Describing future habitat for sensitive species can be helpful in planning conservation efforts to ensure species persistence under new climatic conditions. The Gila monster (Heloderma suspectum) is an iconic lizard of the southwestern United States. The northernmost range of Gila monsters is the Mojave Desert, an area experiencing rapid human population growth and urban sprawl. To understand current and potential future habitat for Gila monsters in the Mojave Desert, we fit ensemble species distribution models using known locations and current environmental variables known to be important to the species' biology. We then projected future suitable habitat under different climate forecasts based on IPCC emission scenarios. To ensure that Gila monsters would be able to disperse to newly suitable habitat, we fit Brownian Bridge movement models using telemetry data from two locations in Nevada. This model indicated that Gila monsters prefer to move through areas with a moderate slope and higher shrub cover. Modeled current suitable habitat for Gila monsters in Nevada was primarily in rugged bajadas and lower elevations at the bases of mountain ranges. Predictions of potential future habitat suggested that overall habitat suitability through 2082 would remain relatively stable throughout the study area in the lower emissions scenario, but in the high emissions scenario potential habitat is greatly reduced in many lower-elevation areas. Future habitat areas at higher elevations under the high emissions scenario showed moderate increases in suitability, though occupancy would likely be limited by Gila monster dispersal capabilities. Finally, we determined how well the protected area network of our study area encompassed future Gila monster habitat to highlight potential opportunities to protect this important species.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.71008","usgsCitation":"Hromada, S.J., Jones, J., Stalker, J., Wood, D.A., Vandergast, A.G., Tracy, C.R., Gienger, C., and Nussear, K.E., 2025, Climate and dispersal ability limit future habitats for Gila monsters in the Mojave Desert: Ecology and Evolution, v. 15, e71008, 15 p., https://doi.org/10.1002/ece3.71008.","productDescription":"e71008, 15 p.","ipdsId":"IP-166958","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":488343,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.71008","text":"Publisher Index Page"},{"id":483582,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California, Nevada, Utah","otherGeospatial":"Mojave Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -113.33194255435204,\n 37.76713352893536\n ],\n [\n -117.13833621353872,\n 37.76713352893536\n ],\n [\n -117.13833621353872,\n 33.75898076102743\n ],\n [\n -113.33194255435204,\n 33.75898076102743\n ],\n [\n -113.33194255435204,\n 37.76713352893536\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","noUsgsAuthors":false,"publicationDate":"2025-03-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Hromada, Steven J.","contributorId":245147,"corporation":false,"usgs":false,"family":"Hromada","given":"Steven","email":"","middleInitial":"J.","affiliations":[{"id":16686,"text":"University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":931420,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Jason L.","contributorId":352480,"corporation":false,"usgs":false,"family":"Jones","given":"Jason L.","affiliations":[{"id":27489,"text":"Nevada Department of Wildlife","active":true,"usgs":false}],"preferred":false,"id":931421,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stalker, Jocelyn B.","contributorId":352484,"corporation":false,"usgs":false,"family":"Stalker","given":"Jocelyn B.","affiliations":[{"id":84237,"text":"Austin Peay State University","active":true,"usgs":false}],"preferred":false,"id":931422,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wood, Dustin A. 0000-0002-7668-9911 dawood@usgs.gov","orcid":"https://orcid.org/0000-0002-7668-9911","contributorId":4179,"corporation":false,"usgs":true,"family":"Wood","given":"Dustin","email":"dawood@usgs.gov","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":931423,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vandergast, Amy G. 0000-0002-7835-6571","orcid":"https://orcid.org/0000-0002-7835-6571","contributorId":57201,"corporation":false,"usgs":true,"family":"Vandergast","given":"Amy","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":931424,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tracy, C. 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However, the organic content of these rocks has likely suffered from the radiation environment on the surface of Mars to an extent yet to be quantified. For the first time, a 1000 sols long ageing experiment was conducted at the surface of Mars, i.e. under actual Martian conditions, relying on the 100 % organic Ertalyte target carried by Perseverance. White at landing, the Ertalyte target has turned brown with time, while its Raman signal changed, with a modification of the background (its maximum has shifted from 1500 to 2000 cm−1) and a reduction of the contribution of the Raman signal of Ertalyte (by a factor of 5 over the first 500 sols). Given the intrinsic resistance of the Ertalyte to UV exposure, which is not anticipated for most Martian organic materials, these results suggest that exposure at the surface of Mars will make the detection of Martian organic molecules challenging.
","language":"English","publisher":"European Association of Geochemistry","doi":"10.7185/geochemlet.2509","usgsCitation":"Bernard, S., Beyssac, O., Manrique, J., Lopez Reyes, G., Ollila, A., Le Mouelic, S., Beck, P., Pilleri, P., Forni, O., Julve-Gonzales, S., Veneranda, M., Reyes Rodriguez, I., Madariaga Mota, J., Aramenda, J., Castro, K., Clave, E., Royer, C., Fornaro, T., Bousquet, B., Sharma, S., Johnson, J., Cloutis, E., Gabriel, T.S., Meslin, P., Gasnault, O., Cousin, A., Wiens, R., and Maurice, S., 2025, Ageing of organic materials at the surface of Mars: A Raman study aboard Perseverance: Geochemical Perspectives Letters, v. 34, p. 25-30, https://doi.org/10.7185/geochemlet.2509.","productDescription":"6 p.","startPage":"25","endPage":"30","ipdsId":"IP-169947","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":488337,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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velocimetry","interactions":[],"lastModifiedDate":"2025-03-18T16:47:13.564948","indexId":"70264626","displayToPublicDate":"2025-03-16T11:34:04","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating the potential to quantify salmon habitat via UAS-based particle image velocimetry","docAbstract":"Continuous, high-resolution data for characterizing freshwater habitat conditions can support successful management of endangered salmonids. Uncrewed aircraft systems (UAS) make acquiring such fine-scale data along river channels more feasible, but workflows for quantifying reach-scale salmon habitats are lacking. We evaluated the potential for UAS-based mapping of hydraulic habitats using spectrally based depth retrieval and particle image velocimetry (PIV) by comparing these methods to a more well-established flow modeling approach. Our results indicated that estimates of water depth, depth-averaged velocity, and flow direction derived via remote sensing and modeling techniques were comparable and in good agreement with field measurements. Predictions of spring-run Chinook salmon (Oncorhynchus tshawytscha) juvenile rearing habitat produced from PIV and model output were similar, with small errors relative to direct field observations. Estimates of hydraulic heterogeneity based on kinetic energy gradients in the flow field were generally consistent between PIV and flow modeling, but errors relative to field measurements were larger. PIV results were sensitive to the velocity index (α) used to convert surface velocities to depth-averaged velocities. Sun glint precluded PIV analysis along the margins of some images and a large degree of overlap between frames was thus required to obtain continuous coverage of the reach. Similarly, shadows cast by riparian vegetation caused gaps in spectrally based bathymetric maps. Despite these limitations, our results suggest that for sites with sufficient water surface texture, UAS-based PIV can provide detailed hydraulic habitat information at the reach scale, with accuracies comparable to traditional field methods and multidimensional flow modeling.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2024WR038045","usgsCitation":"Harrison, L.R., Legleiter, C.J., Overstreet, B., and White, J., 2025, Evaluating the potential to quantify salmon habitat via UAS-based particle image velocimetry: Water Resources Research, v. 3, no. 61, e2024WR038045, 21 p., https://doi.org/10.1029/2024WR038045.","productDescription":"e2024WR038045, 21 p.","ipdsId":"IP-163184","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":488333,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2024wr038045","text":"Publisher Index Page"},{"id":483481,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"North Santiam River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.01923518970605,\n 44.68226153883313\n ],\n [\n -122.36818028867839,\n 44.68226153883313\n ],\n [\n -122.36818028867839,\n 44.857748774184074\n ],\n [\n -123.01923518970605,\n 44.857748774184074\n ],\n [\n -123.01923518970605,\n 44.68226153883313\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"3","issue":"61","noUsgsAuthors":false,"publicationDate":"2025-03-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Harrison, Lee R.","contributorId":174322,"corporation":false,"usgs":false,"family":"Harrison","given":"Lee","email":"","middleInitial":"R.","affiliations":[{"id":6710,"text":"University of California, Santa Barbara, CA","active":true,"usgs":false}],"preferred":false,"id":930994,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Legleiter, Carl J. 0000-0003-0940-8013 cjl@usgs.gov","orcid":"https://orcid.org/0000-0003-0940-8013","contributorId":169002,"corporation":false,"usgs":true,"family":"Legleiter","given":"Carl","email":"cjl@usgs.gov","middleInitial":"J.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":930995,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Overstreet, Brandon 0000-0001-7845-6671 boverstreet@usgs.gov","orcid":"https://orcid.org/0000-0001-7845-6671","contributorId":169201,"corporation":false,"usgs":true,"family":"Overstreet","given":"Brandon","email":"boverstreet@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":930996,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"White, James 0000-0002-7255-3785 jameswhite@usgs.gov","orcid":"https://orcid.org/0000-0002-7255-3785","contributorId":193492,"corporation":false,"usgs":true,"family":"White","given":"James","email":"jameswhite@usgs.gov","affiliations":[],"preferred":true,"id":930997,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70264651,"text":"70264651 - 2025 - Dynamic baseflow storage estimates and the role of topography, geology and evapotranspiration on streamflow recession characteristics in the Neversink Reservoir Watershed, New York","interactions":[],"lastModifiedDate":"2025-03-18T16:31:27.341468","indexId":"70264651","displayToPublicDate":"2025-03-15T11:10:19","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Dynamic baseflow storage estimates and the role of topography, geology and evapotranspiration on streamflow recession characteristics in the Neversink Reservoir Watershed, New York","docAbstract":"Estimates of dynamic groundwater volumes supplying baseflow to streams are important for water availability projections during extended periods of drought. The primary goals of this study were to provide dynamic storage volume estimates, inferred from streamflow recession analysis, for baseflow regimes within seven gaged catchments within the Neversink Reservoir Watershed (NRW), a critical municipal water source for New York City. Additionally, geomorphological properties, surficial geology and hydro-meteorological processes were quantified and described in relation to time and spatially variable recession behaviour and storage estimates across the NRW. To explore these relationships, we (1) evaluated seasonal trends in streamflow recession behaviour in relation to modelled potential evapotranspiration (PET) and catchment runoff rates, (2) derived empirical streamflow models for cool-season runoff using both linear and nonlinear reservoir assumptions for baseflow and (3) calculated metrics related to the geology and geomorphology of each catchment and compared these metrics to area normalised baseflow dynamic storage estimates. Results show that baseflow recession behaves as a nonlinear reservoir, and applying linear groundwater reservoir assumptions may underestimate the total dynamic storage volumes compared to what would be predicted for a nonlinear reservoir. Increases in PET caused decreases in storage conditions that resulted in increased recession rates and nonlinearity in streamflow recession during the growing season. Additionally, we found that while no single physical catchment characteristic solely predicted catchment storage dynamics, sediment volume and stream gradients were stronger predictors of normalised storage volumes than catchment surface area or surface topography alone. Within the NRW, catchments with the highest sediment volume exhibited the lowest recession rates and higher dynamic storage volumes, while the smallest catchment, mostly devoid of sediment, had the fastest recession rate and lowest dynamic storage volume.