Flooding due to storm surge can propagate through coastal regions to threaten the built and natural environments. This propagation is controlled by geographic features of varying scales, from the largest oceans to the smallest marsh channels and sandy dunes. Numerical models to predict coastal flooding have been improved via the use of subgrid corrections, which use information about the smallest-scale flow controls to provide corrections to coarser scale grids. Although previous studies have demonstrated the benefits of subgrid models, especially how coarser models can be more efficient without a trade-off in accuracy, this study systematically investigates subgrid corrections in storm surge models across large domains. Here, we apply the widely used ADVanced CIRCulation (ADCIRC) storm surge model with revised subgrid corrections to develop guidance for resolution of coastal regions. Recent hurricanes in the South Atlantic Bight are simulated with five models, each with varying resolution of coastal islands, estuaries, rivers, and floodplains. Model performance is quantified via comparisons with observed data and high-resolution simulations. Clear degradation is observed in the subgrid model performance as minimum mesh resolution becomes coarser than the width of channels conveying flow or the barrier islands blocking flow. Therefore, subgrid model mesh resolution should account for spatial scales of local flow pathways and barrier islands to maintain proper model mass and momentum transfer. However, with subgrid modeling this can be done at much coarser (and thus computationally faster) resolutions than with conventional models.
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Most orogenic systems are found along the Cordilleran orogen, stretching from California northwards into Alaska, whereas most Coeur d’Alene-type systems occur in the Proterozoic Belt Basin in Idaho and Montana. Although the deposit types in these systems are exploited for precious and base metals, potential exists for the production of critical minerals necessary for current (2025) societal needs in the United States. Publicly available geochemical data compiled for these mineral systems, coupled with mineralogical characteristics, indicate that several critical minerals could potentially be recovered from unmined resources and processed mine waste: arsenic, antimony, tellurium, cobalt, and tungsten from orogenic gold deposits and zinc, antimony, arsenic, and manganese from Coeur d’Alene-type systems. These critical minerals reside primarily in arsenopyrite (arsenic), scheelite (tungsten), siderite (manganese), sphalerite (zinc), tetrahedrite (antimony and arsenic), stibnite (antimony), and telluride (tellurium) minerals.
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U.S. Geological Survey
Box 25046, Mail Stop 973
Denver, CO 80225
Monitoring populations is challenging for cryptic species with seasonal life cycles, where data from multiple field techniques are commonly collected and analyzed as multiple lines of evidence. Data integration can provide comprehensive inferences while improving accuracy, precision, and scope but faces challenges in modeling misaligned resolutions and observational uncertainties. We developed a multi-scale, integrated species distribution model (MS-iSDM) for North American bats to combine data across monitoring types and seasons using joint likelihood methods, observational models with false-negatives and false-positives, and seasonal migratory connectivity. We applied this model to 11 years of data for an imperiled bat species (tricolored bat, Perimyotis subflavus). Relative abundance and occupancy were linked with multi-scale predictors, revealing clear patterns of population declines, but with important differences in spatial trends (abundance: corresponded with white-nose syndrome impacts, occupancy: at the range periphery) and overall severity (abundance: -74.8%, 95% CRI: -79.7% to -69.3%; occupancy: -35.5%, 95% CRI: -41.1% to -30.2%). The asynchrony between occupancy trends and population impacts was explained as an emergent pattern of spatiotemporal variation in abundance in the integrated distribution model. Compared to multiple lines of evidence, the integrated model provided consensus-estimates, increased precision and spatiotemporal scope, and strengthened evidence of population declines.
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Aquatic monitoring of Se is ongoing to assess potential effects; however, exposure to terrestrial, aquatic-dependent wildlife has not been investigated. Tree swallows are a targeted receptor for evaluation of potential Se-related effects as this species is a mid-level consumer with aquatic-terrestrial food web linkages, is sensitive to Se, and reliably uses nest boxes. The goals of this project were to identify tree swallow demographics and metal(loid) concentrations to assess potential species and ecosystem-level effects within the Kootenai River basin study area. During 2022 and 2023, a total of 98 nest boxes were monitored across ~ 120 km of shoreline; 60 eggs were collected. Egg metal(loid) concentrations, including Se, were below levels identified to cause reproductive effects in avian species. However, nest box occupancy increased with distance from the US/Canada border (P < 0.001; R2 = 0.83), and Se concentrations were significantly higher (P = 0.014) in 2023 than 2022 (3.2 (3.0–3.4) and 2.8 (2.6–3.1), respectively; geometric mean, 95% CI; mg/kg, dw). With ongoing mining operations in the drainage basin of the Elk River, these results suggest that long-term monitoring of tree swallows will support assessment of spatiotemporal metal(loid) trends. Additional data, including tree swallow foraging patterns, will allow evaluation of differences in nest box occupancy and metal(loid) concentrations in the Kootenai River basin.
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However, for fuels treatment implementation to be successful, it must comply with regulatory and scientific standards and be supported by local communities, as lack of acceptance can lead to alterations, delays, or abandonment. To foster support, public land managers can engage directly with residents in communities near treatment areas through various communication channels or engage indirectly through trusted local partners. This research uses paired household survey and observed parcel-level wildfire risk assessment data to investigate wildfire risk information sources' role in the acceptability of fuels treatment approaches on public lands near select WUI communities in the Western United States. We find that information deemed useful from sources is often positively correlated with acceptability, while information deemed not useful is sometimes negatively correlated. Local sources of information tend to be widely received, perceived as useful, and have positive correlations with acceptability, while nonlocal sources vary in their receipt, perceived usefulness, and correlations with acceptability. Public land managers, particularly those from national organizations, may benefit from leveraging and aligning messaging with trusted local partners. Developing fuels treatment plans that consider existing local sentiments may facilitate public trust in managers and acceptability of treatments.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.forpol.2025.103537","usgsCitation":"Wallace, K., Brenkert-Smith, H., Champ, P.A., Meldrum, J., Webster, G., Taniguchi, C., Goolsby, J.B., Donovan, C., Wagner, C., Barth, C.M., Kuehn, J., and Wittenbrink, S., 2025, Wildfire risk information sources and the acceptability of fuels treatments near select WUI communities in the Western United States: Journal of Forest Policy and Economics, v. 176, 103537, 19 p., https://doi.org/10.1016/j.forpol.2025.103537.","productDescription":"103537, 19 p.","ipdsId":"IP-169635","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":490169,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.forpol.2025.103537","text":"Publisher Index Page"},{"id":489463,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, 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In response, a variety of water quality improvement projects and regulations have been implemented in recent decades. A recent study showed that, from water years 2003 to 2021, concentrations of total phosphorus at the mouth of the Boise River near Parma decreased by 60 percent, indicating the success of the improvement projects and progress towards reaching the regulatory target. However, although the progress of the system as a whole towards reaching the total phosphorus target is well documented, quantifying contributions and trends in total phosphorus loading from individual tributaries and upstream mainstem locations is needed. Similarly, tributary contributions and trends of other constituents of concern are unknown or have not been evaluated in a decade. To evaluate the success of past water-quality improvement efforts and help prioritize future investments, this study characterized spatial and seasonal patterns in concentrations and loads of suspended sediment, total phosphorus, orthophosphate, total nitrogen, nitrate plus nitrite, Escherichia coli bacteria, and periphyton chlorophyll a (chl-a) at three mainstem and seven tributary sites of the lower Boise River during water years 2019–2023. For sites and constituents with adequate data, temporal trends over a 15-year and 30-year period were also evaluated.
