The Atlantic sturgeon Acipenser oxyrinchus oxyrinchus was once of great commercial importance in many coastal rivers of the eastern USA. Over the 19th and 20th centuries, most historical stocks of Atlantic sturgeon were depleted by human activities. Estimating recruitment for the remaining populations is challenging due to sampling constraints, limited age data, and natural variability. However, recruitment estimates could inform recovery efforts. The objectives of this study were to compare 2 modeling approaches to estimate recruitment of age-1 Atlantic sturgeon and provide an updated index of abundance across more than a decade of sampling in the Altamaha River, Georgia. First, we constructed capture histories of river-resident juveniles, using capture-mark-recapture data collected from 2008 to 2020, and assigned ages based on length-frequency analysis. Second, we compared more traditional Huggins closed population models and a recent nonlinear extension of Huggins models—vector generalized additive models (VGAMs)—to estimate abundance of age-1 fish. Both model types indicated similar yearly age-1 abundance estimates (Huggins: 163 in 2017 to 3839 in 2010; VGAM: 312 in 2020 to 4448 in 2010), but the VGAMs provided more direct interpretation for factors that might affect capture probability (e.g. sampling effort, temperature, fish length). This study indicates that the age-1 Altamaha River Atlantic sturgeon population has remained relatively stable over the past decade and provides a long-term baseline which will better enable managers to assess the effects of either future restoration actions or environmental disturbances on the population.
","language":"English","publisher":"Inter-Research","doi":"10.3354/esr01250","usgsCitation":"Baker, M., Ingram, E., Higginbotham, D., Irwin, B., and Fox, A., 2023, Refining capture-recapture recruitment estimation methods for Atlantic sturgeon: Endangered Species Research, v. 51, p. 203-214, https://doi.org/10.3354/esr01250.","productDescription":"12 p.","startPage":"203","endPage":"214","ipdsId":"IP-143737","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":432972,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":442856,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/esr01250","text":"Publisher Index Page"}],"country":"United States","state":"Georgia","otherGeospatial":"Altamaha River estuary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -81.48760060177855,\n 31.490539509150565\n ],\n [\n -81.48760060177855,\n 31.14793158914553\n ],\n [\n -81.23488559221977,\n 31.14793158914553\n ],\n [\n -81.23488559221977,\n 31.490539509150565\n ],\n [\n -81.48760060177855,\n 31.490539509150565\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"51","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Baker, M.A.","contributorId":340977,"corporation":false,"usgs":false,"family":"Baker","given":"M.A.","email":"","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":907756,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ingram, E.C.","contributorId":340978,"corporation":false,"usgs":false,"family":"Ingram","given":"E.C.","email":"","affiliations":[{"id":36488,"text":"Stony Brook University","active":true,"usgs":false}],"preferred":false,"id":907757,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Higginbotham, D.L.","contributorId":340979,"corporation":false,"usgs":false,"family":"Higginbotham","given":"D.L.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":907758,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Irwin, Brian J. 0000-0002-0666-2641","orcid":"https://orcid.org/0000-0002-0666-2641","contributorId":280043,"corporation":false,"usgs":true,"family":"Irwin","given":"Brian J.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":907759,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fox, A.G.","contributorId":340980,"corporation":false,"usgs":false,"family":"Fox","given":"A.G.","email":"","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":907760,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70256426,"text":"70256426 - 2023 - The Factors Affecting Female Black Bear Harvest Rates in Pennsylvania","interactions":[],"lastModifiedDate":"2024-09-09T15:01:45.550938","indexId":"70256426","displayToPublicDate":"2023-07-05T09:55:01","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5373,"text":"Cooperator Science Series","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"FWS/CSS-150-2023","title":"The Factors Affecting Female Black Bear Harvest Rates in Pennsylvania","docAbstract":"Pennsylvania’s black bear (Ursus americanus) population increased in abundance and distribution during the latter third of the 20th century, leading to an increase in human-bear conflicts. Increases in harvest opportunities from 2002–2018 aimed to stabilize black bear population growth but did not substantially increase harvest, and annual harvest was often below the desired goal of 20% removal. Consequently, additional changes to Pennsylvania’s black bear hunting seasons occurred from 2019–2021, including starting harvest earlier, expanding the length of seasons, and adding additional seasons (i.e., a muzzleloader and special rifle season). Understanding how earlier harvest seasons and new methods of take (i.e., muzzleloader) influence female black bear harvest vulnerability is important to informing harvest management. We trapped and GPS-collared adult female bears in the Sproul State Forest in northcentral Pennsylvania from 2019–2021 to determine home range sizes, patterns of resource selection, and sources of mortality during fall harvest seasons. We assessed annual variability in relative abundance of fall hard mast. We evaluated temporal and spatial variation in hunter activity with road-side surveys and remote camera traps, respectively. We estimated fall and weekly home range size with utilization distributions through an autocorrelated kernel density estimation and evaluated the influence of predictors hypothesized to influence third-order resource selection using generalized linear mixed models. We investigated factors hypothesized to influence female black bear survival during hunting seasons with known-fate models. Mean fall home range size was 248.7 km2 (range = 6.1–2636.1 km2). Home range sizes varied by year and were generally smaller during archery harvest season than other periods. Patterns of weekly resource selection indicated bears selected steeper slopes and higher elevations outside of harvest seasons but shifted to less-steep areas in the week before harvest and the first week of harvest, and to lower elevations during harvest. Bears selected for areas containing oak (Quercus spp.) trees throughout the fall. Survival was lower in older age bears, greater relative mast abundance conditions, steeper slopes, and areas of greater hunter space use during the general firearms season. Survival was higher in areas of greater hunter space use during archery season. Harvest rate of adult female bears was 0.345 in 2019, 0.321 in 2020, and 0.150 in 2021, and averaged 0.272 across all three years. The probability of an adult female black bear surviving all harvest seasons each year was 0.611 (SE = 0.086, 95% CI = 0.436, 0.761). The high harvest rate and low predicted survival may lead to population reduction.
","language":"English","publisher":"U.S. Fish and Wildlife Service","usgsCitation":"Snavely, B.M., and Lonsinger, R.C., 2023, The Factors Affecting Female Black Bear Harvest Rates in Pennsylvania: Cooperator Science Series FWS/CSS-150-2023, ii, 11 p.","productDescription":"ii, 11 p.","ipdsId":"IP-154378","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":431779,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.fws.gov/media/factors-affecting-female-black-bear-harvest-rates-pennsylvania"},{"id":433618,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Snavely, Brandon M.","contributorId":340528,"corporation":false,"usgs":false,"family":"Snavely","given":"Brandon","email":"","middleInitial":"M.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":907330,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lonsinger, Robert Charles 0000-0002-1040-7299","orcid":"https://orcid.org/0000-0002-1040-7299","contributorId":340524,"corporation":false,"usgs":true,"family":"Lonsinger","given":"Robert","email":"","middleInitial":"Charles","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":907331,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70250980,"text":"70250980 - 2023 - Identifying invertebrate indicators for streamflow duration assessments in forested headwater streams","interactions":[],"lastModifiedDate":"2024-01-17T12:49:54.187192","indexId":"70250980","displayToPublicDate":"2023-07-05T06:46:05","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1699,"text":"Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"Identifying invertebrate indicators for streamflow duration assessments in forested headwater streams","docAbstract":"Streamflow-duration assessment methods (SDAMs) are rapid, indicator-based tools for classifying streamflow duration (e.g., intermittent vs perennial flow) at the reach scale. Indicators are easily assessed stream properties used as surrogates of flow duration, which is too resource intensive to measure directly for many reaches. Invertebrates are commonly used as SDAM indicators because many are not highly mobile, and different species have life stages that require flow for different durations and times of the year. The objectives of this study were to 1) identify invertebrate taxa that can be used as SDAM indicators to distinguish between stream reaches having intermittent and perennial flow, 2) to compare indicator strength across different taxonomic and numeric resolutions, and 3) to assess the relative importance of season and habitat type on the ability of invertebrates to predict streamflow-duration class. We used 2 methods, random forest models and indicator species analysis, to analyze aquatic and terrestrial invertebrate data (presence/absence, density, and biomass) at the family and genus levels from 370 samples collected from both erosional and depositional habitats during both wet and dry seasons. In total, 36 intermittent and 53 perennial reaches were sampled along 31 forested headwater streams in 4 level II ecoregions across the United States. Random forest models for family- and genus-level datasets had stream classification accuracy ranging from 88.9 to 93.2%, with slightly higher accuracy for density than for presence/absence and biomass datasets. Season (wet/dry) tended to be a stronger predictor of streamflow-duration class than habitat (erosional/depositional). Many taxa at the family (58.8%) and genus level (61.6%) were collected from both intermittent and perennial reaches, and most taxa that were exclusive to 1 streamflow-duration class were rarely collected. However, 23 family-level or higher taxa (20 aquatic and 3 terrestrial) and 44 aquatic genera were identified as potential indicators of streamflow-duration class for forested headwater streams. The utility of the potential indicators varied across level II ecoregions in part because of representation of intermittent and perennial reaches in the dataset but also because of variable ecological responses to drying among species. Aquatic invertebrates have been an important field indicator of perennial reaches in existing SDAMs, but our findings highlight how including aquatic and terrestrial invertebrates as indicators of intermittent reaches can further maximize the data collected for streamflow-duration classifications.
