Coastal marsh within Mediterranean climate zones is exposed to episodic watershed runoff and sediment loads that occur during storm events. Simulating future marsh accretion under sea level rise calls for attention to: (a) physical processes acting over the time scale of storm events and (b) biophysical processes acting over time scales longer than storm events. Using the upper Newport Bay in Southern California as a case study, we examine the influence of event-scale processes on simulated change in marsh topography by comparing: (a) a biophysical model that integrates with an annual time step and neglects event-scale processes (BP-Annual), (b) a physical model that resolves event-scale processes but neglects biophysical interactions (P-Event), and (c) a biophysical model that resolves event-scale physical processes and biophysical processes at annual and longer time scales (BP-Event). A calibrated BP-Event model shows that large (>20-year return period) episodic storm events are major drivers of marsh accretion, depositing up to 30 cm of sediment in one event. Greater deposition is predicted near fluvial sources and tidal channels and less on marshes further from fluvial sources and tidal channels. In contrast, the BP-Annual model poorly resolves spatial structure in marsh accretion as a consequence of neglecting event-scale processes. Furthermore, the P-Event model significantly overestimates marsh accretion as a consequence of neglecting marsh surface compaction driven by annual scale biophysical processes. Differences between BP-Event and BP-Annual models translate up to 20 cm per century in marsh surface elevation.
On the evening of 15 January 2022, the Hunga Tonga-Hunga Ha’apai volcano1 unleashed a violent underwater eruption, blanketing the surrounding land masses in ash and debris. The eruption generated tsunamis observed around the world. An event of this type last occurred in 1883 during the eruption of Krakatau, and thus we have the first observations of a tsunami from a large emergent volcanic eruption captured with modern instrumentation. Here we show that the explosive eruption generated waves through multiple mechanisms, including: (1) air–sea coupling with the initial and powerful shock wave radiating out from the explosion in the immediate vicinity of the eruption; (2) collapse of the water cavity created by the underwater explosion; and (3) air–sea coupling with the air-pressure pulse that circled the Earth several times, leading to a global tsunami. In the near field, tsunami impacts are strongly controlled by the water-cavity source whereas the far-field tsunami, which was unusually persistent, can be largely described by the air-pressure pulse mechanism. Catastrophic damage in some harbours in the far field was averted by just tens of centimetres, implying that a modest sea level rise combined with a future, similar event would lead to a step-function increase in impacts on infrastructure. Piecing together the complexity of this event has broad implications for coastal hazards in similar geophysical settings, suggesting a currently neglected source of global tsunamis.
Livestock predation can pose socio-economic impacts on rural livelihoods and is the main cause of retaliatory killings of carnivores in many countries. Therefore, appropriate interventions to reduce livestock predation, lower conflict and promote coexistence are needed. Livestock guarding dogs have been traditionally used to reduce predation, yet details regarding the use of dogs, especially the number of dogs per herd effectively required, are rarely studied. In this study, we assessed how the number and presence of guarding dogs in a herd can reduce livestock losses to leopard and wolf in corrals at night and on grazing grounds in day-time. Using systematic interview surveys (2016-2019), we documented sheep/goat losses per attack (predation rates) from 139 shepherds across 32 villages around Golestan National Park, Iran. We analysed the effects of the number of dogs, presence of dogs, presence of shepherds, seasons, corral quality, livestock number, dog size, distance to villages and distance to reserve on predation rates using generalized linear models. For the leopard model, dog presence significantly decreased (β = –1.80, 95% confidence interval –2.61 to –0.81) predation rates during day-time to 1.41 individuals per attack. For wolf attacks in corrals at night, predation rates significantly decreased (β = –0.29, –0.54 to –0.04) with increasing dog numbers. Also, shepherd presence (β = –0.56, –1.10 to –0.10) and herd size (β = –0.36, –0.60 to –0.12) significantly reduced predation rates. In the wolf day-time model, shepherd presence significantly decreased (β = –0.93, –1.74 to –0.10) predation rates. Our study suggests that (1) using dogs can reduce, but not eliminate, predation by leopards during day-time; (2) with every additional dog, predation rates by wolves in corrals at night are likely to decrease on average by 25.2%; and (3) the presence of shepherds in corrals at night and during day-time can reduce predation rates.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.baae.2022.08.001","usgsCitation":"Soofi, M., Soufi, M., Royle, A., Waltert, M., and Khorozyan, I., 2022, Numbers and presence of guarding dogs affect wolf and leopard predation on livestock in northeastern Iran: Basic and Applied Ecology, v. 64, p. 147-156, https://doi.org/10.1016/j.baae.2022.08.001.","productDescription":"10 p.","startPage":"147","endPage":"156","ipdsId":"IP-136891","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":446872,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.baae.2022.08.001","text":"Publisher Index Page"},{"id":408278,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Iran","otherGeospatial":"Azizabad No-Hunting Area, Golestan National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 55.52490234375,\n 37.18876668723709\n ],\n [\n 56.34063720703125,\n 37.18876668723709\n ],\n [\n 56.34063720703125,\n 37.694687703235914\n ],\n [\n 55.52490234375,\n 37.694687703235914\n ],\n [\n 55.52490234375,\n 37.18876668723709\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"64","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Soofi, Mahmood","contributorId":297883,"corporation":false,"usgs":false,"family":"Soofi","given":"Mahmood","email":"","affiliations":[{"id":64430,"text":"Department of Conservation Biology, University of Goettingen,","active":true,"usgs":false}],"preferred":false,"id":854546,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Soufi, Mobin","contributorId":297884,"corporation":false,"usgs":false,"family":"Soufi","given":"Mobin","email":"","affiliations":[{"id":64431,"text":"Department of the Environment, Faculty of Fishery and Environment, Gorgan University of Agriculture and Natural Resources, Gorgan, Iran","active":true,"usgs":false}],"preferred":false,"id":854547,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":146229,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","email":"aroyle@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":854548,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Waltert, Matthias","contributorId":297885,"corporation":false,"usgs":false,"family":"Waltert","given":"Matthias","email":"","affiliations":[{"id":62110,"text":"Department of Conservation Biology, University of Goettingen","active":true,"usgs":false}],"preferred":false,"id":854549,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Khorozyan, Igor","contributorId":297886,"corporation":false,"usgs":false,"family":"Khorozyan","given":"Igor","email":"","affiliations":[{"id":62110,"text":"Department of Conservation Biology, University of Goettingen","active":true,"usgs":false}],"preferred":false,"id":854550,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70243220,"text":"70243220 - 2022 - New projections of 21st century climate and hydrology for Alaska and Hawaiʻi","interactions":[],"lastModifiedDate":"2023-05-04T11:52:28.55815","indexId":"70243220","displayToPublicDate":"2022-08-07T06:50:07","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5567,"text":"Climate Services","active":true,"publicationSubtype":{"id":10}},"title":"New projections of 21st century climate and hydrology for Alaska and Hawaiʻi","docAbstract":"In the United States, high-resolution, century-long, hydroclimate projection datasets have been developed for water resources planning, focusing on the contiguous United States (CONUS) domain. However, there are few statewide hydroclimate projection datasets available for Alaska and Hawaiʻi. The limited information on hydroclimatic change motivates developing hydrologic scenarios from 1950 to 2099 using climate-hydrology impact modeling chains consisting of multiple statistically downscaled climate projections as input to hydrologic model simulations for both states. We adopt an approach similar to the previous CONUS hydrologic assessments where: 1) we select the outputs from ten global climate models (GCM) from the Coupled Model Intercomparison Project Phase 5 with Representative Concentration Pathways 4.5 and 8.5; 2) we perform statistical downscaling to generate climate input data for hydrologic models (12-km grid-spacing for Alaska and 1-km for Hawaiʻi); and 3) we perform process-based hydrologic model simulations. For Alaska, we have advanced the hydrologic model configuration from CONUS by using the full water-energy balance computation, frozen soils and a simple glacier model. The simulations show that robust warming and increases in precipitation produce runoff increases for most of Alaska, with runoff reductions in the currently glacierized areas in Southeast Alaska. For Hawaiʻi, we produce the projections at high resolution (1 km) which highlight high spatial variability of climate variables across the state, and a large spread of runoff across the GCMs is driven by a large precipitation spread across the GCMs. Our new ensemble datasets assist with state-wide climate adaptation and other water planning.
Root hemiparasitic plants both compete with and extract resources from host plants. By reducing the abundance of dominant plants and releasing subordinates from competitive exclusion, they can have an outsized impact on plant communities. Most research on the ecological role of hemiparasites is manipulative and focuses on a small number of hemiparasitic taxa. Here, we ask whether patterns in natural plant communities match the expectation that hemiparasites affect the structure of plant communities. Our data were collected on 129 national park units spanning the continental United States. The most common hemiparasite genera were Pedicularis, Castilleja, Krameria, and Comandra. We used null models and linear mixed models to determine whether hemiparasites were associated with changes in community richness and evenness. Hemiparasite presence did not affect community metrics. Hemiparasite abundance was positively associated with increasing evenness of herbaceous species, but not with species richness. The associations that we observed on a continental scale are consistent with evidence that the impacts of root hemiparasitic plants on evenness can be substantial and abundance dependent but that effects on richness are less pronounced. Hemiparasites mediate competitive exclusion in communities to facilitate species coexistence and merit consideration of inclusion in ecological theories of coexistence.
