Reducing phosphorus (P) concentrations in aquatic ecosystems, is necessary to improve water quality and reduce the occurrence of harmful cyanobacterial algal blooms. Managing P reduction requires information on the role rivers play in P transport from land to downstream water bodies, but we have a poor understanding of when and where river systems are P sources or sinks. During the summers of 2019 and 2021, we sampled streambed sediment at 78 sites throughout the Maumee River network (a major source of P loads to Lake Erie) focusing on the zero equilibrium P concentration (EPC0), the soluble reactive phosphorus (SRP) concentration at which sediment neither sorbs nor desorbs P. We used structural equation modeling to identify direct and indirect drivers of EPC0. Stream sediment was a P sink at 40 % and 67 % of sites in 2019 and 2021, respectively. During both years, spatial variation in EPC0 was shaped by stream water SRP concentrations, sediment P saturation, and sediment physicochemical characteristics. In turn, SRP concentrations and sediment P saturation (PSR) were influenced by agricultural land use and stream size. Effect of stream size differed among years with stream size having a greater effect on SRP in 2019 and on PSR in 2021. Streambed sediment is currently a net P sink across the sites sampled in the Maumee River network during summer, but sediment at these locations, especially sites in headwater streams, may become a P source if stream water SRP concentrations decrease. Our results improve the understanding of watershed- and reach-scale controls on EPC0 but also indicate the need for further research on how changes in SRP concentration as a result of conservation management implementation influences the role of streambed sediment in P transport to Lake Erie.
Resource managers and scientists across western U.S. agencies seek methodologies for identifying environmental attributes important to both wildlife conservation and broad-scale land stewardship. The Greater Sage-Grouse (Centrocercus urophasianus; hereafter, sage-grouse) exemplifies a species in need of this broad-scale approach given widespread population declines that have resulted from loss and degradation of habitat from natural and anthropogenic disturbances. These include agricultural land conversion, conifer expansion, energy development, and wildfire coupled with ecological conversion by invasive plants such as cheatgrass (Bromus tectorum). Development of habitat assessments and conservation actions for sage-grouse benefit from studies that link demographic responses to habitat selection patterns. To address this, we examined nest survival of sage-grouse in relation to fine-scale habitat patterns (i.e., field-based habitat measurements) that influenced nest site selection, using data from nests of telemetered females at 17 sites over 6 years in Nevada and northeastern California, USA. Importantly, sites spanned mesic and xeric average precipitation conditions that contributed substantially to vegetation community structure across cold desert ecosystems of the North American Great Basin. Vegetative cover immediately surrounding sage-grouse nests was important for both nest site selection and nest survival, but responses varied between mesic and xeric sites. For example, while taller perennial grasses were selected at xeric sites, we found no evidence of selection for perennial grass at mesic sites, indicating a functional response to availability of habitat features between hydrographic regions. Furthermore, perennial grass height and forb height both had positive effects on nest survival at xeric sites, but we found varying effects at mesic sites. We emphasize that precipitation conditions driving ecosystem productivity vary regionally among sagebrush communities, shaping vegetation structure and suitable habitat conditions for nesting sage-grouse.
","language":"English","publisher":"American Ornithological Society","doi":"10.1093/ornithapp/duac052","usgsCitation":"Brussee, B.E., Coates, P.S., O’Neil, S.T., Ricca, M.A., Dudko, J.E., Espinosa, S.P., Gardner, S.C., Casazza, M.L., and Delehanty, D.J., 2023, Influence of fine-scale habitat characteristics on sage-grouse nest site selection and nest survival varies by mesic and xeric site conditions: Ornithological Applications, v. 125, no. 1, duac052, 15 p., https://doi.org/10.1093/ornithapp/duac052.","productDescription":"duac052, 15 p.","ipdsId":"IP-123231","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":444825,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/ornithapp/duac052","text":"Publisher Index Page"},{"id":435505,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9EWKWJ3","text":"USGS data release","linkHelpText":"Code to Examine How the Influence of Fine-Scale Habitat Characteristics on Greater Sage-Grouse (Centrocercus urophasianus) Nest Site Selection and Nest Survival Varies by Mesic and Xeric Site Conditions version 1.0"},{"id":435504,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9JJ747B","text":"USGS data release","linkHelpText":"Influence of microhabitat characteristics on sage-grouse nest site selection and nest survival depends on ecological site potential"},{"id":412804,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"125","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-01-16","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":863775,"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":863776,"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":863777,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ricca, Mark A. 0000-0003-1576-513X mark_ricca@usgs.gov","orcid":"https://orcid.org/0000-0003-1576-513X","contributorId":139103,"corporation":false,"usgs":true,"family":"Ricca","given":"Mark","email":"mark_ricca@usgs.gov","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":863778,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dudko, Jonathan E.","contributorId":210049,"corporation":false,"usgs":false,"family":"Dudko","given":"Jonathan","email":"","middleInitial":"E.","affiliations":[{"id":38059,"text":"Idaho State U","active":true,"usgs":false}],"preferred":false,"id":863779,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Espinosa, Shawn P.","contributorId":195583,"corporation":false,"usgs":false,"family":"Espinosa","given":"Shawn","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":863780,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gardner, Scott C.","contributorId":192081,"corporation":false,"usgs":false,"family":"Gardner","given":"Scott","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":863781,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"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":863782,"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":863783,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70240633,"text":"70240633 - 2023 - Dissolved carbon export by large river systems is influenced by source area heterogeneity","interactions":[],"lastModifiedDate":"2023-02-10T12:54:31.17047","indexId":"70240633","displayToPublicDate":"2023-01-16T06:52:18","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1836,"text":"Global Biogeochemical Cycles","active":true,"publicationSubtype":{"id":10}},"title":"Dissolved carbon export by large river systems is influenced by source area heterogeneity","docAbstract":"Rivers and streams export inorganic and organic carbon derived from contributing landscapes and so downstream carbon fluxes are important quantitative indicators of change in ecosystem function and for the full accounting of terrestrial carbon budgets. Carbon concentration-discharge (C-Q) relationships in rivers provide important information about carbon source and behavior in watersheds and are useful for estimating carbon export. However, C-Q relationships are complex in large river systems because of spatial and temporal heterogeneity in carbon dynamics across the watershed and river networks. We quantified dissolved organic carbon (DOC) and dissolved inorganic carbon (DIC) fluxes in the Upper Mississippi River basin and investigated their relationships with land cover and hydrology. The magnitude of dissolved carbon yields ranged widely among stations, 0.6–5.7 g DOC m−2 yr−1 and 2.9–11.8 g DIC m−2 yr−1. Spatial patterns in carbon fluxes were strongly related to land cover, with agricultural sites having high DIC/low DOC exports and forested and wetland areas having the opposite. DIC was always negatively related to discharge (Q), while the DOC-Q relationship varied with land cover. Differential behavior of carbon across the basin resulted in Q having a weak relationship with DOC and DIC at the basin outlet. Hence, there is a need to improve understanding of headwater terrestrial-to-aquatic carbon connections in order to improve basin-to-continental-scale carbon export estimates. Our results demonstrate that quantitative understanding of carbon export by large rivers can be improved by incorporating stream network information, such as the timing, location, and source of constituent flux, rather than relying solely upon relationships between constituent behavior and seasonality or discharge at the basin outlet.
