Plants vary in their hydrological and climatic niches. How these niche dimensions covary among closely related species can help identify co‐adaptations to hydrological and climatic factors, as well as predict biodiversity responses to environmental change.
Western United States.
Relationships between riparian dependence and climate niches of willows (Salix L.) were assessed, incorporating phylogenetics and functional traits to understand the adaptive nature of those relationships. The riparian dependence niche was estimated as the mean distance between georeferenced occurrence records and the nearest stream based on the National Hydrography Database. Results were compared to oaks (Quercus L.), a less riparian‐dependent clade, with the expectation of different niche relationships.
Willows generally occurred closer to streams than expected by chance, but riparian dependence varied substantially among species. Riparian dependence was positively correlated with mean annual temperature and diurnal temperature range niche, both indicators of atmospheric demand on evapotranspiration. Phylogenetic independent contrast correlations for these relationships were significant as well, and the high degree of niche convergence among species indicated evolutionarily labile co‐adaptations to riparian dependence and atmospheric demand. Plant height increased with mean annual temperature niche, and specific leaf area increased with residual variation in height, indicating underlying morphological correlates of niche variation. Oaks, on the other hand, exhibited no relationship between atmospheric demand and riparian dependence, and weaker niche relationships with riparian dependence overall.
These results support the assertion that hydric‐adapted, woody riparian plants compensate for increased atmospheric demand on transpiration with a reliable supply of water provided by riparian habitats and that this trade‐off may be unique from mesic–xeric woody plants. Conservation of warm‐adapted riparian trees and shrubs under increasing temperatures and atmospheric demand may necessitate reversal of groundwater depletion. Cool‐adapted species may be best conserved through maintenance or expansion of riparian buffers as they become more riparian obligate with warming.
","language":"English","publisher":"Wiley","doi":"10.1111/ddi.13192","usgsCitation":"Butterfield, B.J., Palmquist, E.C., and Hultine, K.R., 2021, Regional coordination between riparian dependence and atmospheric demand in willows (Salix L.) of western North America: Diversity and Distributions, v. 27, no. 21, p. 377-388, https://doi.org/10.1111/ddi.13192.","productDescription":"12 p.","startPage":"377","endPage":"388","ipdsId":"IP-116352","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":454296,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ddi.13192","text":"Publisher Index Page"},{"id":382510,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, Mexico, United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.24609374999999,\n 32.54681317351514\n ],\n [\n -114.60937499999999,\n 32.62087018318113\n ],\n [\n -110.830078125,\n 31.353636941500987\n ],\n [\n -108.19335937499999,\n 31.57853542647338\n ],\n [\n -105.64453124999999,\n 27.994401411046148\n ],\n [\n -105.64453124999999,\n 26.03704188651584\n ],\n [\n -104.23828125,\n 25.085598897064752\n ],\n [\n -102.74414062499999,\n 27.839076094777816\n ],\n [\n -101.07421875,\n 25.085598897064752\n ],\n [\n -99.49218749999999,\n 22.268764039073968\n ],\n [\n -97.119140625,\n 26.03704188651584\n ],\n [\n -96.591796875,\n 28.69058765425071\n ],\n [\n -93.42773437499999,\n 29.6880527498568\n ],\n [\n -92.724609375,\n 38.34165619279595\n ],\n [\n -93.69140625,\n 42.293564192170095\n ],\n [\n -96.591796875,\n 46.558860303117164\n ],\n [\n -105.556640625,\n 51.069016659603896\n ],\n [\n -113.90625,\n 52.05249047600099\n ],\n [\n -118.740234375,\n 52.96187505907603\n ],\n [\n -119.091796875,\n 49.89463439573421\n ],\n [\n -122.16796875,\n 49.15296965617042\n ],\n [\n -124.98046874999999,\n 48.40003249610685\n ],\n [\n -124.45312499999999,\n 43.26120612479979\n ],\n [\n -124.541015625,\n 39.70718665682654\n ],\n [\n -121.37695312499999,\n 35.53222622770337\n ],\n [\n -117.24609374999999,\n 32.54681317351514\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"27","issue":"21","noUsgsAuthors":false,"publicationDate":"2020-11-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Butterfield, Bradley J. 0000-0003-0974-9811","orcid":"https://orcid.org/0000-0003-0974-9811","contributorId":167009,"corporation":false,"usgs":false,"family":"Butterfield","given":"Bradley","email":"","middleInitial":"J.","affiliations":[{"id":24591,"text":"Merriam-Powell Center for Environmental Research and Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, USA","active":true,"usgs":false}],"preferred":false,"id":801745,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Palmquist, Emily C. 0000-0003-1069-2154 