Forested landscapes in the Western United States are subject to growing size and severity of wildfires, in part due to historical management strategies focusing on wildfire suppression. Forest restoration treatments and fuels reductions, including thinning and prescribed burning, can reduce the frequency and intensity of wildfires. Extensive restoration and fuels treatment efforts are underway across many areas in the Southwestern United States, including New Mexico. The tradeoff between amenity values provided by forested landscapes and the wildfire risk associated with forested landscapes is becoming increasingly important to understand as development in the wildland-urban interface increases. Understanding how house proximity, relative to forest restoration or fuels treatments, is capitalized into home sale prices can provide useful information about how individuals value forested landscapes that have been altered to reduce wildfire risk or severity. We use a Hedonic Property Model to estimate the average treatment effect of proximity to forest restoration or fuel treatments in New Mexico, United States. We use matching methods to estimate the average treatment effect of proximity to forest restoration. We find that proximity to the forest has a positive amenity value; however, proximity to recent forest restoration or fuel treatments results in a decrease in house sale prices. We combine the results of our two models and calculate that homes not within one kilometer of a treated forest and within one kilometer of Cibola National Forest sell for an average $73,626 premium. The average premium drops to $22,996 for homes within one kilometer of a forest that has been recently treated and within one kilometer of Cibola National Forest.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.landurbplan.2023.104838","usgsCitation":"Fitch, R.A., Mueller, J.M., Meldrum, J., and Huber, C., 2023, Estimating proximity effects to wildfire fuels treatments on house prices in Cibola National Forest, New Mexico, USA: Landscape and Urban Planning, v. 238, 104838, 9 p., https://doi.org/10.1016/j.landurbplan.2023.104838.","productDescription":"104838, 9 p.","ipdsId":"IP-143350","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"links":[{"id":442867,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.landurbplan.2023.104838","text":"Publisher Index Page"},{"id":418740,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Cibola National Forest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -106.57936451046446,\n 35.35726965713178\n ],\n [\n -106.57936451046446,\n 34.84741122784986\n ],\n [\n -106.11539121622326,\n 34.84741122784986\n ],\n [\n -106.11539121622326,\n 35.35726965713178\n ],\n [\n -106.57936451046446,\n 35.35726965713178\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"238","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Fitch, Ryan A.","contributorId":316216,"corporation":false,"usgs":false,"family":"Fitch","given":"Ryan","email":"","middleInitial":"A.","affiliations":[{"id":12698,"text":"Northern Arizona University","active":true,"usgs":false}],"preferred":false,"id":877050,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mueller, Julie M.","contributorId":219795,"corporation":false,"usgs":false,"family":"Mueller","given":"Julie","email":"","middleInitial":"M.","affiliations":[{"id":12698,"text":"Northern Arizona University","active":true,"usgs":false}],"preferred":false,"id":877051,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Meldrum, James R. 0000-0001-5250-3759 jmeldrum@usgs.gov","orcid":"https://orcid.org/0000-0001-5250-3759","contributorId":195484,"corporation":false,"usgs":true,"family":"Meldrum","given":"James","email":"jmeldrum@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":877052,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Huber, Christopher 0000-0001-8446-8134 chuber@usgs.gov","orcid":"https://orcid.org/0000-0001-8446-8134","contributorId":127600,"corporation":false,"usgs":true,"family":"Huber","given":"Christopher","email":"chuber@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":877053,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70254722,"text":"70254722 - 2023 - The scale-dependent role of submerged macrophytes as drift-feeding lotic fish habitat","interactions":[],"lastModifiedDate":"2024-06-11T12:14:10.470494","indexId":"70254722","displayToPublicDate":"2023-07-04T07:10:59","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"The scale-dependent role of submerged macrophytes as drift-feeding lotic fish habitat","docAbstract":"The stable isotopic composition of pedogenic carbonates is central to many studies of past climate and topography, providing a basis for our understanding of Earth's terrestrial history. A core assumption of many applications of oxygen isotope values (δ18O) of pedogenic carbonate is that they reflect the δ18O value of precipitation (rain/snow). This assumption is violated if soil carbonates form in evaporated soil waters. In this work, we develop a means to identify evaporation in ancient soils using the triple oxygen isotope composition (16O-17O-18O) of pedogenic carbonates. Both theoretical predictions of isotope kinetics during evaporation and studies of triple oxygen isotopes in other geological materials show that the deviation in the relationship between δ17O and δ18O from a reference line, evaluated using the parameter Δ'17O, is sensitive to evaporation. As a first step in developing the use of Δ'17O in ancient pedogenic carbonates, we report Δ'17O values from 47 near-modern pedogenic carbonate samples from globally distributed environments that vary in aridity (hyper-arid to humid). The Δ'17O values of pedogenic carbonate range from -154 to -60 per meg (as CaCO3, measured via O2, VSMOW-SLAP), corresponding to calculated soil water values of -66 to +27 per meg (VSMOW-SLAP) (using a carbonate-water triple oxygen isotope fractionation exponent of 0.5250 and clumped isotope-derived carbonate growth temperatures). The Δ'17O values indicate that evaporative modification of soil water from which pedogenic carbonate forms is common, especially in arid environments. Arid environments host pedogenic carbonates formed from soil waters ranging from highly to minimally evaporated, while humid environments host pedogenic carbonates formed from waters that are only minimally evaporated. The variability in Δ'17O within environments classified by the same aridity may relate to the fact that pedogenic carbonates record soil conditions only during times of carbonate mineralization, which may deviate from annual conditions. Thus, Δ'17O may be useful in understanding the specific circumstances of pedogenic carbonate formation but may not provide incontrovertible evidence of the magnitude of environmental aridity. Evaporative modification of δ18O values of pedogenic carbonates can be detected with Δ'17O, thereby improving estimates of δ18O of unevaporated waters. Our data show that evaporation must be (re)considered for all paleoclimate inferences based on the δ18O of pedogenic carbonate. The addition of Δ'17O will re-energize paleoclimate studies that use (or have avoided using) δ18O of pedogenic carbonate.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.gca.2023.06.034","usgsCitation":"Kelson, J., Huth, T., Passey, B.H., Levin, N.E., Petersen, S.V., Ballato, P., Beverly, E.J., Breecker, D.O., Hoke, G.D., Hudson, A.M., Haoyuan, J., Licht, A., and Quade, J., 2023, Triple oxygen isotope compositions of globally distributed soil carbonates record widespread evaporation of soil waters: Geochimica et Cosmochimica Acta, v. 355, p. 138-160, https://doi.org/10.1016/j.gca.2023.06.034.","productDescription":"23 p.","startPage":"138","endPage":"160","ipdsId":"IP-148273","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":442883,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://hal.science/hal-04160695","text":"Publisher Index Page"},{"id":418704,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"355","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kelson, Julia 0000-0002-0588-5018","orcid":"https://orcid.org/0000-0002-0588-5018","contributorId":219941,"corporation":false,"usgs":false,"family":"Kelson","given":"Julia","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":876922,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Huth, Tyler E.","contributorId":315599,"corporation":false,"usgs":false,"family":"Huth","given":"Tyler E.","affiliations":[{"id":68361,"text":"Department of Earth & Environmental Sciences, University of Michigan","active":true,"usgs":false}],"preferred":false,"id":876923,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Passey, Benjamin H.","contributorId":315600,"corporation":false,"usgs":false,"family":"Passey","given":"Benjamin","email":"","middleInitial":"H.","affiliations":[{"id":68361,"text":"Department of Earth & Environmental Sciences, University of Michigan","active":true,"usgs":false}],"preferred":false,"id":876924,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Levin, Naomi E.","contributorId":315601,"corporation":false,"usgs":false,"family":"Levin","given":"Naomi","email":"","middleInitial":"E.","affiliations":[{"id":68361,"text":"Department of Earth & Environmental Sciences, University of Michigan","active":true,"usgs":false}],"preferred":false,"id":876925,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Petersen, Sierra V.","contributorId":201014,"corporation":false,"usgs":false,"family":"Petersen","given":"Sierra","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":876926,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ballato, Paolo","contributorId":315602,"corporation":false,"usgs":false,"family":"Ballato","given":"Paolo","email":"","affiliations":[{"id":68362,"text":"Department of Science, Geological Sciences Section, University of Roma Tre","active":true,"usgs":false}],"preferred":false,"id":876927,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Beverly, Emily J.","contributorId":315603,"corporation":false,"usgs":false,"family":"Beverly","given":"Emily","email":"","middleInitial":"J.","affiliations":[{"id":68365,"text":"Department of Earth and Atmospheric Sciences, University of Houston","active":true,"usgs":false}],"preferred":false,"id":876928,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Breecker, Daniel O.","contributorId":215845,"corporation":false,"usgs":false,"family":"Breecker","given":"Daniel","email":"","middleInitial":"O.","affiliations":[{"id":39318,"text":"University of Texas-Austin","active":true,"usgs":false}],"preferred":false,"id":876929,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hoke, Gregory D.","contributorId":315604,"corporation":false,"usgs":false,"family":"Hoke","given":"Gregory","email":"","middleInitial":"D.","affiliations":[{"id":68366,"text":"Department of Earth and Environmental Sciences, Syracuse University,","active":true,"usgs":false}],"preferred":false,"id":876930,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hudson, Adam M. 0000-0002-3387-9838 ahudson@usgs.gov","orcid":"https://orcid.org/0000-0002-3387-9838","contributorId":195419,"corporation":false,"usgs":true,"family":"Hudson","given":"Adam","email":"ahudson@usgs.gov","middleInitial":"M.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":876931,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Haoyuan, Ji","contributorId":315605,"corporation":false,"usgs":false,"family":"Haoyuan","given":"Ji","email":"","affiliations":[{"id":68367,"text":"Google LLC, Seattle, WA","active":true,"usgs":false}],"preferred":false,"id":876932,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Licht, Alexis","contributorId":315606,"corporation":false,"usgs":false,"family":"Licht","given":"Alexis","email":"","affiliations":[{"id":68368,"text":"Aix-Marseille Université","active":true,"usgs":false}],"preferred":false,"id":876933,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Quade, Jay","contributorId":22108,"corporation":false,"usgs":false,"family":"Quade","given":"Jay","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":876934,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70249392,"text":"70249392 - 2023 - Human and infrastructure exposure to large wildfires in the United States","interactions":[],"lastModifiedDate":"2023-11-20T17:39:09.584907","indexId":"70249392","displayToPublicDate":"2023-07-03T06:43:03","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5791,"text":"Nature Sustainability","active":true,"publicationSubtype":{"id":10}},"title":"Human and infrastructure exposure to large wildfires in the United States","docAbstract":"An increasing number of wildfire disasters have occurred in recent years in the United States. Here we demonstrate that cumulative primary human exposure—the population residing within the perimeters of large wildfires—was 594,850 people from 2000 to 2019 across the contiguous United States (CONUS), 82% of which occurred in the western United States. Primary population exposure increased by 125% in the CONUS in the past two decades; it was noted that there were large statistical uncertainties in the trend analysis due to the short study timeline. Population dynamics from 2000 to 2019 alone accounted for 24% of the observed increase rate in human exposure, and an increased wildfire extent drove the majority of the observed trends. In addition, we document the widespread exposure of roads (412,155 km) and transmission powerlines (14,835 km) to large wildfires in the CONUS, with a relative increase of 58% and 70% in the past two decades, respectively. Our results highlight that deliberate mitigation and adaptation efforts to help societies cope with wildfires are ever more needed.
Earthquake risk associated with Quito, Ecuador; Cali, Colombia; and Santiago de los Caballeros, Dominican Republic is examined by generating a set of hypothetical earthquake scenarios considering seismic sources, recent seismicity, and major historical earthquakes recorded in the vicinity. In this study, particular focus is given to the development of earthquake scenarios for use in emergency planning in each city as well as stimulating discussion with respect to addressing the gaps in current understanding of built stock inventory and their vulnerability when subjected to strong shaking. Exposure and vulnerability models from the Global Earthquake Model foundation, hazard and local site information available for the cities, and the U.S. Geological Survey near‐real‐time products are utilized to estimate potential consequences for postearthquake response planning. Results showed that the historic city centers remain the most susceptible to experiencing severe damage resulting in widespread casualties. Similarly, the scenarios highlight areas susceptible to shaking induced ground failure hazards, which may pose additional challenges when responding to such earthquakes. Moderate earthquakes originating from nearby seismic sources, for example, Quito fault system for Quito or the Septentrional fault zone in the case of Santiago de Los Caballeros, could potentially be of greater consequence in terms of direct economic impact and disruption to the city when compared to very large distant subduction interface earthquakes.
