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 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":70261552,"text":"70261552 - 2023 - Searching for the Achilles heel(s) for maintaining invertebrate biodiversity across complexes of depressional wetlands","interactions":[],"lastModifiedDate":"2024-12-16T15:26:09.876503","indexId":"70261552","displayToPublicDate":"2023-01-11T09:10:40","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2142,"text":"Journal for Nature Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Searching for the Achilles heel(s) for maintaining invertebrate biodiversity across complexes of depressional wetlands","docAbstract":"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.
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.
Wind-abraded rocks and aeolian bedforms have been observed at the Mars 2020 Perseverance landing site, providing evidence for recent and older wind directions. This study reports orientations of aeolian features measured in Perseverance images to infer formative wind directions. It compares these measurements with orbital observations, climate model predictions, and wind data acquired by the Mars Environmental Dynamics Analyzer. Three-dimensional orientations of flute textures on rocks, regolith wind tails extending from behind obstacles, and other aeolian features were measured using Digital Terrain Models (DTMs) derived from Mastcam-Z and navigation camera (Navcam) stereo images. Orientations of rock flutes measured in images acquired through Sol (martian day) 400 yielded a mean azimuth of 94° ± 7° (wind from the west). However, similar measurements of regolith wind tails indicate that recent sand-driving winds have been blowing from the east-southeast, nearly the opposite direction (mean azimuth = 285° ± 15°). Atmospheric modeling generally predicts net annual sand transport from the east-southeast at present, consistent with Perseverance regolith wind tail and orbital observations. The orientation of ventifact flutes thus suggests that they were formed under a different climate regime. Differences in orientations of recent and paleo-wind indicators have been noted at other Mars landing sites and may result from major orbital/axial changes that can cause significant changes in atmospheric circulation. Orientation differences between modern and older wind direction indicators at Jezero are useful clues to the climate history of the region.
Wetlands are the largest natural source of methane (CH4) to the atmosphere. The eddy covariance method provides robust measurements of net ecosystem exchange of CH4, but interpreting its spatiotemporal variations is challenging due to the co-occurrence of CH4 production, oxidation, and transport dynamics. Here, we estimate these three processes using a data-model fusion approach across 25 wetlands in temperate, boreal, and Arctic regions. Our data-constrained model—iPEACE—reasonably reproduced CH4 emissions at 19 of the 25 sites with normalized root mean square error of 0.59, correlation coefficient of 0.82, and normalized standard deviation of 0.87. Among the three processes, CH4 production appeared to be the most important process, followed by oxidation in explaining inter-site variations in CH4 emissions. Based on a sensitivity analysis, CH4 emissions were generally more sensitive to decreased water table than to increased gross primary productivity or soil temperature. For periods with leaf area index (LAI) of ≥20% of its annual peak, plant-mediated transport appeared to be the major pathway for CH4 transport. Contributions from ebullition and diffusion were relatively high during low LAI (<20%) periods. The lag time between CH4 production and CH4 emissions tended to be short in fen sites (3 ± 2 days) and long in bog sites (13 ± 10 days). Based on a principal component analysis, we found that parameters for CH4 production, plant-mediated transport, and diffusion through water explained 77% of the variance in the parameters across the 19 sites, highlighting the importance of these parameters for predicting wetland CH4 emissions across biomes. These processes and associated parameters for CH4 emissions among and within the wetlands provide useful insights for interpreting observed net CH4 fluxes, estimating sensitivities to biophysical variables, and modeling global CH4 fluxes.
The abundance of Culex restuans and Culex pipiens in relation to ecological predictors is poorly understood in regions of the United States where their ranges overlap. It is suspected that these species play different roles in spreading West Nile virus (WNV) in these regions, but few studies have modeled these species separately or accounted for spatial correlation using Bayesian methods. We used mosquito surveillance data collected by the Pennsylvania Department of Environmental Protection from 2002 to 2016 and integrated nested Laplace approximations with the stochastic partial differential equation approach to predict C. restuans and C. pipiens abundance in relation to several ecological predictors. We then made a predictive risk surface of abundance for each species at locations that were not sampled. Explanatory variables in the models included ecological variables previously described to be important predictors of the abundance of these mosquito species. Developed habitat, temperature, and precipitation were important predictor variables for the abundance of C. restuans, whereas developed habitat, snow water equivalent, and normalized difference water index were important predictor variables for the abundance of C. pipiens. The abundance of C. restuans had a negative relationship with developed habitat in contrast to C. pipiens abundance, which had a positive relationship with developed habitat. Julian date was modeled as a temporal trend for both species and showed C. restuans to be more abundant from late April through late June and C. pipiens to be more abundant from July through September. A seasonal crossover was observed between these two species on Julian day 185, 4 July. We observed different spatial patterns of abundance in the predictive risk maps of each of the species. Our results indicate that modeling the abundance of these species spatially and separately in regions where these two mosquito vectors coexist can help gain further insight into understanding the epidemiology of WNV in human and susceptible animal populations.
","language":"English","publisher":"Wiley","doi":"10.1002/ecs2.4346","usgsCitation":"Bondo, K., Montecino-Latorre, D., Williams, L., Helwig, M., Duren, K., Hutchinson, M., and Walter, W., 2023, Spatial modeling of two mosquito vectors of West Nile virus using integrated nested Laplace approximations: Ecosphere, v. 14, no. 1, e4346, 15 p., https://doi.org/10.1002/ecs2.4346.","productDescription":"e4346, 15 p.","ipdsId":"IP-138613","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":467127,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4346","text":"Publisher Index Page"},{"id":466441,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"id\":41,\"properties\":{\"name\":\"Pennsylvania\",\"nation\":\"USA 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Matt","contributorId":348326,"corporation":false,"usgs":false,"family":"Helwig","given":"Matt","affiliations":[{"id":83334,"text":"Department of Environmental Protection","active":true,"usgs":false}],"preferred":false,"id":923365,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Duren, Kenneth","contributorId":348327,"corporation":false,"usgs":false,"family":"Duren","given":"Kenneth","affiliations":[{"id":12891,"text":"Pennsylvania Game Commission","active":true,"usgs":false}],"preferred":false,"id":923366,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hutchinson, Mike","contributorId":348328,"corporation":false,"usgs":false,"family":"Hutchinson","given":"Mike","affiliations":[{"id":83334,"text":"Department of Environmental Protection","active":true,"usgs":false}],"preferred":false,"id":923367,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Walter, W. David 0000-0003-3068-1073","orcid":"https://orcid.org/0000-0003-3068-1073","contributorId":219540,"corporation":false,"usgs":true,"family":"Walter","given":"W. David","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":923368,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70262311,"text":"70262311 - 2023 - Density-habitat relationships of white-tailed deer (Odocoileus virginianus) in Finland","interactions":[],"lastModifiedDate":"2025-01-16T18:06:59.893249","indexId":"70262311","displayToPublicDate":"2023-01-10T11:59:12","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Density-habitat relationships of white-tailed deer (Odocoileus virginianus) in Finland","title":"Density-habitat relationships of white-tailed deer (Odocoileus virginianus) in Finland","docAbstract":"In heterogeneous landscapes, resource selection constitutes a crucial link between landscape and population-level processes such as density. We conducted a non-invasive genetic study of white-tailed deer in southern Finland in 2016 and 2017 using fecal DNA samples to understand factors influencing white-tailed deer density and space use in late summer prior to the hunting season. We estimated deer density as a function of landcover types using a spatial capture-recapture (SCR) model with individual identities established using microsatellite markers. The study revealed second-order habitat selection with highest deer densities in fields and mixed forest, and third-order habitat selection (detection probability) for transitional woodlands (clear-cuts) and closeness to fields. Including landscape heterogeneity improved model fit and increased inferred total density compared with models assuming a homogenous landscape. Our findings underline the importance of including habitat covariates when estimating density and exemplifies that resource selection can be studied using non-invasive methods.