Recent (in other words, water years 2019–2023) concentrations and loads of suspended sediment and total phosphorus were typically greatest during the irrigation season and often exceeded total maximum daily load targets. However, concentrations and loads of suspended sediment, total phosphorus, and orthophosphate have decreased over the past 15 to 30 years at many sites. In contrast, concentrations of total nitrogen and nitrate plus nitrite showed increasing trends at the Boise River near Parma, likely reflecting the effects of regional changes in agricultural practices in recent decades. Periphyton chl-a concentrations during October–November were highly likely increasing over the 30-year period at Boise River at Eckert, but were uncertain at Middleton and Parma. At Boise River at Middleton, periphyton chl-a concentrations exceeded the total maximum daily load target of 150 milligrams per square meter in 75 percent of samples during water years 2019–2023. Results therefore demonstrate that past watershed improvement efforts have been largely effective at reducing concentrations and loads of suspended sediment, total phosphorus, and orthophosphate in the lower Boise River watershed, but different strategies may be needed to reduce concentrations and loads of total nitrogen, nitrate plus nitrite, Escherichia coli, and periphyton chl-a.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255033","collaboration":"Prepared in cooperation with the Lower Boise Watershed Council","usgsCitation":"Baldwin, A.K., and King, T.V., 2025, Spatial patterns and temporal trends in water quality in Idaho’s lower Boise River and its tributaries, 1994–2023: U.S. Geological Survey Scientific Investigations Report 2025–5033, 46 p., https://doi.org/10.3133/sir20255033.","productDescription":"Report viii, 45 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-146130","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":499042,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118592.htm","linkFileType":{"id":5,"text":"html"}},{"id":489233,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5033/sir20255033.XML"},{"id":489232,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5033/images"},{"id":489231,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13VWHMF","text":"USGS data release","description":"USGS data release","linkHelpText":"Water quality concentrations and discharge in the lower Boise River and select tributaries, southwestern Idaho, 1994–2023"},{"id":489230,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255033/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5033"},{"id":489228,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5033/coverthb.jpg"},{"id":489229,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5033/sir20255033.pdf","text":"Report","size":"7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5033"}],"country":"United States","state":"Idaho","otherGeospatial":"Lower Boise River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.03387029585451,\n 43.87149726119398\n ],\n [\n -117.03387029585451,\n 43.477324089144474\n ],\n [\n -116.06261864282659,\n 43.477324089144474\n ],\n [\n -116.06261864282659,\n 43.87149726119398\n ],\n [\n -117.03387029585451,\n 43.87149726119398\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Rd
Boise, Idaho 83702-4520
In cooperation with the Minnesota Department of Natural Resources, the U.S. Geological Survey monitored 98 common loon (Gavia immer) focal territories and an additional 37 nonfocal territories in 2024 across 53 study lakes in Minnesota. Focal territories were those territories from which study inferences will be made, whereas nonfocal territories were observed to monitor common loon dynamics in territories adjacent to focal territories. In collaboration with lake associations and private citizens, we deployed 44 artificial nesting platforms within 44 treatment territories, and the remaining 54 focal territories were controls. We completed territorial surveys from April 29 to August 9, 2024, to evaluate occupancy, nest success, and chick survival. We attempted to visit each territory once a week. At least one nest attempt was observed in 41 of 54 control territories. Precisely one nest attempt was observed in 30 control territories, two nest attempts (first attempts failed) were observed in 9 control territories, and three nest attempts (first and second attempts failed) were observed in 2 control territories. At least one nest attempt was observed in 33 of 44 treatment territories. Precisely one nest attempt was observed in 25 treatment territories, two nest attempts (first attempts failed) were observed in 7 treatment territories, and three nest attempts (first and second attempts failed) were observed in 1 treatment territory. In treatment territories, 8 nests were on an artificial nesting platform; the remaining nest locations were natural. Chicks or other evidence of hatching were observed in 26 of 54 (48.1 percent) control territories and 21 of 44 (47.7 percent) treatment territories, with 7 of those successful treatment nests on an artificial nesting platform. This report includes no formal analysis, but we plan to analyze data after collection of all field data in subsequent years.
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\"}}]}","contact":"Director, Upper Midwest Environmental Sciences Center
U.S. Geological Survey
2630 Fanta Reed Road
La Crosse, Wisconsin 54603
The glacial deposits underlying southeastern Michigan, northeastern Indiana, and northwestern Ohio are a substantial source of water to communities, agriculture, and industry in the region. Previous efforts to characterize aquifer materials in the area cited a need for additional information about the underlying hydrogeologic characteristics and related groundwater availability as well as improved mapping of the extent and properties of the glacial deposits.
Recent U.S. Geological Survey multi-State compilations of water-well drilling records have greatly increased access to high-resolution geologic data, particularly in glacial depositional environments. This study by the U.S. Geological Survey, in cooperation with the Ohio Environmental Protection Agency, uses processed data from the State-managed collections of well records to characterize the glacial deposits in the study area using two methods. The first method creates two-dimensional maps of basic hydrogeologic information commonly required for assessments of groundwater availability, including (1) total thickness of glacial deposits, (2) total thickness of coarse-grained deposits, (3) specific-capacity-based transmissivity and hydraulic conductivity, and (4) texture-based estimated equivalent horizontal and vertical hydraulic conductivity and transmissivity. The second method builds a hydrogeologic framework of the complex glacial aquifer through construction of a volumetric geologic model by using three-dimensional kriging.
Results of the volumetric model indicate that aquifer materials are primarily concentrated in the western parts of the study area near the Indiana-Ohio border. Coarse-grained sediments are also present as surficial deposits in the north of the study area where intermixing glacial advances created complex distributions of unconsolidated deposits. Two-dimensional maps of hydrogeologic properties support the volumetric model, showing thicknesses of coarse-grained deposits that reach up to 250 feet in the western sections of the study area and progressively thin to near absence in the east. Visualization of the aquifer materials with a volumetric model generally shows a highly discontinuous distribution of coarse- and fine-grained materials, with no clearly defined boundaries to delineate the extent of the aquifer. Comparisons of cross sections derived from the volumetric model with existing published maps support previous near-surface hydrogeologic interpretations while filling gaps where data are sparse, particularly in deeper parts of the aquifer. Both the two-dimensional maps and the volumetric model provide data that can directly inform assessments of groundwater availability, in addition to having future applications to studies of groundwater flow and transport.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255008","collaboration":"Prepared in cooperation with the Ohio Environmental Protection Agency","usgsCitation":"Riddle, A.D., Arihood, L.D., Naylor, S., and Lampe, D.C., 2025, Hydrogeologic mapping and three-dimensional geologic modeling of glacial deposits in a multicounty area of southeastern Michigan, northeastern Indiana, and northwestern Ohio: U.S. Geological Survey Scientific Investigations Report 2025–5008, 47 p., https://doi.org/10.3133/sir20255008.","productDescription":"Report: viii, 47 p.; Data Release","numberOfPages":"47","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-146138","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":486276,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5008/images/"},{"id":486275,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5008/sir20255008.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2025-5008 XML"},{"id":486274,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255008/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5008 HTML"},{"id":486273,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5008/sir20255008.pdf","text":"Report","size":"13.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5008 PDF"},{"id":486272,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5008/coverthb.jpg"},{"id":499040,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118589.htm","linkFileType":{"id":5,"text":"html"}},{"id":486277,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13BO3GJ","text":"USGS data release","linkHelpText":"Hydrogeologic framework of the glacial deposits in a multicounty area of southeastern Michigan, northeastern Indiana, and northwestern Ohio"}],"country":"United States","state":"Indiana, Michigan, Ohio","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -85.45494559947987,\n 42.39763689085959\n ],\n [\n -85.45494559947987,\n 40.651853498464675\n ],\n [\n -83.24314510969089,\n 40.651853498464675\n ],\n [\n -83.24314510969089,\n 42.39763689085959\n ],\n [\n -85.45494559947987,\n 42.39763689085959\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Ohio-Kentucky-Indiana Water Science Center
U.S. Geological Survey
6460 Busch Blvd, Suite 100
Columbus, OH 43229
Managing water resources in semiarid watersheds is challenging due to limited supply and uncertain future climate conditions. This paper examines the impact of future climate changes on an urban watershed in southern California using an integrated hydrologic model. GSFLOW modeling software is used to simulate the nonlinear relationships between climate trends and precipitation partitioning into ET, runoff, and subsurface storage. Four global circulation models (GCMs), each with two greenhouse-gas scenarios, RCP45 and RCP85 are used to project future climate conditions. GCMs include the CanESM2, CNRM-CM5, HadGEM2-ES, and MIROC5 models. The model's simulated hydrologic conditions are compared with historical data to assess changes in water budgets and groundwater supply. Results indicate decreased groundwater storage in most scenarios due to increased natural evapotranspiration, vegetation consumptive use, and streamflow out of the watershed. Only scenarios with substantially increased future precipitation show increased groundwater storage. The study also highlights increased future aridity despite the rise in precipitation and large precipitation events forecast by GCMs, which increase the risk of urban floods and decrease stream leakage and water available to vegetation.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ejrh.2025.102461","usgsCitation":"Ryter, D.W., Alzraiee, A.H., and Niswonger, R., 2025, Simulation of the impacts of projected climate change on groundwater resources in the urban, semiarid Yucaipa Valley watershed, southern California using an integrated hydrologic model: Journal of Hydrology, Regional Studies, v. 60, 102461, 16 p., https://doi.org/10.1016/j.ejrh.2025.102461.","productDescription":"102461, 16 p.","ipdsId":"IP-153865","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":493789,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ejrh.2025.102461","text":"Publisher Index Page"},{"id":493644,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Yucaipa Valley watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.09271702186436,\n 34.0874203948469\n ],\n [\n -117.09271702186436,\n 33.9725594754417\n ],\n [\n -116.9002906646693,\n 33.9725594754417\n ],\n [\n -116.9002906646693,\n 34.0874203948469\n ],\n [\n -117.09271702186436,\n 34.0874203948469\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"60","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ryter, Derek W. 0000-0002-2488-626X dryter@usgs.gov","orcid":"https://orcid.org/0000-0002-2488-626X","contributorId":3395,"corporation":false,"usgs":true,"family":"Ryter","given":"Derek","email":"dryter@usgs.gov","middleInitial":"W.","affiliations":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":944909,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Alzraiee, Ayman H. 0000-0001-7576-3449","orcid":"https://orcid.org/0000-0001-7576-3449","contributorId":272120,"corporation":false,"usgs":true,"family":"Alzraiee","given":"Ayman","email":"","middleInitial":"H.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":944910,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Niswonger, Richard G. rniswon@usgs.gov","contributorId":146547,"corporation":false,"usgs":false,"family":"Niswonger","given":"Richard G.","email":"rniswon@usgs.gov","affiliations":[],"preferred":false,"id":944911,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70267395,"text":"sir20245130 - 2025 - Estimating the magnitude and frequency of floods at ungaged locations on streams in Tennessee through the 2013 water year","interactions":[],"lastModifiedDate":"2025-05-29T15:06:41.309366","indexId":"sir20245130","displayToPublicDate":"2025-05-29T08:00:00","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":"2024-5130","displayTitle":"Estimating the Magnitude and Frequency of Floods at Ungaged Locations on Streams in Tennessee Through the 2013 Water Year","title":"Estimating the magnitude and frequency of floods at ungaged locations on streams in Tennessee through the 2013 water year","docAbstract":"To improve estimates of the frequency of annual peak flows for ungaged locations on non-urban, unregulated streams in Tennessee, generalized least-squares multiple linear-regression techniques were used to relate annual peak flows from streamgages operated by the U.S. Geological Survey to physical, climatic, and land-use characteristics of their drainage basins. Geospatial data acquired since the previous study in 2003, annual peak-streamflow data through the 2013 water year, and Bulletin 17C methods for frequency analysis of annual peak-streamflow data were used in the study. Generalized least-squares regression equations were developed for four hydrologic areas with distinct hydrologic, geologic, and topographic characteristics. Drainage area was used as an explanatory variable in equations developed for each hydrologic area. In addition to drainage area, a 2-year recurrence-interval climate factor was used for hydrologic area 1, a 10–85 channel slope was used for hydrologic area 2, and percent imperviousness was used for hydrologic area 4. The regression equations can be used to estimate annual exceedance probability streamflows for ungaged locations on non-urban, unregulated streams in Tennessee. The term “unregulated” indicates that streamflow is not appreciably influenced by regulation from reservoirs or other impoundments. Average standard errors of prediction for the regression equations ranged from 44.4 to 51.4 percent for hydrologic area 1; 30.4 to 42.9 percent for hydrologic area 2; 35.7 to 42.6 percent for hydrologic area 3; and 32.5 to 47.4 percent for hydrologic area 4.
Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
640 Grassmere Park, Suite 100
Nashville, TN 37211
Contact Us- USGS Publications Warehouse
","tableOfContents":"We surveyed for Southwestern Willow Flycatchers (Empidonax traillii extimus; flycatcher) at select locations along the San Luis Rey River, including along the middle San Luis Rey River near Bonsall and the upper San Luis Rey River near Santa Ysabel, California, in 2024. Surveys were completed at six locations: two along the middle San Luis Rey River (Bonsall [BO] and Rincon), which were last surveyed in 2021, and four along the upper San Luis Rey River, including three downstream from Lake Henshaw that have been surveyed annually since 2015 (Rey River Ranch, Cleveland National Forest [CNF], Vista Irrigation District [VID]), and one upstream at VID Lake Henshaw (VLH) that has been surveyed annually since 2018. There were a minimum of 47 territorial flycatchers (26 male, 21 female) detected at 1 location (VLH) and 6 transient flycatchers of unknown subspecies detected at 3 locations (BO, CNF, and VLH). In total, 30 territories were established, containing 21 pairs and 9 flycatchers of undetermined breeding status. Of the 21 pairs, 13 pairs were monogamous (1 male and 1 female), and 8 pairs were polygynous (1 male paired with more than 1 female). No territorial flycatchers were detected downstream from Lake Henshaw or along the middle San Luis Rey River. Brown-headed Cowbirds (Molothrus ater; cowbird) were detected at all six survey locations. No banded flycatchers were detected during surveys.
Flycatchers used four habitat types in the survey area: (1) mixed willow riparian, (2) willow-cottonwood, (3) willow-oak, and (4) willow-sycamore. Of the flycatcher locations, 86 percent were in habitat characterized as mixed willow riparian, and 97 percent were in habitat with greater than 95-percent native plant cover.
We monitored flycatcher nests at VLH to collect baseline data on nest success, productivity, and parasitism rate. There were 22 nests monitored in 13 territories; 9 were successful. Of the 13 failed nests, 8 were depredated, 3 failed for unknown reasons, and 2 failed because of cowbird parasitism. We confirmed 26 juvenile flycatchers in 2024, which included 22 from monitored nests, and an additional 4 juveniles detected in unmonitored territories. Based on 19 nests in which the contents were observed during the egg stage, 16 percent of nests in 2024 were parasitized.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dr1212","programNote":"Ecosystems Mission Area—Species Management Research Program","usgsCitation":"Howell, S.L., and Kus, B.E., 2025, Distribution, abundance, and breeding activities of Southwestern Willow Flycatchers (Empidonax traillii extimus) at select locations on the San Luis Rey River, San Diego County, California—2024 data summary: U.S. Geological Survey Data Report 1212, 16 p., https://doi.org/10.3133/dr1212.","productDescription":"Report: vi, 16 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-175205","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":486429,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/dr/1212/dr1212.XML"},{"id":486427,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96VC5Y4","text":"USGS data release","description":"USGS data release","linkHelpText":"Southwestern Willow Flycatcher (Empidonax traillii extimus) surveys and nest monitoring in San Diego County, California (ver. 4.0, February 2025)"},{"id":486428,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/dr/1212/images"},{"id":486424,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/dr/1212/coverthb.jpg"},{"id":486425,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/dr/1212/dr1212.pdf","text":"Report","size":"3.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DR 1212"},{"id":486426,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/dr1212/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"DR 1212"}],"country":"United States","state":"California","county":"San Diego County","otherGeospatial":"San Luis Rey River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.25,\n 33.333\n ],\n [\n -117.25,\n 33.1667\n ],\n [\n -116.6667,\n 33.1667\n ],\n [\n -116.6667,\n 33.333\n ],\n [\n -117.25,\n 33.333\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
Connecticut has a diverse, largely forested landscape characterized by hills and low mountains in the Western Upland, hills in the Eastern Upland, ridges and broad valleys in the Central Lowland, and many beaches and harbors along the coast of Long Island Sound. Connecticut is manufacturing and service focused, ranking almost highest among the 50 States in the United States in personal income per capita. Due to Connecticut’s dense population, many people, especially the approximately 60 percent living near the coast, may be affected by climate-driven disasters. High-quality elevation data can inform the activities of many nongovernmental organizations and municipal and academic entities statewide, resulting in substantial economic impact. Government at the State and local levels relies on these data to support regulatory permitting, resource and infrastructure management, and various engineering and planning-level analyses. Critical applications that meet the State’s management needs depend on light detection and ranging (lidar) data that provide a highly detailed three-dimensional (3D) model of the Earth’s surface and aboveground features.
