Increased fire size and frequency coupled with annual grass invasion pose major challenges to sagebrush (Artemisia spp.) ecosystem conservation, which is currently focused on protecting sagebrush community composition and structure. A common strategy for mitigating potential fire is to use fuel treatments that alter the structure and amount of burnable material, thus reducing fire behavior and creating access points for fire suppression resources. While there is some recent information on the impacts of fuel treatments on ecological communities, we have little information on fuel treatment effectiveness at modifying fire behavior in sagebrush ecosystems. We present 10 years of data on fuel accumulation and the resultant modeled fire behavior in prescribed fire, mowed, herbicide (tebuthiuron or imazapic), and untreated control plots in the Sagebrush Treatment Evaluation Project (SageSTEP) network in the Great Basin, USA. Fuel data (i.e., aboveground burnable live and dead biomass) were collected in each treatment plot at Years 0 (pretreatment), 1, 2, 3, 6, and 10 posttreatment. We used the Fuel and Fire Tool fire behavior modeling program to test whether treatments impacted potential fire behavior. Prescribed fire initially removed 49% of the total fuel load and 75% of shrubs, and fuel loads remained reduced through Year 10. Mowing shifted fuels from the shrub canopy to the ground surface but did not change the total fuel amount. Prescribed fire and mowing increased herbaceous fuel by the second posttreatment year and that trend persisted through Year 10. Tebuthiuron treatments were ineffective at altering fuel loads. Imazapic suppressed herbaceous vegetation by 30% in Years 2 and 3 following treatment. The modified fuel beds in fire and mow treatments resulted in modeled flame lengths that were significantly lower than untreated control plots for the duration of the study, with shorter term reductions in reaction intensity and rate of spread. Understanding fuel treatment effectiveness will allow natural resource managers to evaluate trade-offs between protecting wildlife habitat and reducing the potential for high-intensity wildfire.
Identifying relatively intact areas within ecosystems and determining the conditions favoring their existence is necessary for effective management in the context of widespread environmental degradation. In this study, we used 3766 surveys of randomly selected sites in the United States and U.S. Territories to identify the correlates of sites categorized as “oases” (defined as sites with relatively high total coral cover). We used occupancy models to evaluate the influence of 10 environmental predictors on the probability that an area (21.2-km2 cell) would harbor coral oases defined at four spatial extents: cross-basin, basin, region, and subregion. Across all four spatial extents, oases were more likely to occur in habitats with high light attenuation. The influence of the other environmental predictors on the probability of oasis occurrence were less consistent and varied with the scale of observation. Oases were most likely in areas of low human population density, but this effect was evident only at the cross-basin and subregional extents. At the regional and subregional extents oases were more likely where sea-surface temperature was more variable, whereas at the larger spatial extents the opposite was true. By identifying the correlates of oasis occurrence, the model can inform the prioritization of reef areas for management. Areas with biophysical conditions that confer corals with physiological resilience, as well as limited human impacts, likely support coral reef oases across spatial extents. Our approach is widely applicable to the development of conservation strategies to protect biodiversity and ecosystems in an era of magnified human disturbance.
A cooperative study led by the U.S. Geological Survey and Wake County Environmental Services was initiated to characterize the fractured-rock aquifer system and assess the sustainability of groundwater resources in and around Wake County. This report contributes to the development of a comprehensive groundwater budget for the study area, thereby helping to enable resource managers to make sound and sustainable water-supply and water-use decisions.
Construction information was used to analyze the well depth, casing depth, and reported well yield of more than 7,500 inventoried wells. The median well depth and casing depth were 265 feet (ft) below land surface (bls) and 68 ft bls, respectively, and the median well yield was 10 gallons per minute. Generally, well yield increased with depth to around 200 ft bls and then began to decrease with depth within the fractured-rock aquifer.
Borehole geophysical logging methods were used to characterize the fractured-rock aquifer by mapping the orientation of geologic structures within the subsurface. Structure measurements were made on resulting log data and mapped to observed general spatial trends within the regional groundwater system and more distinct hydrogeologic units. Many of the fractures observed within the borehole logs are steeply dipping across Wake County, although open fractures with shallow dip angles were also observed in most rock classes. Regional geologic structural trends were observed in proximity to the Jonesboro Fault.
Potential groundwater recharge in the study area was estimated using a Soil-Water-Balance (SWB) model, as well as using base flow hydrograph separation. The SWB model calculated net infiltration below the root zone for 1981 through 2019 for a 5,402-square-mile area that extends to the counties surrounding Wake County. The mean annual net infiltration rate for the 39-year period was about 8.6 inches per year for the study area. The mean annual net infiltration results from the SWB model were comparable to annual base flow estimates using the PART hydrograph-separation method at six U.S. Geological Survey streamgages within the study area. Mean annual base flow for all six drainage basins was near 7.5 inches per year and estimates ranged from 2.9 to 8.9 inches. Comparisons of mean annual potential recharge from the SWB model and base flow estimates were generally within 2 inches, except during high flows for most of the drainage basins in the study area.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225041","collaboration":"Prepared in cooperation with Wake County Environmental Services","usgsCitation":"Antolino, D.J., and Gurley, L.N., 2022, Assessment of well yield, dominant fractures, and groundwater recharge in Wake County, North Carolina (ver. 1.1, May 2022) : U.S. Geological Survey Scientific Investigations Report 2022–5041, 35 p., https://doi.org/10.3133/sir20225041.","productDescription":"Report: viii, 35 p.; 3 Data Releases; Database","numberOfPages":"35","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-115494","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":435852,"rank":11,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MO793B","text":"USGS data release","linkHelpText":"Soil-Water-Balance (SWB) model data sets for the Greater Wake County area, North Carolina, 1981 - 2070"},{"id":399579,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95XKK5V","text":"USGS data release","linkHelpText":"Soil-Water-Balance (SWB) model datasets for the Greater Wake County area, North Carolina, 1981–2019"},{"id":399580,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96HHBIE","text":"USGS data release","linkHelpText":"National Land Cover Database (NLCD) 2016 products (ver. 2.0, July 2020)"},{"id":399576,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5041/sir20225041.pdf","text":"Report","size":"13.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5041"},{"id":399577,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5041/sir20225041.XML"},{"id":399582,"rank":8,"type":{"id":9,"text":"Database"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the Nation"},{"id":399596,"rank":9,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/sir20225041/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":399575,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5041/coverthb2.jpg"},{"id":399578,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5041/images/"},{"id":399581,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9C2J23X","text":"USGS data release","linkHelpText":"Groundwater well yield in Wake County, North Carolina"},{"id":502396,"rank":12,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112959.htm","linkFileType":{"id":5,"text":"html"}},{"id":400310,"rank":10,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2022/5041/versionHist.txt","size":"508 B","linkFileType":{"id":2,"text":"txt"}}],"country":"United States","state":"North Carolina","county":"Wake County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-78.5465,36.0218],[-78.4307,35.9795],[-78.3969,35.9387],[-78.3567,35.9318],[-78.351,35.909],[-78.3385,35.9052],[-78.3347,35.8997],[-78.3302,35.896],[-78.3245,35.896],[-78.3177,35.8963],[-78.3137,35.8976],[-78.3081,35.8935],[-78.2948,35.8797],[-78.292,35.8792],[-78.2893,35.8741],[-78.2859,35.8713],[-78.2831,35.8681],[-78.2782,35.8631],[-78.2749,35.8567],[-78.2756,35.8494],[-78.2707,35.843],[-78.2657,35.8361],[-78.2652,35.8325],[-78.2613,35.8315],[-78.2591,35.826],[-78.2599,35.8183],[-78.3731,35.7523],[-78.4635,35.7072],[-78.4686,35.7087],[-78.4709,35.7078],[-78.4732,35.7046],[-78.4778,35.7011],[-78.5716,35.6255],[-78.708,35.5191],[-78.9196,35.5857],[-78.9956,35.6104],[-78.9796,35.6656],[-78.9439,35.7515],[-78.9421,35.756],[-78.9403,35.7615],[-78.9337,35.7859],[-78.9191,35.8216],[-78.9096,35.8506],[-78.9076,35.8678],[-78.89,35.8676],[-78.8298,35.8689],[-78.8056,35.9281],[-78.7609,35.9176],[-78.751,35.9307],[-78.7372,35.941],[-78.714,35.9729],[-78.7009,36.0068],[-78.6985,36.0131],[-78.7048,36.0091],[-78.7077,36.0087],[-78.7076,36.0132],[-78.7052,36.0223],[-78.7085,36.0287],[-78.7102,36.0287],[-78.713,36.0278],[-78.7164,36.0283],[-78.7232,36.0334],[-78.726,36.0343],[-78.7272,36.0334],[-78.7278,36.0289],[-78.7324,36.0267],[-78.7353,36.0199],[-78.7422,36.0209],[-78.75,36.026],[-78.7551,36.0283],[-78.7545,36.0301],[-78.7511,36.0323],[-78.7499,36.035],[-78.747,36.0395],[-78.7492,36.0427],[-78.7503,36.0468],[-78.7519,36.0491],[-78.7564,36.0532],[-78.7498,36.0718],[-78.7088,36.0768],[-78.6895,36.0752],[-78.5922,36.0378],[-78.5465,36.0218]]]},\"properties\":{\"name\":\"Wake\",\"state\":\"NC\"}}]}","edition":"Version 1.1: May 2022; Version 1.0: April 2022","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