Surface and subsurface moored buoy, ship-based, remotely sensed, and reanalysis datasets are used to investigate thermal variability of northern Gulf of Alaska (NGA) nearshore, coastal, and offshore waters over synoptic to century-long time scales. NGA sea surface temperature (SST) showed a larger positive trend of 0.22 ± 0.10 °C per decade over 1970–2021 compared to 0.10 ± 0.03 °C per decade over 1900–2021. Over synoptic time scales, SST covariance between two stations is small (<10%) when separation exceeds 100 km, while stations separated by 500 km retain 50% of their co-variability for seasonal and longer fluctuations. Relative to in situ sensor data, remotely sensed SST data has limited accuracy in some NGA settings, capturing 60–70% of the daily SST anomaly in coastal and offshore waters, but often <25% nearshore. North Pacific and NGA leading modes of SST variability leave 25–50% of monthly variance unresolved. Analysis of the 2014–2016 Pacific marine heatwave shows that NGA coastal surface temperatures warmed contemporaneously with offshore waters through 2013, but deep inner shelf waters (200–250 m) exhibited delayed warming. Offshore surface waters cooled from 2014 to 2016, while shelf waters continued to warm from the combined effects of local air-sea and advective heat fluxes. We find that annually averaged Sitka air temperature is a leading predictor (r2 = 0.37, p < 0.05) for following-year NGA coastal water column temperature. Our results can inform future environmental monitoring designs, assist forward-looking projections of marine conditions, and show the importance of in situ measurements for nearshore studies that require knowledge of thermal conditions over time scales of days and weeks.
Knowledge graphs are a form of database representation and handling that show the potential to better meet the challenges of data interoperability, semi-automated information reasoning, and information retrieval. Geospatial knowledge graphs (GKG) have at their core specialized forms of applied ontology that provide coherent spatial context to a domain of information including non-spatial attributes. This paper discusses research toward the development of a prototype GKG based on national topographic databases of geospatial feature instances, attributes, properties, metadata, and annotations. The challenges are to capture and represent geographic semantics inherent in the source data, to align such graph models with standards where possible, to test logical computations, and to visualize the data using a cartographic user interface. Data integration from outside sources was tested through SPARQL and GeoSPARQL queries. Called the MapKB, the approaches applied in this prototype use a number of software components to build a system architecture aligned with those objectives and are composed entirely of free and open-source software. The system and ontology design were validated through reasoning and competency questions. Technical aspects of the prototype software succeeded, but customization was found to be needed for user-based design.
","language":"English","publisher":"International Society of Photogrammetry and Remote Sensing","doi":"10.5194/isprs-archives-XLVIII-4-W1-2022-511-2022","usgsCitation":"Varanka, D.E., 2022, A geospatial knowledge graph prototype for national topographic mapping: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, v. XLVIII-4/W1-2022, p. 511-516, https://doi.org/10.5194/isprs-archives-XLVIII-4-W1-2022-511-2022.","productDescription":"6 p.","startPage":"511","endPage":"516","ipdsId":"IP-120273","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":446887,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/isprs-archives-xlviii-4-w1-2022-511-2022","text":"Publisher Index Page"},{"id":411719,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"XLVIII-4/W1-2022","noUsgsAuthors":false,"publicationDate":"2022-08-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Varanka, Dalia E. 0000-0003-2857-9600 dvaranka@usgs.gov","orcid":"https://orcid.org/0000-0003-2857-9600","contributorId":1296,"corporation":false,"usgs":true,"family":"Varanka","given":"Dalia","email":"dvaranka@usgs.gov","middleInitial":"E.","affiliations":[{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true},{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":861370,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70233932,"text":"70233932 - 2022 - Trends analysis of Rangeland Condition Monitoring Assessment and Projection (RCMAP) fractional component time series (1985–2020)","interactions":[],"lastModifiedDate":"2024-01-19T15:18:40.15331","indexId":"70233932","displayToPublicDate":"2022-08-05T11:36:29","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":8118,"text":"GIScience & Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Trends analysis of Rangeland Condition Monitoring Assessment and Projection (RCMAP) fractional component time series (1985–2020)","docAbstract":"Rangelands have a dynamic response to climate change, fire, and other anthropogenic disturbances. The Rangeland Condition, Monitoring, Assessment, and Projection (RCMAP) product aims to capture this response by quantifying the percent cover of eight rangeland components, associated error, and trends across the western United States using Landsat from 1985 to 2020. The current generation of RCMAP has been improved with more training data, regional-scale Landsat composites, and more robust change detection. We assess the temporal patterns in each component with a linear model and a structural change method that determines break points using an 8-year temporal moving window. The linear and structural change methods generally agreed on patterns of change, but the latter found breaks more often, with at least one break point in most pixels. The structural change model provides more robust statistics on the significant minority of pixels with non-monotonic trends, while detrending some interannual signal potentially superfluous from a long-term perspective. Although break point density within one year of fire and vegetation treatments was ~10× and ~4× that of unburned areas, respectively, break point detection in the correct year of fire was only moderately accurate. Climate responses in break points proved more robust, with strong spatiotemporal relation in break point density with both aridity index values and aridity index change. Break point density strongly responds to both increased and decreased aridity and is reflective of ecosystem resilience. Data provide spatiotemporal information on the occurrence of breaks, but even more importantly, attribute those change events to specific component(s).
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/15481603.2022.2104786","usgsCitation":"Shi, H., Rigge, M.B., Postma, K., and Bunde, B., 2022, Trends analysis of Rangeland Condition Monitoring Assessment and Projection (RCMAP) fractional component time series (1985–2020): GIScience & Remote Sensing, v. 59, no. 1, p. 1243-1265, https://doi.org/10.1080/15481603.2022.2104786.","productDescription":"23 p.","startPage":"1243","endPage":"1265","ipdsId":"IP-135462","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":446897,"rank":4,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/15481603.2022.2104786","text":"Publisher Index Page"},{"id":424623,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9SJXUI1","text":"USGS data release","linkFileType":{"id":5,"text":"html"},"linkHelpText":"Rangeland Condition Monitoring Assessment 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Center","active":true,"usgs":true}],"preferred":true,"id":847707,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Postma, Kory 0000-0001-8058-498X","orcid":"https://orcid.org/0000-0001-8058-498X","contributorId":293879,"corporation":false,"usgs":false,"family":"Postma","given":"Kory","affiliations":[{"id":63548,"text":"KBRwyle, under contract to USGS","active":true,"usgs":false}],"preferred":false,"id":847708,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bunde, Brett 0000-0003-0228-779X","orcid":"https://orcid.org/0000-0003-0228-779X","contributorId":288364,"corporation":false,"usgs":false,"family":"Bunde","given":"Brett","affiliations":[{"id":61731,"text":"KBR","active":true,"usgs":false}],"preferred":false,"id":847709,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70234246,"text":"70234246 - 2022 - Bedrock depth influences spatial patterns of summer baseflow, temperature and flow disconnection for mountainous headwater streams","interactions":[],"lastModifiedDate":"2022-08-05T13:15:34.056536","indexId":"70234246","displayToPublicDate":"2022-08-05T08:08:29","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1928,"text":"Hydrology and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Bedrock depth influences spatial patterns of summer baseflow, temperature and flow disconnection for mountainous headwater streams","docAbstract":"In mountain headwater streams, the quality and resilience of summer cold-water habitat is generally regulated by stream discharge, longitudinal stream channel connectivity and groundwater exchange. These critical hydrologic processes are thought to be influenced by the stream corridor bedrock contact depth (sediment thickness), a parameter often inferred from sparse hillslope borehole information, piezometer refusal and remotely sensed data. To investigate how local bedrock depth might control summer stream temperature and channel disconnection (dewatering) patterns, we measured stream corridor bedrock depth by collecting and interpreting 191 passive seismic datasets along eight headwater streams in Shenandoah National Park (Virginia, USA). In addition, we used multi-year stream temperature and streamflow records to calculate several baseflow-related metrics along and among the study streams. Finally, comprehensive visual surveys of stream channel dewatering were conducted in 2016, 2019 and 2021 during summer low flow conditions (124 total km of stream length). We found that measured bedrock depths along the study streams were not well-characterized by soils maps or an existing global-scale geologic dataset where the latter overpredicted measured depths by 12.2 m (mean) or approximately four times the average bedrock depth of 2.9 m. Half of the eight study stream corridors had an average bedrock depth of less than 2 m. Of the eight study streams, Staunton River had the deepest average bedrock depth (3.4 m), the coldest summer temperature profiles and substantially higher summer baseflow indices compared to the other study steams. Staunton River also exhibited paired air and water annual temperature signals suggesting deeper groundwater influence, and the stream channel did not dewater in lower sections during any baseflow survey. In contrast, Paine Run and Piney River did show pronounced, patchy channel dewatering, with Paine Run having dozens of discrete dry channel sections ranging from 1 to greater than 300 m in length. Stream dewatering patterns were apparently influenced by a combination of discrete deep