Bats are important pest control agents in agriculture. Yet, the underlying fine-scale biotic and abiotic mechanisms that drive their foraging behaviors and responses to insect outbreaks are unclear. Herbivore-induced plant volatiles (HIPVs) can attract both invertebrate and vertebrate natural enemies that use the chemical plant cues to locate insect prey. The ability of HIPVs to attract multiple species raises the question of whether they may also be a biotic factor influencing insectivorous bat activity. Additionally, abiotic factors, such as weather conditions, can affect bat activity in agricultural settings, but little is known about how bats respond to shifting environmental conditions on short timescales in this landscape context. Using a model crop system, soybean (Glycine max), our study asked three questions: (1) Which bat species are active in eastern Maryland soybean fields? (2) Is insectivorous bat activity affected by naturally occurring soybean HIPVs and/or synthetic soybean HIPVs (indole or farnesene)? (3) How is insectivorous bat activity affected by hourly weather conditions in this landscape? In soybean fields in eastern Maryland, we created paired treatment plots: HIPV plots (damaged plants or synthetic HIPV dispensers) and control plots (undamaged plants or empty dispensers). We measured bat activity using ultrasonic recorders, summarizing hourly and nightly activity, and detected 10 total species. The most abundant species were big brown/silver-haired bats (Eptesicus fuscus/Lasionycteris noctivagans). Bat activity did not significantly differ between control and HIPV plots in any of the three experiments. Thus, our results do not support our expectation that bats in eastern Maryland use soybean HIPVs to locate insect prey. However, bat activity did increase with increasing average hourly temperature and wind speed. This initial study of bats and HIPVs, as well as the fine-scale examination of weather conditions on bat activity, may serve as a guide for future research on bat–plant interactions that can support the development of new strategies for sustainable pest management.
","language":"English","publisher":"Wiley","doi":"10.1002/ecs2.4575","usgsCitation":"Maynard, L., Ford, W., Parker, J., and Whitehead, S., 2023, Biotic and abiotic factors shaping bat activity in Maryland soybean fields: Ecosphere, v. 14, no. 7, e4575, 13 p., https://doi.org/10.1002/ecs2.4575.","productDescription":"e4575, 13 p.","ipdsId":"IP-145893","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":467104,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4575","text":"Publisher Index Page"},{"id":466422,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"id\":22,\"properties\":{\"name\":\"Maryland\",\"nation\":\"USA 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Mark","email":"wford@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":923305,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Parker, John D.","contributorId":348247,"corporation":false,"usgs":false,"family":"Parker","given":"John D.","affiliations":[{"id":13510,"text":"Smithsonian Environmental Research Center","active":true,"usgs":false}],"preferred":false,"id":923306,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Whitehead, Susan R.","contributorId":348249,"corporation":false,"usgs":false,"family":"Whitehead","given":"Susan R.","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":923307,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70247715,"text":"70247715 - 2023 - 2023 Coastal master plan: ICM-wetlands – Submerged aquatic vegetation (SAV) updates","interactions":[],"lastModifiedDate":"2023-08-15T15:31:34.073116","indexId":"70247715","displayToPublicDate":"2023-07-01T10:27:06","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"chapter":"Attachment D3","title":"2023 Coastal master plan: ICM-wetlands – Submerged aquatic vegetation (SAV) updates","docAbstract":"Submerged aquatic vegetation (SAV) provides critical structural habitat for valuable nekton and wildlife species across coastal ecosystems and can buffer the negative effects of land loss. Landscape change and restoration efforts across coastal Louisiana can impact the occurrence, coverage, and species assemblages of SAV, and changes to these foundational species can have cascading impacts across food webs. To support the 2023 Coastal Master Plan efforts, a unique SAV model was developed to assess coverage and occurrence of SAV across aquatic waterbodies in response to environmental variables evaluated.
This effort created a spatial model describing the probability of presence of SAV across the study area in response to changing conditions over the modeled time period. To develop the initial coverage data layer, we used remotely sensed Normalized Difference Vegetation Index (NDVI) and modified Normalized Difference Water Index (mNDWI) data from 2015-2018 to identify areas containing variable vegetation and water spectral reflectance. Key environmental variables evaluated included total suspended sediments (TSS), salinity, and physical exposure. Seasonal estimates for TSS and salinity were used, as research indicates that seasonal environmental variability is a significant driver for SAV establishment. Seasonal salinity was derived from Coast-wide Reference Monitoring Station (CRMS) data, and seasonal TSS was estimated from hyperspectral imagery. Estimates of physical exposure have previously been provided by calculating fetch (the distance across water over which waves can propagate), but this proved to be too computationally intensive to be feasible, and we found distance to land to be a reasonable proxy for exposure. To represent geographic conditions and historical factors influences on SAV establishment and occurrence (e.g., variables too numerous and complex to model) we developed a basin variable that served as a proxy for complex historical, or prior, conditions, determined by the forested, fresh, intermediate, brackish, or saline (FFIBS) score. The final model included spring TSS, spring salinity, distance to land, and the basin prior.
The model performed well for the area evaluated, correctly classifying SAV (as present or absent) 89% of the time (Kappa = 580). SAV probability of presence responded as expected to change in these environmental variables, with likelihood of occurrence decreasing in response to increasing spring TSS, spring salinity, and distance to land. However, the model was more accurate at predicting absence (true negative = 0.940) than predicting presence (true positive = 0.626), suggesting that the scale of the model may limit the ability to predict presence. Moreover, the simplicity of the model limited the accuracy in highly dynamic environments, for example near the outflow of diversions or areas of significant changes in salinity or TSS. Through incorporating underwater communities like SAV, this master plan provides a holistic view of coastal change and restoration. To create healthy ecological structure and function in wetland habitats, the submergent communities must be considered alongside the emergent habitats. As the benefits of SAV are increasingly recognized, both here in Louisiana and beyond, SAV restoration and the use of SAV communities in assessing and improving ecological condition are becoming more common.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"2023 Louisiana’s comprehensive master plan for a sustainable coast","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"Louisiana Coastal Protection and Restoration Authority","usgsCitation":"DeMarco, K., Schoolmaster, D., and Couvillion, B., 2023, 2023 Coastal master plan: ICM-wetlands – Submerged aquatic vegetation (SAV) updates (Version 2), 58 p.","productDescription":"58 p.","ipdsId":"IP-151482","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":419827,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":419802,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://coastal.la.gov/our-plan/2023-coastal-master-plan/2023-plan-appendices/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Louisiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -93.79077632406495,\n 30.706267411766817\n ],\n [\n -93.79077632406495,\n 28.854615329475607\n ],\n [\n -88.34722956694776,\n 28.27842992330551\n ],\n [\n -89.00478141362511,\n 30.706267411766817\n ],\n [\n -93.79077632406495,\n 30.706267411766817\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Version 2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"DeMarco, Kristin","contributorId":200003,"corporation":false,"usgs":false,"family":"DeMarco","given":"Kristin","email":"","affiliations":[],"preferred":false,"id":880146,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schoolmaster, Donald 0000-0003-0910-4458","orcid":"https://orcid.org/0000-0003-0910-4458","contributorId":202356,"corporation":false,"usgs":true,"family":"Schoolmaster","given":"Donald","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":880147,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Couvillion, Brady 0000-0001-5323-1687","orcid":"https://orcid.org/0000-0001-5323-1687","contributorId":222810,"corporation":false,"usgs":true,"family":"Couvillion","given":"Brady","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":880148,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70247717,"text":"70247717 - 2023 - 2023 Coastal master plan: Landscape input data","interactions":[],"lastModifiedDate":"2023-08-15T15:32:51.936815","indexId":"70247717","displayToPublicDate":"2023-07-01T10:19:53","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"chapter":"Attachment B1","title":"2023 Coastal master plan: Landscape input data","docAbstract":"Coastal Louisiana is a complex landscape. The composition of the landscape, as well as the processes which influence said landscape, vary in both space and time. The models used in the 2023 Coastal Master Plan must attempt to reflect that spatial and temporal variability. It is therefore of the utmost importance that the spatial data sets upon which the models are initialized are of the highest quality.
This task focused on the compilation and creation of spatial data sets pertaining to parameters necessary to initialize models, calibrate their operations, and/or validate their results. Spatial data sets compiled and/or created as part of this effort include 1) an initial Landscape Composition and Configuration spatial data set, 2) an Integrated Topo/Bathymetric Digital Elevation Model 3) a Wetland Vegetation Community Type data set, and 4) Historical Marsh Edge Erosion Rates.
