The Collaborative Science and Adaptive Management Program (CSAMP) has endorsed a goal of reversing the recent downward trajectory of the Delta Smelt population within 5-10 generations, with the long-term aim of establishing a self-sustaining population. An ambitious agenda of management actions is planned, and more management actions are being considered. This White Paper furthers one of the recommendations in the 2019 Delta Smelt Science Plan – the need to predict the potential ecological effects of taking a management action. Existing statistical models can be highly informative in assessing the response of Delta Smelt to changing system conditions and management actions. However, management actions can shift or alter conditions in ways that models based on analysis of historical data may not be able to represent, and short-term or localized effects may be missed with models designed to assess effects at the population level.
Decision support tools (DSTs) are computer-based tools developed to assist decision-making, often combining computationally intensive analysis and spatial mapping of environmental relationships. DSTs can be used in planning processes that evaluate an array of actions, such as in Structured Decision Making (SDM), where DSTs are needed to compare among alternatives. DSTs can also be used to explore the potential effects of different approaches to implementing management actions. The goal of this White Paper is to identify plausible options for DSTs that could be developed for future use to evaluate management actions that seek to either reverse the decline of Delta Smelt or minimize or mitigate the effects of other water management actions.
Different types of management actions lead to different needs for DSTs. This White Paper was developed using three types of actions currently being considered to enhance the Delta Smelt population: Supplementation with Hatchery Fish, Summer-Fall Habitat, and Food Enhancement actions. These three management actions target different parts of the estuary and different processes, with a variety of possible metrics to gauge performance.
Three DSTs are proposed that collectively address management questions related to the management actions considered, with each requiring a slightly different set of processes to be included and producing an array of outputs at varying spatial and temporal scales: DST 1. Modeling Fish Movement, Survival, and Reproduction Across Their Range. This DST can address management questions that require information about Delta Smelt spatial distribution and movement.
• DST 1 could be used to compare conditions with and without management actions in place, how the management action performs among different types of water years (with varied flow and associated abiotic conditions), and to assess relative change with different variations and strategies of the management actions.
• DST 2. Changes in Habitat Conditions and Delta Smelt Response. This DST is intended to evaluate combinations of conditions that are considered to provide suitable habitat for Delta Smelt, and Delta Smelt response. Delta Smelt habitat is generally described as open water with low salinity (0 to 6), turbidity of at least 12 NTU, suitable temperature conditions, and sufficient food availability to support growth.
• DST 3. Regional Effects of Food Subsidy. This DSTs seeks to evaluate effectiveness of food enhancement actions by providing information on responses of the immediate targets of the action (i.e., phytoplankton or zooplankton) and tracing those to projected growth responses of Delta Smelt.
There is not a single DST that adequately addresses management questions relevant to all management actions, although there is some overlap in the management questions each of the three DSTs can address.
For each of the DSTs a substantial foundation of models and approaches already exists and modeling has already been applied to several of the management actions described. However, a number of outstanding issues remain for further development of the proposed DSTs. These are summarized in this White Paper together with potential approaches that could be applied or tested. Some components for the DSTs are already available and thus development could be relatively easy. However, for several of the topics identified there are gaps in knowledge that currently limit formulation of model structure and process representations. This presents challenges to readily incorporate some needed mechanisms into the models.
Eleven next steps, aligned with relevant DSTs, are outlined. The next steps vary in their complexity or technical ‘lift’ required. Many build on existing work, or methods and approaches that have already been developed or are underway, while others require additional thinking to establish a viable approach. Some interim utility for decisions could be gained during initial development of the DSTs with further features added over time.
Development of a DST requires engagement of both managers and scientists. Identifying the outputs and resolution needed for management purposes early in development of any DST is essential for effective pursuit of next steps and suitable approaches to address challenges. Dialog between managers and technical experts also informs what process-based simulation can do, and what tradeoffs are acceptable to meet a given purpose. To further develop the DSTs outlined here for application in the estuary requires:
- Engagement of a committed group of technical experts with appropriate expertise.
- The development of a coordinated workplan including appropriate project management and tracking.
- Dialog between potential users (i.e., managers and policy makers) and technical experts.
- Resources to pursue DST development including personnel and computational resources.
This White Paper demonstrates the potential for moving toward DSTs for a variety of management actions in support of Delta Smelt that include mechanistic representations of physical and biological processes. Through focused effort from technical experts, managers and policy makers, DSTs can be developed to provide quantitative predictions of management effects on the ecosystem, targeting the changes the management actions seek to achieve, how these effects compare to ambient conditions, and how the effects vary among water year types or with timing and location of actions. Importantly, solid foundations exist which can be leveraged, refined, and built upon to specifically inform current and future management decisions.
","language":"English","publisher":"Collaborative Adaptive Management Team","usgsCitation":"Reed, D., Acuna, S., Ateljevich, E., Brown, L.R., Geske, B., Gross, E., Hobbs, J., Kimmerer, W.J., Lucas, L., Nobriga, M., and Rose, K.A., 2021, Toward improved decision-support tools for Delta Smelt management actions: White Paper, v, 34 p.","productDescription":"v, 34 p.","ipdsId":"IP-127826","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":389005,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":389004,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.baydeltalive.com/CSAMP/docs/24756"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Reed, Denise","contributorId":215697,"corporation":false,"usgs":false,"family":"Reed","given":"Denise","affiliations":[{"id":37245,"text":"University of New Orleans","active":true,"usgs":false}],"preferred":false,"id":822849,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Acuna, Shawn","contributorId":257756,"corporation":false,"usgs":false,"family":"Acuna","given":"Shawn","email":"","affiliations":[{"id":52106,"text":"Metropolitan Water District of Southern California","active":true,"usgs":false}],"preferred":false,"id":822850,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ateljevich, Eli","contributorId":187437,"corporation":false,"usgs":false,"family":"Ateljevich","given":"Eli","email":"","affiliations":[],"preferred":false,"id":822851,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brown, Larry R. 0000-0001-6702-4531 lrbrown@usgs.gov","orcid":"https://orcid.org/0000-0001-6702-4531","contributorId":1717,"corporation":false,"usgs":true,"family":"Brown","given":"Larry","email":"lrbrown@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":822852,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Geske, Ben","contributorId":265520,"corporation":false,"usgs":false,"family":"Geske","given":"Ben","email":"","affiliations":[{"id":54715,"text":"Delta Science Program","active":true,"usgs":false}],"preferred":false,"id":822853,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gross, Edward","contributorId":264402,"corporation":false,"usgs":false,"family":"Gross","given":"Edward","affiliations":[{"id":28024,"text":"UCDavis","active":true,"usgs":false}],"preferred":false,"id":822854,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hobbs, Jim","contributorId":200389,"corporation":false,"usgs":false,"family":"Hobbs","given":"Jim","email":"","affiliations":[],"preferred":false,"id":822855,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kimmerer, Wim J.","contributorId":59169,"corporation":false,"usgs":false,"family":"Kimmerer","given":"Wim","email":"","middleInitial":"J.","affiliations":[{"id":6690,"text":"San Francisco State University","active":true,"usgs":false}],"preferred":false,"id":822856,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lucas, Lisa 0000-0001-7797-5517 llucas@usgs.gov","orcid":"https://orcid.org/0000-0001-7797-5517","contributorId":260498,"corporation":false,"usgs":true,"family":"Lucas","given":"Lisa","email":"llucas@usgs.gov","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":822857,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Nobriga, Matthew","contributorId":139247,"corporation":false,"usgs":false,"family":"Nobriga","given":"Matthew","affiliations":[{"id":6678,"text":"U.S. Fish and Wildlife Service, Alaska Maritime National Wildlife Refuge","active":true,"usgs":false}],"preferred":false,"id":822858,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Rose, Kenneth A","contributorId":147274,"corporation":false,"usgs":false,"family":"Rose","given":"Kenneth","email":"","middleInitial":"A","affiliations":[{"id":16815,"text":"Dept. of Oceanography and Coastal Sciences, Louisiana State University, Baton Rouge","active":true,"usgs":false}],"preferred":false,"id":822859,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70221876,"text":"70221876 - 2021 - Global tropical reef fish richness could decline by around half if corals are lost","interactions":[],"lastModifiedDate":"2021-07-13T10:01:20.128986","indexId":"70221876","displayToPublicDate":"2021-06-30T09:50:55","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3173,"text":"Proceedings of the Royal Society B","active":true,"publicationSubtype":{"id":10}},"title":"Global tropical reef fish richness could decline by around half if corals are lost","docAbstract":"Reef fishes are a treasured part of marine biodiversity, and also provide needed protein for many millions of people. Although most reef fishes might survive projected increases in ocean temperatures, corals are less tolerant. A few fish species strictly depend on corals for food and shelter, suggesting that coral extinctions could lead to some secondary fish extinctions. However, secondary extinctions could extend far beyond those few coral-dependent species. Furthermore, it is yet unknown how such fish declines might vary around the world. Current coral mass mortalities led us to ask how fish communities would respond to coral loss within and across oceans. We mapped 6964 coral-reef-fish species and 119 coral genera, and then regressed reef-fish species richness against coral generic richness at the 1° scale (after controlling for biogeographic factors that drive species diversification). Consistent with small-scale studies, statistical extrapolations suggested that local fish richness across the globe would be around half its current value in a hypothetical world without coral, leading to more areas with low or intermediate fish species richness and fewer fish diversity hotspots.
","language":"English","publisher":"The Royal Society","doi":"10.1098/rspb.2021.0274","usgsCitation":"Strona, G., Lafferty, K.D., Fattorini, S., Beck, P., Guilhaumon, F., Arrigoni, R., Montano, S., Seveso, D., Galli, P., Planes, S., and Parravicini, V., 2021, Global tropical reef fish richness could decline by around half if corals are lost: Proceedings of the Royal Society B, v. 288, no. 1953, 8 p., https://doi.org/10.1098/rspb.2021.0274.","productDescription":"8 p.","ipdsId":"IP-130442","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":451701,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1098/rspb.2021.0274","text":"Publisher Index Page"},{"id":387113,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Southeast Asia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 178.59375,\n -32.842673631954305\n ],\n [\n 198.28125,\n -1.0546279422758742\n ],\n [\n 160.3125,\n 20.632784250388028\n ],\n [\n 125.15625000000001,\n 28.613459424004414\n ],\n [\n 108.984375,\n 24.206889622398023\n ],\n [\n 97.3828125,\n 29.84064389983441\n ],\n [\n 88.59374999999999,\n 16.97274101999902\n ],\n [\n 94.21875,\n -12.211180191503997\n ],\n [\n 129.0234375,\n -9.44906182688142\n ],\n [\n 152.9296875,\n -12.897489183755892\n ],\n [\n 178.59375,\n -32.842673631954305\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"288","issue":"1953","noUsgsAuthors":false,"publicationDate":"2021-06-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Strona, Giovanni","contributorId":237089,"corporation":false,"usgs":false,"family":"Strona","given":"Giovanni","affiliations":[{"id":47601,"text":"University of Helsinki, Research Centre for Ecological Change, Helsinki, Finland","active":true,"usgs":false}],"preferred":false,"id":819166,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lafferty, Kevin D. 0000-0001-7583-4593 klafferty@usgs.gov","orcid":"https://orcid.org/0000-0001-7583-4593","contributorId":1415,"corporation":false,"usgs":true,"family":"Lafferty","given":"Kevin","email":"klafferty@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":819167,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fattorini, Simone","contributorId":260938,"corporation":false,"usgs":false,"family":"Fattorini","given":"Simone","email":"","affiliations":[{"id":52729,"text":"Department of Life, Health and Environmental Sciences, University of L'Aquila, Italy","active":true,"usgs":false}],"preferred":false,"id":819168,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Beck, Pieter","contributorId":260939,"corporation":false,"usgs":false,"family":"Beck","given":"Pieter","email":"","affiliations":[{"id":52730,"text":"European Commission, Joint Research Centre (JRC), Ispra, Italy","active":true,"usgs":false}],"preferred":false,"id":819169,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Guilhaumon, Francois","contributorId":260940,"corporation":false,"usgs":false,"family":"Guilhaumon","given":"Francois","email":"","affiliations":[{"id":52731,"text":"MARBEC, IRD, CNRS, University of Montpellier, Ifremer, France","active":true,"usgs":false}],"preferred":false,"id":819170,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Arrigoni, Roberto","contributorId":260941,"corporation":false,"usgs":false,"family":"Arrigoni","given":"Roberto","email":"","affiliations":[{"id":52730,"text":"European Commission, Joint Research Centre (JRC), Ispra, Italy","active":true,"usgs":false}],"preferred":false,"id":819171,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Montano, Simone","contributorId":260942,"corporation":false,"usgs":false,"family":"Montano","given":"Simone","email":"","affiliations":[{"id":52732,"text":"Department of Earth and Environmental Sciences (DISAT), University of Milan - Bicocca, Italy","active":true,"usgs":false}],"preferred":false,"id":819172,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Seveso, Davide","contributorId":260943,"corporation":false,"usgs":false,"family":"Seveso","given":"Davide","email":"","affiliations":[{"id":52732,"text":"Department of Earth and Environmental Sciences (DISAT), University of Milan - Bicocca, Italy","active":true,"usgs":false}],"preferred":false,"id":819173,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Galli, Paolo","contributorId":260944,"corporation":false,"usgs":false,"family":"Galli","given":"Paolo","affiliations":[{"id":52732,"text":"Department of Earth and Environmental Sciences (DISAT), University of Milan - Bicocca, Italy","active":true,"usgs":false}],"preferred":false,"id":819174,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Planes, Serge","contributorId":260945,"corporation":false,"usgs":false,"family":"Planes","given":"Serge","email":"","affiliations":[{"id":52733,"text":"PSL Research University: EPHE-UPVD-CNRS, USR 3278 CRIOBE, Université de Perpignan, France","active":true,"usgs":false}],"preferred":false,"id":819175,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Parravicini, Valeriano","contributorId":260946,"corporation":false,"usgs":false,"family":"Parravicini","given":"Valeriano","email":"","affiliations":[{"id":52733,"text":"PSL Research University: EPHE-UPVD-CNRS, USR 3278 CRIOBE, Université de Perpignan, France","active":true,"usgs":false}],"preferred":false,"id":819176,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70220178,"text":"70220178 - 2021 - Strength recovery and sealing under hydrothermal conditions","interactions":[],"lastModifiedDate":"2021-09-30T15:11:55.401134","indexId":"70220178","displayToPublicDate":"2021-06-30T09:29:44","publicationYear":"2021","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Strength recovery and sealing under hydrothermal conditions","docAbstract":"While there is significant evidence for healing in natural faults, geothermal reservoirs, and lab experiments, the thermal, hydraulic, mechanical, and chemical interactions that influence healing are poorly understood. We present preliminary results of triaxial slide-hold-slide experiments to constrain rates and mechanisms of healing. Experiments were conducted on gouge composed of Westerly granite and on bare surfaces of Westerly granite and Eureka quartzite. Tests were run at 22, 100, and 200˚C. In some experiments, we also determined the in-plane fluid transmissivity. In bare surface experiments we observe that restrengthening depends on both time and temperature. At 200˚C the simulated fractures restrengthen at a rate of ∆µ/∆log(thold) = 0.009/decade while at 22˚C the healing rate is ~ 0.002/decade. In the gouge experiments restrengthening appears to be independent of temperature. This may be related to the heterogenous mineral composition and thickness of the gouge layer which could allow shearing to be accommodated in unhealed zones. In the experiments, an overall reduction in fluid transmissivity is observed but sliding periods are often associated with increases in the fluid transmissivity. The transmissivity reduction tends to be greater at 200˚C relative to room temperature. Our preliminary results suggest that multiple healing mechanisms are operating under hydrothermal conditions.