bedrock (20+ m) features and more subtle sediment thickness variation (1–4 m) depending on local stream valley hydrogeology. In combination, these unique datasets show the first large-scale empirical support for existing conceptual models of headwater stream disconnection based on spatially variable underflow capacity and shallow groundwater supply.","language":"English","publisher":"Copernicus","doi":"10.5194/hess-26-3989-2022","usgsCitation":"Briggs, M., Goodling, P.J., Johnson, Z., Rogers, K., Hitt, N.P., Fair, J.H., and Snyder, C.D., 2022, Bedrock depth influences spatial patterns of summer baseflow, temperature and flow disconnection for mountainous headwater streams: Hydrology and Earth System Sciences, v. 26, no. 15, p. 3989-4011, https://doi.org/10.5194/hess-26-3989-2022.","productDescription":"23 p.","startPage":"3989","endPage":"4011","ipdsId":"IP-132407","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":446904,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/hess-26-3989-2022","text":"Publisher Index Page"},{"id":404871,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","otherGeospatial":"Blue Ridge Mountains, Shenandoah National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.85711669921875,\n 38.098901948321256\n ],\n [\n -78.8433837890625,\n 38.039438891821746\n ],\n [\n -78.71978759765625,\n 38.090255780611486\n ],\n [\n -78.69369506835938,\n 38.182068998322094\n ],\n [\n -78.64151000976562,\n 38.19718009396176\n ],\n [\n -78.60580444335938,\n 38.26945406815749\n ],\n [\n -78.50830078125,\n 38.312568460056966\n ],\n [\n -78.38333129882812,\n 38.33734763569314\n ],\n [\n -78.33663940429688,\n 38.43745529233546\n ],\n [\n -78.26385498046875,\n 38.53957267203905\n ],\n [\n -78.233642578125,\n 38.65119833229951\n ],\n [\n -78.2281494140625,\n 38.716590286734494\n ],\n [\n -78.1402587890625,\n 38.74551518488265\n ],\n [\n -78.13888549804686,\n 38.8407772667165\n ],\n [\n -78.15536499023438,\n 38.89423942194029\n ],\n [\n -78.2061767578125,\n 38.93698019310818\n ],\n [\n -78.23089599609375,\n 38.872859384572244\n ],\n [\n -78.22128295898438,\n 38.81296105899589\n ],\n [\n -78.25698852539062,\n 38.79476766282312\n ],\n [\n -78.26522827148438,\n 38.8225909761771\n ],\n [\n -78.31878662109375,\n 38.82901019751963\n ],\n [\n -78.34625244140625,\n 38.810820900566135\n ],\n [\n -78.41354370117188,\n 38.71980474264237\n ],\n [\n -78.40667724609375,\n 38.63081814300356\n ],\n [\n -78.49868774414062,\n 38.5213096674994\n ],\n [\n -78.59619140625,\n 38.541720956040386\n ],\n [\n -78.55636596679688,\n 38.43960662292255\n ],\n [\n -78.6181640625,\n 38.40302528453207\n ],\n [\n -78.82278442382812,\n 38.25543637637947\n ],\n [\n -78.85711669921875,\n 38.098901948321256\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"26","issue":"15","noUsgsAuthors":false,"publicationDate":"2022-08-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Briggs, Martin A. 0000-0003-3206-4132","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":222756,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - 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2022 - Understory plant communities show resistance to drought, hurricanes, and experimental warming in a wet tropical forest","interactions":[],"lastModifiedDate":"2022-08-04T14:33:52.831258","indexId":"70234236","displayToPublicDate":"2022-08-04T09:23:52","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5860,"text":"Frontiers in Forests and Global Change","active":true,"publicationSubtype":{"id":10}},"title":"Understory plant communities show resistance to drought, hurricanes, and experimental warming in a wet tropical forest","docAbstract":"Global climate change has led to rising temperatures and to more frequent and intense climatic events, such as storms and droughts. Changes in climate and disturbance regimes can have non-additive effects on plant communities and result in complicated legacies we have yet to understand. This is especially true for tropical forests, which play a significant role in regulating global climate. We used understory vegetation data from the Tropical Responses to Altered Climate Experiment (TRACE) in Puerto Rico to evaluate how plant communities responded to climate warming and disturbance. The TRACE understory vegetation was exposed to a severe drought (2015), 2 years of experimental warming (4°C above ambient in half of the plots, 2016–2017 and 2018–2019), and two major hurricanes (Irma and María, September 2017). Woody seedlings and saplings were censused yearly from 2015 to 2019, with an additional census in 2015 after the drought ended. We evaluated disturbance-driven changes in species richness, diversity, and composition across ontogeny. We then used Bayesian predictive trait modeling to assess how species responded to disturbance and how this might influence the functional structure of the plant community. Our results show decreased seedling richness after hurricane disturbance, as well as increased sapling richness and diversity after warming. We found a shift in species composition through time for both seedlings and saplings, yet the individual effects of each disturbance were not significant. At both ontogenetic stages, we observed about twice as many species responding to experimental warming as those responding to drought and hurricanes. Predicted changes in functional structure point to disturbance-driven functional shifts toward a mixture of fast-growing and drought-tolerant species. Our findings demonstrate that the tropical forest understory community is more resistant to climatic stressors than expected, especially at the sapling stage. However, early signs of changes in species composition suggest that, in a warming climate with frequent droughts and hurricanes, plant communities might shift over time toward fast-growing or drought-tolerant species.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/ffgc.2022.733967","usgsCitation":"Alonso-Rodriguez, A.M., Wood, T.E., Torres-Diaz, J., Cavaleri, M.A., Reed, S., and Bachelot, B., 2022, Understory plant communities show resistance to drought, hurricanes, and experimental warming in a wet tropical forest: Frontiers in Forests and Global Change, v. 5, 733967, 16 p., https://doi.org/10.3389/ffgc.2022.733967.","productDescription":"733967, 16 p.","ipdsId":"IP-133340","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":446918,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/ffgc.2022.733967","text":"Publisher Index Page"},{"id":404824,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Puerto Rico","otherGeospatial":"Bosque experimental de Luquillo, Luquillo Experimental Forest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -65.8681869506836,\n 18.240764185529784\n ],\n [\n -65.70304870605469,\n 18.240764185529784\n ],\n [\n -65.70304870605469,\n 18.34800827349917\n ],\n [\n -65.8681869506836,\n 18.34800827349917\n ],\n [\n -65.8681869506836,\n 18.240764185529784\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"5","noUsgsAuthors":false,"publicationDate":"2022-07-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Alonso-Rodriguez, Aura M.","contributorId":206281,"corporation":false,"usgs":false,"family":"Alonso-Rodriguez","given":"Aura","email":"","middleInitial":"M.","affiliations":[{"id":37300,"text":"International Institute of Tropical Forestry, USDA Forest Service, Sabana Field Research Station, Luquillo, Puerto Rico","active":true,"usgs":false}],"preferred":false,"id":848288,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wood, Tana E.","contributorId":33193,"corporation":false,"usgs":true,"family":"Wood","given":"Tana","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":848289,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Torres-Diaz, Jamarys","contributorId":294541,"corporation":false,"usgs":false,"family":"Torres-Diaz","given":"Jamarys","email":"","affiliations":[{"id":63595,"text":"USDA Forest Service International Institute of Tropical Forestry, Jardín Botánico Sur, Río Piedras, Puerto Rico","active":true,"usgs":false}],"preferred":false,"id":848290,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cavaleri, Molly A.","contributorId":206282,"corporation":false,"usgs":false,"family":"Cavaleri","given":"Molly","email":"","middleInitial":"A.","affiliations":[{"id":34284,"text":"School of Forest Resources and Environmental Science, Michigan Technological University","active":true,"usgs":false}],"preferred":false,"id":848291,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reed, Sasha C. 0000-0002-8597-8619","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":205372,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":848292,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bachelot, Benedicte","contributorId":294542,"corporation":false,"usgs":false,"family":"Bachelot","given":"Benedicte","email":"","affiliations":[{"id":63597,"text":"Department of Plant Biology, Ecology, and Evolution, Oklahoma State University, Stillwater, OK, USA","active":true,"usgs":false}],"preferred":false,"id":848293,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70234229,"text":"70234229 - 2022 - A comprehensive assessment of mangrove species and carbon stock on Pohnpei, Micronesia","interactions":[],"lastModifiedDate":"2023-04-14T17:00:52.620563","indexId":"70234229","displayToPublicDate":"2022-08-04T09:07:39","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"A comprehensive assessment of mangrove species and carbon stock on Pohnpei, Micronesia","docAbstract":"Mangrove forests are the most important ecosystems on Pohnpei Island, Federated States of Micronesia, as the island communities of the central Pacific rely on the forests for many essential services including protection from sea-level rise that is occurring at a greater pace than the global average. As part of a multi-component assessment to evaluate vulnerabilities of mangrove forests on Pohnpei, mangrove forests were mapped at two points in time: 1983 and 2018. In 2018, the island had 6,426 ha of mangrove forest. Change analysis indicated a slight (0.76%) increase of mangrove area between 1983 and 2018, contrasting with global mangrove area declines. Forest structure and aboveground carbon (AGC) stocks were inventoried using a systematic sampling of field survey plots and extrapolated to the island using k-nearest neighbor and random forest species models. A gridded or wall to wall approach is suggested when possible for defining carbon stocks of a large area due to high variability seen in our data. The k-nearest neighbor model performed better than random forest models to map species dominance in these forests. Mean AGC was 167 ± 11 MgC ha-1, which is greater than the global average of mangroves (115 ± 7 MgC ha-1) but within their global range (37–255 MgC ha-1) Kauffman et al. (2020). In 2018, Pohnpei mangroves contained over 1.07 million MgC in AGC pools. By assigning the mean AGC stock per species per area to the map, carbon stock distributions were visualized spatially, allowing future conservation efforts to be directed to carbon dense stands.