Each of these data sets constitutes a fundamental descriptor of the coastal landscape, upon which the models depend. This document describes the data sets compiled and the methodologies used to create the best-available spatial data describing the landscape in coastal Louisiana. While data collection dates vary, the data sets created for this effort are intended to represent 2018. The data described herein form initialization data sets upon which most, if not all, models of the 2023 Coastal Master Plan depend in one way or another.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"2023 Louisiana’s comprehensive master plan for a sustainable coast","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"Louisiana Coastal Protection and Restoration Authority","usgsCitation":"Couvillion, B., 2023, 2023 Coastal master plan: Landscape input data (Version 5), 43 p.","productDescription":"43 p.","ipdsId":"IP-151483","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":419826,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":419803,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://coastal.la.gov/our-plan/2023-coastal-master-plan/2023-plan-appendices/"}],"country":"United States","state":"Louisiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -93.79077632406495,\n 30.706267411766817\n ],\n [\n -93.79077632406495,\n 28.854615329475607\n ],\n [\n -88.34722956694776,\n 28.27842992330551\n ],\n [\n -89.00478141362511,\n 30.706267411766817\n ],\n [\n -93.79077632406495,\n 30.706267411766817\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Version 5","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Couvillion, Brady 0000-0001-5323-1687","orcid":"https://orcid.org/0000-0001-5323-1687","contributorId":216668,"corporation":false,"usgs":true,"family":"Couvillion","given":"Brady","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":880149,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70249785,"text":"70249785 - 2023 - Vortex trapping of sand grains over ripples under oscillatory flow","interactions":[],"lastModifiedDate":"2023-10-27T14:14:57.662838","indexId":"70249785","displayToPublicDate":"2023-07-01T09:08:52","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Vortex trapping of sand grains over ripples under oscillatory flow","docAbstract":"Sand ripples significantly impact morphodynamics in the nearshore by generating coherent vortices, which can transport suspended sediment to greater heights in the water column than above flat beds. Coherent vortices can trap sediment grains if the settling velocity of the grain is smaller than the maximum vertical fluid velocity in the vortex (Nielsen 1992). Particle image and tracking velocimetry were used to measure small-scale fluid-sediment interactions over sand ripples in a small oscillatory flow tunnel. Here we present some of the first measurements of vortex-trapped sediment grains under oscillatory flows. Results showed that the vortex-trapped sand grain traversed an orbit offcenter of the vortex near the ripple slope. Some grains then spiralled outward and settled to the bed; others were transported by the flow as the vortex was shed from the crest. Vortex trapping can delay settling and increase settling times, potentially causing inaccurate sediment transport predictions by large-scale numerical models, which do not typically account for this non-linear small-scale process.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of MARID VII","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Marine and River Dunes VII","conferenceDate":"April 3-5, 2023","conferenceLocation":"Rennes, France","language":"English","publisher":"Institute of Physics of Rennes and Geosciences Rennes Laboratory (University of Rennes 1) and the French Naval Hydrographic and Oceanographic Office (Shom)","usgsCitation":"Frank-Gilchrist, D.P., Penko, A., Palmsten, M.L., and Calantoni, J., 2023, Vortex trapping of sand grains over ripples under oscillatory flow, in Proceedings of MARID VII, Rennes, France, April 3-5, 2023, p. 117-123.","productDescription":"7 p.","startPage":"117","endPage":"123","ipdsId":"IP-148729","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":422188,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":422187,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://marid7.sciencesconf.org/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Frank-Gilchrist, Donya P. 0000-0002-7146-0069","orcid":"https://orcid.org/0000-0002-7146-0069","contributorId":292926,"corporation":false,"usgs":true,"family":"Frank-Gilchrist","given":"Donya","email":"","middleInitial":"P.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":887024,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Penko, Allison","contributorId":331234,"corporation":false,"usgs":false,"family":"Penko","given":"Allison","affiliations":[{"id":62875,"text":"U.S. Naval Research Laboratory","active":true,"usgs":false}],"preferred":false,"id":887025,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Palmsten, Margaret L. 0000-0002-6424-2338","orcid":"https://orcid.org/0000-0002-6424-2338","contributorId":239955,"corporation":false,"usgs":true,"family":"Palmsten","given":"Margaret","email":"","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":887026,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Calantoni, Joseph","contributorId":331235,"corporation":false,"usgs":false,"family":"Calantoni","given":"Joseph","email":"","affiliations":[{"id":62875,"text":"U.S. Naval Research Laboratory","active":true,"usgs":false}],"preferred":false,"id":887027,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70248695,"text":"70248695 - 2023 - 2023 PyLith Hackathon report","interactions":[],"lastModifiedDate":"2023-09-19T13:27:25.179777","indexId":"70248695","displayToPublicDate":"2023-07-01T08:26:46","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"2023 PyLith Hackathon report","docAbstract":"The 3rd Pylith Hackathon was held June 12–17, 2023, at the Colorado School of Mines in Golden, Colorado with funding from the Computational Infrastructure for Geodynamics (CIG). The hackathon involved 17 participants working on 5 different projects to implement new features and create new examples for the PyLith crustal deformation modeling software. The projects included (1) spontaneous rupture using fault friction, (2) extending the poroelasticity implementation, (3) developing 2D and 3D examples involving strike-slip faults, (4) integrating PyLith with the cascading adaptive transitional metropolis in parallel (CATMIP) Bayesian inversion framework for use in studies inverting for static fault slip, and (5) adding self-gravitation using the current multiphysics formulation in PyLith. Participants learned how to navigate the PyLith code base, implement point-wise functions for governing equations and bulk and fault rheologies using the finite-element method, extend the code using the modular, object-oriented design, write examples that demonstrate how to use the new features in PyLith simulations, and implement method of manufactured solutions tests and full-scale tests. The PyLith development team benefitted from discussions with the other participants (contributors) about the technical aspects of the various projects as well as general discussions about PyLith design. The in-person format and 6-day duration allowed the groups to make significant progress. Participants appreciated the project-based organization of the hackathon and recommended that future hackathons include online meetings of the various projects before the in-person gathering to self-organize and prepare. Sarah Minson (remote) provided technical advice on the use of the CATMIP Bayesian inversion framework, and this type of participation could be expanded to allow additional technical presentations and advice on various topics in future hackathons.","language":"English","publisher":"Computational Infrastructure for Geodynamics","usgsCitation":"Aagaard, B.T., 2023, 2023 PyLith Hackathon report, 5 p.","productDescription":"5 p.","ipdsId":"IP-156300","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":420948,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":420877,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://geodynamics.org/events/details/287","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Aagaard, Brad T. 0000-0002-8795-9833 baagaard@usgs.gov","orcid":"https://orcid.org/0000-0002-8795-9833","contributorId":192869,"corporation":false,"usgs":true,"family":"Aagaard","given":"Brad","email":"baagaard@usgs.gov","middleInitial":"T.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":883231,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70254723,"text":"70254723 - 2023 - Winners and losers over a ½ century of change in crayfish assemblages of Wyoming, USA","interactions":[],"lastModifiedDate":"2024-06-10T23:58:26.927419","indexId":"70254723","displayToPublicDate":"2023-06-30T10:14:24","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1699,"text":"Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"Winners and losers over a ½ century of change in crayfish assemblages of Wyoming, USA","docAbstract":"Crayfish have experienced extensive assemblage reorganization as a result of global change, with some species becoming globally invasive and others becoming rare or extinct. We combined historical and contemporary sampling data to determine temporal trends of crayfish assemblages of Wyoming, USA, identifying winners and losers over a ½ century of change (1969–2020). We first documented range expansions of several species, including the Virile Crayfish Faxonius virilis (Hagen, 1870), Ringed Crayfish Faxonius neglectus (Faxon, 1885), and Rusty Crayfish Faxonius rusticus (Girard, 1852) as well as range contractions of the Calico Crayfish Faxonius immunis (Hagen, 1870) and Pilose Crayfish Pacifastacus gambelii (Girard, 1852). We then used multispecies occupancy models to investigate potential mechanisms behind the replacement of F. immunis by F. virilis as the most commonly detected crayfish species in Wyoming over time. We hypothesized that F. virilis is more likely to competitively displace F. immunis from more permanent waterbodies, whereas F. immunis is more likely to persist in more ephemeral habitats because of its superior burrowing ability and tolerance of low dissolved oxygen concentrations. Our occupancy models supported this prediction, with F. immunis occupancy declining at more permanent sites in the presence of F. virilis, but F. immunis occupancy was unaffected by F. virilis in less permanent sites. We also found positive associations of F. virilis occupancy and detection probability with water temperature, suggesting that warmer streams may be more vulnerable to new invasions or spread by this species in nonnative regions of western North America. Our results highlight the value of regular, statewide crayfish surveys through documenting substantial changes in Wyoming’s crayfish assemblage structure that may be driven by habitat-mediated competitive interactions.
","language":"English","publisher":"University of Chicago Press","doi":"10.1086/725318","usgsCitation":"Newkirk, B., Larson, E.R., Walker, A.D., and Walters, A.W., 2023, Winners and losers over a ½ century of change in crayfish assemblages of Wyoming, USA: Freshwater Science, v. 42, no. 2, p. 146-160, https://doi.org/10.1086/725318.","productDescription":"15 p.","startPage":"146","endPage":"160","ipdsId":"IP-139290","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":429757,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"42","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Newkirk, Braxton","contributorId":302721,"corporation":false,"usgs":false,"family":"Newkirk","given":"Braxton","email":"","affiliations":[{"id":65540,"text":"Nebraska Cooperative Research Unit","active":true,"usgs":false}],"preferred":false,"id":902883,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Larson, Eric R.","contributorId":175281,"corporation":false,"usgs":false,"family":"Larson","given":"Eric","email":"","middleInitial":"R.","affiliations":[{"id":16989,"text":"University of Tennessee, Knoxville, TN","active":true,"usgs":false}],"preferred":false,"id":902884,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walker, Andrew D.","contributorId":337329,"corporation":false,"usgs":false,"family":"Walker","given":"Andrew","email":"","middleInitial":"D.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":902355,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walters, Annika W. 0000-0002-8638-6682 awalters@usgs.gov","orcid":"https://orcid.org/0000-0002-8638-6682","contributorId":4190,"corporation":false,"usgs":true,"family":"Walters","given":"Annika","email":"awalters@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":902356,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70248105,"text":"70248105 - 2023 - Modeling habitat suitability across different levels of invasive plant abundance","interactions":[],"lastModifiedDate":"2023-10-11T15:53:15.201181","indexId":"70248105","displayToPublicDate":"2023-06-30T09:55:03","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Modeling habitat suitability across different levels of invasive plant abundance","docAbstract":"Predicting where invasive plants are likely to spread and become abundant is critical for informing invasive plant management. Species distribution models are a key tool for informing the geography of invasion risk, but most distribution models are limited by their use of presence data, including no information on invader population abundance. In this study, we ask how habitat suitability varies for different levels of abundance for three invasive plants: stiltgrass (Microstegium vimineum), sericea lespedeza (Lespedeza cuneata), and privet (Ligustrum sinense). For each species, we used an ensemble distribution modeling approach to compare suitability for invasion estimated from subsets of point location data: all presences vs. locations with percent cover ≥ 1%, ≥ 5%, ≥ 10%, ≥ 25%, and ≥ 50%. For all species, the total area predicted as suitable for abundant populations was 32%–68% less than the area predicted as suitable for presence. For stiltgrass and sericea lespedeza, the area suitable for invasion decreased when predicted from higher levels of abundance, whereas for privet, suitable area was similar across abundance levels. Stiltgrass and sericea lespedeza are therefore likely to become highly abundant in a smaller portion of their ranges, while privet could become highly abundant anywhere it can establish at low abundance. Different environmental predictors explained suitability for presence versus abundance, suggesting the environmental niche associated with presence differs from that associated with high population abundance. Analyses of more species and growth forms are still needed, but our results combined with previous studies consistently show that fitting distribution models to point locations with ≥ 5–10% cover refines range maps and can produce a more targeted assessment of invasion risk.