epalmquist@usgs.gov","orcid":"https://orcid.org/0000-0003-1069-2154","contributorId":5669,"corporation":false,"usgs":true,"family":"Palmquist","given":"Emily","email":"epalmquist@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":801746,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hultine, Kevin R. 0000-0001-9747-6037","orcid":"https://orcid.org/0000-0001-9747-6037","contributorId":23772,"corporation":false,"usgs":true,"family":"Hultine","given":"Kevin","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":801747,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70218644,"text":"70218644 - 2021 - Telemetry evaluation of carbon dioxide as a behavioral deterrent for invasive carps","interactions":[],"lastModifiedDate":"2021-03-03T12:58:09.415186","indexId":"70218644","displayToPublicDate":"2020-11-06T06:55:37","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Telemetry evaluation of carbon dioxide as a behavioral deterrent for invasive carps","docAbstract":"Carbon dioxide (CO2) mixed into water is being explored as a possible management strategy to deter the upstream movements of invasive carps through navigation locks and other migratory pinch-points. This study used two-dimensional acoustic telemetry to assess the effectiveness of dissolved CO2 as a chemosensory deterrent to two carp species in a large U-shaped pond. Free-swimming movements of telemetered bighead carp (Hypophthalmichthys nobilis) and grass carp (Ctenopharyngodon idella) were documented 24 h before treatment and 24 h during treatments at 60, 121 and 213 mg/L CO2 (mean concentrations in pond water). Several behavioral endpoints were then quantified and compared to evaluate deterrence efficacy. In general, results showed that both carp species responded similarly to CO2 treatments. Carps consistently relocated into areas away from the injection site and made fewer attempts to re-enter CO2 treated areas. On average, CO2 treatments reduced mid-line crosses between untreated and treated sides of the pond by 58% at 121 mg/L CO2 and 78% at 213 mg/L CO2 relative to normal swimming movements recorded before treatment. Fish swim speeds increased significantly when inside the CO2 plume during treatments during 213 mg/L CO2 trials relative to swim speeds outside the plume, possibly indicative of active searching and avoidance responses. Overall, this study found that CO2 altered the behavior of bighead carp and grass carp. Natural resource agencies could consider the CO2 concentrations identified in this study to inform future applications to deter invasive carps from locations where they are at-risk to move upstream.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2020.10.004","usgsCitation":"Cupp, A.R., Lopez, A.K., Smerud, J.R., Tix, J., Rivera, J., Swyers, N.M., Brey, M.K., Woodley, C.M., Smith, D.L., and Gaikowski, M., 2021, Telemetry evaluation of carbon dioxide as a behavioral deterrent for invasive carps: Journal of Great Lakes Research, v. 47, no. 1, p. 59-68, https://doi.org/10.1016/j.jglr.2020.10.004.","productDescription":"10 p.","startPage":"59","endPage":"68","ipdsId":"IP-113141","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":436647,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9QBSCIE","text":"USGS data release","linkHelpText":"Acoustic telemetry evaluation of carbon dioxide as a behavioral deterrent for invasive fishes data"},{"id":383738,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"47","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Cupp, Aaron R. 0000-0001-5995-2100 acupp@usgs.gov","orcid":"https://orcid.org/0000-0001-5995-2100","contributorId":5162,"corporation":false,"usgs":true,"family":"Cupp","given":"Aaron","email":"acupp@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":811239,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lopez, Ashley K 0000-0002-7676-4803 aelopez@usgs.gov","orcid":"https://orcid.org/0000-0002-7676-4803","contributorId":253119,"corporation":false,"usgs":false,"family":"Lopez","given":"Ashley","email":"aelopez@usgs.gov","middleInitial":"K","affiliations":[{"id":50484,"text":"ERDC","active":true,"usgs":false}],"preferred":false,"id":811240,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smerud, Justin R. 0000-0003-4385-7437 jrsmerud@usgs.gov","orcid":"https://orcid.org/0000-0003-4385-7437","contributorId":5031,"corporation":false,"usgs":true,"family":"Smerud","given":"Justin","email":"jrsmerud@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":811241,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tix, John A.","contributorId":126766,"corporation":false,"usgs":false,"family":"Tix","given":"John A.","affiliations":[{"id":6602,"text":"Great Lakes Science Center, Hammond Bay Biological Station","active":true,"usgs":false}],"preferred":false,"id":811242,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rivera, Jose 0000-0003-3756-6860 jrivera@usgs.gov","orcid":"https://orcid.org/0000-0003-3756-6860","contributorId":201064,"corporation":false,"usgs":true,"family":"Rivera","given":"Jose","email":"jrivera@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":811243,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Swyers, Nicholas M. nswyers@usgs.gov","contributorId":253120,"corporation":false,"usgs":true,"family":"Swyers","given":"Nicholas","email":"nswyers@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":811244,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Brey, Marybeth K. 0000-0003-4403-9655 mbrey@usgs.gov","orcid":"https://orcid.org/0000-0003-4403-9655","contributorId":187651,"corporation":false,"usgs":true,"family":"Brey","given":"Marybeth","email":"mbrey@usgs.gov","middleInitial":"K.