","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0271589","usgsCitation":"Woltz, V., Peneva-Reed, E., Zhu, Z., Bullock, E.L., MacKenzie, R.A., Apwong, M., Krauss, K., and Gesch, D.B., 2022, A comprehensive assessment of mangrove species and carbon stock on Pohnpei, Micronesia: PLoS ONE, v. 17, no. 7, e0271589, 19 p.; Data Release, https://doi.org/10.1371/journal.pone.0271589.","productDescription":"e0271589, 19 p.; Data Release","ipdsId":"IP-120770","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":5055,"text":"Land Change Science","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":446921,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0271589","text":"Publisher Index 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,{"id":70234233,"text":"70234233 - 2022 - Reestablishing a foundational species: limitations on post-wildfire sagebrush seedling establishment","interactions":[],"lastModifiedDate":"2022-08-04T13:30:49.237075","indexId":"70234233","displayToPublicDate":"2022-08-04T08:22:35","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Reestablishing a foundational species: limitations on post-wildfire sagebrush seedling establishment","docAbstract":"Improving post-wildfire restoration of foundational plant species is crucial for conserving imperiled ecosystems. We sought to better understand the initial establishment of sagebrush (Artemisia sp.), a foundational shrubland species over a vast area of western North America, in the first 1–2 years post-wildfire, a critical time period for population recovery. Field data from 460 sagebrush populations sampled across the Great Basin revealed several patterns. Sagebrush seedlings were uncommon in the first 1–2 years after fire, with none detected in 69% of plots, largely because most fires occurred in areas of low resistance to invasive species and resilience to disturbance (hereafter, R&R). Post-fire aerial seeding of sagebrush dramatically increased seedling occupancy, especially in low R&R areas, which exhibited a 3.4-fold increase in occupancy over similar unseeded locations. However, occupancy models and repeat surveys suggested exceptionally high mortality, as occupancy rates declined by as much as 50% between the first and second years after fire. We found the prevalence of “fertile island” microsites (patches beneath fire-consumed sagebrush) to be the best predictor of seedling occupancy, followed by aerial seeding status, native perennial grass cover, and years since fire. In populations where no sagebrush seeding occurred, seedlings were most likely to occur in locations with a combination of high fertile island microsite cover and close proximity to a remnant sagebrush plant. These important attributes were only present in 13% of post-fire locations, making them rare across the Great Basin. Finally, in the absence of fertile islands and remnant plants, seedling establishment was not observed in any unseeded areas, and rarely in seeded locations. Thus, local extirpation of sagebrush could have important, long-term implications for sagebrush reestablishment following future fires if there are no mature individuals to leave behind fertile islands or serve as remnant individuals. These findings highlight the importance of landscape legacy effects and could help guide where and how big sagebrush restoration is conducted in the future.
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Officials experimentally translocated 14 adult female American black bears (Ursus americanus) from Great Smoky Mountains National Park, North Carolina and Tennessee, USA, to Big South Fork National River and Recreation Area in the Cumberland Plateau of Kentucky and Tennessee, USA, in 1996–1997. Since that time, the reintroduced bear population has continued to expand in size and range so our study objective was to use spatially explicit capture-recapture methods across a wide spatial extent to estimate bear population abundance and growth. We constructed 440 (223 in KY, 217 in TN) hair traps in our primary sampling area in 2019 arranged in clusters of 4–9 traps/cluster, which we augmented with data from 138 hair traps in a secondary sampling area in Tennessee collected in 2018. We extracted and genotyped DNA from hair samples to construct spatially explicit capture histories, using spatial covariates to model inhomogeneous densities. Population abundance estimates across our 36,035-km2 study area were 411 males and 406 females excluding cubs. Based on an initial standing population of 18 adult and subadult bears, the mean annual growth rate (λ) from 1998 to 2019 was 1.199. The mean annual harvest rate in Kentucky from 2013 to 2019 was 5.1% and in Tennessee from 2014 to 2019 was 13.2%. Based on simulations, the hunting seasons reduced mean λ from 1.217 to 1.199, but growth was rapid despite harvest. Genetic diversity was retained, with similar expected heterozygosity as in the source population. The lack of conspecifics, highly productive habitat, and an initial age and sex distribution that was skewed toward the most fecund members of the population likely contributed to the rapid growth and high levels of gene retention in this bear population.
Several mechanisms have been proposed to allow highly viscous silicic magma to outgas efficiently enough to erupt effusively. There is increasing evidence that challenges the classic foam-collapse model in which gas escapes through permeable bubble networks, and instead suggests that magmatic fracturing and/or accompanying localized fragmentation and welding within the conduit play an important role in outgassing. The 2011–2012 eruption at Cordón Caulle volcano, Chile, provides direct observations of the role of magmatic fractures. This eruption exhibited a months-long hybrid phase, in which rhyolitic lava extrusion was accompanied by vigorous gas-and-tephra venting through fractures in the lava dome surface. Some of these fractures were preserved as tuffisites (tephra-filled veins) in erupted lava and bombs. We integrate constraints from petrologic analyses of erupted products and video analyses of gas-and-tephra venting to construct a model for magma ascent in a conduit. The one-dimensional, two-phase, steady-state model considers outgassing through deforming permeable bubble networks, magmatic fractures, and adjacent wall rock. Simulations for a range of plausible magma ascent conditions indicate that the eruption of low-porosity lava observed at Cordón Caulle volcano occurs because of significant gas flux through fracture networks in the upper conduit. This modeling emphasizes the important role that outgassing through magmatic fractures plays in sustaining effusive or hybrid eruptions of silicic magma and in facilitating explosive-effusive transitions.