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.9711","usgsCitation":"Poutanen, J., Fuller, A.K., Pusenius, J., Royle, A., Wikström, M., and Brommer, J., 2023, Density-habitat relationships of white-tailed deer (Odocoileus virginianus) in Finland: Ecology and Evolution, v. 13, no. 1, e9711, 14 p., https://doi.org/10.1002/ece3.9711.","productDescription":"e9711, 14 p.","ipdsId":"IP-117427","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":467128,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.9711","text":"Publisher Index Page"},{"id":467013,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Finland","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 22.745787010636263,\n 60.89878772519478\n ],\n [\n 22.745787010636263,\n 60.81018338906668\n ],\n [\n 22.92321705027345,\n 60.81018338906668\n ],\n [\n 22.92321705027345,\n 60.89878772519478\n ],\n [\n 22.745787010636263,\n 60.89878772519478\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"13","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-01-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Poutanen, Jenni","contributorId":348818,"corporation":false,"usgs":false,"family":"Poutanen","given":"Jenni","affiliations":[{"id":25452,"text":"University of Turku","active":true,"usgs":false}],"preferred":false,"id":923803,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fuller, Angela K. 0000-0002-9247-7468 afuller@usgs.gov","orcid":"https://orcid.org/0000-0002-9247-7468","contributorId":3984,"corporation":false,"usgs":true,"family":"Fuller","given":"Angela","email":"afuller@usgs.gov","middleInitial":"K.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":923804,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pusenius, Jyrki","contributorId":348819,"corporation":false,"usgs":false,"family":"Pusenius","given":"Jyrki","affiliations":[{"id":40380,"text":"Natural Resources Institute Finland","active":true,"usgs":false}],"preferred":false,"id":923805,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":146229,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","email":"aroyle@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":923806,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wikström, Mikael","contributorId":348820,"corporation":false,"usgs":false,"family":"Wikström","given":"Mikael","affiliations":[{"id":13690,"text":"Finnish Wildlife Agency","active":true,"usgs":false}],"preferred":false,"id":923807,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brommer, Jon E","contributorId":348821,"corporation":false,"usgs":false,"family":"Brommer","given":"Jon E","affiliations":[{"id":25452,"text":"University of Turku","active":true,"usgs":false}],"preferred":false,"id":923808,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70262069,"text":"70262069 - 2023 - Influence of camera model and alignment on the performance of paired camera stations","interactions":[],"lastModifiedDate":"2025-01-10T16:36:55.371829","indexId":"70262069","displayToPublicDate":"2023-01-10T10:31:08","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"Influence of camera model and alignment on the performance of paired camera stations","docAbstract":"The probability of obtaining images of target species may vary across camera models or relative position of cameras at survey locations. Alignment of cameras within paired camera stations (hereafter, stations) could affect species detection due to issues with image exposure. We quantified effects of 3 camera models and alignment (staggered, offset by a perpendicular distance of 4.6 m, and aligned, directly facing one another) on camera performance in a station design. Mean exposure events (flash from one camera overexposes or underexposes pictures) at aligned stations was 3.93 (SE = 1.01; n = 40), whereas no exposure events were documented at staggered (n = 36) stations. Overall frequency of exposure events of mammal images at aligned cameras was 44% (68 exposure events/153 images). On average, 8% (range 0−35%) of mammal images from aligned stations were exposure events. We detected no difference (P = 0.88) in exposure events among paired camera models. Further, we detected no overall differences (P ≥ 0.07) in paired camera performance (i.e., number of mammal images over survey interval) between aligned or staggered stations, though reliability (i.e., percentage of camera stations that lasted entire survey interval) varied (P ≤ 0.001) between model types. Research deploying 2 cameras within a camera station framework can eliminate exposure events by using a staggered camera alignment without affecting the number of usable mammal photos. Rigorous field testing prior to deployment of stations is warranted to optimize reliability. One of our low-cost models performed as well as a more expensive model within our paired camera stations at collecting mammal images, and thus could be incorporated into study designs without compromising quality of camera photo data. We suggest a pilot study before large-scale deployment to evaluate reliability and performance of cameras, particularly when deploying multiple models.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/wsb.1422","usgsCitation":"Swearingen, T., Klaver, R.W., Anderson, C.R., and Jacques, C., 2023, Influence of camera model and alignment on the performance of paired camera stations: Wildlife Society Bulletin, v. 47, no. 2, e1422, 11 p., https://doi.org/10.1002/wsb.1422.","productDescription":"e1422, 11 p.","ipdsId":"IP-117689","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":467129,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/wsb.1422","text":"Publisher Index Page"},{"id":465997,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois","otherGeospatial":"Alice L. Kibble Field Station","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -91.43161311292845,\n 40.36213807902013\n ],\n [\n -91.43161311292845,\n 40.359129920123905\n ],\n [\n -91.4282069310208,\n 40.359129920123905\n ],\n [\n -91.4282069310208,\n 40.36213807902013\n ],\n [\n -91.43161311292845,\n 40.36213807902013\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"47","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-01-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Swearingen, Tim","contributorId":348115,"corporation":false,"usgs":false,"family":"Swearingen","given":"Tim","affiliations":[{"id":49637,"text":"Western Illinois University","active":true,"usgs":false}],"preferred":false,"id":922951,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Klaver, Robert W. 0000-0002-3263-9701 bklaver@usgs.gov","orcid":"https://orcid.org/0000-0002-3263-9701","contributorId":3285,"corporation":false,"usgs":true,"family":"Klaver","given":"Robert","email":"bklaver@usgs.gov","middleInitial":"W.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":922952,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Charles R. Jr.","contributorId":75042,"corporation":false,"usgs":true,"family":"Anderson","given":"Charles","suffix":"Jr.","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":922996,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jacques, Christopher N.","contributorId":348116,"corporation":false,"usgs":false,"family":"Jacques","given":"Christopher N.","affiliations":[{"id":49637,"text":"Western Illinois University","active":true,"usgs":false}],"preferred":false,"id":922953,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70242151,"text":"70242151 - 2023 - Sound-side inundation and seaward erosion of a barrier island during hurricane landfall","interactions":[],"lastModifiedDate":"2023-04-10T11:46:38.89231","indexId":"70242151","displayToPublicDate":"2023-01-10T06:40:57","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":13797,"text":"JGR - Earth Surface","active":true,"publicationSubtype":{"id":10}},"title":"Sound-side inundation and seaward erosion of a barrier island during hurricane landfall","docAbstract":"Barrier islands are especially vulnerable to hurricanes and other large storms, owing to their mobile composition, low elevations, and detachment from the mainland. Conceptual models of barrier-island evolution emphasize ocean-side processes that drive landward migration through overwash, inlet migration, and aeolian transport. In contrast, we found that the impact of Hurricane Dorian (2019) on North Core Banks, a 36-km barrier island on the Outer Banks of North Carolina, was primarily driven by inundation of the island from Pamlico Sound, as evidenced by storm-surge model results and observations of high-water marks and wrack lines. Analysis of photogrammetry products from aerial imagery collected before and after the storm indicate the loss of about 18% of the subaerial volume of the island through the formation of over 80 erosional washout channels extending from the marsh and washover platform, through gaps in the foredunes, to the shoreline. The washout channels were largely co-located with washover fans deposited by earlier events. Net seaward export of sediment resulted in the formation of deltaic bars offshore of the channels, which became part of the post-storm berm recovery by onshore bar migration and partial filling of the washouts with washover deposits within 2 months. This event represents a volumetric setback in the overwash/rollover behavior required for barrier transgression, but the new ponds and lowland habitats may provide beneficial habit for endangered species and will likely persist for years.