The 3D Elevation Program (3DEP) is managed by the U.S. Geological Survey in partnership with Federal, State, Tribal, U.S. territorial, and local agencies to acquire consistent lidar coverage at quality level 2 or better to meet the many needs of the Nation and Connecticut. The status of available and in-progress 3DEP baseline lidar data in Connecticut is shown. 3DEP baseline lidar data include quality level 2 or better, 1-meter or better digital elevation models, and lidar point clouds, and must meet the Lidar Base Specification version 1.2 or newer requirements. The National Enhanced Elevation Assessment identified user requirements and conservatively estimated that availability of lidar data would result in at least $4.40 million in new benefits annually to the State. The top 10 Connecticut business uses for 3D elevation data, which are based on the estimated annual conservative benefits of 3DEP, are shown.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20253030","usgsCitation":"Harrington, L.E., and Walters, D.H., 2025, The 3D Elevation Program—Supporting Connecticut's economy: U.S. Geological Survey Fact Sheet 2025–3030, 2 p., https://doi.org/10.3133/fs20253030.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-168624","costCenters":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":486450,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2025/3030/images/"},{"id":486449,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2025/3030/fs20253030.XML","linkFileType":{"id":8,"text":"xml"},"description":"FS 2025-3030 XML"},{"id":486448,"rank":3,"type":{"id":39,"text":"HTML 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\"}}]}","contact":"Director, National Geospatial Program
U.S. Geological Survey, MS 511
12201 Sunrise Valley Drive
Reston, VA 20192
Email: 3DEP@usgs.gov
","tableOfContents":"For endangered shortnose sturgeon (Acipenser brevirostrum), the ability to estimate and monitor population size is critical for tracking species’ recovery. Yet, contemporary abundance estimates have not been completed for many shortnose sturgeon populations, largely owing to the difficulty in using traditional abundance estimators for sturgeons. Here, we estimate the adult shortnose sturgeon population size of the Hudson River, NY by integrating data from two largely passive sampling methods – acoustic telemetry and side-scan sonar – into a Bayesian hierarchical model of abundance. We estimated the adult abundance to be 69,798 individuals (95% CI = 9,207-185,666), making the Hudson River the largest extant shortnose sturgeon population. Despite this, the population remains vulnerable to localized disturbances, as over 40% of the population congregated in a small overwintering habitat that coincides with an area of high anthropogenic activity. Accordingly, recurrent demographic surveys may be beneficial for gaining insight into the relative effects of anthropogenic and naturally stochastic processes shaping shortnose sturgeon demography. Our modeling framework provides a relatively low-cost alternative for future demographic monitoring of species of conservation concern.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2024-0395","usgsCitation":"Higgs, A., White, S.L., Madsen, J., Kazyak, D.C., Fox, D., Pendleton, R., Bonemery, A., Smolinski, T., Simmonds, A., and Sullivan, P., 2025, Combining acoustic telemetry and side-scan sonar to estimate abundance of endangered shortnose sturgeon in the Hudson River, New York: Canadian Journal of Fisheries and Aquatic Sciences, v. 82, p. 1-12, https://doi.org/10.1139/cjfas-2024-0395.","productDescription":"12 p.","startPage":"1","endPage":"12","ipdsId":"IP-173509","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":493294,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1139/cjfas-2024-0395","text":"Publisher Index Page"},{"id":490514,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":490933,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13DHPMI","text":"USGS data release","linkHelpText":"Shortnose Sturgeon Abundance Model"}],"country":"United States","state":"New York","otherGeospatial":"Hudson River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -73.16518084744041,\n 44.213068299609006\n ],\n [\n -73.8033572199802,\n 44.20312158009787\n ],\n [\n -74.23343260147449,\n 40.724843913894034\n ],\n [\n -73.75480032206964,\n 40.74061550176276\n ],\n [\n -73.16518084744041,\n 44.213068299609006\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"82","noUsgsAuthors":false,"publicationDate":"2025-05-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Higgs, Amanda","contributorId":225402,"corporation":false,"usgs":false,"family":"Higgs","given":"Amanda","affiliations":[{"id":13678,"text":"New York State Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":940121,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"White, Shannon L. 0000-0003-4687-6596","orcid":"https://orcid.org/0000-0003-4687-6596","contributorId":263424,"corporation":false,"usgs":true,"family":"White","given":"Shannon","email":"","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":940122,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Madsen, John","contributorId":340956,"corporation":false,"usgs":false,"family":"Madsen","given":"John","affiliations":[{"id":36379,"text":"Delaware Division of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":940123,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kazyak, David C. 0000-0001-9860-4045","orcid":"https://orcid.org/0000-0001-9860-4045","contributorId":140409,"corporation":false,"usgs":true,"family":"Kazyak","given":"David","email":"","middleInitial":"C.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":940124,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fox, Dewayne","contributorId":340954,"corporation":false,"usgs":false,"family":"Fox","given":"Dewayne","affiliations":[{"id":37219,"text":"Delaware State University","active":true,"usgs":false}],"preferred":false,"id":940125,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pendleton, Richard","contributorId":348720,"corporation":false,"usgs":false,"family":"Pendleton","given":"Richard","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":940126,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bonemery, Adam","contributorId":351166,"corporation":false,"usgs":false,"family":"Bonemery","given":"Adam","affiliations":[{"id":83929,"text":"Cornell University/NY Dept. of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":940127,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Smolinski, Tomasz","contributorId":356810,"corporation":false,"usgs":false,"family":"Smolinski","given":"Tomasz","affiliations":[{"id":85239,"text":"Delware State University","active":true,"usgs":false}],"preferred":false,"id":940128,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Simmonds, Amanda","contributorId":351168,"corporation":false,"usgs":false,"family":"Simmonds","given":"Amanda","affiliations":[{"id":83929,"text":"Cornell University/NY Dept. of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":940129,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Sullivan, Patrick","contributorId":348055,"corporation":false,"usgs":false,"family":"Sullivan","given":"Patrick","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":940130,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70269445,"text":"70269445 - 2025 - Leisure boat harbours, hidden alien species, and pollution: A case study of Hinsholmskilen harbour (Gothenburg, Sweden)","interactions":[],"lastModifiedDate":"2025-07-23T14:27:23.832772","indexId":"70269445","displayToPublicDate":"2025-05-26T09:22:43","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2391,"text":"Journal of Micropalaeontology","active":true,"publicationSubtype":{"id":10}},"title":"Leisure boat harbours, hidden alien species, and pollution: A case study of Hinsholmskilen harbour (Gothenburg, Sweden)","docAbstract":"Small leisure boat harbours have important aesthetic and recreational values in any country with a coastline. In Sweden, there are about 860 000 leisure boats, which is one of the world's highest numbers in relation to the country's population. However, small boat harbours also present a wide range of environmental problems, including the introduction of alien species and high pollution. In this study, we investigated the ecological quality status (EcoQS) of the Hinsholmskilen small boat harbour, located southwest of the city of Gothenburg (Sweden). We performed a reconnaissance survey of the harbour's previously unstudied benthic foraminiferal communities and analysed surface sediment (0–2 cm) samples for potentially toxic elements: copper (Cu), zinc (Zn), lead (Pb), cobalt (Co), nickel (Ni), chromium (Cr), mercury (Hg), and arsenic (As). The results show that, based on the total benthic foraminiferal distribution (dead and live specimens), the assemblages in Hinsholmskilen harbour represent a typical European estuarine community with highly abundant Ammonia and Elphidium species. Based on molecular and morphological data, we report the presence of two alien and putatively invasive species likely originating from Asia: Trochammina hadai and Ammonia confertitesta (phylotype T6). Both species have recently been identified elsewhere on the Swedish west coast based on molecular and morphological data but do not have a well-known distribution. The sediment analysis for potentially toxic elements showed that the harbour has good to high EcoQS corresponding to no or little deviation from reference conditions for Cd, Co, Ni, and Pb distribution. Some of the contaminants (Pb, As, Zn, and Cr) showed poor to bad EcoQS in the innermost harbour in proximity to high-pressure cleaning plants, where boats are usually lifted, cleaned, and prepared for winter storage on land. Finally, Cu and Hg showed consistently bad and poor EcoQS all over the harbour, reflecting the use of both metals as biocides in antifouling boat paints.