","conferenceTitle":"55th US Rock Mechanics/Geomechanics Symposium","conferenceDate":"Jun 20-23, 2021","conferenceLocation":"Houston, TX","language":"English","publisher":"American Rock Mechanics Association","usgsCitation":"Jeppson, T.N., Lockner, D., Kilgore, B.D., Beeler, N.M., and Taron, J., 2021, Strength recovery and sealing under hydrothermal conditions, 55th US Rock Mechanics/Geomechanics Symposium, Houston, TX, Jun 20-23, 2021, 11 p.","productDescription":"11 p.","ipdsId":"IP-127005","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":390036,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Jeppson, Tamara Nicole 0000-0001-5526-5530","orcid":"https://orcid.org/0000-0001-5526-5530","contributorId":248768,"corporation":false,"usgs":true,"family":"Jeppson","given":"Tamara","email":"","middleInitial":"Nicole","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":814644,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lockner, David A. 0000-0001-8630-6833","orcid":"https://orcid.org/0000-0001-8630-6833","contributorId":257574,"corporation":false,"usgs":true,"family":"Lockner","given":"David A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":814645,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kilgore, Brian D. 0000-0003-0530-7979 bkilgore@usgs.gov","orcid":"https://orcid.org/0000-0003-0530-7979","contributorId":3887,"corporation":false,"usgs":true,"family":"Kilgore","given":"Brian","email":"bkilgore@usgs.gov","middleInitial":"D.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":814646,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Beeler, Nicholas M. 0000-0002-3397-8481 nbeeler@usgs.gov","orcid":"https://orcid.org/0000-0002-3397-8481","contributorId":2682,"corporation":false,"usgs":true,"family":"Beeler","given":"Nicholas","email":"nbeeler@usgs.gov","middleInitial":"M.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":814647,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Taron, Joshua M. 0000-0003-2719-3917","orcid":"https://orcid.org/0000-0003-2719-3917","contributorId":257575,"corporation":false,"usgs":true,"family":"Taron","given":"Joshua M.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":814648,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70223729,"text":"70223729 - 2021 - Appendix E. Water quality and hydrology of Green Lake, Wisconsin, and the response in its near-surface water-quality and metalimnetic dissolved oxygen minima to changes in phosphorus loading","interactions":[],"lastModifiedDate":"2021-09-16T15:12:14.688708","indexId":"70223729","displayToPublicDate":"2021-06-30T09:26:46","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"title":"Appendix E. Water quality and hydrology of Green Lake, Wisconsin, and the response in its near-surface water-quality and metalimnetic dissolved oxygen minima to changes in phosphorus loading","docAbstract":"Green Lake is the deepest natural inland lake in Wisconsin, USA, with a maximum depth of about 72 meters (m). In the early 1900’s, the lake was believed to have very good water quality (low nutrient concentrations and good water clarity), with low dissolved oxygen (DO) concentrations only in the deepest part of the lake. Because of increased phosphorus (P) inputs from anthropogenic activities in its watershed, total phosphorus (TP) concentrations in the lake increased, which led to increased algal production and low DO concentrations not only occurring in its deepest areas but also in the middle of the water column (metalimnion). Routine monitoring of the lake and its tributaries has been conducted by the U.S. Geological Survey since 2004 and 1988, respectively. Results from this monitoring led to the Wisconsin Department of Natural Resources (WDNR) listing the lake as impaired because of low DO concentrations in the metalimnion, with elevated TP concentrations identified as the cause of impairment.
As part of this study, comprehensive sampling of the lake and its tributaries was conducted in 2017–2018 to augment ongoing monitoring and further describe the low DO concentrations in the lake (especially in the metalimnion). Empirical and process-driven water quality models were then used to determine the causes of the low DO concentrations and the magnitude of P load reductions needed to improve the water quality of the lake to meet multiple water-quality goals, including the WDNR criteria for TP and DO.
Data from previous studies showed that DO concentrations in the metalimnion decreased slightly as summer progressed in the early 1900’s, but since the late 1970s have typically dropped below 5 milligrams per liter (mg/L), which is the WDNR criterion for impairment. During 2014–2018 (baseline period for this study), the near-surface geometric-mean TP concentration during June–September in the east side of the lake was 0.020 mg/L and in the west side was 0.016 mg/L (both were below the 0.015 mg/L WDNR criterion for the lake), and the minimum metalimnetic DO concentrations measured in August ranged from 1.0 to 4.7 mg/L. It was believed that the degradation in water quality was caused by excessive P inputs to the lake; therefore, the total P inputs to the lake were estimated. The mean annual external P load during 2014–2018 was estimated to be 8,980 kilograms per year (kg/yr), of which monitored and unmonitored tributary inputs contributed 84 percent, atmospheric inputs contributed 8 percent, waterfowl contributed 7 percent, and septic systems contributed 1 percent. At fall turnover, internal sediment recycling contributed an additional 7,040 kg that increased TP concentrations in shallow areas of the lake by about 0.020 mg/L. The elevated TP concentrations then persisted until the following spring. On an annual basis, however, there is a net deposition of P to the bottom sediments.
Empirical models were used to describe how the near-surface water quality of Green Lake would be expected to respond to changes in external P loading. Predictions from the models showed a relatively linear response between P loading and TP and chlorophyll-a (Chl-a) concentrations in the lake, with the changes in TP and Chl-a concentrations being less on a percentage basis (50–60 percent for TP and 30–70 percent for Chl-a) than the changes in P loading. Mean summer water clarity, indicated by Secchi disk depths, had a larger response to decreases in P loading than to increases in loading. Based on these relations, external P loading to the lake would need to be decreased from 8,980 kg/yr to about 5,460 kg/yr for the geometric mean June–September TP concentration on the east side of the lake, with higher TP concentrations than the west side, to reach the WDNR criterion of 0.015 mg/L. This reduction of 3,520 kg/yr equates to a 46-percent reduction in the potentially controllable external P sources (all external sources except precipitation, atmospheric deposition, and waterfowl) from that measured during water years (WYs) 2014–2018. The total external P loading would need to be decreased to 7,680 kg/yr (17-percent reduction in potentially controllable external P sources) for near-surface June–September TP concentrations in the west side of the lake to reach 0.015 mg/L. Total external P loading would need to be decreased to 3,870–5,320 kg/yr for the lake to be classified as oligotrophic, with a near-surface June-September TP concentration of 0.012 mg/L.
Results from the hydrodynamic water-quality model GLM-AED (General Lake Model coupled to the Aquatic Ecodynamics modeling library) indicated that metalimnetic DO minima are driven by external P loading and internal sediment recycling that lead to high TP concentrations during spring and early summer, which in turn lead to high phytoplankton production, high metabolism and respiration, and ultimately DO consumption in the upper, warmer areas of the metalimnion. GLM-AED results indicated that settling of organic material during summer may be slowed by the colder, denser, and more viscous water in the metalimnion and increase DO consumption. Based on empirical evidence comparing minimum metalimnetic DO concentrations with various meteorological, hydrologic, water quality, and in-lake physical factors, lower metalimnetic DO concentrations occurred when there was warmer metalimnetic water temperatures, higher near-surface Chl-a and TP concentrations, and lower Secchi depths during summer. GLM-AED results indicated that the external P load would need to be reduced to about 4,010 kg/yr, a 57-percent reduction from that measured in 2014–2018, to eliminate the occurrence of metalimnetic DO minima of less than 5 mg/L in over 75 percent of the years (the target provided by the WDNR).
Large reductions in external P loading are expected to have an immediate effect on the near-surface TP concentrations and metalimnetic DO concentrations in Green Lake. However, it may take several years for the full effects of the external load reduction to be observed because internal sediment recycling is an important source of P for the following spring.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Diagnostic and feasibility study findings: Water quality improvements for Green Lake, Wisconsin","largerWorkSubtype":{"id":9,"text":"Other Report"},"language":"English","publisher":"Green Lake Association","usgsCitation":"Robertson, D., Siebers, B.J., Ladwig, R., Hamilton, D., Reneau, P., McDonald, C.P., Prellwitz, S., and Lathrop, R.C., 2021, Appendix E. Water quality and hydrology of Green Lake, Wisconsin, and the response in its near-surface water-quality and metalimnetic dissolved oxygen minima to changes in phosphorus loading, vii, 115 p.","productDescription":"vii, 115 p.","ipdsId":"IP-129488","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":389346,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":388824,"type":{"id":15,"text":"Index Page"},"url":"https://www.greenlakeassociation.org/research/"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Green Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.07920837402344,\n 43.75894467245554\n ],\n [\n -88.9133834838867,\n 43.75894467245554\n ],\n [\n -88.9133834838867,\n 43.864485327996704\n ],\n [\n -89.07920837402344,\n 43.864485327996704\n ],\n [\n -89.07920837402344,\n 43.75894467245554\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Robertson, Dale M. 0000-0001-6799-0596","orcid":"https://orcid.org/0000-0001-6799-0596","contributorId":217258,"corporation":false,"usgs":true,"family":"Robertson","given":"Dale M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":822503,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Siebers, Benjamin J. 0000-0002-2900-5169","orcid":"https://orcid.org/0000-0002-2900-5169","contributorId":206518,"corporation":false,"usgs":true,"family":"Siebers","given":"Benjamin","email":"","middleInitial":"J.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":822504,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ladwig, Robert","contributorId":265278,"corporation":false,"usgs":false,"family":"Ladwig","given":"Robert","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":822505,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hamilton, David P.","contributorId":166840,"corporation":false,"usgs":false,"family":"Hamilton","given":"David P.","affiliations":[{"id":24543,"text":"Environmental Research Institute, University of Waikato, Private Bag 3015, Hamilton 3240, New Zealand.","active":true,"usgs":false}],"preferred":false,"id":822506,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reneau, Paul 0000-0002-1335-7573","orcid":"https://orcid.org/0000-0002-1335-7573","contributorId":217293,"corporation":false,"usgs":true,"family":"Reneau","given":"Paul","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":822507,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McDonald, Cory P. 0000-0002-1208-8471","orcid":"https://orcid.org/0000-0002-1208-8471","contributorId":261754,"corporation":false,"usgs":false,"family":"McDonald","given":"Cory","email":"","middleInitial":"P.","affiliations":[{"id":16203,"text":"Michigan Technological university","active":true,"usgs":false}],"preferred":false,"id":822508,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Prellwitz, Stephanie","contributorId":265281,"corporation":false,"usgs":false,"family":"Prellwitz","given":"Stephanie","email":"","affiliations":[{"id":54642,"text":"Green Lake Association","active":true,"usgs":false}],"preferred":false,"id":822509,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lathrop, Richard C","contributorId":172075,"corporation":false,"usgs":false,"family":"Lathrop","given":"Richard","email":"","middleInitial":"C","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":822510,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70221867,"text":"70221867 - 2021 - Quantifying the representation of plant communities in the protected areas of the U.S.: An analysis based on the U.S. National Vegetation Classification Groups","interactions":[],"lastModifiedDate":"2022-04-13T20:17:41.090462","indexId":"70221867","displayToPublicDate":"2021-06-30T09:14:48","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1689,"text":"Forests","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying the representation of plant communities in the protected areas of the U.S.: An analysis based on the U.S. National Vegetation Classification Groups","docAbstract":"Plant communities represent the integration of ecological and biological processes and they serve as an important component for the protection of biological diversity. To measure progress towards protection of ecosystems in the United States for various stated conservation targets we need datasets at the appropriate thematic, spatial, and temporal resolution. The recent release of the LANDFIRE Existing Vegetation Data Products (2016 Remap) with a legend based on U.S. National Vegetation Classification allowed us to assess the conservation status of plant communities of the U.S. The map legend is based on the Group level of the USNVC, which characterizes the regional differences in plant communities based on dominant and diagnostic plant species. By combining the Group level map with the Protected Areas Database of the United States (PAD-US Ver 2.1), we quantified the representation of each Group. If the mapped vegetation is assumed to be 100% accurate, using the Aichi Biodiversity target (17% land in protection by 2020) we found that 159 of the 265 natural Groups have less than 17% in GAP Status 1 & 2 lands and 216 of the 265 Groups fail to meet a 30% representation target. Only four of the twenty ecoregions have >17% of their extent in Status 1 & 2 lands. Sixteen ecoregions are dominated by Groups that are under-represented. Most ecoregions have many hectares of natural or ruderal vegetation that could contribute to future conservation efforts and this analysis helps identify specific targets and opportunities for conservation across the U.S.