Genetic diversity is critical to a population’s ability to overcome gradual environment change. Large-bodied wildlife existing in regions with relatively high human population density are vulnerable to isolation-induced genetic drift, population bottlenecks, and loss of genetic diversity. Moose (Alces americanus americanus) in eastern North America have a complex history of drastic population changes. Current and potential threats to moose populations in this region could be exacerbated by loss of genetic diversity and connectivity among subpopulations. Existing genetic diversity, gene flow, and population clustering and fragmentation of eastern North American moose are not well quantified, while physical and anthropogenic barriers to population connectivity already exist. Here, single nucleotide polymorphism (SNP) genotyping of 507 moose spanning five northeastern U.S. states and one southeastern Canadian province indicated low diversity, with a high proportion of the genomes sharing identity-by-state, with no consistent evidence of non-random mating. Gene flow estimates indicated bidirectionality between all pairs of sampled areas, with magnitudes reflecting clustering and differentiation patterns. A Discriminant Analysis of Principal Components analysis indicated that these genotypic data were best described with four clusters and indicated connectivity across the Saint Lawrence River and Seaway, a potential physical barrier to gene flow. Tests for genetic differentiation indicated restricted gene flow between populations across the Saint Lawrence River and Seaway, and between many sampled areas facing expanding human activity. These results document current genetic variation and connectivity of moose populations in eastern North America, highlight potential challenges to current population connectivity, and identify areas for future research and conservation.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s10592-022-01496-w","usgsCitation":"Rosenblatt, E., Gieder, K., Donovan, T.M., Murdoch, J., Smith, T., Stephanie McKay, Heaton, M., Kalbfleisch, T., Murdoch, B., Bhattarai, S., Pacht, E., Verbist, E., Basnayake, V., and McKay, S., 2023, Genetic diversity and connectivity of moose (Alces americanus americanus) in eastern North America: Conservation Genetics, v. 24, p. 235-248, https://doi.org/10.1007/s10592-022-01496-w.","productDescription":"14 p.","startPage":"235","endPage":"248","ipdsId":"IP-139721","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":481070,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10592-022-01496-w","text":"Publisher Index Page"},{"id":480758,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"New York, 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California","interactions":[],"lastModifiedDate":"2023-01-18T14:25:55.153483","indexId":"70239758","displayToPublicDate":"2023-01-15T08:20:21","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Changes in habitat suitability for wintering dabbling ducks during dry conditions in the Central Valley of California","docAbstract":"In arid and Mediterranean regions, landscape-scale wetland conservation requires understanding how wildlife responds to dynamic freshwater availability and conservation actions to enhance wetland habitat. Taking advantage of Landsat satellite data and structured and community science bird survey data, we built species distribution models to describe how three duck species, the Northern Pintail (Anas acuta), Green-winged Teal (Anas crecca), and Northern Shoveler (Anas clypeata), respond to freshwater supply and food resources on different flooded land cover types in the Central Valley of California. Specifically, our models compared duck habitat suitability between the wettest and driest conditions in each month from September through April. Using abundance-weighted boosted regression trees, we created three sets of species occurrence models based on different covariates: (1) near real-time (hereafter “real-time”) covariates in which duck observations were matched to the water availability within the 16-day window of a Landsat observation, (2) a combination of real-time covariates and waterfowl food resource covariates describing annual corn and rice biomass and managed wetland moist soil seed yield estimates derived from Landsat data, and (3) long-term average covariates—the most common approach to species distribution modeling—in which long-term average surface water availability was used. We modeled the monthly occurrence of three duck species as a function of surface water availability, land cover type, road density, temperature, and bird data source. We found that dry conditions result in reduced habitat suitability, with the biggest reductions in November through January and in agricultural fields; in contrast, suitability of flooded wetland habitat was relatively robust to surface water availability. When models of habitat suitability based on long-term average climate conditions were compared to models based on real-time conditions, the highest long-term suitability values occurred in areas where suitability was high regardless of whether it was a wet or a dry year. While all models performed well, the inclusion of crop and wetland plant yield covariates resulted in slightly higher model performance. Overall, species distribution models created using data on the environmental conditions present at the time of bird observations can aid conservation efforts under extreme conditions over large spatial scales.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.4367","usgsCitation":"Conlisk, E.E., Byrd, K.B., Matchett, E., Lorenz, A., Casazza, M.L., Golet, G.H., Reynolds, M.D., Sesser, K.A., and Reiter, M.E., 2023, Changes in habitat suitability for wintering dabbling ducks during dry conditions in the Central Valley of California: Ecosphere, v. 14, e4367, 19 p., https://doi.org/10.1002/ecs2.4367.","productDescription":"e4367, 19 p.","ipdsId":"IP-144890","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":444827,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4367","text":"Publisher Index Page"},{"id":412024,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Central Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n 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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":861779,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Golet, Gregory H.","contributorId":89844,"corporation":false,"usgs":false,"family":"Golet","given":"Gregory","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":861780,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Reynolds, Mark D.","contributorId":301023,"corporation":false,"usgs":false,"family":"Reynolds","given":"Mark","email":"","middleInitial":"D.","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":861781,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sesser, Kristin 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restoration","interactions":[],"lastModifiedDate":"2023-03-28T14:38:56.423278","indexId":"70239935","displayToPublicDate":"2023-01-15T07:09:45","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Nest-site selection model for endangered Everglade snail kites to inform ecosystem restoration","docAbstract":"dictors of nesting for snail kites in south Florida. The results of our modeling indicate that hydrology, percent canopy cover, and proximity to recently burned areas were the most important factors associated with nest-site selection for snail kites. Water depths between 75 and 100 cm, water recession rates between 0 and 1.25 cm/day, percent canopy covers <20%, and areas <10 km from recently burned habitat were associated with the greatest likelihood of nest-site selection. KiteNest is applicable to natural resource management decisions in the Everglades and may be useful independently or in conjunction with other ecological models for restoration decision support.
Irregularly flooded wetlands are found above the mean high water tidal datum and are exposed to tides and saltwater less frequently than daily. These wetlands provide important ecosystem services, such as providing habitat for fish and wildlife, enhancing water quality, ameliorating flooding impacts, supporting coastal food webs, and protecting upslope areas from erosion. Mapping irregularly flooded wetlands is challenging given their expansive coverage and dynamic nature. Furthermore, coastal wetlands are expected to change over the coming century due to sea-level rise and changes in the frequency and intensity of extreme storms. Consequently, coastal managers need baseline information on the spatial distribution of wetlands along with efficient and repeatable methods for observing changes. In this study, we used coastal wetlands from existing land use land cover data, best available lidar-derived digital elevation models, and Monte Carlo simulations to incorporate elevation uncertainty to create a probabilistic map of irregularly flooded wetlands along the northern Gulf of Mexico coast (USA). Our approach integrated findings from a review of coastal wetland elevation error in lidar datasets and an analysis of spatial autocorrelations of wetland elevation. We found a positive correlation (r = 0.563, p < 0.0001) when comparing the probability estimated from a digital elevation model and in situ elevation observations. The differences in probability had a mean bias error of −0.04 (i.e., digital elevation model-based probability tends to be slightly lower), a mean absolute error of 0.20, and a root mean square error of 0.26. Beyond this overall validation, we explored error metrics for land cover classes and lidar collection details. To quantify areal coverage of the probabilistic output, we classified the probability values into equal bins using an interval of 0.33. The areal coverage of the lowest probability bin (“unlikely”; probability ≤0.33) was separated into the upper and lower portions of the irregularly flooded wetland zone. Of the coastal wetlands along the northern Gulf of Mexico coast about 38% were classified as unlikely and low with the greatest coverage in south Louisiana and the Everglades and around 33% were classified as unlikely and high with the greatest coverage in the Everglades and Texas. The relative coverage within the highest probability bin (“likely”; probability >0.66) covered around 13%, with the greatest coverage in south Florida, south Louisiana, and Texas. The framework developed in this study can be transferred to other coastal wetland areas and updated to observe changes with sea-level rise.