A major challenge in ecology is disentangling interactions of non-native, potentially invasive species on native species. Conditional two-species occupancy models examine the effects of dominant species (e.g., non-native) on subordinate species (e.g., native) while considering the possibility that occupancy of one species may affect occupancy and/ or detection of the other. Although conditional two-species models are useful for evaluating the influence of one species on presence of another, it is possible that species interactions are density dependent. Therefore, we developed a novel two-species occupancy model that incorporates multiple abundance states (i.e., absent, present, abundant) of the native species. We showcase the utility of this model with a case study that incorporates random effects and covariates on both occupancy and detection to help disentangle species interactions given varying occupancy and detection in different abundance states. We use snorkel survey data from the Umpqua basin, Oregon, where it is hypothesized that smallmouth bass Micropterus dolomieu, a non-native piscivore, exclude Umpqua chub Oregonichthys kalawatseti, a small endemic minnow. From our two-species multi-state (2SMS) model, we concluded that average occupancy was low for both fishes, and that when non-native bass were present, overall native chub occupancy in the present (0.18 ± 0.05 SD) and abundant (0.19 ± 0.03) states was higher than when non-natives were absent (0.14 ± 0.02/ 0.08 ± 0.02), indicating the non-native was not excluding the native species. By incorporating a species interaction factor, we found a positive association (6.75 ± 5.54 SD) between native chub and non-native bass. The covariates strongly related to occupancy were elevation, algae, and land cover type (urban and shrub). Detection probability for both species (0.21–0.82) was most strongly related to the covariates day of year, water temperature, gravel substrate, and stream order/ magnitude. Incorporation of detection probability and covariates enabled interpretation of interactions between the two species that may have been missed without their inclusion in the modeling process. Our new 2SMS occupancy model can be used by scientists and managers with a broad range of survey and covariate data to disentangle species interactions problems to help them inform management decisions.
Rising temperatures in the Arctic and subarctic are driving the rapid thaw of permafrost by reducing permafrost cooling, increasing active layer thickness, and promoting talik formation. In this study, the cyrohydrogeology of a permafrost mound located within the discontinuous permafrost zone near Umiujaq (Nunavik, Québec, Canada) is characterized through the analysis of a dataset covering more than two decades of monitoring. This dataset captures a high degree of interannual variability in air temperature and ground thermal conditions, as well as the formation and closure of a supra-permafrost talik. Data indicate that variable saturation and advective heat transport directly contribute to the expansion and contraction of the talik. Data further indicate the presence of two distinct thermo-hydrologic settings resulting from differences in surface conditions, as well as subsurface thermal and flow regimes. The first, found at the top of the mound feature, is characterized by very low moisture contents (< 0.05 m3/m3), while the second, found at the side of the mound feature, shows higher annual moisture contents that strongly influence the dynamics of heat and groundwater flow. The data were synthesized into a detailed conceptual model of the cyrohydrogeological dynamics that highlights the important role of hydrogeological characterization and long-term datasets in understanding the effects of groundwater flow on seasonal frost and permafrost dynamics. Specifically, the results presented here show that in the absence of long-term datasets, longer-period transient phenomena such as talik opening and closure may be misrepresented as uni-directional feedback loops, as opposed to highly-dynamic temporary phenomena.
The Federal Energy Regulatory Commission has been considering the approval to breach four dams on lower Klamath River in southern Oregon and northern California. Approval of this application would allow for Strikeouts indicate text deletion hereafter. decommissioning and dam removal, beginning as early as 2023. This action would affect Klamath River salmon (Oncorhynchus ssp.) populations, a critical food source for federally endangered Southern Resident Killer Whales (Orcinus orca). In the long run, reintroduction of salmon populations to the upper Klamath River Basin may increase salmon abundance available to Southern Resident Killer Whales, but in the near term, it is uncertain how changes in hatchery management and disease-caused mortality by the myxosporean parasite Ceratonova shasta will influence abundance of salmon populations entering the ocean. To assess this uncertainty, we used the Stream Salmonid Simulator (S3) to simulate population dynamics of juvenile Chinook salmon (Oncorhynchus tshawytscha) for nine different population sources that rear and migrate through the Klamath River.
S3 is a spatially explicit population model that runs on a daily time-step and simulates daily growth, survival, and movement of juvenile Chinook salmon from the time of spawning through ocean entry. The key features of this model relevant to this report include (1) a C. shasta disease submodel; (2) a temperature-dependent bioenergetics model that calculates daily growth rates; (3) size-dependent movement; (4) density-dependent dynamics that are influenced by the effect of flow on suitable habitat area; and (5) habitat, river flow, and water temperature specific to each scenario.
We constructed and ran four scenarios: two scenarios for dams in place (Dams In) and dams removed (Dams Out), and given these dam-removal conditions, a low- and high-spore scenario for C. shasta. Each scenario was run for nine water years representing a range of conditions from dry to wet. Previously published daily river flows and water temperatures for Dams In and Dams Out provided physical inputs for each scenario. Daily spore concentrations were simulated using a three-part mechanistic model that used river discharge, water temperature, and the prevalence of infection (POI) of hatchery-origin Chinook salmon juveniles with C. shasta in the previous year3. We constructed two spore scenarios for each Dams In and Dams Out scenario, a “Low Spore” scenario and a “High Spore” scenario resulting in four scenarios for comparison. Spore scenarios were established by setting the prior-year POI of hatchery fish to 0.15 and 0.75 in the estimation of spore concentrations. Hatchery releases under Dams Out differed from those under the current Dams In scenario. Hatchery releases under the Dams Out scenario were modified to emulate changes in hatchery production that would occur under Dams Out conditions. This included moving hatchery production and releases from Iron Gate Dam to a proposed hatchery at Fall Creek, which would be located about 11 kilometers (km) upstream of Iron Gate Dam. It is anticipated that the Fall Creek hatchery would produce fewer fish at smaller and larger sizes at different release timings. For salmon inputs, we used observed historical abundance of main-stem spawners from brood year 2009 and juvenile salmon entering from tributaries in water year 2010, which represented an average return year for the 2005–18 period. Main-stem spawning was allowed to shift upstream from Iron Gate Dam under the Dams Out scenario. We also included hatchery-origin fish as natural spawners that would have otherwise returned to Iron Gate Hatchery in the first 3 years following dam removal.
The S3 model simulated considerably higher total abundance for Dams Out relative to the respective Dams In scenarios, and higher abundance for the Low Spore scenario relative to the High Spore scenario. The difference in abundance between the four combinations of the dam-removal and spore scenarios varied among population groups. For main-stem natural production, juvenile abundance at ocean entry was 2–3 times higher for Dams Out scenarios than for Dams In scenarios, and juvenile abundance for High Spore scenarios was lower than that for the Dams Out Low Spores scenario. For hatchery releases, abundance at ocean entry was similar between Dams In and Dams Out scenarios for most water years, despite lower release sizes from Fall Creek Hatchery under Dams Out. For tributary populations, abundance for the High Spore scenarios was consistently lower than for the Low Spore scenarios, but differences between dam-removal scenarios varied among water years, with Dams Out scenarios having similar or higher abundance than Dams In scenarios, and dry water years having the largest difference between Dams In and Dams Out scenarios.
