The opossum shrimp, Mysis diluviana, is an important member of the offshore food webs of the Laurentian Great Lakes, but its response to ecosystem changes that have occurred over the past several decades is not well understood. We combined the data of four long-term sampling programs, adding several years of data (post and prior) to previously published analyses to offer a longer-term, cross-basin analysis of M. diluviana populations in the Great Lakes from 1997 to 2019. Densities were high in lakes Superior and Ontario (summer values 100–300/m2), high and variable but declining (from 200–300/m2 in 1997–2004 to less than 100/m2 in 2017–2019) in Lake Michigan, low (∼20–50/m2 since 2005) in Lake Huron, and very low in shallower eastern Lake Erie (<1/m2). Biomass showed similar trends. Life history parameters (mortality, fecundity, and growth) were consistently highest in eastern Lake Erie, followed by lakes Ontario, Michigan, Huron, and Superior. Generation time was 1 year in Lake Erie and 2 years in the other lakes. Cross-basin relationships between annual M. diluviana areal densities and food indices (chlorophyll-a concentration and zooplankton biomass) were non-linear, increasing with food levels up to about 250 mysids/m2 and about 650 mg dry wt/m2. Annual growth rates were also positively correlated to both food indices in the four deep lakes, but fecundity and mortality rates were not. Our results suggest food availability is a primary factor predicting M. diluviana density and biomass. Density-dependent mortality and fish predation could explain some of the inter-lake differences, but these relationships could benefit from further investigations.
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Michigan","active":true,"usgs":false}],"preferred":false,"id":896690,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Boynton, Patrick","contributorId":334848,"corporation":false,"usgs":false,"family":"Boynton","given":"Patrick","email":"","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":896691,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Rudstam, Lars G. 0000-0002-3732-6368","orcid":"https://orcid.org/0000-0002-3732-6368","contributorId":213508,"corporation":false,"usgs":false,"family":"Rudstam","given":"Lars","email":"","middleInitial":"G.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":896692,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70249643,"text":"70249643 - 2023 - Cruise Report for NOAA Ship Nancy Foster Cruise NF-22-06","interactions":[],"lastModifiedDate":"2023-10-23T13:39:48.181636","indexId":"70249643","displayToPublicDate":"2023-09-30T08:29:02","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":17063,"text":"DWH MDBC Cruise Report","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"CR-23-03","title":"Cruise Report for NOAA Ship Nancy Foster Cruise NF-22-06","docAbstract":"Between 9 August and 1 September, 2022, the Mesophotic and Deep Benthic (MDBC) Habitat Assessment and Evaluation (HAE) and Mapping, Ground-truthing, and Predictive Habitat Modeling (MGM) projects implemented remotely operated vehicle (ROV) dives, multibeam surveys, and conductivity, temperature, depth (CTD) operations at deep-sea sites in the northern Gulf of Mexico. The primary sites selected are a region of known deep-sea coral habitats, including Deepwater Horizon (DWH) injured and reference sites at depths of 1,100–2,000 m.
The cruise includes objectives from MGM and HAE projects. Habitat characterization and analysis of biological samples collected with ROV Odysseus maintain long-term data flows and fill critical data gaps on the biology and ecology at impacted and reference sites, assess potential ongoing impacts from threats, refine predictive habitat models, help target locations for direct restoration and protection, and determine a baseline for health and condition. Multibeam echosounder data can help document the broadscale abundance and distribution of MDBC, characterize benthic habitats, and provide information that can help guide future ROV surveys.
","language":"English","publisher":"National Oceanic and Atmospheric Administration","doi":"10.25923/nwxc-ab95","usgsCitation":"Clark, R., and Demopoulos, A., 2023, Cruise Report for NOAA Ship Nancy Foster Cruise NF-22-06: DWH MDBC Cruise Report CR-23-03, 33 p., https://doi.org/10.25923/nwxc-ab95.","productDescription":"33 p.","ipdsId":"IP-153687","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":422038,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -87.5,\n 30\n ],\n [\n -91.5,\n 30\n ],\n [\n -91.5,\n 27\n ],\n [\n -87.5,\n 27\n ],\n [\n -87.5,\n 30\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Clark, Randy","contributorId":218497,"corporation":false,"usgs":false,"family":"Clark","given":"Randy","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":886574,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Demopoulos, Amanda 0000-0003-2096-4694","orcid":"https://orcid.org/0000-0003-2096-4694","contributorId":222183,"corporation":false,"usgs":true,"family":"Demopoulos","given":"Amanda","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":886575,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70260095,"text":"70260095 - 2023 - Petrology and geochronology of Cretaceous–Eocene plutonic rocks in northeastern Washington, USA: Crustal thickening, slab rollback, and origin of the Challis episode","interactions":[],"lastModifiedDate":"2024-10-28T12:02:39.587199","indexId":"70260095","displayToPublicDate":"2023-09-30T07:00:55","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1723,"text":"GSA Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Petrology and geochronology of Cretaceous–Eocene plutonic rocks in northeastern Washington, USA: Crustal thickening, slab rollback, and origin of the Challis episode","docAbstract":"Cretaceous through Eocene plutonic rocks in northeastern Washington, USA, document a 60 m.y. history of crustal thickening and subsequent collapse and extension in response to two terrane-accretion events. Rocks emplaced 113–53 Ma have increasing La/Yb ratios reflecting orogenic plateau development after arrival of the Insular terrane by 100 Ma. Plutons emplaced 52–45 Ma (the Challis episode) document collapse of this plateau and define a SW-younging age progression attributed to breakoff and rollback of the Farallon slab following accretion of the Siletzia terrane at ca. 50 Ma. All of the rocks have chemical traits of arc magmas, likely inherited from their lower-crustal sources, but low B/Be ratios and the lack of evidence for amphibole fractionation indicate the Eocene magmas formed under drier conditions than are typical of active subduction settings. These magmas also originated at greater depth (eclogitic vs. gabbroic source) and were emplaced more shallowly than the earlier ones. All rocks have overlapping Sr-Nd and O isotopic data, indicating significant contributions from older continental crust, and depleted mantle Nd model ages become older toward the east, defining three regions that correspond with previously inferred lower-crustal domains. Farallon slab rollback also drove extension (core complex formation, dike swarms) and crustal uplift, which, along with voluminous magmatism, define the Challis episode. This tectonic model is further supported by seismic tomography, which has identified remnants of a detached slab in the upper mantle beneath the region.
Streamflow monitoring networks provide information for a wide range of public interests in river and streams. A general approach to evaluate monitoring for different interests is developed to support network planning and design. The approach defines three theoretically distinct information metrics (coverage, resolution, and representation) based on the spatial distribution of a variable of interest. Coverage is the fraction of information that a network can provide about a variable when some areas are not monitored. Resolution is the information available from the network relative to the maximum information possible given the number of sites in the network. Representation is the information that a network provides about a benchmark distribution of a variable. Information is defined using Shannon entropy where the spatial discretization of a variable among spatial elements of a landscape or sites in a network indicates the uncertainty in the spatial distribution of the variable. This approach supports the design of networks for monitoring of variables with heterogeneous spatial distributions (“hot spots” and patches) that might otherwise be unmonitored because they occupy insignificant portions of the landscape. Areas where monitoring will maintain or improve the metrics serve as objective priorities for public interests in network design. The approach is demonstrated for the streamflow monitoring network operated by the United States Geological Survey during water year 2020 indicating gaps in the coverage of coastal rivers and the resolution of low flows.
The lack of contemporary data on contaminants in resident fish prevents an analysis of temporal trends in contaminant concentrations and the present-day status of the “Restrictions on Fish and Wildlife Consumption” Beneficial Use Impairment (BUI) in the Niagara River Area of Concern (AOC). During 2018, concentrations of 260 contaminants in four groups of fish species from five areas in or near the upper Niagara River AOC were analyzed to determine the potential risks from fish consumption, responses to remediation in an adjacent AOC, and whether additional remedial actions were warranted in this AOC. The concentrations of most contaminants were generally undetectable or did not exceed established Federal, State, or European Union fish-consumption limits. Several contaminants without State or Federal limits exceeded European Union fish-consumption guidelines in some species and areas. High PCB residues in many bullhead from Scajaquada Creek, some bass from Hoyt Lake, and most common carp from all areas surpassed certain New York and Federal fish-consumption limits and indicate PCBs continue to restrict fish consumption at most study areas. High concentrations of several contaminants in resident fish, especially dioxins and furans in carp, from Cayuga Creek indicate that additional scrutiny of consumption advisories is warranted in this area. Because this study provides a snapshot in time of fish-contaminant data from five areas, additional data from other areas and times, and more detailed information on present-day pollutant sources may be needed before determining the status of the fish-consumption BUI in this AOC.
Current methods for determining the 1-percent annual exceedance probability (AEP) for a streamflow assume stationarity (the assumption that the statistical distribution of data from past observations does not contain trends and will continue unchanged in the future). This assumption allows the 1-percent AEP to be determined based on historical streamflow records. However, the assumption of stationarity is challenged by observed trends in streamflow records.