As a part of the Texas Water Development Board groundwater availability modeling program, the U.S. Geological Survey developed the Gulf Coast Land Subsidence and Groundwater-Flow model (hereinafter, the “GULF model”) and ensemble to simulate groundwater flow and land-surface subsidence in the northern part of the Gulf Coast aquifer system (the study area) in Texas from predevelopment (1897) through 2018. Since the publication of a previous groundwater model for the greater Houston area in 2012, there have been changes to the distribution of groundwater withdrawals and advances in modeling tools. To reflect these changes and to simulate more recent conditions, the GULF model was developed in cooperation with the Harris-Galveston and Fort Bend Subsidence Districts to provide an updated Groundwater Availability Model.
Since the early 1900s, most of the groundwater withdrawals in the study area have been from three of the hydrogeologic units that compose the Gulf Coast aquifer system—the Chicot, Evangeline, and Jasper aquifers and, more recently, from the Catahoula confining unit. Withdrawals from these hydrogeologic units are used for municipal supply, commercial and industrial use, and irrigation purposes. Withdrawals of large quantities of groundwater in the greater Houston area have caused widespread groundwater-level declines in the Chicot, Evangeline, and Jasper aquifers of more than 300 feet (ft). Early development of the aquifer system, which began before 1900, resulted in nearly 50 percent of the eventual historical groundwater-level minimums having been reached as early as 1946 in some areas. These groundwater-level declines led to more than 9 ft of land-surface subsidence—historically in central and southeastern Harris County and Galveston County, but more recently in northern, northwestern, and western Harris County, Montgomery County, and northern Fort Bend County—from depressurization and compaction of clay and silt layers interbedded in the aquifer sediments.
In a generalized conceptual model of the Gulf Coast aquifer system, water enters the groundwater system in topographically high outcrops of the hydrogeologic units in the northwestern part of the aquifer system. Groundwater that does not discharge to streams flows to intermediate and deep zones of the aquifer system southeastward of the outcrop areas where it is discharged by wells and by upward leakage in topographically low areas near the coast. The uppermost parts of the aquifer system, which include outcrop areas, are under water-table (unconfined) conditions where the groundwater is not confined under pressure. As depth increases in the aquifer system and interbedded clay and silt layers accumulate, water-table conditions evolve into confined conditions where the groundwater is under pressure.
Groundwater flow and land-surface subsidence in the GULF model and ensemble were simulated by using MODFLOW 6 with the Skeletal Storage, Compaction, and Subsidence package. The model consists of six layers, one for each of the five hydrogeologic units in the northern part of the Gulf Coast aquifer system and a surficial top layer that includes part of each hydrogeologic unit. Transient groundwater flow was simulated during 1897–2018 by using a combination of multiyear, annual, and monthly stress periods. An initial steady-state stress period was configured to represent predevelopment mean annual inflows and outflows. The subsidence package used in the GULF model and ensemble uses a head-based subsidence formulation that simulates the delayed drainage response from clay and silt sediment to changes in groundwater levels.
The GULF model and ensemble were history matched to groundwater-level observations at selected wells, land-surface subsidence at benchmarks, aquifer compaction at borehole extensometers, and vertical displacement from Global Positioning System stations. A Bayesian framework was used to represent uncertainty in modeled parameters and simulated outputs of interest. History matching and uncertainty quantification were performed by using a Monte Carlo approach enabled through iterative ensemble smoother software to produce an ensemble of models fit to historical data. The iterative ensemble smoother substantially reduced the computational demand of parameter estimation by approximating the first-order relation between model inputs and outputs, thereby allowing 183,207 adjustable parameters to be used for history matching at a relatively low computational and time cost.
The history-matched parameter values are within the ranges of previously published values and agree with the current understanding of the spatial and temporal patterns of parameter uncertainty for the Gulf Coast aquifer system. A good agreement between the observed (or estimated) and simulated groundwater levels, land-surface subsidence, compaction, and vertical displacement was obtained across the modeled area based on qualitative and quantitative comparisons. Ensemble mean annual groundwater-flow rates to the Chicot, Evangeline, Jasper aquifers and Catahoula confining unit were 0.0–0.49 inch (in.), 0.09–0.33 in., 0.01–0.07 in., and 0.01–0.05 in., respectively. GULF model mean annual groundwater-flow rates to the Chicot, Evangeline, and Jasper aquifers and Catahoula confining unit were 0.31 in., 0.19 in., 0.03 in., and 0.03 in., respectively.
The GULF-model-simulated recharge to the outcrop area was the largest inflow (75 percent), and recharge to other areas was 25 percent of the model inflow. The simulated outflows included (1) net surface-water/groundwater exchange with study area streams (50 percent), (2) groundwater use (49 percent), and (3) net surface-water/groundwater exchange with the Gulf of Mexico (1 percent). The sum of the simulated values of the outflows (1,041,973 acre-feet per year [acre-ft/yr]) and the elastic expansion of the fine-grained sediment and numerical solver error (339 acre-ft/yr) minus the inflows (654,172 acre-ft/yr) represents the reduction of storage from the Gulf Coast aquifer system (388,140 acre-ft/yr). Most of the storage depletion is caused by the long-term groundwater-level declines that have resulted primarily in inelastic compaction.
The GULF model was used to estimate Jasper aquifer compaction at selected benchmarks in Montgomery County and northern Harris County, which are the primary locations of Jasper aquifer groundwater use. Simulated Jasper aquifer compaction in northern Harris County was between 0.2 and 0.5 ft, or between about 5 and 16 percent of simulated subsidence at the benchmark locations. Simulated Jasper aquifer compaction in Montgomery County was between 0.8 and 1.2 ft, or between about 33 and 57 percent of simulated subsidence at the benchmark locations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1877","issn":"ISSN 2330-7102","collaboration":"Prepared in cooperation with the Harris-Galveston Subsidence District and the Fort Bend Subsidence District","usgsCitation":"Ellis, J.H., Knight, J.E., White, J.T., Sneed, M., Hughes, J.D., Ramage, J.K., Braun, C.L., Teeple, A., Foster, L., Rendon, S.H., and Brandt, J., 2023, Hydrogeology, land-surface subsidence, and documentation of the Gulf Coast Land Subsidence and Groundwater-Flow (GULF) model, southeast Texas, 1897–2018 (ver. 1.1, November 2023): U.S. Geological Survey Professional Paper 1877, 425 p., https://doi.org/10.3133/pp1877.","productDescription":"Report: xx, 425 p., 8 Appendixes; Data Release","numberOfPages":"450","onlineOnly":"Y","ipdsId":"IP-127938","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":500160,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114230.htm","linkFileType":{"id":5,"text":"html"}},{"id":422702,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/pp/pp1877/versionHist.txt","linkFileType":{"id":2,"text":"txt"}},{"id":411889,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XM8A1P","text":"USGS Data Release","linkHelpText":"MODFLOW 6 model and ensemble used in the simulation of groundwater flow and land-surface subsidence in the northern part of the Gulf Coast aquifer system, 1897–2018"},{"id":422705,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/pp1877/coverthb2.jpg"},{"id":411888,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/pp1877/pp1877.pdf","text":"Report","size":"184 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Texas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -93.54245107965883,\n 31.199747848944256\n ],\n [\n -96.33297842340923,\n 30.997489619299927\n ],\n [\n -96.79440420465926,\n 30.136679255787612\n ],\n [\n -96.02536123590899,\n 28.551820525825022\n ],\n [\n -95.36068838434645,\n 28.86498475853952\n ],\n [\n -94.72348135309639,\n 29.28746086219381\n ],\n [\n -94.65207022028405,\n 29.402380282489133\n ],\n [\n -94.23458975153387,\n 29.574516044800063\n ],\n [\n -93.82809561090883,\n 29.670020494605353\n ],\n [\n -93.89401357965892,\n 29.803574466610613\n ],\n [\n -93.6907665093464,\n 30.05113045792723\n ],\n [\n -93.67428701715903,\n 30.307554456695556\n ],\n [\n -93.6687938530968,\n 30.563309394138372\n ],\n [\n -93.49301260309677,\n 30.841976559030968\n ],\n [\n -93.4765331109094,\n 31.077503645282718\n ],\n [\n -93.54245107965883,\n 31.199747848944256\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Version 1.0: January 13, 2023; Version 1.1: November 28, 2023","contact":"Director, Oklahoma-Texas Water Science Center