","language":"English","publisher":"MDPI","doi":"10.3390/f12070864","usgsCitation":"McKerrow, A., Davidson, A., Rubino, M., Faber-Langendoen, D., and Dockter, D., 2021, Quantifying the representation of plant communities in the protected areas of the U.S.: An analysis based on the U.S. National Vegetation Classification Groups: Forests, v. 12, no. 7, 864, 15 p., https://doi.org/10.3390/f12070864.","productDescription":"864, 15 p.","ipdsId":"IP-129762","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":38128,"text":"Science Analytics and Synthesis","active":true,"usgs":true}],"links":[{"id":451704,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/f12070864","text":"Publisher Index Page"},{"id":387107,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"7","noUsgsAuthors":false,"publicationDate":"2021-06-30","publicationStatus":"PW","contributors":{"authors":[{"text":"McKerrow, Alexa 0000-0002-8312-2905 amckerrow@usgs.gov","orcid":"https://orcid.org/0000-0002-8312-2905","contributorId":127753,"corporation":false,"usgs":true,"family":"McKerrow","given":"Alexa","email":"amckerrow@usgs.gov","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":819084,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Davidson, Anne","contributorId":197967,"corporation":false,"usgs":false,"family":"Davidson","given":"Anne","email":"","affiliations":[],"preferred":false,"id":819085,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rubino, Matthew J. 0000-0003-0651-3053","orcid":"https://orcid.org/0000-0003-0651-3053","contributorId":215500,"corporation":false,"usgs":false,"family":"Rubino","given":"Matthew J.","affiliations":[{"id":39268,"text":"North Carolina State University, NC Cooperative Fish & Wildlife Research Unit","active":true,"usgs":false}],"preferred":false,"id":819086,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Faber-Langendoen, Don","contributorId":260895,"corporation":false,"usgs":false,"family":"Faber-Langendoen","given":"Don","affiliations":[{"id":17658,"text":"NatureServe","active":true,"usgs":false}],"preferred":false,"id":819087,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dockter, Daryn 0000-0003-1914-8657","orcid":"https://orcid.org/0000-0003-1914-8657","contributorId":216814,"corporation":false,"usgs":true,"family":"Dockter","given":"Daryn","email":"","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":819088,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70236252,"text":"70236252 - 2021 - The drying regimes of non-perennial rivers and streams","interactions":[],"lastModifiedDate":"2022-08-31T13:36:51.788646","indexId":"70236252","displayToPublicDate":"2021-06-30T08:34:59","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"The drying regimes of non-perennial rivers and streams","docAbstract":"The flow regime paradigm is central to the aquatic sciences, where flow drives critical functions in lotic systems. Non-perennial streams comprise the majority of global river length, thus we extended this paradigm to stream drying. Using 894 USGS gages, we isolated 25,207 drying events from 1979 to 2018, represented by a streamflow peak followed by no flow. We calculated hydrologic signatures for each drying event and using multivariate statistics, grouped events into drying regimes characterized by: (a) fast drying, (b) long no-flow duration, (c) prolonged drying following low antecedent flows, (d) drying without a distinctive hydrologic signature. 77% of gages had more than one drying regime at different times within the study period. Random forests revealed land cover/use are more important to how a river dries than climate or physiographic characteristics. Clustering stream drying behavior may allow practitioners to more systematically adapt water resource management practices to specific drying regimes or rivers.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021GL093298","usgsCitation":"Price, A.N., Jones, C.N., Hammond, J., Zimmer, M., and Zipper, S., 2021, The drying regimes of non-perennial rivers and streams: Geophysical Research Letters, v. 48, no. 14, e2021GL093298, 12 p., https://doi.org/10.1029/2021GL093298.","productDescription":"e2021GL093298, 12 p.","ipdsId":"IP-127641","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":405993,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"48","issue":"14","noUsgsAuthors":false,"publicationDate":"2021-07-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Price, Adam N. 0000-0002-7211-4758","orcid":"https://orcid.org/0000-0002-7211-4758","contributorId":295971,"corporation":false,"usgs":false,"family":"Price","given":"Adam","email":"","middleInitial":"N.","affiliations":[{"id":27155,"text":"University of California Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":850332,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, C. Nathan 0000-0002-5804-0510","orcid":"https://orcid.org/0000-0002-5804-0510","contributorId":295972,"corporation":false,"usgs":false,"family":"Jones","given":"C.","email":"","middleInitial":"Nathan","affiliations":[{"id":36730,"text":"University of Alabama","active":true,"usgs":false}],"preferred":false,"id":850333,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hammond, John C. 0000-0002-4935-0736","orcid":"https://orcid.org/0000-0002-4935-0736","contributorId":223108,"corporation":false,"usgs":true,"family":"Hammond","given":"John C.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":850334,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zimmer, Margaret 0000-0001-8287-1923","orcid":"https://orcid.org/0000-0001-8287-1923","contributorId":225158,"corporation":false,"usgs":false,"family":"Zimmer","given":"Margaret","affiliations":[{"id":41054,"text":"Earth and Planetary Sciences, University of California, Santa Cruz, CA, 95064, USA","active":true,"usgs":false}],"preferred":false,"id":850335,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zipper, Samuel 0000-0002-8735-5757","orcid":"https://orcid.org/0000-0002-8735-5757","contributorId":225160,"corporation":false,"usgs":false,"family":"Zipper","given":"Samuel","email":"","affiliations":[{"id":41056,"text":"Kansas Geological Survey, University of Kansas, Lawrence KS 66047, USA","active":true,"usgs":false}],"preferred":false,"id":850336,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70221670,"text":"ofr20211060 - 2021 - Estimated water withdrawals and use in Puerto Rico, 2015","interactions":[],"lastModifiedDate":"2021-07-01T11:41:28.037511","indexId":"ofr20211060","displayToPublicDate":"2021-06-30T08:33:16","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-1060","displayTitle":"Estimated Water Withdrawals and Use in Puerto Rico, 2015","title":"Estimated water withdrawals and use in Puerto Rico, 2015","docAbstract":"Water withdrawals and use in Puerto Rico for 2015 were estimated at 2,372 million gallons per day (Mgal/d), which was 21 percent less than withdrawals and use for 2010. The 2015 total water withdrawal and use estimates were the lowest since 1990 and coincided with a substantial decline of 25 percent in saline-water withdrawals for thermoelectric-power cooling processes from 2010 to 2015. Freshwater withdrawals were 671 Mgal/d, or 28 percent of total water withdrawals, and saline-water withdrawals were 1,701 Mgal/d, or 72 percent of total withdrawals. Fresh surface-water withdrawals were estimated at 548 Mgal/d, 10 percent less than in 2010, whereas fresh groundwater withdrawals were estimated at 122 Mgal/d, 2 percent less than in 2010. Saline surface-water withdrawals were 25 percent less than in 2010.
Freshwater withdrawals were greatest for public-supply water and irrigation in 2015 and, combined, accounted for 98 percent of Puerto Rico’s total freshwater withdrawals. Withdrawals in 2015 for public-supply water (576 Mgal/d) were 14 percent lower and withdrawals for irrigation (78 Mgal/d) were 104 percent greater than in 2010, possibly because of drought conditions in agricultural counties along the south and southeast coasts in 2015. The sources for public-supply water withdrawals in 2015 included surface water (88 percent) and groundwater (12 percent). Withdrawals for other uses, which account for the remaining 2 percent of Puerto Rico’s total freshwater withdrawals, were lower in 2015 than in 2010; specifically, withdrawals for domestic self-supplied use decreased by 78 percent, industrial withdrawals decreased by 15 percent, and withdrawals for livestock decreased by 25 percent. Freshwater withdrawals for thermoelectric power and mining were greater in 2015 than in 2010, increasing by 23 percent and 5 percent, respectively.
The total population of Puerto Rico decreased by 7 percent from 2010 to 2015, from 3.73 million people in 2010 to 3.47 million people in 2015. The number of people who obtained potable water from public-supply water facilities in 2015 was about 3.47 million, or about 100 percent of the population of Puerto Rico.
Public-supply water deliveries for domestic use accounted for 338 Mgal/d in 2015, which is 47 percent greater than in 2010, indicating an increase in domestic per capita use from 62 to 98 gallons per person per day from 2010 to 2015. Domestic self-supplied withdrawals were estimated at 0.52 Mgal/d in 2015, for an estimated 4,708 people (less than 1 percent of Puerto Rico’s population). All domestic self-supplied withdrawals were assumed to be from groundwater sources.
Irrigation freshwater withdrawals were 78 Mgal/d in 2015 and accounted for 12 percent of the total freshwater withdrawals for all uses. Surface-water deliveries from irrigation districts accounted for 44 percent of total irrigation withdrawals, whereas groundwater withdrawals accounted for 56 percent. About 37,000 acres were irrigated in 2015, a decrease of 11 percent or about 4,000 acres compared to 2010. About 99 percent of the acreage was irrigated by micro-irrigation and sprinkler systems in 2015. About 65 percent of the irrigation withdrawals were accounted for by four municipalities: Santa Isabel, Salinas, Lajas, and Juana Díaz.
Altogether, freshwater withdrawals for livestock, industrial, mining, and thermoelectric power accounted for 2 percent (16.2 Mgal/d) of freshwater withdrawals for all uses, 9 percent less than in 2010. About 71 percent of the freshwater withdrawn for these categories was from groundwater sources.
In 2015, 50 percent of the total freshwater withdrawn in Puerto Rico was apportioned to six municipalities: Arecibo, Trujillo Alto, Toa Alta, Villalba, Aguada, and Mayagüez. Arecibo accounted for about 18 percent of the total freshwater withdrawals, predominantly for public-supply water use. Trujillo Alto, Toa Alta, Villalba, Aguada, and Mayagüez accounted for about 32 percent (213 Mgal/d) of the total freshwater withdrawals, which were predominantly for public-supply water uses. Withdrawals in some of these municipalities are subsequently distributed to other municipalities such as those in the San Juan metro area. The Puerto Rico Aqueduct and Sewer Authority water service area for the San Juan metro area (referred to as W–102) accounted for about 28 percent of the total water delivered from public-supply water facilities to domestic users, which includes about 34 percent of the total population of Puerto Rico.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211060","collaboration":"Prepared in cooperation with the Puerto Rico Aqueduct and Sewer Authority and the Puerto Rico Environmental Quality Board","usgsCitation":"Molina-Rivera, W.L., and Irizarry-Ortiz, M.M., 2021, Estimated water withdrawals and use in Puerto Rico, 2015: U.S. Geological Survey Open-File Report 2021–1060, 38 p., https://doi.org/10.3133/ofr20211060.","productDescription":"Report: vii, 38 p.; Data Release","numberOfPages":"50","onlineOnly":"Y","ipdsId":"IP-096352","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":386796,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9POVNC6","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Spatial and tabular datasets of water withdrawals and use in Puerto Rico, 2015"},{"id":386795,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1060/ofr20211060.pdf","text":"Report","size":"6.10 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021–1060"},{"id":386794,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1060/coverthb.jpg"}],"country":"United States","otherGeospatial":"Puerto Rico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -67.445068359375,\n 17.764381077782076\n ],\n [\n -65.1873779296875,\n 17.764381077782076\n ],\n [\n -65.1873779296875,\n 18.651449894396634\n ],\n [\n -67.445068359375,\n 18.651449894396634\n ],\n [\n -67.445068359375,\n 17.764381077782076\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
Plant community response to climate change will be influenced by individual plant responses that emerge from competition for limiting resources that fluctuate through time and vary across space. Projecting these responses requires an approach that integrates environmental conditions and species interactions that result from future climatic variability. Dryland plant communities are being substantially affected by climate change because their structure and function are closely tied to precipitation and temperature, yet impacts vary substantially due to environmental heterogeneity, especially in topographically complex regions. Here, we quantified the effects of climate change on big sagebrush (Artemisia tridentata Nutt.) plant communities that span 76 million ha in the western United States. We used an individual-based plant simulation model that represents intra- and inter-specific competition for water availability, which is represented by a process-based soil water balance model. For dominant plant functional types, we quantified changes in biomass and characterized agreement among 52 future climate scenarios. We then used a multivariate matching algorithm to generate fine-scale interpolated surfaces of functional type biomass for our study area. Results suggest geographically divergent responses of big sagebrush to climate change (changes in biomass of −20% to +27%), declines in perennial C3 grass and perennial forb biomass in most sites, and widespread, consistent, and sometimes large increases in perennial C4 grasses. The largest declines in big sagebrush, perennial C3 grass and perennial forb biomass were simulated in warm, dry sites. In contrast, we simulated no change or increases in functional type biomass in cold, moist sites. There was high agreement among climate scenarios on climate change impacts to functional type biomass, except for big sagebrush. Collectively, these results suggest divergent responses to warming in moisture-limited versus temperature-limited sites and potential shifts in the relative importance of some of the dominant functional types that result from competition for limiting resources.
The emerging amphibian pathogen Batrachochytrium salamandrivorans (Bsal) is a severe threat to global urodelan (salamanders, newts, and related taxa) biodiversity. Bsal has not been detected, to date, in North America, but the risk is high because North America is one of the global hotspots for urodelan biodiversity. The North American and United States response to the discovery of Bsal in Europe was to take a risk-based approach to preventive management actions, including interim regulations on importation of captive salamanders and a large-scale surveillance effort. Risk-based approaches to decision-making can extend to adaptive management cycles by periodically incorporating new information that reduces uncertainty in an estimate of risk or to assess the effect of mitigation actions which reduce risk directly. Our objectives were to evaluate the effects of regulatory action on the introduction of Bsal to the U.S., quantify how a large-scale surveillance effort impacted consequence risk, and to combine other new information on species susceptibility to re-evaluate Bsal risk to the U.S. Import regulations effectively reduced import volume of targeted species, but new research on species susceptibility suggests the list of regulated species was incomplete regarding Bsal reservoir species. Not detecting Bsal in an intensive surveillance effort improved confidence that Bsal was not present, however, the overall risk-reduction impact was limited because of the expansive area of interest (conterminous United States) and limited time frame of sampling. Overall, the preventive actions in response to the Bsal threat did reduce Bsal risk in the U.S. and we present an updated risk assessment to provide information for adaptive decision-making.
In this paper, we present an analysis using unsupervised machine learning (ML) to identify the key geologic factors that contribute to the geothermal production in Brady geothermal field. Brady is a hydrothermal system in northwestern Nevada that supports both electricity production and direct use of hydrothermal fluids. Transmissive fluid-flow pathways are relatively rare in the subsurface, but are critical components of hydrothermal systems like Brady and many other types of fluid-flow systems in fractured rock. Here, we analyze geologic data with ML methods to unravel the local geologic controls on these pathways. The ML method, non-negative matrix factorization with k-means clustering (NMFk), is applied to a library of 14 3D geologic characteristics hypothesized to control hydrothermal circulation in the Brady geothermal field. Our results indicate that macro-scale faults and a local step-over in the fault system preferentially occur along production wells when compared to injection wells and non-productive wells. We infer that these are the key geologic characteristics that control the through-going hydrothermal transmission pathways at Brady. Our results demonstrate: (1) the specific geologic controls on the Brady hydrothermal system and (2) the efficacy of pairing ML techniques with 3D geologic characterization to enhance the understanding of subsurface processes.
