The role of hybridization in diversification is complex and may result in many possible outcomes. Not only can hybridization produce new lineages, but those lineages may contain unique combinations of adaptive genetic variation derived from parental taxa that allow hybrid-origin lineages to occupy unique environmental space relative to one (or both) parents. We document such a case of hybridization between two sedge species, Carex nova and Carex nelsonii (Cyperaceae), that occupy partially overlapping environmental space in the southern Rocky Mountains, USA. In the region hypothesized to be the origin of the hybrid lineage, one parental taxon (C. nelsonii) is at the edge of its environmental tolerance. Hybrid-origin individuals display mixed ancestry between the parental taxa – of nearly 7,000 unlinked loci sampled, almost 30% showed evidence of excess ancestry from one parental lineage – approximately half displayed a genomic background skewed towards one parent, and half skewed towards the other. To test whether excess ancestry loci may have conferred an adaptive advantage to the hybrid-origin lineage, we conducted genotype-environment association analyses on different combinations of loci – with and without excess ancestry – and with multiple contrasts between the hybrids and parental taxa. Loci with skewed ancestry showed significant environmental associations distinguishing the hybrid lineage from one parent (C. nelsonii), whereas loci with relatively equal representation of parental ancestries showed no such environmental associations. Moreover, the overwhelming majority of candidate adaptive loci with respect to environmental gradients also had excess ancestry from a parental lineage, implying these loci have facilitated the persistence of the hybrid lineage in an environment unsuitable to at least one parent.
The U.S. Geological Survey (USGS) Central Midwest Water Science Center (CMWSC) includes three States—Illinois, Iowa, and Missouri. USGS water science centers across the Nation provide information on water resources including streamflow, water use, water availability, and the quality of surface water and groundwater (https://www.usgs.gov/mission-areas/water-resources).
The USGS CMWSC Harmful Algal Blooms (HABs) team is dedicated to studying the complexity of HABs and is currently (2021) researching ways to better predict the timing, magnitude, and toxicity of HABs. Updated information about the HABs team including current projects, data releases, and publications are available on the CMWSC website (https://www.usgs.gov/centers/cm-water/science-topics/harmful-algal-blooms).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20223011","usgsCitation":"Summers, K.M., Krempa, H.M., and Garrett, J.D., 2022, Central Midwest Water Science Center— Harmful Algal Blooms team: U.S. Geological Survey Fact Sheet, 2022–3011, 4 p., https://doi.org/10.3133/fs20223011.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"N","ipdsId":"IP-132581","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":400625,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20223011/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":400591,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2022/3011/images"},{"id":400590,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2022/3011/fs20223011.XML"},{"id":400589,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2022/3011/fs20223011.pdf","text":"Report","size":"7.79 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2022-3011"},{"id":400588,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2022/3011/coverthb.jpg"}],"contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
405 North Goodwin
Urbana, IL 61801
The alteration of thermal regimes, including increased temperatures and shifts in seasonality, is a key challenge to the health and survival of federally protected cold-water salmonids in streams of the Willamette River basin in northwestern Oregon. To better support threatened fish species, the U.S. Army Corps of Engineers (USACE) and other water managers seek to improve the thermal regime in the Willamette River and key tributaries downstream of USACE dams by utilizing strategically timed flow releases from USACE dams. To inform flow management decisions, regression relations were developed for 12 Willamette River basin locations below USACE dams relating stream temperature with streamflow and air temperature utilizing publicly available datasets spanning 2000–18. The resulting relations provide simple tools to investigate stream temperature responses to changes in streamflow and climatic conditions in the Willamette River system.
Regression relations on the Willamette River and key tributaries show that, at locations sufficiently distant from the direct temperature influence of upstream dam releases, air temperature and streamflow are reasonable proxies to predict the 7-day average of the daily mean (7dADMean) and 7-day average of the daily maximum (7dADMax) water temperature with errors generally ≤1 degrees Celsius (°C). To account for seasonal variations in the relation between air temperature, streamflow, and stream temperature, a transition-smoothed, seasonal regression approach was used. Stream temperature is inversely correlated with streamflow in all seasons except “winter” (January–March), when it is relatively independent. Stream temperature is positively correlated with air temperature in all seasons, but the slope decreases at very low or very high air temperatures. Generally, fit is best for seasonal models “winter” (January–March), “spring” (April–May), “summer” (June–August), and “early autumn” (September–October). Error in “autumn” (November–December) is larger, probably due to variation in the onset timing of winter storms.
Simulated results from a climatological analysis of predicted stream temperature suggest that, excluding extremes and accounting for some seasonal variability, the 7dADMean and 7dADMax stream temperature sensitivity to air temperature and streamflow varies by location on the river. To investigate the potential range of stream temperature variability based on historical air temperature and streamflow conditions, stream temperature predictions were calculated using synthetic time series comprised of daily temperature values representing the 0.10, 0.33, 0.50, 0.67, and 0.90 quantile of air temperature and streamflow from 1954 (the year meaningful streamflow augmentation began) to 2018. Results show that from a “very hot” (0.90 quantile) and “very dry” (0.10 quantile) year to a “very cool” (0.10 quantile) and “very wet” (0.90; all quantiles from 1954 to 2018) year, the stream temperature sensitivity to air temperature and streamflow is about 3 °C at Harrisburg (river mile 161.0) and increases to about 5 °C at Keizer (river mile 82.2). While the number of days exceeding regulatory criteria are fewer in cooler, wetter years than in warmer, dryer years, the models suggest that the Willamette River will likely continue to exceed the State of Oregon maximum water-temperature criterion of 18 °C for sustained periods from late spring to early autumn and that the flow management practices evaluated in this study, while effective at influencing stream temperature, likely cannot prevent many or all such exceedances.
As modeled for 2018, a representative very hot year with normal to below-normal streamflow, stream temperature sensitivity to changes in streamflow of ±100 to ±1000 cubic feet per second produced mean monthly temperature changes from 0.0 to 1.4 °C at Keizer, Albany, and Harrisburg during summer. For a specified change in flow, temperature sensitivity is greater at upstream locations where streamflow is less than that at downstream locations because the change in streamflow is a greater percentage of total streamflow at upstream locations. Similarly, temperature response to a set change in flow is greater in the summer and early autumn low-flow season than in spring when flows are higher. The regression models developed in this study thus indicate that flow management is likely to have a greater effect on stream temperature at upstream locations (such as Harrisburg or Albany) and during the low-flow season than at downstream locations (such as Keizer) or during periods of higher streamflow.
","largerWorkType":{"id":18,"text":"Report"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215022","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Portland District","usgsCitation":"Stratton Garvin, L.E., Rounds, S.A., and Buccola, N.L., 2022, Estimating stream temperature in the Willamette River Basin, northwestern Oregon—A regression-based approach: U.S. Geological Survey Scientific Investigations Report 2021–5022, 40 p., https://doi.org/10.3133/sir20215022.","productDescription":"Report: viii, 40 p.; Data Release","numberOfPages":"40","onlineOnly":"Y","ipdsId":"IP-119336","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":501948,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113055.htm","linkFileType":{"id":5,"text":"html"}},{"id":400563,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PALKQZ","text":"USGS Data Release","description":"Stratton Garvin, L.E., 2022, Stream temperature predic tions for the Willamette River Basin, northwestern Oregon estimated from regression equations (1954–2018): U.S. Geological Survey data release, https://doi.org/10.5066/P9PALKQZ.","linkHelpText":"Stream temperature predictions for the Willamette River Basin, northwestern Oregon estimated from regression equations (1954–2018)"},{"id":400560,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5022/sir20215022.pdf","text":"Report","size":"8.5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":400559,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5022/covrthb.jpg"},{"id":400561,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5022/sir20215022.xml"},{"id":400562,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5022/images"}],"country":"United States","state":"Oregon","otherGeospatial":"Willamette River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.64013671874999,\n 43.54854811091286\n ],\n [\n -122.18994140624999,\n 43.54854811091286\n ],\n [\n -122.18994140624999,\n 45.99696161820381\n ],\n [\n -123.64013671874999,\n 45.99696161820381\n ],\n [\n -123.64013671874999,\n 43.54854811091286\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
Operators of wind power facilities can mitigate wildlife mortality by slowing or stopping wind turbines (hereafter ‘curtail’) when birds are at an increased risk of collision. Some facility operators curtail when individual birds have flight characteristics (e.g. altitude, distance or relative bearing of a bird's flight path) that exceed some threshold value, but thresholds currently in use have not been empirically evaluated. Overly restrictive thresholds can cause turbine curtailment for birds that never enter rotor-swept zones, thereby resulting in excess power loss. We evaluated the probability that birds, specifically eagles, entered the rotor-swept zone (hereafter ‘entry probability’) in response to their flight characteristics. We used an automated monitoring system to classify individuals as eagles or non-eagles and record flight paths of purported eagles at a wind facility in Wyoming, USA. We used logistic regression with occupancy dynamics and a distance-dependent colonization process to model entry probability. As a result, this model allowed entry probability to decrease with horizontal distance to the nearest turbine. The probability of entry varied with distance to the nearest turbine and approached zero when that distance was more than 202 m. Entry probability peaked when eagles flew 89 m above ground, corresponding to hub heights of turbines (80 m), and decreased to near-zero at altitudes of 189 m or more. Entry probabilities were greatest when flight paths were near the rotor-swept zone and when eagles flew slowly toward the nearest turbine. Compass bearing of a flight path was not associated with entry probability. Our model accurately forecasted entry probability in Wyoming (area under the curve (AUC) = 0.96) and was transferable to another facility in California, USA (AUC = 0.97); therefore, our results may be applicable across a variety of settings. Curtailment criteria can be based on flight path characteristics to forecast entry into rotor-swept zones. The use of distance and altitude thresholds when making curtailment decisions is justified. However, this analysis suggests alteration of the time to collision threshold, with curtailment initiated at greater distances as the speed of the bird decreases. Our novel modelling method and our results can inform curtailment criteria in any situation where curtailment decisions are made in real-time.