In response, the U.S. Geological Survey, in cooperation with the Federal Emergency Management Agency, studied potential changes to the 1-percent AEP streamflows at streamgages in the Housatonic River watershed in Massachusetts, Connecticut, and New York. The study used the Precipitation-Runoff Modeling System—a deterministic hydrologic model. Climate inputs to the model of temperature and precipitation were scaled to anticipated changes based on global climate models that could occur in 2030, 2050, and 2100. The model outputs were used to characterize the 1-percent AEP streamflows for 2030, 2050, and 2100 and compare the results to baseline conditions for 1950 to 2015. Results indicated that the 1-percent AEP streamflow for unregulated streams and rivers may increase from the 1950–2015 baseline period by 7.4, 11.7, and 17.3 percent in 2030, 2050, and 2100, respectively, because of climate change.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235090","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency","usgsCitation":"Olson, S.A., 2023, Characterizing changes in the 1-percent annual exceedance probability streamflows for climate-change scenarios in the Housatonic River watershed of Massachusetts, Connecticut, and New York: U.S. Geological Survey Scientific Investigations Report 2023–5090, 16 p., https://doi.org/10.3133/sir20235090.","productDescription":"Report: iv, 16 p.; Data Release","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-149676","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":501055,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115441.htm","linkFileType":{"id":5,"text":"html"}},{"id":421394,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91CSH0P","text":"USGS data release","linkHelpText":"Data for characterizing changes in the 1-percent annual exceedance probability streamflows for climate change scenarios in the Housatonic River watershed—Massachusetts, Connecticut, and New York"},{"id":421390,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5090/coverthb.jpg"},{"id":421391,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5090/sir20235090.pdf","text":"Report","size":"8.30 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023–5090"},{"id":421392,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5090/sir20235090.XML"},{"id":421393,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5090/images"},{"id":421395,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235090/full"}],"country":"United States","state":"Connecticut, Massachusetts, New York","otherGeospatial":"Housatonic River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -72.73443369971218,\n 41.34286607604693\n ],\n [\n -72.73443369971218,\n 42.92331687334064\n ],\n [\n -74.64605479346228,\n 42.92331687334064\n ],\n [\n -74.64605479346228,\n 41.34286607604693\n ],\n [\n -72.73443369971218,\n 41.34286607604693\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
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The San Francisco Bay supports thousands of breeding waterbirds annually and hosts large populations of American avocets (Recurvirostra americana), black-necked stilts (Himantopus mexicanus), and Forster’s terns (Sterna forsteri). These three species have relied largely on former commercial salt ponds in South San Francisco Bay, which provide wetland foraging habitat and island nesting habitat. The South Bay Salt Pond Restoration Project is in the process of restoring 50–90 percent of 15,100 acres of these former salt ponds to tidal marsh and tidal mudflats. Although this restoration is expected to have numerous benefits, including providing habitat for tidal wetland-dependent species, improving water quality, buffering against storm surge, and protecting inland areas from sea level rise, the reduction in former salt pond habitat and nesting islands may negatively affect breeding waterbirds. To address the reduction in former salt pond habitat available to waterbirds, the South Bay Salt Pond Restoration Project also includes enhancements to remaining pond habitat, such as the construction of new islands for nesting. Moreover, the South Bay Salt Pond Restoration Project follows an adaptive management plan in which waterbird response to the changing landscape is monitored over time to ensure that existing breeding waterbird populations are maintained. In this report, we provide results of waterbird nest monitoring in South San Francisco Bay during the 2022 breeding season and present these results in the context of annual nest monitoring in South San Francisco Bay since 2005. Overall, nest abundance in 2022 remained at or near 18-year lows for American avocets (176 nests) and black-necked stilts (97 nests), but Forster’s tern nest abundance (1,727 nests) was at an 18-year high, reversing historically low abundance observed during 2015–2017. In 2022, there were only 6 American avocet, 4 black-necked stilt, and 4 Forster’s tern major colony nesting sites, which is down from annual averages of 12.4, 6.6, and 6.6 observed during 2005–2009. Nest success (30 percent for American avocets, 29 percent for black-necked stilt, and 53 percent for Forster’s terns) was below the 2005–2007 baseline values established for the South Bay Salt Pond Restoration Project. Average egg-hatching success (98 percent, 100 percent, and 90 percent), and clutch sizes (3.68, 3.70, and 2.63 eggs) of American avocets, black-necked stilts, and Forster’s terns, respectively, were similar to values observed during 2005–2010. All three species displayed notable shifts in nest initiation dates in 2022, with American avocets and Forster’s terns nesting 10–11 days earlier and black-necked stilts nesting 10 days later than during 2005–2010. Finally, the enhanced, managed ponds with newly constructed islands (Ponds A16 and SF2) supported 86 percent of all the Forster’s tern nests recorded in South San Francisco Bay in 2022, which is the first time these managed ponds have hosted such a substantial number of tern nests.
","language":"English","publisher":"U.S. Geological Center","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231067","collaboration":"Prepared in cooperation with California State Coastal Conservancy, California Wildlife Foundation, California Department of Fish and Wildlife, U.S. Fish and Wildlife Service, and South Bay Salt Pond Restoration Project","programNote":"Ecosystems Mission Area—Species Management Research Program","usgsCitation":"Ackerman, J.T., Hartman, C.A., and Herzog, M., 2023, Monitoring nesting waterbirds for the South Bay Salt Pond Restoration Project—2022 breeding season: U.S. Geological Survey Open-File Report 2023–1067, 25 p., https://doi.org/10.3133/ofr20231067.","productDescription":"vi, 25 p.","numberOfPages":"25","onlineOnly":"Y","ipdsId":"IP-151077","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":421402,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231067/full"},{"id":421401,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1067/images"},{"id":421400,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1067/ofr20231067.xml"},{"id":421398,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1067/covrthb.jpg"},{"id":421399,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1067/ofr20231067.pdf","text":"Report","size":"9 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"California","otherGeospatial":"South Bay Salt Pond","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.11258522212694,\n 37.585319000832044\n ],\n [\n -122.11258522212694,\n 37.361346093418206\n ],\n [\n -121.87569252193163,\n 37.361346093418206\n ],\n [\n -121.87569252193163,\n 37.585319000832044\n ],\n [\n -122.11258522212694,\n 37.585319000832044\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Western Ecological Research Center
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Integrating recent scientific knowledge into management decisions supports effective natural resource management and can lead to better resource outcomes. However, finding and accessing scientific knowledge can be time consuming and costly. To assist in this process, the U.S. Geological Survey is creating a series of annotated bibliographies on topics of management concern for western lands. Previously published reports introduced a methodology for preparing annotated bibliographies to facilitate the integration of recent, peer-reviewed science into resource management decisions. Therefore, relevant text from those efforts is reproduced here to frame the presentation. Centrocercus minimus (Gunnison sage-grouse; hereafter GUSG) has been a focus of scientific investigation since the early 2000s. The U.S. Fish and Wildlife Service listed GUSG as threatened under the Endangered Species Act in 2014 because of declining populations and increasing habitat loss. The U.S. Fish and Wildlife Service, Bureau of Land Management, and Colorado Parks and Wildlife have sought to increase the conservation of this species by adapting management and recovery plans to reduce threats and increase population resiliency. GUSG are studied less than the closely related Centrocercus urophasianus (greater sage-grouse); however, research efforts have recently increased to understand the life history, genetics, and habitat suitability of this sagebrush-obligate species. We compiled and summarized peer-reviewed journal articles, data products, and formal technical reports (such as U.S. Department of Agriculture Forest Service General Technical Reports and U.S. Geological Survey Open-File Reports) on GUSG, published between January 2005 and September 2022. We first systematically searched three reference databases and three government databases using the following search phrases: “Gunnison sage-grouse” or “lesser sage-grouse” or “Gunnison grouse” or “Gunnison sage grouse” or “lesser sage grouse” or “Centrocercus minimus.” We refined the initial list of products by removing (1) duplicates, (2) publications that were not published as research, data products, or scientific review articles in peer-reviewed journals or as formal technical reports, and (3) products that did not have GUSG as a research focus or products that did not present new data or findings about GUSG. We summarized each product using a consistent structure (background, objectives, methods, location, findings, and implications) and identified the management topics (for example, population estimates or targets, habitat, and management efforts) addressed by each product. We also noted which publications included new geospatial data. The review process for this annotated bibliography included two initial internal colleague reviews of each summary, requesting input on each summary from an author of the original publication, and a formal peer review. Our initial searches resulted in 80 total products, of which 63 met our criteria for inclusion of which 53 were products that had not been summarized before. Across products summarized in the annotated bibliography, broad-scale habitat characteristics; population estimates or targets; behavior or demographics; and genetics were the most commonly addressed management topics. The bibliographies are available on the Science for Resource Managers tool (https://apps.usgs.gov/science-for-resource-managers) and are searchable by topic, location, and year, and the search tool includes links to each original publication. The studies compiled and summarized in this annotated bibliography may inform planning and management actions that seek to maintain and restore sagebrush landscapes and GUSG populations across the GUSG range.