Detection of the earliest stages of unrest is one of the most challenging and yet critically needed aspects of volcano monitoring. We investigate a sequence of five unusual long-period (LP) earthquakes that occurred in the days prior to the onset of a months-long volcano-tectonic (VT) earthquake swarm beneath Little Sitkin volcano in the Aleutian Islands during late 2012. The long-period earthquakes had two distinctive characteristics: their signals were dominated by a monochromatic spectral peak at approximately 0.57 Hz and they had impulsive P and S-wave arrivals on a seismometer located on Amchitka Island 80 km to the southeast of the volcano. In each case, the monochromatic earthquakes ended with a higher-frequency event after approximately 2 min of duration. We find evidence that the five monochromatic LP earthquakes resulted from the resonance of a tabular magma body at middle crustal depths (15 km) on the western side of Little Sitkin. Based on the resonant frequency and quality factor of the monochromatic LP earthquakes, we infer the magma body to have a lateral extent of 500 m and a thickness of 9 m. We interpret that a magmatic intrusion excited the monochromatic LP earthquakes and subsequently increased the stress beneath the volcano, leading to the onset of the shallow (<10 km depth) VT swarm five days later.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/feart.2021.689651","usgsCitation":"Haney, M.M., Buurman, H., Holtkamp, S., and McNutt, S., 2021, Monochromatic long-period seismicity prior to the 2012 earthquake swarm at Little Sitkin Volcano, Alaska: Frontiers in Earth Science, v. 9, 689651, 13 p., https://doi.org/10.3389/feart.2021.689651.","productDescription":"689651, 13 p.","ipdsId":"IP-128471","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":488700,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2021.689651","text":"Publisher Index Page"},{"id":483943,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Little Sitkin Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 178.42575763155247,\n 52.01044407625301\n ],\n [\n 178.42575763155247,\n 51.8937086668314\n ],\n [\n 178.60197822354405,\n 51.8937086668314\n ],\n [\n 178.60197822354405,\n 52.01044407625301\n ],\n [\n 178.42575763155247,\n 52.01044407625301\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"9","noUsgsAuthors":false,"publicationDate":"2021-06-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Haney, Matthew M. 0000-0003-3317-7884 mhaney@usgs.gov","orcid":"https://orcid.org/0000-0003-3317-7884","contributorId":172948,"corporation":false,"usgs":true,"family":"Haney","given":"Matthew","email":"mhaney@usgs.gov","middleInitial":"M.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":932154,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Buurman, Helena","contributorId":352827,"corporation":false,"usgs":false,"family":"Buurman","given":"Helena","affiliations":[{"id":84294,"text":"University of Alaska-Fairbanks Geophysical Institute","active":true,"usgs":false}],"preferred":false,"id":932155,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Holtkamp, Stephen","contributorId":352828,"corporation":false,"usgs":false,"family":"Holtkamp","given":"Stephen","affiliations":[{"id":84294,"text":"University of Alaska-Fairbanks Geophysical Institute","active":true,"usgs":false}],"preferred":false,"id":932156,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McNutt, Stephen","contributorId":352829,"corporation":false,"usgs":false,"family":"McNutt","given":"Stephen","affiliations":[{"id":7163,"text":"University of South Florida","active":true,"usgs":false}],"preferred":false,"id":932157,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70221893,"text":"70221893 - 2021 - Determination of burn severity models ranging from regional to continental scales for the conterminous United States","interactions":[],"lastModifiedDate":"2021-07-13T18:43:48.420401","indexId":"70221893","displayToPublicDate":"2021-06-29T13:35:52","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Determination of burn severity models ranging from regional to continental scales for the conterminous United States","docAbstract":"Identifying meaningful measures of ecological change over large areas is dependent on the quantification of robust relationships between ecological metrics and remote sensing products. Over the past several decades, ground observations of wildfire and prescribed fire severity have been acquired across hundreds of wildland fires in the United States, primarily utilizing the Composite Burn Index (CBI) plot protocol. These observations have been coupled to spaceborne passive spectral reflectance indices (e.g. Landsat-derived variations of the Normalized Burn Ratio [NBR]) to produce regression models describing their relationship. Here we develop regression models by vegetation type for multiple vegetation classification systems representing a range of spatial scales, and a decision tree framework for evaluating these regression models. Our overall goals were to determine which scale of ecological classifications provided the best estimate of burn severity from Landsat data and how to choose the best regression model. We aggregated a total of 6280 CBI plots for 234 wildland fires that burned between 1994 and 2017 and produced Landsat-derived NBR and differenced NBR (dNBR) values for each plot. We then calculated best fit linear or higher order regression equations between CBI and NBR/dNBR for each landcover classification system from smallest to largest scale: LANDFIRE Biophysical Settings (BPS), National Vegetation Classification macrogroup (NVC) landcover classifications, Omernick III, II, and I ecoregions, LANDFIRE Fire Regime Groups (FRG), and the entire conterminous United States (CONUS) dataset. The CONUS regression model goodness of fit was moderate (R2 = 0.55, P < 0.001) for dNBR and poor (R2 = 0.30, P < 0.001) for NBR. Within landcover classifications, CBI was better fit by dNBR than NBR. Finer scale regional regression models including BPS (dNBR
California has, in recent years, become a hotspot of interannual climatic variability, recording devastating climate-related disturbances with severe effects on tree resources. Understanding the patterns of tree cover change associated with these events is vital for developing strategies to sustain critical habitats of endemic and threatened vegetation communities. We assessed patterns of tree cover change, especially the effects of the 2012–2016 drought within the distribution range of blue oak (Quercus douglasii), an endemic tree species to California with a narrow geographic extent. We utilized multiple, annual land-cover and land-surface change products from the U.S. Geological Survey (USGS) Land Change Monitoring, Assessment and Projection (LCMAP) project along with climate and wildfire datasets to monitor changes in tree cover state and condition and examine their relationships with interannual climate variability between 1985 and 2016. Here, we refer to a change in tree cover class without a land-cover change to another class as “conditional change.” The unusual drought of 2012–2016, accompanied by anomalously high temperatures and vapor pressure deficit, was associated with exceptional spikes in the amount of both fire and non-fire induced tree cover loss and tree cover conditional change, especially in 2015 and 2016. Approximately 1,266 km2 of tree cover loss and 617 km2 of tree cover conditional change were recorded during that drought. Tree cover loss through medium to high severity fires was especially large in exceptionally dry and hot years. Our study demonstrates the usefulness of the LCMAP products for monitoring the effects of climatic extremes and disturbance events on both thematic and conditional land-cover change over a multi-decadal period. Our results signify that blue oak woodlands may be vulnerable to extreme climate events and changing wildfire regimes. Here, we present early evidence that frequent droughts associated with climate warming may continue to affect tree cover in this region, while drought interaction with wildfires and the resulting feedbacks may have substantial influence as well. Consequently, efforts to conserve the blue oak woodlands, and potentially other vegetation communities in the Western United States, may benefit from consideration of climate risks as well as the potential for climate-fire and vegetation feedbacks.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fclim.2021.689945","usgsCitation":"Dwomoh, F.K., Brown, J.F., Tollerud, H.J., and Auch, R.F., 2021, Hotter drought escalates tree cover declines in blue oak woodlands of California: Frontiers in Climate, v. 3, 689945, 15 p., https://doi.org/10.3389/fclim.2021.689945.","productDescription":"689945, 15 p.","ipdsId":"IP-129607","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":451715,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fclim.2021.689945","text":"Publisher Index Page"},{"id":387137,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-122.421439,37.869969],[-122.41847,37.852721],[-122.434403,37.852434],[-122.446316,37.861046],[-122.430958,37.872242],[-122.421439,37.869969]]],[[[-122.3785,37.826505],[-122.377879,37.830648],[-122.369941,37.832137],[-122.358779,37.814278],[-122.362661,37.807577],[-122.372422,37.811301],[-122.3785,37.826505]]],[[[-120.248484,33.999329],[-120.230001,34.010136],[-120.19578,34.004284],[-120.167306,34.008219],[-120.147647,34.024831],[-120.140362,34.025974],[-120.115058,34.019866],[-120.090182,34.019806],[-120.073609,34.024477],[-120.057637,34.03734],[-120.043259,34.035806],[-120.050382,34.013331],[-120.046575,34.000002],[-120.011123,33.979894],[-119.978876,33.983081],[-119.979913,33.969623],[-119.97026,33.944359],[-120.017715,33.936366],[-120.048611,33.915775],[-120.098601,33.907853],[-120.121817,33.895712],[-120.168974,33.91909],[-120.224461,33.989059],[-120.248484,33.999329]]],[[[-119.789798,34.05726],[-119.755521,34.056716],[-119.712576,34.043265],[-119.686507,34.019805],[-119.637742,34.013178],[-119.612226,34.021256],[-119.604287,34.031561],[-119.608798,34.035245],[-119.59324,34.049625],[-119.5667,34.053452],[-119.52064,34.034262],[-119.542449,34.021082],[-119.547072,34.005469],[-119.560464,33.99553],[-119.575636,33.996009],[-119.596877,33.988611],[-119.662825,33.985889],[-119.721206,33.959583],[-119.742966,33.963877],[-119.758141,33.959212],[-119.842748,33.97034],[-119.873358,33.980375],[-119.884896,34.008814],[-119.876329,34.032087],[-119.916216,34.058351],[-119.923337,34.069361],[-119.919155,34.07728],[-119.912857,34.077508],[-119.857304,34.071298],[-119.825865,34.059794],[-119.818742,34.052997],[-119.789798,34.05726]]],[[[-120.46258,34.042627],[-120.440248,34.036918],[-120.415287,34.05496],[-120.403613,34.050442],[-120.390906,34.051994],[-120.368813,34.06778],[-120.370176,34.074907],[-120.362251,34.073056],[-120.354982,34.059256],[-120.36029,34.05582],[-120.358608,34.050235],[-120.346946,34.046576],[-120.331161,34.049097],[-120.302122,34.023574],[-120.317052,34.018837],[-120.347706,34.020114],[-120.35793,34.015029],[-120.409368,34.032198],[-120.427408,34.025425],[-120.454134,34.028081],[-120.465329,34.038448],[-120.46258,34.042627]]],[[[-118.524531,32.895488],[-118.535823,32.90628],[-118.551134,32.945155],[-118.573522,32.969183],[-118.586928,33.008281],[-118.596037,33.015357],[-118.606559,33.01469],[-118.605534,33.030999],[-118.594033,33.035951],[-118.57516,33.033961],[-118.569013,33.029151],[-118.559171,33.006291],[-118.540069,32.980933],[-118.496811,32.933847],[-118.369984,32.839273],[-118.353504,32.821962],[-118.356541,32.817311],[-118.379968,32.824545],[-118.394565,32.823978],[-118.425634,32.800595],[-118.44492,32.820593],[-118.496298,32.851572],[-118.507193,32.876264],[-118.524531,32.895488]]],[[[-118.500212,33.449592],[-118.477646,33.448392],[-118.445812,33.428907],[-118.423576,33.427258],[-118.382037,33.409883],[-118.370323,33.409285],[-118.365094,33.388374],[-118.310213,33.335795],[-118.303174,33.320264],[-118.305084,33.310323],[-118.325244,33.299075],[-118.374768,33.320065],[-118.440047,33.318638],[-118.465368,33.326056],[-118.48877,33.356649],[-118.478465,33.38632],[-118.48875,33.419826],[-118.515914,33.422417],[-118.52323,33.430733],[-118.53738,33.434608],[-118.563442,33.434381],[-118.60403,33.47654],[-118.54453,33.474119],[-118.500212,33.449592]]],[[[-119.543842,33.280329],[-119.528141,33.284929],[-119.465717,33.259239],[-119.429559,33.228167],[-119.444269,33.21919],[-119.476029,33.21552],[-119.545872,33.233406],[-119.564971,33.24744],[-119.578942,33.278628],[-119.562042,33.271129],[-119.543842,33.280329]]],[[[-122.289533,42.007764],[-121.035195,41.993323],[-120.001058,41.995139],[-119.995926,40.499901],[-120.005743,39.228664],[-120.001014,38.999574],[-119.333423,38.538328],[-118.714312,38.102185],[-117.875927,37.497267],[-117.244917,37.030244],[-116.488233,36.459097],[-115.852908,35.96966],[-115.102881,35.379371],[-114.633013,35.002085],[-114.629015,34.986148],[-114.634953,34.958918],[-114.629753,34.938684],[-114.635176,34.875003],[-114.623939,34.859738],[-114.586842,34.835672],[-114.57101,34.794294],[-114.552682,34.766871],[-114.516619,34.736745],[-114.470477,34.711368],[-114.452628,34.668546],[-114.451753,34.654321],[-114.441465,34.64253],[-114.438739,34.621455],[-114.424202,34.610453],[-114.429747,34.591734],[-114.422382,34.580711],[-114.405228,34.569637],[-114.380838,34.529724],[-114.378124,34.507288],[-114.386699,34.457911],[-114.375789,34.447798],[-114.335372,34.450038],[-114.32613,34.437251],[-114.294836,34.421389],[-114.286802,34.40534],[-114.264317,34.401329],[-114.226107,34.365916],[-114.199482,34.361373],[-114.176909,34.349306],[-114.157206,34.317862],[-114.138282,34.30323],[-114.134768,34.268965],[-114.139055,34.259538],[-114.159697,34.258242],[-114.223384,34.205136],[-114.229715,34.186928],[-114.254141,34.173831],[-114.287294,34.170529],[-114.320777,34.138635],[-114.353031,34.133121],[-114.366521,34.118575],[-114.390565,34.110084],[-114.411681,34.110031],[-114.43338,34.088413],[-114.43934,34.057893],[-114.434949,34.037784],[-114.438266,34.022609],[-114.46283,34.008421],[-114.46117,33.994687],[-114.499883,33.961789],[-114.522002,33.955623],[-114.535478,33.934651],[-114.533679,33.926072],[-114.508558,33.906098],[-114.518555,33.889847],[-114.50434,33.876882],[-114.503017,33.867998],[-114.514673,33.858638],[-114.52453,33.858477],[-114.529597,33.848063],[-114.520465,33.827778],[-114.527161,33.816191],[-114.504863,33.760465],[-114.504483,33.750998],[-114.512348,33.734214],[-114.496565,33.719155],[-114.494197,33.707922],[-114.495719,33.698454],[-114.523959,33.685879],[-114.531523,33.675108],[-114.525201,33.661583],[-114.530244,33.65014],[-114.526947,33.637534],[-114.529662,33.622794],[-114.524813,33.611351],[-114.540617,33.591412],[-114.5403,33.580615],[-114.524391,33.553683],[-114.558898,33.531819],[-114.560552,33.518272],[-114.569533,33.509219],[-114.591554,33.499443],[-114.622918,33.456561],[-114.627125,33.433554],[-114.635183,33.422726],[-114.652828,33.412922],[-114.687953,33.417944],[-114.701732,33.408388],[-114.725535,33.404056],[-114.708408,33.384147],[-114.698035,33.352442],[-114.707962,33.323421],[-114.731223,33.302434],[-114.723259,33.288079],[-114.684363,33.276025],[-114.672401,33.26047],[-114.689421,33.24525],[-114.674479,33.225504],[-114.678749,33.203448],[-114.675831,33.18152],[-114.679359,33.159519],[-114.703682,33.113769],[-114.706488,33.08816],[-114.68902,33.084036],[-114.686991,33.070969],[-114.674296,33.057171],[-114.673659,33.041897],[-114.662317,33.032671],[-114.64598,33.048903],[-114.618788,33.027202],[-114.589778,33.026228],[-114.575161,33.036542],[-114.52013,33.029984],[-114.502871,33.011153],[-114.492938,32.971781],[-114.476156,32.975168],[-114.467664,32.966861],[-114.469113,32.952673],[-114.48074,32.937027],[-114.47664,32.923628],[-114.462929,32.907944],[-114.468971,32.845155],[-114.494116,32.823288],[-114.510217,32.816417],[-114.530755,32.793485],[-114.532432,32.776923],[-114.526856,32.757094],[-114.539