Disturbances to aquatic habitats are not uniformly distributed within the Great Lakes and acute effects can be strongest in nearshore areas where both landscape and within lake effects can have strong influence. Furthermore, different fish species respond to disturbances in different ways. A means to identify and evaluate locations and extent of disturbances that affect fish is needed throughout the Great Lakes. We used partial Canonical Correspondence Analysis to separate “natural” effects on nearshore assemblages from disturbance effects. Species-specific quadratic models of fish abundance as functions of in-lake disturbance or watershed-derived disturbance were developed separately for each of 35 species and lakewide predictions mapped for Lake Erie. Most responses were unimodal and more species decreased in abundance with increasing watershed disturbance than increased. However, eight species increased in abundance with current in-lake disturbance conditions. Optimum Yellow Perch (Perca flavescens) abundance occurred at in-lake disturbance values less than the gradient mean, but decreased continuously from minimum watershed disturbance to higher values. Bands of optimum in-lake conditions occurred throughout the eastern and western portions of the Lake Erie nearshore zone; some areas were less disturbed than desirable. However, watershed-derived disturbance conditions were generally poor for Yellow Perch throughout the lake. In contrast, optimum Smallmouth Bass (Micropterus dolomieu) abundance occurred at in-lake disturbance values greater than the gradient mean and continuously increased with increasing watershed disturbance. Smallmouth Bass responses to disturbance indicated that most of the nearshore zone was less disturbed than is desirable and were most abundant in areas that the Yellow Perch response indicated were highly disturbed. Mapping counts of species response models that agreed on the disturbance level in each spatial unit of the nearshore zone showed a fine-scale mosaic of areas in which habitat restoration may benefit many or few species. This tool may assist managers in prioritizing conservation and restoration efforts and evaluating environmental conditions that may be improved.
Neonicotinoid insecticide use has increased over the last decade, including as agricultural seed treatments (application of chemical in a coating to the seed prior to planting). In California, multiple crops, including lettuce, can be grown using neonicotinoid treated seeds or receive a direct neonicotinoid soil application (drenching) at planting. Using research plots, this study compared pesticide runoff in four treatments: (1) imidacloprid seed treatment; (2) clothianidin seed treatment; (3) imidacloprid drench and an azoxystrobin seed treatment; and (4) a control with no pesticidal treatment. Neonicotinoid and azoxystrobin concentrations were measured in surface water runoff during six irrigations events in the 2020 growing seasons. Results showed runoff concentrations up to 1308 (±1200) ng L−1 for imidacloprid drench treatment, 431 (±100) ng L−1 for clothianidin seed treatment, 135 (±60) ng L−1 for imidacloprid seed treatment, 13 (±10) ng L−1 for azoxystrobin seed treatment (treatments averaged). The percent of applied mass in runoff over the entire sampling period varied by compound; the imidacloprid seed treatment and drench were similar (0.015 and 0.019%, respectively) to the clothianidin seed treatment (0.036%) while the azoxystrobin seed treatment was much higher (15%). Although the proportion of imidacloprid in runoff was similar for imidacloprid treatments, the mass applied during soil drench was > 4x the amount applied from the imidacloprid seed treatment. Surface soils were collected before planting and at the end of the trial. The neonicotinoids were detected in soil throughout the study and average maximum concentrations were 9–13 ng g−1; azoxystrobin was detected in only two soils at concentrations up to 0.57 ng g−1. These results elucidate the comparative mass runoff resulting from planting treated seed and soil drench applications and highlight the value of additional work to characterize off-site transport from the many commodities that may be utilizing treated seeds.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envpol.2022.120325","usgsCitation":"Woodward, E., Hladik, M.L., Main, A., Cahn, M., Orlando, J., and Teerlink, J., 2022, Comparing imidacloprid, clothianidin, and azoxystrobin runoff from lettuce fields using a soil drench or treated seeds in the Salinas Valley, California: Environmental Pollution, v. 315, 120325, 8 p., https://doi.org/10.1016/j.envpol.2022.120325.","productDescription":"120325, 8 p.","ipdsId":"IP-141733","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":446170,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envpol.2022.120325","text":"Publisher Index Page"},{"id":408325,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Salinas Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.36528015136717,\n 36.42515002455931\n ],\n [\n -121.33575439453126,\n 36.46933726558023\n ],\n [\n -121.61521911621092,\n 36.75594019674357\n ],\n [\n -121.74293518066406,\n 36.75924093413334\n ],\n [\n -121.75529479980467,\n 36.673375615028256\n ],\n [\n -121.6021728515625,\n 36.584106249883554\n ],\n [\n -121.47583007812501,\n 36.47265029399174\n ],\n [\n -121.36528015136717,\n 36.42515002455931\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"315","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Woodward, Emily E. 0000-0001-9196-1349 ewoodward@usgs.gov","orcid":"https://orcid.org/0000-0001-9196-1349","contributorId":177364,"corporation":false,"usgs":true,"family":"Woodward","given":"Emily","email":"ewoodward@usgs.gov","middleInitial":"E.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":854613,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hladik, Michelle L. 0000-0002-0891-2712","orcid":"https://orcid.org/0000-0002-0891-2712","contributorId":221229,"corporation":false,"usgs":true,"family":"Hladik","given":"Michelle","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":854614,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Main, Anson 0000-0001-9539-760X","orcid":"https://orcid.org/0000-0001-9539-760X","contributorId":202852,"corporation":false,"usgs":false,"family":"Main","given":"Anson","email":"","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":854615,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cahn, Michael","contributorId":297909,"corporation":false,"usgs":false,"family":"Cahn","given":"Michael","email":"","affiliations":[{"id":64448,"text":"Univeristy of California ANR","active":true,"usgs":false}],"preferred":false,"id":854616,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Orlando, James 0000-0002-0099-7221","orcid":"https://orcid.org/0000-0002-0099-7221","contributorId":208413,"corporation":false,"usgs":true,"family":"Orlando","given":"James","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":854617,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Teerlink, Jennifer","contributorId":297910,"corporation":false,"usgs":false,"family":"Teerlink","given":"Jennifer","email":"","affiliations":[{"id":40320,"text":"California Department of Pesticide Regulation","active":true,"usgs":false}],"preferred":false,"id":854618,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70256617,"text":"70256617 - 2022 - The Bathy-drone: An autonomous unmanned drone-tethered sonar system","interactions":[],"lastModifiedDate":"2024-08-27T14:37:31.951355","indexId":"70256617","displayToPublicDate":"2022-10-10T09:32:38","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":18351,"text":"Drones","active":true,"publicationSubtype":{"id":10}},"title":"The Bathy-drone: An autonomous unmanned drone-tethered sonar system","docAbstract":"A unique drone-based system for underwater mapping (bathymetry) was developed at the University of Florida. The system, called the “Bathy-drone”, comprises a drone that drags, via a tether, a small vessel on the water surface in a raster pattern. The vessel is equipped with a recreational commercial off-the-shelf (COTS) sonar unit that has down-scan, side-scan, and chirp capabilities and logs GPS-referenced sonar data onboard or transmitted in real time with a telemetry link. Data can then be retrieved post mission and plotted in various ways. The system provides both isobaths and contours of bottom hardness. Extensive testing of the system was conducted on a 5 acre pond located at the University of Florida Plant Science and Education Unit in Citra, FL. Prior to performing scans of the pond, ground-truth data were acquired with an RTK GNSS unit on a pole to precisely measure the location of the bottom at over 300 locations. An assessment of the accuracy and resolution of the system was performed by comparison to the ground-truth data. The pond ground truth had an average depth of 2.30 m while the Bathy-drone measured an average 21.6 cm deeper than the ground truth, repeatable to within 2.6 cm. The results justify integration of RTK and IMU corrections. During testing, it was found that there are numerous advantages of the Bathy-drone system compared to conventional methods including ease of implementation and the ability to initiate surveys from the land by flying the system to the water or placing the platform in the water. The system is also inexpensive, lightweight, and low-volume, thus making transport convenient. The Bathy-drone can collect data at speeds of 0–24 km/h (0–15 mph) and, thus, can be used in waters with swift currents. Additionally, there are no propellers or control surfaces underwater; hence, the vessel does not tend to snag on floating vegetation and can be dragged over sandbars. An area of more than 10 acres was surveyed using the Bathy-drone in one battery charge and in less than 25 min.
","language":"English","publisher":"MDPI","doi":"10.3390/drones6100294","usgsCitation":"Diaz, A.L., Ortega, A.E., Tingle, H., Pulido, A., Cordero, O., Nelson, M., Cocoves, N.E., Shin, J., Carthy, R., Wilkinson, B.E., and Ifju, P.G., 2022, The Bathy-drone: An autonomous unmanned drone-tethered sonar system: Drones, v. 6, no. 10, 294, 19 p., https://doi.org/10.3390/drones6100294.","productDescription":"294, 19 p.","ipdsId":"IP-144387","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":446174,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/drones6100294","text":"Publisher Index Page"},{"id":433196,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"10","noUsgsAuthors":false,"publicationDate":"2022-10-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Diaz, Antonio L.","contributorId":341377,"corporation":false,"usgs":false,"family":"Diaz","given":"Antonio","email":"","middleInitial":"L.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":908324,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ortega, Andrew E.","contributorId":341378,"corporation":false,"usgs":false,"family":"Ortega","given":"Andrew","email":"","middleInitial":"E.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":908325,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tingle, Henry","contributorId":341379,"corporation":false,"usgs":false,"family":"Tingle","given":"Henry","email":"","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":908326,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pulido, Andres","contributorId":341380,"corporation":false,"usgs":false,"family":"Pulido","given":"Andres","email":"","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":908327,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cordero, Orlando","contributorId":341381,"corporation":false,"usgs":false,"family":"Cordero","given":"Orlando","email":"","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":908328,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nelson, Marisa","contributorId":341382,"corporation":false,"usgs":false,"family":"Nelson","given":"Marisa","email":"","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":908329,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cocoves, Nicholas E.","contributorId":341383,"corporation":false,"usgs":false,"family":"Cocoves","given":"Nicholas","email":"","middleInitial":"E.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":908330,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Shin, Jaejeong","contributorId":341384,"corporation":false,"usgs":false,"family":"Shin","given":"Jaejeong","email":"","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":908331,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Carthy, Raymond 0000-0001-8978-5083","orcid":"https://orcid.org/0000-0001-8978-5083","contributorId":219303,"corporation":false,"usgs":true,"family":"Carthy","given":"Raymond","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908332,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Wilkinson, Benjamin E.","contributorId":341385,"corporation":false,"usgs":false,"family":"Wilkinson","given":"Benjamin","email":"","middleInitial":"E.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":908333,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Ifju, Peter G.","contributorId":341386,"corporation":false,"usgs":false,"family":"Ifju","given":"Peter","email":"","middleInitial":"G.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":908334,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70259362,"text":"70259362 - 2022 - Return from dormancy: Rapid inflation and seismic unrest driven by transcrustal magma transfer at Mt. Edgecumbe (L’´ux Shaa) Volcano, Alaska","interactions":[],"lastModifiedDate":"2024-10-04T12:18:13.532979","indexId":"70259362","displayToPublicDate":"2022-10-10T07:14:59","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Return from dormancy: Rapid inflation and seismic unrest driven by transcrustal magma transfer at Mt. Edgecumbe (L’´ux Shaa) Volcano, Alaska","docAbstract":"In April 2022, a seismic swarm near Mt. Edgecumbe in southeast Alaska suggested renewed activity at this transform fault volcano, which was last active ≈800 years ago. Previously, thin rhyolitic tephras were deposited 5 and 4 ka. Satellite radar data from 2014 to 2022 resolves line-of-sight rapid inflation up to 7.1 cm/yr beginning in August 2018. Bayesian modeling suggests a transcrustal system of a deflating (−0.528 km3) dipping sill at 20 km depth recharging a magma chamber at 10 km (0.222 km3). A near-vertical conduit could capture the volume difference without noticeable surface deformation. Reanalyzed seismicity, recorded 25 km away, shows increases since July 2019. Magma ascent through ductile material and brittle strain release in a stressed overburden could explain the time delay. Cloud-native open data and workflows enabled discovery and analysis of this signal within days after going unnoticed for >3 years.
The phylogeography of the American black bear (Ursus americanus) is characterized by isolation into glacial refugia, followed by population expansion and genetic admixture. Anthropogenic activities, including overharvest, habitat loss, and transportation infrastructure, have also influenced their landscape genetic structure. We describe the genetic structure of the American black bear in the American Southwest and northern Mexico and investigate how prehistoric and contemporary forces shaped genetic structure and influenced gene flow. Using a suite of microsatellites and a sample of 550 bears, we identified 14 subpopulations organized hierarchically following the distribution of ecoregions and mountain ranges containing black bear habitat. The pattern of subdivision we observed is more likely a product of postglacial habitat fragmentation during the Pleistocene and Holocene, rather than a consequence of contemporary anthropogenic barriers to movement during the Anthropocene. We used linear mixed-effects models to quantify the relationship between landscape resistance and genetic distance among individuals, which indicated that both isolation by resistance and geographic distance govern gene flow. Gene flow was highest among subpopulations occupying large tracts of contiguous habitat, was reduced among subpopulations in the Madrean Sky Island Archipelago, where montane habitat exists within a lowland matrix of arid lands, and was essentially nonexistent between two isolated subpopulations. We found significant asymmetric gene flow supporting the hypothesis that bears expanded northward from a Pleistocene refugium located in the American Southwest and northern Mexico and that major highways were not yet affecting gene flow. The potential vulnerability of the species to climate change, transportation infrastructure, and the US–Mexico border wall highlights conservation challenges and opportunities for binational collaboration.
Accurate evaluations of habitat preference are key to understanding optimal conditions for wildlife survival and reproduction. Habitat selection, however, usually is evaluated using a single index of preference, and congruence among multiple, relevant indices of preference is examined rarely.