The U.S. Geological Survey (USGS) National Earthquake Information Center (NEIC) routinely produces finite‐fault models following significant earthquakes. These models are spatiotemporal estimates of coseismic slip critical to constraining downstream response products such as ShakeMap ground motion estimates, Prompt Assessment of Global Earthquake for Response loss estimates, and ground failure assessments. Because large earthquakes can involve slip over tens to hundreds of kilometers, point‐source approximations are insufficient, and it is vital to rapidly assess the amount, timing, and location of slip along the fault. Initially, the USGS finite‐fault products were computed in the first several hours after a significant earthquake, using teleseismic body wave and surface wave observations. With only teleseismic waveforms, it is generally possible to obtain a reliable model for earthquakes of magnitude 7 and larger. Here, we detail newly implemented updates to NEIC’s modeling capabilities, specifically to allow joint modeling of local‐to‐regional strong‐motion accelerometer, Global Navigation Satellite System (GNSS), and Interferometric Synthetic Aperture Radar (InSAR) observations in addition to teleseismic waveforms. We present joint inversion results for the 2015
Fire is an integral component of ecosystems globally and a tool that humans have harnessed for millennia. Altered fire regimes are a fundamental cause and consequence of global change, impacting people and the biophysical systems on which they depend. As part of the newly emerging Anthropocene, marked by human-caused climate change and radical changes to ecosystems, fire danger is increasing, and fires are having increasingly devastating impacts on human health, infrastructure, and ecosystem services. Increasing fire danger is a vexing problem that requires deep transdisciplinary, trans-sector, and inclusive partnerships to address. Here, we outline barriers and opportunities in the next generation of fire science and provide guidance for investment in future research. We synthesize insights needed to better address the long-standing challenges of innovation across disciplines to (i) promote coordinated research efforts; (ii) embrace different ways of knowing and knowledge generation; (iii) promote exploration of fundamental science; (iv) capitalize on the “firehose” of data for societal benefit; and (v) integrate human and natural systems into models across multiple scales. Fire science is thus at a critical transitional moment. We need to shift from observation and modeled representations of varying components of climate, people, vegetation, and fire to more integrative and predictive approaches that support pathways toward mitigating and adapting to our increasingly flammable world, including the utilization of fire for human safety and benefit. Only through overcoming institutional silos and accessing knowledge across diverse communities can we effectively undertake research that improves outcomes in our more fiery future.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/pnasnexus/pgac115","usgsCitation":"Shuman, J.K., Balch, J.K., Barnes, R.T., Higuera, P., Roos, C.I., Schwilk, D.W., Stavros, E.N., Banerjee, T., Bela, M., Bendix, J., Bertolino, S., Bililign, S., Bladon, K.D., Brando, P., Breidenthal, R.E., Buma, B., Calhoun, D., Carvalho, L.M., Cattau, M., Cawley, K.M., Chandra, S., Chipman, M.L., Cobian, J., Conlisk, E., Coop, J., Cullen, A., Davis, K., Dayalu, A., Dolman, M., Ellsworth, L.M., Franklin, S., Guiterman, C., Hamilton, M., Hanan, E.J., Hansen, W.D., Hantson, S., Harvey, B., Holz, A., Hurteau, M., Ilangakoon, N.T., Jennings, M., Jones, C., Klimaszewski-Patterson, A., Kobziar, L., Kominoski, J., Kosovic, B., Krawchuk, M., Laris, P., Leonard, J., Loria- Salazar, S.M., Lucash, M., Mahmoud, H., Margolis, E.Q., Maxwell, T., McCarty, J., McWethy, D.B., Meyer, R., Miesel, J.R., Moser, W., Nagy, R.C., Niyogi, D., Palmer, H.M., Pellegrini, A., Poulter, B., Robertson, K., Rocha, A., Sadegh, M., De Sales, F., Santos, F., Scordo, F., Sexton, J., Sharma, A., Smith, A., Soja, A., Still, C., Swetnam, T., Syphard, A., Tingey, M.W., Tohidi, A., Trugman, A., Turetsky, M., Varner, J., Wang, Y., Whitman, T., Yelenik, S., and Zhang, X., 2022, Reimagine fire science for the anthropocene: PNAS Nexus, v. 1, no. 3, pgac115, 14 p., https://doi.org/10.1093/pnasnexus/pgac115.","productDescription":"pgac115, 14 p.","ipdsId":"IP-139388","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":446940,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1093/pnasnexus/pgac115","text":"External Repository"},{"id":408571,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"1","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-08-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Shuman, Jacquelyn K.","contributorId":298194,"corporation":false,"usgs":false,"family":"Shuman","given":"Jacquelyn","email":"","middleInitial":"K.","affiliations":[{"id":6648,"text":"National Center for Atmospheric Research","active":true,"usgs":false}],"preferred":false,"id":855248,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Balch, Jennifer K.","contributorId":298195,"corporation":false,"usgs":false,"family":"Balch","given":"Jennifer","email":"","middleInitial":"K.","affiliations":[{"id":13693,"text":"University of Colorado Boulder","active":true,"usgs":false}],"preferred":false,"id":855249,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barnes, Rebecca T.","contributorId":298197,"corporation":false,"usgs":false,"family":"Barnes","given":"Rebecca","email":"","middleInitial":"T.","affiliations":[{"id":37163,"text":"Colorado College","active":true,"usgs":false}],"preferred":false,"id":855250,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Higuera, Philip E.","contributorId":298199,"corporation":false,"usgs":false,"family":"Higuera","given":"Philip E.","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":855251,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Roos, Christopher I.","contributorId":298201,"corporation":false,"usgs":false,"family":"Roos","given":"Christopher","email":"","middleInitial":"I.","affiliations":[{"id":20300,"text":"Southern Methodist University","active":true,"usgs":false}],"preferred":false,"id":855252,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schwilk, Dylan W.","contributorId":298203,"corporation":false,"usgs":false,"family":"Schwilk","given":"Dylan","email":"","middleInitial":"W.","affiliations":[{"id":36331,"text":"Texas Tech University","active":true,"usgs":false}],"preferred":false,"id":855253,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stavros, E. 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In the last decades, the ACP landscape experienced extreme climate events and increased lake water withdrawal (LWW) for construction of infrastructure related to resource extraction (primarily ice roads and industrial operations). However, their potential (combined) effects on streamflow are relatively underexplored. Here, we applied the process-based, spatially distributed hydrological and thermal Water Balance Simulation Model (WaSiM) (10 m spatial resolution) to the 30 km² Crea Creek watershed located on the ACP. The impacts of documented seasonal climate extremes and LWW were evaluated on seasonal runoff (May-August), including minimum 7-day mean flow (MQ7), the recovery time of MQ7 to pre-perturbation conditions and the duration of streamflow conditions that prevents fish passage. Low-rainfall scenarios (21% of normal, 1 to 3 summers in a row) caused a larger reduction in MQ7 (56 - 69%) than LWW alone (44 - 58%). Decadal-long consecutive LWW resulted in a new equilibrium in low-flow and seasonal runoff after the third year of LWW that included a disconnected stream network, a reduced contributing area (54% of the watershed area) and limited fish passage throughout summer. Our results highlight that LWW is not offset by same-year snowmelt for lake water levels and streamflow as currently assumed in land management regulations. Effective land management would therefore benefit from considering the combined impact of climate change and industrial lake water withdrawals. \n\n ","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022wr032119","usgsCitation":"Gädeke, A., Arp, C., Liljedahl, A., Daanen, R., Cai, L., Alexeev, V., Jones, B., Wipfli, M.S., and Schulla, J., 2022, Modeled streamflow response to scenarios of Tundra Lake water withdrawal and seasonal climate extremes, Arctic Coastal Plain, Alaska: Water Resources Research, v. 58, no. 8, e2022WR032119, 19 p., https://doi.org/10.1029/2022wr032119.","productDescription":"e2022WR032119, 19 p.","ipdsId":"IP-126871","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":487961,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022wr032119","text":"Publisher Index Page"},{"id":486512,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Arctic Coastal Plain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -155.42580071682042,\n 70.81109388282138\n ],\n [\n -155.42580071682042,\n 69.72800714139643\n ],\n [\n -150.42311039636033,\n 69.72800714139643\n ],\n [\n -150.42311039636033,\n 70.81109388282138\n ],\n [\n -155.42580071682042,\n 70.81109388282138\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"58","issue":"8","noUsgsAuthors":false,"publicationDate":"2022-08-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Gädeke, Anne","contributorId":355846,"corporation":false,"usgs":false,"family":"Gädeke","given":"Anne","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":938264,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Arp, Christopher","contributorId":355847,"corporation":false,"usgs":false,"family":"Arp","given":"Christopher","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":938265,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Liljedahl, Anna K.","contributorId":355848,"corporation":false,"usgs":false,"family":"Liljedahl","given":"Anna K.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":938266,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Daanen, Ronald P.","contributorId":355849,"corporation":false,"usgs":false,"family":"Daanen","given":"Ronald P.","affiliations":[{"id":84845,"text":"Division of Geological and Geophysical Surveys","active":true,"usgs":false}],"preferred":false,"id":938267,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cai, Lei","contributorId":355850,"corporation":false,"usgs":false,"family":"Cai","given":"Lei","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":938268,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Alexeev, Vladimir","contributorId":355851,"corporation":false,"usgs":false,"family":"Alexeev","given":"Vladimir","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":938269,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jones, Benjamin","contributorId":355852,"corporation":false,"usgs":false,"family":"Jones","given":"Benjamin","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":938270,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wipfli, Mark S. 0000-0002-4856-6068 mwipfli@usgs.gov","orcid":"https://orcid.org/0000-0002-4856-6068","contributorId":1425,"corporation":false,"usgs":true,"family":"Wipfli","given":"Mark","email":"mwipfli@usgs.gov","middleInitial":"S.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":938263,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Schulla, Jörg","contributorId":355853,"corporation":false,"usgs":false,"family":"Schulla","given":"Jörg","affiliations":[{"id":84846,"text":"Hydrology Software Consulting","active":true,"usgs":false}],"preferred":false,"id":938271,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70256656,"text":"70256656 - 2022 - Are we falling short on restoring oysters at a regional scale?","interactions":[],"lastModifiedDate":"2024-08-29T15:26:43.155388","indexId":"70256656","displayToPublicDate":"2022-08-03T10:22:34","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":"Are we falling short on restoring oysters at a regional scale?","docAbstract":"Across coastal areas of the northern Gulf of Mexico, the Deepwater Horizon oil spill resulted in significant ecological injury, and over 8 billion USD directed to restoration activities. Oyster restoration projects were implemented with regional goals of restoring oyster abundance, spawning stock, and population resilience. Measuring regional or large-scale ecosystem restoration outcomes challenges traditional project-specific monitoring and outcome reporting. We examine the outcomes of oyster restoration at the project-level and discuss potential pathways to measure progress toward region-level goals. An estimated 15 km2 of oyster habitat was restored across 11 different estuaries with 62 individual reef footprints created, ranging in size from ~0.2 to 1.45 km2. Individual sites were distributed across the salinity gradient, and all reefs were subtidal. One-year post-restoration, mean total oyster density across all sites was 53.0 ± 60.7 ind m−2 of which 38.4 ± 42.2 ind m−2 were adult (>25 mm shell height) oysters. Recent data (2018/2019) available for all sites indicates reduced densities of total oysters (44.6 ± 70.9 ind m−2) and adult oysters (14.6 ± 21.6 ind m−2). These data provide insight into project specific outcomes, suggesting an overall enhancement in oyster abundance compared to pre-restoration, but fall short of informing outcomes at the regional-level that incorporate cumulative effects on adjacent and connected reef populations, or inform overall resiliency of the regional oyster resource. Developing regional outcome benchmarks that enable assessment of cumulative and synergistic impacts of individual projects may benefit from broader spatial and temporal monitoring requirements that can better inform development of regional tools or models. Such tools would enable cumulative effects analyses examining net resource change, resilience and assess impacts of restoration activities on regional resource status.