093,32.756949],[-114.539224,32.749812],[-114.564447,32.749554],[-114.564508,32.742298],[-114.581736,32.742321],[-114.581784,32.734946],[-114.612697,32.734516],[-114.618373,32.728245],[-114.688779,32.737675],[-114.701918,32.745548],[-114.719633,32.718763],[-116.04662,32.623353],[-117.124862,32.534156],[-117.136664,32.618754],[-117.168866,32.671952],[-117.196767,32.688851],[-117.213068,32.687751],[-117.236239,32.671353],[-117.246069,32.669352],[-117.25757,32.72605],[-117.25257,32.752949],[-117.25497,32.786948],[-117.26107,32.803148],[-117.280971,32.822247],[-117.28217,32.839547],[-117.27387,32.851447],[-117.26497,32.848947],[-117.25617,32.859447],[-117.25167,32.874346],[-117.25447,32.900146],[-117.28077,33.012343],[-117.315278,33.093504],[-117.328359,33.121842],[-117.362572,33.168437],[-117.469794,33.296417],[-117.50565,33.334063],[-117.547693,33.365491],[-117.59588,33.386629],[-117.607905,33.406317],[-117.645582,33.440728],[-117.684584,33.461927],[-117.691984,33.456627],[-117.715349,33.460556],[-117.726486,33.483427],[-117.784888,33.541525],[-117.814188,33.552224],[-117.840289,33.573523],[-117.87679,33.592322],[-117.927091,33.605521],[-117.940591,33.620021],[-118.000593,33.654319],[-118.029694,33.676418],[-118.088896,33.729817],[-118.132698,33.753217],[-118.180831,33.763072],[-118.187701,33.749218],[-118.181367,33.717367],[-118.207476,33.716905],[-118.258687,33.703741],[-118.317205,33.712818],[-118.360505,33.736817],[-118.385006,33.741417],[-118.396606,33.735917],[-118.411211,33.741985],[-118.428407,33.774715],[-118.405007,33.800215],[-118.394376,33.804289],[-118.392107,33.840915],[-118.460611,33.969111],[-118.482729,33.995912],[-118.519514,34.027509],[-118.543115,34.038508],[-118.569235,34.04164],[-118.609652,34.036424],[-118.668358,34.038887],[-118.706215,34.029383],[-118.744952,34.032103],[-118.783433,34.021543],[-118.805114,34.001239],[-118.854653,34.034215],[-118.928048,34.045847],[-118.938081,34.043383],[-119.004644,34.066231],[-119.037494,34.083111],[-119.088536,34.09831],[-119.109784,34.094566],[-119.130169,34.100102],[-119.18864,34.139005],[-119.216441,34.146105],[-119.257043,34.213304],[-119.278644,34.266902],[-119.290945,34.274902],[-119.313034,34.275689],[-119.337475,34.290576],[-119.370356,34.319486],[-119.388249,34.317398],[-119.42777,34.353016],[-119.461036,34.374064],[-119.536957,34.395495],[-119.559459,34.413395],[-119.616862,34.420995],[-119.638864,34.415696],[-119.671866,34.416096],[-119.688167,34.412497],[-119.684666,34.408297],[-119.709067,34.395397],[-119.729369,34.395897],[-119.794771,34.417597],[-119.835771,34.415796],[-119.853771,34.407996],[-119.873971,34.408795],[-119.925227,34.433931],[-119.956433,34.435288],[-120.008077,34.460447],[-120.038828,34.463434],[-120.088591,34.460208],[-120.141165,34.473405],[-120.25777,34.467451],[-120.295051,34.470623],[-120.341369,34.458789],[-120.471376,34.447846],[-120.47661,34.475131],[-120.511421,34.522953],[-120.581293,34.556959],[-120.622575,34.554017],[-120.637805,34.56622],[-120.645739,34.581035],[-120.640244,34.604406],[-120.60197,34.692095],[-120.60045,34.70464],[-120.614852,34.730709],[-120.62632,34.738072],[-120.637415,34.755895],[-120.616296,34.816308],[-120.610266,34.85818],[-120.616325,34.866739],[-120.639283,34.880413],[-120.647328,34.901133],[-120.670835,34.904115],[-120.63999,35.002963],[-120.629931,35.061515],[-120.630957,35.101941],[-120.644311,35.139616],[-120.651134,35.147768],[-120.662475,35.153357],[-120.675074,35.153061],[-120.698906,35.171192],[-120.714185,35.175998],[-120.74887,35.177795],[-120.754823,35.174701],[-120.756086,35.160459],[-120.760492,35.15971],[-120.778998,35.168897],[-120.786076,35.177666],[-120.856047,35.206487],[-120.89679,35.247877],[-120.862684,35.346776],[-120.866099,35.393045],[-120.884757,35.430196],[-120.907937,35.449069],[-120.946546,35.446715],[-120.969436,35.460197],[-121.003359,35.46071],[-121.101595,35.548814],[-121.126027,35.593058],[-121.143561,35.606046],[-121.166712,35.635399],[-121.251034,35.656641],[-121.284973,35.674109],[-121.289794,35.689428],[-121.314632,35.71331],[-121.315786,35.75252],[-121.332449,35.783106],[-121.388053,35.823483],[-121.413146,35.855316],[-121.439584,35.86695],[-121.462264,35.885618],[-121.461227,35.896906],[-121.472435,35.91989],[-121.4862,35.970348],[-121.503112,36.000299],[-121.531876,36.014368],[-121.574602,36.025156],[-121.590395,36.050363],[-121.592853,36.065062],[-121.606845,36.072065],[-121.618672,36.087767],[-121.629634,36.114452],[-121.680145,36.165818],[-121.717176,36.195146],[-121.779851,36.227407],[-121.797059,36.234211],[-121.813734,36.234235],[-121.826425,36.24186],[-121.851967,36.277831],[-121.874797,36.289064],[-121.888491,36.30281],[-121.894714,36.317806],[-121.892917,36.340428],[-121.905446,36.358269],[-121.903195,36.393603],[-121.914378,36.404344],[-121.91474,36.42589],[-121.9416,36.485602],[-121.938763,36.506423],[-121.944666,36.521861],[-121.925937,36.525173],[-121.932508,36.559935],[-121.942533,36.566435],[-121.957335,36.564482],[-121.978592,36.580488],[-121.970427,36.582754],[-121.941666,36.618059],[-121.93643,36.636746],[-121.923866,36.634559],[-121.890164,36.609259],[-121.889064,36.601759],[-121.860604,36.611136],[-121.831995,36.644856],[-121.814462,36.682858],[-121.807062,36.714157],[-121.805643,36.750239],[-121.788278,36.803994],[-121.809363,36.848654],[-121.862266,36.931552],[-121.894667,36.961851],[-121.930069,36.97815],[-121.95167,36.97145],[-121.972771,36.954151],[-122.012373,36.96455],[-122.023373,36.96215],[-122.027174,36.95115],[-122.050122,36.948523],[-122.105976,36.955951],[-122.155078,36.98085],[-122.20618,37.013949],[-122.252181,37.059448],[-122.284882,37.101747],[-122.306139,37.116383],[-122.337071,37.117382],[-122.337833,37.135936],[-122.359791,37.155574],[-122.367085,37.172817],[-122.390599,37.182988],[-122.405073,37.195791],[-122.407181,37.219465],[-122.419113,37.24147],[-122.411686,37.265844],[-122.40085,37.359225],[-122.423286,37.392542],[-122.443687,37.435941],[-122.452087,37.48054],[-122.472388,37.50054],[-122.493789,37.492341],[-122.499289,37.495341],[-122.516689,37.52134],[-122.519533,37.537302],[-122.513688,37.552239],[-122.517187,37.590637],[-122.501386,37.599637],[-122.494085,37.644035],[-122.496784,37.686433],[-122.514483,37.780829],[-122.50531,37.788312],[-122.485783,37.790629],[-122.478083,37.810828],[-122.463793,37.804653],[-122.407452,37.811441],[-122.398139,37.80563],[-122.385323,37.790724],[-122.375854,37.734979],[-122.356784,37.729505],[-122.361749,37.71501],[-122.370411,37.717572],[-122.391374,37.708331],[-122.387626,37.67906],[-122.374291,37.662206],[-122.3756,37.652389],[-122.387381,37.648462],[-122.386072,37.637662],[-122.35531,37.615736],[-122.358583,37.611155],[-122.373309,37.613773],[-122.378545,37.605592],[-122.360219,37.592501],[-122.317676,37.590865],[-122.305895,37.575484],[-122.262698,37.572866],[-122.214264,37.538505],[-122.196593,37.537196],[-122.194957,37.522469],[-122.168449,37.504143],[-122.155686,37.501198],[-122.140142,37.507907],[-122.127706,37.500053],[-122.111344,37.50758],[-122.111998,37.528851],[-122.147014,37.588411],[-122.145378,37.600846],[-122.152905,37.640771],[-122.163049,37.667933],[-122.246826,37.72193],[-122.257953,37.739601],[-122.257134,37.745001],[-122.242638,37.753744],[-122.253753,37.761218],[-122.293996,37.770416],[-122.330963,37.786035],[-122.33555,37.799538],[-122.333711,37.809797],[-122.323567,37.823214],[-122.303931,37.830087],[-122.301313,37.847758],[-122.310477,37.873938],[-122.309986,37.892755],[-122.32373,37.905845],[-122.33453,37.908791],[-122.35711,37.908791],[-122.367582,37.903882],[-122.385908,37.908136],[-122.39049,37.922535],[-122.413725,37.937262],[-122.430087,37.963115],[-122.415361,37.963115],[-122.399832,37.956009],[-122.367582,37.978168],[-122.361905,37.989991],[-122.367909,38.01253],[-122.340093,38.003694],[-122.321112,38.012857],[-122.300823,38.010893],[-122.283478,38.022674],[-122.262861,38.0446],[-122.273006,38.07438],[-122.314567,38.115287],[-122.366273,38.141467],[-122.39638,38.149976],[-122.403514,38.150624],[-122.409798,38.136231],[-122.439577,38.116923],[-122.454958,38.118887],[-122.489974,38.112014],[-122.483757,38.071762],[-122.499465,38.032165],[-122.497828,38.019402],[-122.481466,38.007621],[-122.462812,38.003367],[-122.452995,37.996167],[-122.448413,37.984713],[-122.456595,37.978823],[-122.471975,37.981768],[-122.488665,37.966714],[-122.487684,37.948716],[-122.479175,37.941516],[-122.48572,37.937589],[-122.499465,37.939225],[-122.503064,37.928753],[-122.478193,37.918608],[-122.471975,37.910427],[-122.472303,37.902573],[-122.458558,37.894064],[-122.448413,37.89341],[-122.438268,37.880974],[-122.45005,37.871157],[-122.462158,37.868866],[-122.480811,37.873448],[-122.479151,37.825428],[-122.505383,37.822128],[-122.548986,37.836227],[-122.561487,37.851827],[-122.584289,37.859227],[-122.60129,37.875126],[-122.656519,37.904519],[-122.682171,37.90645],[-122.70264,37.89382],[-122.727297,37.904626],[-122.736898,37.925825],[-122.766138,37.938004],[-122.783244,37.951334],[-122.797405,37.976657],[-122.821383,37.996735],[-122.856573,38.016717],[-122.882114,38.025273],[-122.939711,38.031908],[-122.956811,38.02872],[-122.981776,38.009119],[-122.97439,37.992429],[-123.024066,37.994878],[-123.011533,38.003438],[-122.99242,38.041758],[-122.960889,38.112962],[-122.949074,38.15406],[-122.953629,38.17567],[-122.965408,38.187113],[-122.968112,38.202428],[-122.993959,38.237602],[-122.968569,38.242879],[-122.967203,38.250691],[-122.977082,38.267902],[-122.986319,38.273164],[-123.002911,38.295708],[-123.024333,38.310573],[-123.038742,38.313576],[-123.051061,38.310693],[-123.053504,38.299385],[-123.063671,38.302178],[-123.074684,38.322574],[-123.068437,38.33521],[-123.068265,38.359865],[-123.128825,38.450418],[-123.202277,38.494314],[-123.249797,38.511045],[-123.287156,38.540223],[-123.331899,38.565542],[-123.343338,38.590008],[-123.371876,38.607235],[-123.398166,38.647044],[-123.441774,38.699744],[-123.461291,38.717001],[-123.514784,38.741966],[-123.541837,38.776764],[-123.579856,38.802835],[-123.58638,38.802857],[-123.605317,38.822765],[-123.647387,38.845472],[-123.659846,38.872529],[-123.71054,38.91323],[-123.725367,38.917438],[-123.726315,38.936367],[-123.738886,38.95412],[-123.729053,38.956667],[-123.711149,38.977316],[-123.6969,39.004401],[-123.690095,39.031157],[-123.693969,39.057363],[-123.713392,39.108422],[-123.721505,39.125327],[-123.737913,39.143442],[-123.742221,39.164885],[-123.765891,39.193657],[-123.774998,39.212083],[-123.777368,39.237214],[-123.787893,39.264327],[-123.803848,39.278771],[-123.803081,39.291747],[-123.811387,39.312825],[-123.808772,39.324368],[-123.822085,39.343857],[-123.826306,39.36871],[-123.81469,39.446538],[-123.766475,39.552803],[-123.787417,39.604552],[-123.782322,39.621486],[-123.792659,39.684122],[-123.808208,39.710715],[-123.829545,39.723071],[-123.838089,39.752409],[-123.839797,39.795637],[-123.851714,39.832041],[-123.907664,39.863028],[-123.930047,39.909697],[-123.954952,39.922373],[-123.980031,39.962458],[-124.035904,40.013319],[-124.056408,40.024305],[-124.068908,40.021307],[-124.079983,40.029773],[-124.080709,40.06611],[-124.110549,40.103765],[-124.187874,40.130542],[-124.214895,40.160902],[-124.296497,40.208816],[-124.320912,40.226617],[-124.327691,40.23737],[-124.34307,40.243979],[-124.363414,40.260974],[-124.363634,40.276212],[-124.347853,40.314634],[-124.362796,40.350046],[-124.365357,40.374855],[-124.373599,40.392923],[-124.391496,40.407047],[-124.409591,40.438076],[-124.38494,40.48982],[-124.383224,40.499852],[-124.387023,40.504954],[-124.382816,40.519],[-124.329404,40.61643],[-124.158322,40.876069],[-124.137066,40.925732],[-124.118147,40.989263],[-124.112165,41.028173],[-124.125448,41.048504],[-124.138217,41.054342],[-124.153622,41.05355],[-124.154513,41.087159],[-124.160556,41.099011],[-124.159065,41.121957],[-124.165414,41.129822],[-124.158539,41.143021],[-124.149674,41.140845],[-124.1438,41.144686],[-124.106986,41.229678],[-124.072294,41.374844],[-124.063076,41.439579],[-124.066057,41.470258],[-124.081427,41.511228],[-124.081987,41.547761],[-124.092404,41.553615],[-124.101123,41.569192],[-124.097385,41.585251],[-124.100961,41.602499],[-124.114413,41.616768],[-124.120225,41.640354],[-124.135552,41.657307],[-124.147412,41.717955],[-124.164716,41.740126],[-124.17739,41.745756],[-124.194953,41.736778],[-124.23972,41.7708],[-124.248704,41.771459],[-124.255994,41.783014],[-124.245027,41.7923],[-124.230678,41.818681],[-124.208439,41.888192],[-124.203402,41.940964],[-124.204948,41.983441],[-124.211605,41.99846],[-123.656998,41.995137],[-123.624554,41.999837],[-123.347562,41.999108],[-123.145959,42.009247],[-123.045254,42.003049],[-122.893961,42.002605],[-122.289533,42.007764]]]]},\"properties\":{\"name\":\"California\",\"nation\":\"USA \"}}]}","volume":"3","noUsgsAuthors":false,"publicationDate":"2021-06-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Dwomoh, Francis K 0000-0002-5054-2276","orcid":"https://orcid.org/0000-0002-5054-2276","contributorId":260864,"corporation":false,"usgs":false,"family":"Dwomoh","given":"Francis","email":"","middleInitial":"K","affiliations":[{"id":52693,"text":"ASRC Federal","active":true,"usgs":false}],"preferred":false,"id":818996,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brown, Jesslyn F. 0000-0002-9976-1998 jfbrown@usgs.gov","orcid":"https://orcid.org/0000-0002-9976-1998","contributorId":176609,"corporation":false,"usgs":true,"family":"Brown","given":"Jesslyn","email":"jfbrown@usgs.gov","middleInitial":"F.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":818997,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tollerud, Heather J. 0000-0001-9507-4456","orcid":"https://orcid.org/0000-0001-9507-4456","contributorId":210820,"corporation":false,"usgs":true,"family":"Tollerud","given":"Heather","email":"","middleInitial":"J.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":818998,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Auch, Roger F. 0000-0002-5382-5044 auch@usgs.gov","orcid":"https://orcid.org/0000-0002-5382-5044","contributorId":667,"corporation":false,"usgs":true,"family":"Auch","given":"Roger","email":"auch@usgs.gov","middleInitial":"F.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":818999,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70223414,"text":"70223414 - 2021 - Paths to computational fluency for natural resource educators, researchers, and managers","interactions":[],"lastModifiedDate":"2021-08-26T16:21:15.327269","indexId":"70223414","displayToPublicDate":"2021-06-29T11:21:04","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9155,"text":"Natural Resource Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Paths to computational fluency for natural resource educators, researchers, and managers","docAbstract":"Natural resource management and supporting research teams need computational fluency in the data and model-rich 21st century. Computational fluency describes the ability of practitioners and scientists to conduct research and represent natural systems within the computer's environment. Advancement in information synthesis for natural resource management requires more sophisticated computational approaches, as well as reproducible, reusable, extensible, and transferable methods. Despite this importance, many new and current natural resource practitioners lack computational fluency and no common set of recommended resources and practices exist for learning these skills. Broadly, attaining computational fluency entails moving beyond the simple use of computers to applying sound computational principles and methods and including computational experts (such as computer scientists) on research teams. Our path for computational fluency includes using open-source tools when possible; reproducible data management, statistics, and modeling; understanding and applying the benefits of basic computer programming to carry out more complex procedures; tracking code with version control; working in controlled computer environments; and using advanced computing resources.