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":811245,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Woodley, Christa M.","contributorId":253121,"corporation":false,"usgs":false,"family":"Woodley","given":"Christa","email":"","middleInitial":"M.","affiliations":[{"id":18947,"text":"USACE ERDC","active":true,"usgs":false}],"preferred":false,"id":811246,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Smith, David L.","contributorId":192711,"corporation":false,"usgs":false,"family":"Smith","given":"David","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":811247,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Gaikowski, Mark P. 0000-0002-6507-9341 mgaikowski@usgs.gov","orcid":"https://orcid.org/0000-0002-6507-9341","contributorId":149357,"corporation":false,"usgs":true,"family":"Gaikowski","given":"Mark P.","email":"mgaikowski@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":811248,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70216788,"text":"70216788 - 2021 - Nowhere to hide: The importance of instream cover for stream‐living Coastal Cutthroat Trout during seasonal low flow","interactions":[],"lastModifiedDate":"2021-03-19T20:30:11.555251","indexId":"70216788","displayToPublicDate":"2020-11-05T09:03:09","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1471,"text":"Ecology of Freshwater Fish","active":true,"publicationSubtype":{"id":10}},"title":"Nowhere to hide: The importance of instream cover for stream‐living Coastal Cutthroat Trout during seasonal low flow","docAbstract":"Through their multiple functions, refuges may be important for stream‐living fishes, particularly during stressful events such as seasonal low flow or drought. Coastal Cutthroat Trout Oncorhynchus clarkii clarkii is an ideal study organism to understand the importance of refuge. During seasonal low flow, lower water levels limit access to refuge and emigration, survival of fish is low, and predation risk is high. Under these conditions, we studied patterns of cover use from field observations and tested predictions from multiple hypotheses about cover use in a semi‐natural experiment. Boulders were the main cover selected by trout in natural streams. Trout disproportionately used cover near deeper water, and they selected larger‐sized cover in shallower water. Trout showed plasticity to switch among behaviours, concealing under cover and emigrating as first options, followed by grouping, and then habitat shifting. Lack of feeding and growth suggested that perceived threat of predation was a more important driver of behaviour than foraging. Emigration was also linked to cover, with higher levels of emigration associated with less cover availability, revealing a potential link between refuge and demography through emigration. Except for feeding, the intensity of alternative behaviours can increase or decrease depending on refuge availability. Collectively, findings of this work indicate that cover can be considered a critical limiting resource along with other fundamental resources of food and space for stream‐living fish.
Time series of water‐year runoff for 2,109 hydrologic units (HUs) across the conterminous United States (CONUS) for the 1900 through 2014 period were used to identify drought and pluvial (i.e., wet) periods. Characteristics of the drought and pluvial events including frequency, duration, and severity were examined and compared. Additionally, a similar analysis was performed using gridded tree‐ring reconstructions of the Palmer Drought Severity Index (PDSI) for the period 1475 through 2005 to place the drought and pluvial characteristics determined using water‐year runoff for 1900 through 2014 in the context of multi‐century climate variability. The temporal and spatial variability of droughts and pluvials determined using runoff for the 1900 through 2014 period indicated that most drought events in the CONUS occurred before about 1970, whereas most pluvial periods occurred after about 1970. This change in the frequencies of drought and pluvial events around 1970 was largely related to an increase in fall (October through December) precipitation across much of the central United States. Also, the duration and severity of droughts and pluvials identified using runoff for the 1900 through 2014 period generally were not significantly different from the drought and pluvial characteristics identified using the PDSI for the 1475 through 2005 period.