","language":"English","publisher":"Copernicus Publications","doi":"10.5194/jm-44-119-2025","usgsCitation":"Polovodova Asteman, I., Jaffre, E., Olejnik, A., Holzmann, M., McGann, M., Nordberg, K., Pavard, J., Rosel, D., and Schweizer, M., 2025, Leisure boat harbours, hidden alien species, and pollution: A case study of Hinsholmskilen harbour (Gothenburg, Sweden): Journal of Micropalaeontology, v. 44, no. 1, p. 119-143, https://doi.org/10.5194/jm-44-119-2025.","productDescription":"25 p.","startPage":"119","endPage":"143","ipdsId":"IP-175758","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":492882,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/jm-44-119-2025","text":"Publisher Index Page"},{"id":492765,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Sweden","city":"Gothenburg","otherGeospatial":"Hinsholmskilen harbour","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 11.859714003088953,\n 57.665848406215815\n ],\n [\n 11.857574021139172,\n 57.66779256158691\n ],\n [\n 11.85390966848746,\n 57.66816885760571\n ],\n [\n 11.84165607322359,\n 57.65825887915017\n ],\n [\n 11.849336556379455,\n 57.65618872929906\n ],\n [\n 11.85965537344508,\n 57.66374694130421\n ],\n [\n 11.859714003088953,\n 57.665848406215815\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"44","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-05-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Polovodova Asteman, Irina","contributorId":358443,"corporation":false,"usgs":false,"family":"Polovodova Asteman","given":"Irina","affiliations":[{"id":48984,"text":"University of Gothenburg, Sweden","active":true,"usgs":false}],"preferred":false,"id":943766,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jaffre, Emilie","contributorId":358444,"corporation":false,"usgs":false,"family":"Jaffre","given":"Emilie","affiliations":[{"id":24718,"text":"University of Angers, France","active":true,"usgs":false}],"preferred":false,"id":943767,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Olejnik, Agata","contributorId":358446,"corporation":false,"usgs":false,"family":"Olejnik","given":"Agata","affiliations":[{"id":48984,"text":"University of Gothenburg, Sweden","active":true,"usgs":false}],"preferred":false,"id":943768,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Holzmann, Maria","contributorId":304262,"corporation":false,"usgs":false,"family":"Holzmann","given":"Maria","email":"","affiliations":[{"id":66013,"text":"University of Geneva, Switzerland","active":true,"usgs":false}],"preferred":false,"id":943769,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McGann, Mary 0000-0002-3057-2945 mmcgann@usgs.gov","orcid":"https://orcid.org/0000-0002-3057-2945","contributorId":169540,"corporation":false,"usgs":true,"family":"McGann","given":"Mary","email":"mmcgann@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":943770,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nordberg, Kjell","contributorId":358451,"corporation":false,"usgs":false,"family":"Nordberg","given":"Kjell","affiliations":[{"id":48984,"text":"University of Gothenburg, Sweden","active":true,"usgs":false}],"preferred":false,"id":943771,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pavard, Jean-Charles","contributorId":304261,"corporation":false,"usgs":false,"family":"Pavard","given":"Jean-Charles","email":"","affiliations":[{"id":66012,"text":"University of Lille, France","active":true,"usgs":false}],"preferred":false,"id":943772,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rosel, Delia","contributorId":358454,"corporation":false,"usgs":false,"family":"Rosel","given":"Delia","affiliations":[{"id":48984,"text":"University of Gothenburg, Sweden","active":true,"usgs":false}],"preferred":false,"id":943773,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Schweizer, Magali","contributorId":203435,"corporation":false,"usgs":false,"family":"Schweizer","given":"Magali","email":"","affiliations":[{"id":36617,"text":"LPG-BIAF UMR CNRS 6112, University of Angers, 2 Boulevard Lavoisier, 49045 Angers Cedex 01, France","active":true,"usgs":false}],"preferred":false,"id":943774,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70268934,"text":"70268934 - 2025 - Factors associated with survival, recovery, and movements in the western Gulf Coast population of mottled ducks","interactions":[],"lastModifiedDate":"2025-07-11T15:01:30.51809","indexId":"70268934","displayToPublicDate":"2025-05-26T07:55:58","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Factors associated with survival, recovery, and movements in the western Gulf Coast population of mottled ducks","docAbstract":"The mottled duck (Anas fulvigula) is nonmigratory and a priority species for regional conservation and management because of its limited range and declining population trajectory in the western Gulf Coast (WGC) of Louisiana and Texas, USA. We developed multistate dead-recovery models for banding and recovery data (1997–2020) to evaluate potential drivers of survival, recovery, and post-summer movements for the WGC population of mottled ducks in Louisiana and Texas. Annual survival was most strongly associated with sex and year, with females having lower survival ( ± = 0.544 ± 0.114) than males (0.619 ± 0.062). Of the 32 environmental covariates tested, fall precipitation was the factor most strongly associated with survival. Conditional recovery probability (i.e., given mortality, the probability a bird had been shot by a hunter, retrieved, and had their band number reported) varied by sex, age, geographic state, and year, with juvenile males generally having highest conditional recovery (0.303 ± 0.072), followed by juvenile females (0.201 ± 0.100), adult males (0.156 ± 0.038), and adult females (0.095 ± 0.057). Estimates of harvest probabilities followed similar patterns as conditional recovery. Models containing effects of harvest regulations on conditional recovery were not competitive compared to models with general year effects; however, post hoc analyses suggested conditional recovery and harvest probabilities for adult and juvenile females decreased with the daily bag limit reduction in Louisiana and, for juvenile females, implementation of the 5-day closure regulation in Texas. Post-summer movement was substantially higher in the direction of Texas to Louisiana, decreased with distance to the Louisiana–Texas border, was higher for males than females, and varied with winter precipitation. These results contribute to a better understanding of the factors influencing demographic performance, harvest, and movement between states with differing harvest regulations and environmental pressures, which is important for mottled duck conservation planning. Wildlife managers can consider expanding banding effort throughout the full range of the WGC population and collecting and reporting live-recapture data to allow for stronger population-level inferences and increased power to detect differences in important demographic parameters at more refined spatial scales.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.70038","usgsCitation":"Malachowski, C., Kendall, W.L., Collins, D., Kraai, K.J., Olszak, J., and Reynolds, L., 2025, Factors associated with survival, recovery, and movements in the western Gulf Coast population of mottled ducks: Journal of Wildlife Management, v. 89, no. 6, e70038, 33 p., https://doi.org/10.1002/jwmg.70038.","productDescription":"e70038, 33 p.","ipdsId":"IP-168786","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":492473,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.70038","text":"Publisher Index Page"},{"id":492131,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana, Texas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -99.98534654094911,\n 34.74317254350352\n ],\n [\n -99.98534654094911,\n 27.62034513580788\n ],\n [\n -89.48377067387685,\n 27.62034513580788\n ],\n [\n -89.48377067387685,\n 34.74317254350352\n ],\n [\n -99.98534654094911,\n 34.74317254350352\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"89","issue":"6","noUsgsAuthors":false,"publicationDate":"2025-05-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Malachowski, Christopher P.","contributorId":357821,"corporation":false,"usgs":false,"family":"Malachowski","given":"Christopher P.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":942661,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kendall, William L. 0000-0003-0084-9891","orcid":"https://orcid.org/0000-0003-0084-9891","contributorId":204844,"corporation":false,"usgs":true,"family":"Kendall","given":"William","email":"","middleInitial":"L.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":942662,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Collins, Daniel P.","contributorId":356157,"corporation":false,"usgs":false,"family":"Collins","given":"Daniel P.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":942663,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kraai, Kevin J.","contributorId":346855,"corporation":false,"usgs":false,"family":"Kraai","given":"Kevin","email":"","middleInitial":"J.","affiliations":[{"id":27442,"text":"Texas parks and Wildlife Department","active":true,"usgs":false}],"preferred":false,"id":942664,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Olszak, Jason","contributorId":357822,"corporation":false,"usgs":false,"family":"Olszak","given":"Jason","affiliations":[{"id":12717,"text":"Louisiana Department of Wildlife and Fisheries","active":true,"usgs":false}],"preferred":false,"id":942665,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Reynolds, Larry","contributorId":357824,"corporation":false,"usgs":false,"family":"Reynolds","given":"Larry","affiliations":[{"id":12717,"text":"Louisiana Department of Wildlife and Fisheries","active":true,"usgs":false}],"preferred":false,"id":942666,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70274299,"text":"70274299 - 2025 - Harnessing geospatial artificial intelligence and deep learning for landslide inventory mapping: Advances, challenges, and emerging directions","interactions":[],"lastModifiedDate":"2026-03-25T14:54:23.10639","indexId":"70274299","displayToPublicDate":"2025-05-25T00:00:00","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Harnessing geospatial artificial intelligence and deep learning for landslide inventory mapping: Advances, challenges, and emerging directions","docAbstract":"Recent advancements in artificial intelligence (AI) and deep learning enable more accurate, scalable, and automated mapping. This paper provides a comprehensive review of the applications of AI, particularly deep learning, in landslide inventory mapping. In addition to examining commonly used data sources and model architectures, we explore innovative strategies such as feature enhancement and fusion, attention-boosted techniques, and advanced learning approaches, including active learning and transfer learning, to enhance model adaptability and predictability. We also highlight the remaining challenges and potential research directions, including the estimation of more diverse variables in landslide mapping, multimodal data alignment, modeling regional variability and replicability, as well as issues related to data misinterpretation and model explainability. This review aims to serve as a useful resource for researchers and practitioners, promoting the integration of deep learning into landslide research and disaster management.