","language":"English","publisher":"Wiley","doi":"10.1111/nrm.12318","usgsCitation":"Erickson, R.A., Burnett, J.L., Wiltermuth, M.T., Bulliner, E.A., and Hsu, L., 2021, Paths to computational fluency for natural resource educators, researchers, and managers: Natural Resource Modelling, v. 34, no. 3, e12318, 21 p., https://doi.org/10.1111/nrm.12318.","productDescription":"e12318, 21 p.","ipdsId":"IP-124147","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":489797,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/nrm.12318","text":"Publisher Index Page"},{"id":388550,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"34","issue":"3","noUsgsAuthors":false,"publicationDate":"2021-06-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Erickson, Richard A. 0000-0003-4649-482X rerickson@usgs.gov","orcid":"https://orcid.org/0000-0003-4649-482X","contributorId":5455,"corporation":false,"usgs":true,"family":"Erickson","given":"Richard","email":"rerickson@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":821996,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burnett, Jessica Leigh 0000-0002-0896-5099","orcid":"https://orcid.org/0000-0002-0896-5099","contributorId":248195,"corporation":false,"usgs":true,"family":"Burnett","given":"Jessica","email":"","middleInitial":"Leigh","affiliations":[{"id":38128,"text":"Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":821997,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wiltermuth, Mark T. 0000-0002-8871-2816 mwiltermuth@usgs.gov","orcid":"https://orcid.org/0000-0002-8871-2816","contributorId":708,"corporation":false,"usgs":true,"family":"Wiltermuth","given":"Mark","email":"mwiltermuth@usgs.gov","middleInitial":"T.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":821998,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bulliner, Edward A. 0000-0002-2774-9295 ebulliner@usgs.gov","orcid":"https://orcid.org/0000-0002-2774-9295","contributorId":4983,"corporation":false,"usgs":true,"family":"Bulliner","given":"Edward","email":"ebulliner@usgs.gov","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":821999,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hsu, Leslie 0000-0002-5353-807X lhsu@usgs.gov","orcid":"https://orcid.org/0000-0002-5353-807X","contributorId":191745,"corporation":false,"usgs":true,"family":"Hsu","given":"Leslie","email":"lhsu@usgs.gov","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":822000,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70234172,"text":"70234172 - 2021 - Forest thinning in the seaward fringe speeds up surface elevation increment and carbon accumulation in managed mangrove forests","interactions":[],"lastModifiedDate":"2022-08-02T16:20:52.801677","indexId":"70234172","displayToPublicDate":"2021-06-29T11:18:19","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Forest thinning in the seaward fringe speeds up surface elevation increment and carbon accumulation in managed mangrove forests","docAbstract":"Several comprehensive, data-driven geographic information system (GIS) analyses were conducted to assess prospectivity for lode gold in Alaska. These analyses use available geospatial datasets of lithologic, geochemical, mineral occurrence, and geophysical data to build models for recognizing different types of gold deposits within physiographic units defined by stream drainage basins that are approximately 100 square kilometers in area. The analytical methods successfully delineated areas in the State that contain known lode gold deposits and occurrences, providing some measure of confidence in their ability to predict gold prospectivity in areas of unknown lode gold potential. The results of our analyses indicate high prospectivity in a few areas scattered around the State that are not known to contain lode gold deposits.
In addition to assessing the potential for lode gold deposits in Alaska, we designed analyses to distinguish different lode gold deposit types, including orogenic, reduced-intrusion-related, epithermal, and gold-bearing porphyry. These can primarily be differentiated using their unique trace element geochemical fingerprints and elemental enrichments, which reflect the characteristics of the geologic environment and chemistry of the ore-forming fluids. We identified multiple parameters that would discriminate the different types of gold deposits, but owing to the limits of available data, the compositional similarity of ore-forming fluids among some types of lode gold deposits, and overlapping geologic environments, distinguishing deposit types at the state scale in Alaska remains problematic. These limitations resulted in overlapping areas of prospectivity for different deposit types, highlighting the challenges for targeted gold exploration in Alaska. Adjustment of some scoring parameters and recharacterization at smaller scales to highlight individual mineral systems for application of prospectivity analyses may be helpful at a district scale. At a regional scale, the aerial overlap of individual deposit type analyses reinforces confidence in prospectivity for a lode gold resource in a drainage basin. Our analysis for undivided lode gold deposits will be the most practical analysis for landuse decisions in which delineation of areas that have confident potential for gold deposits in general is the primary goal.
Data-driven GIS analysis for lode gold potential in Alaska, although limited by the size and uneven coverage of available datasets, objectively indicates prospectivity in areas where exposure is good as well as in areas under cover. The results of our analyses show medium to high prospectivity in areas that surround known deposits, indicating an overall expansion of areas that have the potential to contain gold deposits. Exploration in these areas may help improve the balance between the volume of gold produced in placer districts statewide and the relatively low volume of identified lode resources that contribute to these placer deposits. The results of our analyses can help focus future investigations in areas that show prospectivity but are not known to contain gold deposits, as well as in areas where data are lacking and the geology is poorly understood, and acquisition of additional data may help better define and constrain gold prospectivity.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211041","collaboration":"Prepared in cooperation with the Alaska Division of Geological & Geophysical Surveys and the Bureau of Land Management","usgsCitation":"Karl, S.M., Kreiner, D.C., Case, G.N.D., Labay, K.A., Shew, N.B., Granitto, M., Wang, B., and Anderson, E.D., 2021, GIS-based identification of areas that have resource potential for lode gold in Alaska (ver. 1.1, October 2021): U.S. Geological Survey Open-File Report 2021–1041, 75 p., 9 plates, https://doi.org/10.3133/ofr20211041.","productDescription":"Report: x, 75 p.; 9 Plates: 11.00 x 17.00 inches or smaller; Data Release; 3 Appendixes","numberOfPages":"75","additionalOnlineFiles":"Y","ipdsId":"IP-099538","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":400764,"rank":18,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/fs20223008","text":"Fact Sheet 2022-3008","description":"Karl, S.M., Kreiner, D.C., Case, G.N.D., and Labay, K., 2022, Geospatial analysis delineates lode gold prospectivity in Alaska: U.S. Geological Survey Fact Sheet 2022–3008, 4 p., https://doi.org/10.3133/fs202230008","linkHelpText":"- Geospatial Analyses Delineate Lode Gold Prospectivity in Alaska"},{"id":391052,"rank":17,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2021/1041/ofr20211041_appendix3.xlsx","text":"Appendix 3","size":"250 KB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"- Lithology-Keyword Search Terms for the “Geologic Map of Alaska”"},{"id":391050,"rank":15,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2021/1041/ofr20211041_appendix1.xlsx","text":"Appendix 1","size":"30 KB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"- Statistical Calculations of Levels of Background Values for Sediment and Rock Geochemical Data"},{"id":391049,"rank":14,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2021/1041/versionHist.txt","size":"5 KB","linkFileType":{"id":2,"text":"txt"}},{"id":386835,"rank":13,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CAM3F9","linkHelpText":"Data and results for GIS-based identification of areas that have resource potential for lode gold in Alaska"},{"id":386834,"rank":12,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2021/1041/ofr20211041_plate9.pdf","text":"Plate 9","size":"3.5 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Map Showing Overlap of Gold-bearing Porphyry-Epithermal Gold and Reduced Intrusion-related-Orogenic Gold Deposit Prospectivity Maps"},{"id":391051,"rank":16,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2021/1041/ofr20211041_appendix2.xlsx","text":"Appendix 2","size":"300 KB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"- Alaska Resource Data File (ARDF) Mineral-Deposit-Keyword-and-Scoring Templates"},{"id":386829,"rank":7,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2021/1041/ofr20211041_plate4.pdf","text":"Plate 4","size":"3.5 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Estimated Resource Potential and Certainty for Reduced Intrusion-related Gold Deposits"},{"id":386823,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1041/ofr20211041_v1.1.pdf","text":"Report","size":"2.5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":386822,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1041/covrthb.jpg"},{"id":386828,"rank":6,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2021/1041/ofr20211041_plate3.pdf","text":"Plate 3","size":"3.5 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Estimated Resource Potential and Certainty for Orogenic Gold Deposits"},{"id":386827,"rank":5,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2021/1041/ofr20211041_plate2.pdf","text":"Plate 2","size":"2.5 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Estimated Resource Potential and Certainty for Lode Gold—Undivided Deposits and Alaska Resource Data File Localities"},{"id":386824,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2021/1041/ofr20211041_plates.pdf","text":"Plates 1 through 9","size":"32 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Combined PDF of all 9 plates"},{"id":386826,"rank":4,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2021/1041/ofr20211041_plate1.pdf","text":"Plate 1","size":"3.5 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Estimated Resource Potential and Certainty for Lode Gold—Undivided Deposits"},{"id":386830,"rank":8,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2021/1041/ofr20211041_plate5.pdf","text":"Plate 5","size":"3.5 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Estimated Resource Potential and Certainty for Epithermal Gold Deposits"},{"id":386831,"rank":9,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2021/1041/ofr20211041_plate6.pdf","text":"Plate 6","size":"3.5 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Map Showing Overlap of Orogenic, Intrusion-related and Epithermal Gold Deposit Prospectivity Maps"},{"id":386832,"rank":10,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2021/1041/ofr20211041_plate7.pdf","text":"Plate 7","size":"3.5 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Estimated Resource Potential and Certainty for Combined Gold-bearing Porphyry and Epithermal Gold Deposits"},{"id":386833,"rank":11,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2021/1041/ofr20211041_plate8.pdf","text":"Plate 8","size":"3.5 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Estimated Resource Potential and Certainty for Combined Reduced Intrusion-related and Orogenic Gold Deposits"}],"country":"United States","state":"Alaska","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"properties\":{},\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-141.0007667541504,69.64681951728146],[-141.064453125,69.80172356231073],[-141.767578125,69.96043926902489],[-142.734375,70.1478274118401],[-143.26171875,70.25945200030638],[-144.99755859375,70.1925497583889],[-146.14013671875,70.21487465331137],[-147.43652343749997,70.32613725493573],[-148.40332031249997,70.51024068514326],[-149.47998046875,70.63448406630856],[-149.85351562499997,70.63448406630856],[-150.64453125,70.59802116106809],[-151.611328125,70.61261423801925],[-151.8310546875,70.7724429742589],[-152.02880859375,70.90226826757711],[-152.666015625,71.0098110139634],[-153.52294921875,71.05979781529196],[-154.31396484375,70.95969716686398],[-154.70947265625,71.20191973293133],[-155.41259765625,71.3219146980122],[-156.46728515625,71.45515260247822],[-157.10449218749997,71.34301347171373],[-157.58789062499997,71.21607526596131],[-157.91748046875,70.99550574822297],[-158.62060546875,70.9883492241249],[-159.30175781249997,70.98119010476937],[-159.98291015625,70.94535555009823],[-160.51025390625,70.73622993891799],[-160.90576171875,70.58341752317065],[-161.5869140625,70.45150843439349],[-161.78466796875,70.45885925640687],[-162.5537109375,70.34092679475283],[-163.05908203125,70.09552886456429],[-163.388671875,69.81689109911446],[-163.564453125,69.51914693717981],[-164.02587890625,69.15474044269264],[-164.90478515625,69.03714171275197],[-165.69580078124997,68.97416358340674],[-166.26708984375,69.01354605132325],[-166.376953125,68.80004113882613],[-166.66259765624997,68.5443150407769],[-167.1240234375,68.39918004344189],[-166.61865234375,68.17155518732503],[-166.5087890625,67.99110834539984],[-165.87158203125,67.8672645403614],[-164.61914062499997,67.47492238478702],[-164.24560546874997,67.23806155909902],[-164.091796875,67.02458758377148],[-163.10302734375,66.87834504307976],[-163.05908203125,66.73990169639414],[-162.66357421875,66.58321725728175],[-162.333984375,66.48697584176404],[-162.3779296875,66.34632215978135],[-163.2568359375,66.31103501145373],[-163.19091796875,66.55700652350038],[-163.76220703124997,66.73990169639414],[-164.46533203125,66.69647781801481],[-165.30029296875,66.55700652350038],[-166.1572265625,66.41674787052298],[-166.9482421875,66.24916310923315],[-167.3876953125,66.01801815922045],[-168.42041015625,65.56754970214311],[-168.02490234375,65.33017791526855],[-167.45361328125,65.18303007291382],[-166.9921875,64.86760781632728],[-166.7724609375,64.49172504435471],[-165.69580078124997,64.24459476798195],[-164.59716796875,64.29229248039543],[-164.13574218749997,64.26368374017731],[-163.49853515625,64.18724867664994],[-162.5537109375,64.27322328178595],[-161.82861328124997,64.24459476798195],[-161.52099609375,63.93737246791484],[-163.125,63.68524808030715],[-163.93798828125,63.41119772365924],[-164.5751953125,63.32254947641308],[-165.41015625,63.15435519659187],[-165.78369140625,62.75472592723178],[-166.26708984375,62.42090322195164],[-166.5966796875,62.155240711732425],[-166.48681640625,61.616843178481375],[-166.2451171875,61.23853141060282],[-165.849609375,60.8663124746226],[-166.5966796875,60.56537850464181],[-167.34375,60.468050120874615],[-167.80517578125,60.20707506634915],[-167.8271484375,60.09771842541544],[-167.89306640624997,59.93300042374631],[-167.03613281249997,59.712097173322924],[-166.640625,59.61221219518693],[-165.95947265624997,59.60109549032134],[-165.47607421874997,59.74532608213611],[-165.10253906249997,59.95501026206206],[-164.794921875,59.987997631212224],[-164.72900390624997,59