","language":"English","publisher":"Wiley","doi":"10.1111/ibi.13076","usgsCitation":"Rolek, B.W., Braham, M., Miller, T.A., Duerr, A.E., Katzner, T., McCabe, J.D., Dunn, L., and McClure, C.J., 2022, Flight characteristics forecast entry by eagles into rotor-swept zones of wind turbines: Ibis, v. 164, no. 4, p. 968-980, https://doi.org/10.1111/ibi.13076.","productDescription":"13 p.","startPage":"968","endPage":"980","ipdsId":"IP-136356","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":447812,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ibi.13076","text":"Publisher Index Page"},{"id":401974,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","county":"Converse County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-104.8991,43.5008],[-104.9001,43.478],[-104.8996,43.4488],[-104.9002,43.3933],[-104.9009,43.3633],[-104.9018,43.2732],[-104.9019,43.1321],[-104.9019,43.1175],[-104.9014,43.0738],[-104.8992,42.8704],[-104.8941,42.6915],[-104.8915,42.6105],[-105.0674,42.6073],[-105.1853,42.6058],[-105.2639,42.6043],[-105.2807,42.6038],[-105.2818,42.4324],[-105.2899,42.4326],[-105.3005,42.4319],[-105.3024,42.4315],[-105.3055,42.4311],[-105.313,42.4308],[-105.3248,42.4306],[-105.3252,42.4201],[-105.3251,42.4065],[-105.3437,42.4064],[-105.3442,42.3769],[-105.3641,42.3768],[-105.3637,42.3218],[-105.3805,42.3217],[-105.3794,42.3017],[-105.3804,42.2922],[-105.4765,42.2913],[-105.515,42.2907],[-105.5361,42.2902],[-105.5733,42.2909],[-105.5932,42.2908],[-105.5927,42.3049],[-105.6125,42.3053],[-105.6126,42.3203],[-105.6128,42.3344],[-105.6129,42.3489],[-105.6125,42.3771],[-105.5746,42.3773],[-105.5748,42.3918],[-105.5749,42.4068],[-105.555,42.4069],[-105.5554,42.4301],[-105.653,42.4301],[-105.6722,42.4304],[-105.7307,42.431],[-105.7511,42.4318],[-105.8885,42.4323],[-105.922,42.4324],[-105.9419,42.4323],[-105.9612,42.4326],[-105.9811,42.4329],[-106.0009,42.4327],[-106.0239,42.4326],[-106.0749,42.4325],[-106.0735,42.4611],[-106.075,42.5193],[-106.0753,42.5752],[-106.0755,42.5898],[-106.0753,42.6643],[-106.0765,42.7789],[-106.0684,42.7792],[-106.0699,42.8588],[-106.0726,43.0089],[-106.0722,43.0235],[-106.0724,43.039],[-106.0724,43.0826],[-106.072,43.0972],[-106.0721,43.1395],[-106.0717,43.154],[-106.0715,43.2268],[-106.0711,43.241],[-106.0709,43.271],[-106.0705,43.2851],[-106.0696,43.3415],[-106.0687,43.3706],[-106.0683,43.387],[-106.0671,43.4734],[-106.0671,43.4944],[-106.0204,43.4946],[-105.6833,43.4973],[-105.5236,43.4976],[-105.5028,43.4977],[-105.4018,43.498],[-105.362,43.4981],[-105.3418,43.4981],[-105.3216,43.4977],[-105.302,43.4978],[-105.2818,43.4978],[-105.2616,43.4979],[-105.242,43.4984],[-105.0817,43.4981],[-105.064,43.4982],[-104.9787,43.4999],[-104.9376,43.5008],[-104.9187,43.5008],[-104.8991,43.5008]]]},\"properties\":{\"name\":\"Converse\",\"state\":\"WY\"}}]}","volume":"164","issue":"4","noUsgsAuthors":false,"publicationDate":"2022-06-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Rolek, Brian W.","contributorId":200318,"corporation":false,"usgs":false,"family":"Rolek","given":"Brian","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":844398,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Braham, Melissa A.","contributorId":140127,"corporation":false,"usgs":false,"family":"Braham","given":"Melissa A.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":844399,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, Tricia A.","contributorId":190591,"corporation":false,"usgs":false,"family":"Miller","given":"Tricia","email":"","middleInitial":"A.","affiliations":[{"id":16210,"text":"Division of Forestry and Natural Resources, West Virginia University","active":true,"usgs":false}],"preferred":false,"id":844400,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Duerr, Adam E.","contributorId":190590,"corporation":false,"usgs":false,"family":"Duerr","given":"Adam","email":"","middleInitial":"E.","affiliations":[{"id":16210,"text":"Division of Forestry and Natural Resources, West Virginia University","active":true,"usgs":false}],"preferred":false,"id":844401,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":191353,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":844402,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McCabe, Jennifer D.","contributorId":264224,"corporation":false,"usgs":false,"family":"McCabe","given":"Jennifer","email":"","middleInitial":"D.","affiliations":[{"id":54406,"text":"The Peregrine Fund, Boise, Idaho","active":true,"usgs":false}],"preferred":false,"id":844403,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dunn, Leah","contributorId":217944,"corporation":false,"usgs":false,"family":"Dunn","given":"Leah","email":"","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":844404,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McClure, Christopher J.W.","contributorId":264223,"corporation":false,"usgs":false,"family":"McClure","given":"Christopher","email":"","middleInitial":"J.W.","affiliations":[{"id":54406,"text":"The Peregrine Fund, Boise, Idaho","active":true,"usgs":false}],"preferred":false,"id":844405,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70231653,"text":"70231653 - 2022 - Estimating occupancy from autonomous recording unit data in the presence of misclassifications and detection heterogeneity","interactions":[],"lastModifiedDate":"2022-08-15T13:51:56.290092","indexId":"70231653","displayToPublicDate":"2022-05-12T07:23:39","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Estimating occupancy from autonomous recording unit data in the presence of misclassifications and detection heterogeneity","docAbstract":"1. Autonomous Recording Units (ARUs) are now widely used to survey communities of species. These surveys generate spatially and temporally replicated counts of unmarked animals, but such data typically include false negatives and misclassified detections, both of which may vary across sites in proportion to abundance. These data challenges can bias estimates of occupancy, and the typical approach of verifying individual detections is expensive.
2. We developed a Bayesian implementation of a two-species, false-positive N-mixture model for estimating occupancy from ARU data or other counts of unmarked animals that does not require manual verification. The model accounts for species misclassification and abundance-induced detection heterogeneity, as well as false negatives. To evaluate this model, we simulated 200 data sets for each of 29 scenarios, including scenarios in which misclassifications outnumbered correct classifications for rare species. We also applied the model to acoustic surveys of bats conducted on Fort Carson Army Post and Piñon Canyon Maneuver Site, Colorado, USA.
3. In the simulation study, bias, coverage, and root mean square error for occupancy estimates obtained from the two-species false-positive N-mixture model were superior to metrics obtained from two competing two-species false-positive occupancy models. Across 29 scenarios, absolute bias was consistently low (range: -0.03–0.07), while coverage averaged 93% (range: 74%–98%). For alternative occupancy models, absolute bias was often high (range: -0.36–0.39), and coverage averaged from 47%–65%. Although our model included an abundance parameter, abundance estimates were not reliable. For two species of Myotis bats, we estimated that 1%–5% of field-recorded detections were misclassified. Estimated occupancy (0.91 and 0.76) was lower than naïve estimates (1.00 and 0.94). Competing occupancy models implausibly estimated local occupancy of 0.00 at sites with numerous detections.
4. Our two-species, false-positive N-mixture model is significant because it accounts for detection heterogeneity and improves occupancy estimates without expensive manual verification of detections. Our field application indicated that misclassifications were not common, yet affected occupancy inferences. Given that ARUs are increasingly used to survey a broad range of taxa, such an occupancy model could be widely useful.
","language":"English","publisher":"Wiley","doi":"10.1111/2041-210X.13895","usgsCitation":"Clement, M., Royle, A., and Mixan, R., 2022, Estimating occupancy from autonomous recording unit data in the presence of misclassifications and detection heterogeneity: Methods in Ecology and Evolution, v. 13, no. 8, p. 1719-1729, https://doi.org/10.1111/2041-210X.13895.","productDescription":"11 p.","startPage":"1719","endPage":"1729","ipdsId":"IP-139383","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":447816,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/2041-210x.13895","text":"Publisher Index Page"},{"id":400804,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"8","noUsgsAuthors":false,"publicationDate":"2022-05-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Clement, Matt","contributorId":291855,"corporation":false,"usgs":false,"family":"Clement","given":"Matt","email":"","affiliations":[{"id":62776,"text":"AZ fish and game","active":true,"usgs":false}],"preferred":false,"id":843247,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":146229,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","email":"aroyle@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":843250,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mixan, Ronald","contributorId":291857,"corporation":false,"usgs":false,"family":"Mixan","given":"Ronald","email":"","affiliations":[{"id":62778,"text":"AZ Game and Fish Dept","active":true,"usgs":false}],"preferred":false,"id":843251,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70231577,"text":"70231577 - 2022 - A validation of satellite derived cyanobacteria detections with state reported events and recreation advisories across U.S. lakes","interactions":[],"lastModifiedDate":"2022-05-16T11:44:17.159917","indexId":"70231577","displayToPublicDate":"2022-05-12T06:20:12","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1878,"text":"Harmful Algae","active":true,"publicationSubtype":{"id":10}},"title":"A validation of satellite derived cyanobacteria detections with state reported events and recreation advisories across U.S. lakes","docAbstract":"Cyanobacteria harmful algal blooms (cyanoHABs) negatively affect ecological, human, and animal health. Traditional methods of validating satellite algorithms with data from water samples are often inhibited by the expense of quantifying cyanobacteria indicators in the field and the lack of public data. However, state recreation advisories and other recorded events of cyanoHAB occurrence reported by local authorities can serve as an independent and publicly available dataset for validation. State recreation advisories were defined as a period delimited by a start and end date where a warning was issued due to detections of cyanoHABs over a state's risk threshold. State reported events were defined as any event that was documented with a single date related to cyanoHABs. This study examined the presence-absence agreement between 160 state reported cyanoHAB advisories and 1,343 events and cyanobacteria biomass estimated by a satellite algorithm called the Cyanobacteria Index (CIcyano). The true positive rate of agreement with state recreation advisories was 69% and 60% with state reported events. CIcyano detected a reduction or absence in cyanobacteria after 76% of the recreation advisories ended. CIcyano was used to quantify the magnitude, spatial extent, and temporal frequency of cyanoHABs; each of these three metrics were greater (r > 0.2) during state recreation advisories compared to non-advisory times with effect sizes ranging from small to large. This is the first study to quantitatively evaluate satellite algorithm performance for detecting cyanoHABs with state reported events and advisories and supports informed management decisions with satellite technologies that complement traditional field observations.