","publisher":"U S Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231079","usgsCitation":"Maxwell, L.M., Teige, E.C., Jordan, S.E., Rutherford, T.K., Samuel, E.M., Selby, L.B., Foster, A.C., Kleist, N.J., and Carter, S.K., 2023, Annotated bibliography of scientific research on Gunnison sage-grouse published from January 2005 to September 2022: U.S. Geological Survey Open-File Report 2023–1079, 52 p., https://doi.org/10.3133/ofr20231079.","productDescription":"vii, 52 p.","onlineOnly":"Y","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":421428,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231079/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2023-1079"},{"id":421397,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1079/ofr20231079.xml"},{"id":421355,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1079/ofr20231079.pdf","text":"Report","size":"2.18 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1079"},{"id":421396,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1079/images"},{"id":421354,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1079/coverthb.jpg"}],"country":"United States","state":"Colorado","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -109.12083328575649,\n 39.47396881795231\n ],\n [\n -109.12083328575649,\n 36.98898041947241\n ],\n [\n -104.41868484825648,\n 36.98898041947241\n ],\n [\n -104.41868484825648,\n 39.47396881795231\n ],\n [\n -109.12083328575649,\n 39.47396881795231\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Fort Collins Science Center
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Ecological restoration is critical for recovering degraded ecosystems but is challenged by variable success and low predictability. Understanding which outcomes are more predictable and less variable following restoration can improve restoration effectiveness. Recent theory asserts that the predictability of outcomes would follow an order from most to least predictable from coarse to fine community properties (physical structure > taxonomic diversity > functional composition > taxonomic composition) and that predictability would increase with more severe environmental conditions constraining species establishment. We tested this “hierarchy of predictability” hypothesis by synthesizing outcomes along an aridity gradient with 11 grassland restoration projects across the United States. We used 1829 vegetation monitoring plots from 227 restoration treatments, spread across 52 sites. We fit generalized linear mixed-effects models to predict six indicators of restoration outcomes as a function of restoration characteristics (i.e., seed mixes, disturbance, management actions, time since restoration) and used variance explained by models and model residuals as proxies for restoration predictability. We did not find consistent support for our hypotheses. Physical structure was among the most predictable outcomes when the response variable was relative abundance of grasses, but unpredictable for total canopy cover. Similarly, one dimension of taxonomic composition related to species identities was unpredictable, but another dimension of taxonomic composition indicating whether exotic or native species dominated the community was highly predictable. Taxonomic diversity (i.e., species richness) and functional composition (i.e., mean trait values) were intermittently predictable. Predictability also did not increase consistently with aridity. The dimension of taxonomic composition related to the identity of species in restored communities was more predictable (i.e., smaller residuals) in more arid sites, but functional composition was less predictable (i.e., larger residuals), and other outcomes showed no significant trend. Restoration outcomes were most predictable when they related to variation in dominant species, while those responding to rare species were harder to predict, indicating a potential role of scale in restoration predictability. Overall, our results highlight additional factors that might influence restoration predictability and add support to the importance of continuous monitoring and active management beyond one-time seed addition for successful grassland restoration in the United States.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.2922","usgsCitation":"Bertuol-Garcia, D., Ladouceur, E., Brudvig, L.A., Laughlin, D.C., Munson, S.M., Curran, M.F., Davies, K.W., Svejcar, L.N., and Shackelford, N., 2023, Testing the hierarchy of predictability in grassland restoration across a gradient of environmental severity: Ecological Applications, v. 33, e2922, 21 p., https://doi.org/10.1002/eap.2922.","productDescription":"e2922, 21 p.","ipdsId":"IP-153040","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":441997,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/eap.2922","text":"Publisher Index Page"},{"id":427818,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Continental United States","geographicExtents":"{\n \"type\": 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Canada","active":true,"usgs":false}],"preferred":false,"id":898925,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ladouceur, Emma","contributorId":270938,"corporation":false,"usgs":false,"family":"Ladouceur","given":"Emma","email":"","affiliations":[{"id":56222,"text":"German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Biodiversity Synthesis & Physiological Diversity","active":true,"usgs":false}],"preferred":false,"id":898926,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brudvig, Lars A.","contributorId":335644,"corporation":false,"usgs":false,"family":"Brudvig","given":"Lars","email":"","middleInitial":"A.","affiliations":[{"id":80453,"text":"Department of Plant Biology and Program in Ecology, Evolution, and Behavior, Michigan State University, Lansing, MI, USA","active":true,"usgs":false}],"preferred":false,"id":898927,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Laughlin, Daniel C.","contributorId":200543,"corporation":false,"usgs":false,"family":"Laughlin","given":"Daniel","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":898928,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":898929,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Curran, Michael F.","contributorId":261573,"corporation":false,"usgs":false,"family":"Curran","given":"Michael","email":"","middleInitial":"F.","affiliations":[{"id":52887,"text":"Program in Ecology, University of Wyoming, 1000 E. University Avenue, Laramie, WY, USA 82071","active":true,"usgs":false}],"preferred":false,"id":898930,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Davies, Kirk W.","contributorId":255108,"corporation":false,"usgs":false,"family":"Davies","given":"Kirk","email":"","middleInitial":"W.","affiliations":[{"id":51433,"text":"Eastern Oregon Agricultural Research Center, USDA Agricultural Research Service, Burns, OR 97720 USA","active":true,"usgs":false}],"preferred":false,"id":898931,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Svejcar, Lauren N.","contributorId":127492,"corporation":false,"usgs":false,"family":"Svejcar","given":"Lauren","email":"","middleInitial":"N.","affiliations":[{"id":6973,"text":"USDA-ARS Jornada Experimental Range and Jornada Basin LTER, Las Cruces, NM; New Mexico State University, Dept. of Plant and Environmental Sciences, Las Cruces, NM","active":true,"usgs":false}],"preferred":false,"id":898932,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Shackelford, Nancy","contributorId":261567,"corporation":false,"usgs":false,"family":"Shackelford","given":"Nancy","email":"","affiliations":[{"id":52880,"text":"Ecology and Evolutionary Biology, University of Colorado Boulder, 1900 Pleasant St, Boulder, Colorado 80309, USA","active":true,"usgs":false}],"preferred":false,"id":898933,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70249184,"text":"sir20235107 - 2023 - Assessing the effects of chloride deicer applications on groundwater near the Siskiyou Pass, southwestern Oregon, July 2018–February 2021","interactions":[],"lastModifiedDate":"2025-07-28T13:13:06.240353","indexId":"sir20235107","displayToPublicDate":"2023-09-29T09:18:15","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5107","displayTitle":"Assessing the Effects of Chloride Deicer Applications on Groundwater near the Siskiyou Pass, Southwestern Oregon, July 2018–February 2021","title":"Assessing the effects of chloride deicer applications on groundwater near the Siskiyou Pass, southwestern Oregon, July 2018–February 2021","docAbstract":"The U.S. Geological Survey, in cooperation with the Oregon Department of Transportation (ODOT), evaluated the effects of cold-weather chloride deicers (road deicing chemicals) on groundwater quality, with a focus on chloride, near the Siskiyou Pass in southwestern Oregon. The study covered the period during July 2018 through February 2021. Between the years 2016 and 2020 ODOT applied up to 16,000 gallons per mile of chloride deicer and 143,000 pounds per mile of road salt along an 11-mile stretch of Interstate 5 (I-5) through the Siskiyou Pass. Despite the benefit of safer driving conditions, there are potentially negative environmental effects associated with the use of chloride-based deicers (such as magnesium chloride and sodium chloride). The results from this study are intended to help ODOT assess the water-quality effects from the application of chloride deicers at the Siskiyou Pass and inform decisions on how those chemicals are used.
Dissolved chloride concentrations tended to be greater in groundwater downgradient from I-5 compared to groundwater upgradient from the interstate. Specific conductance was a good predictor of dissolved chloride concentration (R2 = 0.905). Continuous monitoring showed that specific conductance measurements were greater at four downgradient spring-fed sites at the end of the study period compared with measurements at the beginning of the study. The study results indicate that chloride levels in shallow groundwater downgradient from I-5 are increasing, but dissolved chloride concentrations in domestic wells are not above the U.S. Environmental Protection Agency drinking water recommendations. The approach and methods used in this study, with modifications as site conditions warrant, can be applied in other areas of chloride deicer application to determine if groundwater is affected.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235107","collaboration":"Prepared in cooperation with Oregon Department of Transportation","usgsCitation":"Gingerich, S.B., Wise, D.R., and Stonewall, A.J., 2023, Assessing the effects of chloride deicer applications on groundwater near the Siskiyou Pass, southwestern Oregon, July 2018–February 2021 (ver. 1.1, July 2025): U.S. Geological Survey Scientific Investigations Report 2023–5107, 39 p., https://doi.org/10.3133/sir20235107.","productDescription":"Report: viii, 39 p.; Data Release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-140151","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":492943,"rank":5,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2023/5107/versionHistory.txt","size":"1 KB","linkFileType":{"id":2,"text":"txt"},"description":"Version history"},{"id":421408,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9D6XDIJ","text":"USGS data release","description":"USGS data release","linkHelpText":"Specific conductance and other groundwater quality data, Siskiyou Pass area, southwestern Oregon, 2018 to 2021"},{"id":421403,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5107/coverthb2.jpg"},{"id":421404,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5107/sir20235107.pdf","text":"Report","size":"7.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5107"},{"id":421405,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235107/full","text":"Report","description":"SIR 2023-5107"},{"id":421406,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5107/images"},{"id":421407,"rank":7,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5107/sir20235107.XML"},{"id":421409,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2023/5107/sir20235107_appendix1.xlsx","text":"Appendix 1","size":"45 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2023-5107 Appendix 1"}],"country":"United States","state":"Oregon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.79414603940278,\n 42.22368397834566\n ],\n [\n -122.79414603940278,\n 41.9878942723297\n ],\n [\n -122.42473672058753,\n 41.9878942723297\n ],\n [\n -122.42473672058753,\n 42.22368397834566\n ],\n [\n -122.79414603940278,\n 42.22368397834566\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Version 1.0: September 29, 2023; Version 1.1: July 25, 2025","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
601 SW 2nd Avenue, Suite 1950
Portland, OR 97204
Introduction: Large dam removals provide a restoration opportunity for shrinking coastal wetland habitats. Dam removal can increase sediment delivery to sediment-starved river deltas and estuaries by restoring natural sediment transport and mobilizing reservoir-impounded sediment. However, rapid mobilization of massive quantities of sediment stored behind large dams also constitutes a major ecological perturbation. Information is lacking on coastal habitat responses to sediment pulses of this magnitude.