.7563950493563],[-164.46533203125,59.54545678424146],[-163.8720703125,59.54545678424146],[-163.14697265625,59.60109549032134],[-162.26806640625,59.62332522313024],[-162.20214843749997,59.17592824927136],[-162.35595703125,58.81374171570782],[-162.57568359375,58.6769376725869],[-162.09228515625,58.39019698411526],[-161.455078125,58.39019698411526],[-160.68603515625,58.44773280389084],[-160.1806640625,58.516651799363785],[-159.71923828125,58.58543569119917],[-159.43359375,58.47072082411973],[-159.08203125,58.33256713195789],[-158.55468749999997,58.286395482881034],[-158.44482421874997,58.619777025081675],[-157.60986328125,58.52812515905843],[-158.00537109375,58.00809779306888],[-158.48876953125,57.468589192089354],[-159.49951171875,56.84897198026975],[-161.0595703125,56.389583525613055],[-164.9267578125,54.97761367069628],[-165.9814453125,54.470037612805754],[-168.55224609375,53.73571574532637],[-173.232421875,52.92215137976296],[-175.62744140624997,52.3755991766591],[-177.86865234375,52.13348804077147],[-178.9453125,50.98609893339354],[-178.00048828125,51.440312757160115],[-176.8359375,51.467696956223364],[-175.36376953125,51.7406361640977],[-171.826171875,52.119998657638156],[-167.62939453124997,52.9883372533954],[-166.728515625,53.186287573913305],[-165.9375,53.553362785528094],[-165.30029296875,53.76170183021049],[-164.3115234375,54.149567212540525],[-163.89404296875,54.29088164657006],[-163.3447265625,54.18815548107151],[-162.26806640625,54.07228265560388],[-162.09228515625,54.3549556895541],[-161.89453125,54.7246201949245],[-161.0595703125,54.80068486732233],[-160.400390625,54.67383096593114],[-159.19189453125,54.61025498157912],[-159.14794921875,55.07836723201515],[-158.79638671875,55.429013452407396],[-157.58789062499997,55.825973254619015],[-155.7421875,55.541064956111036],[-154.62158203125,56.01066647040695],[-153.47900390625,56.43820369358165],[-151.45751953125,57.397624055000456],[-151.4794921875,58.07787626787517],[-151.45751953125,58.75680543225761],[-149.74365234374997,59.38917842312835],[-148.51318359375,59.63443457494949],[-146.689453125,59.355596110016315],[-144.51416015625,59.75086102411168],[-144.3109130859375,59.87239799228177],[-143.8330078125,59.968758992382334],[-143.0694580078125,60.031929699115615],[-141.5533447265625,59.842055288480076],[-140.9051513671875,59.68160832698723],[-140.020751953125,59.478568831926395],[-139.1693115234375,59.234986238722],[-138.82873535156247,59.09138238455909],[-138.3233642578125,58.96983560365735],[-138.1146240234375,58.862064179600374],[-138.076171875,58.722598828043374],[-136.9775390625,58.19387126497797],[-136.56005859375,57.7862326105289],[-135.966796875,57.33838126552897],[-136.03271484375,57.052681978717494],[-135.81298828125,56.92099675839107],[-134.571533203125,55.8845546603819],[-134.2034912109375,55.56592203025787],[-133.8958740234375,55.263468250921285],[-133.7530517578125,55.06264118216743],[-133.6102294921875,54.64523407607479],[-133.2421875,54.635697306063854],[-130.6171417236328,54.70637513489091],[-130.62950134277344,54.72422365048395],[-130.62606811523438,54.73651472417763],[-130.65765380859375,54.762274228176494],[-130.62950134277344,54.78247406031503],[-130.5663299560547,54.79237225560392],[-130.49697875976562,54.82877675365454],[-130.42282104492188,54.87423625974835],[-130.34591674804688,54.91569803760518],[-130.27244567871094,54.97288463122321],[-130.18661499023438,55.062247951730015],[-130.18043518066406,55.091729515360875],[-130.15090942382812,55.12393783348962],[-130.14747619628906,55.14160209881279],[-130.10284423828125,55.19219635238084],[-129.97169494628906,55.28146181651345],[-129.97581481933594,55.30022902025666],[-130.02044677734375,55.33890835596374],[-130.0396728515625,55.45043679812318],[-130.0884246826172,55.496749338303694],[-130.12825012207028,55.58144971869657],[-130.10971069335938,55.68223010941079],[-130.14816284179688,55.71473455012689],[-130.15296936035156,55.7649857705176],[-130.12550354003906,55.80475427021683],[-130.0843048095703,55.82134464477078],[-130.00465393066406,55.90573012454021],[-130.00465393066406,55.9130425993163],[-130.0190734863281,55.912657766599715],[-130.00259399414062,56.00605986001467],[-130.10421752929688,56.12297419573329],[-130.24635314941406,56.09693875609652],[-130.3479766845703,56.12794955397159],[-130.42556762695312,56.14134155069025],[-130.4674530029297,56.24373146827144],[-130.55740356445312,56.249454174583384],[-130.5677032470703,56.25479459547735],[-130.62400817871094,56.2685236855868],[-130.78262329101562,56.36715174252849],[-131.08612060546875,56.40668363558357],[-131.16989135742188,56.44883107459549],[-131.473388671875,56.551913918713375],[-131.58119201660156,56.61204220477141],[-131.8352508544922,56.59843662755775],[-131.85997009277344,56.702620872371355],[-131.89979553222656,56.75347577609789],[-131.87232971191406,56.805765643008264],[-132.12432861328122,56.87374615531272],[-132.0467376708984,57.04521234171931],[-132.3687744140625,57.09149987857074],[-132.2472381591797,57.211056900559335],[-132.3680877685547,57.347273783306676],[-132.55210876464844,57.49516565182901],[-132.65853881835938,57.61562391374733],[-132.75466918945312,57.69680911844304],[-132.8693389892578,57.83853792318956],[-133.06983947753906,58.00082136594698],[-133.17283630371094,58.15404059343076],[-133.34518432617188,58.27628739957773],[-133.45985412597656,58.38731772556939],[-133.37608337402344,58.430481925680034],[-133.70567321777344,58.611194853078764],[-133.83956909179685,58.730440812979516],[-134.25979614257812,58.861354043320055],[-134.3360137939453,58.92414471817596],[-134.3140411376953,58.962755708753306],[-134.4060516357422,58.978683427688686],[-134.38133239746094,59.03878841190553],[-134.44656372070312,59.08820785301446],[-134.48501586914062,59.13121539881386],[-134.56329345703125,59.130510792073984],[-134.67933654785156,59.191757369765085],[-134.70130920410156,59.24973478117606],[-134.95742797851562,59.279914277804906],[-135.02883911132812,59.34649517787861],[-134.9897003173828,59.3877798237848],[-135.10093688964844,59.42622028594434],[-135.07827758789062,59.45275367774563],[-135.0274658203125,59.47473269180728],[-135.03021240234375,59.564245132658975],[-135.11810302734372,59.62367244601488],[-135.15586853027344,59.625061301654334],[-135.2190399169922,59.6632323288228],[-135.23345947265625,59.69650975428769],[-135.252685546875,59.69789559656873],[-135.36048889160156,59.73598378851403],[-135.4779052734375,59.79821644465919],[-135.94894409179688,59.6632323288228],[-136.1927032470703,59.63998787256213],[-136.34788513183594,59.60109549032134],[-136.25038146972656,59.56633207991906],[-136.24076843261716,59.55972296971678],[-136.24076843261716,59.52387204745182],[-136.3066864013672,59.46461714320982],[-136.36642456054688,59.4496126517294],[-136.47628784179688,59.46566371970234],[-136.46804809570312,59.28552611855346],[-136.49620056152344,59.27465233689575],[-136.4900207519531,59.26096748461385],[-136.5840911865234,59.166075318301345],[-136.8285369873047,59.16009179641602],[-136.8793487548828,59.13544273484683],[-137.28240966796875,59.0009698708429],[-137.449951171875,58.908900972391415],[-137.52548217773438,58.906418795609426],[-137.5000762939453,58.985760051467075],[-137.54127502441406,59.10478272378236],[-137.60787963867188,59.24376590151355],[-138.62617492675778,59.76746035005358],[-138.66600036621094,59.80961318716828],[-138.6797332763672,59.84481485969105],[-138.70582580566406,59.90650046741583],[-139.05258178710938,59.994179105518434],[-139.19952392578125,60.08950200748712],[-139.0711212158203,60.3187885497516],[-139.07386779785156,60.35243208301854],[-139.69253540039062,60.33544473468298],[-139.97955322265625,60.181818669034776],[-140.4595184326172,60.30858669066228],[-140.5199432373047,60.22003701633967],[-141.00128173828125,60.3058656567224],[-141.0007667541504,69.64681951728146]]]}},{\"type\":\"Feature\",\"properties\":{},\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-173.07586669921875,60.72157115165579],[-173.155517578125,60.69469537287745],[-173.15277099609375,60.64356945377967],[-173.08135986328125,60.61123754937553],[-173.04016113281247,60.58157148491742],[-173.08135986328125,60.53972302275651],[-173.089599609375,60.511343283202464],[-173.05938720703125,60.4788788301667],[-172.98248291015625,60.468050120874615],[-172.94677734374997,60.43689744859958],[-172.8424072265625,60.403001945865476],[-172.78472900390625,60.373144671593685],[-172.7105712890625,60.329667021005825],[-172.6611328125,60.3187885497516],[-172.5897216796875,60.309266913738156],[-172.49908447265625,60.31606836555203],[-172.4139404296875,60.3187885497516],[-172.35076904296875,60.3187885497516],[-172.30682373046872,60.29021531318375],[-172.2381591796875,60.29021531318375],[-172.17498779296875,60.30518536282736],[-172.2381591796875,60.333745513303114],[-172.34527587890625,60.378575303227215],[-172.364501953125,60.40164539086417],[-172.43041992187497,60.40571488624096],[-172.4798583984375,60.39757538658664],[-172.57598876953125,60.41249624776229],[-172.6556396484375,60.43689744859958],[-172.77374267578122,60.4788788301667],[-172.83416748046875,60.50052541051131],[-172.89459228515625,60.550527811064846],[-172.8863525390625,60.588316165776824],[-172.91656494140625,60.62606036274505],[-172.98797607421875,60.658377412327326],[-173.01544189453125,60.69469537287745],[-173.07586669921875,60.72157115165579]]]}},{\"type\":\"Feature\",\"properties\":{},\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-171.650390625,63.809167882566385],[-171.793212890625,63.82128765261384],[-171.80419921875,63.73147780336167],[-171.8426513671875,63.65601144183318],[-171.8865966796875,63.54365806976644],[-171.859130859375,63.42594585479083],[-171.7877197265625,63.34966546248425],[-171.62841796875,63.32501562217765],[-171.474609375,63.28306240110864],[-171.353759765625,63.29540792564745],[-171.2548828125,63.33980806067484],[-171.1395263671875,63.38413977217118],[-171.002197265625,63.389061297647125],[-170.760498046875,63.34966546248425],[-170.57373046875,63.32501562217765],[-170.41992187499997,63.27812271092345],[-170.343017578125,63.1989725264735],[-170.3594970703125,63.156835740093236],[-170.2496337890625,63.156835740093236],[-170.145263671875,63.156835740093236],[-170.0408935546875,63.14194929585152],[-169.9090576171875,63.087300267152735],[-169.8321533203125,63.03753005973634],[-169.7991943359375,62.990169510232555],[-169.8101806640625,62.95522304515911],[-169.74975585937497,62.922735326966595],[-169.617919921875,62.91523303947614],[-169.54650878906247,62.9502272814474],[-169.4915771484375,62.97270150065472],[-169.508056640625,62.99765260346662],[-169.4970703125,63.04251090966805],[-169.43664550781247,63.08978654472616],[-169.34326171874997,63.11712157280328],[-169.178466796875,63.13946747896222],[-169.1070556640625,63.14443090047572],[-168.958740234375,63.104699747121074],[-168.760986328125,63.112153479825004],[-168.67309570312497,63.203925767041305],[-168.662109375,63.26576978358972],[-168.7115478515625,63.3348780927218],[-168.92578125,63.366907787681754],[-169.07958984374997,63.366907787681754],[-169.25537109375,63.37183226679281],[-169.420166015625,63.376755901872734],[-169.5245361328125,63.389061297647125],[-169.6124267578125,63.43331707559086],[-169.705810546875,63.46278300222105],[-169.8211669921875,63.46523712749102],[-169.947509765625,63.48976680530999],[-170.0079345703125,63.59011870211632],[-170.0958251953125,63.658448979940175],[-170.2386474609375,63.704722429433225],[-170.4638671875,63.73390885572919],[-170.5902099609375,63.721751503619956],[-170.7659912109375,63.6779417467744],[-171.2164306640625,63.648697570849286],[-171.474609375,63.6779417467744],[-171.54052734375,63.75334975181205],[-171.650390625,63.809167882566385]]]}},{\"type\":\"Feature\",\"properties\":{},\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-170.40618896484375,57.022794415389725],[-170.3155517578125,57.043718234032625],[-170.22216796875,57.119841130872615],[-170.1947021484375,57.14518072479997],[-170.11505126953125,57.18985535714817],[-170.08209228515625,57.227042992549855],[-170.07110595703125,57.271618718194446],[-170.189208984375,57.23893512461504],[-170.2386474609375,57.22852971878346],[-170.32928466796875,57.22852971878346],[-170.3704833984375,57.22406936030381],[-170.49407958984375,57.20473490715757],[-170.41992187499997,57.12878649751151],[-170.364990234375,57.11387635258491],[-170.42266845703125,57.06910989239133],[-170.46112060546875,57.033257797376066],[-170.40618896484375,57.022794415389725]]]}},{\"type\":\"Feature\",\"properties\":{},\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-169.8321533203125,56.62904228542147],[-169.8211669921875,56.60486209416893],[-169.7991943359375,56.586716786451156],[-169.71405029296875,56.565536245992064],[-169.71405029296875,56.551913918713375],[-169.63165283203125,56.51707901932375],[-169.56024169921875,56.515563731608296],[-169.5025634765625,56.553427752820355],[-169.43115234375,56.58369172128337],[-169.43664550781247,56.626020608371924],[-169.56024169921875,56.63055303322322],[-169.6783447265625,56.62450967912138],[-169.8321533203125,56.62904228542147]]]}}]}","edition":"Version 1.0: Jun 2021; Version 1.1: October 2021","contact":"Director,
Alaska Science Center
U.S. Geological Survey
4210 University Drive
Anchorage, Alaska 99508