We assessed the concordance between patterns of habitat preference using three different indices of breeding site preference in a migratory songbird. Specifically, we compared the chronology of territorial establishment, pair formation and reproductive initiation of the Brewer's sparrow (Spizella breweri) along a gradient of surface disturbance associated with natural gas development in Wyoming, USA during 2019.
We expected all three indices to demonstrate a preference for breeding sites with less surface disturbance, where reproductive success typically is higher. By contrast, all indices suggested suboptimal preference with respect to surface disturbance, with some discrepancy among them. The chronology of settlement and pairing did not vary across the disturbance gradient, whereas nest initiation tended to occur earlier at sites with more disturbance.
If the pattern of suboptimal selection of breeding sites that we identified is generalizable across other populations of migratory birds affected by energy development, the resultant lower fitness in those areas may exacerbate population declines.
Our results suggest that traditional, single-index approaches to the study of habitat selection, if chosen carefully, may provide adequate inference on habitat preferences. Different metrics, however, can lead to at least subtle differences in patterns of habitat selection. The simultaneous examination of multiple indices of preference across a diversity of systems would help clarify the contexts under which preference metrics can become decoupled.
Bird migrations are impressive behavioral phenomena, representing complex spatiotemporal strategies to balance costs of living while maximizing fitness. The field of bird migration research has made great strides over the past decades, yet fundamental gaps remain. Technologies have sparked a transformation in the study of bird migration research by revealing remarkable insights into the underlying behavioral, cognitive, physiological and evolutionary mechanisms of these diverse journeys. Here, we aim to encourage broad discussions and promote future studies by highlighting research fields that are characterized by major knowledge gaps or conflicting evidence, namely the fields of navigation, social learning, individual development, energetics and conservation. We approach each topic by summarizing the current state of knowledge and provide a future outlook of ideas and state-of-the-art methods to further advance the field. Integrating knowledge across these disciplines will allow us to understand the adaptive abilities of different species and to develop effective conservation strategies in a rapidly changing world.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.cub.2022.08.028","usgsCitation":"Flack, A., Aikens, E., Kolzsch, A., Nourani, E., Snell, K., Fiedler, W., Linek, N., Bauer, H., Thorup, K., Partecke, J., Wikelski, M., and Williams, H., 2022, New frontiers in bird migration research: Current Biology, v. 32, no. 20, p. R1187-R1199, https://doi.org/10.1016/j.cub.2022.08.028.","productDescription":"13 p.","startPage":"R1187","endPage":"R1199","ipdsId":"IP-141746","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":489889,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.cub.2022.08.028","text":"Publisher Index Page"},{"id":480932,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"32","issue":"20","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Flack, Andrea","contributorId":348942,"corporation":false,"usgs":false,"family":"Flack","given":"Andrea","affiliations":[{"id":80533,"text":"Max Planck Institute of Animal Behavior","active":true,"usgs":false}],"preferred":false,"id":923884,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aikens, Ellen O.","contributorId":287807,"corporation":false,"usgs":false,"family":"Aikens","given":"Ellen O.","affiliations":[{"id":12729,"text":"UW","active":true,"usgs":false}],"preferred":false,"id":924783,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kolzsch, Andrea","contributorId":243475,"corporation":false,"usgs":false,"family":"Kolzsch","given":"Andrea","email":"","affiliations":[],"preferred":false,"id":923886,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nourani, Elham","contributorId":348943,"corporation":false,"usgs":false,"family":"Nourani","given":"Elham","affiliations":[{"id":55536,"text":"University of Konstanz","active":true,"usgs":false}],"preferred":false,"id":923887,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Snell, Katherine R.S.","contributorId":348944,"corporation":false,"usgs":false,"family":"Snell","given":"Katherine R.S.","affiliations":[{"id":80533,"text":"Max Planck Institute of Animal Behavior","active":true,"usgs":false}],"preferred":false,"id":923888,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fiedler, Wolfgang","contributorId":205077,"corporation":false,"usgs":false,"family":"Fiedler","given":"Wolfgang","email":"","affiliations":[],"preferred":false,"id":923889,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Linek, Nils","contributorId":348945,"corporation":false,"usgs":false,"family":"Linek","given":"Nils","affiliations":[{"id":55536,"text":"University of Konstanz","active":true,"usgs":false}],"preferred":false,"id":923890,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bauer, Hans-Gunther","contributorId":335812,"corporation":false,"usgs":false,"family":"Bauer","given":"Hans-Gunther","email":"","affiliations":[{"id":80533,"text":"Max Planck Institute of Animal Behavior","active":true,"usgs":false}],"preferred":false,"id":923891,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Thorup, Kasper","contributorId":243503,"corporation":false,"usgs":false,"family":"Thorup","given":"Kasper","affiliations":[],"preferred":false,"id":923892,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Partecke, Jesko","contributorId":348946,"corporation":false,"usgs":false,"family":"Partecke","given":"Jesko","affiliations":[{"id":80533,"text":"Max Planck Institute of Animal Behavior","active":true,"usgs":false}],"preferred":false,"id":923893,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Wikelski, Martin","contributorId":205674,"corporation":false,"usgs":false,"family":"Wikelski","given":"Martin","email":"","affiliations":[{"id":37137,"text":"Department of Migration and Immuno-Ecology, Max Planck Institute for Ornithology","active":true,"usgs":false}],"preferred":false,"id":923894,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Williams, Hannah J.","contributorId":348948,"corporation":false,"usgs":false,"family":"Williams","given":"Hannah J.","affiliations":[{"id":55536,"text":"University of Konstanz","active":true,"usgs":false}],"preferred":false,"id":923895,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70238000,"text":"70238000 - 2022 - Wave-driven hydrodynamic processes over fringing reefs with varying slopes, depths, and roughness: Implications for coastal protection","interactions":[],"lastModifiedDate":"2022-11-04T11:31:49.381274","indexId":"70238000","displayToPublicDate":"2022-10-09T13:42:11","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7159,"text":"JGR Oceans","active":true,"publicationSubtype":{"id":10}},"title":"Wave-driven hydrodynamic processes over fringing reefs with varying slopes, depths, and roughness: Implications for coastal protection","docAbstract":"Wave breaking on the steep fore-reef slopes of shallow fringing reefs is effective at dissipating incident sea-swell waves prior to reaching reef shorelines. However, wave setup and free infragravity waves generated during the sea-swell breaking process are often the largest contributors to wave-driven water levels at the shoreline. Laboratory flume experiments and a multi-layer phase-resolving nonhydrostatic wave-flow model, which includes a canopy model to predict drag forces generated by roughness elements, were used to investigate the wave-driven water levels on fringing reefs. Though the model is capable of three dimensional simulations, consistent with the laboratory study, a two-dimensional vertical mode was used. In contrast to many previous studies, both the laboratory experiment and the numerical model account for the effects of large bottom roughness. The numerical model reproduced the observations of the wave transformation and runup over both smooth and rough reef profiles. The numerical model was then extended to quantify the influence of reef geometry and compared to simulations of plane beaches lacking a reef. For a set offshore forcing condition, the fore-reef slope controlled wave runup on reef fronted beaches, whereas the beach slope controlled wave runup on plane beaches. As a result, the coastal protection utility of reefs is dependent on these slopes. For our examples, with a fore-reef slope of 1/5 and a 500 m prototype reef flat length, a beach slope of ~1/30 marked the transition between the reef providing runup reduction for steeper beach slopes and enhancing wave runup for milder slopes. Roughness coverage, spacing, dimensions, and drag coefficient were investigated with results indicating the greatest runup reductions were due to tall roughness elements on the reef flat.","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022JC018857","usgsCitation":"Buckley, M.L., Lowe, R.L., Hansen, J., Dongeren, A.R., Pomeroy, A., Storlazzi, C.D., Rijnsdorp, D., Silva, R.F., Contardo, S., and Green, R., 2022, Wave-driven hydrodynamic processes over fringing reefs with varying slopes, depths, and roughness: Implications for coastal protection: JGR Oceans, v. 127, no. 11, e2022JC018857, 27 p., https://doi.org/10.1029/2022JC018857.","productDescription":"e2022JC018857, 27 p.","ipdsId":"IP-140945","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":446182,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1029/2022jc018857","text":"External Repository"},{"id":409126,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"127","issue":"11","noUsgsAuthors":false,"publicationDate":"2022-11-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Buckley, Mark L. 0000-0002-1909-4831","orcid":"https://orcid.org/0000-0002-1909-4831","contributorId":203481,"corporation":false,"usgs":true,"family":"Buckley","given":"Mark","email":"","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":856512,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lowe, Ryan L.","contributorId":298814,"corporation":false,"usgs":false,"family":"Lowe","given":"Ryan","email":"","middleInitial":"L.","affiliations":[{"id":24588,"text":"The University of Western Australia","active":true,"usgs":false}],"preferred":false,"id":856513,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hansen, Jeff E.","contributorId":298815,"corporation":false,"usgs":false,"family":"Hansen","given":"Jeff E.","affiliations":[{"id":24588,"text":"The University of Western Australia","active":true,"usgs":false}],"preferred":false,"id":856514,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dongeren, Ap R.","contributorId":298816,"corporation":false,"usgs":false,"family":"Dongeren","given":"Ap","email":"","middleInitial":"R.","affiliations":[{"id":36257,"text":"Deltares","active":true,"usgs":false}],"preferred":false,"id":856515,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pomeroy, Andrew","contributorId":298817,"corporation":false,"usgs":false,"family":"Pomeroy","given":"Andrew","affiliations":[{"id":29920,"text":"The University of Melbourne","active":true,"usgs":false}],"preferred":false,"id":856516,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":213610,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":856517,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rijnsdorp, Dirk P.","contributorId":298818,"corporation":false,"usgs":false,"family":"Rijnsdorp","given":"Dirk P.","affiliations":[{"id":17614,"text":"Delft University of Technology","active":true,"usgs":false}],"preferred":false,"id":856518,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Silva, Renan F.","contributorId":298819,"corporation":false,"usgs":false,"family":"Silva","given":"Renan","email":"","middleInitial":"F.","affiliations":[{"id":24588,"text":"The University of Western Australia","active":true,"usgs":false}],"preferred":false,"id":856519,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Contardo, Stephanie","contributorId":298820,"corporation":false,"usgs":false,"family":"Contardo","given":"Stephanie","email":"","affiliations":[{"id":64690,"text":"The University of Western Australia and CSIRO","active":true,"usgs":false}],"preferred":false,"id":856520,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Green, Rebecca H.","contributorId":298821,"corporation":false,"usgs":false,"family":"Green","given":"Rebecca H.","affiliations":[{"id":24588,"text":"The University of Western Australia","active":true,"usgs":false}],"preferred":false,"id":856521,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70255064,"text":"70255064 - 2022 - Fish carcass deposition to suppress invasive lake trout through hypoxia causes limited, non-target effects on benthic invertebrates in Yellowstone Lake","interactions":[],"lastModifiedDate":"2024-06-17T15:16:58.764122","indexId":"70255064","displayToPublicDate":"2022-10-09T10:11:08","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":12812,"text":"Aquaculture, Fish and Fisheries","onlineIssn":"2693-8847","active":true,"publicationSubtype":{"id":10}},"title":"Fish carcass deposition to suppress invasive lake trout through hypoxia causes limited, non-target effects on benthic invertebrates in Yellowstone Lake","docAbstract":"Invasive species can have negative effects on native biodiversity and ecosystem function, and suppression is often required to minimize the effects. However, management actions to suppress invasive species may cause negative, unintended effects on non-target taxa. Across the United States, lake trout (Salvelinus namaycush) are invasive in many freshwater ecosystems, reducing native fish abundance and diversity through predation and competition. In an integrated pest management approach, lake trout embryos in Yellowstone Lake, Wyoming, are suppressed by depositing lake trout carcasses onto spawning sites; the carcasses reduce dissolved oxygen concentrations as they decay, causing embryo mortality. We conducted a field experiment during one ice-free season at four sites in Yellowstone Lake to investigate the non-target effects of carcass treatment on benthic invertebrates, which could have consequences for native fish diets. While overall invertebrate density and biomass did not respond to carcass treatment, Chironomidae midges and Sphaeriidae fingernail clams decreased in abundance. Carcass treatment altered invertebrate community structure based on density, but not biomass. Carcass treatment to suppress invasive fish embryos has spatially localized, non-target effects on some benthic invertebrate taxa. Given the small spatial extent of carcass treatment within the lake, we conclude it is unlikely that carcass treatment will alter food availability for native fishes.