A hydrogeochemical study using high resolution ICP-MS was undertaken at the Taurus and other porphyry Cu-Mo(-Au) occurrences and Ag-Au-Cu (+/- Pb, Zn) occurrences with epithermal-style characteristics in the Yukon-Tanana upland region of eastern Alaska. Surface water samples were collected from 30 sites on creeks that drain known deposits and occurrences and surrounding presumably unmineralized areas. Water samples for the entire ∼9 km length of McCord Creek, which drains the Taurus deposit, and those from streams draining the areas at and near the Bluff and Dennison porphyry occurrences have high conductivity values (492 to 1250 μS/cm) and consistently high concentrations of B (3-250 μg/L), Co (2.3 to 42 μg/L), Mn (339 to 4750 μg/L), Re (0.012 to 0.1 μg/L), and SO42- (>200 mg/L), all of which are well above the median value for this data set and significantly greater than concentrations in water samples from the unmineralized areas. These are the best pathfinder elements specifically for porphyry style deposits because most of them are not anomalous in waters near epithermal occurrences. Copper concentrations are high (up to 115 μg/L) in some low-pH water samples from McCord Creek and drainages around Bluff, and a few near neutral pH waters have high molybdenum (>1 μg/L), but neither element is consistently anomalous in close vicinity to the porphyry occurrences, possibly due to a metal-poor, sulfide-poor leached cap (average of ∼50 m) that overlies supergene and hypogene mineralized zones and is the dominant rock at surface. High concentrations of Bi and/or As occur in many waters associated with mineralized areas, particularly the Bluff and Dennison occurrences. In general, the element associations related to porphyry deposits reflect the deposit mineralogy, as well as size of the footprint related to alteration and mineralization.
Changing environments of temperature, precipitation and moisture availability can affect vegetation in ecosystems, by affecting regeneration from the seed bank. Our objective was to explore the responses of soil seed bank germination to climate-related environments along geographic gradients. We collected seed banks in baldcypress (Taxodium distichum) swamps along the Mississippi River and the Gulf of Mexico Coast in the United States, which have distinct temperature and/or precipitation gradients, and germinated them in a greenhouse. The frequency, richness and seed density of species germinated from the seed bank were compared between various geographic locations, experimental water regimes (saturated, flooded) and wetland types (tidal, non-tidal and inland swamps). We also analyzed the relationship of seed density to the environment by using a Non-metric Multi-dimensional Scaling (NMDS) model. Sixty-one species germinated from the seed bank, differing in pattern by geographic location, experimental water regime and wetland type. The foundation species (i.e., T. distichum and Cephalanthus occidentalis) germinated with a niche affinity for the northern part of the latitudinal gradient (Tennessee and Illinois) and these species may shift northward with climate change. Some species had higher seed density in the locations that were subject to more persistent drought conditions (e.g., Texas) including Cyperus rotundus and Gratiola virginiana, indicating that these species may be better adapted to sites with high temperature and low precipitation. In contrast, certain species including Saururus cernuus and Ludwigia palustris were present throughout the range of these gradients, and so may be more resilient to any future climate shifts. We found that the regeneration potential of baldcypress swamps might be altered by changes in local and climate environment because of nuances of responses of seed banks to climates along latitudinal and longitudinal gradients. Our study can help predict vegetation regeneration potential to climate change environments depending on the ability of these species to disperse and maintain seed banks.
Microbial skin assemblages, including fungal communities, can influence host resistance to infectious diseases. The diversity-invasibility hypothesis predicts that high-diversity communities are less easily invaded than species-poor communities, and thus diverse microbial communities may prevent pathogens from colonizing a host. To explore the hypothesis that host fungal communities mediate resistance to infection by fungal pathogens, we investigated characteristics of bat skin fungal communities as they relate to susceptibility to the emerging disease white-nose syndrome (WNS). Using a culture-based approach, we compared skin fungal assemblage characteristics of 10 bat species that differ in susceptibility to WNS across 10 eastern U.S. states. The fungal assemblages on WNS-susceptible bat species had significantly lower alpha diversity and abundance compared to WNS-resistant species. Overall fungal assemblage structure did not vary based on WNS-susceptibility, but several yeast species were differentially abundant on WNS-resistant bat species. One yeast species inhibited Pseudogymnoascus destructans (Pd), the causative agent on WNS, in vitro under certain conditions, suggesting a possible role in host protection. Further exploration of interactions between Pd and constituents of skin fungal assemblages may prove useful for predicting susceptibility of bat populations to WNS and for developing effective mitigation strategies.