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.70106","usgsCitation":"Benton, J., and Doctor, D.H., 2025, Dynamic baseflow storage estimates and the role of topography, geology and evapotranspiration on streamflow recession characteristics in the Neversink Reservoir Watershed, New York: Hydrological Processes, v. 39, no. 3, e70106, 17 p., https://doi.org/10.1002/hyp.70106.","productDescription":"e70106, 17 p.","ipdsId":"IP-163356","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":483480,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Neversink Reservoir Watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -73.95860919620127,\n 42.2147005922842\n ],\n [\n -74.56712312527952,\n 42.2147005922842\n ],\n [\n -74.56712312527952,\n 41.956641367777735\n ],\n [\n -73.95860919620127,\n 41.956641367777735\n ],\n [\n -73.95860919620127,\n 42.2147005922842\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"39","issue":"3","noUsgsAuthors":false,"publicationDate":"2025-03-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Benton, Joshua R. 0000-0002-1698-6455","orcid":"https://orcid.org/0000-0002-1698-6455","contributorId":352387,"corporation":false,"usgs":false,"family":"Benton","given":"Joshua R.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":84197,"text":"**please fill in","active":true,"usgs":false}],"preferred":false,"id":931072,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Doctor, Daniel H. 0000-0002-8338-9722 dhdoctor@usgs.gov","orcid":"https://orcid.org/0000-0002-8338-9722","contributorId":2037,"corporation":false,"usgs":true,"family":"Doctor","given":"Daniel","email":"dhdoctor@usgs.gov","middleInitial":"H.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":931073,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70264474,"text":"sir20255011 - 2025 - Comparison of hydrologic data and water budgets between 2003–08 and 2018–23 for the eastern part of the Arbuckle-Simpson aquifer, south-central Oklahoma","interactions":[],"lastModifiedDate":"2025-07-23T17:07:13.510916","indexId":"sir20255011","displayToPublicDate":"2025-03-14T15:26:55","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-5011","displayTitle":"Comparison of Hydrologic Data and Water Budgets Between 2003–08 and 2018–23 for the Eastern Part of the Arbuckle-Simpson Aquifer, South-Central Oklahoma","title":"Comparison of hydrologic data and water budgets between 2003–08 and 2018–23 for the eastern part of the Arbuckle-Simpson aquifer, south-central Oklahoma","docAbstract":"The Arbuckle-Simpson aquifer is divided spatially into three parts (eastern, central, and western). The largest groundwater withdrawals are from the eastern part of the Arbuckle-Simpson aquifer, which provides water to approximately 39,000 people in Ada and Sulphur, Oklahoma, and surrounding areas. The Arbuckle-Simpson aquifer, including the eastern part, is designated a sole source aquifer for its service area. Based primarily on data collected between 2003 and 2008, a series of comprehensive hydrologic studies of the Arbuckle-Simpson aquifer was published to provide the information necessary to perform groundwater-flow model simulations so that the Oklahoma Water Resources Board could determine how much water could be withdrawn from the aquifer while maintaining flow to springs and streams. As part of the Phase 1 studies, an aquifer water budget was developed from a numerical model for the period 2003–08. For this report, Phase 1 refers to the 2003–08 data collection period, although for some of the analyses, data collected prior to 2003 were used to inform model development work. Allocation of water from this aquifer was then established by the Oklahoma Water Resources Board in 2013. Additional well-spacing rules were also established by the Oklahoma Water Resources Board for sensitive sole source groundwater basins. To determine how the water budget for the eastern part of the Arbuckle-Simpson aquifer has changed over time, recently collected hydrologic data (2018–23) were compared to data collected during 2003–08. The analysis of changes in the aquifer water budget from 2003–08 to 2018–23 could help resource managers better understand changes in the overall balance of water in storage and the potential effects on streamflow, changes in groundwater levels, and the effects of different water uses in the aquifer area on available water in the eastern part of the Arbuckle-Simpson aquifer and streams overlying the eastern part of the Arbuckle-Simpson aquifer.
Director, Oklahoma-Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754–4501
Contact Us- USGS Publications Warehouse
","tableOfContents":"The mummichog Fundulus heteroclitus is a trophically important fish inhabiting Atlantic coastal salt marshes, with few in situ estimates of overwinter survival throughout the species range. We estimated overwinter apparent survival rates of F. heteroclitus at the approximate mid-latitudinal species range [coastal North Carolina (USA)] in four tidal creeks that experience variable winter water temperatures. To estimate apparent survival, we fitted a Cormack-Jolly-Seber model to daily mark-resight data autonomously obtained from fish marked with passive integrated transponder tags. Creek, year, mean daily water temperature, change in mean daily temperature, fish length and fish condition were considered for effects on the modelled parameters: apparent survival (Φ) (product of true survival and site fidelity) and detection probability (p). Modelling showed that water temperature and fish metrics were not related to Φ. Water temperature was directly related to p, indicating reduced fish activity and thus reduced detection probability or poor antenna detection performance at low temperatures. Creek was related to Φ and p, and the creek most open to its downstream estuary (lacking a culvert) had lower rates than the others. Greater loss (fish mortality plus emigration) in this one creek may more effectively transfer production of F. heteroclitus to larger waterbodies via emigration or predation. Conversely, lower Φ may reflect reduced detection efficiency. The results suggest that F. heteroclitus survival is insensitive to variable winter water temperatures typical of thermal dynamics in shallow estuaries in this region of its range. Median creek-specific overwinter Φ rates (range of median values, 2 × 10−8, 0.04) were roughly equal to previously published rates for these creeks during the growing season (April–October). At these latitudes and with increasingly moderate winters, the results indicate that natural mortality could arise equally or more so from predation during the growing season than mechanisms such as starvation, direct mortality, thermal morbidity and stress-related susceptibility to predation resulting from intermittently low water temperatures during the overwinter season.
","language":"English","publisher":"Wiley","doi":"10.1111/jfb.70020","usgsCitation":"Rudershausen, P.J., and O'Donnell, M.J., 2025, Overwinter survival of an estuarine resident fish (Fundulus heteroclitus) in North Carolina salt marsh creeks: Journal of Fish of Biology, v. 107, no. 1, p. 188-200, https://doi.org/10.1111/jfb.70020.","productDescription":"13 p.","startPage":"188","endPage":"200","ipdsId":"IP-168105","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":488323,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/jfb.70020","text":"Publisher Index Page"},{"id":483454,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -76.61589538108844,\n 34.739737828981234\n ],\n [\n -76.80342045072118,\n 34.74057409854757\n ],\n [\n -76.80219234343787,\n 34.68681714274115\n ],\n [\n -76.61593931817359,\n 34.68548980814643\n ],\n [\n -76.61589538108844,\n 34.739737828981234\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"107","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-03-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Rudershausen, P. J.","contributorId":352331,"corporation":false,"usgs":false,"family":"Rudershausen","given":"P.","middleInitial":"J.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":930816,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O'Donnell, Matthew J. 0000-0002-9089-2377","orcid":"https://orcid.org/0000-0002-9089-2377","contributorId":295467,"corporation":false,"usgs":true,"family":"O'Donnell","given":"Matthew","middleInitial":"J.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":930817,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70269914,"text":"70269914 - 2025 - Temporal and spatial equivalence in demographic responses of emperor penguins (Aptenodytes forsteri) to environmental change","interactions":[],"lastModifiedDate":"2025-08-07T17:05:49.242218","indexId":"70269914","displayToPublicDate":"2025-03-13T09:31:49","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2158,"text":"Journal of Animal Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Temporal and spatial equivalence in demographic responses of emperor penguins (Aptenodytes forsteri) to environmental change","docAbstract":"1. Population ecology and biogeography applications often necessitate the transfer of models across spatial and/or temporal dimensions to make predictions outside the bounds of the data used for model fitting. However, ecological data are often spatiotemporally unbalanced such that the spatial or the temporal dimension tends to contain more data than the other. This unbalance frequently leads model transfers to become substitutions, which are predictions to a different dimension than the predictive model was built on. Despite the prevalence of substitutions in ecology, studies validating their performance and their underlying assumptions are scarce.
2. Here, we present a successful case study demonstrating both space-for-time and time-for-space substitutions using emperor penguins (Aptenodytes forsteri) as the focal species. Using abundance-based species distribution models (aSDM) of adult emperor penguins in attendance during spring across 50 colonies, we predict long-term annual fluctuations in fledgling abundance and breeding success at a single colony, Pointe Géologie. Subsequently, we construct statistical models from time series of extended counts on Pointe Géologie to predict average fledgling abundance across 50 colonies.
3. Our analysis reveals that distance to nearest open water (NOW) exhibits the strongest association with both temporal and spatial data. aSDM’s space-for-time substitution performance, as measured by Pearson correlation coefficient was 0.63 and 0.56 when predicting breeding success and fledgling abundance time series, respectively. Linear regression of fledgling abundance on NOW yields similar time-for-space substitution performance when predicting abundance distribution of emperor penguin colonies with a correlation coefficient of 0.58.