We determined that different factors affected the response of each population group. For main-stem natural production, survival from fry emergence to ocean entry was higher under Dams Out scenarios compared to Dams In scenarios because juveniles emerged later and tended to arrive at the ocean sooner and at larger sizes, causing the population to have less time-dependent in-river mortality. Owing to their late release timing, hatchery populations had high disease-caused mortality in Dams In and Dams Out High Spore scenarios. Furthermore, a high proportion of infected fish (those that would be expected to die at some future point) survived to the ocean. Iron Gate Hatchery fish had lower survival rates than releases from Fall Creek Hatchery because the last mid-June release group from the 2010 Iron Gate Hatchery release incurred nearly total mortality in most water years owing to water temperatures exceeding 24 degrees Celsius. Our analysis shows how the S3 model was able to track different populations and provide insights on how the differential response of each population combined to influence the simulated number of juvenile Chinook salmon arriving at the Pacific Ocean where they become available as a food source for Southern Resident Killer Whales.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221106","collaboration":"Prepared in cooperation with the National Marine Fisheries Service and the U.S. Fish and Wildlife Service","usgsCitation":"Perry, R.W., Plumb, J.M., Dodrill, M.J., Som, N.A., Robinson, H.E., and Hetrick, N.J., 2023, Simulating post-dam removal effects of hatchery operations and disease on juvenile Chinook salmon (Oncorhynchus tshawytscha) production in the Lower Klamath River, California: U.S. Geological Survey Open-File Report 2022–1106, 33 p., https://doi.org/10.3133/ofr20221106.","productDescription":"vii, 33 p.","onlineOnly":"Y","ipdsId":"IP-137471","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":410980,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1106/coverthb2.jpg"},{"id":410983,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1106/images"},{"id":410981,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1106/ofr20221106.pdf","text":"Report","size":"6.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1106"},{"id":499722,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114179.htm","linkFileType":{"id":5,"text":"html"}},{"id":410984,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1106/ofr20221106.XML"},{"id":410982,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221106/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1106"}],"country":"United States","state":"California","otherGeospatial":"Lower Klamath River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -124.36610471757332,\n 40.58470369882767\n ],\n [\n -120.32485220783963,\n 40.58470369882767\n ],\n [\n -120.32485220783963,\n 42.21557817118634\n ],\n [\n -124.36610471757332,\n 42.21557817118634\n ],\n [\n -124.36610471757332,\n 40.58470369882767\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016
More than 2 million Californians rely on groundwater from privately owned domestic wells for drinking-water supply. This report summarizes a water-quality survey of domestic and small-system drinking-water supply wells in the Modesto, Turlock, and Merced subbasins of the San Joaquin Valley where more than 78,000 residents are estimated to use privately owned domestic wells. Results indicate that inorganic and organic constituents in groundwater were respectively present above regulatory (maximum contaminant level, MCL) benchmarks for public drinking-water quality in 37 percent and 9 percent of the aquifer area used for domestic drinking-water supplies (herein, “domestic groundwater resources”).
The most prevalent inorganic constituents exceeding regulatory benchmarks were nitrate, uranium, and arsenic. The only organic constituents exceeding regulatory benchmarks were the fumigant constituents 1,2,3-trichloropropane (1,2,3-TCP) and 1,2-dibromo-3-chloropropane (DBCP), but the herbicides atrazine and simazine were detected at low concentrations below one-tenth of regulatory benchmarks in 30 percent of domestic groundwater resources. Total dissolved solids (TDS) and manganese exceeded aesthetic-based (secondary maximum contaminant level [SMCL]) benchmarks for drinking water in 3 percent and 13 percent of domestic groundwater resources, respectively. Per- and polyfluoroalkyl substances (PFAS) were detected in 23 percent of domestic groundwater resources, with 4 percent exceeding California state notification or response levels for specific compounds. Total coliform bacteria were detected in 20 percent of domestic groundwater resources.
Elevated concentrations of nitrate, uranium, TDS, and pesticides (fumigant constituents and herbicides) are related to agricultural land use and were typically present at shallow depths up to 75 meters below land surface. Agriculturally derived constituents were detected in wells screened below the Corcoran Clay Member of the Tulare Formation (herein, “Corcoran Clay”) in the southeastern part of the study area, where the Corcoran Clay tends to be shallower and thinner than in areas to the northwest. Nitrate, uranium, and TDS were most prevalent in the northwest part of the study area proximal to the valley trough where soils are poorly drained and agricultural land uses are predominantly grain, alfalfa, and dairy farms. Pesticides tended to occur in groundwater below coarse-grained surficial deposits and within a northwest to southeast trending band along the eastern extent of the Corcoran Clay that typically demarcates the western extent of well-drained soils associated with perennial orchard crops. Elevated concentrations of arsenic tended to occur west of this band in reducing groundwater but also sometimes co-occurred with elevated nitrate in oxic groundwater, most likely because of geochemical conditions in agriculturally affected groundwater that can enhance the mobility of arsenic from aquifer sediments.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221116","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","programNote":"GAMA Program","usgsCitation":"Levy, Z.F., Balkan, M., and Shelton, J.L., 2023, Quality of groundwater used for domestic supply in the Modesto, Turlock, and Merced Subbasins of the San Joaquin Valley, California: U.S. Geological Survey Open-File Report 2022-1116, 13 p., https://doi.org/10.3133/ofr20221116.","productDescription":"Report: 13 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-139668","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":411493,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96R55KQ","text":"USGS data release","description":"USGS data release","linkHelpText":"Groundwater-quality data in the Modesto-Turlock-Merced Domestic-Supply Aquifer Study Unit, 2020-2021: Results from the California GAMA Priority Basin Project"},{"id":411490,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1116/coverthb.jpg"},{"id":411494,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1116/images"},{"id":411491,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1116/ofr20221116.pdf","text":"Report","size":"6.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1116"},{"id":411492,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221116/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1116"},{"id":411495,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1116/ofr20221116.XML"},{"id":499725,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114178.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"California","otherGeospatial":"San Joaquin Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.79107113798727,\n 38.18457756338151\n ],\n [\n -121.79107113798727,\n 37.036293717738104\n ],\n [\n -119.63866490997714,\n 37.036293717738104\n ],\n [\n -119.63866490997714,\n 38.18457756338151\n ],\n [\n -121.79107113798727,\n 38.18457756338151\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"GAMA Project Chief
U.S. Geological Survey
California Water Science Center
6000 J Street
Placer Hall, Sacramento, CA 95819
Telephone number: (916) 278-3000
GAMA Program Unit Chief State Water Resources Control Board Division of Water Quality
PO Box 2231
Sacramento, CA 95812
Telephone number: (916) 341-5855
Models that assess the vulnerability of freshwater species to shifting environmental conditions do not always account for short-duration extremes, which are increasingly common. Life cycle models for Pacific salmon (Oncorhynchus spp.) generally focus on average conditions that fish experience during each life stage, yet many floods, low flows, and elevated water temperatures only last days to weeks. We developed a process-based life cycle model that links coho salmon (Oncorhynchus kisutch) abundance to daily streamflow and thermal regimes to assess: (1) “How does salmon abundance respond to short-duration floods, low flows, and high temperatures in glacier-, snow-, and rain-fed streams?” and (2) “How does the temporal resolution of flow and temperature data influence these responses?”. Our simulations indicate that short-duration extremes can reduce salmon abundance in some contexts. However, after daily flow and temperature data were aggregated into weekly and monthly averages, the impact of extreme events on populations declined. Our analysis demonstrates that novel modeling frameworks that capture daily variability in flow and temperature are needed to examine impacts of extreme events on Pacific salmon.