The ability of young fish to find and consume food during early life history is an important factor affecting survival and recruitment. While dietary assessments for age-0 Scaphirhynchus sturgeon (shovelnose sturgeon and pallid sturgeon) in the Missouri River, USA have received increased attention over the last 15 years, there is currently limited information available to evaluate long-term trends in prey consumption and body condition. To better understand interannual factors during early-life history, we examined foraging and body condition of age-0 (<12.0 cm) Scaphirhynchus in relation to discharge and the availability of hypothesized foraging and food-producing habitats at a single reach (Lexington) of the Missouri River over a span of five years (2014–2018). Relatively high discharge in 2015 led to concomitant maxima in foraging and lipid levels for age-0 sturgeon. However, lower water levels in 2014 did not see declines in lipid content as would be expected given the low level of foraging observed that year. Additionally, the availability of hypothesized foraging and food-producing habitats had little effect on age-0 sturgeon prey consumption and condition in the Lexington Reach. Our results suggest that other factors in addition to river discharge may affect age-0 sturgeon foraging and condition and more research focused on understanding the flow-habitat relationships would be critical.
Increased fire size and frequency coupled with annual grass invasion pose major challenges to sagebrush (Artemisia spp.) ecosystem conservation, which is currently focused on protecting sagebrush community composition and structure. A common strategy for mitigating potential fire is to use fuel treatments that alter the structure and amount of burnable material, thus reducing fire behavior and creating access points for fire suppression resources. While there is some recent information on the impacts of fuel treatments on ecological communities, we have little information on fuel treatment effectiveness at modifying fire behavior in sagebrush ecosystems. We present 10 years of data on fuel accumulation and the resultant modeled fire behavior in prescribed fire, mowed, herbicide (tebuthiuron or imazapic), and untreated control plots in the Sagebrush Treatment Evaluation Project (SageSTEP) network in the Great Basin, USA. Fuel data (i.e., aboveground burnable live and dead biomass) were collected in each treatment plot at Years 0 (pretreatment), 1, 2, 3, 6, and 10 posttreatment. We used the Fuel and Fire Tool fire behavior modeling program to test whether treatments impacted potential fire behavior. Prescribed fire initially removed 49% of the total fuel load and 75% of shrubs, and fuel loads remained reduced through Year 10. Mowing shifted fuels from the shrub canopy to the ground surface but did not change the total fuel amount. Prescribed fire and mowing increased herbaceous fuel by the second posttreatment year and that trend persisted through Year 10. Tebuthiuron treatments were ineffective at altering fuel loads. Imazapic suppressed herbaceous vegetation by 30% in Years 2 and 3 following treatment. The modified fuel beds in fire and mow treatments resulted in modeled flame lengths that were significantly lower than untreated control plots for the duration of the study, with shorter term reductions in reaction intensity and rate of spread. Understanding fuel treatment effectiveness will allow natural resource managers to evaluate trade-offs between protecting wildlife habitat and reducing the potential for high-intensity wildfire.
The researcher's lament is shared by many environmental and conservation scientists who complain about the little support they receive for their research proposals during the review and selection process. Understandably, any hopes of having their anticipated scientific findings applied toward the formulation of environmental management decisions or natural resource policy action are shattered. They attribute this lack of endorsement to shortcomings and limitations among decision makers and proposal selection officials when, in many cases, the rejection of project proposals is often a function of a handful of self-inflicted failures by applied scientists who anchor themselves stubbornly to doomed approaches. Familiar deficiencies in their research proposals perpetuate the disconnect between the enterprise of science and real-world resource management challenges. Researchers themselves can affect conditions that turn up the appetite for their scientific endeavors as a more meaningful component of the decision-making process, namely, to stage and deliver science that is more readily \"actionable.\" Perhaps it is time for them to consider a course correction to improve the viability of their actionable science proposals. A few basic steps may help rejigger the science planning process in this direction and, consequently, help avoid the researcher's lament. The likelihood of gaining support during the proposal review and award adjudication process, and securing practical application of scientific products, increases when the products are (1) the result of active engagement of researchers with decision makers; (2) better connected to social and political priorities; (3) clearly designed to inform specific management decisions; and (4) tailored to fit the needs of targeted end users. These considerations and activities exist beyond the comfort zone of many environmental or conservation scientists. Yet, those who adopt them will spend less time lamenting rejection and become more influential in the production of actionable knowledge.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.4044","usgsCitation":"Bisbal, G.A., 2022, The researcher's lament: Why do they ignore my science?: Ecosphere, v. 13, no. 5, e4044, 8 p., https://doi.org/10.1002/ecs2.4044.","productDescription":"e4044, 8 p.","ipdsId":"IP-130726","costCenters":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":447824,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4044","text":"Publisher Index Page"},{"id":412693,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"5","noUsgsAuthors":false,"publicationDate":"2022-05-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Bisbal, Gustavo A. 0000-0002-6674-9941","orcid":"https://orcid.org/0000-0002-6674-9941","contributorId":213767,"corporation":false,"usgs":true,"family":"Bisbal","given":"Gustavo","email":"","middleInitial":"A.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":863369,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70231235,"text":"sir20225018 - 2022 - Characterization of and relations among precipitation, streamflow, suspended-sediment, and water-quality data at the U.S. Army Garrison Fort Carson and Piñon Canyon Maneuver Site, Colorado, water years 2016–18","interactions":[],"lastModifiedDate":"2022-05-27T15:09:06.333588","indexId":"sir20225018","displayToPublicDate":"2022-05-11T14:34:07","publicationYear":"2022","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":"2022-5018","displayTitle":"Characterization of and Relations Among Precipitation, Streamflow, Suspended-Sediment, and Water-Quality Data at the U.S. Army Garrison Fort Carson and Piñon Canyon Maneuver Site, Colorado, Water Years 2016–18","title":"Characterization of and relations among precipitation, streamflow, suspended-sediment, and water-quality data at the U.S. Army Garrison Fort Carson and Piñon Canyon Maneuver Site, Colorado, water years 2016–18","docAbstract":"Frequent and prolonged military training maneuvers are an intensive type of land use that may disturb land cover, compact soils, and have lasting effects on adjacent stream hydrology and ecosystems. To better understand the potential effect of military training on hydrologic and environmental processes, the U.S. Geological Survey in cooperation with the U.S. Army established hydrologic and water-quality data-collection networks at the U.S. Army Garrison Fort Carson (AGFC) in 1978 and at the Piñon Canyon Maneuver Site (PCMS) in 1982. The purpose of this report is to present precipitation, streamflow, suspended-sediment, and water-quality data collected by the U.S. Geological Survey at the AGFC and PCMS for water years (WYs) 2016–18 and to evaluate those data in relation to long-term data from the AGFC and PCMS. In WYs 2016–18, the U.S. Geological Survey monitored 26 sites on the AGFC and 17 sites on the PCMS for precipitation amount, streamflow, suspended sediment, and (or) water quality.
On the AGFC, total annual precipitation in WYs 2016–18 was larger than the long-term mean for all 3 years at Rod and Gun Meteorologic Station at Fort Carson, CO (Rod and Gun). There were statistically significant upward trends in annual precipitation at Rod and Gun and Young Hollow Meteorologic Station at Fort Carson, CO (Young Hollow) with slopes of 1.25 and 0.66 inches per year (in/yr), respectively. The precipitation totals for WY 2017 were either the largest on record or in the top three for both sites and at Sullivan Park Meteorologic Station at Fort Carson, CO. On the PCMS, total annual precipitation was larger than the long-term mean in WYs 2016–18 at Brown Sheep Camp Meteorologic Station near Tyrone, CO; CIG Pipeline South Meteorologic Station near Simpson, CO; Bear Springs Hills Meteorologic Station near Houghton, CO (Bear Springs); and Upper Red Rock Canyon Meteorologic Station near Houghton, CO (Upper Red Rock). There were statistically significant upward trends in precipitation at Bear Springs and Upper Red Rock with slopes of 0.16 and 0.19 in/yr, respectively. The precipitation totals for WY 2017 were the largest on record for all sites except for Upper Bent Canyon Meteorological Station near Delhi, CO.
Streamflow was calculated at 18 sites on the AGFC and 7 sites on the PCMS in at least 1 of WYs 2016–18. At AGFC, mean annual (or seasonal) streamflow in WYs 2016–18 was less than the long-term mean at 7 sites and greater than the long-term mean at 3 sites. There were statistically significant downward trends in mean annual or seasonal streamflow at Womack Ditch from Little Fountain Creek near Fort Carson, CO, and Ripley Ditch from Little Fountain Creek at Fort Carson, CO, with slopes of −0.036 and −0.028 cubic feet per second per year (ft3/s/y), respectively; and a significant upward trend in streamflow at Turkey Creek West Seepage below Teller Reservoir near Stone City, CO, with a slope of less than 0.001 ft3/s/y. Unlike for precipitation, the mean annual or seasonal streamflow for WY 2017 was not in the top 3 for any of the 12 sites with measured flow.
At the PCMS, mean annual (or seasonal) streamflow was less than the long-term mean streamflow in WYs 2016–18 at the Taylor Arroyo below Rock Crossing near Thatcher, CO, and Bent Canyon Creek at Mouth near Timpas, CO, sites; and in WYs 2016 and 2018 at the Purgatoire River near Thatcher, CO (Purgatoire Thatcher), and Purgatoire River at Rock Crossing near Timpas, CO (Purgatoire Rock Crossing). There were no statistically significant trends in mean annual (or seasonal) streamflow at sites on the PCMS, and unlike for precipitation, the mean streamflow for WY 2017 was not in the top three for any sites except Purgatoire Rock Crossing. In WYs 2016–18, streamflow from sites on the AGFC and PCMS represented only a small fraction of streamflow in Fountain Creek or the Purgatoire River, and changes in streamflow that resulted from military maneuvers on the AGFC and PCMS were not likely to be detected in the downstream receiving waters.