4. We posit that such space-time equivalence arises because: 1) emperor penguins colonies conform to their existing fundamental niche; 2) there is not yet any environmental novelty when comparing the spatial vs temporal variation of distance to nearest open water; and 3) models of more specific components of life histories, such as fledgling abundance, rather than occurrence or total population abundance, are more transferable. Identifying these conditions empirically can enhance the qualitative validation of substitutions in cases where direct validation data are lacking.
","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2656.70025","usgsCitation":"Şen, B., Che-Castaldo, C., LaRue, M., Krumhardt, K., Landrum, L., Holland, M., Lynch, H., Delord, K., Barbraud, C., and Jenouvrier, S., 2025, Temporal and spatial equivalence in demographic responses of emperor penguins (Aptenodytes forsteri) to environmental change: Journal of Animal Ecology, v. 94, no. 5, p. 932-942, https://doi.org/10.1111/1365-2656.70025.","productDescription":"11 p.","startPage":"932","endPage":"942","ipdsId":"IP-170330","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":496436,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2656.70025","text":"Publisher Index Page"},{"id":493730,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Antarctica, Pointe Géologie","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 154.44140675588028,\n -67.88310899484881\n ],\n [\n 154.44140675588028,\n -70.08242540623479\n ],\n [\n 161.81002372233837,\n -70.08242540623479\n ],\n [\n 161.81002372233837,\n -67.88310899484881\n ],\n [\n 154.44140675588028,\n -67.88310899484881\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"94","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-03-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Şen, Bilgecan","contributorId":359058,"corporation":false,"usgs":false,"family":"Şen","given":"Bilgecan","affiliations":[{"id":37215,"text":"University of Maryland Center for Environmental Science","active":true,"usgs":false}],"preferred":false,"id":944928,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Che-Castaldo, Christian Joseph 0000-0002-7670-2178","orcid":"https://orcid.org/0000-0002-7670-2178","contributorId":347906,"corporation":false,"usgs":true,"family":"Che-Castaldo","given":"Christian Joseph","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":944929,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"LaRue, Michelle A.","contributorId":348627,"corporation":false,"usgs":false,"family":"LaRue","given":"Michelle A.","affiliations":[{"id":37172,"text":"University of Canterbury","active":true,"usgs":false}],"preferred":false,"id":944930,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Krumhardt, Kristen M.","contributorId":359059,"corporation":false,"usgs":false,"family":"Krumhardt","given":"Kristen M.","affiliations":[{"id":85742,"text":"NSF National Center for Atmospheric Research","active":true,"usgs":false}],"preferred":false,"id":944931,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Landrum, Laura","contributorId":359060,"corporation":false,"usgs":false,"family":"Landrum","given":"Laura","affiliations":[{"id":85742,"text":"NSF National Center for Atmospheric Research","active":true,"usgs":false}],"preferred":false,"id":944932,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Holland, Marika M.","contributorId":359062,"corporation":false,"usgs":false,"family":"Holland","given":"Marika M.","affiliations":[{"id":85742,"text":"NSF National Center for Atmospheric Research","active":true,"usgs":false}],"preferred":false,"id":944933,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lynch, Heather J.","contributorId":347911,"corporation":false,"usgs":false,"family":"Lynch","given":"Heather J.","affiliations":[{"id":36488,"text":"Stony Brook University","active":true,"usgs":false}],"preferred":false,"id":944934,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Delord, Karine 0000-0001-6720-951X","orcid":"https://orcid.org/0000-0001-6720-951X","contributorId":197702,"corporation":false,"usgs":false,"family":"Delord","given":"Karine","email":"","affiliations":[],"preferred":false,"id":944935,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Barbraud, Christophe","contributorId":197701,"corporation":false,"usgs":false,"family":"Barbraud","given":"Christophe","email":"","affiliations":[],"preferred":false,"id":944936,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Jenouvrier, Stéphanie","contributorId":359063,"corporation":false,"usgs":false,"family":"Jenouvrier","given":"Stéphanie","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":944937,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70264367,"text":"ofr20211104F - 2025 - Potential effects of sea level rise and high tide flooding on Laterallus jamaicensis jamaicensis (eastern black rail) coastal breeding areas","interactions":[{"subject":{"id":70264367,"text":"ofr20211104F - 2025 - Potential effects of sea level rise and high tide flooding on Laterallus jamaicensis jamaicensis (eastern black rail) coastal breeding areas","indexId":"ofr20211104F","publicationYear":"2025","noYear":false,"chapter":"F","displayTitle":"Potential Effects of Sea Level Rise and High Tide Flooding on Laterallus jamaicensis jamaicensis (Eastern Black Rail) Coastal Breeding Areas","title":"Potential effects of sea level rise and high tide flooding on Laterallus jamaicensis jamaicensis (eastern black rail) coastal breeding areas"},"predicate":"IS_PART_OF","object":{"id":70228323,"text":"ofr20211104 - 2022 - Effects of climate change on fish and wildlife species in the United States","indexId":"ofr20211104","publicationYear":"2022","noYear":false,"title":"Effects of climate change on fish and wildlife species in the United States"},"id":1}],"isPartOf":{"id":70228323,"text":"ofr20211104 - 2022 - Effects of climate change on fish and wildlife species in the United States","indexId":"ofr20211104","publicationYear":"2022","noYear":false,"title":"Effects of climate change on fish and wildlife species in the United States"},"lastModifiedDate":"2025-07-23T16:56:40.604898","indexId":"ofr20211104F","displayToPublicDate":"2025-03-12T15:03:12","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-1104","chapter":"F","displayTitle":"Potential Effects of Sea Level Rise and High Tide Flooding on Laterallus jamaicensis jamaicensis (Eastern Black Rail) Coastal Breeding Areas","title":"Potential effects of sea level rise and high tide flooding on Laterallus jamaicensis jamaicensis (eastern black rail) coastal breeding areas","docAbstract":"Laterallus jamaicensis jamaicensis (eastern black rails; Gmelin, 1789) are facing increasing risk from flooding in coastal breeding habitats because of rising sea levels combined with standard high tide flooding. In this report, we examine regional differences in relative rates of sea level rise, days in the breeding season above historical high tide flooding thresholds, future inundation of current (2021) emergent wetlands, and potential marsh resiliency for the breeding distribution of the eastern black rail across the Atlantic and U.S. Gulf coasts. By midcentury (2050), two sea level rise scenarios (intermediate low and intermediate) indicate that areas analyzed in Texas and the Mid-Atlantic will experience at least minor flood levels for more than half of the breeding season. By the end of the century (2100), all tidal gages in the Atlantic and U.S. Gulf coasts are projected to experience at least moderate flood levels for most of the current (April–September) eastern black rail breeding season. In some areas like New Jersey, this translates to inundation for most of the emergent wetlands in the representative parishes and counties analyzed in this report. In other parts of the coastal distribution, estimates of increases in inundation are lower or more variable, stemming from differences in the elevation of existing emergent marsh, especially at the herbaceous wetland/woody wetland transition zone. Sea level rise and tidal flooding are not projected to pose an equal risk across the coastal distribution of the eastern black rail, leading to variation in risk of nest loss because of flooding. The degree to which these wetlands and birds will adapt to changing sea level and salinity depends on a range of factors including future expansion of developed areas and the ability of marsh areas to move inland. Restoration and active management of coastal wetland areas may be necessary to maintain appropriate breeding habitat.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211104F","usgsCitation":"Nikiel, C.A., and Lyons, M.P., 2025, Potential effects of sea level rise and high tide flooding on Laterallus jamaicensis jamaicensis (eastern black rail) coastal breeding areas: U.S. Geological Survey Open-File Report 2021–1104–F, 40 p., https://doi.org/10.3133/ofr20211104F.","productDescription":"vii, 40 p.","numberOfPages":"52","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-172341","costCenters":[{"id":65882,"text":"Midwest Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":483246,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20211104F/full"},{"id":483244,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1104/f/ofr20211104f.XML"},{"id":483243,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1104/f/ofr20211104f.pdf","text":"Report","size":"15 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1104-F"},{"id":483242,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1104/f/coverthb.jpg"},{"id":483245,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1104/f/images/"},{"id":492780,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118482.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","otherGeospatial":"Atlantic Coast, Gulf Coast","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -66.73369411465748,\n 44.87861692762931\n ],\n [\n -67.9395715369188,\n 45.91302389167819\n ],\n [\n -68.52891205677287,\n 46.14233382856975\n ],\n [\n -69.66609739851674,\n 44.904840367756236\n ],\n [\n -71.8455845133013,\n 43.01632555370077\n ],\n [\n -75.76042364090121,\n 40.73258218965182\n ],\n [\n -77.41422284991526,\n 39.32302567933269\n ],\n [\n -77.11953264135055,\n 36.58955309284522\n ],\n [\n -79.0153316043617,\n 34.430624116007294\n ],\n [\n -82.3380440342791,\n 31.342877305678\n ],\n [\n -87.14213042595998,\n 31.473505392669267\n ],\n [\n -87.74548189802837,\n 32.39195075385649\n ],\n [\n -89.00813665013129,\n 32.354083649747\n ],\n [\n -89.30755056658234,\n 31.271920212222028\n ],\n [\n -92.00443786768639,\n 31.222304379727817\n ],\n [\n -95.98918412828937,\n 30.505582509882984\n ],\n [\n -98.19210772787893,\n 28.060885389466677\n ],\n [\n -98.10578570219339,\n 26.094479941263742\n ],\n [\n -97.05626247225148,\n 25.880720528127156\n ],\n [\n -97.21103649173618,\n 27.232424454623654\n ],\n [\n -95.67794712232511,\n 28.598718054492764\n ],\n [\n -93.37262411904577,\n 29.53246193068931\n ],\n [\n -90.09201823404798,\n 28.868540112379208\n ],\n [\n -88.84955647397418,\n 28.787680093703898\n ],\n [\n -88.58294319870708,\n 29.755309328858473\n ],\n [\n -86.26626920949336,\n 30.023219777079703\n ],\n [\n -84.98796116952035,\n 29.29748111241001\n ],\n [\n -83.97817016398578,\n 29.677155423717906\n ],\n [\n -82.92684471060598,\n 28.711279338050616\n ],\n [\n -83.33453111961292,\n 28.007674975959418\n ],\n [\n -81.38398690858428,\n 24.942184191892167\n ],\n [\n -81.48743115456318,\n 24.146104924998653\n ],\n [\n -79.34128084180263,\n 25.993764942081356\n ],\n [\n -81.14405051637162,\n 30.851402909345737\n ],\n [\n -74.95193417969506,\n 35.431852837245344\n ],\n [\n -75.10789103469754,\n 37.38614632113877\n ],\n [\n -73.3440560833726,\n 40.10806605773732\n ],\n [\n -69.15888557248354,\n 41.691566830140545\n ],\n [\n -70.25945555475435,\n 43.01474979449651\n ],\n [\n -66.73369411465748,\n 44.87861692762931\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Midwest Climate Adaptation Science Center
U.S. Geological Survey
1954 Buford Avenue
St. Paul, MN 55108
Drought and its effect on streamflow are important to understand because of the potential to adversely affect water supply, agricultural production, and ecological conditions. The Red River of the North Basin in north-central United States and central Canada is susceptible to dry conditions. During an extended drought, streamflow conditions in the Red River of the North may become inadequate to support existing water supply needs in the basin for agriculture, industry, human use, and aquatic life. To understand potential future low-streamflow conditions in the Red River of the North Basin, the U.S. Geological Survey, in cooperation with the International Joint Commission, North Dakota Department of Water Resources, Red River Joint Water Resource District, and Red River Watershed Management Board, developed a water-balance model of the Red River of the North Basin upstream from Emerson, Manitoba, Canada, and coupled the model with stochastic weather inputs to simulate possible future low-streamflow conditions.