","language":"English","publisher":"Wiley","doi":"10.1002/aff2.72","usgsCitation":"Briggs, M.A., Albertson, L., Lujan, D.R., Tronstad, L.M., Glassic, H., Guy, C.S., and Koel, T., 2022, Fish carcass deposition to suppress invasive lake trout through hypoxia causes limited, non-target effects on benthic invertebrates in Yellowstone Lake: Aquaculture, Fish and Fisheries, v. 2, no. 6, p. 470-483, https://doi.org/10.1002/aff2.72.","productDescription":"14 p.","startPage":"470","endPage":"483","ipdsId":"IP-125603","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":446185,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/aff2.72","text":"Publisher Index Page"},{"id":430278,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Yellowstone Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -110.49944251778561,\n 44.46178424523711\n ],\n [\n -110.54113066061247,\n 44.48062295233594\n ],\n [\n -110.5803112459764,\n 44.45831001852345\n ],\n [\n -110.58344569280504,\n 44.39938227974491\n ],\n [\n -110.52389120305199,\n 44.3786364013329\n ],\n [\n -110.4543064834462,\n 44.41702039274938\n ],\n [\n -110.40681961398506,\n 44.38695587716806\n ],\n [\n -110.44709725573931,\n 44.35330737652469\n ],\n [\n -110.36716886159768,\n 44.36487763116595\n ],\n [\n -110.33770506140421,\n 44.27149601451338\n ],\n [\n -110.31639082296691,\n 44.27131743221993\n ],\n [\n -110.19352050726671,\n 44.28523362890047\n ],\n [\n -110.20731207331477,\n 44.357501926872644\n ],\n [\n -110.27877746101787,\n 44.437864945144355\n ],\n [\n -110.26122455877496,\n 44.50748785782456\n ],\n [\n -110.29382280579776,\n 44.57174586122437\n ],\n [\n -110.38503520852399,\n 44.56870871706496\n ],\n [\n -110.44866447915439,\n 44.53708615570581\n ],\n [\n -110.42296201515602,\n 44.488140599780934\n ],\n [\n -110.49944251778561,\n 44.46178424523711\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"2","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-10-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Briggs, Michelle A.","contributorId":338490,"corporation":false,"usgs":false,"family":"Briggs","given":"Michelle","email":"","middleInitial":"A.","affiliations":[{"id":36244,"text":"MSU","active":true,"usgs":false}],"preferred":false,"id":903304,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Albertson, Lindsey K.","contributorId":338491,"corporation":false,"usgs":false,"family":"Albertson","given":"Lindsey K.","affiliations":[{"id":36244,"text":"MSU","active":true,"usgs":false}],"preferred":false,"id":903305,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lujan, Dominique R.","contributorId":338492,"corporation":false,"usgs":false,"family":"Lujan","given":"Dominique","email":"","middleInitial":"R.","affiliations":[{"id":40829,"text":"uwy","active":true,"usgs":false}],"preferred":false,"id":903306,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tronstad, Lusha M.","contributorId":338493,"corporation":false,"usgs":false,"family":"Tronstad","given":"Lusha","email":"","middleInitial":"M.","affiliations":[{"id":40829,"text":"uwy","active":true,"usgs":false}],"preferred":false,"id":903307,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Glassic, Hayley C.","contributorId":338494,"corporation":false,"usgs":false,"family":"Glassic","given":"Hayley C.","affiliations":[{"id":36244,"text":"MSU","active":true,"usgs":false}],"preferred":false,"id":903308,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Guy, Christopher S. 0000-0002-9936-4781 cguy@usgs.gov","orcid":"https://orcid.org/0000-0002-9936-4781","contributorId":2876,"corporation":false,"usgs":true,"family":"Guy","given":"Christopher","email":"cguy@usgs.gov","middleInitial":"S.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5062,"text":"Office of the Chief Scientist for Ecosystems","active":true,"usgs":true}],"preferred":true,"id":903303,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Koel, Todd M.","contributorId":338495,"corporation":false,"usgs":false,"family":"Koel","given":"Todd M.","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":903309,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70237751,"text":"70237751 - 2022 - Monitoring offshore CO2 sequestration using marine CSEM methods; constraints inferred from field- and laboratory-based gas hydrate studies","interactions":[],"lastModifiedDate":"2022-10-21T14:14:05.787062","indexId":"70237751","displayToPublicDate":"2022-10-09T09:12:32","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10757,"text":"Energies","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Monitoring offshore CO2 sequestration using marine CSEM methods; constraints inferred from field- and laboratory-based gas hydrate studies","title":"Monitoring offshore CO2 sequestration using marine CSEM methods; constraints inferred from field- and laboratory-based gas hydrate studies","docAbstract":"Offshore geological sequestration of CO2 offers a viable approach for reducing greenhouse gas emissions into the atmosphere. Strategies include injection of CO2 into the deep-ocean or ocean-floor sediments, whereby depending on pressure–temperature conditions, CO2 can be trapped physically, gravitationally, or converted to CO2 hydrate. Energy-driven research continues to also advance CO2-for-CH4 replacement strategies in the gas hydrate stability zone (GHSZ), producing methane for natural gas needs while sequestering CO2. In all cases, safe storage of CO2 requires reliable monitoring of the targeted CO2 injection sites and the integrity of the repository over time, including possible leakage. Electromagnetic technologies used for oil and gas exploration, sensitive to electrical conductivity, have long been considered an optimal monitoring method, as CO2, similar to hydrocarbons, typically exhibits lower conductivity than the surrounding medium. We apply 3D controlled-source electromagnetic (CSEM) forward modeling code to simulate an evolving CO2 reservoir in deep-ocean sediments, demonstrating sufficient sensitivity and resolution of CSEM data to detect reservoir changes even before sophisticated inversion of data. Laboratory measurements place further constraints on evaluating certain systems within the GHSZ; notably, CO2 hydrate is measurably weaker than methane hydrate, and >1 order of magnitude more conductive, properties that may affect site selection, stability, and modeling considerations.
","language":"English","publisher":"MDPI","doi":"10.3390/en15197411","usgsCitation":"Constable, S., and Stern, L.A., 2022, Monitoring offshore CO2 sequestration using marine CSEM methods; constraints inferred from field- and laboratory-based gas hydrate studies: Energies, v. 15, no. 19, 7411, 16 p., https://doi.org/10.3390/en15197411.","productDescription":"7411, 16 p.","ipdsId":"IP-142378","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":446187,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/en15197411","text":"Publisher Index Page"},{"id":408604,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"19","noUsgsAuthors":false,"publicationDate":"2022-10-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Constable, Steven","contributorId":9178,"corporation":false,"usgs":false,"family":"Constable","given":"Steven","email":"","affiliations":[{"id":16196,"text":"Scripps Institution of Oceanography, La Jolla, CA","active":true,"usgs":false}],"preferred":false,"id":855447,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stern, Laura A. 0000-0003-3440-5674","orcid":"https://orcid.org/0000-0003-3440-5674","contributorId":212238,"corporation":false,"usgs":true,"family":"Stern","given":"Laura","email":"","middleInitial":"A.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":855448,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70237298,"text":"ofr20221057 - 2022 - Channel mapping of the Colorado River from Glen Canyon Dam to Lees Ferry in Glen Canyon National Recreation Area, Arizona","interactions":[],"lastModifiedDate":"2026-03-27T20:28:39.65672","indexId":"ofr20221057","displayToPublicDate":"2022-10-07T11:57:33","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-1057","displayTitle":"Channel Mapping of the Colorado River from Glen Canyon Dam to Lees Ferry in Glen Canyon National Recreation Area, Arizona","title":"Channel mapping of the Colorado River from Glen Canyon Dam to Lees Ferry in Glen Canyon National Recreation Area, Arizona","docAbstract":"Bathymetric and topographic data were collected from May 2013 to February 2016 along the 15.84-mile reach of the Colorado River spanning from Glen Canyon Dam to Lees Ferry in Glen Canyon National Recreation Area, Arizona. Channel bathymetry was mapped using multibeam and singlebeam echo sounders; subaerial topography was mapped using a combination of ground-based total stations and aerial photogrammetry. These data were combined to produce a digital elevation model (DEM), spatially variable estimates of DEM uncertainty, and bed-substrate distribution maps. This project is part of a larger effort to monitor the status and trends of sand storage along the Colorado River in Glen Canyon National Recreation Area and Grand Canyon National Park. This report documents the study methodologies (survey methods and post-processing procedures, DEM production and uncertainty assessment, and bed-substrate classification) and presents the resulting datasets.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221057","collaboration":"Prepared in cooperation with Northern Arizona University and Marda Science LLC","usgsCitation":"Kaplinski, M., Hazel, J.E., Jr., Grams, P.E., Gushue, T., Buscombe, D.D., and Kohl, K., 2022, Channel mapping of the Colorado River from Glen Canyon Dam to Lees Ferry in Glen Canyon National Recreation Area, Arizona: U.S. Geological Survey Open-File Report 2022-1057, 20 p., https://doi.org/10.3133/ofr20221057.","productDescription":"Report: v, 20 p.","numberOfPages":"20","onlineOnly":"Y","ipdsId":"IP-120853","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":408061,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1057/ofr20221057.pdf","text":"Report","size":"3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Open-File Report 2022-1057"},{"id":408100,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1057/covrthb.jpg"},{"id":408101,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98GFP93","text":"Channel mapping Glen Canyon Dam to Lees Ferry in Glen Canyon National Recreation Area, Arizona - Data","description":"Kaplinski, M., Hazel, J.E., Jr., Grams, P.E., Gushue, T., Buscombe, D.D., and Kohl, K., 2022, Channel mapping Glen Canyon Dam to Lees Ferry in Glen Canyon National Recreation Area—Data: U.S. Geological Survey data release, https://doi.org/10.5066/P98GFP93."},{"id":501782,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113614.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Arizona","otherGeospatial":"Colorado River, Glen Canyon Dam, Glen Canyon National Recreation Area, Lees Ferry","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.48668289184569,\n 36.93466271122842\n ],\n [\n -111.48376464843749,\n 36.928625118149235\n ],\n [\n -111.49028778076172,\n 36.92148916432789\n ],\n [\n -111.49972915649414,\n 36.92039126599804\n ],\n [\n -111.50522232055664,\n 36.91599951460428\n ],\n [\n -111.50453567504883,\n 36.90446996392354\n ],\n [\n -111.52050018310547,\n 36.90392089423511\n ],\n [\n -111.52616500854491,\n 36.90172457596916\n ],\n [\n -111.52788162231445,\n 36.894036964201895\n ],\n [\n -111.53406143188475,\n 36.89060474464471\n ],\n [\n -111.53200149536133,\n 36.88470096601324\n ],\n [\n -111.5196418762207,\n 36.87975791652459\n ],\n [\n -111.53200149536133,\n 36.881954866912125\n ],\n [\n -111.54642105102539,\n 36.880856399619006\n ],\n [\n -111.55414581298827,\n 36.87605041942542\n ],\n [\n -111.56805038452148,\n 36.87756090293265\n ],\n [\n -111.57096862792969,\n 36.8708321556463\n ],\n [\n -111.55809402465819,\n 36.85613670839554\n ],\n [\n -111.54779434204102,\n 36.84803240254599\n ],\n [\n -111.55036926269531,\n 36.84624659252608\n ],\n [\n -111.56822204589844,\n 36.84638396400846\n ],\n [\n -111.57337188720703,\n 36.8549005138863\n ],\n [\n -111.5742301940918,\n 36.862180038184434\n ],\n [\n -111.57800674438477,\n 36.86753622642931\n ],\n [\n -111.59156799316406,\n 36.86822289007559\n ],\n [\n -111.60221099853516,\n 36.861630664314674\n ],\n [\n -111.61027908325195,\n 36.852840145275046\n ],\n [\n -111.61869049072266,\n 36.851191810400394\n ],\n [\n -111.62160873413086,\n 36.83608041796078\n ],\n [\n -111.62881851196289,\n 36.8308594247793\n ],\n [\n -111.63843154907227,\n 36.811895979233846\n ],\n [\n -111.64735794067383,\n 36.80474911423461\n ],\n [\n -111.64752960205077,\n 36.7952647442859\n ],\n [\n -111.65147781372069,\n 36.78344200140682\n ],\n [\n -111.65834426879881,\n 36.77752994587241\n ],\n [\n -111.66709899902344,\n 36.76515440007755\n ],\n [\n -111.66915893554688,\n 36.756627862079114\n ],\n [\n -111.68100357055664,\n 36.75236423762844\n ],\n [\n -111.6976547241211,\n 36.74191047837866\n ],\n [\n -111.69919967651367,\n 36.731180139463724\n ],\n [\n -111.70675277709961,\n 36.72746544193304\n ],\n [\n -111.7119026184082,\n 36.72361297320252\n ],\n [\n -111.71791076660155,\n 36.69787903078789\n ],\n [\n -111.73559188842773,\n 36.69113448723155\n ],\n [\n -111.74348831176758,\n 36.682875056701356\n ],\n [\n -111.74692153930664,\n 36.66029475441398\n ],\n [\n -111.76185607910156,\n 36.65423549724267\n ],\n [\n -111.7664909362793,\n 36.649139843693824\n ],\n [\n -111.7668342590332,\n 36.63674360313849\n ],\n [\n -111.7690658569336,\n 36.62530974650164\n ],\n [\n -111.76374435424805,\n 36.61552763134925\n ],\n [\n -111.76614761352539,\n 36.61222072017988\n ],\n [\n -111.77095413208008,\n 36.601610089482534\n ],\n [\n -111.79533004760742,\n 36.58093583857703\n ],\n [\n -111.8107795715332,\n 36.5736296124793\n ],\n [\n -111.82863235473633,\n 36.552534175868985\n ],\n [\n -111.83309555053711,\n 36.53612263184686\n ],\n [\n -111.84991836547852,\n 36.52136305889455\n ],\n [\n -111.85129165649414,\n 36.516534549935\n ],\n [\n -111.86073303222656,\n 36.50687662812643\n ],\n [\n -111.86416625976562,\n 36.501495263232684\n ],\n [\n -111.86038970947266,\n 36.49556152992\n ],\n [\n -111.84837341308594,\n 36.49445752937066\n ],\n [\n -111.84442520141602,\n 36.49224948105883\n ],\n [\n -111.85283660888672,\n 