","language":"English","publisher":"Springer","doi":"10.1007/s10530-023-03118-z","usgsCitation":"Beaury, E.M., Jarnevich, C.S., Pearse, I., Evans, A.E., Teich, N., Engelstad, P., LaRoe, J., and Bradley, B., 2023, Modeling habitat suitability across different levels of invasive plant abundance: Biological Invasions, v. 25, p. 3471-3483, https://doi.org/10.1007/s10530-023-03118-z.","productDescription":"13 p.","startPage":"3471","endPage":"3483","ipdsId":"IP-137901","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":435269,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P939IXCP","text":"USGS data release","linkHelpText":"Thresholded abundance models for three invasive plant species in the United States"},{"id":420481,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"25","noUsgsAuthors":false,"publicationDate":"2023-06-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Beaury, Evelyn M.","contributorId":236820,"corporation":false,"usgs":false,"family":"Beaury","given":"Evelyn","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":881874,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jarnevich, Catherine S. 0000-0002-9699-2336 jarnevichc@usgs.gov","orcid":"https://orcid.org/0000-0002-9699-2336","contributorId":3424,"corporation":false,"usgs":true,"family":"Jarnevich","given":"Catherine","email":"jarnevichc@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":881875,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pearse, Ian S. 0000-0001-7098-0495","orcid":"https://orcid.org/0000-0001-7098-0495","contributorId":211154,"corporation":false,"usgs":true,"family":"Pearse","given":"Ian","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":881876,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Evans, Annette E. 0000-0001-6439-4908","orcid":"https://orcid.org/0000-0001-6439-4908","contributorId":328976,"corporation":false,"usgs":false,"family":"Evans","given":"Annette","email":"","middleInitial":"E.","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":881877,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Teich, Nathan","contributorId":328972,"corporation":false,"usgs":false,"family":"Teich","given":"Nathan","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":881878,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Engelstad, Peder","contributorId":238758,"corporation":false,"usgs":false,"family":"Engelstad","given":"Peder","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":881879,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"LaRoe, Jillian 0000-0002-1429-9811","orcid":"https://orcid.org/0000-0002-1429-9811","contributorId":299950,"corporation":false,"usgs":false,"family":"LaRoe","given":"Jillian","affiliations":[{"id":64987,"text":"Student contractor to USGS Fort Collins Science Center","active":true,"usgs":false}],"preferred":false,"id":881880,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bradley, Bethany A. 0000-0003-4912-4971","orcid":"https://orcid.org/0000-0003-4912-4971","contributorId":299998,"corporation":false,"usgs":true,"family":"Bradley","given":"Bethany A.","affiliations":[{"id":64995,"text":"University of Massachusetts, Northeast Climate Adaptation Science Center","active":true,"usgs":false}],"preferred":false,"id":881881,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70251410,"text":"70251410 - 2023 - A new deglacial climate and sea-level record from 20 to 8 ka from IODP381 site M0080, Alkyonides Gulf, eastern Mediterranean","interactions":[],"lastModifiedDate":"2024-02-09T13:10:38.395887","indexId":"70251410","displayToPublicDate":"2023-06-30T07:07:33","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3219,"text":"Quaternary Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"A new deglacial climate and sea-level record from 20 to 8 ka from IODP381 site M0080, Alkyonides Gulf, eastern Mediterranean","docAbstract":"Records of relative sea-level rise for the last deglaciation are mostly limited to coral reef records and geophysical model estimates, but observational data from regions with temperate climates is sparse. We present a new relative climatic and regional sea-level rise record for glacial Termination 1 (Marine Isotope Stages [MIS] 2–1) based on ostracode paleoecology from the upper 8 m of the International Ocean Discovery Program (IODP) Site M0080 collected on Expedition 381, in the Gulf of Alkyonides, eastern Corinth basin of the Mediterranean Sea. Results show a series of major faunal transitions from lacustrine (Ponto-Caspian, Lake Corinth) glacial-age assemblages to fully marine (Mediterranean) interglacial assemblages between 20 and 8 ka. During glacial and early deglacial intervals, the Gulf of Alkyonides was characterized by non-marine lacustrine conditions with episodic sediment input from coastal, saline lake environments. Relatively stable lake shoreline conditions marked by the distinctive Tuberoloxoconcha sp. Existed from ∼17.5 to 15 ka. During the peak deglacial interval, the BØlling-AllerØd (B-A, ∼15–13.5 ka), rapid sea-level rise is indicated by a fully marine ostracode fauna colonization, which persisted from 13.5 to 7.5 ka (Late Pleistocene-Early to Middle Holocene).
","language":"English","publisher":"Elsevier","doi":"10.1016/j.quascirev.2023.108192","usgsCitation":"Mazzini, I., Cronin, T.M., Gawthorpe, R., Collier, R.S., De Gelder, G., Golub, A., Toomey, M., Poirier, R., Huang, H.M., Turkey, M., McNeill, L., and Shillington, D.J., 2023, A new deglacial climate and sea-level record from 20 to 8 ka from IODP381 site M0080, Alkyonides Gulf, eastern Mediterranean: Quaternary Science Reviews, v. 313, 108192, 8 p., https://doi.org/10.1016/j.quascirev.2023.108192.","productDescription":"108192, 8 p.","ipdsId":"IP-154358","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":442896,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.quascirev.2023.108192","text":"Publisher Index 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J.","contributorId":210202,"corporation":false,"usgs":false,"family":"Shillington","given":"Donna","email":"","middleInitial":"J.","affiliations":[{"id":38091,"text":"Lamont Doherty Earth Observatory, Columbia University","active":true,"usgs":false}],"preferred":false,"id":894475,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70246319,"text":"70246319 - 2023 - Using state-and-transition simulation models to scope post-fire success in restoring greater sage-grouse habitat","interactions":[],"lastModifiedDate":"2023-07-05T11:23:52.480787","indexId":"70246319","displayToPublicDate":"2023-06-30T06:40:21","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Using state-and-transition simulation models to scope post-fire success in restoring greater sage-grouse habitat","docAbstract":"Wildfires are increasingly modifying wildlife habitat in the western United States and managers need ways to scope the pace and degree to which post-fire restoration actions can re-create habitat in dynamic landscapes. We developed a spatially explicit state-transition simulation model (STSM) to project post-fire revegetation and the potential for sage-grouse habitat restoration in sagebrush ecosystems. The model included annual fires, annual grass invasion, conifer encroachment, and projected annual vegetation growth caused by natural regeneration as well as sagebrush seeding and planting. We cross-referenced resulting vegetation maps with greater sage-grouse (Centrocercus urophasianus) habitat needs and evaluated trajectories of potential habitat at three Priority Areas for Conservation in the Great Basin. We compared outcomes among different types of revegetation actions (natural regeneration, seeding, planting), treatment durations, and treatment area sizes. In all scenarios, sagebrush cover was generally insufficient to meet sage-grouse needs for at least a decade post-fire, and the best habitat classes declined or remained at low proportions of landscapes for >50 years post-fire. Under current fire patterns, the pace of habitat restoration is likely to lag behind losses from wildfires. Our results indicate additional efforts beyond sagebrush revegetation actions (e.g., fire suppression, invasive grass treatment) will likely be necessary to maintain and restore areas to meet sage-grouse habitat needs in burned landscapes. Our results also underscore the need for broad-scale habitat restoration strategies that expand the ability to reestablish sagebrush in large, burned areas, as well as strategies for defining which areas should be prioritized for revegetation within the biome. Our landscape models and resulting vegetation maps can be integrated with other restoration prioritization or wildlife monitoring tools that support land manager decision-making. By gauging potential benefits of restoration decisions, our approach can provide information to aid choices on where to invest time, money, and effort and how best to mitigate losses and plan long-term restoration and recovery for landscapes across the sagebrush biome.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2023.110396","usgsCitation":"Orning, E.K., Heinrichs, J., Pyke, D.A., Coates, P.S., and Aldridge, C.L., 2023, Using state-and-transition simulation models to scope post-fire success in restoring greater sage-grouse habitat: Ecological Modelling, v. 483, 110396, 19 p., https://doi.org/10.1016/j.ecolmodel.2023.110396.","productDescription":"110396, 19 p.","ipdsId":"IP-150259","costCenters":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":442902,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolmodel.2023.110396","text":"Publisher Index Page"},{"id":435271,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PYHZF7","text":"USGS data release","linkHelpText":"State-and-Transition Simulation Models to explore post-fire habitat restoration in three greater sage-grouse (Centrocercus urophasianus) Priority Areas for Conservation, USA (2018-2068)"},{"id":418676,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Great Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.1530893537961,\n 46.72935427298586\n ],\n [\n -121.1530893537961,\n 34.336583229480425\n ],\n [\n -107.711590841332,\n 34.336583229480425\n ],\n [\n -107.711590841332,\n 46.72935427298586\n ],\n [\n -121.1530893537961,\n 46.72935427298586\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"483","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Orning, Elizabeth Kari 0000-0002-1376-729X","orcid":"https://orcid.org/0000-0002-1376-729X","contributorId":315548,"corporation":false,"usgs":true,"family":"Orning","given":"Elizabeth","email":"","middleInitial":"Kari","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":876800,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Heinrichs, Julie A. 0000-0001-7733-5034","orcid":"https://orcid.org/0000-0001-7733-5034","contributorId":240888,"corporation":false,"usgs":false,"family":"Heinrichs","given":"Julie A.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":876801,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pyke, David A. 0000-0002-4578-8335 david_a_pyke@usgs.gov","orcid":"https://orcid.org/0000-0002-4578-8335","contributorId":3118,"corporation":false,"usgs":true,"family":"Pyke","given":"David","email":"david_a_pyke@usgs.gov","middleInitial":"A.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":876802,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Coates, Peter S. 0000-0003-2672-9994 pcoates@usgs.gov","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":3263,"corporation":false,"usgs":true,"family":"Coates","given":"Peter","email":"pcoates@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":876803,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Aldridge, Cameron L. 0000-0003-3926-6941 aldridgec@usgs.gov","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":191773,"corporation":false,"usgs":true,"family":"Aldridge","given":"Cameron","email":"aldridgec@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":876804,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70247013,"text":"70247013 - 2023 - Constraints on near-ridge magmatism using 40Ar/39Ar geochronology of enriched MORB from the 8°20' N seamount chain","interactions":[],"lastModifiedDate":"2023-08-08T14:42:32.909724","indexId":"70247013","displayToPublicDate":"2023-06-29T16:09:54","publicationYear":"2023","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}},"displayTitle":"Constraints on near-ridge magmatism using 40Ar/39Ar geochronology of enriched MORB from the 8°20' N seamount chain","title":"Constraints on near-ridge magmatism using 40Ar/39Ar geochronology of enriched MORB from the 8°20' N seamount chain","docAbstract":"Our understanding of the spatial-temporal-compositional relationships between off-axis magmatism and mid-ocean ridge spreading centers is limited. Determining the 40Ar/39Ar ages of mid-ocean ridge basalt (MORB) lavas erupting near mid-ocean ridges (MOR) has been a challenge due to the characteristically low K2O contents in incompatible element-depleted normal MORB (NMORB). High-precision 40Ar/39Ar geochronology is used here to determine ages of young, basaltic lavas erupted along the 8°20' N seamount chain west of the East Pacific Rise (EPR) axis that have a range of incompatible element enrichments (EMORB) suitable for 40Ar/39Ar geochronology (e.g., K2O contents > 0.3 wt%). 