Historical changes in low-streamflow conditions were characterized across the Red River of the North Basin using multiple change-point analysis for 12 streamgages. Across these stations, significant change-point years in 1943 and 1994 marked increases in the magnitude of low-streamflow conditions. During 1920–2015, conversion of primary land (not affected by human use) to agricultural and secondary land was followed by a conversion from smalls grains to corn and soybeans as the dominant crop type. From land-use analysis, 1940–2000 was determined to have relatively stable land use and therefore was used as the calibration period for the water-balance model.
A deterministic water-balance model was developed for the Red River of the North Basin upstream from Emerson, Manitoba. The water-balance model was calibrated with data from 37 U.S. Geological Survey streamgages for 1940–2000 and verified using data for 2001–15. The calibrated water-balance model simulated streamflow distributions that mirrored the seasonal patterns of the observed mean monthly streamflow and the standard deviation of the monthly streamflow data, especially during the fall and winter months when streamflow was lowest. For the verification period, during the low-streamflow months of December through January, the difference between simulated and observed data was similar to the calibration comparison and successfully reproduced seasonal trends in the distribution of streamflow, even when using weather data that were outside the calibration period.
To determine the future risk of low-streamflow conditions in the Red River of the North Basin, a block-bootstrap method was used to generate multiple possible future climates. These stochastically generated weather time series were then input to a water-balance model to simulate a distribution of possible streamflows. Three sets of experiments were performed, with each experiment containing a set of scenarios. The first set of experiments from the stochastic streamflow model were designed to investigate how changes in reservoir management would affect the distribution of low streamflow. Relative to scenario 1 (present-day [2023] reservoir operation), scenario 2 (no reservoir operation) shifted the low-streamflow frequency curves downward, reducing the annual minimum monthly streamflow for the Emerson subbasin. Subbasins were defined by the contributing area upstream from a selected streamgage station. Relative to scenario 1, scenario 3 (regulated streamflow with an increased reservoir capacity of 10 percent) shifted the low-streamflow frequency curves upward for the Emerson subbasin. The magnitude of this upward shift, caused by increased reservoir capacity, was lower than the magnitude of the shift caused by the absence of the reservoirs, which indicates that the streamflow was most affected when the reservoirs were first constructed.
The second set of experiments from the stochastic streamflow model included two scenarios that were performed to better understand how the Red River of the North Basin responds to long periods of low or high precipitation. The results indicate that the model consistently overestimated streamflow, but the relative change between a wet and dry climate state of simulated streamflow distribution reasonably matched the relative change of historical streamflow. Across the subbasins, the model was most accurate for low-streamflow conditions associated with nonexceedance probabilities between 20 and 40 percent.
The third set of experiments from the stochastic streamflow model were done to investigate low-streamflow response across the basin to several drought events. Low-end streamflow was reduced when the basin was exposed to a drought, and the magnitude of the reduction increased with longer or more intense droughts. Compared to the low-intensity drought scenarios, the range of percent reductions (as indicated by the interquartile range) was larger for the high-intensity drought scenarios for all subbasins, and the subbasins of Grand Forks and Emerson had a smaller range of reductions compared to the other three subbasins. The larger drainage area—combined with the large contribution of the Red Lake River and several other Minnesota tributaries that generally experience wetter climate conditions—upstream from the Emerson and Grand Forks subbasins may contribute to the smaller range in reductions under the high intensity scenarios. Comparison of the percent reduction in low-end streamflow among subbasins also indicated that the effects of drought duration and intensity could be cumulative. Combining factors of time and intensity produced a larger reduction in streamflow than when each effect was isolated. The array of drought scenarios can be used to determine how a subbasin would respond to multiple possible future conditions. Based on climate predictions, the drought scenario that best matches a future anticipated drought scenario can be used to estimate a low streamflow response for a given subbasin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255002","collaboration":"Prepared in cooperation with the International Joint Commission, North Dakota Department of Water Resources, Red River Joint Water Resource District, and Red River Watershed Management Board","usgsCitation":"Redoloza, F.S., Glas, R.L., Nustad, R.A., and Ryberg, K.R., 2025, Evaluating drought risk of the Red River of the North Basin using historical and stochastic streamflow upstream from Emerson, Manitoba: U.S. Geological Survey Scientific Investigations Report 2025–5002, 58 p., https://doi.org/10.3133/sir20255002.","productDescription":"Report: viii, 58 p.; Data Release; Dataset","numberOfPages":"70","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-160450","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":492779,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118481.htm","linkFileType":{"id":5,"text":"html"}},{"id":483206,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13XEN8U","text":"USGS data release","linkHelpText":"Red River of the North low flow water-balance model and supporting data"},{"id":483203,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5002/sir20255002.XML"},{"id":483202,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5002/sir20255002.pdf","text":"Report","size":"9.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5002"},{"id":483201,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5002/coverthb.jpg"},{"id":483204,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5002/images/"},{"id":483207,"rank":7,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the Nation"},{"id":483205,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255002/full"}],"country":"Canada, United States","state":"Manitoba, Minnesota, North Dakota","otherGeospatial":"Red River of the North Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -97.08881710576394,\n 49.037592614274644\n ],\n [\n -97.61189514667993,\n 49.237246321777064\n ],\n [\n -97.98430773681044,\n 49.25792746144549\n ],\n [\n -98.47156466708684,\n 49.30311814027007\n ],\n [\n -98.18869515177104,\n 48.806510092341696\n ],\n [\n -98.92510212635796,\n 48.563256003263746\n ],\n [\n -98.41426650704827,\n 48.10818045779425\n ],\n [\n -97.49283622534884,\n 48.05240253638604\n ],\n [\n -97.3523048621935,\n 47.017146908752025\n ],\n [\n -97.10429716720503,\n 45.72316825195222\n ],\n [\n -95.52291599413297,\n 45.59412827523792\n ],\n [\n -94.77240339220764,\n 46.995377381657505\n ],\n [\n -94.76454577568065,\n 47.45566932791883\n ],\n [\n -93.68493211560182,\n 47.83688445747143\n ],\n [\n -94.11770692662546,\n 48.33322840096503\n ],\n [\n -95.73784376997673,\n 48.92757937919353\n ],\n [\n -97.08881710576394,\n 49.037592614274644\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Dakota Water Science Center
U.S. Geological Survey
821 East Interstate Avenue, Bismarck, ND 58503
1608 Mountain View Road, Rapid City, SD 57702
The umbrella species concept is often used as a tool to guide management decisions and focus efforts towards one focal species whose habitat needs overlap that of other species. We assessed this concept in the context of an agriculturally dominant landscape using one of the most well-studied avian species in North America as a target for conservation efforts: Northern Bobwhite (Colinus virginianus). This species is often viewed as an umbrella species for grassland and shrubland bird conservation throughout its native range due to its complex, year-round habitat requirements. We assessed the influence of Northern Bobwhite habitat management on six songbird species of conservation concern in Iowa by evaluating similarities and differences in habitat associations between each species. Our objectives were to (1) assess which vegetation characteristics were most strongly associated with Northern Bobwhite occupancy and (2) evaluate whether those characteristics were also associated with abundance of the focal songbird species. We used occupancy and N-mixture models to assess relationships between vegetation characteristics and Northern Bobwhite occupancy and songbird abundance, respectively. We found that the vegetation characteristics most strongly associated with Northern Bobwhite occupancy probability were the amounts of closed canopy forest, early successional woody vegetation, non-vegetated areas, and percent cover of bare ground. We found that for some of these covariates, including the amounts of forest and non-vegetated area, the effect on focal songbird species abundance aligned with Northern Bobwhite occupancy. For others, including the amount of early successional woody vegetation, the effects differed. This assessment of overlap and variability in habitat associations suggests that Northern Bobwhite-targeted management can provide benefits to other grassland and shrubland birds, but may also come with some trade-offs. This work adds to existing literature, further highlighting the nuances of the umbrella species concept in that land management benefits from the assessment of trade-offs and inclusion of local community dynamics.
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Production capacity can limit future supply, depending on how rapidly that capacity is able to expand. Current capacity can be evaluated on the basis of past production. Decreases to future capacity can be taken into account from announcements of planned shutdowns of mines or processing facilities, which are frequently publicized well in advance of such closures. Likewise, capacity expansions, which usually involve multiple stages—such as permitting, financing, and construction (all of which take time)—can also be estimated. As such, it is possible to evaluate midterm future capacity based on estimates of today’s capacities along with consideration of future investment plans. This World Minerals Outlook provides estimated capacities for cobalt, gallium, helium, lithium, magnesium, palladium, platinum, and titanium for 2025 through 2029.