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2022-0129","usgsCitation":"Bellmore, J.R., Sergeant, C.J., Bellmore, R.A., Falke, J.A., and Fellman, J.B., 2023, Modeling coho salmon (Oncorhynchus kisutch) population response to streamflow and water temperature extremes, v. 80, no. 2, p. 243-260, https://doi.org/10.1139/cjfas-2022-0129.","productDescription":"18 p.","startPage":"243","endPage":"260","ipdsId":"IP-141126","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":487894,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/11122/14923","text":"External Repository"},{"id":485214,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"80","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-01-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Bellmore, J. Ryan","contributorId":104790,"corporation":false,"usgs":true,"family":"Bellmore","given":"J.","email":"","middleInitial":"Ryan","affiliations":[],"preferred":false,"id":934959,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sergeant, Christopher J.","contributorId":140496,"corporation":false,"usgs":false,"family":"Sergeant","given":"Christopher","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":934960,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bellmore, Rebecca A.","contributorId":275276,"corporation":false,"usgs":false,"family":"Bellmore","given":"Rebecca","email":"","middleInitial":"A.","affiliations":[{"id":39693,"text":"Southeast Alaska Watershed Coalition","active":true,"usgs":false}],"preferred":false,"id":934961,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Falke, Jeffrey A. 0000-0002-6670-8250 jfalke@usgs.gov","orcid":"https://orcid.org/0000-0002-6670-8250","contributorId":5195,"corporation":false,"usgs":true,"family":"Falke","given":"Jeffrey","email":"jfalke@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":934962,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fellman, Jason B.","contributorId":198741,"corporation":false,"usgs":false,"family":"Fellman","given":"Jason","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":934963,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70246796,"text":"70246796 - 2023 - Out of the frying pan and into the fire: Effects of volcanic heat and other stressors on the conservation of a critically endangered plant in Hawaiʻi","interactions":[],"lastModifiedDate":"2023-07-19T13:36:39.868035","indexId":"70246796","displayToPublicDate":"2023-01-06T08:34:04","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1531,"text":"Environmental Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Out of the frying pan and into the fire: Effects of volcanic heat and other stressors on the conservation of a critically endangered plant in Hawaiʻi","docAbstract":"Loss of local biodiversity resulting from abrupt environmental change is a significant environmental problem throughout the world. Extinctions of plants are particularly important yet are often overlooked. Drawing from a case in Hawai‘i, a global hotspot for plant and other extinctions, we demonstrate an effort to better understand and determine priorities for the management of an endangered plant (‘Ihi makole or Portulaca sclerocarpa) in the face of rapid and extreme environmental change. Volcanic heat emissions and biological invasions have anecdotally been suggested as possible threats to the species. We integrated P. sclerocarpa outplanting with efforts to collect geological and ecological data to gauge the role of elevated soil temperatures and invasive grasses in driving P. sclerocarpa mortality and population decline. We measured soil temperature, soil depth, surrounding cover and P. sclerocarpa survivorship over three decades. The abundance of wild P. sclerocarpa decreased by 99.7% from the 1990s to 2021. Only 51% of outplantings persisted through 3–4 years. Binomial regression and structural equation modelling revealed that, among the variables we analysed, high soil temperatures were most strongly associated with population decline. Finding the niche where soil temperatures are low enough to allow P. sclerocarpa survival but high enough to limit other agents of P. sclerocarpa mortality may be necessary to increase population growth of this species.
","language":"English","publisher":"Cambridge University Press","doi":"10.1017/S0376892922000480","usgsCitation":"Gill, N.S., Stallman, J., Pratt, L., Lewicki, J.L., Elias, T., Nadeau, P.A., and Yelenik, S.G., 2023, Out of the frying pan and into the fire: Effects of volcanic heat and other stressors on the conservation of a critically endangered plant in Hawaiʻi: Environmental Conservation, v. 20, no. 2, p. 108-115, https://doi.org/10.1017/S0376892922000480.","productDescription":"8 p.","startPage":"108","endPage":"115","ipdsId":"IP-138767","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":444933,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1017/s0376892922000480","text":"Publisher Index Page"},{"id":435520,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9P1CA58","text":"USGS data release","linkHelpText":"Hawaii Volcanoes National Park, Puhimau Geothermal Area vegetation and abiotic data, 2011-2021"},{"id":419148,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Hawai‘i Volcanoes National Park, Puhimau Thermal Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -155.2342961755231,\n 19.403837326641053\n ],\n [\n -155.2342961755231,\n 19.27954820153461\n ],\n [\n -155.0608186659034,\n 19.27954820153461\n ],\n [\n -155.0608186659034,\n 19.403837326641053\n ],\n [\n -155.2342961755231,\n 19.403837326641053\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"20","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-01-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Gill, Nathan S.","contributorId":211061,"corporation":false,"usgs":false,"family":"Gill","given":"Nathan","email":"","middleInitial":"S.","affiliations":[{"id":38177,"text":"Department of Integrative Biology, University of Wisconsin-Madison, Madison","active":true,"usgs":false}],"preferred":false,"id":878305,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stallman, Jeff 0000-0003-4713-2193","orcid":"https://orcid.org/0000-0003-4713-2193","contributorId":245750,"corporation":false,"usgs":false,"family":"Stallman","given":"Jeff","email":"","affiliations":[{"id":13341,"text":"Hawai‘i Cooperative Studies Unit, University of Hawai‘i at Hilo","active":true,"usgs":false}],"preferred":false,"id":878306,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pratt, Linda","contributorId":316790,"corporation":false,"usgs":false,"family":"Pratt","given":"Linda","affiliations":[{"id":68693,"text":"PIERC (Formerly)","active":true,"usgs":false}],"preferred":false,"id":878307,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lewicki, Jennifer L. 0000-0003-1994-9104 jlewicki@usgs.gov","orcid":"https://orcid.org/0000-0003-1994-9104","contributorId":5071,"corporation":false,"usgs":true,"family":"Lewicki","given":"Jennifer","email":"jlewicki@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":878308,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Elias, Tamar 0000-0002-9592-4518 telias@usgs.gov","orcid":"https://orcid.org/0000-0002-9592-4518","contributorId":3916,"corporation":false,"usgs":true,"family":"Elias","given":"Tamar","email":"telias@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":878309,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nadeau, Patricia A. 0000-0002-6732-3686","orcid":"https://orcid.org/0000-0002-6732-3686","contributorId":215616,"corporation":false,"usgs":true,"family":"Nadeau","given":"Patricia","email":"","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":878310,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Yelenik, Stephanie G. 0000-0002-9011-0769","orcid":"https://orcid.org/0000-0002-9011-0769","contributorId":256836,"corporation":false,"usgs":false,"family":"Yelenik","given":"Stephanie","email":"","middleInitial":"G.","affiliations":[{"id":51875,"text":"formerly U.S. Geological Survey; currently Rocky Mountain Research Station, U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":878311,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70248766,"text":"70248766 - 2023 - Intensified warming and aridity accelerate terminal lake desiccation in the Great Basin of the western United States","interactions":[],"lastModifiedDate":"2023-09-20T11:42:25.220554","indexId":"70248766","displayToPublicDate":"2023-01-06T06:40:11","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5026,"text":"Earth and Space Science","active":true,"publicationSubtype":{"id":10}},"title":"Intensified warming and aridity accelerate terminal lake desiccation in the Great Basin of the western United States","docAbstract":"Terminal lakes in the Great Basin (GB) of the western US host critical wildlife habitat and food for migrating birds and can be associated with serious human health and economic consequences when they desiccate. Water levels have declined dramatically in the last 100+ years due to diversion of inflows, drought and climate change. Satellite-derived environmental science data records (ESDRs) from the MODerate-resolution Imaging Spectroradiometer (MODIS) (snow cover, evapotranspiration (ET) and land surface temperature (LST)), enable a unique approach to evaluate the effects of aridification on terminal lakes and to study their individual vulnerabilities. Surface and air temperatures in the GB are rising dramatically, with a sharp rise in the rate of increase observed beginning around 2011, while the number of days of snow cover is declining especially in the western mountainous part of the GB as exemplified in Mono Basin, California. Rising temperatures coincide with fewer days of snow cover, a decrease of inflow to the lakes and greater evaporation of water from the lakes. MODIS ESDRs show strong and statistically significant increasing surface temperature (LST) in the GB, a reduction in the number of days of snow cover, and mixed results in ET. ET declined slightly in the more arid parts of the GB due to greater moisture restrictions to evaporation from extended drought, while ET increased in the more-vegetated, wetter, mountainous northeastern parts as temperatures have risen. Severe and costly ecological, human health and economic consequences are expected if the lakes continue to decline as predicted.