40Ar/39Ar ages were determined in 29 well-characterized basalts sampled using HOV Alvin and dredging. Detailed geochronology and geochemical analyses provide important constraints on the timing, distribution, and origins of lavas that constructed this extensive volcanic lineament relative to magmatism beneath the adjacent EPR axis. Seamount eruption ages are up to ∼1.6 Ma younger than the underlying lithosphere, supporting a model of prolonged off-axis magmatism for at least 2 Myrs at distances as great as ∼90 km from the ridge axis. Increasing geochemical heterogeneity with eruption distance reflects the diminishing effect of sub-ridge melt focusing. The range of geochemically distinct lavas erupted at given distances from the ridge highlights the dynamic nature of the near-ridge magmatic environment over Myr timescales. Linear ridge-like (EPR-parallel) morphotectonic features erupt the youngest and most incompatible element-enriched lavas of the entire seamount chain, indicating there is a recent change in the influence of mantle heterogeneity and off-axis melt metasomatism on the near-ridge lithospheric mantle. Changes in seamount morphologies are attributed to counter-clockwise rotation and southward migration of the nearby Siqueiros transform over the last few million years.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2023.118278","usgsCitation":"Anderson, M., Perfit, M., Morgan, L.E., Fornari, D., Cosca, M.A., and Wanless, V.D., 2023, Constraints on near-ridge magmatism using 40Ar/39Ar geochronology of enriched MORB from the 8°20' N seamount chain: Earth and Planetary Science Letters, v. 618, 118278, 12 p.; Data Release, https://doi.org/10.1016/j.epsl.2023.118278.","productDescription":"118278, 12 p.; Data Release","ipdsId":"IP-147683","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":442904,"rank":4,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.epsl.2023.118278","text":"Publisher Index Page"},{"id":435272,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ECGKYO","text":"USGS data release","linkHelpText":"Argon data for enriched MORB from the 8°20' N seamount chain"},{"id":419230,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":419594,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://www.sciencebase.gov/catalog/item/623c7021d34e915b67d2ddc8","text":"Argon data for enriched MORB from the 8°20' N seamount chain","linkFileType":{"id":5,"text":"html"}}],"otherGeospatial":"East Pacific Rise, Pacific Ocean","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -106,\n 9\n ],\n [\n -106,\n 7.75\n ],\n [\n -104,\n 7.75\n ],\n [\n -104,\n 9\n ],\n [\n -106,\n 9\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"618","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Anderson, Molly","contributorId":316857,"corporation":false,"usgs":false,"family":"Anderson","given":"Molly","email":"","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":878547,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perfit, Michael","contributorId":13736,"corporation":false,"usgs":false,"family":"Perfit","given":"Michael","affiliations":[],"preferred":false,"id":878548,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morgan, Leah E. 0000-0001-9930-524X lemorgan@usgs.gov","orcid":"https://orcid.org/0000-0001-9930-524X","contributorId":176174,"corporation":false,"usgs":true,"family":"Morgan","given":"Leah","email":"lemorgan@usgs.gov","middleInitial":"E.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":878549,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fornari, Daniel","contributorId":316858,"corporation":false,"usgs":false,"family":"Fornari","given":"Daniel","affiliations":[{"id":68715,"text":"Woods Hole, Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":878550,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cosca, Michael A. 0000-0002-0600-7663 mcosca@usgs.gov","orcid":"https://orcid.org/0000-0002-0600-7663","contributorId":1000,"corporation":false,"usgs":true,"family":"Cosca","given":"Michael","email":"mcosca@usgs.gov","middleInitial":"A.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":878551,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wanless, V. 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Consequently, efforts to assess the condition of stream fishes and their habitats must not only attempt to characterize the effects of human stressors but must account for the effects of natural influences as well. This study is an assessment of all stream fish habitats in the Mississippi River basin, USA. The basin supports over 400 stream fish species, drains a land area of 3.2 M km2, and includes a myriad of human stressors such as intensive agriculture, urbanization, nutrient loading, and habitat fragmentation by dams and road/stream crossings. To effectively characterize types and levels of human stressors specifically impacting the basin’s stream fish species, our assessment approach first accounted for the influence of natural landscape conditions on species abundances with multiple steps, including stratifying our analyses by region and stream size and quantitatively modeling the influences of natural factors on stream fishes. We next quantified individual fish species responses to explicit human stressors for different measures of land use, fragmentation, and water quality, including summaries of measures in local vs. catchment extents. Results showed that many species had negative threshold responses to human stressors and that impacts varied by species, by region, and by the spatial extents in which stressors were summarized. Our spatially explicit results indicated the degree of stream reach impairment for specific stressor categories, for individual species, and for entire assemblages, all of which are types of information that can aid decision makers in achieving specific conservation goals in the region.
","language":"English","publisher":"MDPI","doi":"10.3390/w15132400","usgsCitation":"Ross, J., Infante, D.M., Cooper, A.R., Whittier, J.B., and Daniel, W., 2023, Assessing impacts of human stressors on stream fish habitats across the Mississippi River basin: Water, v. 15, no. 13, 2400, 19 p., https://doi.org/10.3390/w15132400.","productDescription":"2400, 19 p.","ipdsId":"IP-154339","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":442912,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w15132400","text":"Publisher Index Page"},{"id":419562,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Mississippi River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -88.70500995271088,\n 29.01665894418747\n ],\n [\n -87.84690317711288,\n 33.54915630164602\n ],\n [\n -81.00873115774787,\n 37.45591553762907\n ],\n [\n -78.93790401814765,\n 41.96679217920834\n ],\n [\n -83.62542898487561,\n 41.81918715620617\n ],\n [\n -87.73555865475336,\n 41.70064246159154\n ],\n [\n -88.67261557203858,\n 44.96630422012075\n ],\n [\n -93.08599492063011,\n 47.38065175487887\n ],\n [\n -98.48423664388794,\n 48.43354009429689\n ],\n [\n -112.80019584593275,\n 48.34084011217669\n ],\n [\n -109.13885539240077,\n 44.853455766288505\n ],\n [\n -105.17484654049274,\n 41.33941938263584\n ],\n [\n -103.17753122235543,\n 38.76054766960715\n ],\n [\n -101.04477212147036,\n 36.16726262455268\n ],\n [\n -98.00084294825474,\n 32.268870505741845\n ],\n [\n -92.62187823928058,\n 29.79492566370429\n ],\n [\n -88.70500995271088,\n 29.01665894418747\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","issue":"13","noUsgsAuthors":false,"publicationDate":"2023-06-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Ross, Jared 0000-0002-0582-3589","orcid":"https://orcid.org/0000-0002-0582-3589","contributorId":289993,"corporation":false,"usgs":false,"family":"Ross","given":"Jared","email":"","affiliations":[{"id":6590,"text":"Department of Fisheries and Wildlife, Michigan State University","active":true,"usgs":false}],"preferred":false,"id":879593,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Infante, Dana M.","contributorId":146114,"corporation":false,"usgs":false,"family":"Infante","given":"Dana","email":"","middleInitial":"M.","affiliations":[{"id":16583,"text":"Department of Fisheries and Wildlife, 480 Wilson Rd. 13 Natural Resources Building, Michigan State University, East Lansing, MI 48824","active":true,"usgs":false}],"preferred":false,"id":879594,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cooper, Arthur R.","contributorId":187646,"corporation":false,"usgs":false,"family":"Cooper","given":"Arthur","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":879595,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Whittier, Joanna B.","contributorId":53151,"corporation":false,"usgs":false,"family":"Whittier","given":"Joanna","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":879596,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Daniel, Wesley 0000-0002-7656-8474","orcid":"https://orcid.org/0000-0002-7656-8474","contributorId":219312,"corporation":false,"usgs":true,"family":"Daniel","given":"Wesley","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":879597,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70245765,"text":"ofr20231040 - 2023 - Least Bell's Vireos and Southwestern Willow Flycatchers at the San Luis Rey Flood Risk Management Project Area in San Diego County, California—Breeding activities and habitat use—2022 annual report","interactions":[],"lastModifiedDate":"2023-06-30T10:52:30.004365","indexId":"ofr20231040","displayToPublicDate":"2023-06-29T09:10:19","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-1040","displayTitle":"Least Bell's Vireos and Southwestern Willow Flycatchers at the San Luis Rey Flood Risk Management Project Area in San Diego County, California: Breeding Activities and Habitat Use—2022 Annual Report","title":"Least Bell's Vireos and Southwestern Willow Flycatchers at the San Luis Rey Flood Risk Management Project Area in San Diego County, California—Breeding activities and habitat use—2022 annual report","docAbstract":"We completed four protocol surveys for Least Bell’s Vireos (Vireo bellii pusillus; vireo) during the breeding season, supplemented by weekly territory monitoring visits. We identified a total of 133 territorial male vireos; 114 were confirmed as paired, and 3 were confirmed as single males. For the remaining 16 territories, we were unable to confirm breeding status. Two transient vireos were detected in 2022. The vireo population in the Project Area increased by 9 percent from 2021 to 2022. The vireo population at Marine Corps Base Camp Pendleton also increased (4 percent), whereas the population at Marine Corps Air Station remained relatively stable (decreased from 10 pairs to 9) and the Otay River population decreased by 10 percent (2 territories).
We used an index of treatment (Treatment Index) to evaluate the effect of on-going vegetation clearing on the Project Area vireo population. The Treatment Index measures the cumulative effect of vegetation treatment within a territory (since 2005) by using the percentage area treated weighted by the number of years since treatment. We determined that the Treatment Index for unoccupied habitat was more than four times that of occupied habitat, indicating that vireos selected habitat that was less treated in which to settle.
We monitored vireo nests at three general site types: (1) within the flood channel where exotic and native vegetation removal has occurred regularly (Channel), (2) three sites near the flood channel where limited exotic and native vegetation removal has occurred (Off-channel), and (3) three sites that have been actively restored by planting native vegetation (Restoration). Nesting activity was monitored in 80 territories, 3 of which were occupied by single males and 1 by a male whose breeding status could not be confirmed. Overall, 38 percent of completed nests were successful and nest success did not differ among the three sites. In 2022, there were no differences with regard to clutch size, hatching, or fledging success among Channel, Off-channel and Restoration sites. Overall breeding success and productivity were slightly higher in 2022 than in 2021, with 72 percent of pairs fledgling at least one young and pairs fledging an average of 2.2±1.7 young.
To investigate if the cumulative years of treatment had an effect on vireo reproductive effort, we looked at the effects of the Treatment Index on reproductive parameters. Results from generalized linear models indicated that treatment did not have an effect on vireo nesting effort or the number of vireo fledglings per pair produced in 2022. Similarly, we did not detect an effect of Treatment Index on daily survival rate (DSR) of nests.
Analysis of vegetation data collected at vireo nests from 2006 to 2022 did not reveal an effect of vegetation cover at the nest on DSR. We did find, however, that Channel nests were placed higher in the host plant than Off-channel nests. In the Channel and Off-channel sites, successful nests were placed closer to the edge of the host plants than unsuccessful nests. Additionally, successful Off-channel nests were placed lower in the vegetation, in shorter host plants, and closer to the edge of the vegetation clump than unsuccessful nests.