The results of this analysis indicate that two mineral commodities important to the manufacture of lithium-ion batteries—cobalt and lithium—are expected to have large capacity growth in the next few years, likely owing to expectations for increased demand for these batteries. For gallium, helium, palladium, and platinum, capacity is expected to remain stable or exhibit moderate growth. Still, these expected capacity levels are higher than current production, allowing for future production growth. The production capacity outlook is opaque for magnesium and titanium metal, which have a significant fraction of current production in nonmarket economies, such as China and Russia. Ultimately, though, where free market conditions prevail, full utilization of capacity potential for those commodities is likely to depend on supply deficits and prices that are above production costs.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255021","usgsCitation":"Alonso, E., Brioche, A.S., Schulte, R.F., Trimmer, L.M., Kim, J.-E., Gulley, A.L., and Pineault, D.G., 2025, World minerals outlook—Cobalt, gallium, helium, lithium, magnesium, palladium, platinum, and titanium through 2029 (ver. 1.1, March 14, 2025): U.S. Geological Survey Scientific Investigations Report 2025–5021, 19 p., https://doi.org/10.3133/sir20255021.","productDescription":"Report: vi, 19 p.; Data Release","numberOfPages":"19","onlineOnly":"Y","ipdsId":"IP-173545","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":483354,"rank":7,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2025/5021/versionHist.txt","size":"4.64 KB","linkFileType":{"id":2,"text":"txt"}},{"id":483159,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1HTTCWN","text":"USGS data release","linkHelpText":"World minerals outlook to 2029—Cobalt, gallium, helium, lithium, magnesium, palladium, platinum, and titanium data"},{"id":483408,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5021//images/"},{"id":483406,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255021/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5021 HTML"},{"id":492776,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118478.htm","linkFileType":{"id":5,"text":"html"}},{"id":483407,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5021/sir20255021.XML","description":"SIR 2025-5021 XML"},{"id":483145,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5021/sir20255021.pdf","text":"Report","size":"2.16 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5021 PDF"},{"id":483144,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5021/coverthb2.jpg"}],"edition":"Version 1.0: March 11, 2025; Version 1.1: March 14, 2025","contact":"Director, National Minerals Information Center
U.S. Geological Survey
12201 Sunrise Valley Drive
988 National Center
Reston, VA 20192
Email: nmicrecordsmgt@usgs.gov
","tableOfContents":"Understanding mine production and potential capacity growth can help inform the growing need for the minerals that support economic growth, technological change, and national security for businesses and policy makers. How much a mine can produce affects future supply, especially as capacities can change over time. This report estimates production capacities for cobalt, gallium, helium, lithium, magnesium, palladium, platinum, and titanium through 2029. The results of the analysis suggest that cobalt and lithium, which are key for lithium-ion batteries, are likely to see significant increases in production capacity owing to rising demand, whereas gallium and platinum are expected to see stable or moderate growth, exceeding current production levels. However, the future for magnesium and titanium is less clear because much of their production comes from countries with nonmarket economies, like China and Russia. In free markets, using full production capacity is likely to depend on supply shortages and prices being above production costs.
","publicationDate":"2025-03-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Alonso, Elisa 0000-0002-0090-8284","orcid":"https://orcid.org/0000-0002-0090-8284","contributorId":223015,"corporation":false,"usgs":true,"family":"Alonso","given":"Elisa","email":"","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":930300,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brioche, Amanda Sarah 0000-0002-9650-2456","orcid":"https://orcid.org/0000-0002-9650-2456","contributorId":332784,"corporation":false,"usgs":true,"family":"Brioche","given":"Amanda Sarah","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":930301,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schulte, Ruth 0000-0003-4724-5905","orcid":"https://orcid.org/0000-0003-4724-5905","contributorId":201973,"corporation":false,"usgs":true,"family":"Schulte","given":"Ruth","email":"","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":930302,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Trimmer, Loyd M. III 0000-0003-4121-7874 ltrimmer@usgs.gov","orcid":"https://orcid.org/0000-0003-4121-7874","contributorId":194120,"corporation":false,"usgs":true,"family":"Trimmer","given":"Loyd","suffix":"III","email":"ltrimmer@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":false,"id":930303,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kim, Ji-Eun 0000-0002-7668-5072","orcid":"https://orcid.org/0000-0002-7668-5072","contributorId":331665,"corporation":false,"usgs":true,"family":"Kim","given":"Ji-Eun","email":"","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":930304,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gulley, Andrew L. 0000-0003-4717-2080","orcid":"https://orcid.org/0000-0003-4717-2080","contributorId":203953,"corporation":false,"usgs":true,"family":"Gulley","given":"Andrew","email":"","middleInitial":"L.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":930305,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pineault, David 0009-0001-6801-4711","orcid":"https://orcid.org/0009-0001-6801-4711","contributorId":352217,"corporation":false,"usgs":true,"family":"Pineault","given":"David","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":930306,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70264230,"text":"sir20245121 - 2025 - Updating and recalibrating the integrated Santa Rosa Plain Hydrologic Model to assess stream depletion and to simulate future climate and management scenarios in Santa Rosa, Sonoma County, California","interactions":[],"lastModifiedDate":"2025-07-23T16:41:23.789208","indexId":"sir20245121","displayToPublicDate":"2025-03-10T12:15:19","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2024-5121","displayTitle":"Updating and Recalibrating the Integrated Santa Rosa Plain Hydrologic Model to Assess Stream Depletion and to Simulate Future Climate and Management Scenarios in Santa Rosa, Sonoma County, California","title":"Updating and recalibrating the integrated Santa Rosa Plain Hydrologic Model to assess stream depletion and to simulate future climate and management scenarios in Santa Rosa, Sonoma County, California","docAbstract":"The Santa Rosa Plain Hydrologic Model (SRPHM) was developed and published in 2014 through a collaboration between the U.S. Geological Survey (USGS) and Sonoma Water to analyze the hydrologic system in the Santa Rosa Plain watershed, help meet the increasing demand for fresh water, and prepare for future uncertainties in water resources. The original model simulated hydrological conditions and water use from water years 1975 to 2010. Recently (2023), the USGS, in cooperation with Sonoma Water and the California State Water Resources Control Board, updated the SRPHM model to extend its simulation period to the end of the 2018 calendar year, incorporate new estimates of rural and agricultural water use, and use efficient input format for climate variables. The updated model was recalibrated, and evaluation of the new model calibration is included in this report. This report presents the results of comparing the hydraulic heads, streamflow, and groundwater budget simulated by the updated model with those generated by the original model and observed data. The main difference in the simulated budget between the original and updated SRPHM is the estimates of agricultural pumping, rural domestic pumping, and return flow generated from rural water use that was not simulated in the original model. The revised agricultural pumping is simulated using the agricultural package, which constrains pumping to available groundwater. The use of the agricultural package leads to a more realistic estimation of agricultural water use, with revised agricultural pumping being one-third less than that in the original model. The revised rural pumping is about half of the pumping in the original model because of using detailed parcel data to estimate population density in rural areas instead of coarse census tracts. Overall, average total inflows for water years 2006–10 simulated by the updated model were about 2 percent less than the original model, and the average total updated outflows were nearly 5 percent less than the original model. The updated model was then used to generate stream depletion maps, simulate climate change scenarios during 2019–99, and simulate water rights allocation using the Model for Decision Support in Integrated River Basin Management (MODSIM). The results from simulating eight future climate scenarios indicated either an increase in groundwater storage or no significant change in the next 80 years, along with an increase in recharge, an increase in actual evapotranspiration in six out of eight climate projections, and an increase in surface runoff. The increases in the simulated future groundwater storage, recharge, evapotranspiration, and runoff in most climate projections are mainly driven by the projected increase in precipitation in most of the future climate scenarios. The updated model also was used to test a pilot case study demonstrating water-resource allocation among different users with different water rights using the integrated MODSIM-Groundwater and Surface-Water Flow Model (GSFLOW) platform. The updated SRPHM serves as a valuable tool for analyzing historical and future hydrologic conditions in the Santa Rosa Plain watershed and preparing for future uncertainties.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245121","collaboration":"Prepared in cooperation with the California State Water Resources Control Board and Sonoma Water","programNote":"Water Availability and Use Science Program—Water Resources Mission Area","usgsCitation":"Alzraiee, A., Rich, A., Woolfenden, L., Ryter, D., Triana, E., and Niswonger, R., 2025, Updating and recalibrating the integrated Santa Rosa Plain Hydrologic Model to assess stream depletion and to simulate future climate and management scenarios in Santa Rosa, Sonoma County, California: U.S. Geological Survey Scientific Investigations Report 2024–5121, 57 p., https://doi.org/10.3133/sir20245121.","productDescription":"Report: x, 57 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-155752","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":483079,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1MCCAOM","text":"USGS Data Release","description":"Ryter, D.W., and Alzraiee, A.H., 2025, Santa Rosa Plain integrated hydrological model: simulating the hydrological system of the Santa Rosa Plain, California with analysis of future climate scenarios: U.S. Geological Survey data release, https://doi.org/10.5066/P1MCCAOM.","linkHelpText":"Santa Rosa Plain integrated hydrological model—Simulating the hydrological system of the Santa Rosa Plain, California, with analysis of future climate scenarios"},{"id":483078,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245121/full"},{"id":483077,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5121/images"},{"id":492772,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118477.htm","linkFileType":{"id":5,"text":"html"}},{"id":483076,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5121/sir20245121.XML"},{"id":483075,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5121/sir20245121.pdf","text":"Report","size":"37 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":483074,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5121/coverthb.jpg"}],"country":"United States","state":"California","county":"Sonoma County","city":"Santa Rosa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.91744261022642,\n 38.59807780006835\n ],\n [\n -122.91744261022642,\n 38.246500889944485\n ],\n [\n -122.55883901675656,\n 38.246500889944485\n ],\n [\n -122.55883901675656,\n 38.59807780006835\n ],\n [\n -122.91744261022642,\n 38.59807780006835\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
Freshwater megafishes are among some of the most commercially and ecologically important aquatic organisms yet are disproportionately threatened with range and population reduction. Anthropogenic alterations of rivers influencing migrations are among the most significant causes for these declines. However, migratory fishes do not always respond similarly to movement barriers and thus it is necessary to develop models to predict movements of freshwater migratory fishes in the face of anthropogenic alteration. Predicting movement of freshwater fishes is often investigated using statistical packages. However, empirical studies assessing these packages have led to mixed results, questioning its applicability to all taxa. We argue that spatial, temporal, and environmental attributes are more influential for movement of a migratory megafish, the Alligator Gar (Atractosteus spatula), than the current parameters explored in a globally relevant fish movement model.