Methods: Removal of two large dams along the Elwha River (Washington, USA) in 2011–2014 released ~20.5 Mt of impounded sediment, ~5.4 Mt of which were deposited in the delta and estuary (hereafter, delta). We used time series of aerial imagery, digital elevation models, and vegetation field sampling to examine plant community responses to this sediment pulse across seven years during and after dam removal.
Results: Between 2011 and 2018, the Elwha River delta increased by ~26.8 ha. Vegetation colonized ~16.4 ha of new surfaces, with mixed pioneer vegetation on supratidal beach, river bars, and river mouth bars and emergent marsh vegetation in intertidal aquatic habitats. Colonization occurred on surfaces that were higher and more stable in elevation and farther from the shoreline. Compared to established delta plant communities, vegetation on new surfaces had lower cover of dominant species and functional groups, with very low woody cover, and lower graminoid cover than dunegrass and emergent marsh communities. Over time following surface stabilization, however, vegetation on new surfaces increased in species richness, cover, and similarity to established communities. By 2018, ~1.0 ha of vegetation on new surfaces had developed into dunegrass or willow–alder communities and ~5.9 ha had developed into emergent marsh. At the same time, dam removal had few discernible effects on established delta plant communities.
Discussion: Together, these results suggest that rapid sediment mobilization during large dam removal has potential to expand coastal wetland habitat without negatively affecting established plant communities. However, as sediment loads declined in 2016–2018, new delta surfaces decreased by ~4.5 ha, and ~1.6 ha of new vegetation reverted to no vegetation. Long-term persistence of the expanded coastal habitat will depend on ongoing erosional and depositional processes under the restored natural sediment regime.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fevo.2023.1233903","usgsCitation":"Perry, L.G., Shafroth, P., Alfieri, S.J., and Miller, I.M., 2023, Coastal vegetation responses to large dam removal on the Elwha River: Frontiers in Ecology and Evolution, v. 11, 1233903, 21 p., https://doi.org/10.3389/fevo.2023.1233903.","productDescription":"1233903, 21 p.","ipdsId":"IP-153758","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":442000,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2023.1233903","text":"Publisher Index Page"},{"id":435165,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9O6NML1","text":"USGS data release","linkHelpText":"Vegetation and geomorphic surfaces in the Elwha River delta, Washington, after dam removal, derived from 2016 and 2018 aerial imagery and 2007, 2014, and 2018 field surveys"},{"id":422399,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Elwha River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.8042115532547,\n 48.18296274689851\n ],\n [\n -123.8042115532547,\n 47.722552996994835\n ],\n [\n -123.34685932477454,\n 47.722552996994835\n ],\n [\n -123.34685932477454,\n 48.18296274689851\n ],\n [\n -123.8042115532547,\n 48.18296274689851\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"11","noUsgsAuthors":false,"publicationDate":"2023-09-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Perry, Laura G.","contributorId":220048,"corporation":false,"usgs":false,"family":"Perry","given":"Laura","email":"","middleInitial":"G.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":887673,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shafroth, Patrick B. 0000-0002-6064-871X","orcid":"https://orcid.org/0000-0002-6064-871X","contributorId":225182,"corporation":false,"usgs":true,"family":"Shafroth","given":"Patrick B.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":887674,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Alfieri, Samuel J.","contributorId":329742,"corporation":false,"usgs":false,"family":"Alfieri","given":"Samuel","email":"","middleInitial":"J.","affiliations":[{"id":78705,"text":"self","active":true,"usgs":false}],"preferred":false,"id":887675,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, Ian M. 0000-0002-3289-6337","orcid":"https://orcid.org/0000-0002-3289-6337","contributorId":41951,"corporation":false,"usgs":false,"family":"Miller","given":"Ian","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":887676,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70249968,"text":"70249968 - 2023 - Biocrusts indicators of livestock grazing effects on soil stability in sagebrush steppe: A case study from a long-term experiment in the northern Great Basin","interactions":[],"lastModifiedDate":"2024-07-17T21:34:54.964345","indexId":"70249968","displayToPublicDate":"2023-09-29T07:00:32","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6002,"text":"Rangeland Ecology & Management","active":true,"publicationSubtype":{"id":10}},"title":"Biocrusts indicators of livestock grazing effects on soil stability in sagebrush steppe: A case study from a long-term experiment in the northern Great Basin","docAbstract":"Biocrusts are sensitive to changes in livestock grazing intensity in arid rangelands and may be useful indicators of ecosystem functions, particularly soil properties like soil stability, which may suggest the potential for soil erosion. We compared biocrust community composition and surface soil stability in a big sagebrush (Artemisia tridentata) steppe rangeland in the northwestern Great Basin in several paired sites, with or without long-term cattle grazing exclusion, and similar soils (mostly sandy loams), climate, and vegetation composition. We found that livestock grazing was associated with both lower surface soil stability and cover of several biocrust morphogroups, especially lichens, compared with sites with long-term livestock exclusion. Surface soil stability did not modify the effects of grazing on most biocrust components via interactive effects. Livestock grazing effects on total biocrust cover were partially mediated by changes in surface soil stability. Though lichens were more sensitive to grazing disturbance, our results suggest that moss (mostly Tortula ruralis in this site) might be a more readily observable indicator of grazing-related soil stability change in this area due to their relatively higher abundance compared with lichens (moss: mean, 8.5% cover, maximum, 96.1%, lichens: mean, 1.0% cover, maximum, 14.1%). These results highlight the potential for biocrust components as sensitive indicators of change in soil-related ecosystem functions in sagebrush steppe rangelands. However, further research is needed to identify relevant indicator groups across the wide range of biocrust community composition associated with site environmental characteristics, variable grazing systems, other rangeland health metrics, and other disturbance types such as wildfire.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rama.2023.09.001","usgsCitation":"Copeland, S., Condon, L.A., Rosentreter, R., Miller, J., and Kahn-Abrams, M., 2023, Biocrusts indicators of livestock grazing effects on soil stability in sagebrush steppe: A case study from a long-term experiment in the northern Great Basin: Rangeland Ecology & Management, v. 91, p. 82-86, https://doi.org/10.1016/j.rama.2023.09.001.","productDescription":"5 p.","startPage":"82","endPage":"86","ipdsId":"IP-147342","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":442004,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rama.2023.09.001","text":"Publisher Index Page"},{"id":422476,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Northern Great Basin","volume":"91","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Copeland, Stella M.","contributorId":196218,"corporation":false,"usgs":false,"family":"Copeland","given":"Stella M.","affiliations":[{"id":37009,"text":"USDA Agricultural Research Service","active":true,"usgs":false}],"preferred":false,"id":887850,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Condon, Lea A. 0000-0002-9357-3881","orcid":"https://orcid.org/0000-0002-9357-3881","contributorId":202908,"corporation":false,"usgs":true,"family":"Condon","given":"Lea","email":"","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":887851,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rosentreter, Roger","contributorId":257441,"corporation":false,"usgs":false,"family":"Rosentreter","given":"Roger","affiliations":[{"id":52018,"text":"Biology Department, Boise State University, Boise, Idaho","active":true,"usgs":false}],"preferred":false,"id":887852,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, Jesse","contributorId":147734,"corporation":false,"usgs":false,"family":"Miller","given":"Jesse","email":"","affiliations":[{"id":16916,"text":"Dept. of Zoology, University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":887853,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kahn-Abrams, Maya","contributorId":331492,"corporation":false,"usgs":false,"family":"Kahn-Abrams","given":"Maya","email":"","affiliations":[{"id":36589,"text":"USDA","active":true,"usgs":false}],"preferred":false,"id":887854,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70251891,"text":"70251891 - 2023 - Benchmarking satellite-derived shoreline mapping algorithms","interactions":[],"lastModifiedDate":"2024-03-05T13:03:29.556435","indexId":"70251891","displayToPublicDate":"2023-09-29T06:59:04","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":8956,"text":"Communications Earth & Environment","active":true,"publicationSubtype":{"id":10}},"title":"Benchmarking satellite-derived shoreline mapping algorithms","docAbstract":"Satellite remote sensing is becoming a widely used monitoring technique in coastal sciences. Yet, no benchmarking studies exist that compare the performance of popular satellite-derived shoreline mapping algorithms against standardized sets of inputs and validation data. Here we present a new benchmarking framework to evaluate the accuracy of shoreline change observations extracted from publicly available satellite imagery (Landsat and Sentinel-2). Accuracy and precision of five established shoreline mapping algorithms are evaluated at four sandy beaches with varying geologic and oceanographic conditions. Comparisons against long-term in situ beach surveys reveal that all algorithms provide horizontal accuracy on the order of 10 m at microtidal sites. However, accuracy deteriorates as the tidal range increases, to more than 20 m for a high-energy macrotidal beach (Truc Vert, France) with complex foreshore morphology. The goal of this open-source, collaborative benchmarking framework is to identify areas of improvement for present algorithms, while providing a stepping stone for testing future developments, and ensuring reproducibility of methods across various research groups and applications.