The ChemCam instrument on the Curiosity rover provides chemical compositions of Martian rocks and soils using remote laser-induced breakdown spectroscopy (LIBS). The elemental calibration is stable as a function of distance for Ti, Fe, Mg, and Ca. The calibration shows small, systematically increasing abundance trends as a function of distance for Al, Na, K, and to some extent, Si. The distance effect is known to be due to a dependence with distance on the relative strengths of atomic transition lines. Emission lines representing transitions from relatively low energy levels remain intense at longer distances while emission lines representing transitions from higher energy levels decrease in intensity more rapidly as a function of distance. The multivariate algorithms used to determine elemental compositions rely on a large number of emission lines in many cases, so rather than trying to correct all emission lines, a study was made of the predicted compositions as a function of distance, in order to determine an empirical correction. Abundance trends can be well approximated by a linear trend with distance within the ranges of abundances and distances observed up to ~6 m. Data from 11 distinct geological members and data groups of the Murray formation in Gale crater, Mars, were used to form the model, selecting the members and data groups yielding the best statistics. The model was tested using data from several targets observed from two different distances, and using data from the Kimberley formation, the composition of which is significantly different from the Murray formation, showing that the model works on other compositions beyond those used to build the model. For long-distance observations up to ~6 m, corrections can be made back to an equivalent composition at the median distance of ChemCam observations (2.6 m). The model has been validated up to 6.2 m, although ChemCam is able to observe bedrock targets to >7 m, and iron meteorites to distances of >9 m.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.sab.2021.106247","usgsCitation":"Wiens, R.C., Blazon-Brown, A.J., Melikechi, N., Frydenvang, J., Dehouck, E., Clegg, S.M., Delapp, D., Anderson, R.B., Cousin, A., and Maurice, S., 2021, Improving ChemCam LIBS long-distance elemental compositions using empirical abundance trends: Spectrochimica Acta Part B: Atomic Spectroscopy, v. 182, 106247, https://doi.org/10.1016/j.sab.2021.106247.","productDescription":"106247","ipdsId":"IP-127439","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":451723,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://insu.hal.science/insu-03672412","text":"Publisher Index Page"},{"id":410791,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Mars","volume":"182","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wiens, Roger C.","contributorId":140330,"corporation":false,"usgs":false,"family":"Wiens","given":"Roger","email":"","middleInitial":"C.","affiliations":[{"id":13447,"text":"Los Alamos National Laboratory","active":true,"usgs":false}],"preferred":false,"id":859635,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blazon-Brown, A. J.","contributorId":300205,"corporation":false,"usgs":false,"family":"Blazon-Brown","given":"A.","email":"","middleInitial":"J.","affiliations":[{"id":65042,"text":"LANL, U. Mass.","active":true,"usgs":false}],"preferred":false,"id":859636,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Melikechi, N.","contributorId":300206,"corporation":false,"usgs":false,"family":"Melikechi","given":"N.","affiliations":[{"id":65043,"text":"U. Mass.","active":true,"usgs":false}],"preferred":false,"id":859637,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Frydenvang, J.","contributorId":181927,"corporation":false,"usgs":false,"family":"Frydenvang","given":"J.","affiliations":[],"preferred":false,"id":859638,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dehouck, E.","contributorId":290073,"corporation":false,"usgs":false,"family":"Dehouck","given":"E.","affiliations":[{"id":62330,"text":"Univ. Lyon, Univ. Lyon 1, ENSL, CNRS","active":true,"usgs":false}],"preferred":false,"id":859639,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Clegg, S. M.","contributorId":300207,"corporation":false,"usgs":false,"family":"Clegg","given":"S.","email":"","middleInitial":"M.","affiliations":[{"id":27196,"text":"LANL","active":true,"usgs":false}],"preferred":false,"id":859640,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Delapp, D.","contributorId":290074,"corporation":false,"usgs":false,"family":"Delapp","given":"D.","affiliations":[{"id":62306,"text":"Space and Planetary Exploration Team, Los Alamos National Laboratory","active":true,"usgs":false}],"preferred":false,"id":859641,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Anderson, Ryan B. 0000-0003-4465-2871 rbanderson@usgs.gov","orcid":"https://orcid.org/0000-0003-4465-2871","contributorId":170054,"corporation":false,"usgs":true,"family":"Anderson","given":"Ryan","email":"rbanderson@usgs.gov","middleInitial":"B.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":859642,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Cousin, A.","contributorId":290035,"corporation":false,"usgs":false,"family":"Cousin","given":"A.","affiliations":[{"id":62314,"text":"Institut de Recherche en Astrophysique et Planétologie, Université de Toulouse","active":true,"usgs":false}],"preferred":false,"id":859643,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Maurice, S.","contributorId":296856,"corporation":false,"usgs":false,"family":"Maurice","given":"S.","affiliations":[{"id":64219,"text":"Institut de Recherche en Astrophysique et Planetologie, Universite de Toulouse 3 Paul Sabatier, CNRS, CNES","active":true,"usgs":false}],"preferred":false,"id":859644,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70221750,"text":"70221750 - 2021 - Increasing hydroperiod in a karst-depression wetland based on 165 years of simulated daily water levels","interactions":[],"lastModifiedDate":"2021-07-01T12:27:24.261014","indexId":"70221750","displayToPublicDate":"2021-06-29T07:25:03","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Increasing hydroperiod in a karst-depression wetland based on 165 years of simulated daily water levels","docAbstract":"The hydrology of seasonally inundated depression wetlands can be highly sensitive to climatic fluctuations. Hydroperiod—the number of days per year that a wetland is inundated—is often of primary ecological importance in these systems and can vary interannually depending on climate conditions. In this study we re-examined an existing hydrologic model to simulate daily water levels in Sinking Pond, a 35-hectare seasonally inundated karst-depression wetland in Tennessee, USA. We recalibrated the model using 22 years of climate and water-level observations and used the recalibrated model to reconstruct (hindcast) daily water levels over a 165-year period from 1855 to 2019. A trend analysis of the climatic data and reconstructed water levels over the hindcasting period indicated substantial increases in pond hydroperiod over time, apparently related to increasing regional precipitation. Wetland hydroperiod increased on average by 5.9 days per decade between 1920 and 2019, with a breakpoint around the year 1970. Hydroperiod changes of this magnitude may have profound consequences for wetland ecology, such as a transition from a forested wetland to a mostly open-water pond at the Sinking Pond site. More broadly, this study illustrates the needs for robust hydrologic models of depression wetlands and for consideration of model transferability in time (i.e., hindcasting and forecasting) under non-stationary hydroclimatic conditions. As climate change is expected to influence water cycles, hydrologic processes, and wetland ecohydrology in the coming decades, hydrologic model projections may become increasingly important to detect, anticipate, and potentially mitigate ecological impacts in depression wetland ecosystems.
The 55‐km‐long Sargent fault connects the creeping Calaveras fault with the locked San Andreas fault through the Santa Cruz Mountains west of Gilroy, California. The position of the Sargent fault between these two faults may have implications for slip transfer and strain accumulation between a creeping and locked fault. The detection and measurement of creep on the Sargent fault would indicate where interseismic strain is accumulating adjacent to these neighboring faults. In 1969, two alignment arrays separated by 3.7 km were installed across the central section of the Sargent fault to investigate potential creep. These arrays were measured in 1970 and 1975, and comparison of these measurements yielded a creep rate of 3.4 ± 0.6 mm/yr across two fault strands in the northern array; results from the southern array were never published. In 2019 and 2020, we resurveyed both arrays using a total station and analyzed the results to determine accumulated fault creep. Our results show that between 1970 and 2020, a period of 49.3 yr, the northern array was dextrally offset 164 ± 25 mm across the same two fault strands that were active in the 1970s, yielding an average creep rate of 3.3 ± 1.3 mm/yr. Thus, it appears that the 5 and 50 yr creep rates at this site are similar. The southern array, which may not span the entire fault zone, was dextrally offset 84 ± 13 mm across two fault strands between 1970 and 2019, yielding an average creep rate of 1.7 ± 0.8 mm/yr over 48.9 yr. These recent surveys document continued creep on the Sargent fault, which may reduce seismic strain accumulation and therefore seismic hazard. However, continued aseismic slip on this fault may result in the redistribution of stress and strain to adjacent faults and should be an area of continued study.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120210041","usgsCitation":"Mongovin, D., and Philibosian, B.E., 2021, Creep on the Sargent Fault over the past 50 yr from alignment arrays with implications for slip transfer between the Calaveras and San Andreas Faults, California: Bulletin of the Seismological Society of America, v. 111, no. 6, p. 3189-3203, https://doi.org/10.1785/0120210041.","productDescription":"15 p.","startPage":"3189","endPage":"3203","ipdsId":"IP-120386","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":386886,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sargent Fault","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.29980468749999,\n 36.31512514748051\n ],\n [\n -120.78369140624999,\n 36.31512514748051\n ],\n [\n -120.78369140624999,\n 37.23032838760387\n ],\n [\n -122.29980468749999,\n 37.23032838760387\n ],\n [\n -122.29980468749999,\n 36.31512514748051\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"111","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-06-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Mongovin, Daniel 0000-0002-1623-2637","orcid":"https://orcid.org/0000-0002-1623-2637","contributorId":255012,"corporation":false,"usgs":false,"family":"Mongovin","given":"Daniel","email":"","affiliations":[],"preferred":false,"id":818566,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Philibosian, Belle E. 0000-0003-3138-4716","orcid":"https://orcid.org/0000-0003-3138-4716","contributorId":206110,"corporation":false,"usgs":true,"family":"Philibosian","given":"Belle","email":"","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":818567,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70226817,"text":"70226817 - 2021 - Characterizing ground motion amplification by extensive flat sediments: The seismic response of the eastern U.S. Atlantic Coastal Plain strata","interactions":[],"lastModifiedDate":"2021-12-14T12:58:24.210836","indexId":"70226817","displayToPublicDate":"2021-06-29T06:56:31","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Characterizing ground motion amplification by extensive flat sediments: The seismic response of the eastern U.S. Atlantic Coastal Plain strata","docAbstract":"We examine the effects that Atlantic Coastal Plain (ACP) strata have on ground motions in the eastern and southeastern United States. The ACP strata consist of widespread, nearly flat‐lying sediments, the upper portions of which are unconsolidated or semiconsolidated. The ACP sediments are deposited primarily on crystalline basement rocks, creating large velocity and density contrasts with the underlying rocks. At 211 sites on ACP strata to thicknesses of 4000 m, we compute spectral ratios relative to the average of four bedrock sites west or northwest of the strata. Sites consist of stations of Earthscope’s USArray Transportable Array (TA), and temporary deployments in the Southeast Suture of the Atlantic Margin Experiment (SESAME), Eastern North American Margin (ENAM) experiment, and the DCShake deployment in Washington, D.C. For the TA and SESAME stations, we use signals from 13 teleseisms and three regional earthquakes as input, combining the north and east components of motion after taking the Fourier transforms. We also include similarly processed site responses from the ENAM and DCShake arrays that were computed in earlier studies. Results show prominent, fundamental resonance peaks at frequencies determined by reverberations in the entire sediment column, and that often define the largest amplifications for each frequency. As frequencies increase, these resonance peaks migrate to thinner ACP strata and increase in amplitude. The peaks are well defined at frequencies below about 1 Hz, but become narrower and less defined regionally at higher frequencies. We develop simple equations to characterize amplification versus ACP thickness, which we approximate by cosine and Gaussian curves with amplifications of 1 on bedrock and rising to the resonance peak, and then decreasing to an average amplification at thicknesses greater than twice the resonance peak. Comparisons with other site corrections for the central and eastern United States based on sediment thickness show similarities on thin ACP strata but divergence on thicker sediments. The results also demonstrate the effectiveness of using teleseismic arrivals to characterize the site responses of sedimentary sequences.
Daily mean streamflow data from 28 U.S. Geological Survey streamflow-gaging stations in Puerto Rico with 10 or more years of unregulated or minimally affected flow record through water year 2018 were used to develop regression equations for flow duration and annual n-day low-flow statistics. Ordinary least-squares and generalized least-squares regression techniques were used to develop regional regression equations for flow-duration statistics at the 99th, 98th, 95th, 90th, 80th, 70th, 60th, and 50th percent exceedance probabilities and annual n-day low-flow frequency statistics for the 1-, 7-, 14-, and 30-day mean low flows with the 2-year (0.5 nonexceedance probability), 5-year (0.2 nonexceedance probability), and 10-year (0.1 nonexceedance probability) recurrence intervals. A StreamStats web application was developed to estimate basin and climatic characteristics for the regional regression equation analysis. Basin and climatic characteristics determined to be significant explanatory variables in one or more regression equations included drainage area, mean total annual reference evapotranspiration, and minimum basin elevation. The adjusted coefficient of determination for the flow-duration regression equations ranged from 57.7 to 81.4 percent. The pseudo coefficient of determination for the annual n-day low-flow regression equations ranged from 64.6 to 70.7 percent. The StreamStats web application incorporates the flow duration, and annual n-day low-flow regression equations and can provide streamflow estimates for most ungaged sites in the island.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215054","collaboration":"Prepared in cooperation with the Puerto Rico Environmental Quality Board","usgsCitation":"Williams-Sether, T., 2021, Estimating flow-duration statistics and low-flow frequencies for selected streams and the implementation of a StreamStats web-based tool in Puerto Rico: U.S. Geological Survey Scientific Investigations Report 2021–5054, 18 p., https://doi.org/10.3133/sir20215054.","productDescription":"Report: v, 17 p.; Data Release; Dataset","numberOfPages":"28","onlineOnly":"Y","ipdsId":"IP-118184","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":386816,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5054/coverthb.jpg"},{"id":386817,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5054/sir20215054.pdf","text":"Report","size":"5.32 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5054"},{"id":386819,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","linkHelpText":"— USGS water data for the Nation"},{"id":386818,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Y2QVJ6","text":"USGS data release","linkHelpText":"Data files for the development of regression equations for flow-duration statistics and n-day low-flow frequencies for ungaged streams in Puerto Rico through water year 2018"}],"country":"United States","state":"Puerto Rico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -67.3187255859375,\n 17.85590441431915\n ],\n [\n -65.5828857421875,\n 17.85590441431915\n ],\n [\n -65.5828857421875,\n 18.557739984085266\n ],\n [\n -67.3187255859375,\n 18.557739984085266\n ],\n [\n -67.3187255859375,\n 17.85590441431915\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Dakota Water Science Center
U.S. Geological Survey
821 East Interstate Avenue, Bismarck, ND 58503
1608 Mountain View Road, Rapid City, SD 57702