","language":"English","publisher":"MDPI","doi":"10.3390/rs17111856","usgsCitation":"Chen, X., Li, W., Hsu, C., Arundel, S.T., and Bretwood Higman, 2025, Harnessing geospatial artificial intelligence and deep learning for landslide inventory mapping: Advances, challenges, and emerging directions: Remote Sensing, v. 17, no. 11, 1856, 39 p., https://doi.org/10.3390/rs17111856.","productDescription":"1856, 39 p.","ipdsId":"IP-177148","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":501598,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs17111856","text":"Publisher Index Page"},{"id":501497,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"17","issue":"11","noUsgsAuthors":false,"publicationDate":"2025-05-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Chen, Xiao 0009-0009-8338-2983","orcid":"https://orcid.org/0009-0009-8338-2983","contributorId":367832,"corporation":false,"usgs":false,"family":"Chen","given":"Xiao","affiliations":[],"preferred":false,"id":957786,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Li, Wenwen 0000-0003-2237-9499","orcid":"https://orcid.org/0000-0003-2237-9499","contributorId":219356,"corporation":false,"usgs":false,"family":"Li","given":"Wenwen","email":"","affiliations":[{"id":6607,"text":"Arizona State University","active":true,"usgs":false}],"preferred":false,"id":957787,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hsu, Chia-Yu","contributorId":367833,"corporation":false,"usgs":false,"family":"Hsu","given":"Chia-Yu","affiliations":[],"preferred":false,"id":957788,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Arundel, Samantha T. 0000-0002-4863-0138 sarundel@usgs.gov","orcid":"https://orcid.org/0000-0002-4863-0138","contributorId":192598,"corporation":false,"usgs":true,"family":"Arundel","given":"Samantha","email":"sarundel@usgs.gov","middleInitial":"T.","affiliations":[{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true},{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":957789,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bretwood Higman","contributorId":367834,"corporation":false,"usgs":false,"family":"Bretwood Higman","affiliations":[],"preferred":false,"id":957790,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70269694,"text":"70269694 - 2025 - Effects of restoration thinning on live tree carbon in northern secondary coastal redwood forests","interactions":[],"lastModifiedDate":"2025-07-30T14:47:41.642988","indexId":"70269694","displayToPublicDate":"2025-05-23T09:38:46","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Effects of restoration thinning on live tree carbon in northern secondary coastal redwood forests","docAbstract":"At Redwood National and State parks restoration efforts are underway to promote the recovery of forests following a history of intense logging. Unmanaged secondary forests at the parks have high stem density with slow stand development. Restoration thinning treatments of these stands are designed to promote the representation of redwood and improve the growth of residual trees. Restoration treatments, by definition, remove live tree carbon, so there is a potential conflict with restoration and carbon sequestration goals. We used data from 151 monitoring plots to determine early treatment effects (mostly ≤ 10 years following treatments) on live tree forest carbon in thinned and unthinned stands. Aboveground live tree carbon in untreated secondary forests was primarily related to stand age. Both treated and untreated stands accumulated carbon over time, with evidence that treated stands had a slightly faster rate of carbon accumulation. For a subset of plots where we had sufficient replicates of thinning prescriptions, we found thinning resulted in reductions in live tree aboveground carbon, particularly for heavy thinning, but with plots accumulating live tree carbon stocks similar to pre-treatment levels within 6–10 years. Stand projections suggested that both thinned and unthinned stands have the capacity to greatly increase aboveground live tree carbon in coming decades, with thinned stands accumulating aboveground live tree carbon at a slightly faster pace.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2025.122817","usgsCitation":"van Mantgem, P., Wright, M., and Teraoka, J., 2025, Effects of restoration thinning on live tree carbon in northern secondary coastal redwood forests: Forest Ecology and Management, v. 591, 122817, 9 p., https://doi.org/10.1016/j.foreco.2025.122817.","productDescription":"122817, 9 p.","ipdsId":"IP-173324","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":493183,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Redwood National and State Parks","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -124.2,\n 41.8\n ],\n [\n -124.2,\n 41.1\n ],\n [\n -123.8,\n 41.1\n ],\n [\n -123.8,\n 41.8\n ],\n [\n -124.2,\n 41.8\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"591","noUsgsAuthors":false,"publicationDate":"2025-05-23","publicationStatus":"PW","contributors":{"authors":[{"text":"van Mantgem, Phillip J. 0000-0002-3068-9422","orcid":"https://orcid.org/0000-0002-3068-9422","contributorId":204320,"corporation":false,"usgs":true,"family":"van Mantgem","given":"Phillip J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":944455,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wright, Micah C. 0000-0002-5324-1110","orcid":"https://orcid.org/0000-0002-5324-1110","contributorId":229071,"corporation":false,"usgs":true,"family":"Wright","given":"Micah","middleInitial":"C.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":944456,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Teraoka, Jason","contributorId":131056,"corporation":false,"usgs":false,"family":"Teraoka","given":"Jason","affiliations":[{"id":6924,"text":"National Park Service, Upper Columbia Basin Network","active":true,"usgs":false}],"preferred":false,"id":944457,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70267491,"text":"70267491 - 2025 - Modeling individual-level and population-level nest success of California Condors from movement data","interactions":[],"lastModifiedDate":"2025-05-27T14:03:49.537407","indexId":"70267491","displayToPublicDate":"2025-05-23T08:44:31","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2442,"text":"Journal of Raptor Research","active":true,"publicationSubtype":{"id":10}},"title":"Modeling individual-level and population-level nest success of California Condors from movement data","docAbstract":"The California Condor (Gymnogyps californianus) is a critically endangered species with populations that are not currently self-sustaining. Although understanding nest success is key to understanding trends in their populations, field monitoring of condor nests has become increasingly challenging as the number of nesting condors has increased and their range has expanded. We investigated whether California Condor nest fate could be accurately estimated from telemetry data with limited field observations. Our study focused on the southern California population of California Condors (2015–2022), and we used a recently published Bayesian hierarchical modeling framework that combines movement data and occasional field observations to estimate individual-level and population-level nest success. The model detected shifts in space use to categorize if each nest failed or if a young fledged. Estimated model parameters suggested that after nest failure, condors shifted toward more expansive space use. Additional field observations, not included as data in the model, provided evidence that we accurately categorized nest fate for 63 out of 65 California Condor nesting attempts. Finally, we scaled individual-level reproductive success to estimate annual population-level nesting success. These methods offer managers a way to reduce field monitoring efforts while still allowing for estimation of nest success, which will be key as the breeding populations of California Condors continue to grow and become more widely spread across the landscape.
","language":"English","publisher":"Raptor Research Foundation","doi":"10.3356/jrr2464","usgsCitation":"Blackburn, A., Eisaguirre, J.M., Brandt, J.C., Punzalan, A., Mcmahon, L., Astell, M., Seal Faith, N., Meyer, D.J., and Sandhaus, E., 2025, Modeling individual-level and population-level nest success of California Condors from movement data: Journal of Raptor Research, v. 59, no. 3, jrr2464, 11 p., https://doi.org/10.3356/jrr2464.","productDescription":"jrr2464, 11 p.","ipdsId":"IP-169837","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":488102,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3356/jrr2464","text":"Publisher Index Page"},{"id":486571,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.32211025552813,\n 36.28940419433357\n ],\n [\n -120.00478872484904,\n 34.43478894822218\n ],\n [\n -118.61047283563802,\n 34.31101307176946\n ],\n [\n -117.16910974890232,\n 34.36199636242087\n ],\n [\n -117.12500300122358,\n 35.49657369871312\n ],\n [\n -118.83340436132296,\n 37.334518704354934\n ],\n [\n -121.32211025552813,\n 36.28940419433357\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"59","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Blackburn, Andrea","contributorId":355921,"corporation":false,"usgs":false,"family":"Blackburn","given":"Andrea","affiliations":[{"id":84857,"text":"Santa Barbara Zoo","active":true,"usgs":false}],"preferred":false,"id":938382,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eisaguirre, Joseph Michael 0000-0002-0450-8472","orcid":"https://orcid.org/0000-0002-0450-8472","contributorId":301980,"corporation":false,"usgs":true,"family":"Eisaguirre","given":"Joseph","email":"","middleInitial":"Michael","affiliations":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"preferred":true,"id":938383,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brandt, Joseph C.","contributorId":288474,"corporation":false,"usgs":false,"family":"Brandt","given":"Joseph","email":"","middleInitial":"C.","affiliations":[{"id":61768,"text":"U.S. Fish and Wildlife Service, Hopper Mountain National Wildlife Refuge Complex, Ventura, CA","active":true,"usgs":false}],"preferred":false,"id":938384,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Punzalan, Arianna","contributorId":355922,"corporation":false,"usgs":false,"family":"Punzalan","given":"Arianna","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":938385,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mcmahon, Laura","contributorId":275577,"corporation":false,"usgs":false,"family":"Mcmahon","given":"Laura","email":"","affiliations":[],"preferred":false,"id":938386,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Astell, Molly","contributorId":199753,"corporation":false,"usgs":false,"family":"Astell","given":"Molly","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":938387,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Seal Faith, Nadya E.","contributorId":355923,"corporation":false,"usgs":false,"family":"Seal Faith","given":"Nadya E.","affiliations":[{"id":84857,"text":"Santa Barbara Zoo","active":true,"usgs":false}],"preferred":false,"id":938388,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Meyer, David