","language":"English","publisher":"Springer","doi":"10.1007/s00267-022-01691-y","usgsCitation":"La Peyre, M., Marshall, D.A., Buie, S.C., Hijuelos, A., and Steyer, G., 2022, Are we falling short on restoring oysters at a regional scale?: Environmental Management, v. 70, p. 581-592, https://doi.org/10.1007/s00267-022-01691-y.","productDescription":"12 p.","startPage":"581","endPage":"592","ipdsId":"IP-138828","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":433315,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"northern Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -83.36958808470514,\n 24.1126519217827\n ],\n [\n -80.85940900302997,\n 24.714635678707992\n ],\n [\n -81.10116830711196,\n 25.46706673170469\n ],\n [\n -82.39537707405206,\n 27.091011945078975\n ],\n [\n -82.65786309241751,\n 28.308364041898628\n ],\n [\n -82.5772062119935,\n 28.999162563752748\n ],\n [\n -83.9904926193391,\n 30.19347675768212\n ],\n [\n -85.07008045187222,\n 29.677396598341033\n ],\n [\n -86.43938452544526,\n 30.518697342417497\n ],\n [\n -87.63633030899686,\n 30.340763113128546\n ],\n [\n -88.02876199353206,\n 30.727492702231586\n ],\n [\n -88.68357561069969,\n 30.436884709045927\n ],\n [\n -89.8845804986809,\n 30.130244087006545\n ],\n [\n -89.88022780179678,\n 29.65775338151731\n ],\n [\n -94.0525922925487,\n 29.622956144774975\n ],\n [\n -96.92033720263936,\n 28.066156015973654\n ],\n [\n -97.46297846111713,\n 26.978138281620108\n ],\n [\n -97.21131853158765,\n 25.94538903066173\n ],\n [\n -83.36958808470514,\n 24.1126519217827\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"70","noUsgsAuthors":false,"publicationDate":"2022-08-03","publicationStatus":"PW","contributors":{"authors":[{"text":"La Peyre, Megan K. 0000-0001-9936-2252","orcid":"https://orcid.org/0000-0001-9936-2252","contributorId":264343,"corporation":false,"usgs":true,"family":"La Peyre","given":"Megan K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908523,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Marshall, Danielle Aguilar","contributorId":341509,"corporation":false,"usgs":false,"family":"Marshall","given":"Danielle","email":"","middleInitial":"Aguilar","affiliations":[{"id":32913,"text":"Louisiana State University Agricultural Center","active":true,"usgs":false}],"preferred":false,"id":908524,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buie, Sarah Catherine Leblanc","contributorId":341510,"corporation":false,"usgs":false,"family":"Buie","given":"Sarah","email":"","middleInitial":"Catherine Leblanc","affiliations":[{"id":32913,"text":"Louisiana State University Agricultural Center","active":true,"usgs":false}],"preferred":false,"id":908525,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hijuelos, Ann","contributorId":341511,"corporation":false,"usgs":false,"family":"Hijuelos","given":"Ann","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":908526,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Steyer, Gregory 0000-0001-7231-0110","orcid":"https://orcid.org/0000-0001-7231-0110","contributorId":218813,"corporation":false,"usgs":true,"family":"Steyer","given":"Gregory","affiliations":[{"id":5064,"text":"Southeast Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":908527,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70236526,"text":"70236526 - 2022 - Evaluating hydrologic region assignment techniques for ungaged basins in Alaska, USA","interactions":[],"lastModifiedDate":"2022-11-16T17:03:55.108551","indexId":"70236526","displayToPublicDate":"2022-08-03T07:21:33","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating hydrologic region assignment techniques for ungaged basins in Alaska, USA","docAbstract":"Building continental-scale hydrologic models in data-sparse regions requires an understanding of spatial variation in hydrologic processes. Extending these models to ungaged locations requires techniques to group ungaged locations with gaged ones to make process importance and model parameter transfer decisions to ungaged locations. This analysis (1) tested the utility of fundamental streamflow statistics (FDSS) in defining hydrologic regions across Alaska, USA; (2) evaluated if the hydrologic regions represented different hydrologic processes; and (3) tested the ability of random forest and direct assignment techniques, informed by statistically estimated FDSS (FDSSest) and basin characteristics (BCs), to correctly assign ungaged locations to hydrologic regions. Six hydrologic regions were identified across the domain using FDSS. Differences in mean flow, phase shift of the seasonal cycle, and skewness were the primary characteristics defining each region. Two regions represented arctic and continental climates, generally in the northern portion of the domain; four regions represented the southern, maritime portion of the domain. Random forest modeling with BCs (67% success rate) outperformed FDSSest (58% success rate) suggesting that no statistically estimated streamflow was needed to assign ungaged locations to a region. For regions with many sites, most region assignment techniques performed similarly. Random forest modeling performance declined when BCs and FDSSest were both used to predict region membership, suggesting FDSSest had little information in addition to BCs. This analysis demonstrated that FDSS-based hydrologic regions discern process differences across a data-sparse and hydrologically diverse landscape. Process importance rankings from random forest-derived BCs provided model-independent information for making modeling decisions.
We investigate the shallow plumbing system of the Deccan Traps Large Igneous Province using rock and mineral data from Giant Plagioclase Basalt (GPB) lava flows from around the entire province, but with a focus on the Saurashtra Peninsula, the Malwa Plateau, and the base and top of the Western Ghats (WG) lava pile. GPB lavas in the WG typically occur at the transition between chemically distinct basalt formations. Most GPB samples are evolved basalts, with high Fe and Ti contents, and show major and trace elements and Sr-Nd-Pb isotopic compositions generally similar to those of previously studied Deccan basalts. Major element modeling suggests that high-Fe, evolved melts typical of GPB basalts may derive from less evolved Deccan basalts by low-pressure fractional crystallization in a generally dry magmatic plumbing system. The basalts are strongly porphyritic, with 6–25% of mm- to cm-sized plagioclase megacrysts, frequently occurring as crystal clots, plus relatively rare olivine and clinopyroxene. The plagioclase crystals are mostly labradoritic, but some show bytownitic cores (general range of anorthite mol%: 78–55). A common feature is a strong Fe enrichment at the plagioclase rims, indicating interaction with an Fe-rich melt similar to that represented by the matrix compositions (FeOt up to 16–17 wt%). Plagioclase minor and trace elements and Sr isotopic compositions analyzed by laser ablation inductively coupled plasma mass spectrometry show evidence of a hybrid and magma mixing origin. In particular, several plagioclase crystals show variable 87Sr/86Sri, which only partially overlaps with the 87Sr/86Sri of the surrounding matrix. Diffusion modeling suggests residence times of decades to centuries for most plagioclase megacrysts. Notably, some plagioclase crystal clots show textural evidence of deformation as recorded by electron back-scatter diffraction analyses and chemical maps, which suggest that the plagioclase megacrysts were deformed in a crystal-rich environment in the presence of melt. We interpret the plagioclase megacrysts as remnants of a crystal mush originally formed in the shallow plumbing system of the Deccan basalts. In this environment, plagioclase acquired a zoned composition due to the arrival of chemically distinct basaltic magmas. Prior to eruption, a rapidly rising but dense Fe-rich magma was capable of disrupting the shallow level crystal mush, remobilizing part of it and carrying a cargo of buoyant plagioclase megacrysts. Our findings suggest that basaltic magmas from the Deccan Traps, and possibly from LIPs in general, are produced within complex transcrustal magmatic plumbing systems with widespread crystal mushes developed in the shallow crust.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/petrology/egac075","usgsCitation":"Marzoli, A., Renne, P.R., Andreasen, R., Spiess, R., Chiaradia, M., Ruth, D.C., Tholt, A., Pande, K., and Costa, F.J., 2022, The Shallow Magmatic Plumbing System of the Deccan Traps, Evidence from Plagioclase Megacrysts and Their Host Lavas: Journal of Petrology, v. 63, no. 9, egac075, https://doi.org/10.1093/petrology/egac075.","productDescription":"egac075","ipdsId":"IP-137938","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":489006,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://pure.au.dk/portal/en/publications/28790e6d-08a1-4f02-b893-195df971663e","text":"External Repository"},{"id":463238,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"63","issue":"9","noUsgsAuthors":false,"publicationDate":"2022-08-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Marzoli, A.","contributorId":167328,"corporation":false,"usgs":false,"family":"Marzoli","given":"A.","email":"","affiliations":[{"id":24687,"text":"Universitá Degli Studi di Padova, Padova, Italy","active":true,"usgs":false}],"preferred":false,"id":916902,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Renne, Paul R. 0000-0003-1769-5235","orcid":"https://orcid.org/0000-0003-1769-5235","contributorId":229577,"corporation":false,"usgs":false,"family":"Renne","given":"Paul","email":"","middleInitial":"R.","affiliations":[{"id":37390,"text":"Department of Earth and Planetary Science, University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":916903,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Andreasen, R","contributorId":345557,"corporation":false,"usgs":false,"family":"Andreasen","given":"R","email":"","affiliations":[{"id":37318,"text":"Aarhus University","active":true,"usgs":false}],"preferred":false,"id":916904,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Spiess, R","contributorId":345558,"corporation":false,"usgs":false,"family":"Spiess","given":"R","email":"","affiliations":[{"id":82629,"text":"Universita di Padova","active":true,"usgs":false}],"preferred":false,"id":916905,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chiaradia, M","contributorId":345561,"corporation":false,"usgs":false,"family":"Chiaradia","given":"M","email":"","affiliations":[{"id":82630,"text":"Universite de Geneve","active":true,"usgs":false}],"preferred":false,"id":916906,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ruth, Dawn Catherine Sweeney 0000-0001-9369-9364","orcid":"https://orcid.org/0000-0001-9369-9364","contributorId":334908,"corporation":false,"usgs":true,"family":"Ruth","given":"Dawn","email":"","middleInitial":"Catherine Sweeney","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":916907,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Tholt, A.J.","contributorId":345562,"corporation":false,"usgs":false,"family":"Tholt","given":"A.J.","email":"","affiliations":[{"id":38176,"text":"Berkeley Geochronology