Suspended-sediment concentrations, loads, and yields for WYs 2016–18, were analyzed at two sites on the AGFC and five sites on the PCMS. On the AGFC, mean seasonal suspended-sediment concentrations ranged from 3.10 to 155 milligrams per liter (mg/L), mean seasonal suspended-sediment loads ranged from 0.04 to 27.1 tons per day (t/d), and seasonal suspended-sediment yields ranged from 0.28 to 216 tons per season per square mile (t/s/mi2). Suspended-sediment yields at the two AGFC sites in WYs 2016–18 were all less than the long-term means. On the PCMS, mean seasonal suspended-sediment concentrations (at sites with some streamflow during a WY) ranged from 1.12 to 41.8 mg/L, mean suspended-sediment loads ranged from 0.01 to 13.1 t/d, and seasonal suspended-sediment yields ranged from 0.06 to 57.4 t/s/mi2. Suspended-sediment yields at the five PCMS sites in WYs 2016–18 were all less than the long-term means. In WYs 2016–18, mean daily suspended-sediment loads at Little Fountain were 1.3, 2.5, and 7.6 percent, respectively, of the mean daily suspended-sediment load at Fountain Creek at Security, Colorado. Likewise, the total of mean daily suspended-sediment loads from the five tributary sites to the Purgatoire River in WYs 2016–18 were about 0.25, 0.17, and 3.2 percent, respectively, of the historical mean daily suspended-sediment load at Purgatoire Thatcher.
Spearman’s rank correlation coefficient was used to evaluate the strength and form of the relations between daily total precipitation and daily mean streamflow and between daily mean streamflow and suspended-sediment concentration and load for WYs 2016–18. For the sites on the AGFC and PCMS, there were weak or statistically insignificant positive correlations between precipitation and streamflow at nearby streamgauges, but strong statistically significant positive correlations between streamflow and suspended-sediment concentration and load. The ephemeral nature of the streams, quantity and timing of precipitation, air temperature, seasonal soil-moisture deficits, and effective runoff detention in erosion-control ponds could all contribute to inconsistent conversion of precipitation to streamflow.
Water-quality data were analyzed for as many as 43 parameters from 9 samples collected from 3 sites on the AGFC and from 37 samples collected from 4 sites on PCMS during WYs 2016–18. The concentrations of selected water-quality parameters were compared to regulatory standards for aquatic life from the Colorado Department of Public Health and Environment (CDPHE) or aquatic-life criteria from the U.S. Environmental Protection Agency (EPA). There is at least 1 CDPHE standard or EPA criterion for 30 of the 43 water-quality parameters.
For all samples from both the AGFC and the PCMS in WYs 2016–18, the concentrations of most water-quality parameters were compliant with the associated standards or criteria. However, there were some exceedances of standards or criteria: 11 samples exceeded the CDPHE recreational class standard for Escherichia coli concentration, 9 samples exceeded the CDPHE chronic unfiltered phosphorus aquatic-life standard, 36 samples exceeded the CDPHE chronic sulfate aquatic-life standard, 5 samples exceeded the EPA criterion for selenium, 7 samples exceeded the EPA criterion for aluminum, 2 samples exceeded the CDPHE chronic standard for iron, and 15 samples exceeded the CDPHE chronic standard for manganese.
Identifying potential effects of military training on water quality in adjacent streams on the AGFC and PCMS is difficult due to the ephemeral nature of streamflow, limited number of sampling locations and samples, and limited access to the study areas. At the PCMS, pairs of water-quality samples were collected in March and May 2017 before and after an April–May 2017 military training event. At the Purgatoire Rock Crossing site, streamflow at the time of the May sample was approximately 35 times larger than streamflow for the March sample. The absolute percent differences of concentrations for 27 parameters ranged from −71.7 to 183 percent, and 7 parameters had increases in concentration whereas 22 parameters had no change or decreases in concentrations. The absolute percent differences of loads for 24 parameters ranged from 141 to 198 percent. The generally lower concentrations and higher loads were expected given the higher streamflows at the time of collection of the May compared to the March samples.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225018","collaboration":"Prepared in cooperation with the U.S. Department of the Army","usgsCitation":"Battaglin, W.A., and Kisfalusi, Z.D., 2022, Characterization of and relations among precipitation, streamflow, suspended-sediment, and water-quality data at the U.S. Army Garrison Fort Carson and Piñon Canyon Maneuver Site, Colorado, water years 2016–18: U.S. Geological Survey Scientific Investigations Report 2022–5018, 94 p., https://doi.org/10.3133/sir20225018.","productDescription":"Report: ix, 94 p.; Database; Data Release","onlineOnly":"Y","ipdsId":"IP-115539","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":400092,"rank":4,"type":{"id":9,"text":"Database"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System—","linkHelpText":"USGS water data for the Nation: U.S. Geological 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U.S. Geological Survey
Box 25046, MS-415
Denver, CO 80225
No abstract available.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Institute on Lake Superior Geology: Proceedings, 2022","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"68th Annual Meeting: Institute on Lake Superior Geology","conferenceDate":"May 10-11, 2022","conferenceLocation":"Sudbury, Ontario, Canada","language":"English","publisher":"Institute on Lake Superior Geology","usgsCitation":"Hayes, T.S., and Mazdab, F., 2022, Preliminary petrographic and geochemical data for potential source rocks for sediment-hosted stratabound copper deposits in the Lake Superior portion of the Midcontinent Rift, in Institute on Lake Superior Geology: Proceedings, 2022, v. 68, Sudbury, Ontario, Canada, May 10-11, 2022, p. 27-28.","productDescription":"2 p.","startPage":"27","endPage":"28","ipdsId":"IP-139851","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":410255,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":410254,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.lakesuperiorgeology.org/Volumes.html","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Michigan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -90.28036239412515,\n 46.8\n ],\n [\n -90.28036239412515,\n 46.489824751406104\n ],\n [\n -89.49724152382714,\n 46.489824751406104\n ],\n [\n -89.49724152382714,\n 46.8\n ],\n [\n -90.28036239412515,\n 46.8\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"68","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hayes, Timothy S. 0000-0002-1224-4219","orcid":"https://orcid.org/0000-0002-1224-4219","contributorId":290116,"corporation":false,"usgs":true,"family":"Hayes","given":"Timothy","email":"","middleInitial":"S.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":840306,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mazdab, Frank K.","contributorId":290118,"corporation":false,"usgs":false,"family":"Mazdab","given":"Frank K.","affiliations":[{"id":62341,"text":"University of Arizona, Department of Geosciences; 1040 E. 4th St.; Tucson, AZ 85721-0077","active":true,"usgs":false}],"preferred":false,"id":840307,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70237607,"text":"70237607 - 2022 - Quantitative method development to determine feed consumption using a dye","interactions":[],"lastModifiedDate":"2022-10-14T15:00:42.427626","indexId":"70237607","displayToPublicDate":"2022-05-11T09:59:02","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2885,"text":"North American Journal of Aquaculture","active":true,"publicationSubtype":{"id":10}},"title":"Quantitative method development to determine feed consumption using a dye","docAbstract":"Although there are many methods to determine ingestion and absorption of aquafeeds, none exist that are simple, cost-effective, and quantitative and that can mark fish with a long-lasting, visible indicator. In addition to aquafeed development, selective baits are needed that can be used for aquatic invasive species removal efforts, including for Grass Carp Ctenopharyngodon idella. Bait incorporated with a pesticide would allow for selective removal of targeted species. A method to quickly assess multiple bait formulations was developed to expediate development for invasive species management. Incorporation of Sudan Black B (SBB) in aquafeeds at concentrations greater than 75 and 120 mg SBB/kg fish resulted in pigmented external soft tissues of Largemouth Bass Micropterus salmoides and Rainbow Trout Oncorhynchus mykiss, respectively, 24 h after consumption. Visual confirmation of consumption was detectable in the gastrointestinal tract at all concentrations tested (≥10 mg SBB/kg) and quantifiable by absorbance measured at 601 nm from extracted SBB in tissues at concentrations less than those required for visual pigmentation. Although SBB was detectable in multiple tissues, fin and mandible tissues yielded the greatest accuracy in estimating consumption from extracted SBB. Compared with other tissues tested, liver tissue accumulated the highest level of SBB but had the greatest variability, while muscle tissue accumulated little detectable SBB. We used the SBB analytical method to compare consumption of six novel baits that were in the initial developmental stages to produce a palatable bait formulation designed to attract Grass Carp for management control. Overwhelming preference of a rapeseed bait formulation was confirmed using SBB as a tracer of consumption in the laboratory; however, use of SBB under natural conditions may be valuable for answering additional questions. Baits incorporated with SBB allowed for the rapid, simultaneous assessment of multiple formulations and could allow for future refinement of management baits, with results available as quickly as 24–72 h after application.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/naaq.10246","usgsCitation":"Wamboldt, J.J., Nelson, J., Thomas, L.M., Steiner, J.N., Hebert, J., Erickson, R.A., and Putnam, J.G., 2022, Quantitative method development to determine feed consumption using a dye: North American Journal of Aquaculture, v. 84, no. 3, p. 354-369, https://doi.org/10.1002/naaq.10246.","productDescription":"16 p.","startPage":"354","endPage":"369","ipdsId":"IP-133251","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":447826,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/naaq.10246","text":"Publisher Index Page"},{"id":435849,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9M1WO7O","text":"USGS data release","linkHelpText":"Data release for Quantitative method development to determine feed consumption using a dye"},{"id":408323,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"84","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-05-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Wamboldt, James J. 0000-0003-3043-5198","orcid":"https://orcid.org/0000-0003-3043-5198","contributorId":219060,"corporation":false,"usgs":true,"family":"Wamboldt","given":"James","email":"","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":854639,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nelson, Justine 0000-0003-2530-5815 jenelson@usgs.gov","orcid":"https://orcid.org/0000-0003-2530-5815","contributorId":168767,"corporation":false,"usgs":true,"family":"Nelson","given":"Justine","email":"jenelson@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":854640,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thomas, Linnea M 0000-0002-0140-1207","orcid":"https://orcid.org/0000-0002-0140-1207","contributorId":244022,"corporation":false,"usgs":true,"family":"Thomas","given":"Linnea","email":"","middleInitial":"M","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":854641,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Steiner, J. Nolan 0000-0003-2809-9009 jsteiner@usgs.gov","orcid":"https://orcid.org/0000-0003-2809-9009","contributorId":220768,"corporation":false,"usgs":true,"family":"Steiner","given":"J.","email":"jsteiner@usgs.gov","middleInitial":"Nolan","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":854642,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hebert, Jillian 0000-0003-4893-8287","orcid":"https://orcid.org/0000-0003-4893-8287","contributorId":297917,"corporation":false,"usgs":false,"family":"Hebert","given":"Jillian","affiliations":[{"id":39297,"text":"former U.S. Geological Survey employee","active":true,"usgs":false}],"preferred":false,"id":854643,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Erickson, Richard A. 0000-0003-4649-482X rerickson@usgs.gov","orcid":"https://orcid.org/0000-0003-4649-482X","contributorId":5455,"corporation":false,"usgs":true,"family":"Erickson","given":"Richard","email":"rerickson@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":854644,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Putnam, Joel G. 0000-0002-5464-4587 jgputnam@usgs.gov","orcid":"https://orcid.org/0000-0002-5464-4587","contributorId":5783,"corporation":false,"usgs":true,"family":"Putnam","given":"Joel","email":"jgputnam@usgs.gov","middleInitial":"G.