1770 Corporate Drive
Norcross, GA 30093
Climate change can act to facilitate or inhibit invasions of non-native species. Here, we address the influence of climate change on control of non-native common carp (hereafter, carp), a species recognized as one of the “world's worst” invaders across the globe. Control of this species is exceedingly difficult, as it exhibits rapid population growth and compensatory density dependence. In many locations where carp have invaded, however, climate change is altering hydrologic regimes and may influence population demography and efficacy of human control efforts. To further evaluate these processes, we employed a modified version of an age-based population model (CarpMOD), to investigate how hydrologic variability (change in lake area) influences carp population dynamics and control efforts in Malheur Lake, southeastern Oregon, USA. We explored how changes in lake area influence carp populations under three control scenarios: (1) no carp removal, (2) carp removal during low water years, and (3) carp removal during all years. Lake area fluctuations strongly influenced carp populations and the efficacy of carp control. Modeled carp biomass peaked when the lake transitioned from high-to-low levels, and carp biomass declined when lake area transitioned from low-to-high. Removing carp during low water periods—when fish were concentrated into a smaller area—reduced carp populations almost as much as removing carp every year. Furthermore, the effectiveness of control efforts increased with the prevalence and severity of low lake conditions (longer durations of very low lake area). These simulations suggest that a drier climate may naturally decrease carp populations and make them easier to control. However, drier conditions may also negatively affect aquatic ecosystems and potentially have a greater impact than non-native species themselves.
Debris flows pose a significant hazard to communities in mountainous areas, and there is a continued need for methods to delineate hazard zones associated with debris-flow inundation. In certain situations, such as scenarios following wildfire, where there could be an abrupt increase in the likelihood and size of debris flows that necessitates a rapid hazard assessment, the computational demands of inundation models play a role in their utility. The inability to efficiently determine the downstream effects of anticipated debris-flow events remains a critical gap in our ability to understand, mitigate, and assess debris-flow hazards. To better understand the downstream effects of debris flows, we introduce a computationally efficient, reduced-complexity inundation model, which we refer to as the Progressive Debris-Flow routing and inundation model (ProDF). We calibrate ProDF against mapped inundation from five watersheds near Montecito, CA, that produced debris flows shortly after the 2017 Thomas Fire. ProDF reproduced 70% of mapped deposits across a 40 km2 study area. While this study focuses on a series of post-wildfire debris flows, ProDF is not limited to simulating debris-flow inundation following wildfire and could be applied to any scenario where it is possible to estimate a debris-flow volume. However, given its ability to reproduce mapped debris-flow deposits downstream of the 2017 Thomas Fire burn scar, and the modest run time associated with a simulation over this 40 km2 study area, results suggest ProDF may be particularly promising for post-wildfire hazard assessment applications.
An accretionary tectonic model for the Mesoproterozoic ca. 1500–1340 Ma tectonic evolution of the southern Laurentian margin is presented. The tectonic model incorporates key observations about the nature and timing of Mesoproterozoic deposition, magmatism, regional metamorphism, and deformation across the 5000-km-long southern Laurentian margin. This time period was one of transition in the supercontinent cycle and occurred between the breakup of Columbia and the formation of Rodinia, and the southern Laurentian margin was a significant component of a much greater accretionary margin extending into Baltica and Amazonia and possibly parts of Antarctica and Australia. However, fundamental questions and contradictions remain in our understanding of the tectonic evolution of Laurentia and paleogeography during this time interval.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Laurentia: Turning points in the evolution of a continent","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Geological Society of America","doi":"10.1130/2022.1220(08)","usgsCitation":"Daniel, C.G., Aronoff, R., Indares, A., and Jones, J.V., 2022, Laurentia in transition during the Mesoproterozoic: Observations and speculation on the ca. 1500–1340 Ma tectonic evolution of the southern Laurentian margin, chap. of Laurentia: Turning points in the evolution of a continent, https://doi.org/10.1130/2022.1220(08).","ipdsId":"IP-134080","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":400620,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"Online First","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Daniel, Christopher G.","contributorId":195246,"corporation":false,"usgs":false,"family":"Daniel","given":"Christopher","email":"","middleInitial":"G.","affiliations":[{"id":25242,"text":"Department of Biology, Bucknell University, Lewisburg, Pennsylvania 17837, USA","active":true,"usgs":false}],"preferred":false,"id":843031,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aronoff, Ruth 0000-0001-5320-6596","orcid":"https://orcid.org/0000-0001-5320-6596","contributorId":291773,"corporation":false,"usgs":false,"family":"Aronoff","given":"Ruth","email":"","affiliations":[{"id":62750,"text":"Furman University","active":true,"usgs":false}],"preferred":false,"id":843032,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Indares, Aphrodite 0000-0002-9604-079X","orcid":"https://orcid.org/0000-0002-9604-079X","contributorId":291774,"corporation":false,"usgs":false,"family":"Indares","given":"Aphrodite","email":"","affiliations":[{"id":62751,"text":"Memorial University Newfoundland","active":true,"usgs":false}],"preferred":false,"id":843033,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jones, James V. III 0000-0002-6602-5935 jvjones@usgs.gov","orcid":"https://orcid.org/0000-0002-6602-5935","contributorId":201245,"corporation":false,"usgs":true,"family":"Jones","given":"James","suffix":"III","email":"jvjones@usgs.gov","middleInitial":"V.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":843034,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70234285,"text":"70234285 - 2022 - Water-use data in the United States: Challenges and future directions","interactions":[],"lastModifiedDate":"2022-08-08T11:38:57.659502","indexId":"70234285","displayToPublicDate":"2022-05-10T06:32:20","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Water-use data in the United States: Challenges and future directions","docAbstract":"In the United States, greater attention has been given to developing water supplies and quantifying available waters than determining who uses water, how much they withdraw and consume, and how and where water use occurs. As water supplies are stressed due to an increasingly variable climate, changing land-use, and growing water needs, greater consideration of the demand side of the water balance equation is essential. Data about the spatial and temporal aspects of water use for different purposes are now critical to long-term water supply planning and resource management. We detail the current state of water-use data, the major stakeholders involved in their collection and applications, and the challenges in obtaining high-quality nationally consistent data applicable to a range of scales and purposes. Opportunities to improve access, use, and sharing of water-use data are outlined. We cast a vision for a world-class national water-use data product that is accessible, timely, and spatially detailed. Our vision will leverage the strengths of existing local, state, and federal agencies to facilitate rapid and informed decision-making, modeling, and science for water resources. To inform future decision-making regarding water supplies and uses, we must coordinate efforts to substantially improve our capacity to collect, model, and disseminate water-use data.