Center","active":true,"usgs":false}],"preferred":false,"id":916908,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Pande, K","contributorId":345563,"corporation":false,"usgs":false,"family":"Pande","given":"K","email":"","affiliations":[{"id":7210,"text":"Indian Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":916909,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Costa, Fabio J. V.","contributorId":289278,"corporation":false,"usgs":false,"family":"Costa","given":"Fabio","email":"","middleInitial":"J. V.","affiliations":[{"id":62093,"text":"Policia Federal","active":true,"usgs":false}],"preferred":false,"id":916910,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70234148,"text":"70234148 - 2022 - Management of diseases in free-ranging wildlife populations","interactions":[],"lastModifiedDate":"2022-09-16T15:20:49.939288","indexId":"70234148","displayToPublicDate":"2022-08-02T08:46:38","publicationYear":"2022","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"9","title":"Management of diseases in free-ranging wildlife populations","docAbstract":"Diseases are increasingly threatening the conservation of wildlife species. Spillover of pathogens into humans and domestic animals may negatively impact public health and the economy, requiring increased proactive management actions. The North American Wildlife Management Model provides the philosophical basis for managing wildlife and underpins all management options. Diseases in wildlife populations may be managed by manipulation of the environment, manipulation of the host, manipulation of the agent, and modification of human behavior. Important considerations include setting management goals, and metrics to assess success. Future strategies include using systems and One Health approaches to develop interventions that optimize outcomes for humans, animals, and the environment.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Fowler's zoo and wild animal medicine current therapy, volume 10","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","usgsCitation":"Drew, M.L., and Sleeman, J.M., 2022, Management of diseases in free-ranging wildlife populations, chap. 9 of Fowler's zoo and wild animal medicine current therapy, volume 10, p. 47-53.","productDescription":"7 p.","startPage":"47","endPage":"53","ipdsId":"IP-124038","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":404653,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":404632,"type":{"id":15,"text":"Index Page"},"url":"https://www.elsevier.com/books/fowler's-zoo-and-wild-animal-medicine-current-therapyvolume-10/978-0-323-82852-9"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Miller, Eric","contributorId":294470,"corporation":false,"usgs":false,"family":"Miller","given":"Eric","affiliations":[],"preferred":false,"id":848064,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Lamberski, Nadine","contributorId":259228,"corporation":false,"usgs":false,"family":"Lamberski","given":"Nadine","affiliations":[{"id":38792,"text":"San Diego Zoo Global","active":true,"usgs":false}],"preferred":false,"id":848065,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Calle, Paul","contributorId":294471,"corporation":false,"usgs":false,"family":"Calle","given":"Paul","email":"","affiliations":[{"id":47877,"text":"Wildlife Conservation Society, Bronx, NY, USA","active":true,"usgs":false}],"preferred":false,"id":848066,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Drew, Mark L.","contributorId":169527,"corporation":false,"usgs":false,"family":"Drew","given":"Mark","email":"","middleInitial":"L.","affiliations":[{"id":25555,"text":"Idaho Dept. of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":847980,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sleeman, Jonathan M. 0000-0002-9910-6125 jsleeman@usgs.gov","orcid":"https://orcid.org/0000-0002-9910-6125","contributorId":128,"corporation":false,"usgs":true,"family":"Sleeman","given":"Jonathan","email":"jsleeman@usgs.gov","middleInitial":"M.","affiliations":[{"id":82110,"text":"Midcontinent Regional Director's Office","active":true,"usgs":true},{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":847981,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70239760,"text":"70239760 - 2022 - Predation thresholds for reintroduction of native avifauna following suppression of invasive brown treesnakes on Guam","interactions":[],"lastModifiedDate":"2023-01-18T14:30:11.981529","indexId":"70239760","displayToPublicDate":"2022-08-02T08:26:58","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Predation thresholds for reintroduction of native avifauna following suppression of invasive brown treesnakes on Guam","docAbstract":"The brown treesnake (BTS) (Boiga irregularis) invasion on Guåhan (in English, Guam) led to the extirpation of nearly all native forest birds. In recent years, methods have been developed to reduce BTS abundance on a landscape scale. To help assess the prospects for the successful reintroduction of native birds to Guåhan following BTS suppression, we modeled bird population persistence based on their life history characteristics and relative sensitivity to BTS predation. We constructed individual-based models and simulated BTS predation in hypothetical founding populations for each of seven candidate bird species. We represented BTS predation risk in two steps: risk of being encountered and risk of mortality if encountered. We link encounter risk from the bird's perspective to snake contact rates at camera traps with live animal lures, the most direct practical means of estimating BTS predation risk. Our simulations support the well-documented fact that Guåhan's birds cannot persist with an uncontrolled population of BTS but do indicate that bird persistence in Guåhan's forests is possible with suppression short of total eradication. We estimate threshold BTS contact rates would need to be below 0.0002–0.0006 snake contacts per bird per night for these birds to persist on the landscape, which translates to an annual encounter probability of 0.07–0.20. We simulated the effects of snake-proof nest boxes for Sihek (Todiramphus cinnamominus) and Såli (Aplonis opaca), but the benefits were small relative to the overall variation in contact rate thresholds among species. This variation among focal bird species in sustainable predation levels can be used to prioritize species for reintroduction in a BTS-suppressed landscape, but variation among these species is narrow relative to the required reduction from current BTS levels, which may be four orders of magnitude higher (>0.18). Our modeling indicates that the required predation thresholds may need to be lower than have yet been demonstrated with current BTS management. Our predation threshold metric provides an important management tool to help estimate target BTS suppression levels that can be used to determine when bird reintroduction campaigns might begin and serves as a model for other systems to match predator control with reintroduction efforts.
","language":"English","publisher":"Wiley","doi":"10.1002/eap.2716","usgsCitation":"McElderry, R., Paxton, E.H., Nguyen, A.V., and Siers, S.R., 2022, Predation thresholds for reintroduction of native avifauna following suppression of invasive brown treesnakes on Guam: Ecological Applications, v. 32, no. 8, e2716, 19 p., https://doi.org/10.1002/eap.2716.","productDescription":"e2716, 19 p.","ipdsId":"IP-130719","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":446952,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/eap.2716","text":"Publisher Index Page"},{"id":412025,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Guam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 144.97077826134404,\n 13.59091065759955\n ],\n [\n 144.85095546721982,\n 13.663691679762252\n ],\n [\n 144.77392652814024,\n 13.509785599826927\n ],\n [\n 144.6134495717218,\n 13.445281650900142\n ],\n [\n 144.6284274209881,\n 13.332878728890421\n ],\n [\n 144.6797800470419,\n 13.235003984055268\n ],\n [\n 144.726853287589,\n 13.224589457355279\n ],\n [\n 144.78890437740444,\n 13.272492591536036\n ],\n [\n 144.7931837629091,\n 13.401575642368869\n ],\n [\n 144.93226379180425,\n 13.509785472844925\n ],\n [\n 144.97077826134404,\n 13.59091065759955\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"32","issue":"8","noUsgsAuthors":false,"publicationDate":"2022-09-30","publicationStatus":"PW","contributors":{"authors":[{"text":"McElderry, Robert","contributorId":265185,"corporation":false,"usgs":false,"family":"McElderry","given":"Robert","email":"","affiliations":[{"id":54632,"text":"Research Corporation of the University of Guam","active":true,"usgs":false}],"preferred":false,"id":861792,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Paxton, Eben H. 0000-0001-5578-7689","orcid":"https://orcid.org/0000-0001-5578-7689","contributorId":19640,"corporation":false,"usgs":true,"family":"Paxton","given":"Eben","email":"","middleInitial":"H.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":861793,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nguyen, Andre Van 0000-0001-5917-0360","orcid":"https://orcid.org/0000-0001-5917-0360","contributorId":301028,"corporation":false,"usgs":true,"family":"Nguyen","given":"Andre","email":"","middleInitial":"Van","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":861794,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Siers, Shane R.","contributorId":152305,"corporation":false,"usgs":false,"family":"Siers","given":"Shane","email":"","middleInitial":"R.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":861795,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70237209,"text":"70237209 - 2022 - Chapter 1: General conceptual model for climate change in the Upper San Francisco Estuary","interactions":[],"lastModifiedDate":"2022-10-05T20:04:24.970765","indexId":"70237209","displayToPublicDate":"2022-08-01T11:35:25","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":12617,"text":"IEP Technical Report","active":true,"publicationSubtype":{"id":2}},"seriesNumber":"99","chapter":"1","title":"Chapter 1: General conceptual model for climate change in the Upper San Francisco Estuary","docAbstract":"This report is a collaboration by many state and federal agencies working in the Upper San Francisco Estuary to analyze the potential impacts of climate change to different ecosystems found here. Management stategies for ecological values in the face of climate change require reliable and focused information. In this technical report, our focus is on the Upper San Francisco Estuary (SFE), which contains the Sacramento-San Joaquin Delta and Suisun Bay. This area is home to three interconnected ecosystems: open water, floodplain, and tidal marsh. For this geographical area, we have decades of in-depth monitoring information and scientific investigations that have been successfully used to address a number of management needs. In 2019, the Interagency Ecological Program established a diverse work team to improve our ability to anticipate and respond to climate change impacts. The charge to the group was to:
• synthesize science relevant to climate change,
• determine important knowledge gaps, and
• identify ecosystem metrics for climate change.