This study explored two independent mobile telemetry datasets investigating Alligator Gar movement on the Brazos and Trinity rivers. Environmental associations were investigated to predict Alligator Gar displacement and dispersal using generalized additive models, generalized linear models, and model selection. Leptokurtosis of Alligator Gar populations was also assessed. Predictability of the movement model was tested by comparing observed to model derived stationary and mobile components making up a leptokurtic movement distribution.
Our study suggests that current and antecedent measures of discharge and water temperature are positively correlated with Alligator Gar displacement and dispersal. However, these patterns are only detectable when monthly relocation intervals are explored rather than seasonal scales. Leptokurtosis was observed in both Alligator Gar populations. However, movement was normally distributed (i.e., mesokurtic) under tracking events following high flood pulses. Additionally, predicted Alligator Gar movement was significantly farther under modeled values compared to observed values, in part because the species undergoes cyclical migrations for reproduction that are sensitive to water temperature and discharge.
In conclusion, this study provides an alternative framework to assess the movement patterns of migratory fishes, which could be tested on additional freshwater fishes, and suggests that assessing spatial, environmental, and temporal processes simultaneously are necessary to capture the complexities of fish movement which currently are unavailable for the movement model we investigated.
","language":"English","publisher":"BMC","doi":"10.1186/s40462-025-00544-7","usgsCitation":"Roberts, H.C., Kappen, F., Acre, M.R., Daugherty, D.J., Smith, N.G., and Perkin, J., 2025, Meta-analysis of a megafish: Assessing patterns and predictors of Alligator Gar movement across multiple populations: Movement Ecology, v. 13, no. 1, 15, 18 p., https://doi.org/10.1186/s40462-025-00544-7.","productDescription":"15, 18 p.","ipdsId":"IP-172438","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":488371,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40462-025-00544-7","text":"Publisher Index Page"},{"id":483713,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -96.70591756751243,\n 30.894440659055704\n ],\n [\n -96.70591756751243,\n 29.622760974861365\n ],\n [\n -94.82999949548378,\n 29.622760974861365\n ],\n [\n -94.82999949548378,\n 30.894440659055704\n ],\n [\n -96.70591756751243,\n 30.894440659055704\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"13","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-03-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Roberts, Hayden C.","contributorId":335083,"corporation":false,"usgs":false,"family":"Roberts","given":"Hayden","email":"","middleInitial":"C.","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":931580,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kappen, Florian","contributorId":352518,"corporation":false,"usgs":false,"family":"Kappen","given":"Florian","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":931581,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Acre, Matthew Ross 0000-0002-5417-9523","orcid":"https://orcid.org/0000-0002-5417-9523","contributorId":268034,"corporation":false,"usgs":true,"family":"Acre","given":"Matthew","email":"","middleInitial":"Ross","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":931582,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Daugherty, Daniel J.","contributorId":335084,"corporation":false,"usgs":false,"family":"Daugherty","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":27442,"text":"Texas parks and Wildlife Department","active":true,"usgs":false}],"preferred":false,"id":931583,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smith, Nathan G.","contributorId":268036,"corporation":false,"usgs":false,"family":"Smith","given":"Nathan","email":"","middleInitial":"G.","affiliations":[{"id":55541,"text":"Heart of the Hills Fisheries Science Center","active":true,"usgs":false}],"preferred":false,"id":931584,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Perkin, Joshuah S.","contributorId":238286,"corporation":false,"usgs":false,"family":"Perkin","given":"Joshuah S.","affiliations":[{"id":47708,"text":"Department of Wildlife and Fisheries Sciences, Texas A&M University, College Station, TX","active":true,"usgs":false}],"preferred":false,"id":931585,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70264193,"text":"sir20255004 - 2025 - Assessment of effects of channelization mitigation alternatives of Stoney Brook, Carlton and St. Louis Counties, Minnesota","interactions":[],"lastModifiedDate":"2025-07-23T16:37:17.642571","indexId":"sir20255004","displayToPublicDate":"2025-03-10T08:26:00","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-5004","displayTitle":"Assessment of Effects of Channelization Mitigation Alternatives of Stoney Brook, Carlton and St. Louis Counties, Minnesota","title":"Assessment of effects of channelization mitigation alternatives of Stoney Brook, Carlton and St. Louis Counties, Minnesota","docAbstract":"The U.S. Geological Survey, in cooperation with the Fond du Lac Band of Lake Superior Chippewa (FDLB), studied the effects of channel modification alternatives on lake levels and floodplain inundation in the Stoney Brook watershed in northeast Minnesota. Northern wild rice (Zizania palustris), also referred to as manoomin by the Ojibwe/Chippewa people, is a natural and cultural resource to the FDLB and is sensitive to water levels and rates of water-level changes, particularly during the early stages of growth. Drainage ditches constructed in the early 1900s in the Stoney Brook watershed lowered lake-water levels, caused greater fluctuations in the lakes, and created a loss in wetland coverage. The FDLB is committed to minimizing large fluctuations of the lakes with natural wild rice production in the Stoney Brook watershed and restoring a more natural hydrology to Stoney Brook. The hydrologic response of these lakes and floodplain storage to simulated channel modification alternatives were examined.
Hydrologic and hydraulic models were developed for the watershed and calibrated to historical rainfall events. The models used probabilistic frequency rainfall events of 24-hour duration for 1-, 2-, 5-, and 10-year annual recurrence intervals (100-, 50-, 20-, and 10-percent annual exceedance probability) to simulate watershed management scenarios with existing and alternative conditions. The hydraulic model outputs for peak flows, volume accumulation, water levels, and inundation duration and depths were assessed to quantify the effects of the channel modification alternatives. The channel modification alternatives were simulated with four different terrain conditions: existing conditions, bank spoil breach, original channel reconnection, and original channel reconnection with bank spoil breach. Hydrologic characteristics from six distinct areas were used in the model to evaluate the effects from the channel modification alternatives.
The simulated results of two lakes in which wild rice was planted demonstrated that the lakes would take longer to draw down following an event with the channel modification alternatives compared to existing conditions with little change to peak water-surface elevations. The alternatives provided minor to no increases in flows or conveyances at the downstream reference location at Pine Drive bridge. The restored floodplain locations had increased flows and conveyances for the channel modification alternatives that could be considered substantial when compared to flows with existing conditions. The inundation extent, duration, and water-depth distribution were assessed within selected floodplain areas. Generally, the channel modification alternatives produced increases in the higher depth (3–4 and greater than 4 feet) and duration (10–14 and greater than 14 days) categories for these areas, which may be beneficial to increases in wetland coverage and floodplain storage.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255004","collaboration":"Prepared in cooperation with the Fond du Lac Band of Lake Superior Chippewa","usgsCitation":"Cigrand, C.V., 2025, Assessment of effects of channelization mitigation alternatives of Stoney Brook, Carlton and St. Louis Counties, Minnesota: U.S. Geological Survey Scientific Investigations Report 2025–5004, 44 p., https://doi.org/10.3133/sir20255004.","productDescription":"Report: ix, 44 p.; Data Release; Dataset","numberOfPages":"58","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-132433","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":483061,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the Nation"},{"id":483062,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13KFQSL","text":"USGS data release","linkHelpText":"Archive of hydraulic and hydrologic models used in the Stoney Brook watershed in Carlton and St. Louis Counties, Minnesota, 2008–2024"},{"id":483057,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5004/coverthb.jpg"},{"id":483058,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5004/sir20255004.pdf","text":"Report","size":"9.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025–5004"},{"id":483059,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5004/sir20255004.XML"},{"id":483060,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5004/images/"},{"id":483063,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255004/full"},{"id":492770,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118476.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Minnesota","county":"Carlton County, St. Louis County","otherGeospatial":"Stoney Brook watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -92.4667,\n 46.8667\n ],\n [\n -92.8,\n 46.8667\n ],\n [\n -92.8,\n 46.633\n ],\n [\n -92.4667,\n 46.633\n ],\n [\n -92.4667,\n 46.8667\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
400 South Clinton Street, Suite 269
Iowa City, IA 52240
In the United States, wildlife managers are entrusted with preserving culturally and economically important ungulate populations in the face of the ongoing spread of chronic wasting disease (CWD). The U.S. Fish and Wildlife Service established an adaptive management plan to reduce the reliance of elk (Cervus canadensis) on supplemental winter feeding on the National Elk Refuge. The end goal of reducing the unnaturally high aggregation of elk during the winter is to mitigate the threat of disease outbreaks and to meet the objectives of sustainable populations of elk on the refuge. In this case study, we evaluated 6 years (2017–2022) of data from GPS-collared elk to determine the efficacy of shortening the length of the annual feeding period on the refuge to reduce elk aggregation. We measured aggregation using proximity rates, based on pairwise interactions over time, in both raw form as an index as well as predicted proximity as a function of other abiotic influences. We created a new R package, wildagg, to help with the process of computing the metrics from our study and to increase reproducibility in the future. Aggregation declined in years with less feeding on the refuge according to raw aggregation metrics when examined in isolation and dependent on the baseline feeding year used for comparison. However, accounting for abiotic factors while modeling proximity rates suggested in some years the decision to shorten the feeding period had less influence on aggregation than predicted. Our results underscore the complexity of measuring management outcomes and the usefulness of multiple approaches to evaluation.