Streams in the Loup River Basin are sensitive to groundwater withdrawals because of the close hydrologic connection between groundwater and surface water. The U.S. Geological Survey, in cooperation with the Upper Loup and Lower Loup Natural Resources Districts, and the Nebraska Environmental Trust, studied the age and water-quality characteristics of groundwater near the South Loup River to assess the possible effects of a multiyear drought on streamflow.
Groundwater sampled in wells screened in Quaternary-age deposits displayed a wide range of mean ages (27 to 2,100 years), fraction modern, and susceptibility index values. Groundwater with higher concentrations of chloride and higher specific conductance was indicative of younger groundwater with a narrower age distribution and is more sensitive to climatic disturbances such as short-term drought conditions, based on the calculated susceptibility index. Groundwater samples from wells and springs in Pliocene-age deposits were categorized into two groups with different geochemical and age characteristics. One sample group of springs and wells, called the Western Pliocene, had higher concentrations of chloride and nitrate with young mean ages (18 to 77 years) and narrow age distributions. Groundwater in the Western Pliocene sample group is susceptible to short-term drought. In contrast, the other sample group from Pliocene-age deposits to the east (called Pliocene) had lower concentrations of nitrate, chloride, and mean groundwater ages ranging from 1,900 to 2,900 years old and is less likely to be affected by short-term drought conditions. Groundwater sampled from three wells screened in the Ogallala Formation was shown to have the oldest mean ages ranging from 8,700 to 23,000 years and the lowest calculated susceptibility index values observed in this study. Strong upward hydraulic gradients measured in wells indicated that groundwater from the Ogallala Formation is likely contributing to streamflow of the South Loup River.
Continuously measured gage height and specific conductance data indicated groundwater discharge from Quaternary-age deposits was highly responsive to precipitation events. In contrast, groundwater discharge from Pliocene-age deposits (Pliocene sample group) was far less responsive, indicating groundwater discharge from Pliocene-age deposits is likely more resilient to short-term drought conditions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225042","collaboration":"Prepared in cooperation with the Upper Loup and Lower Loup Natural Resources Districts and the Nebraska Environmental Trust","usgsCitation":"Hobza, C.M., and Solder, J.E., 2022, Age and water-quality characteristics of groundwater discharge to the South Loup River, Nebraska, 2019: U.S. Geological Survey Scientific Investigations Report 2022–5042, 57 p., https://doi.org/10.3133/sir20225042.","productDescription":"Report: ix, 57 p.; Data Release","numberOfPages":"72","onlineOnly":"Y","ipdsId":"IP-129114","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":400241,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5042/sir20225042.pdf","text":"Report","size":"15.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5042"},{"id":502397,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112991.htm","linkFileType":{"id":5,"text":"html"}},{"id":400244,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9L6B4XE","text":"USGS data release","linkHelpText":"Lumped parameter models of groundwater age, South Loup River, Nebraska"},{"id":400243,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5042/images"},{"id":400242,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5042/sir20225042.XML"},{"id":400333,"rank":6,"type":{"id":11,"text":"Document"},"url":"https://pubs.er.usgs.gov/publication/sir20225042/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":400240,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5042/coverthb.jpg"}],"country":"United States","state":"Nebraska","otherGeospatial":"South Loup River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -100.8599853515625,\n 41.075210270566636\n ],\n [\n -98.5089111328125,\n 41.075210270566636\n ],\n [\n -98.5089111328125,\n 42.07376224008719\n ],\n [\n -100.8599853515625,\n 42.07376224008719\n ],\n [\n -100.8599853515625,\n 41.075210270566636\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Nebraska Water Science Center
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Although declines in grassland birds have been documented, national initiatives to conserve grasslands and their biota have fallen short in part because the non-market values of natural ecosystems and species are often not recognized in political decision making. Identifying shared, anthropogenic threats faced by market-valued and non-market-valued species may generate additional support for grassland conservation. We quantify the relationship between the market value of grasslands to commercial beekeepers and the importance of grasslands for birds of conservation concern in North and South Dakota. Our models estimated beekeeping annual revenue increased by $7525 USD and grassland bird abundances increased 2 to 7% per 10-km2 increase in grassland area. We estimated grassland conversion from 2006 to 2012 resulted in a $2.0 to $2.8 M USD decrease in annual revenue for beekeepers in the Dakotas. Through this study we demonstrate both the market value of grasslands to commercial beekeepers and the non-market benefits of grasslands in supporting migratory birds and discuss the implications of future land-use change. As grassland conversion and subsequent biodiversity loss continue, understanding the co-benefits of grassland conservation may be necessary to illuminate their contributions to society.
Chemically intensive crop production depletes wildlife food resources, hinders animal development, health, survival, and reproduction, and it suppresses wildlife immune systems, facilitating emergence of infectious diseases with excessive mortality rates. Gut microbiota is crucial for wildlife's response to environmental stressors. Its composition and functionality are sensitive to diet changes and environmental pollution associated with modern crop production. In this study we use shotgun metagenomics (median 8,326,092 sequences/sample) to demonstrate that exposure to modern crop production detrimentally affects cecal microbiota of sharp-tailed grouse (Tympanuchus phasianellus: 9 exposed, 18 unexposed and greater prairie chickens (T. cupido; 11, 11). Exposure to crop production had greater effect on microbiota richness (t = 6.675, P < 0.001) and composition (PERMANOVA r2 = 0.212, P = 0.001) than did the host species (t = 4.762, P < 0.001; r2 = 0.070, P = 0.001) or their interaction (t = 3.449; r2 = 0.072, both P = 0.001), whereas sex and age had no effect. Although microbiota richness was greater in exposed (T. cupido chao1 = 152.8 ± 20.5; T. phasianellus 115.3 ± 17.1) than in unexposed (102.9 ± 15.1 and 101.1 ± 17.2, respectively) birds, some beneficial bacteria dropped out of exposed birds' microbiota or declined and were replaced by potential pathogens. Exposed birds also had higher richness and load of virulome (mean ± standard deviation; T. cupido 24.8 ± 10.0 and 10.1 ± 5.5, respectively; T. phasianellus 13.4 ± 6.8/4.9 ± 2.8) and resistome (T. cupido 46.8 ± 11.7/28.9 ± 10.2, T. phasianellus 38.3 ± 16.7/18.9 ± 14.2) than unexposed birds (T. cupido virulome: 14.2 ± 13.5, 4.5 ± 4.2; T. cupido resistome: 31.6 ± 20.2 and 13.1 ± 12.0; T. phasianellus virulome: 5.2 ± 4.7 and 1.4 ± 1.5; T. phasianellus resistome: 13.7 ± 16.1 and 4.0 ± 6.4).
A state-space model (SSM) of infiltration estimates daily groundwater recharge using time-series of groundwater-level altitude and meteorological inputs (liquid precipitation, snowmelt, and evapotranspiration). The model includes diffuse and preferential flow through the unsaturated zone, where preferential flow is a function of liquid precipitation and snowmelt rates and a threshold rate, above which there is direct recharge to the water table. Model parameters are estimated over seasonal periods and the SSM is coupled with the Kalman Filter (KF) to assimilate recent observations (hydraulic head) and meteorological inputs into recharge estimates. The approach can take advantage of real-time hydrologic and meteorological data to deliver real-time recharge estimates. The model is demonstrated on daily observations from two bedrock wells in carbonate aquifers of northwestern New York (USA) between 2013 and 2018. Meteorological inputs for liquid precipitation and snowmelt are compiled from SNODAS (2021). Results for recharge during winter and spring seasons show preferential flow events to the water table from liquid precipitation, snowmelt, or a combination of the two. Recharge estimates summed annually are consistent with previous estimates of recharge reported from groundwater flow and surface-process models. Results from the SSM and KF point to errors in meteorological inputs, such as the snowmelt rate, that are not compatible with hydraulic head observations. Whereas liquid and solid precipitation are measured at discrete stations and extrapolated to 1-km2 grid cells, snowmelt is a meteorological modeled outcome that may not represent conditions in the vicinity of monitoring well locations.