This report describes a sensitivity analysis of a water-budget model that was completed to identify the most important types of hydrologic information needed to reduce the uncertainty of model recharge estimates. The sensitivity of model recharge estimates for the Hawaiian Islands of Oʻahu and Maui was analyzed for seven model parameters potentially affected by land-cover changes within a watershed. The seven model parameters tested were canopy capacity, canopy-cover fraction, crop coefficient, fog-catch efficiency, root depth, stemflow, and trunk-storage capacity.
Results of the sensitivity analysis were used to (1) quantify the relative importance of the seven model parameters to recharge assessments for three moisture zones (dry, mesic, and wet) on Oʻahu and Maui and (2) prepare a list of critical information needs for each moisture zone. The list of critical information needs was developed for three general types of land cover (forest, shrubland, and grassland) that are assumed to be affected by watershed management in the Hawaiian Islands. Identified information needs included estimates or measurements of (1) evapotranspiration processes needed to determine crop coefficients for land-cover types in all moisture zones, (2) rooting depths for land-cover types in the dry and mesic moisture zones, (3) canopy-cover fraction for forests in the wet and mesic moisture zones, (4) ratios of fog interception to rainfall for forests and shrublands in the wet moisture zone, and (5) canopy capacity for forests in the wet and mesic moisture zones. The list of information needs can guide data-collection strategies of future projects. Collection and analysis of the identified hydrologic information may help model users develop a better parameterization scheme, reduce uncertainty of values that model users assign to land-cover dependent parameters, and therefore allow future applications of the water-budget model to more accurately quantify how recharge in the Hawaiian Islands might be affected by future land-cover changes within a watershed.
","language":"English","publisher":"U.S. Geological Center","publisherLocation":"Reston, VA","doi":"10.3133/sir20235022","collaboration":"Prepared in cooperation with the State of Hawai‘i Commission on Water Resource Management","usgsCitation":"Johnson, A.G., Mair, A., and Oki, D.S., 2023, Identifying the relative importance of water-budget information needed to quantify how land-cover change affects recharge, Hawaiian Islands: U.S. Geological Survey Scientific Investigations Report 2023–5022, 28 p., https://doi.org/10.3133/sir20235022.","productDescription":"Report: vi, 28 p.; Data Release","numberOfPages":"28","onlineOnly":"Y","ipdsId":"IP-129378","costCenters":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"links":[{"id":500874,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115438.htm","text":"Maui","linkFileType":{"id":5,"text":"html"}},{"id":500873,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115437.htm","text":"Oahu","linkFileType":{"id":5,"text":"html"}},{"id":421316,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9X9ZEE3","text":"USGS Data Release","description":"Johnson, A.G., and Kāne, H.L., 2023, Model subareas and moisture zones used in a sensitivity analysis of a water-budget model completed in 2022 for the islands of Oahu and Maui, Hawaii: U.S. Geological Survey data release, https://doi.org/10.5066/P9X9ZEE3.","linkHelpText":"Model subareas and moisture zones used in a sensitivity analysis of a water-budget model completed in 2022 for the islands of Oahu and Maui, Hawaii"},{"id":421315,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5022/sir20235022.pdf","text":"Report","size":"10 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":421314,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5022/covrthb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Maui, O'ahu","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -156.75858532451014,\n 21.145379373074235\n ],\n [\n -156.75858532451014,\n 20.508739201099033\n ],\n [\n -155.89066540263516,\n 20.508739201099033\n ],\n [\n -155.89066540263516,\n 21.145379373074235\n ],\n [\n -156.75858532451014,\n 21.145379373074235\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -158.3516029026351,\n 21.83029675022702\n ],\n [\n -158.3516029026351,\n 21.17099365241016\n ],\n [\n -157.59354626201016,\n 21.17099365241016\n ],\n [\n -157.59354626201016,\n 21.83029675022702\n ],\n [\n -158.3516029026351,\n 21.83029675022702\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director,
Pacific Islands Water Science Center
U.S. Geological Survey
Inouye Regional Center
1845 Wasp Blvd., B176
Honolulu, HI 96818
Most of the population of the Treasure Valley and the surrounding area of southwestern Idaho and easternmost Oregon depends on groundwater for domestic supply, either from domestic or municipal-supply wells. Current and projected rapid population growth in the area has caused concern about the long-term sustainability of the groundwater resource. In 2016, the U.S. Geological Survey, in cooperation with the Idaho Water Resource Board and the Idaho Department of Water Resources, began a project to construct a numerical groundwater-flow model of the westernmost portion of the western Snake River Plain aquifer system, called the Treasure Valley.
The development of the model was guided by several objectives, including:
The model was constructed with a spatial scale and level of detail that aimed to meet these objectives while balancing the sometimes-competing goals of fast runtimes, numerical stability, usability, and parsimony.
The Treasure Valley Groundwater Flow Model (TVGWFM) is a three-dimensional finite-difference numerical model constructed using MODFLOW 6 (Langevin and others, 2017, Documentation for the MODFLOW 6 Groundwater Flow Model: U.S. Geological Survey Techniques and Methods, book 6, chap. A55, 197 p., https://doi.org/10.3133/tm6A55). The model covers the westernmost portion of the western Snake River Plain and is discretized into a regular grid of 64 by 65 cells with a side length of 1 mile and 6 layers of varying depth and active area. A historical model period was developed consisting of 360 month-long stress periods for 1986–2015. The model builds upon previous modeling efforts by adding a transient period, incorporating new head and discharge observations to constrain parameters, incorporating information from the hydrogeologic framework model (HFM) of Bartolino (2019, Hydrogeologic framework of the Treasure Valley and surrounding area, Idaho and Oregon: U.S. Geological Survey Scientific Investigations Report 2019–5138, https://doi.org/10.3133/sir20195138) and incorporating refined estimates of evapotranspiration and irrigation classification of lands in the study area.
The TVGWFM includes all significant components of recharge to and discharge from the aquifer. Inflows include canal seepage, irrigation and precipitation recharge, mountain-front recharge, rivers and stream seepage, and seepage from Lake Lowell. Outflows include discharge to agricultural drainage ditches, discharge to rivers and streams, pumping, and discharge to Lake Lowell. Each recharge or discharge component is represented separately using individual MODFLOW 6 packages.
Parameter values were derived with a combination of trial-and-error steps and automated parameter estimation using PEST software (Doherty, J.E., 2005, PEST, model-independent parameter estimation–User manual: Watermark Numerical Computing, https://pesthomepage.org/documentation). Parameter estimates were constrained with several types of observation data, including water levels, water level changes, vertical water level differences, drain discharges, change in drain discharges, river seepage, seepage from Lake Lowell, and change in seepage from Lake Lowell. Material properties from the hydrogeologic framework were also used to assign the minimum and maximum values of some parameters.
A final parameter realization was reached that minimized residuals between the observed and modelled values for the various observation groups. Mean residuals for the observation groups were 15.4 feet (ft) for water levels, 0.2 ft for water level changes, 19.4 ft for vertical water level differences, −3.9 cubic feet per second (ft3/s) for drain discharges, 0.0 ft3/s for changes in drain discharge, 45.0 ft3/s for river seepage, −40.1 ft3/s for Lake Lowell seepage, and 126.3 ft3/s for changes in Lake Lowell seepage. The quality of the model’s fit to observations varied spatially, with notable areas of under- or over-simulation of water levels present to the northwest and southwest of Lake Lowell, in the foothills along the eastern model boundary, and near the City of Eagle. Trends were observed in the residuals of many of the observation groups, indicating that the model is missing or not fully reproducing some phenomena that are observed in the system.
The TVGWFM can be used as a tool for water resource planning, for understanding the interactions of groundwater and surface water at a basin scale, and for facilitating conjunctive management, but may lack the precision needed for water rights administration at a local scale. Additional sources of uncertainty or limitations of the model are noted. The quantity and spatial distribution of canal seepage and infiltration of irrigation water recharge, the largest sources of recharge to the system, are unknown and approximated indirectly. There is poor understanding of how canal seepage and incidental recharge change as land is converted from agricultural (irrigated) to suburban (semi-irrigated). These uncertainties will affect any scenarios that investigate changes to land use or irrigation practices. Finally, the model has relatively high water-level residuals around and to the southwest of Lake Lowell and should not be used to estimate water level effects in that region.