Red/arroyo willow (Salix laevigata or Salix lasiolepis) were the species most commonly selected for nesting by vireos in all three site types. Black willow (Salix gooddingii) and mule fat (Baccharis salicifolia) also were commonly used. Vireos used a wider variety of species for nesting in Channel and Off-channel sites (eight and six species, respectively) compared to Restoration sites (two species), although there was limited nesting in Restoration sites in 2022.
There were 43 vireos banded before the 2022 breeding season that were resighted and identified at the Project Area in 2022, all of which were originally banded in the Project Area. Adult birds of known age ranged from 1 to 7 years old. A total of 146 vireos were newly banded in 2022. There were 8 adult vireos banded with a unique color combination, and 138 nestlings were banded with a single dark blue numbered federal band on the left leg. Between 2006 and 2022, survivorship of males (66±11 percent) was consistently higher than that of females (59±12 percent). First-year birds from 2006 to 2022 had an average annual survivorship of 15±6 percent.
First-year dispersal in 2022 averaged 6.7±7.4 kilometers (km), with the longest dispersal (15.3 km) by a male that was recaptured at Fallbrook Creek, Fallbrook Naval Weapons Station (FNWS). From 2007 to 2011, most returning first-year vireos returned to the Project Area, whereas from 2014 to 2016, the majority of returning birds dispersed to areas outside of the Project Area. From 2018 to 2021, the trend shifted, and more first-year vireos returned to the Project area. In 2022, only one first-year vireo returned to the project area and two dispersed to sites outside the Project Area (upstream to the middle San Luis Rey River and to Fallbrook Creek, FNWS). However, the total number of identified first-year vireos was low and the trend in 2022 will likely shift as additional returning first-year vireos are identified in subsequent years.
Most of the returning adult male vireos showed strong between-year site fidelity to their previous territories. Seventy-three percent of males (27/37) occupied a territory in 2022 that they had defended in 2021 (within 100 meters [m]). There were no females (0/4) detected in 2022 that returned to a territory they occupied in 2021; however, 50 percent of females (2/4) detected in 2022 returned to areas adjacent to their previous territories (within 300 m). The average between-year movement for returning adult vireos was 0.3±0.7 km. The amount of treatment at adults’ 2021 territories did not affect the distance adults moved to their 2022 territories.
We completed four protocol surveys for the endangered Southwestern Willow Flycatcher (Empidonax traillii extimus; flycatcher) at the Project Area between May 16 and July 25, 2022. Four transient Willow Flycatchers were detected in the Project Area in 2022. Two transients were detected in Reach 1, one in Reach 3a, and one in Pilgrim Pond. There were not any resident flycatchers documented in the Project Area in 2022.
A total of 46 vegetation transects (528 points) were sampled at the Project Area in 2022. Seventy-one percent (378/528) of points were located in the Channel, and 22 percent (115/528) were in Upper Pond. The remaining 7 percent (35/528) of points were at the Whelan Restoration site. Foliage cover below 2 m was higher at the Channel points compared to Upper Pond and Whelan Restoration, which can be attributed to the dense herbaceous vegetation that grows after mowing. Above 2 m, foliage cover was similar at the Channel and Whelan Restoration sites and was higher than at Upper Pond. Average canopy height was higher in the Channel (5.6±3.4 m) compared to Upper Pond (4.7±2.9 m) and Whelan Restoration (4.6±1.9 m). From 2006 to 2022, total foliage cover declined above 2 m in the Channel, in contrast to Upper Pond and Whelan Restoration, where little directional change in vegetation cover has occurred and where vegetation cover has largely recovered to 2006 levels. Within the Channel, the steepest declines occurred between 2009 and 2013 and between 2014 and 2016. Since 2016, we observed an increase in foliage cover, largely herbaceous, between 0 and 2 m within the Channel. The percent cover remained below levels detected before 2009 for other height classes.
We sampled vegetation at 44 vireo nests and 44 random plots (“territory” plots) within territories in the Channel and Upper Pond after the 2022 breeding season. Vireos in the Channel established territories in areas with significantly more cover from 3 to 6 m but less cover below 2 m relative to the available habitat. Within territories, Channel vireos selected nest sites with significantly more foliage cover from 2 to 3 m. Vireos at Upper Pond established territories in areas with significantly more foliage cover from 5 to 6 m and below 1 m relative to available habitat. However, within territories, Upper Pond vireos selected nest sites with significantly less foliage cover from 5 to 6 m and below 1 m.
Data either are not available or have limited availability owing to restrictions of the funding entity (U.S. Army Corps of Engineers). Please contact Christopher Chabot, Planning Division, Los Angeles District, U.S. Army Corps of Engineers, for more information.
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Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
Mobile radio tracking is an important tool in fisheries research and management. Yet, the accuracy of location estimates can be highly variable across studies and within a given dataset. While some methods are available to deal with error, they generally assume a static value for error across all detections. We provide a novel method for making detection-specific error estimates using detections of recovered transmitters (i.e., mortalities or tag expulsion). These data are used to establish the relationship between received signal strength (RSS) and positional error, which can then be used to predict positional error of detections for fish at large. We then show how detection-specific estimates can be integrated into a Monte Carlo framework to analyze movement in ways robust to spatial uncertainty.
In a telemetry study in a large river (~ 90 m), we recovered 22 transmitters to estimate and model positional error. Error averaged 94 m (range = 1–727 m) for transmitters tracked by researchers on foot using a Yagi antenna, and 200 m (range = 1–1141 m) for transmitters tracked from vehicles using an omnidirectional whip antenna. Transmitters located near roads were tracked more accurately with both methods. Received signal strength was a strong predictor of positional error (r2 = 0.86, ground tracking; 0.65, tracking from truck) and was thus used to make detection-specific estimates of error for detections of fish at large. Monte Carlo analysis for a binary movement classification revealed that only 18% of location estimates could be confidently assigned to movement (p < 0.05); the remainder were associated with stasis or movement that was within the range of positional error. Ignoring positional error led to positive bias of up to 1300% in individual movement estimates and varied seasonally—it was highest when fish were inactive and lowest when fish were most active.
Using recovered transmitters and RSS models to estimate telemetry error is a viable alternative to staged ‘dummy transmitter’ trials and assuming error is a constant. Our proposed approaches to incorporate detection-specific error estimates into analysis are broadly applicable and can ‘make the most’ out of highly accurate detections while also cautiously extracting spatial information from less-accurate detections.
Climate change is leading to species redistributions. In the tundra biome, shrubs are generally expanding, but not all tundra shrub species will benefit from warming. Winner and loser species, and the characteristics that may determine success or failure, have not yet been fully identified. Here, we investigate whether past abundance changes, current range sizes and projected range shifts derived from species distribution models are related to plant trait values and intraspecific trait variation. We combined 17,921 trait records with observed past and modelled future distributions from 62 tundra shrub species across three continents. We found that species with greater variation in seed mass and specific leaf area had larger projected range shifts, and projected winner species had greater seed mass values. However, trait values and variation were not consistently related to current and projected ranges, nor to past abundance change. Overall, our findings indicate that abundance change and range shifts will not lead to directional modifications in shrub trait composition, since winner and loser species share relatively similar trait spaces.
","language":"English","publisher":"Springer Nature","doi":"10.1038/s41467-023-39573-4","usgsCitation":"Garcia Criado, M., Myers-Smith, I.H., Bjorkman, A., Normand, S., Blach-Overgaard, A., Thomas, H.J., Eskelinen, A., Happonen, K., Alatalo, J., Anadon-Rosell, A., Aubin, I., te Beest, M., Betway-May, K.R., Blok, D., Buras, A., Cerabolini, B.E., Christie, K.S., Cornelissen, J.H., Forbes, B.C., Frei, E.R., Grogan, P., Hermanutz, L., Hollister, R.D., Hudson, J., Iturrate-Garcia, M., Kaarlejarvi, E., Kleyer, M., Lamarque, L.J., Lembrechts, J.J., Levesque, E., Luoto, M., Macek, P., May, J., Prevey, J.S., Schaepman-Strub, G., Sheremetiev, S.N., Siegwart Collier, L., Soudzilovskaia, N.A., Trant, A., Venn, S.E., and Virkkala, A., 2023, Plant traits poorly predict winner and loser shrub species in a warming tundra biome: Nature Communications, v. 14, 3837, 17 p., https://doi.org/10.1038/s41467-023-39573-4.","productDescription":"3837, 17 p.","ipdsId":"IP-135517","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":442929,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41467-023-39573-4","text":"Publisher Index Page"},{"id":420469,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Northern Hemisphere","volume":"14","noUsgsAuthors":false,"publicationDate":"2023-06-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Garcia Criado, Mariana","contributorId":328994,"corporation":false,"usgs":false,"family":"Garcia Criado","given":"Mariana","email":"","affiliations":[{"id":61891,"text":"School of GeoSciences, University of Edinburgh, Kings Buildings, 113 Crew Building, West Mains Road, Edinburgh EH9 3FF, UK","active":true,"usgs":false}],"preferred":false,"id":881901,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Myers-Smith, Isla H.","contributorId":328995,"corporation":false,"usgs":false,"family":"Myers-Smith","given":"Isla","email":"","middleInitial":"H.","affiliations":[{"id":61891,"text":"School of GeoSciences, University of Edinburgh, Kings Buildings, 113 Crew Building, West Mains Road, Edinburgh EH9 3FF, UK","active":true,"usgs":false}],"preferred":false,"id":881902,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bjorkman, Anne 0000-0003-2174-7800","orcid":"https://orcid.org/0000-0003-2174-7800","contributorId":260911,"corporation":false,"usgs":false,"family":"Bjorkman","given":"Anne","email":"","affiliations":[{"id":52710,"text":"(1) Department of Biological and Environmental Sciences, University of Gothenburg, Gothenburg, Sweden (2) Gothenburg Global Biodiversity Centre, Gothenburg, Sweden","active":true,"usgs":false}],"preferred":false,"id":881903,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Normand, Signe","contributorId":30545,"corporation":false,"usgs":true,"family":"Normand","given":"Signe","email":"","affiliations":[],"preferred":false,"id":881904,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Blach-Overgaard, Anne","contributorId":328999,"corporation":false,"usgs":false,"family":"Blach-Overgaard","given":"Anne","email":"","affiliations":[{"id":52728,"text":"Department of Biology, Aarhus University, Denmark","active":true,"usgs":false}],"preferred":false,"id":881905,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Thomas, Haydn J. 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Jaguars (Panthera onca) are one such species whose population trends and survival rates remain unknown across working lands. We integrated nine years of camera trap data and tourist photos to estimate jaguar density, survival, abundance, and probability of tourist sightings on a working ranch and tourism destination in Colombia. We found that abundance increased from five individuals in 2014 to 28 in 2022, and density increased from 1.88 ± 0.87 per 100 km2 in 2014 to 3.80 ± 1.08 jaguars per 100 km2 in 2022. The probability of a tourist viewing a jaguar increased from 0% in 2014 to 40% in 2020 before the Covid-19 pandemic. Our results are the first robust estimates of jaguar survival and abundance on working lands. Our findings highlight the importance of productive lands for jaguar conservation and suggest that a tourism destination and working ranch can host an abundant population of jaguars when accompanied by conservation agreements and conflict interventions. Our analytical model that combines conventional data collection with tourist sightings can be applied to other species that are observed during tourism activities.