","language":"English","publisher":"National Ground Water Association","doi":"10.1111/gwat.13206","usgsCitation":"Shapiro, A.M., Day-Lewis, F., Kappel, W.M., and Williams, J., 2022, Incorporating snowmelt into daily estimates of recharge using a state-space model of infiltration: Groundwater, v. 60, no. 6, p. 721-746, https://doi.org/10.1111/gwat.13206.","productDescription":"26 p.","startPage":"721","endPage":"746","ipdsId":"IP-130903","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":447877,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gwat.13206","text":"Publisher Index Page"},{"id":435854,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MRGR88","text":"USGS data release","linkHelpText":"Algorithms for model parameter estimation and state estimation applied to a state-space model for one-dimensional vertical infiltration incorporating snowmelt rate as a system input"},{"id":400497,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"60","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-05-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Shapiro, Allen M. 0000-0002-6425-9607 ashapiro@usgs.gov","orcid":"https://orcid.org/0000-0002-6425-9607","contributorId":2164,"corporation":false,"usgs":true,"family":"Shapiro","given":"Allen","email":"ashapiro@usgs.gov","middleInitial":"M.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":842636,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Day-Lewis, Frederick 0000-0003-3526-886X","orcid":"https://orcid.org/0000-0003-3526-886X","contributorId":216359,"corporation":false,"usgs":true,"family":"Day-Lewis","given":"Frederick","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":842637,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kappel, William M. 0000-0002-2382-9757 wkappel@usgs.gov","orcid":"https://orcid.org/0000-0002-2382-9757","contributorId":1074,"corporation":false,"usgs":true,"family":"Kappel","given":"William","email":"wkappel@usgs.gov","middleInitial":"M.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":842638,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Williams, John 0000-0002-6054-6908 jhwillia@usgs.gov","orcid":"https://orcid.org/0000-0002-6054-6908","contributorId":1553,"corporation":false,"usgs":true,"family":"Williams","given":"John","email":"jhwillia@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":842639,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70254768,"text":"70254768 - 2022 - Using predictions from multiple anthropogenic threats to estimate future population persistence of an imperiled species","interactions":[],"lastModifiedDate":"2024-06-07T14:46:22.029683","indexId":"70254768","displayToPublicDate":"2022-05-06T09:38:02","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3871,"text":"Global Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Using predictions from multiple anthropogenic threats to estimate future population persistence of an imperiled species","docAbstract":"Imperiled species face numerous and diverse anthropogenic threats to their persistence, and wildlife managers charged with making conservation decisions benefit from a sound understanding of how populations, species, and ecosystems will respond to future changes in threats to biodiversity. In southeastern North America, the gopher tortoise (Gopherus polyphemus) is a keystone species in upland ecosystems; however, tortoise populations have declined strongly over the last century, and the species is a candidate for increased protection by the United States federal government under the Endangered Species Act (ESA). Here, we sought to support conservation decision making for G. polyphemus by developing a spatially-explicit predictive population model that linked four anthropogenic threats (climate warming, sea-level rise, urbanization, habitat degradation) to demographic vital rates and used the model to estimate future changes in the number of individuals, populations, and metapopulations across the species’ range. Using recent survey data, we projected 457 populations for 80 years into the future under scenarios varying in threat magnitude, management magnitude, and demographic uncertainty. Population projections predicted that the number of individuals, populations, and metapopulations would decline among all simulated scenarios in the next 80 years. Model predictions were more sensitive to variation in adult survival and immigration rates than to variation in threat magnitude. A scenario with decreased habitat management and threat effects from climate warming, sea-level rise, and urbanization predicted geographic variation in persistence probabilities for populations that might result in decreased genetic representation across the species' range. Our results can be used to support conservation listing decisions for the gopher tortoise as part of its federal Species Status Assessment and provide an analytical framework for how to link diverse threats to geographically-varying demographic rates during population viability analyses for wide-ranging imperiled species around the world.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.gecco.2022.e02143","usgsCitation":"Folt, B., Marshall, M., Emanuel, J.A., Dziadzio, M., Cooke, J., Mena, L., Hinderliter, M., Hoffmann, S., Rankin, N., Tupy, J., and McGowan, C., 2022, Using predictions from multiple anthropogenic threats to estimate future population persistence of an imperiled species: Global Ecology and Conservation, v. 36, e02143, 21 p., https://doi.org/10.1016/j.gecco.2022.e02143.","productDescription":"e02143, 21 p.","ipdsId":"IP-133548","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":447881,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gecco.2022.e02143","text":"Publisher Index Page"},{"id":429647,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"36","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Folt, Brian","contributorId":267702,"corporation":false,"usgs":false,"family":"Folt","given":"Brian","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":902450,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Marshall, Michael","contributorId":337474,"corporation":false,"usgs":false,"family":"Marshall","given":"Michael","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":902451,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Emanuel, Jo Anna","contributorId":337478,"corporation":false,"usgs":false,"family":"Emanuel","given":"Jo","email":"","middleInitial":"Anna","affiliations":[{"id":81021,"text":"Florida Ecological Services","active":true,"usgs":false}],"preferred":false,"id":902452,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dziadzio, Michelina","contributorId":337480,"corporation":false,"usgs":false,"family":"Dziadzio","given":"Michelina","email":"","affiliations":[{"id":12556,"text":"Florida Fish and Wildlife Conservation Commission","active":true,"usgs":false}],"preferred":false,"id":902453,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cooke, Jane","contributorId":337481,"corporation":false,"usgs":false,"family":"Cooke","given":"Jane","email":"","affiliations":[{"id":81021,"text":"Florida Ecological Services","active":true,"usgs":false}],"preferred":false,"id":902454,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mena, Lourdes","contributorId":105576,"corporation":false,"usgs":true,"family":"Mena","given":"Lourdes","email":"","affiliations":[],"preferred":false,"id":902455,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hinderliter, Matthew","contributorId":337483,"corporation":false,"usgs":false,"family":"Hinderliter","given":"Matthew","email":"","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":902456,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hoffmann, Scott","contributorId":337616,"corporation":false,"usgs":false,"family":"Hoffmann","given":"Scott","email":"","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":902457,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rankin, Nicole","contributorId":337485,"corporation":false,"usgs":false,"family":"Rankin","given":"Nicole","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":902458,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Tupy, John","contributorId":337486,"corporation":false,"usgs":false,"family":"Tupy","given":"John","affiliations":[{"id":81024,"text":"Mississippi Ecological Services Office","active":true,"usgs":false}],"preferred":false,"id":902459,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"McGowan, Conor P. 0000-0002-7330-9581 cmcgowan@usgs.gov","orcid":"https://orcid.org/0000-0002-7330-9581","contributorId":3381,"corporation":false,"usgs":true,"family":"McGowan","given":"Conor P.","email":"cmcgowan@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":902460,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70231312,"text":"70231312 - 2022 - Permeability of methane hydrate-bearing sandy silts in the deep-water Gulf of Mexico (Green Canyon Block 955)","interactions":[],"lastModifiedDate":"2022-05-06T14:20:14.06089","indexId":"70231312","displayToPublicDate":"2022-05-06T09:17:01","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":605,"text":"AAPG Bulletin","printIssn":"0149-1423","active":true,"publicationSubtype":{"id":10}},"title":"Permeability of methane hydrate-bearing sandy silts in the deep-water Gulf of Mexico (Green Canyon Block 955)","docAbstract":"Permeability is one of the most crucial properties governing fluid flow in methane hydrate reservoirs. This paper presents a comprehensive permeability analysis of hydrate-bearing sandy silt pressure-cored from Green Canyon Block 955 (GC 955) in the deep-water Gulf of Mexico. We developed an experimental protocol to systematically characterize the transport and petrophysical properties in pressure cores. The in situ effective permeability ranges from 0.1 md (1.0 × 10−16 m2) to 2.4 md (2.4 × 10−15 m2) in these natural sandy silts cores with hydrate occupying 83%–93% of the pore space. When hydrate dissociates from these cores, the measured intrinsic permeability (k0) is 0.3 md (3.0 × 10−16 m2) to 9.3 md (9.3 × 10−15 m2); these results are affected by fines migration during hydrate dissociation. We analyzed samples reconstituted from these sandy silts and found k0 to range from ∼12 md (∼1.2 × 10−14 m2) to ∼41 md (∼4.1 × 10−14 m2). The water relative permeabilities (krw) of GC 955 pressure cores are large relative to other natural pressure cores from offshore Japan, offshore India, and onshore Alaska. These krw values are also higher than predicted by current conceptual relative permeability models where hydrate fills the pores or coats the grains of the sediments. This fundamental conundrum requires further study. Our work provides essential parameters to reservoir simulation models seeking to predict hydrate formation in geological systems, evaluate the gas production potential, and explore the best way to produce this energy resource in sandy silt reservoirs.