36.48051816892598\n ],\n [\n -111.84442520141602,\n 36.46740460028067\n ],\n [\n -111.8418502807617,\n 36.45359844696098\n ],\n [\n -111.85455322265625,\n 36.44628018910229\n ],\n [\n -111.85609817504883,\n 36.43827073840857\n ],\n [\n -111.87395095825195,\n 36.43357515880956\n ],\n [\n -111.87652587890625,\n 36.423906894561256\n ],\n [\n -111.87257766723633,\n 36.41382299361495\n ],\n [\n -111.88339233398438,\n 36.406362827148655\n ],\n [\n -111.88751220703125,\n 36.39917828607653\n ],\n [\n -111.88493728637694,\n 36.39296035862884\n ],\n [\n -111.87549591064453,\n 36.38922936340128\n ],\n [\n -111.85489654541016,\n 36.39268399475275\n ],\n [\n -111.8547248840332,\n 36.38922936340128\n ],\n [\n -111.88871383666992,\n 36.38176683577235\n ],\n [\n -111.89712524414061,\n 36.373888946305556\n ],\n [\n -111.89352035522461,\n 36.36421325359297\n ],\n [\n -111.87652587890625,\n 36.3472087646811\n ],\n [\n -111.86330795288086,\n 36.32937079795403\n ],\n [\n -111.86708450317383,\n 36.31968957141092\n ],\n [\n -111.86897277832031,\n 36.31000714221622\n ],\n [\n -111.8609046936035,\n 36.30419710747953\n ],\n [\n -111.86502456665039,\n 36.29755653772329\n ],\n [\n -111.86382293701172,\n 36.29382096878581\n ],\n [\n -111.83206558227539,\n 36.25880861429488\n ],\n [\n -111.82931900024414,\n 36.23555062950767\n ],\n [\n -111.80545806884766,\n 36.200650676227696\n ],\n [\n -111.80477142333984,\n 36.19663341291529\n ],\n [\n -111.81987762451172,\n 36.181255086867964\n ],\n [\n -111.8162727355957,\n 36.16434929946814\n ],\n [\n -111.8214225769043,\n 36.14910324993565\n ],\n [\n -111.82039260864258,\n 36.14258812489666\n ],\n [\n -111.83429718017577,\n 36.113887411565116\n ],\n [\n -111.8301773071289,\n 36.10598247395818\n ],\n [\n -111.83635711669922,\n 36.10764673746366\n ],\n [\n -111.84545516967772,\n 36.10182166093424\n ],\n [\n -111.84511184692383,\n 36.097799332209796\n ],\n [\n -111.84991836547852,\n 36.09835414841387\n ],\n [\n -111.85867309570312,\n 36.0907250822317\n ],\n [\n -111.86914443969725,\n 36.093083236312616\n ],\n [\n -111.88201904296875,\n 36.08753452585921\n ],\n [\n -111.88253402709961,\n 36.080875556280155\n ],\n [\n -111.8763542175293,\n 36.07685215551436\n ],\n [\n -111.89523696899414,\n 36.06922100242124\n ],\n [\n -111.91566467285156,\n 36.05090321430484\n ],\n [\n -111.94673538208006,\n 36.049931697391784\n ],\n [\n -111.98175430297852,\n 36.05437281968144\n ],\n [\n -112.01488494873047,\n 36.07046978723051\n ],\n [\n -112.03325271606444,\n 36.08642473676437\n ],\n [\n -112.08749771118163,\n 36.10556640257244\n ],\n [\n -112.09573745727538,\n 36.10306992798007\n ],\n [\n -112.10329055786131,\n 36.10542771162082\n ],\n [\n -112.12646484375,\n 36.10112817067241\n ],\n [\n -112.14088439941406,\n 36.110281749234474\n ],\n [\n -112.15564727783203,\n 36.110697795643894\n ],\n [\n -112.17178344726562,\n 36.103486012588036\n ],\n [\n -112.20027923583983,\n 36.101960358252065\n ],\n [\n -112.22345352172852,\n 36.1113912014288\n ],\n [\n -112.22791671752928,\n 36.12414877519126\n ],\n [\n -112.23443984985352,\n 36.13565654678543\n ],\n [\n -112.26190567016602,\n 36.14868740705872\n ],\n [\n -112.29349136352539,\n 36.15201408833908\n ],\n [\n -112.30087280273438,\n 36.15908281751799\n ],\n [\n -112.3048210144043,\n 36.1838876271496\n ],\n [\n -112.32868194580078,\n 36.21560970545108\n ],\n [\n -112.33503341674805,\n 36.2340275438345\n ],\n [\n -112.34155654907227,\n 36.2394274409703\n ],\n [\n -112.35031127929688,\n 36.24067351811116\n ],\n [\n -112.36026763916016,\n 36.24676516486063\n ],\n [\n -112.39717483520508,\n 36.24828800236324\n ],\n [\n -112.41949081420898,\n 36.238319800169904\n ],\n [\n -112.42738723754883,\n 36.22724252902252\n ],\n [\n -112.42876052856445,\n 36.20591436439329\n ],\n [\n -112.42172241210938,\n 36.205637336998635\n ],\n [\n -112.41657257080078,\n 36.22959658044717\n ],\n [\n -112.39580154418945,\n 36.2408119699007\n ],\n [\n -112.3733139038086,\n 36.238873622531884\n ],\n [\n -112.36009597778319,\n 36.238873622531884\n ],\n [\n -112.35254287719725,\n 36.23222749524095\n ],\n [\n -112.3458480834961,\n 36.23195056101004\n ],\n [\n -112.3355484008789,\n 36.207576508170014\n ],\n [\n -112.31597900390625,\n 36.183471968776296\n ],\n [\n -112.31237411499023,\n 36.16033017416435\n ],\n [\n -112.305850982666,\n 36.149241863737984\n ],\n [\n -112.2867965698242,\n 36.1416177408265\n ],\n [\n -112.26276397705077,\n 36.141063230254474\n ],\n [\n -112.24010467529295,\n 36.1280311035974\n ],\n [\n -112.23392486572266,\n 36.110281749234474\n ],\n [\n -112.22465515136717,\n 36.10057337405567\n ],\n [\n -112.20439910888672,\n 36.09336066155288\n ],\n [\n -112.16577529907225,\n 36.09668968804945\n ],\n [\n -112.15599060058594,\n 36.10140556751167\n ],\n [\n -112.1455192565918,\n 36.10223775215315\n ],\n [\n -112.12852478027344,\n 36.09349937380574\n ],\n [\n -112.1048355102539,\n 36.097244512088324\n ],\n [\n -112.09505081176756,\n 36.09391550909547\n ],\n [\n -112.0835494995117,\n 36.097244512088324\n ],\n [\n -112.05951690673828,\n 36.086008561814516\n ],\n [\n -112.03496932983398,\n 36.07671341388517\n ],\n [\n -112.02398300170898,\n 36.066723373326525\n ],\n [\n -111.98535919189453,\n 36.04757224925469\n ],\n [\n -111.94793701171875,\n 36.04021586880111\n ],\n [\n -111.92338943481444,\n 36.043824745098114\n ],\n [\n -111.91858291625977,\n 36.041326309894316\n ],\n [\n -111.90330505371094,\n 36.043824745098114\n ],\n [\n -111.88974380493164,\n 36.063809372490276\n ],\n [\n -111.88116073608398,\n 36.06533576734184\n ],\n [\n -111.8686294555664,\n 36.071996052851304\n ],\n [\n -111.86656951904297,\n 36.07754585998861\n ],\n [\n -111.87326431274414,\n 36.0850374783633\n ],\n [\n -111.8598747253418,\n 36.08365019548198\n ],\n [\n -111.84906005859375,\n 36.088089414531225\n ],\n [\n -111.84614181518553,\n 36.09197352555871\n ],\n [\n -111.8385887145996,\n 36.091002515795886\n ],\n [\n -111.83412551879883,\n 36.10085077285374\n ],\n [\n -111.82760238647461,\n 36.09946376906971\n ],\n [\n -111.82228088378906,\n 36.10598247395818\n ],\n [\n -111.82416915893555,\n 36.11305535033531\n ],\n [\n -111.81798934936523,\n 36.12095957607491\n ],\n [\n -111.80631637573241,\n 36.163517773207886\n ],\n [\n -111.80923461914062,\n 36.17446549576358\n ],\n [\n -111.80992126464844,\n 36.17986950381666\n ],\n [\n -111.79704666137695,\n 36.18984515478542\n ],\n [\n -111.79481506347655,\n 36.202312931782544\n ],\n [\n -111.80614471435547,\n 36.218933545852614\n ],\n [\n -111.81919097900389,\n 36.23915053224153\n ],\n [\n -111.82193756103516,\n 36.26226903225169\n ],\n [\n -111.85541152954102,\n 36.29617301452927\n ],\n [\n -111.8514633178711,\n 36.30129192777897\n ],\n [\n -111.85077667236328,\n 36.306410505090085\n ],\n [\n -111.85970306396484,\n 36.31360361344308\n ],\n [\n -111.85438156127928,\n 36.32812613620453\n ],\n [\n -111.85764312744139,\n 36.33780631461915\n ],\n [\n -111.86931610107422,\n 36.35439810755854\n ],\n [\n -111.88064575195311,\n 36.36227797065827\n ],\n [\n -111.8873405456543,\n 36.37112458545978\n ],\n [\n -111.88613891601562,\n 36.37402716176924\n ],\n [\n -111.85352325439453,\n 36.382181439429935\n ],\n [\n -111.84648513793944,\n 36.38508360313973\n ],\n [\n -111.8437385559082,\n 36.391716713449014\n ],\n [\n -111.84768676757812,\n 36.39765839419146\n ],\n [\n -111.8569564819336,\n 36.39986913619829\n ],\n [\n -111.87463760375977,\n 36.39448034238433\n ],\n [\n -111.8789291381836,\n 36.39738204701894\n ],\n [\n -111.87875747680664,\n 36.40069814823783\n ],\n [\n -111.86777114868164,\n 36.40815885862307\n ],\n [\n -111.86502456665039,\n 36.41271782897365\n ],\n [\n -111.86708450317383,\n 36.4203155183223\n ],\n [\n -111.8686294555664,\n 36.42611688968639\n ],\n [\n -111.86450958251953,\n 36.43095103471328\n ],\n [\n -111.8521499633789,\n 36.432055939882105\n ],\n [\n -111.8488883972168,\n 36.43481813399704\n ],\n [\n -111.8463134765625,\n 36.444346949113836\n ],\n [\n -111.83618545532227,\n 36.447937213608554\n ],\n [\n -111.83292388916016,\n 36.45318422438426\n ],\n [\n -111.83584213256836,\n 36.46699045144776\n ],\n [\n -111.84425354003906,\n 36.47775760202128\n ],\n [\n -111.84425354003906,\n 36.48176039194775\n ],\n [\n -111.83687210083008,\n 36.49252549054039\n ],\n [\n -111.84202194213867,\n 36.49818346814959\n ],\n [\n -111.85403823852538,\n 36.49942540790511\n ],\n [\n -111.85438156127928,\n 36.503151107655604\n ],\n [\n -111.84803009033203,\n 36.50922223422133\n ],\n [\n -111.84442520141602,\n 36.51667251151527\n ],\n [\n -111.84391021728516,\n 36.519707604051945\n ],\n [\n -111.8327522277832,\n 36.529225985680085\n ],\n [\n -111.82451248168945,\n 36.534329563007525\n ],\n [\n -111.82382583618164,\n 36.54784551881367\n ],\n [\n -111.82125091552734,\n 36.55115518861395\n ],\n [\n -111.81421279907225,\n 36.56039393337068\n ],\n [\n -111.80425643920898,\n 36.57169955053531\n ],\n [\n -111.79361343383789,\n 36.575283912895365\n ],\n [\n -111.76734924316406,\n 36.596097497458956\n ],\n [\n -111.76340103149414,\n 36.60560647239554\n ],\n [\n -111.75859451293945,\n 36.61042941741603\n ],\n [\n -111.75516128540039,\n 36.6164921203925\n ],\n [\n -111.76202774047852,\n 36.62696293911277\n ],\n [\n -111.75859451293945,\n 36.634126363996586\n ],\n [\n -111.75962448120116,\n 36.64252876365686\n ],\n [\n -111.7584228515625,\n 36.64776258214948\n ],\n [\n -111.74280166625977,\n 36.6551995018735\n ],\n [\n -111.7390251159668,\n 36.66291110439972\n ],\n [\n -111.73816680908203,\n 36.680672392083736\n ],\n [\n -111.72958374023438,\n 36.68755550957869\n ],\n [\n -111.71121597290039,\n 36.69498858456907\n ],\n [\n -111.7064094543457,\n 36.71301768775457\n ],\n [\n -111.70486450195312,\n 36.722237044678316\n ],\n [\n -111.6928482055664,\n 36.72870369441065\n ],\n [\n -111.69095993041992,\n 36.739571942595916\n ],\n [\n -111.67551040649414,\n 36.74865056520353\n ],\n [\n -111.66349411010742,\n 36.754152238021554\n ],\n [\n -111.66143417358398,\n 36.76102877424881\n ],\n [\n -111.65319442749023,\n 36.774229995650714\n ],\n [\n -111.64581298828125,\n 36.780004815311294\n ],\n [\n -111.64461135864258,\n 36.7846793506642\n ],\n [\n -111.64066314697266,\n 36.79430249620881\n ],\n [\n -111.64083480834961,\n 36.8021375933119\n ],\n [\n -111.63225173950195,\n 36.80722310453566\n ],\n [\n -111.62813186645506,\n 36.817942805467766\n ],\n [\n -111.62469863891602,\n 36.827012149156175\n ],\n [\n -111.61834716796875,\n 36.83182121345616\n ],\n [\n -111.61474227905273,\n 36.83662997546104\n ],\n [\n -111.61508560180664,\n 36.84349911104911\n ],\n [\n -111.61405563354492,\n 36.847620296243555\n ],\n [\n -111.60907745361328,\n 36.84775766525785\n ],\n [\n -111.60375595092772,\n 36.8509170844658\n ],\n [\n -111.59963607788086,\n 36.856823474483754\n ],\n [\n -111.5939712524414,\n 36.85874638670163\n ],\n [\n -111.588134765625,\n 36.8631414329529\n ],\n [\n -111.58315658569336,\n 36.8631414329529\n ],\n [\n -111.57989501953125,\n 36.861630664314674\n ],\n [\n -111.5797233581543,\n 36.8553125809442\n ],\n [\n -111.57508850097656,\n 36.84789503402531\n ],\n [\n -111.57302856445312,\n 36.842674847355426\n ],\n [\n -111.56633377075195,\n 36.84075153085174\n ],\n [\n -111.55740737915038,\n 36.841850574776956\n ],\n [\n -111.55071258544922,\n 36.84130105478872\n ],\n [\n -111.54247283935547,\n 36.84404861524222\n ],\n [\n -111.54075622558594,\n 36.84940607417791\n ],\n [\n -111.55088424682617,\n 36.857784936640186\n ],\n [\n -111.56375885009766,\n 36.87042017227047\n ],\n [\n -111.56375885009766,\n 36.87289203919785\n ],\n [\n -111.56118392944336,\n 36.87302936279296\n ],\n [\n -111.55431747436523,\n 36.87110680999585\n ],\n [\n -111.55105590820312,\n 36.87151878966862\n ],\n [\n -111.54401779174805,\n 36.87618773734233\n ],\n [\n -111.54058456420898,\n 36.87673700654107\n ],\n [\n -111.53234481811523,\n 36.87852210415612\n ],\n [\n -111.52547836303711,\n 36.875775782851\n ],\n [\n -111.51723861694336,\n 36.875363826137715\n ],\n [\n -111.5115737915039,\n 36.879483293282064\n ],\n [\n -111.51311874389648,\n 36.883465233639356\n ],\n [\n -111.51792526245116,\n 36.8868977741857\n ],\n [\n -111.52650833129881,\n 36.886485877468054\n ],\n [\n -111.5280532836914,\n 36.887996154568654\n ],\n [\n -111.52204513549805,\n 36.89280138293983\n ],\n [\n -111.52204513549805,\n 36.89870453512981\n ],\n [\n -111.51947021484375,\n 36.899528194484695\n ],\n [\n -111.50522232055664,\n 36.89897908923586\n ],\n [\n -111.50007247924805,\n 36.90199911920969\n ],\n [\n -111.49784088134766,\n 36.90886237918357\n ],\n [\n -111.49818420410156,\n 36.915450527897036\n ],\n [\n -111.4918327331543,\n 36.91599951460428\n ],\n [\n -111.48805618286133,\n 36.91723472024699\n ],\n [\n -111.48324966430664,\n 36.92121469122741\n ],\n [\n -111.4779281616211,\n 36.924371072232816\n ],\n [\n -111.47655487060547,\n 36.92821344666079\n ],\n [\n -111.47998809814453,\n 36.9367208722872\n ],\n [\n -111.48668289184569,\n 36.93466271122842\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Ecosystem modeling is a critical process for understanding complex systems at spatiotemporal scales needed to conserve, manage, and restore ecosystem services (ESs). Although mangrove wetlands are sources of ESs worth billions of dollars, there is a lack of modeling tools. This is reflected in our lack of understanding of mangroves’ functional and structural attributes. Here, we discuss the “state of the art” of mangrove models used in the planning and monitoring of R/R projects during the last 30 years. The main objectives were to characterize the most frequent modeling approach, their spatiotemporal resolution, and their current utility/application in management decisions. We identified 281 studies in six broad model categories: conceptual, agent-based (ABM), process-based (PBM), spatial, statistical, and socioeconomic/management (ScoEco). The most widely used models are spatial and statistical, followed by PBM, ScoEco, and conceptual categories, while the ABMs were the least frequently used. Yet, the application of mangrove models in R/R projects since the early 1990s has been extremely limited, especially in the mechanistic model category. We discuss several approaches to help advance model development and applications, including the targeted allocation of potential revenue from global carbon markets to R/R projects using a multi-model and integrated approach.