We focus our analyses on the likely impacts of climate change on interconnected aquatic habitats. We illustrate how changes in habitats are likely to affect diverse species.
In this report we describe ecological trends attributable to climate change and likely future impacts. We address four principal questions:
1. How have the habitats and biotic communities changed due to climatic trends and events?
2. How are estuarine habitats, flora, and fauna likely to change as climate change trends continue?
3. What are key metrics to document ecosystem change as a result of climate change?
4. How should our monitoring change to improve information value?
Our work builds on the similar work of the San Francisco Baylands Goals Project (Goals Project 2015), which addressed climate change impacts to wetlands downstream of the confluence of the Sacramento and San Joaquin Rivers. We aim to contribute to an integrated baseline understanding of climate change impacts for the entire San Francisco Estuary.
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Moreover, the automotive manufacturing industries are reliant on complex and sometimes opaque multi-tiered global supply chains. Among the many industries on which automotive supply chains depend are the electronics and semiconductor industries, which are themselves material-intensive and reliant on opaque global supply chains. A linear programming model built on mineral end-use data and input-output tables provides a tool for investigating inter-industry relationships between the two sets of industry sectors and industrial vulnerability to mineral commodity supply disruptions. Supply disruptions in aluminum, magnesium metal, and zinc—metals used in the body-in-white, wheels and other parts—have significant potential to disrupt the automotive industries. On the other hand, supply disruptions in gallium, tellurium, and indium for example—semiconductor elements used in power electronics, screen coatings and other parts—have significant potential to impact the electronics and computer industries. More interestingly, case studies of the automotive and electronics industries show how supply disruptions in mineral commodities that are generally considered semiconductor materials, such as gallium, can significantly impact the automotive sector.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.resourpol.2022.102894","usgsCitation":"Manley, R., Alonso, E., and Nassar, N.T., 2022, Examining industry vulnerability: A focus on mineral commodities used in the automotive and electronics industries: Resources Policy, v. 78, 102894, 8 p., https://doi.org/10.1016/j.resourpol.2022.102894.","productDescription":"102894, 8 p.","ipdsId":"IP-135107","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":487793,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.resourpol.2022.102894","text":"Publisher Index Page"},{"id":408492,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"78","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Manley, Ross 0000-0002-3341-4766","orcid":"https://orcid.org/0000-0002-3341-4766","contributorId":223012,"corporation":false,"usgs":true,"family":"Manley","given":"Ross","email":"","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":854894,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Alonso, Elisa 0000-0002-0090-8284","orcid":"https://orcid.org/0000-0002-0090-8284","contributorId":223015,"corporation":false,"usgs":true,"family":"Alonso","given":"Elisa","email":"","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":854895,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nassar, Nedal T. 0000-0001-8758-9732 nnassar@usgs.gov","orcid":"https://orcid.org/0000-0001-8758-9732","contributorId":197864,"corporation":false,"usgs":true,"family":"Nassar","given":"Nedal","email":"nnassar@usgs.gov","middleInitial":"T.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":854896,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70234118,"text":"70234118 - 2022 - Crowd-sourced SfM: Best practices for high resolution monitoring of coastal cliffs and bluffs","interactions":[],"lastModifiedDate":"2022-08-01T14:36:06.939046","indexId":"70234118","displayToPublicDate":"2022-08-01T09:25:19","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1333,"text":"Continental Shelf Research","active":true,"publicationSubtype":{"id":10}},"title":"Crowd-sourced SfM: Best practices for high resolution monitoring of coastal cliffs and bluffs","docAbstract":"Structure from motion (SfM) photogrammetry is an increasingly common technique for measuring landscape change over time by deriving 3D point clouds and surface models from overlapping photographs. Traditional change detection approaches require photos that are geotagged with a differential GPS (DGPS) location, which requires expensive equipment that can limit the ability of communities and researchers to perform frequent (i.e. daily, weekly, and/or monthly) surveys. Crowd-sourced photos can lower the barrier to entry and substantially increase the frequency of surveys, although such photos often lack accurate location information and can vary in quality. This paper presents a SfM approach for monitoring environmental change in high relief coastal environments that does not require all photos have DGPS location information and does not require field survey data. A 1.5 km section of coastal bluffs near the Elwha River Delta (Washington state) is used to demonstrate the efficacy of this approach. Photos of the bluff were collected with a digital SLR camera or phone camera while either on foot along the beach or from a boat as part of monitoring following removal of two large dams along the Elwha River during 2011–2013. Only 33% of photos had DGPS location information, whereas most photos had no location information or locations that were accurate to a couple of meters. All photos were processed using 3D, 4D, and fixed-floating (FF) SfM alignment methods and the resulting dense point clouds are used to compare the different alignment approaches with crowd-sourced photo sets. Results demonstrate that 4D and FF approaches are more likely to reconstruct and are more accurate than the 3D approach. While the 4D and FF have comparable accuracies, the FF approach is several orders of magnitude more efficient, as this method can leverage camera location information from relatively few photos to improve the accuracy of all aligned and derived products. Effectively utilizing crowd-sourced photos in SfM change detection can improve the frequency of surveying a landscape in a more cost-effective approach that also has potential for citizen-science engagement and communication. This is especially important for data-poor environments such as high-relief coastal cliffs and bluffs, where near-nadir imagery and LIDAR may fail to accurately capture near-vertical cliffs or bluff faces. Based on the analysis of different photo alignment and filtering approaches, we present suggested best practices for engaging citizen scientists in coastal cliff and bluff monitoring efforts through collecting photos amenable for SfM reconstruction.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.csr.2022.104799","usgsCitation":"Wernette, P., Miller, I.M., Ritchie, A.C., and Warrick, J.A., 2022, Crowd-sourced SfM: Best practices for high resolution monitoring of coastal cliffs and bluffs: Continental Shelf Research, v. 245, 104799, 12 p., https://doi.org/10.1016/j.csr.2022.104799.","productDescription":"104799, 12 p.","ipdsId":"IP-129225","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":446968,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.5061/dryad.63xsj3v4s","text":"External Repository"},{"id":404570,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Elwha River Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.54572296142578,\n 48.146846885734256\n ],\n [\n -123.52460861206055,\n 48.12805945422104\n ],\n [\n -123.51877212524414,\n 48.13413175409871\n ],\n [\n -123.52632522583006,\n 48.13963057588326\n ],\n [\n -123.53284835815428,\n 48.146846885734256\n ],\n [\n -123.54537963867186,\n 48.150970035875766\n ],\n [\n -123.54572296142578,\n 48.146846885734256\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"245","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wernette, Phillipe Alan 0000-0002-8902-5575","orcid":"https://orcid.org/0000-0002-8902-5575","contributorId":259274,"corporation":false,"usgs":true,"family":"Wernette","given":"Phillipe Alan","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":847869,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miller, Ian M. 0000-0002-3289-6337","orcid":"https://orcid.org/0000-0002-3289-6337","contributorId":41951,"corporation":false,"usgs":false,"family":"Miller","given":"Ian","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":847870,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ritchie, Andrew C. aritchie@usgs.gov","contributorId":4984,"corporation":false,"usgs":true,"family":"Ritchie","given":"Andrew","email":"aritchie@usgs.gov","middleInitial":"C.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":847871,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Warrick, Jonathan A. 0000-0002-0205-3814 jwarrick@usgs.gov","orcid":"https://orcid.org/0000-0002-0205-3814","contributorId":167736,"corporation":false,"usgs":true,"family":"Warrick","given":"Jonathan","email":"jwarrick@usgs.gov","middleInitial":"A.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":847872,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}