","language":"English","publisher":"American Association of Petroleum Geologists","doi":"10.1306/08102121001","usgsCitation":"Fang, Y., Flemings, P., Daigle, H., Phillips, S.C., and O’Connell, J., 2022, Permeability of methane hydrate-bearing sandy silts in the deep-water Gulf of Mexico (Green Canyon Block 955): AAPG Bulletin, v. 106, no. 5, p. 1071-1100, https://doi.org/10.1306/08102121001.","productDescription":"30 p.","startPage":"1071","endPage":"1100","ipdsId":"IP-125587","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":400282,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Green Canyon Block 955, Green Knoll, Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.417236328125,\n 26.82407078047018\n ],\n [\n -89.527587890625,\n 26.82407078047018\n ],\n [\n -89.527587890625,\n 28.497660832963472\n ],\n [\n -91.417236328125,\n 28.497660832963472\n ],\n [\n -91.417236328125,\n 26.82407078047018\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"106","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Fang, Yi","contributorId":138799,"corporation":false,"usgs":false,"family":"Fang","given":"Yi","email":"","affiliations":[{"id":6727,"text":"Pacific Northwest National Laboratory, Richland, WA","active":true,"usgs":false}],"preferred":false,"id":842290,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flemings, Peter","contributorId":198205,"corporation":false,"usgs":false,"family":"Flemings","given":"Peter","affiliations":[{"id":13127,"text":"Jackson School of Geosciences, University of Texas, Austin","active":true,"usgs":false}],"preferred":false,"id":842291,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Daigle, Hugh","contributorId":291400,"corporation":false,"usgs":false,"family":"Daigle","given":"Hugh","email":"","affiliations":[{"id":12430,"text":"University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":842292,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Phillips, Stephen C. 0000-0003-0858-4701","orcid":"https://orcid.org/0000-0003-0858-4701","contributorId":268177,"corporation":false,"usgs":true,"family":"Phillips","given":"Stephen","email":"","middleInitial":"C.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":842293,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"O’Connell, Joshua","contributorId":239907,"corporation":false,"usgs":false,"family":"O’Connell","given":"Joshua","email":"","affiliations":[{"id":48038,"text":"Institute for Geophysics and Department of Geological Sciences, Jackson School of Geosciences, University of Texas","active":true,"usgs":false}],"preferred":false,"id":842294,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70231324,"text":"70231324 - 2022 - Assessing conservation and management actions with ecosystem services better communicates conservation value to the public","interactions":[],"lastModifiedDate":"2022-05-06T14:14:23.881476","indexId":"70231324","displayToPublicDate":"2022-05-06T09:08:02","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Assessing conservation and management actions with ecosystem services better communicates conservation value to the public","docAbstract":"Fish and wildlife populations are under unprecedented threats from changes in land use and climate. With increasing threats comes a need for an expanded constituency that can contribute to the public support and financial capital needed for habitat conservation and management. Using an ecosystem services approach can provide a framework for a more holistic accounting of conservation benefits. Our objective here is to provide a greater understanding of the role that taking an ecosystem services approach can have in expanding the public constituency that supports the use of financial capital required to conserve and manage the nation’s natural capital. To demonstrate a methodology and the usefulness of taking an ecosystem services approach when communicating the value of conserving and managing fish and wildlife habitats, we performed an evaluation of U.S. Fish and Wildlife Service-owned Waterfowl Production Areas, National Wildlife Refuges, and easement lands (both wetland and grassland) in Stutsman County, North Dakota. We quantified amphibian habitat, grassland bird habitat, floral resources for pollinators, and carbon storage services under various scenarios of conservation. While we did not include all possible ecosystem services in our model, our case study shows how this process can provide a more complete picture of the collateral benefits of conservation directed primarily toward waterfowl. Using this ecosystem services approach, we documented marked losses in all services modeled if current conservation lands were developed for the production of agricultural crops. By having access to a more complete picture of benefits provided by conservation lands, decision makers can better communicate their value. By garnering greater public support through a more accurate accounting of societal benefits, conservation and management of dwindling natural capital may someday attain the same level of thought and consideration that is put into the conservation and management of the nation’s financial capital.","language":"English","publisher":"Allen Press","doi":"10.3996/JFWM-21-083","usgsCitation":"Mushet, D., Post van der Burg, M., and Anteau, M.J., 2022, Assessing conservation and management actions with ecosystem services better communicates conservation value to the public: Journal of Fish and Wildlife Management, v. 13, no. 1, 13 p., https://doi.org/10.3996/JFWM-21-083.","productDescription":"13 p.","ipdsId":"IP-126556","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":447884,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/jfwm-21-083","text":"Publisher Index Page"},{"id":400280,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Dakota","county":"Stutsman County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-99.2669,47.3268],[-98.8466,47.327],[-98.8392,47.327],[-98.8232,47.3272],[-98.8152,47.3271],[-98.4991,47.327],[-98.467,47.3266],[-98.4677,47.2402],[-98.4685,46.9788],[-98.4412,46.9789],[-98.4396,46.6296],[-98.7894,46.6294],[-99.0379,46.6309],[-99.1616,46.6317],[-99.4122,46.6316],[-99.4498,46.6319],[-99.4477,46.8044],[-99.4476,46.9788],[-99.4821,46.9795],[-99.4824,47.0089],[-99.4822,47.0162],[-99.4821,47.0249],[-99.4826,47.0396],[-99.4827,47.1558],[-99.4801,47.3267],[-99.2669,47.3268]]]},\"properties\":{\"name\":\"Stutsman\",\"state\":\"ND\"}}]}","volume":"13","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-03-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Mushet, David M. 0000-0002-5910-2744","orcid":"https://orcid.org/0000-0002-5910-2744","contributorId":248468,"corporation":false,"usgs":true,"family":"Mushet","given":"David M.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":842305,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Post van der Burg, Max 0000-0002-3943-4194 maxpostvanderburg@usgs.gov","orcid":"https://orcid.org/0000-0002-3943-4194","contributorId":4947,"corporation":false,"usgs":true,"family":"Post van der Burg","given":"Max","email":"maxpostvanderburg@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":842306,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anteau, Michael J. 0000-0002-5173-5870 manteau@usgs.gov","orcid":"https://orcid.org/0000-0002-5173-5870","contributorId":3427,"corporation":false,"usgs":true,"family":"Anteau","given":"Michael","email":"manteau@usgs.gov","middleInitial":"J.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":842307,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70231649,"text":"70231649 - 2022 - A forested wetland at a climate-induced tipping-point: 17-year demographic evidence of widespread tree recruitment failure","interactions":[],"lastModifiedDate":"2022-05-18T13:55:43.960202","indexId":"70231649","displayToPublicDate":"2022-05-06T08:46:54","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"A forested wetland at a climate-induced tipping-point: 17-year demographic evidence of widespread tree recruitment failure","docAbstract":"Regeneration and survival of forested wetlands are affected by environmental variables related to the hydrologic regime. Climate change, specifically alterations to precipitation patterns, may have outsized effects on these forests. In Tennessee, USA, precipitation has increased by 15% since 1960. The goal of our research was to assess the evidence for whether this change in precipitation patterns resulted in shorter growing seasons and recruitment failure in common canopy trees for a forest wetland. In 2001 and 2018, the density of Quercus lyrata (overcup oak), Liquidambar styraciflua (sweetgum), Quercus phellos (willow oak), and Betula nigra (river birch) seedling, sapling and adult density were mapped in an area of 2.3 ha within a