J.","contributorId":149174,"corporation":false,"usgs":false,"family":"Meyer","given":"David","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":938389,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Sandhaus, Estelle A.","contributorId":355924,"corporation":false,"usgs":false,"family":"Sandhaus","given":"Estelle A.","affiliations":[{"id":84857,"text":"Santa Barbara Zoo","active":true,"usgs":false}],"preferred":false,"id":938390,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70266896,"text":"ofr20251020 - 2025 - Using high-resolution geospatial imagery and data to document the evolution of the Wilderness Breach that was created by Hurricane Sandy in 2012 at Fire Island National Seashore, New York","interactions":[],"lastModifiedDate":"2026-01-26T18:18:00.059455","indexId":"ofr20251020","displayToPublicDate":"2025-05-22T13:55:00","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":"2025-1020","displayTitle":"Using High-Resolution Geospatial Imagery and Data To Document the Evolution of the Wilderness Breach That Was Created by Hurricane Sandy in 2012 at Fire Island National Seashore, New York","title":"Using high-resolution geospatial imagery and data to document the evolution of the Wilderness Breach that was created by Hurricane Sandy in 2012 at Fire Island National Seashore, New York","docAbstract":"The U.S. Geological Survey’s National Civil Applications Center obtained remote sensing data and imagery collected from 1939 through 2023 to monitor changes at Fire Island National Seashore, New York. On October 29, 2012, an inlet was created during Hurricane Sandy on Fire Island that remained open for 10 years. This inlet, named the “Wilderness Breach,” formed at the same location where an inlet had previously existed and remained open from 1763 to 1825. This report documents the morphological changes that occurred at the Wilderness Breach during the 10-year existence of this feature.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251020","isbn":"978-1-4113-4607-9","usgsCitation":"Fisher, G.B., 2025, Using high-resolution geospatial imagery and data to document the evolution of the Wilderness Breach that was created by Hurricane Sandy in 2012 at Fire Island National Seashore, New York: U.S. Geological Survey Open-File Report 2025–1020, 27 p., https://doi.org/10.3133/ofr20251020.","productDescription":"Report: iv, 27 p.; Data Release","numberOfPages":"27","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-172331","costCenters":[{"id":36171,"text":"National Civil Applications Center","active":true,"usgs":true}],"links":[{"id":499032,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118577.htm","linkFileType":{"id":5,"text":"html"}},{"id":486116,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1020/ofr20251020_print.pdf","text":"Report","size":"186 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1020 PDF","linkHelpText":"High-resolution version"},{"id":486120,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1382HXH","text":"USGS data release","linkHelpText":"Inlet shorelines, Wilderness Breach, Fire Island, NY"},{"id":486119,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1020/images/"},{"id":486118,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1020/ofr20251020.XML","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2025-1020 XML"},{"id":486117,"rank":4,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251020/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2025-1020 HTML"},{"id":486115,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1020/ofr20251020_web.pdf","text":"Report","size":"6.57 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1020 PDF"},{"id":486114,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1020/coverthb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Fire Island National Seashore, Wilderness Breach","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -72.91743128283203,\n 40.73591066652804\n ],\n [\n -72.91743128283203,\n 40.71852473853389\n ],\n [\n -72.885125351772,\n 40.71852473853389\n ],\n [\n -72.885125351772,\n 40.73591066652804\n ],\n [\n -72.91743128283203,\n 40.73591066652804\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, National Civil Applications Center
National Land Imaging Program
U.S. Geological Survey
12201 Sunrise Valley Drive, MS 562
Reston, VA 20192
Email: cac@usgs.gov
","tableOfContents":"The U.S. Geological Survey is working with Federal land management agencies to develop a series of science syntheses to support National Environmental Policy Act (NEPA) analyses. This report synthesizes science information about the potential effects of nonmotorized recreation on ungulates in the western United States. We conducted a structured literature search to find published science, data, and analysis methods about the characteristics of nonmotorized recreation, ungulate exposure and response to nonmotorized recreation, and approaches to mitigate negative effects of nonmotorized recreation on ungulates. The sections of the report align with standard elements of the NEPA analysis process. We found that timing, intensity, duration, and spatial distribution of nonmotorized recreation are important factors to understand when assessing effects of recreation on ungulates. Several aspects of ungulate biology, which vary by species, population, and individual, affect ungulate susceptibility to effects from recreation, including diet, migration and movement, and seasonal biology. Techniques for assessing effects include basic spatial analyses based on buffers around trails and recreation sites and more technical analytical methods based on displacement or avoidance of recreation sites. Options for mitigating negative effects of nonmotorized recreation on ungulates include timing and type-of-use restrictions, recreator education, and project design features to avoid human-ungulate conflicts. Public land managers can use this report by incorporating it by reference in NEPA analyses or as a general reference to find literature or identify gaps in the literature about the effects of noise from nonmotorized recreation on ungulates.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sir20255014","collaboration":"Prepared in cooperation with the Bureau of Land Management","usgsCitation":"Jordan, S.E., Ganz, T.R., Rutherford, T.K., Blocker, M.J., Domschke, C.T., Klasner, F.L., Masters, E.H., Morgan, T.A., Ratajczak, D.R., Teige, E.C., and Carter, S.K., 2025, Effects of nonmotorized recreation on ungulates in the western United States—A science synthesis to inform National Environmental Policy Act analyses: U.S. Geological Survey Scientific Investigations Report 2025–5014, 60 p., https://doi.org/10.3133/sir20255014.","productDescription":"x, 60 p.","onlineOnly":"Y","ipdsId":"IP-164198","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":489405,"rank":9,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255014/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":489396,"rank":8,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5014/sir20255014.xml","description":"SIR 2025-5014"},{"id":489395,"rank":7,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5014/images"},{"id":486381,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20235114","text":"Effects of Noise from Oil and Gas Development on Ungulates and Small Mammals—A Science Synthesis to Inform National Environmental Policy Act Analyses"},{"id":486387,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20245087","text":"Effects of Noise from Oil and Gas Development on Raptors and Songbirds—A Science Synthesis to Inform National Environmental Policy Act Analyses"},{"id":486378,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5014/coverthb2.jpg"},{"id":486382,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20235132","text":"Effects of Culverts on Habitat Connectivity in Streams—A Science Synthesis to Inform National Environmental Policy Act Analyses"},{"id":486379,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5014/sir20255014.pdf","text":"Report","size":"4.30 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5014"},{"id":486380,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/fs20243028","text":"Structured Science Syntheses to Inform Decision Making on Federal Public Lands"}],"contact":"Director, Fort Collins Science Center
U.S. Geological Survey
2150 Centre Ave., Bldg. C
Fort Collins, CO 80526-8118
The calcified structures of fishes provide insight into their periodic growth rates and can be combined with other biological variables to identify metrics such as size or age at maturity and mortality rates. Collecting this information on growth and life history can help evaluate the success of conservation efforts and inform future management decisions for a species in need. However, before these life history data can be applied to larger stock assessments that direct management decisions, confidence in the validity of the data needs to be reported through metrics of accuracy and precision. For this report, we assessed the bias and precision of paired reader estimations of spawning marks on scales of Blueback herring (Alosa aestivalis) collected in the U.S. Fish & Wildlife (USFWS) Annual Adult River Herring Stock Assessment for the lower Connecticut River basin. The paired reads on scales from a total of 8,698 fish over the ten years of the long term monitoring program were evaluated for the annual presence of systematic bias and precision using a combination of qualitative (i.e., frequency tables) and quantitative (i.e., Evan’s and Hoenig’s Test of Symmetry, and Coefficient of Variation (CV) calculations) analyses. While seven out of the ten survey years had systematic bias detected by the tests of symmetry, only three years (2013, 2016, 2018) had imprecision values >10% CV threshold. Data were further categorized into specific age classes within survey years to increase our resolution on where bias and imprecision was most prevalent. While the ability for accurate bias detection was limited by sufficient sample sizes (>25 fish), average imprecision values increased with age, and median age classes (4 through 6) commonly had bias detected. However, the removal of insufficient age classes prior to calculating average annual CV did not significantly change the initial average. Lastly, 2023, which was the first year to implement a standardized training procedure prior to production estimating, had the highest precision for both the annual average and specific age classes compared to all prior survey years. This standardized training procedure will continue to be used by USFWS for the lower Connecticut River tributaries, and can be modified for other river systems. Overall, this report’s results highlight the importance of assessing precision and encourage the standardization of spawning mark identification quality control and assurance for future studies. With more quality assessments and baseline information on precision and bias, there can be more beneficial discussion on defining thresholds and how to implement spawning history variability into catch curve analyses.