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/wsb.1574","usgsCitation":"Janousek, W.M., Cole, E., Dewey, S.R., and Graves, T., 2025, Informing adaptive management to reduce ungulate aggregations: A case study involving winter feeding of elk: Wildlife Society Bulletin, v. 49, no. 1, e1574, 12 p., https://doi.org/10.1002/wsb.1574.","productDescription":"e1574, 12 p.","ipdsId":"IP-153310","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":488309,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/wsb.1574","text":"Publisher Index Page"},{"id":483356,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"National Elk Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -110.7137912687953,\n 43.57693522181455\n ],\n [\n -110.7137912687953,\n 43.5282857345309\n ],\n [\n -110.63727861874892,\n 43.5282857345309\n ],\n [\n -110.63727861874892,\n 43.57693522181455\n ],\n [\n -110.7137912687953,\n 43.57693522181455\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"49","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-03-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Janousek, William Michael 0000-0003-3978-1775","orcid":"https://orcid.org/0000-0003-3978-1775","contributorId":237980,"corporation":false,"usgs":true,"family":"Janousek","given":"William","email":"","middleInitial":"Michael","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":930720,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cole, Eric K. 0000-0002-2229-5853","orcid":"https://orcid.org/0000-0002-2229-5853","contributorId":145755,"corporation":false,"usgs":false,"family":"Cole","given":"Eric K.","affiliations":[{"id":16228,"text":"U.S. Fish and Wildlife Service, National Elk Refuge, PO Box 510, Jackson, WY 83001 USA","active":true,"usgs":false}],"preferred":false,"id":930721,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dewey, Sarah R.","contributorId":264423,"corporation":false,"usgs":false,"family":"Dewey","given":"Sarah","email":"","middleInitial":"R.","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":930722,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Graves, Tabitha A. 0000-0001-5145-2400","orcid":"https://orcid.org/0000-0001-5145-2400","contributorId":202084,"corporation":false,"usgs":true,"family":"Graves","given":"Tabitha A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":930723,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70269684,"text":"70269684 - 2025 - Characterizing the scale of regional landslide triggering from storm hydrometeorology","interactions":[],"lastModifiedDate":"2025-07-30T14:49:56.57927","indexId":"70269684","displayToPublicDate":"2025-03-10T07:42:20","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17114,"text":"Natural Hazards and Earth Systems Sciences (NHESS)","active":true,"publicationSubtype":{"id":10}},"title":"Characterizing the scale of regional landslide triggering from storm hydrometeorology","docAbstract":"Rainfall strongly affects landslide triggering; however, understanding how storm characteristics relate to the severity of landslides at the regional scale has thus far remained unclear, despite the societal benefits that would result from defining this relationship. As mapped landslide inventories typically cover a small region relative to a storm system, here we develop a dimensionless index for landslide-inducing rainfall, A*, based on extremes of modeled soil water relative to its local climatology. We calibrate A* using four landslide inventories, comprising over 11 000 individual landslides over four unique storm events, and find that a common threshold can be applied to estimate regional shallow-landslide-triggering potential across diverse climatic regimes in California (USA). We then use the spatial distribution of A*, along with topography, to calculate the landslide potential area (LPA) for nine landslide-inducing storm events over the past 20 years, and we test whether atmospheric metrics describing the strength of landfalling storms, such as integrated water vapor transport, correlate with the magnitude of hazardous landslide-inducing rainfall. We find that although the events with the largest LPA do occur during exceptional atmospheric river (AR) storms, the strength of landfalling atmospheric rivers does not scale neatly with landslide potential area, and even exceptionally strong ARs may yield minimal landslide impacts. Other factors, such as antecedent soil moisture driven by storm frequency and mesoscale precipitation features within storms, are instead more likely to dictate the patterns of landslide-generating rainfall throughout the state.
","language":"English","publisher":"European Geosciences Union","doi":"10.5194/nhess-25-1037-2025","usgsCitation":"Perkins, J.P., Oakley, N.S., Collins, B.D., Corbett, S.C., and Burgess, W.P., 2025, Characterizing the scale of regional landslide triggering from storm hydrometeorology: Natural Hazards and Earth Systems Sciences (NHESS), v. 25, no. 3, p. 1037-1056, https://doi.org/10.5194/nhess-25-1037-2025.","productDescription":"20 p.","startPage":"1037","endPage":"1056","ipdsId":"IP-144518","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":493301,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/nhess-25-1037-2025","text":"Publisher Index Page"},{"id":493184,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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For long-lived animals and those with boom-and-bust life histories, perspective across time contributes to discerning temporal trends in occupancy and persistence, and potentially in identifying mechanisms affecting those parameters. Long-term data are particularly useful in protected areas to quantify indicators of change that may be less obvious or occur more slowly. We used long-term amphibian data from Rocky Mountain National Park (RMNP) in a Bayesian occupancy modeling framework to estimate changes in occupancy, colonization, and persistence of amphibians over three decades and to explore the effects of climate, landscape change, and visitor use as mechanisms behind observed changes. Our results indicate that colonization and persistence are low and/or declining for Pseudacris maculata, Lithobates sylvaticus, and Ambystoma mavortium, and that occupied catchments are increasingly isolated. We found visitor use to have a consistently negative effect on occupancy and persistence of amphibians in RMNP, and that all species are more likely to occupy catchments with more complex habitat and a higher proportion of wetlands. While these results are sobering, they also provide a way forward where mitigation efforts can target identified drivers of change.
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study of the U.S. Virgin Islands","docAbstract":"Reducing the potential for loss of life from tsunamis is challenging on islands located in complex seismic regions given the multiple sources that surround islands, differences among islands in the amount of time needed to evacuate before wave arrival, and the high number of residents, employees, and tourists in tsunami-hazard zones. We examine variations in population vulnerability in island communities to multiple tsunami threats and use the United States territory of the U.S. Virgin Islands (USVI), including St. Thomas Island, St. John Island, and St. Croix Island, as our case study. We estimate the tsunami-hazard exposure of residents, employees, and cruise-ship passengers on vessels docking at USVI maritime facilities, as well as model pedestrian travel times out of inundation zones for 13 credible tsunami scenarios. Results indicate that the threat to life safety in USVI posed by tsunamis is not equal among the three islands, both in terms of the magnitude of people in hazard zones and the amount of time available to evacuate for the various scenarios. The number of employees and cruise-ship passengers in tsunami-hazard zones is orders of magnitude higher than the number of residents, suggesting that risk assessments that only account for residents are under-estimating threats to life safety from tsunamis. Finally, reducing departure delays has a greater impact than increasing pedestrian travel speeds on reducing the number of people that may have insufficient time to evacuate hazard zones before wave arrival.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ijdrr.2025.105289","usgsCitation":"Wood, N.J., Peters, J., and Moore, C., 2025, Population vulnerability of residents, employees, and cruise-ship passengers to tsunami hazards of islands in complex seismic regions: A case study of the U.S. Virgin Islands: International Journal of Disaster Risk Reduction, v. 119, 105289, 15 p., https://doi.org/10.1016/j.ijdrr.2025.105289.","productDescription":"105289, 15 p.","ipdsId":"IP-172610","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":487887,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ijdrr.2025.105289","text":"Publisher Index Page"},{"id":482556,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"U.S. Virgin Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -65.10271729681736,\n 18.453483664421626\n ],\n [\n -65.10271729681736,\n 18.217661626050017\n ],\n [\n -64.66350061715465,\n 18.217661626050017\n ],\n [\n -64.66350061715465,\n 18.453483664421626\n ],\n [\n -65.10271729681736,\n 18.453483664421626\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"119","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wood, Nathan J. 0000-0002-6060-9729 nwood@usgs.gov","orcid":"https://orcid.org/0000-0002-6060-9729","contributorId":3347,"corporation":false,"usgs":true,"family":"Wood","given":"Nathan","email":"nwood@usgs.gov","middleInitial":"J.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":928795,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peters, Jeff 0000-0003-4312-0590 jpeters@usgs.gov","orcid":"https://orcid.org/0000-0003-4312-0590","contributorId":4711,"corporation":false,"usgs":true,"family":"Peters","given":"Jeff","email":"jpeters@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":928796,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moore, Christopher","contributorId":202056,"corporation":false,"usgs":false,"family":"Moore","given":"Christopher","affiliations":[{"id":33877,"text":"CNTS","active":true,"usgs":false}],"preferred":false,"id":928797,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70271427,"text":"70271427 - 2025 - UAV-derived models of vegetation characteristics do not transfer to extreme drought and wet conditions across a northern Arizona landscape","interactions":[],"lastModifiedDate":"2025-09-15T13:19:09.227483","indexId":"70271427","displayToPublicDate":"2025-03-07T07:46:19","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"UAV-derived models of vegetation characteristics do not transfer to extreme drought and wet conditions across a northern Arizona landscape","docAbstract":"Context
Shifts in precipitation regimes due to climate change are significantly impacting dryland ecosystems, including vegetation composition and structure. Unoccupied aerial vehicles (UAVs) are widely used to monitor vegetation, but whether models built to predict changes in these characteristics are robust under extreme precipitation regimes is unclear.
Objectives
We aimed to predict key vegetation characteristics under three precipitation regimes (ambient, drought, and water addition) and assess model performance across these moisture conditions. We also evaluated how models built under ambient conditions predicted vegetation characteristics under extreme precipitation regimes.
Methods
UAV surveys were conducted at five sites subject to long-term precipitation manipulation along an elevation gradient in northern Arizona, United States (U.S.). Twenty-one vegetation indices and point cloud data from the UAV imagery were used to develop models to predict vegetation structure and composition characteristics. Model performance and transferability were assessed via error and directional bias within each treatment (i.e., in situ) and from ambient to precipitation treatments (i.e., model transfer).
Results
UAV-based models accurately measured vegetation characteristics across all regimes, but maximum height showed significantly higher error under drought conditions. Models developed under ambient precipitation and applied to extreme precipitation treatments exhibited significant differences in the error and directional bias, indicating they may not be suitable under climate change.