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":854645,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70256736,"text":"70256736 - 2022 - Heterogeneity of recreationists in a park and protected area","interactions":[],"lastModifiedDate":"2024-09-04T14:35:26.19182","indexId":"70256736","displayToPublicDate":"2022-05-11T09:26:35","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Heterogeneity of recreationists in a park and protected area","docAbstract":"Limited information and resources have caused many parks and protected areas (PPAs) to functionally manage recreationists as a single homogeneous group, despite potential negative social and ecological consequences. We aimed to evaluate the homogeneity of recreationists at the Valentine National Wildlife Refuge (NWR) by 1) quantifying frequencies of consumptive (i.e., hunting), intermediate-consumptive (i.e., fishing), and non-consumptive recreational-activity groups (e.g., wildlife viewing), and 2) evaluating sociodemographic differences among these groups. We used onsite surveys to determine that Valentine NWR supports heterogeneous groups of recreationists. The intermediate-consumptive group was most frequent (77% of all parties). All three recreational-activity groups varied in party size, distance traveled, household income, population type (urban or rural residence), and vehicle type (two-wheel or four-wheel drive). Tracking and accounting for diverse recreationists will equip managers with the ability to sustain recreational activities while also preserving ecological systems.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0268303","usgsCitation":"DaRugna, O., Kaemingk, M., Chizinski, C., and Pope, K.L., 2022, Heterogeneity of recreationists in a park and protected area: PLoS ONE, v. 17, no. 5, e0268303, 10 p., https://doi.org/10.1371/journal.pone.0268303.","productDescription":"e0268303, 10 p.","ipdsId":"IP-119655","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":447828,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0268303","text":"Publisher Index Page"},{"id":433444,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska","county":"Cherry County","otherGeospatial":"Valentine National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -100.74599698070318,\n 42.60461214848425\n ],\n [\n -100.7232432482346,\n 42.457648941727655\n ],\n [\n -100.59625734423919,\n 42.46023422263612\n ],\n [\n -100.53217881824406,\n 42.414425137075085\n ],\n [\n -100.35449893676504,\n 42.40875114015742\n ],\n [\n -100.34278745681826,\n 42.45464094790627\n ],\n [\n -100.36361716043805,\n 42.471056711002646\n ],\n [\n -100.4500311517603,\n 42.48944701469524\n ],\n [\n -100.45019845861653,\n 42.551882863354706\n ],\n [\n -100.74599698070318,\n 42.60461214848425\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"17","issue":"5","noUsgsAuthors":false,"publicationDate":"2022-05-11","publicationStatus":"PW","contributors":{"authors":[{"text":"DaRugna, O.A.","contributorId":341724,"corporation":false,"usgs":false,"family":"DaRugna","given":"O.A.","email":"","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":908829,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kaemingk, M.A.","contributorId":340850,"corporation":false,"usgs":false,"family":"Kaemingk","given":"M.A.","email":"","affiliations":[{"id":17628,"text":"University of North Dakota","active":true,"usgs":false}],"preferred":false,"id":908830,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chizinski, C.J.","contributorId":340849,"corporation":false,"usgs":false,"family":"Chizinski","given":"C.J.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":908831,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pope, Kevin L. 0000-0003-1876-1687","orcid":"https://orcid.org/0000-0003-1876-1687","contributorId":270762,"corporation":false,"usgs":true,"family":"Pope","given":"Kevin","email":"","middleInitial":"L.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":908832,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70234145,"text":"70234145 - 2022 - Scale dependence of coral reef oases and their environmental correlates","interactions":[],"lastModifiedDate":"2022-10-31T14:28:22.452608","indexId":"70234145","displayToPublicDate":"2022-05-11T07:09:24","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Scale dependence of coral reef oases and their environmental correlates","docAbstract":"Identifying relatively intact areas within ecosystems and determining the conditions favoring their existence is necessary for effective management in the context of widespread environmental degradation. In this study, we used 3766 surveys of randomly selected sites in the United States and U.S. Territories to identify the correlates of sites categorized as “oases” (defined as sites with relatively high total coral cover). We used occupancy models to evaluate the influence of 10 environmental predictors on the probability that an area (21.2-km2 cell) would harbor coral oases defined at four spatial extents: cross-basin, basin, region, and subregion. Across all four spatial extents, oases were more likely to occur in habitats with high light attenuation. The influence of the other environmental predictors on the probability of oasis occurrence were less consistent and varied with the scale of observation. Oases were most likely in areas of low human population density, but this effect was evident only at the cross-basin and subregional extents. At the regional and subregional extents oases were more likely where sea-surface temperature was more variable, whereas at the larger spatial extents the opposite was true. By identifying the correlates of oasis occurrence, the model can inform the prioritization of reef areas for management. Areas with biophysical conditions that confer corals with physiological resilience, as well as limited human impacts, likely support coral reef oases across spatial extents. Our approach is widely applicable to the development of conservation strategies to protect biodiversity and ecosystems in an era of magnified human disturbance.
Feedbacks within ecosystems can lead to internal reinforcement of the current state providing ecosystem resilience. Often, multiple biotic interactions across trophic levels play a role in such feedbacks, yet these are generally studied independently, obscuring the relative importance of interactions among different factors. We look at various potential feedbacks in intact and degraded mesic forests on Hawaiʻi Island where managers have planted native Acacia koa (koa) trees in an attempt to jumpstart succession in former cattle pastures. These restoration forests, however, have not undergone secondary succession, instead maintaining a koa overstory with an exotic pasture grass understory. We contrasted different trophic level processes that influence the capacity for natural understory regeneration: feedbacks between bird-mediated seed rain and fruiting understory (“top-down”), as well as links between understory composition and microhabitats for native seed germination (“bottom-up”). We quantified bird-mediated seed rain under canopy trees along transects spanning intact, fragmented, and restoration forests. Along these transects, we established plots around focal overstory trees to measure abundance of fruiting understory species, ground cover (e.g., exotic grass, bryophyte), and obtained estimates of bird density to evaluate the contribution of each of these factors to seedling abundance. We also used a factorial seed addition/grass removal experiment to directly compare the influence of seed rain and germination substrate. We found evidence of both top-down and bottom-up feedbacks that reinforced the current state of each forest type. In the intact and fragmented forests, the combination of comparatively high seed rain and ample germination substrate is likely critical for maintaining a diverse forest system. In contrast, exotic grasses exhibit priority effects in restoration forests, inhibiting seed germination and effectively negating any benefits that could be derived from bird-mediated seed rain. Such internal reinforcement suggests that active, rather than passive, restoration would be beneficial to increase forest diversity in restoration areas.
Identify hotspots and areas of high species richness for Arctic marine mammals.
Circumpolar Arctic.
A total of 2115 biologging devices were deployed on marine mammals from 13 species in the Arctic from 2005 to 2019. Getis-Ord Gi* hotspots were calculated based on the number of individuals in grid cells for each species and for phylogenetic groups (nine pinnipeds, three cetaceans, all species) and areas with high species richness were identified for summer (Jun-Nov), winter (Dec-May) and the entire year. Seasonal habitat differences among species’ hotspots were investigated using Principal Component Analysis.
Hotspots and areas with high species richness occurred within the Arctic continental-shelf seas and within the marginal ice zone, particularly in the “Arctic gateways” of the north Atlantic and Pacific oceans. Summer hotspots were generally found further north than winter hotspots, but there were exceptions to this pattern, including bowhead whales in the Greenland-Barents Seas and species with coastal distributions in Svalbard, Norway and East Greenland. Areas with high species richness generally overlapped high-density hotspots. Large regional and seasonal differences in habitat features of hotspots were found among species but also within species from different regions. Gap analysis (discrepancy between hotspots and IUCN ranges) identified species and regions where more research is required.
This study identified important areas (and habitat types) for Arctic marine mammals using available biotelemetry data. The results herein serve as a benchmark to measure future distributional shifts. Expanded monitoring and telemetry studies are needed on Arctic species to understand the impacts of climate change and concomitant ecosystem changes (synergistic effects of multiple stressors). While efforts should be made to fill knowledge gaps, including regional gaps and more complete sex and age coverage, hotspots identified herein can inform management efforts to mitigate the impacts of human activities and ecological changes, including creation of protected areas.