","language":"English","publisher":"MDPI","doi":"10.3390/f13101638","usgsCitation":"Rivera-Monroy, V.H., Zhao, X., Wang, H., and Xue, Z.G., 2022, Are existing modeling tools useful to evaluate outcomes in mangrove restoration and rehabilitation projects? A minireview: Forests, v. 13, no. 10, 1638, 21 p., https://doi.org/10.3390/f13101638.","productDescription":"1638, 21 p.","ipdsId":"IP-144365","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":446191,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/f13101638","text":"Publisher Index Page"},{"id":408477,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"10","noUsgsAuthors":false,"publicationDate":"2022-10-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Rivera-Monroy, Victor H. 0000-0003-2804-4139","orcid":"https://orcid.org/0000-0003-2804-4139","contributorId":200322,"corporation":false,"usgs":false,"family":"Rivera-Monroy","given":"Victor","email":"","middleInitial":"H.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":854879,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhao, Xiaochen","contributorId":219696,"corporation":false,"usgs":false,"family":"Zhao","given":"Xiaochen","email":"","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":854880,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wang, Hongqing 0000-0002-2977-7732","orcid":"https://orcid.org/0000-0002-2977-7732","contributorId":222813,"corporation":false,"usgs":true,"family":"Wang","given":"Hongqing","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":854881,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Xue, Zuo G.","contributorId":298021,"corporation":false,"usgs":false,"family":"Xue","given":"Zuo","email":"","middleInitial":"G.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":854882,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70238492,"text":"70238492 - 2022 - Genetic structure and historic demography of endangered unarmoured threespine stickleback at southern latitudes signals a potential new management approach","interactions":[],"lastModifiedDate":"2022-12-15T15:55:17.220395","indexId":"70238492","displayToPublicDate":"2022-10-07T07:51:41","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2774,"text":"Molecular Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Genetic structure and historic demography of endangered unarmoured threespine stickleback at southern latitudes signals a potential new management approach","docAbstract":"Habitat loss, flood control infrastructure, and drought have left most of southern California and northern Baja California's native freshwater fish near extinction, including the endangered unarmoured threespine stickleback (Gasterosteus aculeatus williamsoni). This subspecies, an unusual morph lacking the typical lateral bony plates of the G. aculeatus complex, occurs at arid southern latitudes in the eastern Pacific Ocean and survives in only three inland locations. Managers have lacked molecular data to answer basic questions about the ancestry and genetic distinctiveness of unarmoured populations. These data could be used to prioritize conservation efforts. We sampled G. aculeatus from 36 localities and used microsatellites and whole genome data to place unarmoured populations within the broader evolutionary context of G. aculeatus across southern California/northern Baja California. We identified three genetic groups with none consisting solely of unarmoured populations. Unlike G. aculeatus at northern latitudes, where Pleistocene glaciation has produced similar historical demographic profiles across populations, we found markedly different demographics depending on sampling location, with inland unarmoured populations showing steeper population declines and lower heterozygosity compared to low armoured populations in coastal lagoons. One exception involved the only high elevation population in the region, where the demography and alleles of unarmoured fish were similar to low armoured populations near the coast, exposing one of several cases of artificial translocation. Our results suggest that the current “management-by-phenotype” approach, based on lateral plates, is incidentally protecting the most imperilled populations; however, redirecting efforts toward evolutionary units, regardless of phenotype, may more effectively preserve adaptive potential.
","language":"English","publisher":"Wiley","doi":"10.1111/mec.16722","usgsCitation":"Turba, R., Richmond, J.Q., Fitz-Gibbon, S., Morselli, M., Fisher, R., Swift, C.C., Ruiz-Campos, G., Backlin, A.R., Dellith, C., and Jacobs, D.K., 2022, Genetic structure and historic demography of endangered unarmoured threespine stickleback at southern latitudes signals a potential new management approach: Molecular Ecology, v. 31, no. 24, p. 6515-6530, https://doi.org/10.1111/mec.16722.","productDescription":"16 p.","startPage":"6515","endPage":"6530","ipdsId":"IP-144634","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":446193,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/mec.16722","text":"Publisher Index Page"},{"id":409689,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","state":"Baja California, California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -115.59972346173339,\n 29.66662912056644\n ],\n [\n -116.3228483705328,\n 34.94795462564349\n ],\n [\n -120.9183518200569,\n 35.38592392602483\n ],\n [\n -120.53381107775209,\n 34.39232111031369\n ],\n [\n -120.2934320651216,\n 32.72373688169593\n ],\n [\n -117.30697616896543,\n 32.28570882745247\n ],\n [\n -115.66154688239834,\n 29.533400726878227\n ],\n [\n -115.59972346173339,\n 29.66662912056644\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"31","issue":"24","noUsgsAuthors":false,"publicationDate":"2022-10-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Turba, Rachel","contributorId":299368,"corporation":false,"usgs":false,"family":"Turba","given":"Rachel","email":"","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":857622,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Richmond, Jonathan Q. 0000-0001-9398-4894 jrichmond@usgs.gov","orcid":"https://orcid.org/0000-0001-9398-4894","contributorId":5400,"corporation":false,"usgs":true,"family":"Richmond","given":"Jonathan","email":"jrichmond@usgs.gov","middleInitial":"Q.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":857623,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fitz-Gibbon, Sorel","contributorId":299371,"corporation":false,"usgs":false,"family":"Fitz-Gibbon","given":"Sorel","email":"","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":857624,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Morselli, Marco","contributorId":299374,"corporation":false,"usgs":false,"family":"Morselli","given":"Marco","email":"","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":857625,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fisher, Robert N. 0000-0002-2956-3240","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":51675,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":857626,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Swift, Camm C.","contributorId":139395,"corporation":false,"usgs":false,"family":"Swift","given":"Camm","email":"","middleInitial":"C.","affiliations":[{"id":12725,"text":"Natural History Museum of Los Angeles County","active":true,"usgs":false}],"preferred":false,"id":857627,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ruiz-Campos, Gorgonio","contributorId":169077,"corporation":false,"usgs":false,"family":"Ruiz-Campos","given":"Gorgonio","email":"","affiliations":[{"id":25412,"text":"Laboratorio de Vertebrados, Facultad de Ciencias, Ensenada, Baja California","active":true,"usgs":false}],"preferred":false,"id":857628,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Backlin, Adam R. 0000-0001-5618-8426 abacklin@usgs.gov","orcid":"https://orcid.org/0000-0001-5618-8426","contributorId":3802,"corporation":false,"usgs":true,"family":"Backlin","given":"Adam","email":"abacklin@usgs.gov","middleInitial":"R.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":857629,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Dellith, Chris","contributorId":139396,"corporation":false,"usgs":false,"family":"Dellith","given":"Chris","email":"","affiliations":[{"id":6678,"text":"U.S. Fish and Wildlife Service, Alaska Maritime National Wildlife Refuge","active":true,"usgs":false}],"preferred":false,"id":857630,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Jacobs, David K.","contributorId":139394,"corporation":false,"usgs":false,"family":"Jacobs","given":"David","email":"","middleInitial":"K.","affiliations":[{"id":12763,"text":"University of California, Los Angeles","active":true,"usgs":false}],"preferred":false,"id":857631,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70237980,"text":"70237980 - 2022 - Identifying key stressors driving biological impairment in freshwater streams in the Chesapeake Bay watershed, USA","interactions":[],"lastModifiedDate":"2022-11-02T11:40:22.029965","indexId":"70237980","displayToPublicDate":"2022-10-07T06:37:16","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1547,"text":"Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Identifying key stressors driving biological impairment in freshwater streams in the Chesapeake Bay watershed, USA","docAbstract":"Biological communities in freshwater streams are often impaired by multiple stressors (e.g., flow or water quality) originating from anthropogenic activities such as urbanization, agriculture, or energy extraction. Restoration efforts in the Chesapeake Bay watershed, USA seek to improve biological conditions in 10% of freshwater tributaries and to protect the biological integrity of existing healthy watersheds. To achieve these goals, resource managers need to better understand which stressors are most likely driving biological impairment. Our study addressed this knowledge gap through two approaches: 1) reviewing and synthesizing published multi-stressor studies, and 2) examining 303(d) listed impairments linked to biological impairment as identified by jurisdiction regulatory agencies (the states within the watershed and the District of Columbia). Results identified geomorphology (i.e., physical habitat), salinity, and toxic contaminants as important for explaining variability in benthic community metrics in the literature review. Geomorphology (i.e., physical habitat and sediment), salinity, and nutrients were the most reported stressors in the jurisdictional impairment analysis. Salinity is likely a major stressor in urban and mining settings, whereas geomorphology was commonly reported in agricultural settings. Toxic contaminants, such as pesticides, were rarely measured; more research is needed to quantify the extent of their effects in the region. Flow alteration was also highlighted as an important urban stressor in the literature review but was rarely measured in the literature or reported by jurisdictions as a cause of impairment. These results can be used to prioritize stressor monitoring by managers, and to improve stressor identification methods for identifying causes of biological impairment.
Trap-and-haul programs can maintain connection among habitats for migratory salmonids in fragmented systems. To conserve diversity within and among life history strategies, downstream trap and transport of juvenile salmonids could ideally mimic the natural, underlying out-migration dynamics of the population. A two-way trap-and-haul program is implemented in the lower Clark Fork River, Montana, to conserve adfluvial Bull Trout Salvelinus confluentus. We used PIT technology to assess whether downstream trapping efforts are effectively capturing variation in the out-migration dynamics of juvenile Bull Trout in Graves Creek, a key spawning and rearing tributary in the system. We tagged 821 juvenile Bull Trout in Graves Creek and used these tagged Bull Trout in conjunction with stationary PIT antennas to monitor out-migration and evaluate efficiency of the downstream trapping program. Capture efficiency in Graves Creek varied substantially from autumn to spring, with 89–96% of autumn out-migrating Bull Trout captured and 5–10% of spring out-migrating Bull Trout captured. Overall, we found that Bull Trout transported during the autumn out-migration periods generally reflect the natural out-migration dynamics of the population; however, Bull Trout that out-migrate in the spring are currently underrepresented in the downstream transport program. By understanding the underlying out-migration dynamics of the Bull Trout population in Graves Creek, management of the downstream trapping efforts can focus on minimizing potential selection for or against out-migrants based on timing and age at out-migration. Minimizing selection will conserve variation within the adfluvial life history strategy and therefore maximize resilience of the adfluvial Bull Trout populations.