","language":"English","publisher":"U.S. Fish and Wildlife Service","doi":"10.3996/css36742600","usgsCitation":"Stephens, J.B., Jordaan, A., Perkins, D., Sprankle, K., and Roy, A.H., 2025, Quality assessment of past spawning mark estimations from a long-term survey in the Connecticut River watershed: Cooperator Science Series CSS-168-2025, ii, 72 p., https://doi.org/10.3996/css36742600.","productDescription":"ii, 72 p.","ipdsId":"IP-176656","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":494748,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Connecticut, Massachusetts","otherGeospatial":"Connecticut River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -72.96748212492314,\n 42.29494671693686\n ],\n [\n -72.95372317204433,\n 41.28995606733855\n ],\n [\n -72.16868601132036,\n 41.26947837383972\n ],\n [\n -72.16868601132036,\n 42.30090777357515\n ],\n [\n -72.96748212492314,\n 42.29494671693686\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2025-05-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Stephens, Jacqueline B.","contributorId":360502,"corporation":false,"usgs":false,"family":"Stephens","given":"Jacqueline","middleInitial":"B.","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":947139,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jordaan, Adrian","contributorId":257709,"corporation":false,"usgs":false,"family":"Jordaan","given":"Adrian","affiliations":[{"id":37201,"text":"UMass Amherst","active":true,"usgs":false}],"preferred":false,"id":947140,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Perkins, David","contributorId":342184,"corporation":false,"usgs":false,"family":"Perkins","given":"David","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":947141,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sprankle, Kenneth","contributorId":349559,"corporation":false,"usgs":false,"family":"Sprankle","given":"Kenneth","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":947142,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Roy, Allison H. 0000-0002-8080-2729 aroy@usgs.gov","orcid":"https://orcid.org/0000-0002-8080-2729","contributorId":4240,"corporation":false,"usgs":true,"family":"Roy","given":"Allison","email":"aroy@usgs.gov","middleInitial":"H.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":947143,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70267811,"text":"70267811 - 2025 - Monitoring visitor activity and informal trail disturbance in Yosemite Valley meadows to assess temporal changes in use and impacts","interactions":[],"lastModifiedDate":"2025-06-03T15:52:20.268589","indexId":"70267811","displayToPublicDate":"2025-05-22T08:47:23","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5520,"text":"Journal of Outdoor Recreation and Tourism","active":true,"publicationSubtype":{"id":10}},"title":"Monitoring visitor activity and informal trail disturbance in Yosemite Valley meadows to assess temporal changes in use and impacts","docAbstract":"Montane meadows provide vital habitat that supports ecosystems, regulate hydrological processes, and offer valuable recreational opportunities. Meadows account for 3 % of Yosemite National Park's area, including Yosemite Valley, and are particularly susceptible to human impacts such as formation of informal trails. We collected observational data on visitor activity and quantified social trail disturbance to compare with resource monitoring datasets and through similar parameters to Walden-Schreiner and Leung (2013) who studied visitor use and behavior in three Yosemite Valley meadows in 2011. We documented change in number of visitors per hour and primary activity pursued. We also compared trends of meadow disturbance (informal trail length and disturbed area) from the early 2000s - 2023. Informal trail length at El Capitan Meadow decreased from 2004 to 2018, followed by recent increases. Disturbed area for Cooks A, Sentinel A, Slaughterhouse B, Stoneman A, and Stoneman B sub-meadows increased from 2006 to 2023. Between 2011 and 2023, the proportion of those engaged in active versus stationary pursuits showed that visitors engaged in more active pursuits in two of three meadows. Moreover, there were >3.5 times more visitors per hour in Cooks, El Capitan, and Leidig meadows in 2023 compared to 2011, yet, most visitors utilized designated trails. Meadow locational context was linked to activity preference and types of impacts. Management strategies, such as fencing and signage have been effective at minimizing impacts in several meadows. Parsing nuances of informal trail use and drivers of disturbance for various meadows is crucial for informed park management decisions and actions.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jort.2025.100896","usgsCitation":"Shiflett, S., Jenkins, J., Mattos, R., Thiry, K., Ibsen, P.C., Booher, M., Tricomi, A., and Athearn, N.D., 2025, Monitoring visitor activity and informal trail disturbance in Yosemite Valley meadows to assess temporal changes in use and impacts: Journal of Outdoor Recreation and Tourism, v. 50, 100896, 13 p., https://doi.org/10.1016/j.jort.2025.100896.","productDescription":"100896, 13 p.","ipdsId":"IP-172211","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":490667,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jort.2025.100896","text":"Publisher Index Page"},{"id":489476,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Yosemite Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.73284138722612,\n 37.993305694720945\n ],\n [\n -119.73284138722612,\n 37.66294383877451\n ],\n [\n -119.39779065426013,\n 37.66294383877451\n ],\n [\n -119.39779065426013,\n 37.993305694720945\n ],\n [\n -119.73284138722612,\n 37.993305694720945\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"50","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Shiflett, Sheri A.","contributorId":347753,"corporation":false,"usgs":false,"family":"Shiflett","given":"Sheri A.","affiliations":[{"id":39509,"text":"National Park Service, Yosemite National Park","active":true,"usgs":false}],"preferred":false,"id":938991,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jenkins, Jeffery S.","contributorId":347754,"corporation":false,"usgs":false,"family":"Jenkins","given":"Jeffery S.","affiliations":[{"id":38695,"text":"University of California Merced","active":true,"usgs":false}],"preferred":false,"id":938992,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mattos, Rachel F.","contributorId":347755,"corporation":false,"usgs":false,"family":"Mattos","given":"Rachel F.","affiliations":[{"id":39509,"text":"National Park Service, Yosemite National Park","active":true,"usgs":false}],"preferred":false,"id":938993,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thiry, Kai","contributorId":356273,"corporation":false,"usgs":false,"family":"Thiry","given":"Kai","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":938994,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ibsen, Peter Christian 0000-0002-3436-9100","orcid":"https://orcid.org/0000-0002-3436-9100","contributorId":260735,"corporation":false,"usgs":true,"family":"Ibsen","given":"Peter","email":"","middleInitial":"Christian","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":938995,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Booher, Melissa","contributorId":356275,"corporation":false,"usgs":false,"family":"Booher","given":"Melissa","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":938996,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Tricomi, Angela","contributorId":356276,"corporation":false,"usgs":false,"family":"Tricomi","given":"Angela","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":938997,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Athearn, Nicole D","contributorId":221011,"corporation":false,"usgs":false,"family":"Athearn","given":"Nicole","email":"","middleInitial":"D","affiliations":[{"id":40310,"text":"NPS, Yosemite National Park, CA","active":true,"usgs":false}],"preferred":false,"id":938998,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70266892,"text":"sir20255032 - 2025 - Flood-inundation maps for 14.8 miles of Little and Big Papillion Creeks in Omaha, Nebraska, 2023","interactions":[],"lastModifiedDate":"2025-08-07T21:16:38.983416","indexId":"sir20255032","displayToPublicDate":"2025-05-21T08:56:33","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":"2025-5032","displayTitle":"Flood-Inundation Maps for 14.8 Miles of Little and Big Papillion Creeks in Omaha, Nebraska, 2023","title":"Flood-inundation maps for 14.8 miles of Little and Big Papillion Creeks in Omaha, Nebraska, 2023","docAbstract":"Digital flood-inundation map libraries for two reaches that constitute 14.8 miles of Little and Big Papillion Creeks in Omaha, Nebraska, were created by the U.S. Geological Survey (USGS) in cooperation with the Papio-Missouri River Natural Resource District. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Program website at https://www.usgs.gov/mission-areas/water-resources/science/flood-inundation-mapping-fim-program, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at Little Papillion Creek at Irvington, Nebr. (USGS station 06610750), Little Papillion Creek at Ak-Sar-Ben at Omaha, Nebr. (USGS station 06610765), and Big Papillion Creek at Q Street at Omaha, Nebr. (USGS station 06610770) streamgages. Near-real-time stages at these streamgages may be obtained from the USGS National Water Information System database at https://doi.org/10.5066/F7P55KJN or from the National Weather Service Advanced Hydrologic Prediction Service at https://water.weather.gov/ahps/.
Flood profiles were computed for two different reaches that constitute 14.8 miles of stream length in the study area by using hydraulic models. The models were calibrated by adjusting roughness coefficients to best represent the current (2022) stage-streamflow relation at the streamgages within the study reach.
The hydraulic models were then used to compute water-surface profiles at 1-foot stage intervals for selected stage ranges to represent various flooding scenarios at the streamgages in each reach. The simulated water-surface profiles then were combined with a digital elevation model using a geographic information system, which had a 10-foot grid spacing to delineate the flooding extents and water depths for each stage. The availability of these flood-inundation maps, along with information regarding current stage from the USGS streamgages, can provide emergency management personnel and residents with information that is critical for flood response activities and post flood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255032","collaboration":"Prepared in cooperation with the Papio-Missouri River Natural Resource District","usgsCitation":"Strauch, K.R., and Hoefer, B.R., 2025, Flood-inundation maps for 14.8 miles of Little and Big Papillion Creeks in Omaha, Nebraska, 2023: U.S. Geological Survey Scientific Investigations Report 2025–5032, 14 p., https://doi.org/10.3133/sir20255032.","productDescription":"Report: vi, 14 p.; Data Release; Dataset","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-152753","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":493771,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118579.htm","linkFileType":{"id":5,"text":"html"}},{"id":485915,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5032/coverthb.jpg"},{"id":485916,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5032/sir20255032.pdf","text":"Report","size":"2.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5032"},{"id":485920,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5032/sir20255032.XML"},{"id":485921,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5032/images/"},{"id":485922,"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":485923,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9OU7E42","text":"USGS data release","linkHelpText":"Flood-inundation geospatial datasets for 14.8 miles of the Little and Big Papillion Creeks in Omaha, Nebraska, 2023"},{"id":485924,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255032/full"}],"country":"United States","state":"Nebraska","city":"Omaha","otherGeospatial":"Little and Big Papillion Creeks","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -96.15305796306968,\n 41.36725587936067\n ],\n [\n -96.15305796306968,\n 41.117996650104345\n ],\n [\n -95.92667071234595,\n 41.117996650104345\n ],\n [\n -95.92667071234595,\n 41.36725587936067\n ],\n [\n -96.15305796306968,\n 41.36725587936067\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Nebraska Water Science Center
U.S. Geological Survey
5231 South 19th Street
Lincoln, NE 68512
In species inhabiting stressful environments, some individuals experience negative growth in body mass during their lives, potentially influencing survival, reproduction, populations, and ecosystems. Using data from a long-term (1997–2015) study of brook trout (Salvelinus fontinalis), brown trout (Salmo trutta), and juvenile Atlantic salmon (Salmo salar) in Massachusetts, USA, we analyzed the frequency, causes, and consequences of seasonal mass loss. Negative growth occurred in 14.8% of observations (3573 instances), with the highest prevalence during summer (June–September). Species differed markedly: 42.5% of juvenile Atlantic salmon, 24.9% of brook trout, but only 7.7% of brown trout exhibited negative growth. The likelihood of mass loss increased with size, age, and low stream flows, particularly in summer. Brook trout in the small or isolated tributaries exhibited less summer mass loss than those in the larger streams. Other factors, including temperature and population density, had minimal or inconsistent effects. Individuals experiencing negative growth, especially brook trout in summer and autumn, were less likely to be re-encountered. As we observed no association of mass loss with movement, this suggests a potential survival cost of negative body mass growth.
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