","language":"English","publisher":"Wiley","doi":"10.1111/ddi.13543","usgsCitation":"Hamilton, C., Lydersen, C., Aars, J., Acquarone, M., Atwood, T.C., Baylis, A., Biuw, M., Boltunov, A.N., Born, E.W., Boveng, P.L., Brown, T.M., Cameron, M., Citta, J.J., Crawford, J.A., Dietz, R., Elias, J., Ferguson, S.H., Fisk, A., Folkow, L.P., Frost, K.J., Glazov, D.M., Granquist, S.M., Gryba, R., Harwood, L.A., Haug, T., Heide-Jorgensen, M.P., Hussey, N.E., Kalinek, J., Laidre, K.L., Litovka, D.I., London, J.M., Loseto, L., MacPhee, S., Marcoux, M., Matthews, C.J., Nilssen, K.J., Nordoy, E.S., O’Corry-Crowe, G., Oien, N., Tange Olsen, M., Quakenbush, L.T., Rosing-Asvid, A., Semenova, V., Shelden, K.E., Shpak, O.V., Stenson, G., Storrie, L., Sveegaard, S., Teilmann, J., Ugarte, F., Von Duyke, A.L., Watt, C., Wiig, O., Wilson, R., Yurkowski, D.J., and Kovacs, K.M., 2022, Marine mammal hotspots across the circumpolar Arctic: Diversity and Distributions, v. 28, no. 12, p. 2729-2753, https://doi.org/10.1111/ddi.13543.","productDescription":"25 p.","startPage":"2729","endPage":"2753","ipdsId":"IP-133700","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":447836,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/ddi.13543","text":"External Repository"},{"id":400800,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Arctic","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -179.9,\n 90\n ],\n [\n -179.9,\n 60\n ],\n [\n 179.9,\n 60\n ],\n [\n 179.9,\n 90\n ],\n [\n -179.9,\n 90\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"28","issue":"12","noUsgsAuthors":false,"publicationDate":"2022-05-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Hamilton, Charmain","contributorId":291891,"corporation":false,"usgs":false,"family":"Hamilton","given":"Charmain","email":"","affiliations":[{"id":62784,"text":"Dept. 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Michael","contributorId":214207,"corporation":false,"usgs":false,"family":"Cameron","given":"Michael","email":"","affiliations":[{"id":38993,"text":"Marine Mammal Laboratory, Alaska Fisheries Science Center, National Marine Fisheries Service","active":true,"usgs":false}],"preferred":false,"id":843317,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Citta, John J.","contributorId":175350,"corporation":false,"usgs":false,"family":"Citta","given":"John","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":843318,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Crawford, Justin A.","contributorId":214225,"corporation":false,"usgs":false,"family":"Crawford","given":"Justin","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":843319,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Dietz, 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Not all science-based conservation and sustainability initiatives that address issues facing humanity and ecosystems and global problems have gained public support. Conservation decisions and policy prescriptions are and may be based on perceptions about and experiences with the environment, local land use, and ecosystems that may not align with or be grounded in science or evidence from experts in the field. Values, beliefs, and perceptions associated with nature play a critical role in how individuals view biodiversity conservation, sustainability, and natural resource management. This study first examines the gap between experts (scientists and other field experts) and the public (farmers and non-farmers) about the state of water and land resources, wildlife and associated habitats, and aquatic biodiversity in the Smoky Hill River Watershed in western Kansas. Second, the study examines the role that values and beliefs play in shaping environmental perceptions for farmers and non-farmers. Analysis confirms that a gap between experts and farmers/non-farmers does exist, especially with respect to the state of the Ogallala Aquifer, playas, rivers and streams, lakes and reservoirs, native grasslands, wildlife habitats, farmland, native fish populations, and wildlife species. Ordered-logistic regression analyses, meanwhile, indicate that farmer and non-farmer perceptions about the state of the local environment are influenced by traditional and self-interested values, as well as environmental values and beliefs, but less so by religiosity and political ideology. Despite broad takeaways, results exhibited heterogeneity across the farmer and non-farmer subpopulations. If environmental professionals cannot align ecological data, stakeholders’ values/perceptions, and policies, then the existing body of technical research and management on sustainability in natural and social sciences may be of little value.
Marbled murrelets (Brachyramphus marmoratus) have been listed as “endangered” by the State of California and “threatened” by the U.S. Fish and Wildlife Service since 1992 in California, Oregon, and Washington. Information regarding marbled murrelet abundance, distribution, population trends, and habitat associations is critical for risk assessment, effective management, evaluation of conservation efficacy, and ultimately, to meet federal- and state-mandated recovery efforts for this species. During June–August 2020 and 2021, the U.S. Geological Survey Western Ecological Research Center continued previously established, long-term (1999–present), at-sea surveys to estimate abundance and productivity of marbled murrelets in U.S. Fish and Wildlife Service Conservation Zone 6 (San Francisco Bay to Point Sur in central California). The abundance estimated for the entire study area was 470 birds (95-percent confidence interval, 313–707 birds) in 2020 and 402 birds (95-percent confidence interval, 219–737 birds) in 2021. Estimated abundances for both years are comparable with most prior years of study. We estimated reproductive productivity (calculated as the hatch-year to after-hatch-year ratio) after date-correcting hatch-year and after-hatch-year counts to account for birds expected to be absent from the water while inland at nests. The date-corrected juvenile ratio was 0.018±0.011 standard error in 2020 and 0.041±0.024 standard error in 2021. We updated a comprehensive database of all Zone 6 marbled murrelet survey data since 1999 with 2020–21 data to allow scientists and managers to evaluate established survey methods and assess trends in abundance and productivity estimates.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dr1157","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","programNote":"Ecosystems Mission Area—Species Management Research Program","usgsCitation":"Felis, J.J., Adams, J., Horton, C.A., Kelsey, E.C., and White, L.M., 2022, Abundance and productivity of Marbled Murrelets (Brachyramphus marmoratus) off central California during the 2020 and 2021 breeding seasons: U.S. Geological Survey Data Report 1157, 12 p., https://doi.org/10.3133/dr1157.","productDescription":"Report: vi, 12 p.; Data Release","numberOfPages":"12","onlineOnly":"Y","ipdsId":"IP-134849","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":400463,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/dr/1157/dr1157.pdf","text":"Report","size":"6 MB"},{"id":400464,"rank":2,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/dr/1157/images"},{"id":400465,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/dr/1157/dr1157.xml"},{"id":400466,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F75B01RW","text":"Annual marbled murrelet abundance and productivity surveys off central California (Zone 6), 1999–2021","description":"Felis, J.J., Adams, J., Peery, M.Z., Henry, R.W., Henkel, L.A., Becker, B.H., and Halbert, P., 2022, Annual marbled murrelet abundance and productivity surveys off central California (Zone 6), 1999–2021: U.S. Geological Survey data release, https://doi.org/10.5066/F75B01RW."},{"id":400473,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/dr/1157/covrthb.jpg"},{"id":400472,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/dr1157/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"DR 1157"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.59918212890626,\n 36.87962060502676\n ],\n [\n -121.717529296875,\n 36.87962060502676\n ],\n [\n -121.717529296875,\n 37.65773212628272\n ],\n [\n -122.59918212890626,\n 37.65773212628272\n ],\n [\n -122.59918212890626,\n 36.87962060502676\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
A cooperative study led by the U.S. Geological Survey and Wake County Environmental Services was initiated to characterize the fractured-rock aquifer system and assess the sustainability of groundwater resources in and around Wake County. This report contributes to the development of a comprehensive groundwater budget for the study area, thereby helping to enable resource managers to make sound and sustainable water-supply and water-use decisions.
Construction information was used to analyze the well depth, casing depth, and reported well yield of more than 7,500 inventoried wells. The median well depth and casing depth were 265 feet (ft) below land surface (bls) and 68 ft bls, respectively, and the median well yield was 10 gallons per minute. Generally, well yield increased with depth to around 200 ft bls and then began to decrease with depth within the fractured-rock aquifer.
Borehole geophysical logging methods were used to characterize the fractured-rock aquifer by mapping the orientation of geologic structures within the subsurface. Structure measurements were made on resulting log data and mapped to observed general spatial trends within the regional groundwater system and more distinct hydrogeologic units. Many of the fractures observed within the borehole logs are steeply dipping across Wake County, although open fractures with shallow dip angles were also observed in most rock classes. Regional geologic structural trends were observed in proximity to the Jonesboro Fault.
Potential groundwater recharge in the study area was estimated using a Soil-Water-Balance (SWB) model, as well as using base flow hydrograph separation. The SWB model calculated net infiltration below the root zone for 1981 through 2019 for a 5,402-square-mile area that extends to the counties surrounding Wake County. The mean annual net infiltration rate for the 39-year period was about 8.6 inches per year for the study area. The mean annual net infiltration results from the SWB model were comparable to annual base flow estimates using the PART hydrograph-separation method at six U.S. Geological Survey streamgages within the study area. Mean annual base flow for all six drainage basins was near 7.5 inches per year and estimates ranged from 2.9 to 8.9 inches. Comparisons of mean annual potential recharge from the SWB model and base flow estimates were generally within 2 inches, except during high flows for most of the drainage basins in the study area.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225041","collaboration":"Prepared in cooperation with Wake County Environmental Services","usgsCitation":"Antolino, D.J., and Gurley, L.N., 2022, Assessment of well yield, dominant fractures, and groundwater recharge in Wake County, North Carolina (ver. 1.1, May 2022) : U.S. Geological Survey Scientific Investigations Report 2022–5041, 35 p., https://doi.org/10.3133/sir20225041.","productDescription":"Report: viii, 35 p.; 3 Data Releases; Database","numberOfPages":"35","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-115494","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":399581,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9C2J23X","text":"USGS data release","linkHelpText":"Groundwater well yield in Wake County, North Carolina"},{"id":435853,"rank":11,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MO793B","text":"USGS data release","linkHelpText":"Soil-Water-Balance (SWB) model data sets for the Greater Wake County area, North Carolina, 1981 - 2070"},{"id":399596,"rank":9,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20225041/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":399578,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5041/images/"},{"id":399575,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5041/coverthb2.jpg"},{"id":400310,"rank":10,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2022/5041/versionHist.txt","size":"508 B","linkFileType":{"id":2,"text":"txt"}},{"id":399582,"rank":8,"type":{"id":9,"text":"Database"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the Nation"},{"id":399580,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96HHBIE","text":"USGS data release","linkHelpText":"National Land Cover Database (NLCD) 2016 products (ver. 2.0, July 2020)"},{"id":399579,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95XKK5V","text":"USGS data release","linkHelpText":"Soil-Water-Balance (SWB) model datasets for the Greater Wake County area, North Carolina, 1981–2019"},{"id":399577,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5041/sir20225041.XML"},{"id":399576,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5041/sir20225041.pdf","text":"Report","size":"13.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5041"}],"country":"United States","state":"North Carolina","county":"Wake County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-78.5465,36.0218],[-78.4307,35.9795],[-78.3969,35.9387],[-78.3567,35.9318],[-78.351,35.909],[-78.3385,35.9052],[-78.3347,35.8997],[-78.3302,35.896],[-78.3245,35.896],[-78.3177,35.8963],[-78.3137,35.8976],[-78.3081,35.8935],[-78.2948,35.8797],[-78.292,35.8792],[-78.2893,35.8741],[-78.2859,35.8713],[-78.2831,35.8681],[-78.2782,35.8631],[-78.2749,35.8567],[-78.2756,35.8494],[-78.2707,35.843],[-78.2657,35.8361],[-78.2652,35.8325],[-78.2613,35.8315],[-78.2591,35.826],[-78.2599,35.8183],[-78.3731,35.7523],[-78.4635,35.7072],[-78.4686,35.7087],[-78.4709,35.7078],[-78.4732,35.7046],[-78.4778,35.7011],[-78.5716,35.6255],[-78.708,35.5191],[-78.9196,35.5857],[-78.9956,35.6104],[-78.9796,35.6656],[-78.9439,35.7515],[-78.9421,35.756],[-78.9403,35.7615],[-78.9337,35.7859],[-78.9191,35.8216],[-78.9096,35.8506],[-78.9076,35.8678],[-78.89,35.8676],[-78.8298,35.8689],[-78.8056,35.9281],[-78.7609,35.9176],[-78.751,35.9307],[-78.7372,35.941],[-78.714,35.9729],[-78.7009,36.0068],[-78.6985,36.0131],[-78.7048,36.0091],[-78.7077,36.0087],[-78.7076,36.0132],[-78.7052,36.0223],[-78.7085,36.0287],[-78.7102,36.0287],[-78.713,36.0278],[-78.7164,36.0283],[-78.7232,36.0334],[-78.726,36.0343],[-78.7272,36.0334],[-78.7278,36.0289],[-78.7324,36.0267],[-78.7353,36.0199],[-78.7422,36.0209],[-78.75,36.026],[-78.7551,36.0283],[-78.7545,36.0301],[-78.7511,36.0323],[-78.7499,36.035],[-78.747,36.0395],[-78.7492,36.0427],[-78.7503,36.0468],[-78.7519,36.0491],[-78.7564,36.0532],[-78.7498,36.0718],[-78.7088,36.0768],[-78.6895,36.0752],[-78.5922,36.0378],[-78.5465,36.0218]]]},\"properties\":{\"name\":\"Wake\",\"state\":\"NC\"}}]}","edition":"Version 1.1: May 2022; Version 1.0: April 2022","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
1770 Corporate Drive
Norcross, GA 30093
Renewable energy production, mostly via wind, solar, and biofuels, is central to goals worldwide to reduce carbon emissions and mitigate anthropogenic climate change (IPCC, 2014; Pörtner et al., 2021). Nevertheless, adverse impacts to natural systems, especially fatalities of wildlife and alteration of habitat, are key challenges for renewable energy production (Allison et al., 2019; Katzner et al., 2019).