","language":"English","publisher":"Wiley","doi":"10.1002/nafm.10817","usgsCitation":"Lewis, M., Guy, C.S., Oldenburg, E., and McMahon, T., 2022, Temporal variation in capture efficiency underrepresents spring out-migrating Bull Trout in a trap-and-haul program: North American Journal of Fisheries Management, v. 42, no. 5, p. 1237-1249, https://doi.org/10.1002/nafm.10817.","productDescription":"13 p.","startPage":"1237","endPage":"1249","ipdsId":"IP-139824","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":485511,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Montana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.33181112337759,\n 48.716602752324974\n ],\n [\n -116.33181112337759,\n 48.106842812139405\n ],\n [\n -115.54832319686268,\n 48.106842812139405\n ],\n [\n -115.54832319686268,\n 48.716602752324974\n ],\n [\n -116.33181112337759,\n 48.716602752324974\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"42","issue":"5","noUsgsAuthors":false,"publicationDate":"2022-09-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Lewis, Madeline C.","contributorId":354619,"corporation":false,"usgs":false,"family":"Lewis","given":"Madeline C.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":936002,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Guy, Christopher S. 0000-0002-9936-4781 cguy@usgs.gov","orcid":"https://orcid.org/0000-0002-9936-4781","contributorId":2876,"corporation":false,"usgs":true,"family":"Guy","given":"Christopher","email":"cguy@usgs.gov","middleInitial":"S.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":5062,"text":"Office of the Chief Scientist for Ecosystems","active":true,"usgs":true}],"preferred":true,"id":936003,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Oldenburg, Eric W.","contributorId":354620,"corporation":false,"usgs":false,"family":"Oldenburg","given":"Eric W.","affiliations":[{"id":84641,"text":"Noxon Natural Resources Office","active":true,"usgs":false}],"preferred":false,"id":936004,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McMahon, Thomas E.","contributorId":354621,"corporation":false,"usgs":false,"family":"McMahon","given":"Thomas E.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":936005,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70255211,"text":"70255211 - 2022 - Industrial energy development decouples ungulate migration from the green wave","interactions":[],"lastModifiedDate":"2024-06-13T16:04:59.632829","indexId":"70255211","displayToPublicDate":"2022-10-06T10:58:02","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6505,"text":"Nature Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Industrial energy development decouples ungulate migration from the green wave","docAbstract":"The ability to freely move across the landscape to track the emergence of nutritious spring green-up (termed ‘green-wave surfing’) is key to the foraging strategy of migratory ungulates. Across the vast landscapes traversed by many migratory herds, habitats are being altered by development with unknown consequences for surfing. Using a unique long-term tracking dataset, we found that when energy development occurs within mule deer (Odocoileus hemionus) migration corridors, migrating animals become decoupled from the green wave. During the early phases of a coalbed natural gas development, deer synchronized their movements with peak green-up. But faced with increasing disturbance as development expanded, deer altered their movements by holding up at the edge of the gas field and letting the green wave pass them by. Development often modified only a small portion of the migration corridor but had far-reaching effects on behaviour before and after migrating deer encountered it, thus reducing surfing along the entire route by 38.65% over the 14-year study period. Our study suggests that industrial development within migratory corridors can change the behaviour of migrating ungulates and diminish the benefits of migration. Such disruptions to migratory behaviour present a common mechanism whereby corridors become unprofitable and could ultimately be lost on highly developed landscapes.
","language":"English","publisher":"Nature","doi":"10.1038/s41559-022-01887-9","collaboration":"Western EcoSystems, INC","usgsCitation":"Aikens, E.O., Wyckoff, T., Sawyer, H., and Kauffman, M., 2022, Industrial energy development decouples ungulate migration from the green wave: Nature Ecology and Evolution, v. 6, p. 1733-1741, https://doi.org/10.1038/s41559-022-01887-9.","productDescription":"9 p.","startPage":"1733","endPage":"1741","ipdsId":"IP-136329","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":430147,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -108.50057122965278,\n 41.908308585415085\n ],\n [\n -108.50057122965278,\n 40.99058578879266\n ],\n [\n -107.30804228444518,\n 40.99058578879266\n ],\n [\n -107.30804228444518,\n 41.908308585415085\n ],\n [\n -108.50057122965278,\n 41.908308585415085\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"6","noUsgsAuthors":false,"publicationDate":"2022-10-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Aikens, Ellen O.","contributorId":272241,"corporation":false,"usgs":false,"family":"Aikens","given":"Ellen","email":"","middleInitial":"O.","affiliations":[{"id":40829,"text":"uwy","active":true,"usgs":false}],"preferred":false,"id":903738,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wyckoff, Teal B.","contributorId":339010,"corporation":false,"usgs":false,"family":"Wyckoff","given":"Teal B.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":903739,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sawyer, Hall","contributorId":287880,"corporation":false,"usgs":false,"family":"Sawyer","given":"Hall","affiliations":[{"id":61660,"text":"Western Ecosystems Technology, Inc., Laramie, WY","active":true,"usgs":false}],"preferred":false,"id":903740,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kauffman, Matthew J. 0000-0003-0127-3900","orcid":"https://orcid.org/0000-0003-0127-3900","contributorId":202921,"corporation":false,"usgs":true,"family":"Kauffman","given":"Matthew","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":903741,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70237280,"text":"70237280 - 2022 - Immunogenicity, safety, and anti-viral efficacy of a subunit SARS-CoV-2 vaccine candidate in captive black-footed ferrets (Mustela nigripes) and their susceptibility to viral challenge","interactions":[],"lastModifiedDate":"2022-10-17T16:41:14.433649","indexId":"70237280","displayToPublicDate":"2022-10-06T09:33:35","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3700,"text":"Viruses","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Immunogenicity, safety, and anti-viral efficacy of a subunit SARS-CoV-2 vaccine candidate in captive black-footed ferrets (Mustela nigripes) and their susceptibility to viral challenge","title":"Immunogenicity, safety, and anti-viral efficacy of a subunit SARS-CoV-2 vaccine candidate in captive black-footed ferrets (Mustela nigripes) and their susceptibility to viral challenge","docAbstract":"A preliminary vaccination trial against the emergent pathogen, SARS-CoV-2, was completed in captive black-footed ferrets (Mustela nigripes; BFF) to assess safety, immunogenicity, and anti-viral efficacy. Vaccination and boosting of 15 BFF with purified SARS-CoV-2 S1 subunit protein produced a nearly 150-fold increase in mean antibody titers compared to pre-vaccination titers. Serum antibody responses were highest in young animals, but in all vaccinees, antibody response declined rapidly. Anti-viral activity from vaccinated and unvaccinated BFF was determined in vitro, as well as in vivo with a passive serum transfer study in mice. Transgenic mice that received BFF serum transfers and were subsequently challenged with SARS-CoV-2 had lung viral loads that negatively correlated (p < 0.05) with the BFF serum titer received. Lastly, an experimental challenge study in a small group of BFF was completed to test susceptibility to SARS-CoV-2. Despite viral replication and shedding in the upper respiratory tract for up to 7 days post-challenge, no clinical disease was observed in either vaccinated or naive animals. The lack of morbidity or mortality observed indicates SARS-CoV-2 is unlikely to affect wild BFF populations, but infected captive animals pose a potential risk, albeit low, for humans and other animals.
","language":"English","publisher":"MDPI","doi":"10.3390/v14102188","usgsCitation":"Leon, A.E., Garelle, D., Hartwig, A., Falendysz, E., Ip, H., Lankton, J.S., Tretten, T., Spraker, T., Bowen, R., and Rocke, T.E., 2022, Immunogenicity, safety, and anti-viral efficacy of a subunit SARS-CoV-2 vaccine candidate in captive black-footed ferrets (Mustela nigripes) and their susceptibility to viral challenge: Viruses, v. 14, no. 10, 2188, 15 p., https://doi.org/10.3390/v14102188.","productDescription":"2188, 15 p.","ipdsId":"IP-144258","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":446199,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/v14102188","text":"Publisher Index Page"},{"id":435663,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9GZEXN9","text":"USGS data release","linkHelpText":"Viral loads, histology, and adverse events in transgenic mice after passive transfer of serum from black-footed ferrets (Mustela nigripes) used to assess the anti-viral efficacy of a subunit SARS-CoV-2 vaccine candidate"},{"id":408037,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"10","noUsgsAuthors":false,"publicationDate":"2022-10-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Leon, Ariel Elizabeth 0000-0001-9246-4619","orcid":"https://orcid.org/0000-0001-9246-4619","contributorId":247573,"corporation":false,"usgs":true,"family":"Leon","given":"Ariel","email":"","middleInitial":"Elizabeth","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":853959,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Garelle, Della","contributorId":297372,"corporation":false,"usgs":false,"family":"Garelle","given":"Della","email":"","affiliations":[{"id":64382,"text":"US Fish and Wildlife Service, National Black-Footed Ferret Conservation Center, P.O. Box 190, Wellington, Colorado","active":true,"usgs":false}],"preferred":false,"id":853960,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hartwig, Airn","contributorId":297373,"corporation":false,"usgs":false,"family":"Hartwig","given":"Airn","email":"","affiliations":[{"id":64383,"text":"Colorado State University, Department of Biomedical Sciences, 3107 Rampart Road, Fort Collins, Colorado","active":true,"usgs":false}],"preferred":false,"id":853961,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Falendysz, Elizabeth 0000-0003-2895-8918 efalendysz@usgs.gov","orcid":"https://orcid.org/0000-0003-2895-8918","contributorId":127751,"corporation":false,"usgs":true,"family":"Falendysz","given":"Elizabeth","email":"efalendysz@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":853962,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ip, Hon S. 0000-0003-4844-7533","orcid":"https://orcid.org/0000-0003-4844-7533","contributorId":126815,"corporation":false,"usgs":true,"family":"Ip","given":"Hon S.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":853963,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lankton, Julia S. 0000-0002-6843-4388 jlankton@usgs.gov","orcid":"https://orcid.org/0000-0002-6843-4388","contributorId":5888,"corporation":false,"usgs":true,"family":"Lankton","given":"Julia","email":"jlankton@usgs.gov","middleInitial":"S.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":853964,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Tretten, Tyler","contributorId":297374,"corporation":false,"usgs":false,"family":"Tretten","given":"Tyler","affiliations":[{"id":64384,"text":"US Fish and Wildlife Service, National Black-Footed Ferret Conservation Center","active":true,"usgs":false}],"preferred":false,"id":853965,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Spraker, Terry","contributorId":297375,"corporation":false,"usgs":false,"family":"Spraker","given":"Terry","affiliations":[{"id":64385,"text":"Colorado State University, Department of Microbiology, Immunology and Pathology, 2450 Gillette Dr, Fort Collins, CO 80526","active":true,"usgs":false}],"preferred":false,"id":853966,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Bowen, Richard","contributorId":297376,"corporation":false,"usgs":false,"family":"Bowen","given":"Richard","affiliations":[{"id":64386,"text":"Colorado State University, Department of Biomedical Sciences, 3107 Rampart Road, Fort Collins, Colorado 80523 USA","active":true,"usgs":false}],"preferred":false,"id":853967,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Rocke, Tonie E. 0000-0003-3933-1563 trocke@usgs.gov","orcid":"https://orcid.org/0000-0003-3933-1563","contributorId":2665,"corporation":false,"usgs":true,"family":"Rocke","given":"Tonie","email":"trocke@usgs.gov","middleInitial":"E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":853968,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70237277,"text":"70237277 - 2022 - Absolute accuracy assessment of lidar point cloud using amorphous objects","interactions":[],"lastModifiedDate":"2022-10-06T14:30:04.492861","indexId":"70237277","displayToPublicDate":"2022-10-06T09:26:08","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Absolute accuracy assessment of lidar point cloud using amorphous objects","docAbstract":"The accuracy assessment of airborne lidar point cloud typically estimates vertical accuracy by computing RMSEz (root mean square error of the z coordinate) from ground check points (GCPs). Due to the low point density of the airborne lidar point cloud, there is often not enough accurate semantic context to find an accurate conjugate point. To advance the accuracy assessment in full three-dimensional (3D) context, geometric features, such as the three-plane intersection point or two-line intersection point, are often used. Although the point density is still low, geometric features are mathematically modeled from many points. Thus, geometric features provide a robust determination of the intersection point, and the point is considered as a GCP. When no regular built objects are available, we describe the process of utilizing features of irregular shape called amorphous natural objects, such as a tree or a rock. When scanned to a high-density point cloud, an amorphous natural object can be used as ground truth reference data to estimate 3D georeferencing errors of the airborne lidar point cloud. The algorithm to estimate 3D accuracy is the optimization that minimizes the sum of the distance between the airborne lidar points to the ground scanned data. The search volume partitioning was the most important procedure to improve the computational efficiency. We also performed an extensive study to address the external uncertainty associated with the amorphous object method. We describe an accuracy assessment using amorphous objects (108 trees) spread over the project area. The accuracy results for ∆x, ∆y, and ∆z obtained using the amorphous object method were 3.1 cm, 3.6 cm, and 1.7 cm RMSE, along with a mean error of 0.1 cm, 0.1 cm, and 4.5 cm, respectively, satisfying the accuracy requirement of U.S. Geological Survey lidar base specification. This approach shows strong promise as an alternative to geometric feature methods when artificial targets are scarce. The relative convenience and advantages of using amorphous targets, along with its good performance shown here, make this amorphous object method a practical way to perform 3D accuracy assessment.