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Groundwater is the primary source of drinking water in the Coachella Valley in the desert region of southern California. Although most people in Coachella Valley are served by public drinking-water systems, about 20,000 people rely on private domestic or small-system wells (referred to herein as domestic wells). Recently, the U.S. Geological Survey (USGS) found that 39 percent of the groundwater resources used by domestic wells in Coachella Valley contained arsenic, fluoride, or both constituents at concentrations greater than the maximum contaminant levels established for public drinking-water systems. Uranium, chromium, nitrate, and perchlorate were detected at moderate concentrations below maximum contaminant levels. Elevated (above background) perchlorate concentrations in some areas indicate that domestic wells may receive recharge from Colorado River water used for irrigation or aquifer replenishment. Moderate total dissolved solids (TDS) concentrations throughout the study area and the co-occurrence of high concentrations of TDS and perchlorate indicates that Colorado River water is a source of recharge in the southeastern Indio groundwater subbasin. Four volatile organic compounds were detected at low concentrations, and pesticides and per- and polyfluoroalkyl substances were not detected.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221122","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Soldavini, A.L., Harkness, J.S., Levy, Z.F., and Fram, M.S., 2023, Quality of groundwater used for domestic drinking-water supply in the Coachella Valley, 2020: U.S. Geological Survey Open-File Report 2022-1122, 6 p., https://doi.org/10.3133/ofr20221122.","productDescription":"Report: 6 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-127493","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":411823,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9UYXI95","text":"USGS data release","description":"USGS data release","linkHelpText":"Groundwater-quality data in the Coachella Valley Domestic Supply Aquifer Study Unit, 2020: Results from the California GAMA Priority Basin 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U.S. Geological Survey
California Water Science Center
6000 J Street, Placer Hall
Sacramento, CA 95819
Telephone number: (916) 278-3000
Unit Chief State Water Resources Control Board Division of Water Quality
P.O. Box 2231, Sacramento, CA 95812
Telephone number: (916) 341-5779
Differences in the life history pathways (LHPs) of juvenile animals are often associated with differences in demographic rates in later life stages. For migratory animals, different LHPs often result in animals from the same population occupying distinct habitats subjected to different environmental drivers. Understanding how demographic rates differ among animals expressing different LHPs may reveal fitness trade-offs that drive the expression of alternative LHPs and enable better prediction of population dynamics in a changing environment. To understand how demographic outcomes and their relationships with environmental variables differ among animals with different LHPs, we analyzed a long-term (2006–2021) mark–recapture dataset for Chinook salmon (Oncorhynchus tshawytscha) from the Wenatchee River, Washington, USA. Distinct LHPs represented in this population include either remaining in the natal stream until emigrating to the ocean as a 1-year-old (natal-reach rearing) or emigrating from the natal stream and rearing in downstream habitats for several months before completing the emigration to the ocean as a 1-year-old (downstream rearing). We found that downstream-rearing fish emigrated to the ocean 19 days earlier on average and returned as adults from the ocean at higher rates. We detected a positive correlation between rate of return from the ocean by downstream-rearing fish and coastal upwelling in their spring of outmigration, whereas for natal-reach-rearing fish we detected a positive correlation with sea surface temperature during their first marine summer. Different responses to environmental variability should lead to asynchrony in adult abundance among juvenile LHPs. A higher proportion of downstream-rearing fish returned at younger ages compared with natal-reach-rearing fish, which contributed to variability in age at reproduction and greater mixing across generations. Our results demonstrate how diversity in juvenile LHPs is associated with heterogeneity in demographic rates during subsequent life stages, which can in turn affect variance in aggregate population abundance and response to environmental change. Our findings underscore the importance of considering life history diversity in demographic analyses and provide insights into the effects of life history diversity on population dynamics and trade-offs that contribute to the maintenance of life history diversity.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.4366","usgsCitation":"Sorel, M.H., Murdoch, A.R., Zabel, R.W., Jorgensen, J.C., Kamphaus, C.M., and Converse, S.J., 2023, Juvenile life history diversity is associated with lifetime individual heterogeneity in a migratory fish: Ecosphere, v. 14, no. 1, e4366, 14 p., https://doi.org/10.1002/ecs2.4366.","productDescription":"e4366, 14 p.","ipdsId":"IP-141079","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":444836,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4366","text":"Publisher Index Page"},{"id":430212,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Wenatchee River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.2,\n 48.2\n ],\n [\n -121.2,\n 47.4\n ],\n [\n -120.2,\n 47.4\n ],\n [\n -120.2,\n 48.2\n ],\n [\n -121.2,\n 48.2\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"14","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-01-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Sorel, Mark H.","contributorId":171739,"corporation":false,"usgs":false,"family":"Sorel","given":"Mark","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":903770,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Murdoch, Andrew R.","contributorId":339213,"corporation":false,"usgs":false,"family":"Murdoch","given":"Andrew","email":"","middleInitial":"R.","affiliations":[{"id":12438,"text":"Washington Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":903771,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zabel, Richard W.","contributorId":272049,"corporation":false,"usgs":false,"family":"Zabel","given":"Richard","email":"","middleInitial":"W.","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":903772,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jorgensen, Jeffrey C.","contributorId":339208,"corporation":false,"usgs":false,"family":"Jorgensen","given":"Jeffrey","email":"","middleInitial":"C.","affiliations":[{"id":36612,"text":"National Marine Fisheries Service","active":true,"usgs":false}],"preferred":false,"id":903773,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kamphaus, Cory M.","contributorId":339215,"corporation":false,"usgs":false,"family":"Kamphaus","given":"Cory","email":"","middleInitial":"M.","affiliations":[{"id":39287,"text":"Yakama Nation Fisheries","active":true,"usgs":false}],"preferred":false,"id":903774,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Converse, Sarah J. 0000-0002-3719-5441 sconverse@usgs.gov","orcid":"https://orcid.org/0000-0002-3719-5441","contributorId":173772,"corporation":false,"usgs":true,"family":"Converse","given":"Sarah","email":"sconverse@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":903775,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70240158,"text":"70240158 - 2023 - Genetic basis of thiaminase I activity in a vertebrate, zebrafish Danio rerio","interactions":[],"lastModifiedDate":"2023-01-31T13:17:58.425689","indexId":"70240158","displayToPublicDate":"2023-01-13T07:15:57","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Genetic basis of thiaminase I activity in a vertebrate, zebrafish Danio rerio","docAbstract":"Thiamine (vitamin B1) metabolism is an important driver of human and animal health and ecological functioning. Some organisms, including species of ferns, mollusks, and fish, contain thiamine-degrading enzymes known as thiaminases, and consumption of these organisms can lead to thiamine deficiency in the consumer. Consumption of fish containing thiaminase has led to elevated mortality and recruitment failure in farmed animals and wild salmonine populations around the world. In the North American Great Lakes, consumption of the non-native prey fish alewife (Alosa pseudoharengus) by native lake trout (Salvelinus namaycush) led to thiamine deficiency in the trout, contributed to elevated fry mortality, and impeded natural population recruitment. Several thiaminases have been genetically characterized in bacteria and unicellular eukaryotes, and the source of thiaminase in multicellular organisms has been hypothesized to be gut microflora. In an unexpected discovery, we identified thiaminase I genes in zebrafish (Danio rerio) with homology to bacterial tenA thiaminase II. The biochemical activity of zebrafish thiaminase I (GenBank NP_001314821.1) was confirmed in a recombinant system. Genes homologous to the zebrafish tenA-like thiaminase I were identified in many animals, including common carp (Cyprinus carpio), zebra mussel (Dreissena polymorpha) and alewife. Thus, the source of thiaminase I in alewife impacting lake trout populations is likely to be de novo synthesis.