The model was built with multiple, broadly expressed objectives and did not optimize performance for specific uses. However, the model and the tools included in an associated data release provide ample flexibility to improve the model for future uses. Adjustments and improvements could be made by refining the model in an area of interest, collecting additional calibration data, applying more rigorous boundary conditions, or re-estimating model parameters to optimize model performance for a specific model forecast.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235096","collaboration":"Prepared in cooperation with the Idaho Water Resource Board and the Idaho Department of Water Resources","usgsCitation":"Hundt, S.A., and Bartolino, J.R., 2023, Groundwater-flow model of the Treasure Valley, southwestern Idaho, 1986–2015: U.S. Geological Survey Scientific Investigations Report 2023–5096, 107 p., https://doi.org/10.3133/sir20235096.","productDescription":"Report: xii, 107 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-127901","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":501062,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115439.htm","linkFileType":{"id":5,"text":"html"}},{"id":421318,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5096/sir20235096.pdf","text":"Report","size":"30.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5096"},{"id":421321,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5096/images"},{"id":421317,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5096/coverthb.jpg"},{"id":421320,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9U6OOPH","text":"USGS data release","description":"USGS data release","linkHelpText":"Data and archive for a groundwater flow model of the Treasure Valley aquifer system, southwestern Idaho"},{"id":421322,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5096/sir20235096.XML"}],"country":"United States","state":"Idaho","otherGeospatial":"Treasure Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.26392993194762,\n 44.27650517719664\n ],\n [\n -117.26392993194762,\n 42.71456173603502\n ],\n [\n -115.50611743194747,\n 42.71456173603502\n ],\n [\n -115.50611743194747,\n 44.27650517719664\n ],\n [\n -117.26392993194762,\n 44.27650517719664\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702-4520
The Sparta-Memphis aquifer, present across much of eastern Arkansas, is the second most used groundwater resource in the State, with the Mississippi River Valley alluvial aquifer being the primary groundwater resource. The U.S. Geological Survey, in cooperation with Arkansas Department of Agriculture-Natural Resources Division, Arkansas Geological Survey, Natural Resources Conservation Service, Union County Water Conservation Board, and the Union County Conservation District, collects groundwater data across the Sparta-Memphis aquifer extent in Arkansas. This report presents water-level data for measurements conducted during two time periods, January–May 2013 and January–June 2015, and discusses water-level altitude changes for the 2011–13 and 2013–15 periods in the Sparta-Memphis aquifer. Accompanying water-level data in this report include groundwater-quality data for the period 2010–15 in the Sparta-Memphis aquifer. Groundwater data can guide ongoing and future groundwater-monitoring efforts and inform management of the aquifers in Arkansas.
Water levels measured at 306 wells from January to May 2013 and 273 wells from January to June 2015 are graphically presented as potentiometric-surface maps. Measurements from 2011, 2013, and 2015 were used in the construction of 2011–13 and 2013–15 water-level change maps. Select long-term hydrographs are included in the report to illustrate water-level changes at the local scale.
Water-level data show the influence of climate, pumping, and conservation and management efforts on groundwater levels. With respect to climate, the study area experienced extreme drought conditions between January 2011 and December 2012. The proximate effects of drought—increased evapotranspiration, decreased recharge, and increased irrigation needs—resulted in water-level declines that were particularly notable in the northern and central portions of the study area.
Groundwater sampled in 2010–15 from 148 wells completed in the Sparta-Memphis aquifer was analyzed for specific conductance, pH, chloride (Cl) concentration, and bromide (Br) concentration. In 2015, groundwater-quality data from 103 wells completed in the Sparta-Memphis aquifer had a median specific conductance of 356 microsiemens per centimeter at 25 degrees Celsius and a median Cl concentration of 9.5 milligrams per liter (mg/L). The data show two areas of higher Cl (greater than 10 mg/L) and higher Br (greater than 0.5 mg/L) concentrations in Union, Calhoun, and Bradley Counties in southern Arkansas and Monroe and Phillips Counties in eastern-central Arkansas. A Cl and Br mixing model indicates the two regions of wells may have different sources of higher salinity. In the greater Union County area, water in most wells may be a mixture of recharge or precipitation and higher salinity groundwater from the Nacatoch aquifer. Water in wells in eastern-central Arkansas may be sourced from aquifers having a higher Cl concentration (and thus, also a higher Cl-to-Br ratio).
Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
640 Grassmere Park, Suite 100
Nashville, TN 37211
Removal of invasive Silver Carp Hypophthalmichthys molitrix is a primary control action in North America. Strong avoidance responses to underwater sound and electricity have been shown to facilitate herding and mass removal of these fish. We conducted a telemetry study on a closed population of Silver Carp (i.e., 10 telemetered fish) to assess fine-scale movement responses to herding stimuli. Two herding boats traveled along bank-to-bank transects through the study area (longitudinal progression rate = 0.37 m/s) emitting sound and electricity (“combination technique”) or no added stimuli (“control”). The combination technique was most effective in terms of increasing fish presence (2.2 x the control) in the refuge-zones when herding had concluded and effective range (i.e., fish reaction distance; 1.6 x the control) relative to the herding boats. Fish median (~1 m/s) and maximum (~2 m/s) swimming velocity was relatively stable across fixed effects, except for the negative influence of water depth on maximum velocity. Water depth also exhibited a negative effect on fish reaction distance. Our results suggest effective range of the combination technique was conservatively 200 m (~20 dB re 1 μPa > ambient level) when accounting for water depth in the study area. Herding deployments less than 1 m/s (longitudinal progression) could control fish passing and maintain fish movements towards an intended location. Information provided herein can serve to assist planning, design, and application of herding efforts used to manage, control, and remove these invasive fish.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10955","usgsCitation":"Ridgway, J.L., Acre, M.R., Hessler, T.M., Broaddus, D., Morris, J., and Calfee, R.D., 2023, Silver carp herding: A telemetry evaluation of efficacy and implications for design and application: North American Journal of Fisheries Management, v. 43, no. 6, p. 1750-1764, https://doi.org/10.1002/nafm.10955.","productDescription":"15 p.","startPage":"1750","endPage":"1764","ipdsId":"IP-144362","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":442012,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/nafm.10955","text":"Publisher Index Page"},{"id":435166,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VQECFP","text":"USGS data release","linkHelpText":"Telemetry evaluation of invasive carp herding in Jonathan Creek Embayment, Kentucky Lake, Kentucky"},{"id":422098,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kentucky","otherGeospatial":"Jonathan Creek embayment, Kentucky Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -88.19285937344272,\n 36.82937300194537\n ],\n [\n -88.22829442891907,\n 36.81640599482829\n ],\n [\n -88.24424020388349,\n 36.764718425521735\n ],\n [\n -88.21310797657148,\n 36.76046024751608\n ],\n [\n -88.19285937344272,\n 36.82937300194537\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"43","issue":"6","noUsgsAuthors":false,"publicationDate":"2023-09-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Ridgway, Josey Lee 0000-0003-4157-7255","orcid":"https://orcid.org/0000-0003-4157-7255","contributorId":238277,"corporation":false,"usgs":true,"family":"Ridgway","given":"Josey","email":"","middleInitial":"Lee","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":886803,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Acre, Matthew Ross 0000-0002-5417-9523","orcid":"https://orcid.org/0000-0002-5417-9523","contributorId":268034,"corporation":false,"usgs":true,"family":"Acre","given":"Matthew","email":"","middleInitial":"Ross","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":886804,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hessler, Tyler Michael 0000-0001-5062-2340","orcid":"https://orcid.org/0000-0001-5062-2340","contributorId":272075,"corporation":false,"usgs":true,"family":"Hessler","given":"Tyler","email":"","middleInitial":"Michael","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":886805,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Broaddus, Dustin 0000-0002-3160-0477","orcid":"https://orcid.org/0000-0002-3160-0477","contributorId":331134,"corporation":false,"usgs":true,"family":"Broaddus","given":"Dustin","email":"","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":886806,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Morris, Jessica","contributorId":331135,"corporation":false,"usgs":false,"family":"Morris","given":"Jessica","email":"","affiliations":[{"id":53972,"text":"Kentucky Department of Fish and Wildlife Resources","active":true,"usgs":false}],"preferred":false,"id":886807,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Calfee, Robin D. 0000-0001-6056-7023 rcalfee@usgs.gov","orcid":"https://orcid.org/0000-0001-6056-7023","contributorId":1841,"corporation":false,"usgs":true,"family":"Calfee","given":"Robin","email":"rcalfee@usgs.gov","middleInitial":"D.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":886808,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70249582,"text":"70249582 - 2023 - Move it or lose it: Predicted effects of culverts and population density on Mojave desert tortoise (Gopherus agassizii) connectivity","interactions":[],"lastModifiedDate":"2023-10-19T13:20:32.889322","indexId":"70249582","displayToPublicDate":"2023-09-28T06:44:34","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Move it or lose it: Predicted effects of culverts and population density on Mojave desert tortoise (Gopherus agassizii) connectivity","title":"Move it or lose it: Predicted effects of culverts and population density on Mojave desert tortoise (Gopherus agassizii) connectivity","docAbstract":"Roadways and railways can reduce wildlife movements across landscapes, negatively impacting population connectivity. Connectivity may be improved by structures that allow safe passage across linear barriers, but connectivity could be adversely influenced by low population densities. The Mojave desert tortoise is threatened by habitat loss, fragmentation, and population declines. The tortoise continues to decline as disturbance increases across the Mojave Desert in the southwestern United States. While underground crossing structures, like hydrological culverts, have begun receiving attention, population density has not been considered in tortoise connectivity. Our work asks a novel question: How do culverts and population density affect connectivity and potentially drive genetic and demographic patterns? To explore the role of culverts and population density, we used agent-based spatially explicit forward-in-time simulations of gene flow. We constructed resistance surfaces with a range of barriers to movement and representative of tortoise habitat with anthropogenic disturbance. We predicted connectivity under variable population densities. Simulations were run for 200 non-overlapping generations (3400 years) with 30 replicates using 20 microsatellite loci. We evaluated population genetic structure and diversity and found that culverts would not entirely negate the effects of linear barriers, but gene flow improved. Our results also indicated that density is important for connectivity. Low densities resulted in declines regardless of the landscape barrier scenario (> 75% population census size, > 97% effective population size). Results from our simulation using current anthropogenic disturbance predicted decreased population connectivity over time. Genetic and demographic effects were detectable within five generations (85 years) following disturbance with estimated losses in effective population size of 69%. The pronounced declines in effective population size indicate this could be a useful monitoring metric. We suggest management strategies that improve connectivity, such as roadside fencing tied to culverts, conservation areas in a connected network, and development restricted to disturbed areas.