Because of the magnitude of these challenges, extensive effort has been invested in surveys and science to understand the environmental effects of renewable energy on species and systems. Nevertheless, these impacts have not been formally compared relative to counterfactual conditions (Bull et al., 2021; Coetzee and Gaston, 2021), i.e., those occurring in the absence of renewable energy. As such, cumulative ecological impact assessments required by many regulating agencies typically only consider the adverse impacts of renewables, without evaluating whether mitigative effects of current and planned build-out (e.g., Larson et al., 2020) will offset their adverse impacts to species and natural systems (Allison et al., 2014). Accordingly, these critical decision processes have an insufficient perspective to foster fully informed decisions, and, for some species or systems, renewable energy could lead to more profound impacts than those it is intended to prevent. Furthermore, because of this approach and, despite the well-studied benefits to society of renewable energy development (IPCC, 2014), the ecological value of renewable energy is often premised on the plausible but untested assumption that its negative effects to natural populations and systems are less consequential than the negative effects in alternative scenarios with less renewable energy and greater climate change.
A more comprehensive framing of the counterfactual in cumulative ecological impact assessments would evaluate, for each species or system, the incremental effects of renewables over their full life cycle against the incremental effects they provide by mitigating climate change. This framing is important because a given species or system may see net positive or net negative effects from either renewables or climate change. Furthermore, cumulative impact assessments could identify optimized tradeoffs that balance, for each species or system, the effects of both climate change and renewable energy.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fcosc.2022.844286","usgsCitation":"Katzner, T., Allison, T.D., Diffendorfer, J.E., Hale, A., Lantz, E.J., and Veers, P., 2022, Counterfactuals to assess effects to species and systems from renewable energy development: Frontiers in Conservation Science, v. 3, 844286, 4 p., https://doi.org/10.3389/fcosc.2022.844286.","productDescription":"844286, 4 p.","ipdsId":"IP-131158","costCenters":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":447841,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fcosc.2022.844286","text":"Publisher Index Page"},{"id":417251,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","noUsgsAuthors":false,"publicationDate":"2022-05-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":191353,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":873250,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Allison, Taber D","contributorId":223428,"corporation":false,"usgs":false,"family":"Allison","given":"Taber","email":"","middleInitial":"D","affiliations":[{"id":39329,"text":"American Wind Wildlife Institute","active":true,"usgs":false}],"preferred":false,"id":873251,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Diffendorfer, Jay E. 0000-0003-1093-6948 jediffendorfer@usgs.gov","orcid":"https://orcid.org/0000-0003-1093-6948","contributorId":55137,"corporation":false,"usgs":true,"family":"Diffendorfer","given":"Jay","email":"jediffendorfer@usgs.gov","middleInitial":"E.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":false,"id":873252,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hale, Amanda","contributorId":219856,"corporation":false,"usgs":false,"family":"Hale","given":"Amanda","email":"","affiliations":[{"id":25471,"text":"Texas Christian University","active":true,"usgs":false}],"preferred":false,"id":873253,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lantz, Eric J.","contributorId":305585,"corporation":false,"usgs":false,"family":"Lantz","given":"Eric","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":873254,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Veers, Paul","contributorId":305586,"corporation":false,"usgs":false,"family":"Veers","given":"Paul","email":"","affiliations":[],"preferred":false,"id":873255,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70231918,"text":"70231918 - 2022 - Isotopic analysis of radium geochemistry at discrete intervals in the Midwestern Cambrian-Ordovician aquifer system","interactions":[],"lastModifiedDate":"2022-06-03T13:42:47.59382","indexId":"70231918","displayToPublicDate":"2022-05-10T08:42:19","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Isotopic analysis of radium geochemistry at discrete intervals in the Midwestern Cambrian-Ordovician aquifer system","docAbstract":"Radium (Ra) is a geogenic radioactive contaminant that frequently occurs at elevated levels in the Midwestern Cambrian-Ordovician aquifer system (MCOAS). Geochemical indicators (e.g., redox conditions or total dissolved solids) can broadly characterize conditions associated with elevated Ra levels in groundwater, but do not consistently correlate to elevated Ra within specific stratigraphic horizons. A coupled geochemical and isotopic study of groundwater and aquifer solids for major and trace elements, Ra, and uranium (U) at discrete intervals in the MCOAS was used to elucidate processes that may be responsible for this disconnect, via analysis of groundwater as well as extracted and digested solid aquifer samples. We find that the potential for Ra mobilization varies by stratigraphic unit, as observed by whole-rock 226Ra/238U (dis)equilibrium. Overall, the examined aqueous geochemical characteristics (e.g., redox conditions, total dissolved solids) do not explain Ra concentrations within the system, suggesting that alternative factors, like solid-phase associations or the extent of alpha recoil damage, may be more important. A relation between aqueous 87Sr/86Sr and 226Ra suggests that minerals with radiogenic 87Sr/86Sr are more likely to release 226Ra to the aqueous system. Overall, the release of U and Ra due to water-rock interaction varies with discrete stratigraphy, depending on aqueous geochemistry and available mineral associations. Due to complex Ra-rock interactions and the heterogeneous geology of the MCOAS, aqueous geochemistry does not fully predict the mobilization and concentration of Ra in groundwater. As sources and sinks of Ra within the MCOAS vary across stratigraphy, knowledge of aqueous geochemistry, available solid-phase associations, and nuclide leachability all are important to consider for understanding elevated Ra occurrence in aquifer systems.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2022.105300","usgsCitation":"Mathews, M.J., Scott, S.R., Gotkowitz, M.B., Hunt, R., and Ginder-Vogel, M., 2022, Isotopic analysis of radium geochemistry at discrete intervals in the Midwestern Cambrian-Ordovician aquifer system: Applied Geochemistry, v. 142, 105300, 11 p., https://doi.org/10.1016/j.apgeochem.2022.105300.","productDescription":"105300, 11 p.","ipdsId":"IP-135098","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":401679,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.1865234375,\n 46.057985244793024\n ],\n [\n -92.30712890625,\n 46.042735653846506\n ],\n [\n -92.7685546875,\n 45.90529985724799\n ],\n [\n -92.8564453125,\n 45.5679096098613\n ],\n [\n -92.6806640625,\n 45.42929873257377\n ],\n [\n -92.79052734375,\n 44.793530904744074\n ],\n [\n -92.471923828125,\n 44.5435052132082\n ],\n [\n -91.9720458984375,\n 44.35527821160296\n ],\n [\n -91.702880859375,\n 44.09547572946637\n ],\n [\n -91.2689208984375,\n 43.88205730390537\n ],\n [\n -91.263427734375,\n 43.51270490464819\n ],\n [\n -91.2139892578125,\n 43.38508989465156\n ],\n [\n -91.07666015625,\n 43.28920196020127\n ],\n [\n -91.1700439453125,\n 43.137069765760344\n ],\n [\n -91.1590576171875,\n 42.92827401776912\n ],\n [\n -91.01074218749999,\n 42.69858589169842\n ],\n [\n -90.71411132812499,\n 42.64608143458068\n ],\n [\n -90.615234375,\n 42.500453028125584\n ],\n [\n -87.7972412109375,\n 42.48830197960227\n ],\n [\n -87.7532958984375,\n 42.75104599038353\n ],\n [\n -87.8631591796875,\n 43.04079076668198\n ],\n [\n -87.8631591796875,\n 43.32118142926661\n ],\n [\n -87.66540527343749,\n 43.79885402720353\n ],\n [\n -87.5006103515625,\n 44.19402066387343\n ],\n [\n -86.7864990234375,\n 45.463983441272724\n ],\n [\n -86.99523925781249,\n 45.413876460821086\n ],\n [\n -87.967529296875,\n 44.55524925971063\n ],\n [\n -88.04443359375,\n 44.59829048984011\n ],\n [\n -87.6434326171875,\n 44.99588261816546\n ],\n [\n -87.6214599609375,\n 45.10066901851988\n ],\n [\n -87.7313232421875,\n 45.21687321093267\n ],\n [\n -87.6104736328125,\n 45.40616374516014\n ],\n [\n -87.8631591796875,\n 45.36372498305678\n ],\n [\n -87.7972412109375,\n 45.625563438215984\n ],\n [\n -88.6981201171875,\n 44.465151013519616\n ],\n [\n -90.4779052734375,\n 45.556371735883125\n ],\n [\n -91.1865234375,\n 46.057985244793024\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"142","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mathews, Madeleine J","contributorId":292236,"corporation":false,"usgs":false,"family":"Mathews","given":"Madeleine","email":"","middleInitial":"J","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":844116,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Scott, Sean R","contributorId":292237,"corporation":false,"usgs":false,"family":"Scott","given":"Sean","email":"","middleInitial":"R","affiliations":[{"id":17815,"text":"Wisconsin State Laboratory of Hygiene","active":true,"usgs":false}],"preferred":false,"id":844117,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gotkowitz, Madeline B","contributorId":292239,"corporation":false,"usgs":false,"family":"Gotkowitz","given":"Madeline","email":"","middleInitial":"B","affiliations":[{"id":36941,"text":"Montana Bureau of Mines and Geology","active":true,"usgs":false}],"preferred":false,"id":844118,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hunt, Randall J. 0000-0001-6465-9304","orcid":"https://orcid.org/0000-0001-6465-9304","contributorId":16118,"corporation":false,"usgs":true,"family":"Hunt","given":"Randall J.