Mercury (Hg) exposure to fish, wildlife, and humans is widespread and of global concern, thus stimulating efforts to reduce emissions. Because the relationships between rates of inorganic Hg loading, methylmercury (MeHg) production, and bioaccumulation are extremely complex and challenging to predict, there is a need for reliable biosentinels to understand the distribution of Hg in the environment and monitor the effectiveness of reduction efforts. However, it is important to assess how temporal and spatial variation at multiple scales influences the efficacy of specific biosentinels. Seasonal and interannual variation in total Hg (THg) concentrations of dragonfly larvae were examined in relation to spatial variability among 21 sites in two U.S. national parks with contrasting ecologies and Hg deposition patterns. Dragonfly THg differed among sampling events at 17 of the 21 sites, but by an average of only 20.4 % across events, compared to an average difference of 52.7 % among sites. Further, THg concentrations did not follow consistent seasonal patterns across sites or years, suggesting that the observed temporal variation was unlikely to bias monitoring efforts. Importantly, for a specific site, there was no difference in % MeHg in dragonflies among sampling events. Finally, there was significant temporal variability in the biogeochemical factors (aqueous inorganic Hg, aqueous MeHg, DOC, SO4, and pH) influencing dragonfly THg, with the importance of individual factors varying by 2.4 to 4.3-fold across sampling events. Despite these results, it is noteworthy that the observed temporal variation in dragonfly THg concentrations was neither large nor consistent enough to bias spatial assessments. Thus, although this temporal variation may provide insights into the processes influencing biological Hg concentrations, it is unlikely to impair the use of dragonflies as biosentinels for monitoring spatial or temporal patterns at scales relevant to most mitigation efforts.
Plecoptera (stoneflies) are an order of insects where most species rely on clean, fast-moving freshwater for an aquatic larval stage followed by a short terrestrial adult stage. Most species of Plecoptera seem to be restricted to specific stream types and thermal regimes. Climate-driven changes are likely to alter stream temperatures and flow, resulting in physiological stress, reduced reproductive success, and possibly latitudinal or elevational distribution shifts. This report focuses on climate projections and the resulting ecological effect for three species of Appalachian stoneflies: Remenus kirchneri, Acroneuria kosztarabi, and Tallaperla lobata. Although species-specific information is sparse for these three species, climate studies for other Plecoptera spp. are applicable. In the focal region, temperature is increasing and likely leading to increased stream temperatures. In response, Plecoptera spp. will likely experience physiological stress from increasing metabolic rates and energy demands concurrent with changing food quality and access. Warming temperatures and decreased larval energy stores are likely to contribute to lower adult body size and longevity, thus decreasing reproductive success. Whereas projected changes to precipitation and runoff are less certain, under drier future climate projections, decreased streamflow may further stress larval Plecoptera. Remenus kirchneri, A. kosztarabi, and T. lobata will likely retain stable permanent stream habitats for the analyzed future (2006–99). Changing climate is of particular concern for mountaintop species R. kirchneri and T. lobata because they may be unable to track shifts in suitable climate and habitat.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Effects of climate change on fish and wildlife species in the United States","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211104B","usgsCitation":"Lyons, M.P., Nikiel, C.A., LeDee, O.E., and Boyles, R., 2023, Potential effects of climate change on Appalachian stoneflies (Remenus kirchneri, Acroneuria kosztarabi, and Tallaperla lobata): U.S. Geological Survey Open-File Report 2021–1104–B, 41 p., https://doi.org/10.3133/ofr20211104B.","productDescription":"Report: viii, 41 p.; Data release","numberOfPages":"54","onlineOnly":"Y","ipdsId":"IP-141912","costCenters":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":411793,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9B2O22V","text":"USGS data release","linkHelpText":"CMIP5 MACAv2-METDATA monthly water balance model projections 1950–2099 for the contiguous United States"},{"id":411792,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1104/b/images"},{"id":411791,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1104/b/ofr20211104b.XML"},{"id":411790,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1104/b/ofr20211104b.pdf","text":"Report","size":"74.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021–1104–B"},{"id":411789,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1104/b/coverthb.jpg"}],"country":"United States","state":"North Carolina, Tennessee, Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -84.36021079719424,\n 35.42843231038343\n ],\n [\n -78.2983320325932,\n 35.42843231038343\n ],\n [\n -78.2983320325932,\n 38.58463308582091\n ],\n [\n -84.36021079719424,\n 38.58463308582091\n ],\n [\n -84.36021079719424,\n 35.42843231038343\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Midwest Climate Adaptation Science Center
U.S. Geological Survey
1954 Buford Avenue
St. Paul, MN 55108
Snow Lake, a glacially dammed lake on the Snow Glacier near Seward, Alaska, drains rapidly every 14 months–3 years, causing flooding along the Snow River. Highway, railroad, and utility infrastructure on the lower Snow River floodplain is vulnerable to flood damage. Historical hydrology, geomorphology, and two-dimensional hydraulic and sediment transport modeling were used to assess the flood risks from Snow Lake outburst floods. Floods have become more frequent, peaked more rapidly, and have had generally higher peaks over the last 20 years as the Snow Glacier has thinned, translating to a greater potential for flood damage. Rapidly shifting channel locations and the occasional introduction of large volumes of debris to the river also threaten infrastructure on the floodplain and in the channel. An assessment of the historical channel planform between 1951 and 2019 showed that there have been more and less stable segments along the lower Snow River and that channel migration has generally been toward the east. An analysis of floodplain elevations using 2008 light detection and ranging (lidar) showed that the main channel is relatively high compared to floodplain channels that carry floodwaters along the railroad grade, so that once the main channel banks are overtopped water rapidly disperses throughout the floodplain. A two-dimensional flow and sediment transport model was developed, and its simulation results were compared to three past outburst floods from 2007, 2017, and 2019. Despite the complex floodplain and channel geometry, coarse resolution of the mesh, and sediment input data, the model successfully simulated areas of observed scour along the railroad grade and at the guidebank to the highway bridge. The modeled water-surface elevations generally replicated peak elevations recorded at a streamgage in the middle of the model domain and at pressure transducers installed on the floodplain and main channel, although there were discrepancies on the rising limb and some locations had a poorer fit than others. A model of a hypothetical check flood, approximately 150 percent of the largest recorded outburst flood, was developed to provide hydraulic variables to use when planning for infrastructure upgrades.