","language":"English","publisher":"MDPI","doi":"10.3390/rs14194767","usgsCitation":"Kim, M., Stoker, J.M., Irwin, J., Danielson, J.J., and Park, S., 2022, Absolute accuracy assessment of lidar point cloud using amorphous objects: Remote Sensing, v. 14, no. 19, 4767, 18 p., https://doi.org/10.3390/rs14194767.","productDescription":"4767, 18 p.","ipdsId":"IP-145321","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":446201,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs14194767","text":"Publisher Index Page"},{"id":408035,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"19","noUsgsAuthors":false,"publicationDate":"2022-09-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Kim, Minsu 0000-0003-4472-0926","orcid":"https://orcid.org/0000-0003-4472-0926","contributorId":297371,"corporation":false,"usgs":false,"family":"Kim","given":"Minsu","affiliations":[{"id":54490,"text":"KBR, Inc., under contract to USGS","active":true,"usgs":false}],"preferred":false,"id":853945,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stoker, Jason M. 0000-0003-2455-0931 jstoker@usgs.gov","orcid":"https://orcid.org/0000-0003-2455-0931","contributorId":3021,"corporation":false,"usgs":true,"family":"Stoker","given":"Jason","email":"jstoker@usgs.gov","middleInitial":"M.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":true,"id":853946,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Irwin, Jeffrey 0000-0001-5828-0787 jrirwin@usgs.gov","orcid":"https://orcid.org/0000-0001-5828-0787","contributorId":222485,"corporation":false,"usgs":true,"family":"Irwin","given":"Jeffrey","email":"jrirwin@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":853947,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Danielson, Jeffrey J. 0000-0003-0907-034X daniels@usgs.gov","orcid":"https://orcid.org/0000-0003-0907-034X","contributorId":3996,"corporation":false,"usgs":true,"family":"Danielson","given":"Jeffrey","email":"daniels@usgs.gov","middleInitial":"J.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":853948,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Park, Seonkyung 0000-0003-3203-1998 seonkyungpark@contractor.usgs.gov","orcid":"https://orcid.org/0000-0003-3203-1998","contributorId":222488,"corporation":false,"usgs":false,"family":"Park","given":"Seonkyung","email":"seonkyungpark@contractor.usgs.gov","affiliations":[{"id":40547,"text":"United Support Services, Contractor to the USGS Earth Resources Observation and Science (EROS) Center","active":true,"usgs":false}],"preferred":false,"id":853949,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70237290,"text":"70237290 - 2022 - Sediment source fingerprinting as an aid to large-scale landscape conservation and restoration: A review for the Mississippi River Basin","interactions":[],"lastModifiedDate":"2022-10-06T14:25:24.776873","indexId":"70237290","displayToPublicDate":"2022-10-06T09:19:21","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Sediment source fingerprinting as an aid to large-scale landscape conservation and restoration: A review for the Mississippi River Basin","docAbstract":"Reliable quantitative information on sediment sources to rivers is critical to mitigate contamination and target conservation and restoration actions. However, the determination of the relative importance of sediment sources is complicated at the scale of large river basins by immense variability in erosional processes and sediment sources over space and time, heterogeneity in sediment transport and deposition, and a paucity of sediment monitoring data. Sediment source fingerprinting is an increasingly adopted field-based technique that identifies the nature and relative source contribution of sediment transported in waterways. Notably, sediment source fingerprinting provides information that is independent of other field, modeling, or remotely sensed techniques. However, the diversity in sediment fingerprinting sampling, analytical, and interpretive methods has been recognized as a problem in terms of developing standardized procedures for its application at the scale of large river basins. Accordingly, this review focuses on established sediment source fingerprinting studies conducted within the Mississippi River Basin (MRB), summarizes unique information provided by sediment source fingerprinting that is distinct from traditional monitoring techniques, evaluates consistency and reliability of methodological approaches among MRB studies, and provides prospects for the use of the sediment source fingerprinting technique as an aid to large-scale landscape conservation and restoration under current management frameworks. Most established MRB studies got creditable fingerprinting results and considered near-channel sources as the dominant sediment sources in most cases, while the comparability of their results suffers from a lack of standardization in procedural steps. Findings from MRB studies demonstrate that sediment source fingerprinting is a highly valuable and reliable sediment source assessment approach to assist land and water resource management under current management frameworks, but efforts are still needed to make this technique ready to be used in a more predominant way in large-scale landscape conservation and restoration efforts. We summarized research needs and suggested the best fingerprinting practices for management purposes with the aim of ensuring that this technique is as robust and reliable as it moves forward.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2022.116260","usgsCitation":"Xu, Z., Belmont, P., Brahney, J., and Gellis, A.C., 2022, Sediment source fingerprinting as an aid to large-scale landscape conservation and restoration: A review for the Mississippi River Basin: Journal of Environmental Management, v. 324, 116260, 20 p., https://doi.org/10.1016/j.jenvman.2022.116260.","productDescription":"116260, 20 p.","ipdsId":"IP-141762","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":446204,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jenvman.2022.116260","text":"Publisher Index Page"},{"id":408033,"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 \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.0869140625,\n 29.57345707301757\n ],\n [\n -89.7802734375,\n 28.729130483430154\n ],\n [\n -89.20898437499999,\n 29.34387539941801\n ],\n [\n -89.5166015625,\n 30.107117887092357\n ],\n [\n -89.384765625,\n 33.65120829920497\n ],\n [\n -82.8369140625,\n 34.77771580360469\n ],\n [\n -79.40917968749999,\n 36.59788913307022\n ],\n [\n -77.6953125,\n 42.391008609205045\n ],\n [\n -79.365234375,\n 42.4234565179383\n ],\n [\n -81.9580078125,\n 41.31082388091818\n ],\n [\n -87.099609375,\n 41.0130657870063\n ],\n [\n -87.62695312499999,\n 41.672911819602085\n ],\n [\n -88.2861328125,\n 43.229195113965005\n ],\n [\n -90.1318359375,\n 46.49839225859763\n ],\n [\n -92.021484375,\n 46.558860303117164\n ],\n [\n -93.8232421875,\n 47.54687159892238\n ],\n [\n -95.00976562499999,\n 47.54687159892238\n ],\n [\n -98.61328125,\n 47.100044694025215\n ],\n [\n -104.0185546875,\n 49.009050809382046\n ],\n [\n -115.00488281250001,\n 49.03786794532644\n ],\n [\n -114.60937499999999,\n 46.92025531537451\n ],\n [\n -114.521484375,\n 45.85941212790755\n ],\n [\n -112.8076171875,\n 44.62175409623324\n ],\n [\n -111.1376953125,\n 44.99588261816546\n ],\n [\n -109.2919921875,\n 44.715513732021336\n ],\n [\n -108.896484375,\n 42.65012181368022\n ],\n [\n -106.12792968749999,\n 40.88029480552824\n ],\n [\n -105.3369140625,\n 39.26628442213066\n ],\n [\n -105.29296874999999,\n 37.16031654673677\n ],\n [\n -105.29296874999999,\n 34.92197103616377\n ],\n [\n -103.0517578125,\n 34.23451236236987\n ],\n [\n -97.646484375,\n 33.46810795527896\n ],\n [\n -93.955078125,\n 31.353636941500987\n ],\n [\n -94.0869140625,\n 29.57345707301757\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"324","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Xu, Zhen","contributorId":297389,"corporation":false,"usgs":false,"family":"Xu","given":"Zhen","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":853997,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belmont, Patrick","contributorId":275033,"corporation":false,"usgs":false,"family":"Belmont","given":"Patrick","affiliations":[{"id":28050,"text":"USU","active":true,"usgs":false}],"preferred":false,"id":853998,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brahney, Janice","contributorId":269810,"corporation":false,"usgs":false,"family":"Brahney","given":"Janice","email":"","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":853999,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gellis, Allen C. 0000-0002-3449-2889 agellis@usgs.gov","orcid":"https://orcid.org/0000-0002-3449-2889","contributorId":197684,"corporation":false,"usgs":true,"family":"Gellis","given":"Allen","email":"agellis@usgs.gov","middleInitial":"C.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":854000,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70237272,"text":"70237272 - 2022 - Simple statistical models can be sufficient for testing hypotheses with population time series data","interactions":[],"lastModifiedDate":"2022-10-06T14:10:39.16442","indexId":"70237272","displayToPublicDate":"2022-10-06T08:52:34","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Simple statistical models can be sufficient for testing hypotheses with population time series data","docAbstract":"Time-series data offer wide-ranging opportunities to test hypotheses about the physical and biological factors that influence species abundances. Although sophisticated models have been developed and applied to analyze abundance time series, they require information about species detectability that is often unavailable. We propose that in many cases, simpler models are adequate for testing hypotheses. We consider three relatively simple regression models for time series, using simulated and empirical (fish and mammal) datasets. Model A is a conventional generalized linear model of abundance, model B adds a temporal autoregressive term, and model C uses an estimate of population growth rate as a response variable, with the option of including a term for density dependence. All models can be fit using Bayesian and non-Bayesian methods. Simulation results demonstrated that model C tended to have greater support for long-lived, lower-fecundity organisms (K life-history strategists), while model A, the simplest, tended to be supported for shorter-lived, high-fecundity organisms (r life-history strategists). Analysis of real-world fish and mammal datasets found that models A, B, and C each enjoyed support for at least some species, but sometimes yielded different insights. In particular, model C indicated effects of predictor variables that were not evident in analyses with models A and B. Bayesian and frequentist models yielded similar parameter estimates and performance. We conclude that relatively simple models are useful for testing hypotheses about the factors that influence abundance in time-series data, and can be appropriate choices for datasets that lack the information needed to fit more complicated models. When feasible, we advise fitting datasets with multiple models because they can provide complementary information.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.9339","usgsCitation":"Wenger, S., Stowe, E.S., Gido, K.B., Freeman, M., Kanno, Y., Franssen, N.R., Olden, J., Poff, N.L., Walters, A.W., Bumpers, P.M., Mims, M.C., Hooten, M.B., and Lu, X., 2022, Simple statistical models can be sufficient for testing hypotheses with population time series data: Ecology and Evolution, v. 12, no. 9, e9339, 13 p., https://doi.org/10.1002/ece3.9339.","productDescription":"e9339, 13 p.","ipdsId":"IP-133439","costCenters":[{"id":683,"text":"Wyoming Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":446206,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/ece3.9339","text":"External Repository"},{"id":408029,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"9","noUsgsAuthors":false,"publicationDate":"2022-09-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Wenger, Seth J.","contributorId":177838,"corporation":false,"usgs":false,"family":"Wenger","given":"Seth J.","affiliations":[],"preferred":false,"id":853925,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stowe, Edward S.","contributorId":273256,"corporation":false,"usgs":false,"family":"Stowe","given":"Edward","email":"","middleInitial":"S.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":853926,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gido, Keith B.","contributorId":198487,"corporation":false,"usgs":false,"family":"Gido","given":"Keith","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":853927,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Freeman, Mary 0000-0001-7615-6923 mcfreeman@usgs.gov","orcid":"https://orcid.org/0000-0001-7615-6923","contributorId":3528,"corporation":false,"usgs":true,"family":"Freeman","given":"Mary","email":"mcfreeman@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":853928,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kanno, Yoichiro","contributorId":210653,"corporation":false,"usgs":false,"family":"Kanno","given":"Yoichiro","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":853929,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Franssen, Nathan R.","contributorId":273252,"corporation":false,"usgs":false,"family":"Franssen","given":"Nathan","email":"","middleInitial":"R.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":853930,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Olden, Julian 0000-0003-2143-1187","orcid":"https://orcid.org/0000-0003-2143-1187","contributorId":296007,"corporation":false,"usgs":false,"family":"Olden","given":"Julian","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":853931,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Poff, N. LeRoy","contributorId":261271,"corporation":false,"usgs":false,"family":"Poff","given":"N.","email":"","middleInitial":"LeRoy","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":853932,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"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":853933,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Bumpers, Phillip M.","contributorId":203871,"corporation":false,"usgs":false,"family":"Bumpers","given":"Phillip","email":"","middleInitial":"M.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":853934,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Mims, Meryl C. 0000-0003-0570-988X","orcid":"https://orcid.org/0000-0003-0570-988X","contributorId":209951,"corporation":false,"usgs":false,"family":"Mims","given":"Meryl","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":853935,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Hooten, Mevin B. 0000-0002-1614-723X","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":292295,"corporation":false,"usgs":false,"family":"Hooten","given":"Mevin","email":"","middleInitial":"B.","affiliations":[{"id":12430,"text":"University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":853936,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Lu, Xinyi","contributorId":279368,"corporation":false,"usgs":false,"family":"Lu","given":"Xinyi","affiliations":[{"id":13606,"text":"CSU","active":true,"usgs":false}],"preferred":false,"id":853937,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70237276,"text":"70237276 - 2022 - Range-wide population projections for Northern Red-Bellied Cooters (Pseudemys rubriventris)","interactions":[],"lastModifiedDate":"2022-10-06T13:47:45.013432","indexId":"70237276","displayToPublicDate":"2022-10-06T08:35:56","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2334,"text":"Journal of Herpetology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Range-wide population projections for Northern Red-Bellied Cooters (Pseudemys rubriventris)","title":"Range-wide population projections for Northern Red-Bellied Cooters (Pseudemys rubriventris)","docAbstract":"Northern Red-Bellied Cooters (Pseudemys rubriventris) have a disjunct distribution with a relictual population in southeastern Massachusetts and a larger range across the mid-Atlantic United States. The relictual population is currently listed with protections under the U.S. Endangered Species Act but the status of the population in the remainder of the species' range has not been assessed, and there is concern that it may be at risk of extinction without protection. The U.S. Fish and Wildlife Service requires scientific information of the species' status to inform conservation decisions. There is little empirical information available from P. rubriventris populations and, furthermore, the majority of what exists comes from the disjunct northern subpopulation. To fill data gaps in the species' life history and reduce geographic bias, we supplement available data from P. rubriventris with demographic rate estimates from other Pseudemys species to parameterize an age-structured population projection model. Our estimate of mean population growth rate was 0.987 (0.92–1.04), indicating that P. rubriventris populations may be in decline. However, there was considerable uncertainty in our results, with 35% of projections resulting in stable or increasing populations. Additional uncertainty about parameter values, geographic variation, and current threats limit the assessment. We discuss the merits and limitations of our population projection modeling (PPM) approach where other analytical methods are precluded by lack of available data.