Xanthe Terra is a high-standing cratered plain located southeast of Lunae Planum and south of Chryse Planitia in the western equatorial region of Mars. It contains landforms shaped by diverse geologic processes, including various scales of channels and valleys, chaotic terrains, delta fan deposits, and landslides. An extensive outflow channel system is located within Xanthe Terra and the surrounding circum-Chryse region, including Shalbatana and Ravi Valles, thought to have formed by catastrophic flooding during the Hesperian to Amazonian Periods. The study region within Xanthe Terra is defined by Mars Transverse Mercator (MTM) quadrangles 00042 and 00047 (2.5° to −2.5° N, 310° to 320° E) and includes Orson Welles crater (124.5 km diameter, the source region for Shalbatana Vallis), the southernmost portion of Shalbatana Vallis, Aromatum Chaos (the source region for Ravi Vallis), the westernmost portion of Ravi Vallis, and the source area of Nanedi Valles. The Mars Odyssey Thermal Emission Image System (THEMIS) IR daytime mosaic (100 m/pixel) was used as the primary base map. We constructed the geologic map of the source region of Shalbatana Vallis at 1:750,000 scale. We defined 16 geologic units in the map area, which we divided into the following groups: plains units, channel units, crater units, chaos units, flow units, and surficial units. Mapped linear features include ridge crests, scarp crests, channels, crests of crater rims, crests of buried or degraded crater rims, graben traces, grooves, troughs, and faults. Surface features include secondary crater chains and dark ejecta material. The geologic history of the map region can be summarized as follows. During the Noachian Period, ancient highland materials in the Xanthe Terra region, including lava and any ancient sedimentary units present, were reworked by impacts during the heavy bombardment. In particular, the impact that formed a basin that later underwent widespread resurfacing, likely as a combination of lava flows, reworked crater materials, and sedimentary deposits resulting in the flat-lying, smooth plains of Chryse Planitia. The Hesperian Period was characterized by the impact that formed Orson Welles crater and the subsequent formation of Shalbatana Vallis, as well as Aromatum Chaos and Ravi Vallis. During this period, depressions were filled with smooth material that was subsequently modified by collapse, subsidence, and flooding. Water filled and overflowed the tops of Orson Welles crater and other depressions. The Amazonian Period was characterized by ongoing collapse, as well as the formation of flow and surficial materials, including a lava flow that extends from Aromatum Chaos.
Astrogeology Science Center
U.S. Geological Survey
2255 N. Gemini Dr.
Flagstaff, AZ 86001
In a system that uses supplemental stocking to enhance a fishery that serves a dual purpose, an understanding of the contributions from natural and hatchery-produced fish is important so that hatchery resources can be appropriately allocated. Kokanee Oncorhynchus nerka were first stocked in Flaming Gorge Reservoir (FGR), Wyoming–Utah, in 1963 and serve a dual purpose as a prey resource and sport fish. Although natural recruitment occurs in the reservoir, a supplemental stocking program was initiated in 1991. We sought to identify the natal origin (i.e., natural, hatchery) of kokanee in FGR using otolith microchemistry. We evaluated return to the creel, composition of spawning aggregates, and growth of kokanee in FGR and focused on differences associated with natal origin. We analyzed kokanee otoliths that we collected from hatcheries (n = 60) and FGR (n = 1,003) for the strontium isotope ratio, 87Sr/86Sr, using laser ablation and a multicollector inductively coupled plasma mass spectrometer. We conducted Kruskal–Wallis tests to compare the strontium isotope ratios from the otolith edge of kokanee that we sampled from hatcheries and FGR. Based on 87Sr/86Sr ratios, we could distinguish natural-origin kokanee from 11 of the 12 hatcheries (P < 0.01); however, the Wigwam Hatchery was not significantly different from FGR (P = 0.84). We used model-based discriminant function analysis to assign natal origins for kokanee caught in FGR. Hatchery contribution to the population at large varied from 21 to 50% among year classes from 2014 to 2018. The percentage of hatchery origin kokanee in the creel (18–50%) was similar to what we observed in the population. Hatchery-produced kokanee contributed a higher proportion to tributary-spawning aggregates (40–90%) than shoreline-spawning aggregates (19–58%) by sample year. Growth of natural and hatchery kokanee was similar, suggesting similar performance in the system. Results from this study identify that hatchery supplementation contributes to the population and recreational harvest of kokanee in FGR. This research also provides insight into the ecology of kokanee that is useful for better understanding kokanee population dynamics in reservoir systems.
","language":"English","publisher":"Allen Press","doi":"10.3996/JFWM-22-009","usgsCitation":"Black, A., Walrath, J., Willmes, M., and Quist, M.C., 2023, Natal contributions of Kokanee salmon to Flaming Gorge Reservoir, Wyoming–Utah: An evaluation using otolith microchemistry: Journal of Fish and Wildlife Management, v. 14, no. 1, p. 90-107, https://doi.org/10.3996/JFWM-22-009.","productDescription":"18 p.","startPage":"90","endPage":"107","ipdsId":"IP-134905","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":444961,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.3996/jfwm-22-009","text":"Publisher Index Page"},{"id":429872,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah, Wyoming","otherGeospatial":"Flaming Gorge Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -109.36367201626237,\n 41.43666565226448\n ],\n [\n -109.73395063659062,\n 41.43666565226448\n ],\n [\n -109.73395063659062,\n 40.835428277844755\n ],\n [\n -109.36367201626237,\n 40.835428277844755\n ],\n [\n -109.36367201626237,\n 41.43666565226448\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"14","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-01-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Black, Aaron","contributorId":288737,"corporation":false,"usgs":false,"family":"Black","given":"Aaron","email":"","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":902314,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walrath, John D.","contributorId":171507,"corporation":false,"usgs":false,"family":"Walrath","given":"John D.","affiliations":[],"preferred":false,"id":902315,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Willmes, Marte","contributorId":337272,"corporation":false,"usgs":false,"family":"Willmes","given":"Marte","affiliations":[{"id":64417,"text":"University of California--Davis","active":true,"usgs":false}],"preferred":false,"id":902316,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Quist, Michael C. 0000-0001-8268-1839","orcid":"https://orcid.org/0000-0001-8268-1839","contributorId":207142,"corporation":false,"usgs":true,"family":"Quist","given":"Michael","middleInitial":"C.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":902317,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70239827,"text":"70239827 - 2023 - Experimental infection of Mexican free-tailed bats (Tadarida brasiliensis) with SARS-CoV-2","interactions":[],"lastModifiedDate":"2023-03-01T17:12:26.997493","indexId":"70239827","displayToPublicDate":"2023-01-04T06:44:19","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5160,"text":"mSphere","active":true,"publicationSubtype":{"id":10}},"title":"Experimental infection of Mexican free-tailed bats (Tadarida brasiliensis) with SARS-CoV-2","docAbstract":"Groundwater in northwestern Louisiana is a valuable resource needed for expanding public-supply needs as well as possible energy development needs arising from Haynesville Formation natural-gas production. The Red River alluvial and the Carrizo-Wilcox aquifers are two of the most important and heavily pumped aquifers in northwestern Louisiana; however, little documentation of the regional hydrogeologic framework is available. The U.S. Geological Survey and the Louisiana Department of Transportation and Development have consolidated information from, and built upon, previous studies of the Red River alluvial and the Carrizo-Wilcox aquifers to characterize and document the regional hydrogeologic framework of northwestern Louisiana.