Alaska Science Center
U.S. Geological Survey
4210 University Drive
Anchorage, Alaska 99508
One of the most critical challenges we face today is access to clean water. Climate change, industrialization, high rates of urbanization, and population growth have resulted in many countries suffering from water crises, especially in the arid and semi-arid areas. Countries in different regions of the world have also been struggling over regional water availability and it is anticipated that these struggles may result in conflicts over shared water resources in these regions. Considering the adverse consequences of the water crisis, countries have been trying to increasingly cope with this problem of water availability by implementing sustainable water management plans and looking for alternative water supply sources.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fenvs.2023.1132758","usgsCitation":"Bustos-Terrones, Y.A., Norman, L., Perez-Estrada, L., El Nemr, A., and Bandala, E.R., 2023, Editorial: Advanced physico-chemical technologies for water detoxification and disinfection: Frontiers in Environmental Science, v. 11, 1132758, 3 p., https://doi.org/10.3389/fenvs.2023.1132758.","productDescription":"1132758, 3 p.","ipdsId":"IP-147820","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":444843,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fenvs.2023.1132758","text":"Publisher Index Page"},{"id":416549,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","noUsgsAuthors":false,"publicationDate":"2023-01-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Bustos-Terrones, Yaneth A.","contributorId":304606,"corporation":false,"usgs":false,"family":"Bustos-Terrones","given":"Yaneth","email":"","middleInitial":"A.","affiliations":[{"id":66127,"text":"CONACYT - Division of Postgraduate Studies and Research, Technological Institute of Culiacan, Culiacan, Sinaloa, Mexico.","active":true,"usgs":false}],"preferred":false,"id":871141,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Norman, Laura M. 0000-0002-3696-8406","orcid":"https://orcid.org/0000-0002-3696-8406","contributorId":203300,"corporation":false,"usgs":true,"family":"Norman","given":"Laura M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":871142,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Perez-Estrada, Leonidas","contributorId":304607,"corporation":false,"usgs":false,"family":"Perez-Estrada","given":"Leonidas","email":"","affiliations":[{"id":65218,"text":"EURECAT, Spain","active":true,"usgs":false}],"preferred":false,"id":871143,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"El Nemr, Ahmed","contributorId":304608,"corporation":false,"usgs":false,"family":"El Nemr","given":"Ahmed","email":"","affiliations":[{"id":66129,"text":"Environment Division, National Institute of Oceanography and Fisheries (NIOF), Kayet Bey, Elanfoushy, Alexandria, Egypt. E-mail: ahmedmoustafaelnemr@yahoo.com","active":true,"usgs":false}],"preferred":false,"id":871144,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bandala, Erick R.","contributorId":304605,"corporation":false,"usgs":false,"family":"Bandala","given":"Erick","email":"","middleInitial":"R.","affiliations":[{"id":66126,"text":"Division of Hydrologic Sciences. Desert Research Institute. 755 E. Flamingo Road, Las Vegas, Nevada 89119, USA, Tel: 702 862 5395, e-mail: erick.bandala@dri.edu","active":true,"usgs":false}],"preferred":false,"id":871140,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70252492,"text":"70252492 - 2023 - Broadening benefits and anticipating tradeoffs with a proposed ecosystem service analysis framework for the US Army Corps of Engineers","interactions":[],"lastModifiedDate":"2024-03-26T12:04:21.344614","indexId":"70252492","displayToPublicDate":"2023-01-12T06:59:37","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1547,"text":"Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Broadening benefits and anticipating tradeoffs with a proposed ecosystem service analysis framework for the US Army Corps of Engineers","docAbstract":"Would-be adopters of ecosystem service analysis frameworks might ask, ‘Do such frameworks improve ecosystem service provision or social benefits sufficiently to compensate for any extra effort?’ Here we explore that question by retrospectively applying an ecosystem goods and services (EGS) analysis framework to a large river restoration case study conducted by the US Army Corps of Engineers (USACE) and comparing potential time costs and outcomes of traditional versus EGS-informed planning. USACE analytic methods can have a large influence on which river and wetland restoration projects are implemented in the United States because they affect which projects or project elements are eligible for federal cost-share funding. A new framework is designed for the USACE and is primarily distinguished from current procedures by adding explicit steps to document and compare tradeoffs and complementarity among all affected EGS, rather than the subset that falls within project purposes. Further, it applies economic concepts to transform ecological performance indicators into social benefit indicators, even if changes cannot be valued. We conclude that, for large multi-partner restoration projects like our case study, using the framework provides novel information on social outcomes that could be used to enhance project design, without substantially increasing scoping costs. The primary benefits of using the framework in the case study appeared to stem from early comprehensive identification of stakeholder interests that might have prevented project delays late in the process, and improving the communication of social benefits and how tradeoffs among EGS benefits were weighed during planning.
Biodiversity conservation under a changing climate is a challenging endeavor. Landscapes are shifting as a result of climate change and sea level rise but plant communities in particular may not keep up with the pace of change. Predictive ecological models can help decision makers understand how species are likely to respond to change and then adjust management actions to align with desired future conditions. Florida’s Everglades is a wetland ecosystem that is host to many species, including a large number of endangered and endemic species. Everglades ecosystem restoration has been ongoing for decades, but consideration of sea level rise impacts in restoration planning is more recent. Incorporating potential impacts from sea level rise into restoration planning should benefit species and their coastal habitats, most notably at the southern Florida peninsula. The endangered Cape Sable seaside sparrow (Ammospiza maritima mirabilis) occurs in marl prairie habitat at the southern end of the Everglades. The locations of three of its six subpopulations are proximate to the coast. We used a spatially explicit predictive model, EverSparrow, to estimate probability of sparrow presence considering both hydrologic change from restoration and sea level rise. We found that the probability of sparrow presence decreased with increasing sea level rise. Within approximately 50 years, probability of presence significantly decreased for all three coastal subpopulation areas, with areas above 40% probability increasingly limited. Given the exceptionally low dispersal ability of this species and the geographic restrictions for habitat expansion, our results highlight the importance of freshwater flow into the southern Everglades marl prairie for habitat conservation.
The “dimensional stability” approach measures different components of ecological stability to investigate how they are related. Yet, most empirical work has used small-scale and short-term experimental manipulations. Here, we apply this framework to a long-term observational dataset of stream macroinvertebrates sampled between the winter flooding and summer monsoon seasons. We test hypotheses that relate variation among stability metrics across different taxa, the magnitude of antecedent (monsoon) and immediate (winter) floods to stability metrics, and the relative importance of disturbance magnitude and taxonomic richness on community dimensional stability. Cluster analysis revealed four distinct stability types, and we found that the magnitude of floods during the prior monsoon was more important in influencing stability than the winter flood itself. For dimensional stability at the community level, taxonomic richness was more important than disturbance magnitude. This work demonstrates that abiotic and biotic factors determine dimensional stability in a natural ecosystem.
The identification of factors that may be forcing ecological observations to approach the upper boundary provides insight into potential mechanisms affecting driver-response relationships, and can help inform ecosystem management, but has rarely been explored. In this study, we propose a novel framework integrating quantile regression with interpretable machine learning. In the first stage of the framework, we estimate the upper boundary of a driver-response relationship using quantile regression. Next, we calculate “potentials” of the response variable depending on the driver, which are defined as vertical distances from the estimated upper boundary of the relationship to observations in the driver-response variable scatter plot. Finally, we identify key factors impacting the potential using a machine learning model. We illustrate the necessary steps to implement the framework using the total phosphorus (TP)-Chlorophyll a (CHL) relationship in lakes across the continental US. We found that the nitrogen to phosphorus ratio (N:P), annual average precipitation, total nitrogen (TN), and summer average air temperature were key factors impacting the potential of CHL depending on TP. We further revealed important implications of our findings for lake eutrophication management. The important role of N:P and TN on the potential highlights the co-limitation of phosphorus and nitrogen and indicates the need for dual nutrient criteria. Future wetter and/or warmer climate scenarios can decrease the potential which may reduce the efficacy of lake eutrophication management. The novel framework advances the application of quantile regression to identify factors driving observations to approach the upper boundary of driver-response relationships.