Causes of population collapse and failed recovery often remain enigmatic in marine forage fish like Pacific herring (Clupea pallasii) that experience dramatic population oscillations. Diseases such as ichthyophoniasis are hypothesized to contribute to these declines, but lack of long-term datasets frequently prevents inference. Analysis of pathogen surveillance and population assessment datasets spanning 2007–2019 indicate that the age-based prevalence estimate of Ichthyophonus infection was, on average, 54% greater among a collapsed population of Pacific herring (Prince William Sound, Alaska, USA) as compared to a nearby population (Sitka Sound, Alaska, USA) that is relatively robust. During the study years, the age-based infection prevalence ranged from 14 to 44% in Prince William Sound and 5 to 33% in Sitka Sound. At both sites, the age-based infection prevalence declined over time, with an average decrease of 7% per year. Statistical analyses indicated that infection prevalence between the two populations was reduced by regional factors affecting both sites, and that these factors were independent of herring density. Infection prevalence in both populations was positively correlated with herring age and negatively correlated with the Pacific Decadal Oscillation. This study demonstrates how synthesis of environmental, stock assessment, and disease assessment data can be leveraged to elucidate epidemiological trends in diseases of wild fish.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/icesjms/fsad147","usgsCitation":"Groner, M., Bravo-Mendosa, E.D., MacKenzie, A., Gregg, J.L., Conway, C.M., Trochta, J.T., and Hershberger, P., 2023, Temporal, environmental, and demographic correlates of Ichthyophonus sp. infections in mature Pacific herring populations: ICES Journal of Marine Science, fsad147, 14 p., https://doi.org/10.1093/icesjms/fsad147.","productDescription":"fsad147, 14 p.","ipdsId":"IP-131654","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":442017,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/icesjms/fsad147","text":"Publisher Index Page"},{"id":421382,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2023-09-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Groner, Maya L. 0000-0002-3381-6415","orcid":"https://orcid.org/0000-0002-3381-6415","contributorId":292708,"corporation":false,"usgs":false,"family":"Groner","given":"Maya","middleInitial":"L.","affiliations":[{"id":62985,"text":"Senior Research Scientist, Bigelow Laboratory for Ocean Sciences, 60 Bigelow Drive, East Boothbay, ME 04544","active":true,"usgs":false}],"preferred":false,"id":884529,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bravo-Mendosa, Eliana D.","contributorId":330269,"corporation":false,"usgs":false,"family":"Bravo-Mendosa","given":"Eliana","email":"","middleInitial":"D.","affiliations":[{"id":78857,"text":"Previously a volunteer for the USGS Western Fisheries Research Center","active":true,"usgs":false}],"preferred":false,"id":884530,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"MacKenzie, Ashley 0000-0002-7402-7877 amackenzie@usgs.gov","orcid":"https://orcid.org/0000-0002-7402-7877","contributorId":150817,"corporation":false,"usgs":true,"family":"MacKenzie","given":"Ashley","email":"amackenzie@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":884531,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gregg, Jacob L. 0000-0001-5328-5482 jgregg@usgs.gov","orcid":"https://orcid.org/0000-0001-5328-5482","contributorId":203912,"corporation":false,"usgs":true,"family":"Gregg","given":"Jacob","email":"jgregg@usgs.gov","middleInitial":"L.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":884532,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Conway, Carla M. 0000-0002-3851-3616 cmconway@usgs.gov","orcid":"https://orcid.org/0000-0002-3851-3616","contributorId":2946,"corporation":false,"usgs":true,"family":"Conway","given":"Carla","email":"cmconway@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":884533,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Trochta, John T.","contributorId":279655,"corporation":false,"usgs":false,"family":"Trochta","given":"John","email":"","middleInitial":"T.","affiliations":[{"id":57329,"text":"School of Aquatic and Fishery Sciences, Box 355020, University of Washington, Seattle WA, 98195, USA","active":true,"usgs":false}],"preferred":false,"id":884534,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hershberger, Paul 0000-0002-2261-7760","orcid":"https://orcid.org/0000-0002-2261-7760","contributorId":203322,"corporation":false,"usgs":true,"family":"Hershberger","given":"Paul","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":884535,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70248933,"text":"ofr20231069 - 2023 - Assessing the value and usage of data management planning and data management plans within the U.S. Geological Survey","interactions":[],"lastModifiedDate":"2023-10-26T20:09:51.762052","indexId":"ofr20231069","displayToPublicDate":"2023-09-27T14:00:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-1069","displayTitle":"Assessing the Value and Usage of Data Management Planning and Data Management Plans Within the U.S. Geological Survey","title":"Assessing the value and usage of data management planning and data management plans within the U.S. Geological Survey","docAbstract":"As of 2016, the U.S. Geological Survey (USGS) Fundamental Science Practices require data management plans (DMPs) for all USGS and USGS-funded research. The USGS Science Data Management Branch of the Science Analytics and Synthesis Program has been working to help the USGS (Bureau) meet this requirement. However, USGS researchers still encounter common data management-related challenges that may be reduced or eliminated by better planning. In 2021, USGS staff were given a series of surveys aimed to better understand current data management planning practices, perceptions, and needs. The survey results indicated that adoption and integration of data management planning and DMPs into USGS research project workflows are broad, if inconsistent, across USGS Science Centers and programs. The USGS Science Data Management Branch can help improve clarity and guidance on the purpose, intended audience, content, workflows, and evaluation processes for DMPs. It would also be beneficial to provide additional supporting cyberinfrastructure to support DMP activities. Survey responses indicated it would be beneficial for the Science Data Management Branch to develop a strategy, other than through DMPs, for teaching and encouraging good data management practices. Although these surveys were an opportunity for USGS staff to provide feedback on their experiences, the surveys may also have revealed the desire for more frequent evaluations, cross-disciplinary communication, and training on research data management and DMP development and integration, in the context of USGS policy, Fundamental Science Practices requirements, and overall Bureau expectations. Data management-related roles such as data manager or steward, information technologist, and repository manager may need to be formally recognized as skilled professional career positions within the Bureau. At a minimum, the best practice for USGS would be to create and maintain DMPs as living documents, integrated with existing systems that are broadly accessible to all stakeholders, and include quantitatively measurable benefits tied directly to a clearly defined purpose.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231069","programNote":"Science Synthesis, Analysis, and Research Program","usgsCitation":"Langseth, M.L., Sellers, E.A., Donovan, G.C., and Liford, A.N., 2023, Assessing the value and usage of data management planning and data management plans within the U.S. Geological Survey: U.S. Geological Survey Open-File Report 2023–1069, 44 p., https://doi.org/10.3133/ofr20231069.","productDescription":"Report: vi, 44 p.; 6 Appendixes; Data Release","onlineOnly":"Y","ipdsId":"IP-139788","costCenters":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true},{"id":38128,"text":"Science Analytics and Synthesis","active":true,"usgs":true}],"links":[{"id":421261,"rank":9,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91WKCA3","text":"USGS data release","description":"Data release associated with OFR 2023-1069","linkHelpText":"U.S. Geological Survey 2021 Data Management Planning Survey Results and Analyses"},{"id":422160,"rank":12,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231069/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2023-1069"},{"id":421342,"rank":11,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1069/ofr20231069.xml"},{"id":421254,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2023/1069/ofr20231069_appendix3.pdf","text":"Appendix 3","size":"180 kB","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2023-1069 Appendix 3","linkHelpText":"- Data Management Planning Questionnaire for Center Directors"},{"id":421255,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2023/1069/ofr20231069_appendix4.pdf","text":"Appendix 4","size":"168kB","description":"OFR 2023-1069 Appendix 4","linkHelpText":"- Data Management Planning Questionnaire for Program Coordinators and Bureau Approving Officials Appendix"},{"id":421257,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2023/1069/ofr20231069_appendix6.pdf","text":"Appendix 6","size":"88 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1069 Appendix 6","linkHelpText":"- Interview Questions for Data Managers"},{"id":421219,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2023/1069/ofr20231069_appendix1.pdf","text":"Appendix 1","size":"184 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1069 Appendix 1","linkHelpText":"- Data Management Planning Questionnaire for Researchers"},{"id":421253,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2023/1069/ofr20231069_appendix2.pdf","text":"Appendix 2","size":"184 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1069 Appendix 2","linkHelpText":"- Data Management Planning Questionnaire for Data Managers and Information Technologists"},{"id":421341,"rank":10,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1069/images"},{"id":421256,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2023/1069/ofr20231069_appendix5.pdf","text":"Appendix 5","size":"108 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1069 Appendix 5","linkHelpText":"- Interview Questions for Researchers"},{"id":421217,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1069/coverthb.jpg"},{"id":421218,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1069/ofr20231069.pdf","text":"Report","size":"1.69 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1069"}],"contact":"Director, Science Analytics and Synthesis Program
U.S. Geological Survey
P.O. Box 25046, Mail Stop 302
Denver, CO 80225