","language":"English","publisher":"Society for the Study of Amphibians and Reptiles","doi":"10.1670/21-065","usgsCitation":"Fleming, J.E., Moore, J.F., Waddle, H., Martin, J., and Campbell Grant, E.H., 2022, Range-wide population projections for Northern Red-Bellied Cooters (Pseudemys rubriventris): Journal of Herpetology, v. 56, no. 3, p. 362-369, https://doi.org/10.1670/21-065.","productDescription":"8 p.","startPage":"362","endPage":"369","ipdsId":"IP-130062","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":408028,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland, Massachusetts, New Jersey, North Carolina, Pennsylvania, Virginia, West Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.332763671875,\n 34.551811369170494\n ],\n [\n -76.607666015625,\n 34.6241677899049\n ],\n [\n -76.201171875,\n 34.831841149828655\n ],\n [\n -75.399169921875,\n 35.23664622093195\n ],\n [\n -75.322265625,\n 35.47856499535729\n ],\n [\n -75.377197265625,\n 35.84453450421662\n ],\n [\n -75.83862304687499,\n 37.046408899699564\n ],\n [\n -74.970703125,\n 38.26406296833961\n ],\n [\n -74.981689453125,\n 38.65119833229951\n ],\n [\n -74.827880859375,\n 38.8824811975508\n ],\n [\n -74.168701171875,\n 39.58029027440865\n ],\n [\n -73.80615234375,\n 40.33817045213394\n ],\n [\n -74.1357421875,\n 40.49709237269567\n ],\n [\n -77.750244140625,\n 40.75557964275589\n ],\n [\n -79.332275390625,\n 39.715638134796336\n ],\n [\n -79.595947265625,\n 38.59970036588819\n ],\n [\n -78.134765625,\n 35.71975793933433\n ],\n [\n -77.332763671875,\n 34.551811369170494\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.202392578125,\n 41.72213058512578\n ],\n [\n -70.499267578125,\n 41.72213058512578\n ],\n [\n -70.499267578125,\n 42.27730877423709\n ],\n [\n -71.202392578125,\n 42.27730877423709\n ],\n [\n -71.202392578125,\n 41.72213058512578\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"56","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Fleming, Jillian Elizabeth 0000-0003-2570-914X","orcid":"https://orcid.org/0000-0003-2570-914X","contributorId":238931,"corporation":false,"usgs":true,"family":"Fleming","given":"Jillian","email":"","middleInitial":"Elizabeth","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":853940,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moore, Jennifer F.","contributorId":189122,"corporation":false,"usgs":false,"family":"Moore","given":"Jennifer","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":853941,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Waddle, Hardin 0000-0003-1940-2133","orcid":"https://orcid.org/0000-0003-1940-2133","contributorId":206866,"corporation":false,"usgs":true,"family":"Waddle","given":"Hardin","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":853942,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Martin, Julien 0000-0002-7375-129X","orcid":"https://orcid.org/0000-0002-7375-129X","contributorId":216734,"corporation":false,"usgs":true,"family":"Martin","given":"Julien","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":853943,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Campbell Grant, Evan H. 0000-0003-4401-6496 ehgrant@usgs.gov","orcid":"https://orcid.org/0000-0003-4401-6496","contributorId":150443,"corporation":false,"usgs":true,"family":"Campbell Grant","given":"Evan","email":"ehgrant@usgs.gov","middleInitial":"H.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":853944,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70238817,"text":"70238817 - 2022 - Post-fire seed dispersal of a wind-dispersed shrub declined with distance to seed source, yet had high levels of unexplained variation","interactions":[],"lastModifiedDate":"2022-12-13T13:40:55.160716","indexId":"70238817","displayToPublicDate":"2022-10-06T07:10:53","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5538,"text":"AoB PLANTS","active":true,"publicationSubtype":{"id":10}},"title":"Post-fire seed dispersal of a wind-dispersed shrub declined with distance to seed source, yet had high levels of unexplained variation","docAbstract":"Plant-population recovery across large disturbance areas is often seed-limited. An understanding of seed dispersal patterns is fundamental for determining natural-regeneration potential. However, forecasting seed dispersal rates across heterogeneous landscapes remains a challenge. Our objectives were to determine (i) the landscape patterning of post-disturbance seed dispersal, and underlying sources of variation and the scale at which they operate, and (ii) how the natural seed dispersal patterns relate to a seed augmentation strategy. Vertical seed trapping experiments were replicated across 2 years and five burned and/or managed landscapes in sagebrush steppe. Multi-scale sampling and hierarchical Bayesian models were used to determine the scale of spatial variation in seed dispersal. We then integrated an empirical and mechanistic dispersal kernel for wind-dispersed species to project rates of seed dispersal and compared natural seed arrival to typical post-fire aerial seeding rates. Seeds were captured across the range of tested dispersal distances, up to a maximum distance of 26 m from seed-source plants, although dispersal to the furthest traps was variable. Seed dispersal was better explained by transect heterogeneity than by patch or site heterogeneity (transects were nested within patch within site). The number of seeds captured varied from a modelled mean of ~13 m−2 adjacent to patches of seed-producing plants, to nearly none at 10 m from patches, standardized over a 49-day period. Maximum seed dispersal distances on average were estimated to be 16 m according to a novel modelling approach using a ‘latent’ variable for dispersal distance based on seed trapping heights. Surprisingly, statistical representation of wind did not improve model fit and seed rain was not related to the large variation in total available seed of adjacent patches. The models predicted severe seed limitations were likely on typical burned areas, especially compared to the mean 95–250 seeds per m2 that previous literature suggested were required to generate sagebrush recovery. More broadly, our Bayesian data fusion approach could be applied to other cases that require quantitative estimates of long-distance seed dispersal across heterogeneous landscapes.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/aobpla/plac045","usgsCitation":"Applestein, C., Caughlin, T., and Germino, M., 2022, Post-fire seed dispersal of a wind-dispersed shrub declined with distance to seed source, yet had high levels of unexplained variation: AoB PLANTS, v. 14, no. 6, plac045, 13 p., https://doi.org/10.1093/aobpla/plac045.","productDescription":"plac045, 13 p.","ipdsId":"IP-127630","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":446211,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/aobpla/plac045","text":"Publisher Index Page"},{"id":410359,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.2526670227266,\n 45.4\n ],\n [\n -117.2526670227266,\n 43.21761290801206\n ],\n [\n -113.74569616023115,\n 43.21761290801206\n ],\n [\n -113.74569616023115,\n 45.4\n ],\n [\n -117.2526670227266,\n 45.4\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"14","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-10-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Applestein, Cara 0000-0002-7923-8526","orcid":"https://orcid.org/0000-0002-7923-8526","contributorId":218003,"corporation":false,"usgs":true,"family":"Applestein","given":"Cara","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":858780,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Caughlin, Trevor 0000-0001-6752-2055","orcid":"https://orcid.org/0000-0001-6752-2055","contributorId":256964,"corporation":false,"usgs":false,"family":"Caughlin","given":"Trevor","email":"","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":858781,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Germino, Matthew J. 0000-0001-6326-7579","orcid":"https://orcid.org/0000-0001-6326-7579","contributorId":251901,"corporation":false,"usgs":true,"family":"Germino","given":"Matthew J.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":858782,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70240117,"text":"70240117 - 2022 - Antecedent climatic conditions spanning several years influence multiple land-surface phenology events in semi-arid environments","interactions":[],"lastModifiedDate":"2023-01-27T13:09:43.480884","indexId":"70240117","displayToPublicDate":"2022-10-06T07:02:49","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3910,"text":"Frontiers in Ecology and Evolution","onlineIssn":"2296-701X","active":true,"publicationSubtype":{"id":10}},"title":"Antecedent climatic conditions spanning several years influence multiple land-surface phenology events in semi-arid environments","docAbstract":"Ecological processes are complex, often exhibiting non-linear, interactive, or hierarchical relationships. Furthermore, models identifying drivers of phenology are constrained by uncertainty regarding predictors, interactions across scales, and legacy impacts of prior climate conditions. Nonetheless, measuring and modeling ecosystem processes such as phenology remains critical for management of ecological systems and the social systems they support. We used random forest models to assess which combination of climate, location, edaphic, vegetation composition, and disturbance variables best predict several phenological responses in three dominant land cover types in the U.S. Northwestern Great Plains (NWP). We derived phenological measures from the 25-year series of AVHRR satellite data and characterized climatic predictors (i.e., multiple moisture and/or temperature based variables) over seasonal and annual timeframes within the current year and up to 4 years prior. We found that antecedent conditions, from seasons to years before the current, were strongly associated with phenological measures, apparently mediating the responses of communities to current-year conditions. For example, at least one measure of antecedent-moisture availability [precipitation or vapor pressure deficit (VPD)] over multiple years was a key predictor of all productivity measures. Variables including longer-term lags or prior year sums, such as multi-year-cumulative moisture conditions of maximum VPD, were top predictors for start of season. Productivity measures were also associated with contextual variables such as soil characteristics and vegetation composition. Phenology is a key process that profoundly affects organism-environment relationships, spatio-temporal patterns in ecosystem structure and function, and other ecosystem dynamics. Phenology, however, is complex, and is mediated by lagged effects, interactions, and a diversity of potential drivers; nonetheless, the incorporation of antecedent conditions and contextual variables can improve models of phenology.
Dissolved organic matter (DOM) and particulate organic matter (POM) can influence biogeochemical processes in aquatic systems. An understanding, however, of the source, composition, and processes driving inland reservoir organic matter (OM) cycling at a regional scale over the long term is currently unexplored. Here, we quantify decadal patterns (> 20 yr) of DOM quantity and composition and POM in 40 reservoirs in the midcontinent United States. We built 184 Random Forest models to identify how the relative influence of watershed characteristics and limnological parameters on OM dynamics may vary over time and in synchrony with hydroclimatic anomalies. The reservoir OM quantity and composition varied nonmonotonically through time and in contrast to lake browning observed in the northern hemisphere. Reservoir DOM composition switched from humic and aromatic during wet summers to aliphatic, potentially autochthonous DOM during particularly prolonged dry summers in the mid-2000s. The shift in reservoir DOM quantity and composition could be attributed to the change in time-varying control of watershed and limnological factors mediated by the hydroclimatic conditions. Watershed control (e.g., percent crops) was predominant during wet summers, while the effect of reservoir morphology (e.g., maximum depth) and water quality parameters (e.g., Secchi depth, chlorophyll a) were evident during dry summers. Thus, future predictions of drier conditions may promote “greening” with negative implications for reservoir water quality and treated drinking water. Considering the nonlinear nature of reservoir OM dynamics and its controls will help to better mitigate water quality issues in these constructed systems increasingly impacted by global changes.
Multispecies risk assessments have developed within many international conservation programs, reflecting a widespread need for efficiency. Under the United States Endangered Species Act (ESA), multispecies assessments ultimately lead to species-level listing decisions. Although this approach provides opportunities for improved efficiency, it also risks overwhelming or biasing the assessment process and would benefit from clear guidance for practitioners. We reviewed multispecies assessments conducted between 1993 and 2019 for ESA listing decisions to identify the ecological basis for combining species, the assessment approach used, and the policy factors influencing their efficacy. We identified 42 cases covering 359 species. Most assessments (81%) included two to five species, although the maximum was 82. A common theme involved grouping narrow endemics or habitat specialists based on taxonomic relatedness, similar distributions, and common threats to persistence. All assessments included a combined threats analysis, but few employed a common species' response model or expert elicitation process. Although ESA risk assessments are distinct from policy decisions, most assessments (50%) supported decisions that all species warranted endangered status. Available guidance has generally emphasized ecological similarity as the key attribute leading to successful multispecies assessments. The challenge with consistently selecting species based on qualitative proxies such as common distributions or threats to persistence is that ecological patterns and processes are scale dependent. Focusing instead on the assessment methods and their potential for bias and increased efficiency may provide a stronger basis for developing consistent and transparent guidance.
","language":"English","publisher":"Society for Conservation Biology","doi":"10.1111/csp2.12825","usgsCitation":"Fitzgerald, D.B., Freeman, M., Maloney, K.O., Young, J.A., Rosenberger, A.E., Kazyak, D., and Smith, D.R., 2022, Multispecies approaches to status assessments in support of endangered species classifications: Conservation Science and Practice, v. 4, no. 11, e12825, 11 p., https://doi.org/10.1111/csp2.12825.","productDescription":"e12825, 11 p.","ipdsId":"IP-127956","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":446217,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/csp2.12825","text":"Publisher Index Page"},{"id":408261,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"4","issue":"11","noUsgsAuthors":false,"publicationDate":"2022-10-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Fitzgerald, Daniel Bruce 0000-0002-3254-7428","orcid":"https://orcid.org/0000-0002-3254-7428","contributorId":245718,"corporation":false,"usgs":true,"family":"Fitzgerald","given":"Daniel","email":"","middleInitial":"Bruce","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":854454,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Freeman, Mary 0000-0001-7615-6923 mcfreeman@usgs.gov","orcid":"https://orcid.org/0000-0001-7615-6923","contributorId":3528,"corporation":false,"usgs":true,"family":"Freeman","given":"Mary","email":"mcfreeman@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":854455,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Maloney, Kelly O. 0000-0003-2304-0745 kmaloney@usgs.gov","orcid":"https://orcid.org/0000-0003-2304-0745","contributorId":4636,"corporation":false,"usgs":true,"family":"Maloney","given":"Kelly","email":"kmaloney@usgs.gov","middleInitial":"O.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":854456,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Young, John A. 0000-0002-4500-3673 jyoung@usgs.gov","orcid":"https://orcid.org/0000-0002-4500-3673","contributorId":3777,"corporation":false,"usgs":true,"family":"Young","given":"John","email":"jyoung@usgs.gov","middleInitial":"A.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":854457,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rosenberger, Amanda E. 0000-0002-5520-8349 arosenberger@usgs.gov","orcid":"https://orcid.org/0000-0002-5520-8349","contributorId":5581,"corporation":false,"usgs":true,"family":"Rosenberger","given":"Amanda","email":"arosenberger@usgs.gov","middleInitial":"E.","affiliations":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":854458,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kazyak, David C. 0000-0001-9860-4045","orcid":"https://orcid.org/0000-0001-9860-4045","contributorId":202481,"corporation":false,"usgs":true,"family":"Kazyak","given":"David C.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":854459,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Smith, David R. 0000-0001-6074-9257 drsmith@usgs.gov","orcid":"https://orcid.org/0000-0001-6074-9257","contributorId":168442,"corporation":false,"usgs":true,"family":"Smith","given":"David","email":"drsmith@usgs.gov","middleInitial":"R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":854460,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ]}