","language":"English","publisher":"Springer","doi":"10.1007/s11783-023-1676-2","usgsCitation":"Liang, Z., Xu, Y., Zhao, G., Lu, W., Fu, Z., Wang, S., and Wagner, T., 2023, Approaching the upper boundary of driver-response relationships: Identifying factors using a novel framework integrating quantile regression with interpretable machine learning: Frontiers of Environmental Science & Engineering, v. 17, 76, https://doi.org/10.1007/s11783-023-1676-2.","productDescription":"76","ipdsId":"IP-137079","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":466007,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"17","noUsgsAuthors":false,"publicationDate":"2023-01-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Liang, Zhongyao","contributorId":347986,"corporation":false,"usgs":false,"family":"Liang","given":"Zhongyao","affiliations":[{"id":83275,"text":"Chinese Research Academy of Environmental Sciences","active":true,"usgs":false}],"preferred":false,"id":922791,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Xu, Yaoyang","contributorId":347987,"corporation":false,"usgs":false,"family":"Xu","given":"Yaoyang","affiliations":[{"id":32415,"text":"Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":922792,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhao, Gang","contributorId":347988,"corporation":false,"usgs":false,"family":"Zhao","given":"Gang","affiliations":[{"id":30217,"text":"Carnegie Institution for Science","active":true,"usgs":false}],"preferred":false,"id":922793,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lu, Wentao","contributorId":347989,"corporation":false,"usgs":false,"family":"Lu","given":"Wentao","affiliations":[{"id":83276,"text":"Institute of Strategic Planning","active":true,"usgs":false}],"preferred":false,"id":922794,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fu, Zhenghui","contributorId":347990,"corporation":false,"usgs":false,"family":"Fu","given":"Zhenghui","affiliations":[{"id":83275,"text":"Chinese Research Academy of Environmental Sciences","active":true,"usgs":false}],"preferred":false,"id":922795,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wang, Shuhang","contributorId":347991,"corporation":false,"usgs":false,"family":"Wang","given":"Shuhang","affiliations":[{"id":83275,"text":"Chinese Research Academy of Environmental Sciences","active":true,"usgs":false}],"preferred":false,"id":922796,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":922797,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70247741,"text":"70247741 - 2023 - On the scale-dependence of fault surface roughness","interactions":[],"lastModifiedDate":"2023-08-15T14:27:36.245618","indexId":"70247741","displayToPublicDate":"2023-01-11T09:25:32","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7501,"text":"JGR Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"On the scale-dependence of fault surface roughness","docAbstract":"Defining roughness as the ratio of height to length, the standard approach to characterize amplitudes of single fault, joint and fracture surfaces is to measure average height as a function of profile length. Empirically, this roughness depends strongly on scale. The ratio is approximately 0.01 at a few mm but 10× smaller at a few tens of meters. Surfaces are rougher at small scales. However, these conclusions are metric-dependent. If instead height is averaged over wavelength, roughness is nearly Brown spatial noise, having almost scale-independent apparent surface height to wavelength ratio. The small deviation from scale-independence is of the opposite sense than found using the standard metric; surfaces are slightly rougher at long wavelengths. Some natural surfaces may be Brownian within the measurement uncertainties. These contradictions are curiosities of surfaces that have Hurst exponents between 0.5 and 1, as natural fault surfaces do. The wavelength-based analysis of roughness and how it changes with scale are straight-forward; a normalized Fourier transform approximately preserves amplitude and its scale dependence in the wavelength domain. Among the conclusions from reconsideration of scale dependence are that the scale dependence is weak and much smaller than that of other fault and shear zone properties. Background and aftershock seismicity, jogs and step-overs indicate strong localization (smoothing) with slip and scale. The lack of strong scale dependence to surface roughness suggests it is not the dominant control on brittle shear zone evolution.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022JB024856","usgsCitation":"Beeler, N.M., 2023, On the scale-dependence of fault surface roughness: JGR Solid Earth, v. 128, no. 2, e2022JB024856, 22 p., https://doi.org/10.1029/2022JB024856.","productDescription":"e2022JB024856, 22 p.","ipdsId":"IP-131685","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":419814,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"128","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-02-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Beeler, Nicholas M. 0000-0002-3397-8481 nbeeler@usgs.gov","orcid":"https://orcid.org/0000-0002-3397-8481","contributorId":2682,"corporation":false,"usgs":true,"family":"Beeler","given":"Nicholas","email":"nbeeler@usgs.gov","middleInitial":"M.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":880226,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70239357,"text":"fs20223088 - 2023 - Research needs identified for potential effects of energy development activities on environmental resources of the Williston Basin, United States","interactions":[],"lastModifiedDate":"2026-02-04T20:26:08.038844","indexId":"fs20223088","displayToPublicDate":"2023-01-11T09:22:49","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-3088","displayTitle":"Research Needs Identified for Potential Effects of Energy Development Activities on Environmental Resources of the Williston Basin, United States","title":"Research needs identified for potential effects of energy development activities on environmental resources of the Williston Basin, United States","docAbstract":"Unconventional oil and gas development that uses horizontal drilling and hydraulic fracturing is rapidly changing the landscape and exponentially increasing oil production within the Williston Basin, especially in North Dakota and eastern Montana. The activities associated with unconventional oil and gas development are complex and wide reaching and include, in part, road and well-pad construction, leaks from pits or tanks, chemical spills, discharge of wastewater, drilling before casing installation, leaks during or after hydraulic fracturing, failed casing seals, pipeline breaks, abandoned wells, deep-well disposal of flowback or produced wastewater, and induced subsurface migration pathways that can potentially adversely affect the environmental resources within the Williston Basin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20223088","usgsCitation":"Delzer, G.C., and Post van der Burg, M., 2023, Research needs identified for potential effects of energy development activities on environmental resources of the Williston Basin, United States: U.S. Geological Survey Fact Sheet 2022–3088, 6 p., https://doi.org/10.3133/fs20223088.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"Y","ipdsId":"IP-142397","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":499561,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114229.htm","linkFileType":{"id":5,"text":"html"}},{"id":411643,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2022/3088/images"},{"id":411641,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2022/3088/fs20223088.pdf","text":"Report","size":"1.84 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2022–3088"},{"id":411642,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2022/3088/fs20223088.XML"},{"id":411640,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2022/3088/coverthb.jpg"},{"id":411720,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20223088/full","text":"Report","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Montana, North Dakota, South Dakota","otherGeospatial":"Williston Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -101.85992433948707,\n 44.748962924301054\n ],\n [\n -100.27178237770465,\n 45.62378897009327\n ],\n [\n -99.72386467913583,\n 47.01666497234379\n ],\n [\n -98.92422494544115,\n 48.99070414841606\n ],\n [\n -106.85334014872393,\n 49.00199336720374\n ],\n [\n -106.20557284548465,\n 47.60278245148987\n ],\n [\n -105.42666681945474,\n 46.15028300648845\n ],\n [\n -104.32046634105996,\n 45.350667945249626\n ],\n [\n -103.35976723012234,\n 45.170260895064786\n ],\n [\n -102.7400085664068,\n 44.590251713951545\n ],\n [\n -101.96303401243244,\n 44.60899148746665\n ],\n [\n -101.85992433948707,\n 44.748962924301054\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Dakota Water Science Center
U.S. Geological Survey
821 East Interstate Avenue, Bismarck, ND 58503
1608 Mountain View Road, Rapid City, SD 57702