seasonally flooded karst depression. Overall, the percentage of the growing season experiencing inundation was 26% greater in the deep than in shallow areas between 2001 and 2018. Saplings and small adults of all four species were restricted to shallow areas, and their abundance has declined substantially. Overcup oak and sweetgum individuals that were recruited into the adult life history stage were repelled from the deep zone. Overcup oak and sweetgum adults experienced lower mortality across the 2.3-ha study area (11% and 26%, respectively) relative to willow oak (56%) and river birch (64%) over the 17-year study. Growing-season inundation showed no relation to mortality in adult sweetgum and willow oak, a positive relation to mortality among adult river birch across size classes and among small adult overcup oak, and an inverse relation to mortality among large adult overcup oak. In shallow regions, overcup oak and sweetgum adults had greater basal area increment relative to the intermediate and deep regions of the pond. Results of hydrologic modeling for the study area, based on rainfall and temperature records covering 1855–2019, show ponding durations after 1970 considerably longer than the historical baseline, across ponding-depth classes. Our results strongly suggest that climate change is a driving factor suppressing tree regeneration since 1970 in this seasonally flooded karst depression.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2022.120247","usgsCitation":"Evans, J., McCarthy-Neumann, S., Pritchard, A., Cartwright, J.M., and Wolfe, W., 2022, A forested wetland at a climate-induced tipping-point: 17-year demographic evidence of widespread tree recruitment failure: Forest Ecology and Management, v. 517, 120247, 12 p., https://doi.org/10.1016/j.foreco.2022.120247.","productDescription":"120247, 12 p.","ipdsId":"IP-135244","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":447887,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.foreco.2022.120247","text":"Publisher Index Page"},{"id":400755,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Tennessee","otherGeospatial":"Arnold Engineering Development Complex, Sinking Pond","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -86.09521865844725,\n 35.38932985634939\n ],\n [\n -86.04337692260742,\n 35.38932985634939\n ],\n [\n -86.04337692260742,\n 35.42151066245934\n ],\n [\n -86.09521865844725,\n 35.42151066245934\n ],\n [\n -86.09521865844725,\n 35.38932985634939\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"517","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Evans, Jonathan","contributorId":291851,"corporation":false,"usgs":false,"family":"Evans","given":"Jonathan","affiliations":[{"id":62773,"text":"University of the South at Sewanee","active":true,"usgs":false}],"preferred":false,"id":843227,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCarthy-Neumann, Sarah","contributorId":291852,"corporation":false,"usgs":false,"family":"McCarthy-Neumann","given":"Sarah","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":843228,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pritchard, Angus","contributorId":291853,"corporation":false,"usgs":false,"family":"Pritchard","given":"Angus","email":"","affiliations":[{"id":62773,"text":"University of the South at Sewanee","active":true,"usgs":false}],"preferred":false,"id":843229,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cartwright, Jennifer M. 0000-0003-0851-8456 jmcart@usgs.gov","orcid":"https://orcid.org/0000-0003-0851-8456","contributorId":5386,"corporation":false,"usgs":true,"family":"Cartwright","given":"Jennifer","email":"jmcart@usgs.gov","middleInitial":"M.","affiliations":[{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":843230,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wolfe, William J. 0000-0002-3292-051X","orcid":"https://orcid.org/0000-0002-3292-051X","contributorId":224729,"corporation":false,"usgs":false,"family":"Wolfe","given":"William J.","affiliations":[{"id":7065,"text":"USGS emeritus","active":true,"usgs":false}],"preferred":false,"id":843231,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70232355,"text":"70232355 - 2022 - Laboratory simulation of groundwater along uranium-mining-affected flow paths near the Grand Canyon, Arizona, USA","interactions":[],"lastModifiedDate":"2022-06-29T12:12:57.807473","indexId":"70232355","displayToPublicDate":"2022-05-06T07:09:25","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2745,"text":"Mine Water and the Environment","active":true,"publicationSubtype":{"id":10}},"title":"Laboratory simulation of groundwater along uranium-mining-affected flow paths near the Grand Canyon, Arizona, USA","docAbstract":"Mining of volumetrically small, but relatively enriched (average 0.6% U3O8) breccia pipe uranium (BPU) deposits near the Grand Canyon, Arizona, USA has the potential to affect groundwater and springs in the area. Such deposits also contain base metal sulfides that can oxidize to generate acid mine drainage and release trace metals. In this study, sequential batch experiments were conducted to simulate the geochemistry of local shallow groundwater that contacts BPU ore and then moves downgradient through sedimentary strata. The experiments simulated shallow groundwater in a carbonate aquifer followed by contact with BPU ore. The experiments subsequently simulated contact with sedimentary rocks and changing oxygen availability. Concentrations of several contaminants of potential concern became substantially elevated in the waters exposed to BPU ore, including As, Co, Ni, U, and Zn, and to a lesser extent, Mo. Of these, Co, Mo, Ni, and U were minimally attenuated by downgradient processes, whereas Zn was partially attenuated. Sb and Tl concentrations were more moderately elevated but also generally minimally attenuated. Although the mixture of elements is particular to these BPU ore deposits, sulfide oxidation in the ore and carbonate buffering of pH by sedimentary rocks generates patterns of water chemistry common in acid mine drainage settings. Ultimately, downgradient concentrations of elements sourced from BPU ore will also be strongly influenced by non-geochemical factors such as the quantities of water contacting BPU materials, heterogeneity of materials along flow paths, and mixing with waters that have not contacted BPU materials.
Stream fish movement in response to changing resource availability and habitat needs is important for fish growth, survival and reproduction. The authors used radio telemetry to evaluate individual movements, daily movement rates, home ranges and habitat-use characteristics of adult (278–464 mm LT) Neosho smallmouth bass Micropterus dolomieu velox in three Ozark Highlands streams from June 2016 to February 2018. The authors quantified variation in movement and habitat use among seasons and streams and examined relations with select environmental cues (i.e., temperature and discharge), fish size and sex. Maximum movement distances were an order of magnitude greater in the larger Elk River (17.0 km) and Buffalo Creek (12.9 km) than in the smaller Sycamore Creek (1.71 km), were similar in both upstream and downstream directions and typically occurred during the spring. Most movement rates were ≤10 m day−1 in all streams and seasons, except for Elk River during spring. Ranking of linear mixed-effects models using AICc supported that movement rates were much greater in spring and increased with stream size. Spring movement rate increased with discharge and water temperature; only weak relationships were apparent during other seasons. Increased variation in water temperature had a small negative effect on movement rate. Home range size was highly variable among individuals, ranging 45–15,061 m (median: 773 m), and was not related to fish size, sex, season or stream. Although some fish moved between rivers, this study's tagged fish did not use reservoir or associated interface habitat. Water temperatures used by this study's tagged fish followed seasonal patterns but indicated the use of thermal refugia during summer and winter. Deeper-water habitats were used in Buffalo Creek and in winter across all study streams, whereas greater velocities used in the Elk River likely reflect the increased use of run habitats. Use of pool habitats predominated among tagged fish, particularly in smaller streams. The results of this study indicate considerable heterogeneity in movement and habitat use within and among lotic populations of Neosho smallmouth bass. These findings suggest that population-specific management may be appropriate and highlight the importance of natural flow conditions (i.e., spring high flows) and connected habitats for this endemic sport fish, particularly in smaller streams.
