","startPage":"339","endPage":"368","ipdsId":"IP-145602","costCenters":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science 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