Wetlands are among the most threatened ecosystems worldwide due to climate change and land-use conversion. Regional biodiversity of temporary wetlands is dependent on the existence of habitat complexes with variable hydroperiods. Because temperature and rainfall regimes are predicted to shift globally, together with land-use patterns, different scenarios of wetland loss are expected in the future. To understand how wetland biodiversity might change in the future, it is important to evaluate how the loss of particular hydroperiods will affect overall diversity in a region. Using invertebrate datasets from five wetland complexes distributed across South and North America, we calculated beta diversity metrics for each region. Then we contrasted those metrics to simulations of sequential deletions of subsets (30%) of the long-, moderate- and short-hydroperiod wetlands to assess which wetland class would most affect invertebrate beta diversity in each region. Deletions of the short-hydroperiod wetlands led to the most significant decline in beta diversity. However, deletion effects of different wetland classes varied across study regions, with a negative correlation existing between deletions of the long- and short-hydroperiod wetlands on invertebrate beta diversity. Our simulations indicate that loss of short-hydroperiod wetlands will have the most significant effects on invertebrate beta diversity, but loss of long-hydroperiod wetlands will also be important. Thus, wetlands from both hydroperiod extremes should be considered when assessing potential biodiversity declines associated with habitat loss.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jnc.2023.126332","usgsCitation":"Pires, M.M., Garcia, P.E., Maltchik, L., Stenert, C., Epele, L.B., McLean, K., Kneitel, J., Racey, S., and Batzer, D., 2023, Searching for the Achilles heel(s) for maintaining invertebrate biodiversity across complexes of depressional wetlands: Journal for Nature Conservation, v. 72, 126332, 8 p., https://doi.org/10.1016/j.jnc.2023.126332.","productDescription":"126332, 8 p.","ipdsId":"IP-144845","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":467126,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jnc.2023.126332","text":"Publisher Index Page"},{"id":465145,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"72","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Pires, Mateus M.","contributorId":347168,"corporation":false,"usgs":false,"family":"Pires","given":"Mateus","email":"","middleInitial":"M.","affiliations":[{"id":83092,"text":"Programa de Pós-Graduação em Biologia de Ambientes Aquáticos Continentais, Universidade Federal do Rio Grande (FURG), Rio Grande, RS, Brazil","active":true,"usgs":false}],"preferred":false,"id":921003,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Garcia, Patricia E.","contributorId":347170,"corporation":false,"usgs":false,"family":"Garcia","given":"Patricia","email":"","middleInitial":"E.","affiliations":[{"id":83093,"text":"Grupo de Ecología de Sistemas Acuáticos a Escala de Paisaje (GESAP), INIBIOMA-CONICET Universidad Nacional del Comahue, Bariloche, Argentina","active":true,"usgs":false}],"preferred":false,"id":921005,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Maltchik, Leonardo","contributorId":347171,"corporation":false,"usgs":false,"family":"Maltchik","given":"Leonardo","affiliations":[{"id":83092,"text":"Programa de Pós-Graduação em Biologia de Ambientes Aquáticos Continentais, Universidade Federal do Rio Grande (FURG), Rio Grande, RS, Brazil","active":true,"usgs":false}],"preferred":false,"id":921006,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stenert, Cristina","contributorId":347172,"corporation":false,"usgs":false,"family":"Stenert","given":"Cristina","email":"","affiliations":[{"id":83092,"text":"Programa de Pós-Graduação em Biologia de Ambientes Aquáticos Continentais, Universidade Federal do Rio Grande (FURG), Rio Grande, RS, Brazil","active":true,"usgs":false}],"preferred":false,"id":921007,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Epele, Luis B.","contributorId":347173,"corporation":false,"usgs":false,"family":"Epele","given":"Luis","email":"","middleInitial":"B.","affiliations":[{"id":57276,"text":"Centro de Investigación Esquel de Montaña y Estepa Patagónica (CONICET-UNPSJB), Roca 12 780, Esquel, Chubut, Argentina","active":true,"usgs":false}],"preferred":false,"id":921008,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McLean, Kyle 0000-0003-3803-0136 kmclean@usgs.gov","orcid":"https://orcid.org/0000-0003-3803-0136","contributorId":168533,"corporation":false,"usgs":true,"family":"McLean","given":"Kyle","email":"kmclean@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":921009,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kneitel, Jamie M.","contributorId":347174,"corporation":false,"usgs":false,"family":"Kneitel","given":"Jamie M.","affiliations":[{"id":83096,"text":"Department of Biological Sciences, California State University, 6000 J St, Sacramento, CA 95819, USA","active":true,"usgs":false}],"preferred":false,"id":921010,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Racey, Sophie","contributorId":347169,"corporation":false,"usgs":false,"family":"Racey","given":"Sophie","email":"","affiliations":[{"id":57293,"text":"Department of Entomology, University of Georgia, Athens, GA, USA","active":true,"usgs":false}],"preferred":false,"id":921004,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Batzer, Darold P.","contributorId":347175,"corporation":false,"usgs":false,"family":"Batzer","given":"Darold P.","affiliations":[{"id":83097,"text":"Department of Entomology, 120 Cedar St, University of Georgia, Athens, GA 30605, USA","active":true,"usgs":false}],"preferred":false,"id":921011,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70239405,"text":"70239405 - 2023 - An aridity threshold model of fire sizes and annual area burned in extensively forested ecoregions of the western USA","interactions":[],"lastModifiedDate":"2023-01-12T13:17:30.735297","indexId":"70239405","displayToPublicDate":"2023-01-11T07:15:42","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"An aridity threshold model of fire sizes and annual area burned in extensively forested ecoregions of the western USA","docAbstract":"Wildfire occurrence varies among regions and through time due to the long-term impacts of climate on fuel structure and short-term impacts on fuel flammability. Identifying the climatic conditions that trigger extensive fire years at regional scales can enable development of area burned models that are both spatially and temporally robust, which is crucial for understanding the impacts of past and future climate change. We identified region-specific thresholds in fire-season aridity that distinguish years with limited, moderate, and extensive area burned for 11 extensively forested ecoregions in the western United States. We developed a new area burned model using these relationships and demonstrate its application in the Southern Rocky Mountains using climate projections from five global climate models (GCMs) that bracket the range of projected changes in aridity. We used the aridity thresholds to classify each simulation year as having limited, moderate, or extensive area burned and defined fire-size distributions from historical fire records for these categories. We simulated individual fires from a regression relating fire season aridity to the annual number of fires and drew fire sizes from the corresponding fire-size distributions. We project dramatic increases in area burned after 2020 under most GCMs and after 2060 with all GCMs as the frequency of extensive fire years increases. Our adaptable model can readily incorporate new observations (e.g., extreme fire years) to directly address the non-stationarity of fire-climate relationships as climatic conditions diverge from past observations. Our aridity threshold fire model provides a simple yet spatially robust approach to project regional changes in area burned with broad applicability to ecosystem and vegetation simulation models.
Understanding uncertainties in extreme wind-wave events is essential for offshore/coastal risk and adaptation estimates. Despite this, uncertainties in contemporary extreme wave events have not been assessed, and projections are still limited. Here, we quantify, at global scale, the uncertainties in contemporary extreme wave estimates across an ensemble of widely used global wave reanalyses/hindcasts supported by observations. We find that contemporary uncertainties in 50-year return period wave heights (
We study stress‐loading mechanisms for the California faults used in rupture forecasts. Stress accumulation drives earthquakes, and that accumulation mechanism governs recurrence. Most moment release in California occurs because of relative motion between the Pacific plate and the Sierra Nevada block; we calculate relative motion directions at fault centers and compare with fault displacement directions. Dot products between these vectors reveal that some displacement directions are poorly aligned with plate motions. We displace a 3D finite‐element model according to relative motions and resolve stress tensors onto defined fault surfaces, which reveal that poorly aligned faults receive no tectonic loading. Because these faults are known to be active, we search for other loading mechanisms. We find that nearly all faults with no tectonic loading show increase in stress caused by slip on the San Andreas fault, according to an elastic dislocation model. Globally, faults that receive a sudden stress change respond with triggered earthquakes that obey an Omori law rate decay with time. We therefore term this class of faults as “aftershock faults.” These faults release ∼4% of the moment release in California, have ∼0.1%–5% probability of M 6.7 earthquakes in 30 yr, and have a 0.001%–1% 30 yr M 7.7 probability range.