The U.S. Geological Survey and the Idaho Department of Water Resources measured groundwater levels during spring 2022 and autumn 2022 to create detailed potentiometric-surface maps for the alluvial aquifer in the Big Lost River Valley in south-central Idaho. Wells were assigned to shallow, intermediate, and deep water-bearing units based on well depth, groundwater potentiometric-surface altitude, and hydrogeologic unit. Potentiometric-surface contours were created for each of the three water-bearing units for spring 2022 and autumn 2022. Groundwater flow generally follows topography down valley to the south. The groundwater-level data also were used to calculate changes in groundwater levels from spring to autumn 2022 and from historical measurement events in 1968 and 1991 to 2022. Groundwater levels declined at most wells from spring 1968 to spring 2022 and from spring 1991 to spring 2022. Although groundwater-level changes are sensitive to interannual wet and dry periods, long-term groundwater-level declines suggest that recharge and down-valley groundwater flows are insufficient to fully recover groundwater-level declines from pumping in some parts of the alluvial aquifer in the Big Lost River Valley.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3509","collaboration":"Prepared in cooperation with the Idaho Department of Water Resources","usgsCitation":"Ducar, S.D., and Zinsser, L.M., 2023, Groundwater potentiometric-surface altitude in 2022 and groundwater-level changes between 1968, 1991, and 2022, in the alluvial aquifer in the Big Lost River Valley, south-central Idaho: U.S. Geological Survey Scientific Investigations Map 3509, 1 sheet, scale 1:150,000, 11-p. pamphlet, https://doi.org/10.3133/sim3509.","productDescription":"Pamphlet: viii, 11 p.; Map: 22.51 × 30.00 inches","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-140355","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":500438,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115436.htm","linkFileType":{"id":5,"text":"html"}},{"id":421346,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93NQAP9","text":"USGS data release","description":"USGS data release","linkHelpText":"Groundwater potentiometric-surface contours and well numbers used to map groundwater potentiometric-surface altitude in 2022 and groundwater-level changes between 1968, 1991, and 2022 in the alluvial aquifer in the Big Lost River Valley, south-central Idaho"},{"id":421275,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sim/3509/sim3509_pamphlet.XML"},{"id":421274,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sim/3509/images"},{"id":421270,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3509/coverthb.jpg"},{"id":421271,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3509/sim3509.pdf","text":"Sheet","size":"2.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3509"},{"id":421272,"rank":3,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/sim/3509/sim3509_pamphlet.pdf","text":"Pamphlet","size":"3.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3509 Pamphlet"},{"id":421273,"rank":4,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sim3509/full","text":"Pamphlet","linkFileType":{"id":5,"text":"html"},"description":"SIM 3509 Pamphlet"}],"country":"United States","state":"Idaho","otherGeospatial":"Big Lost River Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -114.0,\n 44.15\n ],\n [\n -114,\n 43.30\n ],\n [\n -113.15,\n 43.3\n ],\n [\n -113.15,\n 44.15\n ],\n [\n -114,\n 44.15\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702-4520
Compound earthquakes involving simultaneous ruptures along multiple faults often define a region’s upper threshold of maximum magnitude. Yet, the potential for linked faulting remains poorly understood given the infrequency of these events in the historic era. Geological records provide longer perspectives, although temporal uncertainties are too broad to clearly pinpoint single multifault events. Here, we use dendrochronological dating and a cosmogenic radiation pulse to constrain the death dates of earthquake-killed trees along two adjacent fault zones near Seattle, Washington to within a 6-month period between the 923 and 924 CE growing seasons. Our narrow constraints conclusively show linked rupturing that occurred either as a single composite earthquake of estimated magnitude 7.8 or as a closely spaced double earthquake sequence with estimated magnitudes of 7.5 and 7.3. These scenarios, which are not recognized in current hazard models, increase the maximum earthquake size needed for seismic preparedness and engineering design within the Puget Sound region of >4 million residents.
","language":"English","publisher":"AAAS","doi":"10.1126/sciadv.adh4973","usgsCitation":"Black, B., Pearl, J., Pearson, C., Pringle, P., Frank, D., Page, M.T., Buckley, B., Cook, E.R., Harley, G.L., King, K., Hughes, J.F., Reynolds, D.J., and Sherrod, B.L., 2023, A multifault earthquake threat for the Seattle metropolitan region revealed by mass tree mortality: Science Advances, v. 9, no. 39, eadh4973, 9 p., https://doi.org/10.1126/sciadv.adh4973.","productDescription":"eadh4973, 9 p.","ipdsId":"IP-143345","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":489961,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1126/sciadv.adh4973","text":"Publisher Index Page"},{"id":482643,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","city":"Seattle","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.4,\n 47.7\n ],\n [\n -123.4,\n 47\n ],\n [\n -122,\n 47\n ],\n [\n -122,\n 47.7\n ],\n [\n -123.4,\n 47.7\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"9","issue":"39","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Black, Bryan","contributorId":300775,"corporation":false,"usgs":false,"family":"Black","given":"Bryan","affiliations":[{"id":65257,"text":"University of Arizona, USA","active":true,"usgs":false}],"preferred":false,"id":929114,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pearl, Jessie K. 0000-0002-1556-2159","orcid":"https://orcid.org/0000-0002-1556-2159","contributorId":336799,"corporation":false,"usgs":false,"family":"Pearl","given":"Jessie K.","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":929115,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pearson, Charlotte","contributorId":351616,"corporation":false,"usgs":false,"family":"Pearson","given":"Charlotte","affiliations":[{"id":28236,"text":"Univ of Arizona","active":true,"usgs":false}],"preferred":false,"id":929116,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pringle, Patrick T.","contributorId":330195,"corporation":false,"usgs":false,"family":"Pringle","given":"Patrick T.","affiliations":[{"id":78849,"text":"Centralia College, Washington","active":true,"usgs":false}],"preferred":false,"id":929117,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Frank, David C.","contributorId":351617,"corporation":false,"usgs":false,"family":"Frank","given":"David C.","affiliations":[{"id":28236,"text":"Univ of Arizona","active":true,"usgs":false}],"preferred":false,"id":929118,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Page, Morgan T. 0000-0001-9321-2990 mpage@usgs.gov","orcid":"https://orcid.org/0000-0001-9321-2990","contributorId":3762,"corporation":false,"usgs":true,"family":"Page","given":"Morgan","email":"mpage@usgs.gov","middleInitial":"T.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":929119,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Buckley, Brendan M.","contributorId":351618,"corporation":false,"usgs":false,"family":"Buckley","given":"Brendan M.","affiliations":[{"id":84016,"text":"Lamont-Dohtery Earth Obs.","active":true,"usgs":false}],"preferred":false,"id":929120,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cook, Edward R.","contributorId":225235,"corporation":false,"usgs":false,"family":"Cook","given":"Edward","email":"","middleInitial":"R.","affiliations":[{"id":17701,"text":"Lamont-Doherty Earth Observatory","active":true,"usgs":false}],"preferred":false,"id":929121,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Harley, Grant L.","contributorId":204186,"corporation":false,"usgs":false,"family":"Harley","given":"Grant","email":"","middleInitial":"L.","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":929122,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"King, Karen J.","contributorId":351635,"corporation":false,"usgs":false,"family":"King","given":"Karen J.","affiliations":[],"preferred":false,"id":929123,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Hughes, Jonathan F.","contributorId":184055,"corporation":false,"usgs":false,"family":"Hughes","given":"Jonathan","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":929124,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Reynolds, David J.","contributorId":279711,"corporation":false,"usgs":false,"family":"Reynolds","given":"David","email":"","middleInitial":"J.","affiliations":[{"id":57351,"text":"Centre for Geography and Environmental Sciences, University of Exeter, Penryn, Cornwall, TR10 9EZ, UK","active":true,"usgs":false}],"preferred":false,"id":929125,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Sherrod, Brian L. 0000-0002-4492-8631 bsherrod@usgs.gov","orcid":"https://orcid.org/0000-0002-4492-8631","contributorId":2834,"corporation":false,"usgs":true,"family":"Sherrod","given":"Brian","email":"bsherrod@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":929126,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70250569,"text":"70250569 - 2023 - Thirteen years of turtle capture–mark–recapture in a small urban pond complex in Louisiana, USA","interactions":[],"lastModifiedDate":"2024-09-13T15:54:02.773662","indexId":"70250569","displayToPublicDate":"2023-09-27T06:36:12","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2334,"text":"Journal of Herpetology","active":true,"publicationSubtype":{"id":10}},"title":"Thirteen years of turtle capture–mark–recapture in a small urban pond complex in Louisiana, USA","docAbstract":"Turtles are one of the most imperiled vertebrate groups in the world. With habitat destruction unabated in many places, urban and suburban greenspaces may serve as refugia for turtles, at least those species able to tolerate heavily altered landscapes. In south-central Louisiana, we have conducted a turtle capture–mark–recapture effort in two ponds in an urban greenspace for 13 yr to understand species composition, survival, and individual growth rates. We had 574 total captures of 251 individuals of five species from 2009–2021, with Trachemys scripta elegans (Red-Eared Sliders) and Sternotherus odoratus (Eastern Musk Turtles) being the most common. Apparent annual survival for T. scripta (0.79) was similar to estimates reported in other studies in altered habitats, whereas apparent annual survival for S. odoratus (0.89) was slightly or much higher than other published studies. Growth rates of T. scripta were comparable to other studies and showed both sexes have similar rates of growth until maturity, which is earlier and at a smaller size in males. The two ponds showed marked differences in captures by size, with significantly more juvenile T. scripta captured in the pond with more vegetation, depth, and a softer bottom. Most T. scripta (78.5%) that were recaptured came from the same pond from which they were originally captured. The basic demographic data gained in this study can serve as a starting point for broader questions on urbanization effects and as a comparison to more natural populations.