","language":"English","publisher":"Wiley","doi":"10.1111/jfb.15076","usgsCitation":"Miller, A., and Brewer, S.K., 2022, Movement and habitat use by smallmouth bass Micropterus dolomieu velox in a dynamic Ozark Highlands riverscape: Journal of Fish Biology, v. 101, no. 1, p. 100-114, https://doi.org/10.1111/jfb.15076.","productDescription":"15 p.","startPage":"100","endPage":"114","ipdsId":"IP-133584","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":447901,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/jfb.15076","text":"External Repository"},{"id":433317,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri, Oklahoma","otherGeospatial":"Brush Creek, Elk River, Sycamore Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -95.00337991937396,\n 36.9787447036027\n ],\n [\n -95.00337991937396,\n 36.50639274310335\n ],\n [\n -94.07756711091189,\n 36.50639274310335\n ],\n [\n -94.07756711091189,\n 36.9787447036027\n ],\n [\n -95.00337991937396,\n 36.9787447036027\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"101","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-05-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Miller, Andrew D.","contributorId":341518,"corporation":false,"usgs":false,"family":"Miller","given":"Andrew D.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":908547,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brewer, Shannon K. 0000-0002-1537-3921 skbrewer@usgs.gov","orcid":"https://orcid.org/0000-0002-1537-3921","contributorId":2252,"corporation":false,"usgs":true,"family":"Brewer","given":"Shannon","email":"skbrewer@usgs.gov","middleInitial":"K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":908548,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70240353,"text":"70240353 - 2022 - Invasion of annual grasses following wildfire corresponds to maladaptive habitat selection by a sagebrush ecosystem indicator species","interactions":[],"lastModifiedDate":"2023-02-06T15:55:04.895367","indexId":"70240353","displayToPublicDate":"2022-05-05T09:50:54","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3871,"text":"Global Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Invasion of annual grasses following wildfire corresponds to maladaptive habitat selection by a sagebrush ecosystem indicator species","docAbstract":"Numerous wildlife species within semi-arid shrubland ecosystems across western North America are experiencing substantial habitat loss and fragmentation. These changes in habitat are often attributed to a diverse suite of factors including prolonged and increasingly severe droughts, conifer expansion, anthropogenic development, domestic and feral livestock grazing, and invasion of exotic annual grasses, which promotes increased wildfire frequency and severity. Greater sage-grouse (Centrocercus urophasianus; hereafter, sage-grouse) are considered an indicator of sagebrush ecosystem health and have experienced widespread population decline associated with habitat loss and degradation, as well as changes in predator communities. Our objectives were to model and map sage-grouse habitat selection and survival during the important brood-rearing life stage in relation to landscape-scale environmental predictors. Furthermore, we sought to understand impacts of wildfire and annual grass invasion on brood habitat, as these accelerated disturbance regimes are a primary cause of habitat loss within the Great Basin region of the USA. We used a hierarchical Bayesian modeling framework to estimate resource selection functions and survival for early and late brood-rearing stages of sage-grouse in relation to a broad suite of habitat characteristics evaluated at multiple spatial scales within the Great Basin from 2009 to 2019. Sage-grouse selected for greater perennial grass cover, higher relative elevations, and areas closer to springs and wet meadows during both early and late brood-rearing. Terrain characteristics, including heat load and aspect, were important in survival models, as was variation in shrub height. We also found strong evidence for higher survival for both early and late broods within previously burned areas, but survival within burned areas decreased as annual grass cover (i.e. cheatgrass, Bromus tectorum) increased. This interaction effect demonstrates how invasion of annual grasses into burned areas, which has become prevalent in Great Basin sagebrush ecosystems, can lead to maladaptive habitat selection by brood-rearing greater sage-grouse. Understanding these complex relationships aids wildlife conservation and habitat management as wildfire and annual grass cycles continue to accelerate across western ecosystems.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.gecco.2022.e02147","usgsCitation":"Brussee, B.E., Coates, P.S., O’Neil, S.T., Casazza, M.L., Espinosa, S.P., Boone, J., Ammon, E., Gardner, S.C., and Delehanty, D.J., 2022, Invasion of annual grasses following wildfire corresponds to maladaptive habitat selection by a sagebrush ecosystem indicator species: Global Ecology and Conservation, v. 37, e02147, 19 p., https://doi.org/10.1016/j.gecco.2022.e02147.","productDescription":"e02147, 19 p.","ipdsId":"IP-133908","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":447908,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gecco.2022.e02147","text":"Publisher Index Page"},{"id":435856,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9B593DZ","text":"USGS data release","linkHelpText":"Spatially-Explicit Predictive Maps of Greater Sage-Grouse Brood Selection Integrated with Brood Survival in Nevada and Northeastern California, USA"},{"id":412740,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Nevada","otherGeospatial":"Great Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -115.11100469577016,\n 37.65679718030911\n ],\n [\n -114.01367957532398,\n 37.81079149850166\n ],\n [\n -114.06841886178916,\n 41.950546575009156\n ],\n [\n -120.51366289783158,\n 41.94877001660362\n ],\n [\n -120.95831043718897,\n 40.25557232247007\n ],\n [\n -120.37729928858255,\n 39.092072629058066\n ],\n [\n -119.0529053921718,\n 39.74527180686712\n ],\n [\n -117.0729066045891,\n 38.04894793599695\n ],\n [\n -115.11005550665487,\n 37.598613857563834\n ],\n [\n -115.11100469577016,\n 37.65679718030911\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"37","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Brussee, Brianne E. 0000-0002-2452-7101 bbrussee@usgs.gov","orcid":"https://orcid.org/0000-0002-2452-7101","contributorId":4249,"corporation":false,"usgs":true,"family":"Brussee","given":"Brianne","email":"bbrussee@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":863533,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coates, Peter S. 0000-0003-2672-9994 pcoates@usgs.gov","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":3263,"corporation":false,"usgs":true,"family":"Coates","given":"Peter","email":"pcoates@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":863534,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O’Neil, Shawn T. 0000-0002-0899-5220","orcid":"https://orcid.org/0000-0002-0899-5220","contributorId":206589,"corporation":false,"usgs":true,"family":"O’Neil","given":"Shawn","email":"","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":863535,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":863536,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Espinosa, Shawn P.","contributorId":195583,"corporation":false,"usgs":false,"family":"Espinosa","given":"Shawn","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":863537,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Boone, John D.","contributorId":300334,"corporation":false,"usgs":false,"family":"Boone","given":"John D.","affiliations":[{"id":65087,"text":"Great Basin Bird Observatory, Reno, Nevada, USA","active":true,"usgs":false}],"preferred":false,"id":863538,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ammon, Elisabeth M.","contributorId":302116,"corporation":false,"usgs":false,"family":"Ammon","given":"Elisabeth M.","affiliations":[{"id":65418,"text":"Great Basin Bird Observatory, 1755 E. Plumb Ln Ste 256 A, Reno, NV 89502, USA","active":true,"usgs":false}],"preferred":false,"id":863539,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gardner, Scott C.","contributorId":192081,"corporation":false,"usgs":false,"family":"Gardner","given":"Scott","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":863540,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Delehanty, David J.","contributorId":195584,"corporation":false,"usgs":false,"family":"Delehanty","given":"David","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":863541,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70236087,"text":"70236087 - 2022 - High‐frequency rupture processes of the 2014 Mw 8.2 Iquique and 2015 Mw 8.3 Illapel, Chile, earthquakes determined from strong‐motion recordings","interactions":[],"lastModifiedDate":"2022-08-29T12:07:32.607079","indexId":"70236087","displayToPublicDate":"2022-05-05T07:04:41","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"High‐frequency rupture processes of the 2014 Mw 8.2 Iquique and 2015 Mw 8.3 Illapel, Chile, earthquakes determined from strong‐motion recordings","docAbstract":"Strong‐motion recordings of the 2014
Feral burros (Equus asinus) and horses (E. ferus caballus) inhabiting public land in the western United States are intended to be managed at population levels established to promote a thriving, natural ecological balance. Double-observer sightability (MDS) models, which use detection records from multiple observers and sighting covariates, perform well for estimating feral horse abundances, but their effectiveness for use in burro populations is less understood. These MDS models help minimize detection bias, yet bias can be further reduced with models that account for unmodeled variation, or residual heterogeneity, in detection probability. In populations containing radio-marked individuals, residual heterogeneity can be estimated with MDS models by including a covariate that corresponds to the marked status of a group (MH models). Another approach is to use information from detections missed by both observers to account for the characteristics that make groups more or less likely to be detected, or recaptured, by the second observer (MR models). We used aerial survey data from 3 burro populations (Sinbad Herd Management Area, UT [2016–2018], Lake Pleasant Herd Management Area, AZ [2017], and Fort Irwin National Training Center, CA [2016–2017]) to develop MDS models applicable for feral burros in the southwestern United States. Our objectives were to quantify precision and bias of standard MDS surveys for feral burros and to examine which model type for incorporating residual heterogeneity (MH or MR) would result in the least-biased estimates of burro populations relative to the minimum number known alive (MNKA) within the Sinbad Herd Management Area. Standard MDS model estimates achieved a mean coefficient of variation of 0.08, while underestimating MNKA by an average of 27.1%. Accounting for residual heterogeneity through recapture probability in MR models resulted in estimates closer to MNKA than MH models (9.5% vs. 16.5% less than MNKA). Our results indicate that MDS models can achieve precise enough estimates to monitor feral burro populations, but they routinely produce negatively biased estimates. We encourage the use of radio-collars to reduce bias in future burro surveys by accounting for residual heterogeneity through MR models.