","language":"English","publisher":"Nature","doi":"10.1038/s41598-023-36935-2","usgsCitation":"Hyde, M., Payan, E., Barragan, J., Stasiukynas, D., Kendall, W.L., Rincon, S., Rodriguez, J., Crooks, K., Breck, S., and Boron, V., 2023, Tourism-supported working lands sustain a growing jaguar population in the Colombian Llanos: Scientific Reports, v. 13, 10408, 11 p., https://doi.org/10.1038/s41598-023-36935-2.","productDescription":"10408, 11 p.","ipdsId":"IP-151847","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":442932,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-023-36935-2","text":"Publisher Index Page"},{"id":430051,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","noUsgsAuthors":false,"publicationDate":"2023-06-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Hyde, Matthew","contributorId":338376,"corporation":false,"usgs":false,"family":"Hyde","given":"Matthew","email":"","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":903230,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Payan, Esteban","contributorId":338377,"corporation":false,"usgs":false,"family":"Payan","given":"Esteban","email":"","affiliations":[{"id":81049,"text":"Panthera","active":true,"usgs":false}],"preferred":false,"id":903231,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barragan, Jorge","contributorId":338378,"corporation":false,"usgs":false,"family":"Barragan","given":"Jorge","email":"","affiliations":[{"id":81123,"text":"Reserva Natural de la Sociedad Civil Hato La Aurora","active":true,"usgs":false}],"preferred":false,"id":903232,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stasiukynas, Diana","contributorId":338379,"corporation":false,"usgs":false,"family":"Stasiukynas","given":"Diana","email":"","affiliations":[{"id":81049,"text":"Panthera","active":true,"usgs":false}],"preferred":false,"id":903233,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kendall, William L. 0000-0003-0084-9891","orcid":"https://orcid.org/0000-0003-0084-9891","contributorId":204844,"corporation":false,"usgs":true,"family":"Kendall","given":"William","email":"","middleInitial":"L.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":903234,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rincon, Samantha","contributorId":338382,"corporation":false,"usgs":false,"family":"Rincon","given":"Samantha","email":"","affiliations":[{"id":81049,"text":"Panthera","active":true,"usgs":false}],"preferred":false,"id":903235,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rodriguez, Jeronimo","contributorId":338383,"corporation":false,"usgs":false,"family":"Rodriguez","given":"Jeronimo","email":"","affiliations":[{"id":81049,"text":"Panthera","active":true,"usgs":false}],"preferred":false,"id":903236,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Crooks, Kevin R.","contributorId":338384,"corporation":false,"usgs":false,"family":"Crooks","given":"Kevin R.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":903237,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Breck, Stewart W.","contributorId":338385,"corporation":false,"usgs":false,"family":"Breck","given":"Stewart W.","affiliations":[{"id":81125,"text":"United States Department of Agriculture (USDA)-Wildlife Services","active":true,"usgs":false}],"preferred":false,"id":903238,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Boron, Valeria","contributorId":338386,"corporation":false,"usgs":false,"family":"Boron","given":"Valeria","email":"","affiliations":[{"id":81049,"text":"Panthera","active":true,"usgs":false}],"preferred":false,"id":903239,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70245175,"text":"ofr20231035 - 2023 - Integrated rangeland fire management strategy actionable science plan completion assessment— Climate and weather topic, 2015–20","interactions":[],"lastModifiedDate":"2026-02-11T21:13:34.077099","indexId":"ofr20231035","displayToPublicDate":"2023-06-27T12:48:18","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-1035","displayTitle":"Integrated Rangeland Fire Management Strategy Actionable Science Plan Completion Assessment: Climate and Weather Topic, 2015–20","title":"Integrated rangeland fire management strategy actionable science plan completion assessment— Climate and weather topic, 2015–20","docAbstract":"Loss and degradation of sagebrush (Artemisia spp.) rangelands due to an accelerated invasive annual grass-wildfire cycle and other stressors are significant management, conservation, and economic issues in the western U.S. These sagebrush rangelands comprise a unique biome spanning 11 states, support over 350 wildlife species, and provide important ecosystem services that include stabilizing the economies of western communities. Impacts to sagebrush ecosystem processes over large areas due to the annual grass-wildfire cycle necessitated the development of a coordinated, science-based strategy for improving efforts to achieve long-term protection, conservation, and restoration of sagebrush rangelands, which was framed in 2015 under the Integrated Rangeland Fire Management Strategy (IRFMS). Central to this effort was the development of an Actionable Science Plan (Plan) that identified 37 priority science needs (hereinafter, “Needs”) for informing the actions proposed under the five topics (Fire, Invasives, Restoration, Sagebrush and Sage-Grouse (Centrocercus urophasianus), Climate and Weather) that were part of the collective focus of the IRFMS. Notable keys to this effort were identification of the Needs co-produced by managers and researchers, and a focus on resulting science being “actionable.”
Substantial investments aimed at fulfilling the Needs identified in the Plan have been made since its release in 2016. While the state of the science has advanced considerably, the extent to which knowledge gaps remain relative to identified Needs is relatively unknown. Moreover, new Needs have likely emerged since the original strategy as results from actionable science reveal new questions and possible (yet untested) solutions. A quantifiable assessment of the progress made on the original science Needs can identify unresolved gaps and new information that can help inform prioritization of future research efforts.
This report details a systematic literature review that evaluated how well peer-reviewed journal articles and formal technical reports published between January 1, 2015, and December 31, 2020, addressed four Needs identified under the Climate and Weather topic in the Plan. The topic outlined research Needs broadly focused on understanding the potential effects of climate change on vegetative resilience to inform restoration of sagebrush rangelands. We established the level of progress towards addressing each Need following a standardized set of criteria, and developed summaries detailing how research objectives nested within Needs identified in the Plan (hereinafter, “Next Steps”) were either addressed well, partially addressed or remain outstanding (that is, addressed poorly) in the literature through 2020. Our searches resulted in the inclusion of 92 science products that at least partially addressed a Need identified in the Climate and Weather topic. The Needs that were well and partially addressed included:
The Need addressed poorly was the identification of native plant species, genotypes and ecotypes, and seed mixes that may be resilient to a changing climate. The information provided in this assessment will assist updating the Plan, and can inform updates of other relevant science planning documents as needed.
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Living shorelines gain increasing attention because they stabilize shorelines and reduce erosion. This study leverages physics-based models and bagged regression tree (BRT) machine learning algorithm to simulate wave dynamics at a living shoreline composed of constructed oyster reefs (CORs) in upper Delaware Bay. The physics-based models consist of coupled Delft3D-FLOW and SWAN in four-level nested domains. The model accuracy converges with increasing mesh resolution. The simulated wave-induced current circulation substantiates the effectiveness of CORs in trapping sediments. The simulated yearly-averaged wave power correlates qualitatively with historical shoreline retreat rates. BRT is adopted to improve the model accuracy, identify key processes responsible for simulation errors in wave height (H8) and wave period (Tp), and quantify their importance. In the CORs sheltered area, BRT reveals that simulation errors of wind seas mainly arise from wind forcing, wave breaking and wave triad interactions. Wave breaking is seven times more important than wind forcing for simulating H8, while wind forcing and triad interactions are of equal importance for simulating Tp. Simulation errors of swells mostly stem from bottom friction and offshore wave boundary conditions. Results from this study can help the assessment and adaptive management of CORs-based living shoreline restoration projects under climate change.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.oceaneng.2023.115207","usgsCitation":"Zhu, L., Chen, Q., Wang, H., Wang, N., Hu, K., Capurso, W.D., Niemoczynski, L., and Snedden, G., 2023, Modeling surface wave dynamics in upper Delaware Bay with living shorelines: Ocean Engineering, v. 284, 115207, 17 p., https://doi.org/10.1016/j.oceaneng.2023.115207.","productDescription":"115207, 17 p.","ipdsId":"IP-146841","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":419147,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Jersey","otherGeospatial":"upper Delaware Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.244,\n 39.2775\n ],\n [\n -75.244,\n 39.2755\n ],\n [\n -75.241,\n 39.2755\n ],\n [\n -75.241,\n 39.2775\n ],\n [\n -75.244,\n 39.2775\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"284","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Zhu, Ling 0000-0003-0261-6848","orcid":"https://orcid.org/0000-0003-0261-6848","contributorId":222169,"corporation":false,"usgs":false,"family":"Zhu","given":"Ling","affiliations":[{"id":38331,"text":"Northeastern University","active":true,"usgs":false}],"preferred":false,"id":878283,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chen, Q. 0000-0002-6540-8758","orcid":"https://orcid.org/0000-0002-6540-8758","contributorId":56532,"corporation":false,"usgs":false,"family":"Chen","given":"Q.","affiliations":[{"id":38331,"text":"Northeastern University","active":true,"usgs":false}],"preferred":true,"id":878284,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wang, Hongqing 0000-0002-2977-7732","orcid":"https://orcid.org/0000-0002-2977-7732","contributorId":221902,"corporation":false,"usgs":true,"family":"Wang","given":"Hongqing","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":878285,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wang, Nan 0000-0001-7569-9598","orcid":"https://orcid.org/0000-0001-7569-9598","contributorId":291600,"corporation":false,"usgs":false,"family":"Wang","given":"Nan","email":"","affiliations":[{"id":38331,"text":"Northeastern University","active":true,"usgs":false}],"preferred":false,"id":878286,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hu, Kelin","contributorId":177218,"corporation":false,"usgs":false,"family":"Hu","given":"Kelin","email":"","affiliations":[],"preferred":false,"id":878287,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Capurso, William D. 0000-0003-1182-2846","orcid":"https://orcid.org/0000-0003-1182-2846","contributorId":218672,"corporation":false,"usgs":true,"family":"Capurso","given":"William","email":"","middleInitial":"D.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":878288,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Niemoczynski, Lukasz M. 0000-0003-2008-9148","orcid":"https://orcid.org/0000-0003-2008-9148","contributorId":222171,"corporation":false,"usgs":true,"family":"Niemoczynski","given":"Lukasz","middleInitial":"M.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":878289,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Snedden, Gregg 0000-0001-7821-3709","orcid":"https://orcid.org/0000-0001-7821-3709","contributorId":213411,"corporation":false,"usgs":true,"family":"Snedden","given":"Gregg","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":878290,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ]}