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":844119,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ginder-Vogel, Matthew","contributorId":176769,"corporation":false,"usgs":false,"family":"Ginder-Vogel","given":"Matthew","email":"","affiliations":[],"preferred":false,"id":844120,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70248943,"text":"70248943 - 2022 - Age of the late Holocene Bonneville landslide and submerged forest of the Columbia River Gorge, Oregon and Washington, USA, by radiocarbon dating","interactions":[],"lastModifiedDate":"2023-09-27T12:16:30.658314","indexId":"70248943","displayToPublicDate":"2022-05-10T07:13:52","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3218,"text":"Quaternary Research","active":true,"publicationSubtype":{"id":10}},"title":"Age of the late Holocene Bonneville landslide and submerged forest of the Columbia River Gorge, Oregon and Washington, USA, by radiocarbon dating","docAbstract":"The late Holocene Bonneville landslide, a 15.5 km2 rockslide-debris avalanche, descended 1000 m from the north side of the Columbia River Gorge and dammed the Columbia River where it bisects the Cascade Range of Oregon and Washington, USA. The landslide, inundation, and overtopping created persistent geomorphic, ecologic, and cultural consequences to the river corridor, reported by Indigenous narratives and explorer accounts, as well as scientists and engineers. From new dendrochronology and radiocarbon dating of three trees killed by the landslide, one entrained and buried by the landslide and two killed by rising water in the impounded Columbia River upstream of the blockage, we find (1) the two drowned trees and the buried tree died the same year, and (2) the age of tree death, and hence the landslide (determined by combined results of nine radiocarbon analyses of samples from the three trees), falls within AD 1421–1455 (3σ confidence interval). This result provides temporal context for the tremendous physical, ecological, and cultural effects of the landslide, as well as possible triggering mechanisms. The age precludes the last Cascadia Subduction Zone earthquake of AD 1700 as a landslide trigger, but not earlier subduction zone or local crustal earthquakes.
Sirenian social and reproductive behaviors lack much complexity or diversity. Whereas sirenians are usually sighted as solitary, or as cows with single calves, aggregations of many individuals can occur. Persistent social groupings are unknown. Home ranges are widely overlapping. Mating systems of dugongs (Dugong dugon) have been variously described as leks or as scramble promiscuity (mating herds ) and lone mating pairs have been observed in areas of low density, but further research into the hypothesized leks is needed (especially because scramble promiscuity has been observed in the same region). Dugongs and all manatees (Trichechus) show scramble promiscuity, wherein males form groups that escort single females with much physical contact for many days. The strongest social bonds are between females and nursing calves. Florida manatees (Trichechus manatus latirostris) show natal philopatry for years after weaning. Socially transmitted knowledge (tradition) appears important to Florida manatees and perhaps all species of sirenians, particularly in regions where seasonal movements during winter are necessary for survival, such as in winter for Florida manatees, and dugongs at the high latitude limits of their range. Some populations of Antillean, Amazonian, and African manatees have regular movements in response to seasonal flooding and access to food, which also may be learned through tradition . Dugongs may rely on group movements based on traditional knowledge in response to regional loss of food supply from extreme weather events. Communication is most obvious through vocalizations, which can show individual distinctiveness. Vocal communication is most prevalent between mothers and calves. Allomaternal care occurs in Florida manatees at shared aggregation sites. Florida manatees occupying a given region can consist of multiple matrilines that develop through the early bonding of calves to mothers and subsequent natal philopatry. Population genetics research supports male-biased dispersal and possible female-based philopatry in other trichechids, but perhaps not as strongly in dugongids. Considerable further research is needed on these and related topics to more comprehensively understand sirenian social and reproductive behavior.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Ethology and Behavioral Ecology of Sirenia","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-030-90742-6_4","usgsCitation":"O'Shea, T., Beck, C., Hodgson, A.J., Keith-Diagne, L., and Marmontel, M., 2022, Social and reproductive behaviors, chap. 4 of Ethology and Behavioral Ecology of Sirenia, p. 101-154, https://doi.org/10.1007/978-3-030-90742-6_4.","productDescription":"54 .","startPage":"101","endPage":"154","ipdsId":"IP-109802","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":447848,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/978-3-030-90742-6_4","text":"Publisher Index Page"},{"id":400856,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2022-05-10","publicationStatus":"PW","contributors":{"authors":[{"text":"O'Shea, Thomas J.","contributorId":291933,"corporation":false,"usgs":false,"family":"O'Shea","given":"Thomas J.","affiliations":[{"id":12608,"text":"USGS, retired","active":true,"usgs":false}],"preferred":false,"id":843410,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beck, Cathy 0000-0002-5388-5418 cbeck@usgs.gov","orcid":"https://orcid.org/0000-0002-5388-5418","contributorId":168987,"corporation":false,"usgs":true,"family":"Beck","given":"Cathy","email":"cbeck@usgs.gov","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":843411,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hodgson, Amanda J.","contributorId":291934,"corporation":false,"usgs":false,"family":"Hodgson","given":"Amanda","email":"","middleInitial":"J.","affiliations":[{"id":62787,"text":"Aquatic Megafauna Research Unit, Murdoch University, Western Australia","active":true,"usgs":false}],"preferred":false,"id":843412,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Keith-Diagne, Lucy W","contributorId":261440,"corporation":false,"usgs":false,"family":"Keith-Diagne","given":"Lucy W","affiliations":[{"id":36882,"text":"African Aquatic Conservation Fund","active":true,"usgs":false}],"preferred":false,"id":843413,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Marmontel, Miriam","contributorId":291935,"corporation":false,"usgs":false,"family":"Marmontel","given":"Miriam","affiliations":[{"id":62788,"text":"Mamiraua Institute for Sustainable Development, Amazonia, Brazil","active":true,"usgs":false}],"preferred":false,"id":843414,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70231552,"text":"70231552 - 2022 - A new indicator approach to reconstruct agricultural land use in Europe from sedimentary pollen assemblages","interactions":[],"lastModifiedDate":"2022-06-01T15:35:32.750509","indexId":"70231552","displayToPublicDate":"2022-05-10T06:39:10","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2996,"text":"Palaeogeography, Palaeoclimatology, Palaeoecology","printIssn":"0031-0182","active":true,"publicationSubtype":{"id":10}},"title":"A new indicator approach to reconstruct agricultural land use in Europe from sedimentary pollen assemblages","docAbstract":"The reconstruction of human impact is pivotal in palaeoecological studies, as humans are among the most important drivers of Holocene vegetation and ecosystem change. Nevertheless, separating the anthropogenic footprint on vegetation dynamics from the impact of climate and other environmental factors (disturbances such as fire, erosion, floods, landslides, avalanches, volcanic eruptions) is a challenging and still largely open issue. For this purpose, palynologists mostly rely on cultural indicator pollen types and related indices that consist of sums or ratios of these pollen types. However, the high environmental and biogeographical specificity of cultural indicator plants hinders the application of the currently available indices to wide geographical settings. Furthermore, the achievable taxonomic resolution of cultural indicator pollen types may hamper their indicative capacity. In this study, we propose the agricultural land use probability (LUP) index, a novel approach to quantify human impact intensity on European ecosystems based on cultural indicator pollen types. From the ‘classic’ cultural indicators, we construct the LUP index by selecting those with the best indicator capacity based on bioindication criteria. We first train the LUP index using twenty palynological sequences along a broad environmental gradient, spanning from treeless alpine to subtropical mediterranean evergreen plant communities. We then validate the LUP index using independent pollen datasets and archaeological proxies. Finally, we discuss the suitability of the selected pollen types and the potential of the LUP index for quantifying Holocene human impact in Europe, concluding that careful application of the LUP index may significantly contribute to refining pollen-based land-use reconstructions.
Climate change can act to facilitate or inhibit invasions of non-native species. Here, we address the influence of climate change on control of non-native common carp (hereafter, carp), a species recognized as one of the “world's worst” invaders across the globe. Control of this species is exceedingly difficult, as it exhibits rapid population growth and compensatory density dependence. In many locations where carp have invaded, however, climate change is altering hydrologic regimes and may influence population demography and efficacy of human control efforts. To further evaluate these processes, we employed a modified version of an age-based population model (CarpMOD), to investigate how hydrologic variability (change in lake area) influences carp population dynamics and control efforts in Malheur Lake, southeastern Oregon, USA. We explored how changes in lake area influence carp populations under three control scenarios: (1) no carp removal, (2) carp removal during low water years, and (3) carp removal during all years. Lake area fluctuations strongly influenced carp populations and the efficacy of carp control. Modeled carp biomass peaked when the lake transitioned from high-to-low levels, and carp biomass declined when lake area transitioned from low-to-high. Removing carp during low water periods—when fish were concentrated into a smaller area—reduced carp populations almost as much as removing carp every year. Furthermore, the effectiveness of control efforts increased with the prevalence and severity of low lake conditions (longer durations of very low lake area). These simulations suggest that a drier climate may naturally decrease carp populations and make them easier to control. However, drier conditions may also negatively affect aquatic ecosystems and potentially have a greater impact than non-native species themselves.