Conclusions
UAV-based models are effective for monitoring vegetation characteristics but may lose accuracy under extreme precipitation regimes expected under climate change. This study emphasizes the need to improve model transferability and suggests refining landscape monitoring approaches to consider extreme changes in precipitation and associated vegetation responses.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s10980-025-02064-6","usgsCitation":"Blackburn, R.C., Allington, G.R., Motzer, N., Munson, S.M., and Huang, Q., 2025, UAV-derived models of vegetation characteristics do not transfer to extreme drought and wet conditions across a northern Arizona landscape: Landscape Ecology, v. 40, 59, 17 p., https://doi.org/10.1007/s10980-025-02064-6.","productDescription":"59, 17 p.","ipdsId":"IP-171149","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":496414,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10980-025-02064-6","text":"Publisher Index Page"},{"id":495407,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"northern Arizona","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -112.00885151827934,\n 35.49924603762916\n ],\n [\n -112.00885151827934,\n 34.90066874429827\n ],\n [\n -111.00177522680366,\n 34.90066874429827\n ],\n [\n -111.00177522680366,\n 35.49924603762916\n ],\n [\n -112.00885151827934,\n 35.49924603762916\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"40","noUsgsAuthors":false,"publicationDate":"2025-03-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Blackburn, Ryan C. 0000-0002-2952-0865","orcid":"https://orcid.org/0000-0002-2952-0865","contributorId":361388,"corporation":false,"usgs":false,"family":"Blackburn","given":"Ryan","middleInitial":"C.","affiliations":[{"id":86267,"text":"Smithsonian Conservation Biology Institute, Front Royal, Virginia, USA","active":true,"usgs":false}],"preferred":false,"id":948728,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Allington, Ginger R. H. 0000-0003-0446-0576","orcid":"https://orcid.org/0000-0003-0446-0576","contributorId":213452,"corporation":false,"usgs":false,"family":"Allington","given":"Ginger","email":"","middleInitial":"R. H.","affiliations":[{"id":34680,"text":"George Washington University","active":true,"usgs":false}],"preferred":false,"id":948729,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Motzer, Nicole","contributorId":361389,"corporation":false,"usgs":false,"family":"Motzer","given":"Nicole","affiliations":[{"id":86268,"text":"Office of Research Development, Montana State University, Bozeman, MT, USA","active":true,"usgs":false}],"preferred":false,"id":948730,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":220026,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":948731,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Huang, Qiongyu","contributorId":298920,"corporation":false,"usgs":false,"family":"Huang","given":"Qiongyu","affiliations":[{"id":37784,"text":"Smithsonian Conservation Biology Institute","active":true,"usgs":false}],"preferred":false,"id":948732,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70264110,"text":"70264110 - 2025 - Letter to Editor regarding “Potential impact of the 2023 Lahaina wildfire on the marine environment: Modeling the transport of ash-laden benzo[a]pyrene and pentachlorophenol” by Downs et al. (2024) https://doi.org/10.1016/j.scitotenv.2024.176346","interactions":[],"lastModifiedDate":"2025-03-07T14:06:47.659517","indexId":"70264110","displayToPublicDate":"2025-03-05T10:05:06","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Letter to Editor regarding “Potential impact of the 2023 Lahaina wildfire on the marine environment: Modeling the transport of ash-laden benzo[a]pyrene and pentachlorophenol” by Downs et al. (2024) https://doi.org/10.1016/j.scitotenv.2024.176346","docAbstract":"No abstract available.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2025.178965","usgsCitation":"Storlazzi, C.D., Takesue, R.K., and Hendrix, A., 2025, Letter to Editor regarding “Potential impact of the 2023 Lahaina wildfire on the marine environment: Modeling the transport of ash-laden benzo[a]pyrene and pentachlorophenol” by Downs et al. (2024) https://doi.org/10.1016/j.scitotenv.2024.176346: Science of the Total Environment, v. 970, 178965, 3 p., https://doi.org/10.1016/j.scitotenv.2025.178965.","productDescription":"178965, 3 p.","ipdsId":"IP-172655","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":482976,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"970","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Storlazzi, Curt D. 0000-0001-8057-4490","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":213610,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":929835,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Takesue, Renee K. 0000-0003-1205-0825 rtakesue@usgs.gov","orcid":"https://orcid.org/0000-0003-1205-0825","contributorId":2159,"corporation":false,"usgs":true,"family":"Takesue","given":"Renee","email":"rtakesue@usgs.gov","middleInitial":"K.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":929836,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hendrix, Alicia 0000-0003-3897-1788","orcid":"https://orcid.org/0000-0003-3897-1788","contributorId":351988,"corporation":false,"usgs":false,"family":"Hendrix","given":"Alicia","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":929837,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70264020,"text":"sir20235064E - 2025 - Peak streamflow trends in Minnesota and their relation to changes in climate, water years 1921–2020","interactions":[{"subject":{"id":70264020,"text":"sir20235064E - 2025 - Peak streamflow trends in Minnesota and their relation to changes in climate, water years 1921–2020","indexId":"sir20235064E","publicationYear":"2025","noYear":false,"chapter":"E","displayTitle":"Peak Streamflow Trends in Minnesota and Their Relation to Changes in Climate, Water Years 1921–2020","title":"Peak streamflow trends in Minnesota and their relation to changes in climate, water years 1921–2020"},"predicate":"IS_PART_OF","object":{"id":70251152,"text":"sir20235064 - 2024 - Peak streamflow trends and their relation to changes in climate in Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin","indexId":"sir20235064","publicationYear":"2024","noYear":false,"title":"Peak streamflow trends and their relation to changes in climate in Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin"},"id":1}],"isPartOf":{"id":70251152,"text":"sir20235064 - 2024 - Peak streamflow trends and their relation to changes in climate in Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin","indexId":"sir20235064","publicationYear":"2024","noYear":false,"title":"Peak streamflow trends and their relation to changes in climate in Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin"},"lastModifiedDate":"2025-07-21T18:36:06.830058","indexId":"sir20235064E","displayToPublicDate":"2025-03-04T14:51:20","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5064","chapter":"E","displayTitle":"Peak Streamflow Trends in Minnesota and Their Relation to Changes in Climate, Water Years 1921–2020","title":"Peak streamflow trends in Minnesota and their relation to changes in climate, water years 1921–2020","docAbstract":"This report chapter summarizes the effect of hydroclimatic variability of annual peak streamflow in Minnesota and is part of a larger U.S. Geological Survey multistate study to assess potential nonstationarity in annual peak streamflows across the Midwest. Spatial and temporal patterns were examined for nonstationarity in annual peak streamflow, daily mean streamflow, and modeled climatic data in four analysis periods: (1) a 100-year period, 1921–2020; (2) a 75-year period, 1946–2020; (3) a 50-year period, 1971–2020; and (4) a 30-year period, 1991–2020. Upward trends in annual peak streamflow were detected in northwest to southeast and north to south directions. Downward trends in annual peak streamflow were detected in northeastern and southeastern areas. Trends in peak-flow timing indicated that peak streamflows are being detected later in the water year (the period from October 1 to September 30 designated by the year in which it ends) mainly in the southern areas and earlier in the water year mainly in the northern areas.
Changes in climate data point to wetter conditions in southern areas and drier conditions in northern areas. Annual precipitation was determined to be increasing in a northwest to southeast direction and in the east. In contrast, some areas in the north and northwest indicated decreasing annual precipitation. Annual snowfall was determined to be decreasing except in the extreme northeast, where annual snowfall was determined to be increasing. Decreases in annual potential evapotranspiration were detected in the south, and increases were detected in the north. Annual soil moisture increased in southern areas and decreased in northern and eastern areas. The potential spatial and temporal nonstationarity violations detected in the four analysis periods have important implications for flood-frequency analysis and point to the need for guidance on how to incorporate nonstationarities into future flood-frequency analysis in Minnesota.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235064E","collaboration":"Prepared in cooperation with the Illinois Department of Transportation, Iowa Department of Transportation, Michigan Department of Transportation, Minnesota Department of Transportation, Missouri Department of Transportation, Montana Department of Natural Resources and Conservation, North Dakota Department of Water Resources, South Dakota Department of Transportation, and Wisconsin Department of Transportation","usgsCitation":"Williams-Sether, T., and Sanocki, C., 2025, Peak streamflow trends in Minnesota and their relation to changes in climate, water years 1921–2020, chap. 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\"}}]}","contact":"Director, Dakota Water Science Center
U.S. Geological Survey
821 East Interstate Avenue, Bismarck, ND 58503
1608 Mountain View Road, Rapid City, SD 57702
Standardized guidelines for completing flood-flow frequency analyses are presented in a U.S. Geological Survey Techniques and Methods report known as Bulletin 17C, https://doi.org/10.3133/tm4B5. In recent decades (since about 2000), a better understanding of long-term climatic persistence (periods of clustered floods or droughts, or wet or dry periods) and concerns about potential climate change and land-use change have caused a reexamination of the stationarity assumptions underlying methods in Bulletin 17C. Bulletin 17C does not offer guidance on incorporating nonstationarities and further identifies a need for flood-frequency studies that incorporate changing climate or basin characteristics. As part of that reexamination, a study of annual peak streamflow (peak flow) has begun in the Midwest. This chapter of the study summarizes how hydroclimatic variability affects peak flows in North Dakota.
In this analysis of peak flow, daily streamflow, and climate metrics, four periods were selected: (1) a 100-year period, 1921–2020; (2) a 75-year period, 1946–2020; (3) a 50-year period, 1971–2020; and (4) a 30-year period, 1991–2020. Output from a monthly water-balance model was used for the climate data. Statistical analysis of peak flow consisted of evaluations of autocorrelation, trends, and change points and was augmented with analyses of seasonality and daily streamflow. The long-term pattern of decreasing peak flow in the west and increasing peak flow in the east is a pattern of opposing signals on either side of the 100th meridian. Analyses indicate that a key factor in changing hydroclimatology is the increase in fall precipitation. The trends in soil moisture closely match the trends in annual precipitation. Nonstationary flood-frequency analysis necessitates detailed exploratory data analysis and additional data and information about climate, land use, and other factors. This study provides extensive exploratory analysis for peak flow, daily streamflow, and climate data for North Dakota, setting the stage for informed nonstationary flood-frequency analysis.
Director, Dakota Water Science Center
U.S. Geological Survey
821 East Interstate Avenue, Bismarck, ND 58503
1608 Mountain View Road, Rapid City, SD 57702