The study area has been tectonically modified and includes abundant structural features such as salt domes and areally extensive faulting in addition to minor folding related to these features, all of which impact the sedimentological and hydraulic characteristics of the freshwater-bearing strata. The hydrogeologic framework of northwestern Louisiana comprises a sequence of structurally modifi ed, complexly interbedded, varyingly interconnected, clayey, sandy, and gravelly alluvial sediments. The important freshwater hydrogeologic units include the Quaternary Red River alluvial and upland terrace aquifers, and the underlying Tertiary Sparta, Cane River, and Carrizo-Wilcox aquifers. The Midway confining unit underlies the Carrizo-Wilcox aquifer throughout the study area. No freshwater is present in or below the Midway Group.
Tertiary-age formations exposed at land surface in the study area have been incised by the Red River and are hydraulically connected to the Quaternary Red River alluvium in the Red River valley. In 2010, 7.73 million gallons per day (Mgal/d) of water were withdrawn from the Red River alluvial aquifer in the study area, representing an increase of 2.00 Mgal/d, or about 35 percent, over 2005 withdrawal rates.
The Tertiary Carrizo Sand and Wilcox Group crop out across much of the study area. The two units are hydraulically connected and function as a single hydrologic unit referred to as the Carrizo-Wilcox aquifer. In 2010, 19.33 Mgal/d of water were withdrawn from the Carrizo-Wilcox aquifer in the study area, representing an increase of nearly 1.8 Mgal/d, or about 10 percent, over 2005 withdrawal rates. Any expansion in energy development, as well as water needs of an increasing population, could result in an increased demand on groundwater in northwestern Louisiana.
","language":"English","publisher":"Louisiana Department of Transportation and Development","usgsCitation":"Hays, P.D., Nottmeier, A.M., Fendick, R.B., Daugherty, W.J., and Carter, K., 2023, Hydrogeologic framework of the Red River alluvial aquifer and Carrizo-Wilcox aquifer in northwestern Louisiana: Water Resources Technical Report of the Louisiana Department of Transportation and Development, Office of Public Works 82, 35 p.","productDescription":"35 p.","ipdsId":"IP-122443","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":427146,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":427145,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://wise.er.usgs.gov/dp/pdfs/USGSDOTD_WRTR82.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Louisiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -94.04836792990136,\n 33.02200760162475\n ],\n [\n -94.04836792990136,\n 31.205735114403552\n ],\n [\n -91.87339632735423,\n 31.205735114403552\n ],\n [\n -91.87339632735423,\n 33.02200760162475\n ],\n [\n -94.04836792990136,\n 33.02200760162475\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hays, Phillip D. 0000-0001-5491-9272 pdhays@usgs.gov","orcid":"https://orcid.org/0000-0001-5491-9272","contributorId":4145,"corporation":false,"usgs":true,"family":"Hays","given":"Phillip","email":"pdhays@usgs.gov","middleInitial":"D.","affiliations":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true},{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":836782,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nottmeier, Anna M. 0000-0002-0205-0955 anottmeier@usgs.gov","orcid":"https://orcid.org/0000-0002-0205-0955","contributorId":5283,"corporation":false,"usgs":true,"family":"Nottmeier","given":"Anna","email":"anottmeier@usgs.gov","middleInitial":"M.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":836783,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fendick, Robert B.","contributorId":287472,"corporation":false,"usgs":false,"family":"Fendick","given":"Robert","email":"","middleInitial":"B.","affiliations":[{"id":37374,"text":"Retired USGS","active":true,"usgs":false}],"preferred":false,"id":836784,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Daugherty, William J.","contributorId":287473,"corporation":false,"usgs":false,"family":"Daugherty","given":"William","email":"","middleInitial":"J.","affiliations":[{"id":37814,"text":"Former USGS","active":true,"usgs":false}],"preferred":false,"id":897434,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Carter, Kayla kcarter@usgs.gov","contributorId":5681,"corporation":false,"usgs":true,"family":"Carter","given":"Kayla","email":"kcarter@usgs.gov","affiliations":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":false,"id":897435,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70240147,"text":"70240147 - 2023 - Maximizing the water quality benefits of wetlands in croplands","interactions":[],"lastModifiedDate":"2023-01-31T16:09:46.160963","indexId":"70240147","displayToPublicDate":"2023-01-01T10:06:18","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":13286,"text":"Conservation Insight","active":true,"publicationSubtype":{"id":1}},"title":"Maximizing the water quality benefits of wetlands in croplands","docAbstract":"Key Takeaways
Nutrient loads from croplands continue to negatively affect surface water quality, despite considerable investments in and adoption of agricultural conservation practices aimed at reducing nutrient losses.
Numerous studies indicate that effective restoration and management of wetlands in and adjacent to cultivated croplands could reduce surface and subsurface nutrient loads to downstream waters.
Current drainage basin-scale models do not effectively account for the local-scale processes that are important in understanding the functional variability of wetlands and their potential as conservation practices across different spatial and temporal scales.
Findings presented here from a literature review and simulation modeling study help inform bottom-up field-scale modeling of nitrogen and phosphorus dynamics and improve our understanding of the capacity for wetlands to provide nutrient retention services in agricultural drainage basins to inform strategic agricultural wetland restoration
","language":"English","publisher":"U.S. Department of Agriculture","usgsCitation":"McKenna, O.P., Ross, C.D., and Prenger, J., 2023, Maximizing the water quality benefits of wetlands in croplands: Conservation Insight, 4 p.","productDescription":"4 p.","ipdsId":"IP-123979","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":412507,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":412472,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.nrcs.usda.gov/sites/default/files/2023-01/CEAP-Wetlands-2023-ConservationInsight-WetlandsWaterQuality.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McKenna, Owen P. 0000-0002-5937-9436 omckenna@usgs.gov","orcid":"https://orcid.org/0000-0002-5937-9436","contributorId":198598,"corporation":false,"usgs":true,"family":"McKenna","given":"Owen","email":"omckenna@usgs.gov","middleInitial":"P.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":862766,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ross, Caryn D 0000-0002-9125-1424","orcid":"https://orcid.org/0000-0002-9125-1424","contributorId":300667,"corporation":false,"usgs":true,"family":"Ross","given":"Caryn","email":"","middleInitial":"D","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":862767,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Prenger, Joseph","contributorId":301843,"corporation":false,"usgs":false,"family":"Prenger","given":"Joseph","email":"","affiliations":[{"id":65354,"text":"USDA Natural Resources Conservation Service","active":true,"usgs":false}],"preferred":false,"id":862768,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70250602,"text":"70250602 - 2023 - Geologic map of Okmok Volcano","interactions":[],"lastModifiedDate":"2023-12-21T15:32:24.005778","indexId":"70250602","displayToPublicDate":"2023-01-01T09:28:59","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":5492,"text":"Report of Investigations of the Alaska Department of Natural Resources, Division of Geological & Geophysical Surveys","active":false,"publicationSubtype":{"id":2}},"seriesNumber":"2023-1","title":"Geologic map of Okmok Volcano","docAbstract":"The geologic map and description of map units presented here cover approximately 880 km2 of northeastern Umnak Island, Aleutian Islands, Alaska. This report focuses on Okmok Volcano and its eruptive products and updates the mid-20th-century geologic map of Byers (1959). Mapped deposits reflect the state of the volcano just prior to the 2008 eruption. Published information about other portions of Umnak Island geology, including Mount Recheshnoi and Mount Vsevidof, can be found in Byers (1959). The 2008 eruption and its deposits are described in Larsen and others (2009, 2013, 2015).