The widespread availability of high-fidelity topography combined with advances in geospatial analysis offer the opportunity to reimagine approaches to the difficult problem of predicting sediment delivery from watersheds. Here we present a model that uses high-resolution topography to filter sediment sources to quantify sediment delivery to the watershed outlet. It is a reduced-complexity, top-down model that defines transfer functions—topographic filters—between spatially distributed sediment sources and spatially integrated sediment delivery. The goal of the model is to forecast changes in watershed suspended sediment delivery in response to spatially distributed changes in sediment source magnitude or delivery, whether a result of watershed drivers or intentional management actions. Such an application requires the context of a watershed model that accounts for all sediment sources, enforces sediment mass balance throughout the spatial domain, and accommodates sediment storage and delivery over time. The model is developed for a HUC-8 watershed with a flat upland dominated by corn-soybean agriculture and deeply incised valleys near the watershed outlet with large sediment contributions from near-channel sources. Topofilter computes delivery and storage of field-derived sediment according to its spatial and structural connectivity to the stream channel network; subsequently, delivery of both field- and near-channel-derived sediment along with floodplain storage are computed in the stream channel network to the watershed outlet. The model outputs provide a spatially rich representation of sediment delivery and storage on field and along the stream that is consistent with available independent information on sediment accumulations and fluxes. Rather than a single best-calibrated solution, Topofilter uses the Generalized Likelihood Uncertainty Estimate (GLUE) approach to develop many possible solutions with sediment delivery rates expressed as probability distributions across the watershed. The ensemble of simulation outputs provides a useful basis for estimating uncertainty in sediment delivery and the effectiveness of different landscape management allocation across a watershed.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2022.155701","usgsCitation":"Cho, J., Wilcock, P.R., and Gran, K.B., 2022, Implementing landscape connectivity with topographic filtering model: A simulation of suspended sediment delivery in an agricultural watershed: Science of the Total Environment, v. 836, 155701, 16 p., https://doi.org/10.1016/j.scitotenv.2022.155701.","productDescription":"155701, 16 p.","ipdsId":"IP-127448","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":447923,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2022.155701","text":"Publisher Index Page"},{"id":400202,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","otherGeospatial":"Le Sueur River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.46868896484375,\n 43.61619382369185\n ],\n [\n -93.087158203125,\n 43.61619382369185\n ],\n [\n -93.087158203125,\n 44.27273816279087\n ],\n [\n -94.46868896484375,\n 44.27273816279087\n ],\n [\n -94.46868896484375,\n 43.61619382369185\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"836","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Cho, Jong 0000-0001-5514-6056","orcid":"https://orcid.org/0000-0001-5514-6056","contributorId":291384,"corporation":false,"usgs":true,"family":"Cho","given":"Jong","email":"","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":842241,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilcock, Peter R 0000-0001-5756-9829","orcid":"https://orcid.org/0000-0001-5756-9829","contributorId":291385,"corporation":false,"usgs":false,"family":"Wilcock","given":"Peter","email":"","middleInitial":"R","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":842242,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gran, Karen B.","contributorId":288093,"corporation":false,"usgs":false,"family":"Gran","given":"Karen","email":"","middleInitial":"B.","affiliations":[{"id":6915,"text":"University of Minnesota - Duluth","active":true,"usgs":false}],"preferred":true,"id":842243,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70231238,"text":"70231238 - 2022 - Amphibian mucus triggers a developmental transition in the frog-killing chytrid fungus","interactions":[],"lastModifiedDate":"2022-07-07T16:55:24.723137","indexId":"70231238","displayToPublicDate":"2022-05-04T08:40:27","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1352,"text":"Current Biology","active":true,"publicationSubtype":{"id":10}},"title":"Amphibian mucus triggers a developmental transition in the frog-killing chytrid fungus","docAbstract":"The frog-killing chytrid fungus Batrachochytrium dendrobatidis (Bd) is decimating amphibian populations around the world. Bd has a biphasic life cycle, alternating between motile zoospores that disperse within aquatic environments and sessile sporangia that grow within the mucus-coated skin of amphibians. Zoospores lack cell walls and swim rapidly through aquatic environments using a posterior flagellum and crawl across solid surfaces using actin structures similar to those of human cells. Bd transitions from this motile dispersal form to its reproductive form by absorbing its flagellum, rearranging its actin cytoskeleton, and rapidly building a chitin-based cell wall—a process called “encystation.” The resulting sporangium increases in volume by two or three orders of magnitude while undergoing rounds of mitosis without cytokinesis to form a large ceonocyte. The sporangium then cellurizes by dividing its cytoplasm into dozens of new zoospores. After exiting the sporangium through a discharge tube onto the amphibian skin, daughter zoospores can then reinfect the same individual or find a new host. Although encystation is critical to Bd growth, whether and how this developmental transition is triggered by external signals was previously unknown. We discovered that exposure to amphibian mucus triggers rapid and reproducible encystation within minutes. This response can be recapitulated with purified mucin, the bulk component of mucus, but not by similarly viscous methylcellulose or simple sugars. Mucin-induced encystation does not require gene expression but does require surface adhesion, calcium signaling, and modulation of the actin cytoskeleton. Mucus-induced encystation may represent a key mechanism for synchronizing Bd development with the arrival at the host.
","language":"English","publisher":"Cell Press","doi":"10.1016/j.cub.2022.04.006","usgsCitation":"Robinson, K.A., Prostak, S.M., Campbell Grant, E.H., and Fritz-Laylin, L.K., 2022, Amphibian mucus triggers a developmental transition in the frog-killing chytrid fungus: Current Biology, v. 32, no. 12, p. 2765-2771.e4, https://doi.org/10.1016/j.cub.2022.04.006.","productDescription":"12 p.","startPage":"2765","endPage":"2771.e4","ipdsId":"IP-139126","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":447925,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.cub.2022.04.006","text":"Publisher Index Page"},{"id":400128,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"32","issue":"12","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Robinson, Kristyn A.","contributorId":291342,"corporation":false,"usgs":false,"family":"Robinson","given":"Kristyn","email":"","middleInitial":"A.","affiliations":[{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false}],"preferred":false,"id":842115,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Prostak, Sarah M.","contributorId":291343,"corporation":false,"usgs":false,"family":"Prostak","given":"Sarah","email":"","middleInitial":"M.","affiliations":[{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false}],"preferred":false,"id":842116,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Campbell Grant, Evan H. 0000-0003-4401-6496 ehgrant@usgs.gov","orcid":"https://orcid.org/0000-0003-4401-6496","contributorId":150443,"corporation":false,"usgs":true,"family":"Campbell Grant","given":"Evan","email":"ehgrant@usgs.gov","middleInitial":"H.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":842117,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fritz-Laylin, Lillian K.","contributorId":291345,"corporation":false,"usgs":false,"family":"Fritz-Laylin","given":"Lillian","email":"","middleInitial":"K.","affiliations":[{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false}],"preferred":false,"id":842118,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}