Okmok Volcano is one of 54 historically active volcanoes in the Alaska–Aleutian volcanic arc that stretches across southern mainland Alaska and the Aleutian Islands (fig. 1; Wood and Kienle, 1990; Miller and others, 1998; Cameron and others, 2020). The highest point of the modern Okmok Caldera is along the caldera’s northern rim, 967 m in elevation, and formally named “Mount Okmok” (U.S. Board on Geographic Names, www.usgs.gov/core-science-systems/ngp/boardon-geographic-names/domestic-names). Okmok Volcano dominates the northeastern portion of Umnak Island, which is 100 km southwest of Unalaska/Dutch Harbor and 1,400 km southwest of Anchorage (figs. 1, 2). The Port of Dutch Harbor on Unalaska Island produces the highest volume of seafood for any port in the United States (see fisheries.noaa.gov/resource/document/fisheries-united-states-2018-report). Unalaska city and the Port of Dutch Harbor have been impacted by ash fall and drifting ash clouds from Okmok Volcano’s explosive eruptions as recently as 2008. Holocene and late Pleistocene volcanic rocks and deposits of Okmok Volcano rest upon glaciated Tertiary volcanic and sedimentary rocks (Byers, 1959).
The first geologic mapping expedition to Okmok Volcano was by the U.S. Geological Survey (USGS) after the 1945 eruption, largely in response to concerns about volcanic hazards to U.S. military activities in the Aleutians Islands (Byers and others, 1947, 1959; Byers and Brannock, 1949; Byers, 1955, 1959, 1961). The State of Alaska conducted further mapping and geochemical studies as part of its geothermal exploration program in the 1980s (Nye, 1983; Nye and Reid, 1986; Motyka and others, 1993). Additional modern geological work focused on Okmok Volcano and the rest of Umnak Island to address the geochemistry and origin of primary Aleutian arc magmas and subduction zone mass recycling (Marsh, 1982; Brophy and Marsh, 1986; Nye and Reid, 1986; Myers and Marsh, 1987; Miller and others, 1992; Fournelle and others, 1994; Kay and Kay, 1994).
In 1998, the Alaska Volcano Observatory (AVO) began a multi-year effort to expand geophysical monitoring in the central Aleutians Islands, including at Okmok Volcano. As part of this effort, AVO geologists from the University of Alaska Fairbanks Geophysical Institute (UAF/GI), the Alaska Division of Geological & Geophysical Surveys (DGGS), and USGS also began a renewed effort to document Okmok Volcano’s recent eruption products. The project started with reconnaissance fieldwork to document and sample products from the 1997 eruption within Okmok Caldera. This evolved into an effort to produce an updated geologic map of Okmok Volcano and gather more information about its eruptive history and hazards. Three significant eruptions occurred at Okmok Volcano in 1958, 1997, and 2008—after fieldwork had been conducted for the original 1:63,360-scale geologic map produced by Byers (1959)—resulting in new volcanic deposits not previously described.
Okmok Volcano is one of the most frequently active volcanoes in the Aleutian volcanic arc. Seismic and geodetic monitoring indicate ongoing unrest at Okmok Volcano since at least 1997. Geodetic observations of inflation before and after the 1997 and 2008 eruptions indicate a nearly continuous input of new magma from a depth consistent with frequent eruptions of basalt and basaltic andesite magmas over the past 200 years (Larsen and others, 2013; Lu and others, 2000, 2003, 2005; Mann, 2002; Mann and others, 2002). To better understand the likelihood and character of future eruptions from Okmok Volcano, it is necessary to understand its past behavior, including eruptions since the first geologic map was published by Byers (1959).
","language":"English","publisher":"Alaska Division of Geological and Geophysical Surveys","doi":"10.14509/31015","usgsCitation":"Larsen, J., Neal, C.A., Schaefer, J., and Nye, C., 2023, Geologic map of Okmok Volcano: Report of Investigations of the Alaska Department of Natural Resources, Division of Geological & Geophysical Surveys 2023-1, 63 p., https://doi.org/10.14509/31015.","productDescription":"63 p.","ipdsId":"IP-142905","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":444978,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.14509/31015","text":"Publisher Index Page"},{"id":423837,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Okmok Volcano, Umnak Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -168.4940614057107,\n 53.01297120722842\n ],\n [\n -167.799296762778,\n 53.38973492849598\n ],\n [\n -167.78079711252238,\n 53.5365823869877\n ],\n [\n -168.09734668356276,\n 53.57077373403283\n ],\n [\n -168.38306350417713,\n 53.49991813616461\n ],\n [\n -168.7222237588632,\n 53.274349397005494\n ],\n [\n -169.14976831531723,\n 52.810922775693314\n ],\n [\n -168.97504939623653,\n 52.78979597004388\n ],\n [\n -168.4940614057107,\n 53.01297120722842\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Larsen, Jessica 0000-0003-1171-129X","orcid":"https://orcid.org/0000-0003-1171-129X","contributorId":242808,"corporation":false,"usgs":false,"family":"Larsen","given":"Jessica","email":"","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":890527,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Neal, Christina A. 0000-0002-7697-7825 tneal@usgs.gov","orcid":"https://orcid.org/0000-0002-7697-7825","contributorId":131135,"corporation":false,"usgs":true,"family":"Neal","given":"Christina","email":"tneal@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":890528,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schaefer, Janet","contributorId":199547,"corporation":false,"usgs":false,"family":"Schaefer","given":"Janet","affiliations":[],"preferred":false,"id":890529,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nye, Christopher J.","contributorId":332578,"corporation":false,"usgs":false,"family":"Nye","given":"Christopher J.","affiliations":[{"id":79497,"text":"Alaska Division of Geological & Geophysical Surveys (retired)","active":true,"usgs":false}],"preferred":false,"id":890530,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70240926,"text":"70240926 - 2023 - Inferring geologic structure from gravity anomalies: Proceed with caution","interactions":[],"lastModifiedDate":"2026-03-19T14:29:29.206183","indexId":"70240926","displayToPublicDate":"2023-01-01T09:28:09","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Inferring geologic structure from gravity anomalies: Proceed with caution","docAbstract":"Characterization of key geologic structures within a study region, such as basin depths, fault offsets, and fault dip, are often derived from gravity data. Gravity modeling of such subsurface geologic structure generally assumes either homogeneous or spatially uncorrelated densities within modeled rock bodies and overlying sediments. This assumption allows modeling to focus on the shape of the subsurface bodies, for example, body depth or fault dip, which then underpin subsequent structural interpretations. However, both surface and drill-hole samples from rock bodies and sediments show a range of density values that exhibit spatial correlation, The spatially-correlated densities add low-frequency noise to the models that is difficult to detect and characterize which can lead to misinterpretations of the subsurface structure.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Geologic mapping forum 22/23 abstracts","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Minnesota Geological Survey","usgsCitation":"Phelps, G., 2023, Inferring geologic structure from gravity anomalies: Proceed with caution, in Geologic mapping forum 22/23 abstracts, p. 39-40.","productDescription":"2 p.","startPage":"39","endPage":"40","ipdsId":"IP-147435","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":501306,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":501305,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://hdl.handle.net/11299/256180"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Phelps, Geoffrey 0000-0003-1958-2736 gphelps@usgs.gov","orcid":"https://orcid.org/0000-0003-1958-2736","contributorId":127489,"corporation":false,"usgs":true,"family":"Phelps","given":"Geoffrey","email":"gphelps@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":865326,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ]}