Human-mediated hybridization threatens many native species, but the effects of introgressive hybridization on life-history expression are rarely quantified, especially in vertebrates. We quantified the effects of non-native rainbow trout admixture on important life-history traits including growth and partial migration behavior in three populations of westslope cutthroat trout over five years. Rainbow trout admixture was associated with increased summer growth rates in all populations and decreased spring growth rates in two populations with cooler spring temperatures. These results indicate that non-native admixture may increase growth under warmer conditions, but cutthroat trout have higher growth rates during cooler periods. Non-native admixture consistently increased expression of migratory behavior, suggesting that there is a genomic basis for life-history differences between these species. Our results show that effects of interspecific hybridization on fitness traits can be the product of genotype-by-environment interactions even when there are minor differences in environmental optima between hybridizing species. These results also indicate that while environmentally mediated traits like growth may play a role in population-level consequences of admixture, strong genetic influences on migratory life-history differences between these species likely explains the continued spread of non-native hybridization at the landscape-level, despite selection against hybrids at the population-level.
","language":"English","publisher":"Wiley","doi":"10.1111/eva.13163","usgsCitation":"Strait, J., Eby, L., Kovach, R., Muhlfeld, C.C., Boyer, M., Amish, S.J., Smith, S., Lowe, W., and Luikart, G., 2021, Hybridization alters growth and migratory life-history expression of native trout: Evolutionary Applications, v. 14, p. 821-833, https://doi.org/10.1111/eva.13163.","productDescription":"13 p.","startPage":"821","endPage":"833","ipdsId":"IP-120443","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":454307,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/eva.13163","text":"Publisher Index Page"},{"id":387126,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.213623046875,\n 47.04766864046083\n ],\n [\n -111.64306640625,\n 47.04766864046083\n ],\n [\n -111.64306640625,\n 49.009050809382046\n ],\n [\n -115.213623046875,\n 49.009050809382046\n ],\n [\n -115.213623046875,\n 47.04766864046083\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"14","noUsgsAuthors":false,"publicationDate":"2020-12-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Strait, Jeffrey 0000-0002-0901-3911","orcid":"https://orcid.org/0000-0002-0901-3911","contributorId":260879,"corporation":false,"usgs":false,"family":"Strait","given":"Jeffrey","email":"","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":819039,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eby, Lisa A","contributorId":251751,"corporation":false,"usgs":false,"family":"Eby","given":"Lisa A","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":819040,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kovach, Ryan P.","contributorId":126724,"corporation":false,"usgs":false,"family":"Kovach","given":"Ryan P.","affiliations":[{"id":6580,"text":"University of Montana, Flathead Lake Biological Station, Polson, Montana 59860, USA","active":true,"usgs":false}],"preferred":false,"id":819041,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Muhlfeld, Clint C. 0000-0002-4599-4059 cmuhlfeld@usgs.gov","orcid":"https://orcid.org/0000-0002-4599-4059","contributorId":924,"corporation":false,"usgs":true,"family":"Muhlfeld","given":"Clint","email":"cmuhlfeld@usgs.gov","middleInitial":"C.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":819042,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Boyer, Matthew","contributorId":124595,"corporation":false,"usgs":false,"family":"Boyer","given":"Matthew","affiliations":[{"id":5133,"text":"Montana Fish Wildlife and Parks, Kalispell, Montana 59901","active":true,"usgs":false}],"preferred":false,"id":819043,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Amish, Stephen J.","contributorId":104799,"corporation":false,"usgs":false,"family":"Amish","given":"Stephen","email":"","middleInitial":"J.","affiliations":[{"id":5097,"text":"University of Montana, Division of Biological Sciences","active":true,"usgs":false}],"preferred":false,"id":819044,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Smith, Seth","contributorId":189234,"corporation":false,"usgs":false,"family":"Smith","given":"Seth","email":"","affiliations":[],"preferred":false,"id":819045,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lowe, Winsor H.","contributorId":64532,"corporation":false,"usgs":false,"family":"Lowe","given":"Winsor H.","affiliations":[{"id":5097,"text":"University of Montana, Division of Biological Sciences","active":true,"usgs":false}],"preferred":false,"id":819046,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Luikart, Gordon","contributorId":124531,"corporation":false,"usgs":false,"family":"Luikart","given":"Gordon","affiliations":[{"id":5091,"text":"Flathead Lake Biological Station, Fish and Wildlife Genomics Group, Division of Biological Sciences, University of Montana, Polson, MT 59860, USA","active":true,"usgs":false}],"preferred":false,"id":819047,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70211530,"text":"70211530 - 2021 - Foreword","interactions":[],"lastModifiedDate":"2021-04-19T16:35:11.260297","indexId":"70211530","displayToPublicDate":"2020-11-03T11:30:33","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Foreword","docAbstract":"No abstract available.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Spatial dynamics and ecology of large ungulate populations in tropical forests of India","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","usgsCitation":"Royle, J.A., 2021, Foreword, chap. of Spatial dynamics and ecology of large ungulate populations in tropical forests of India, p. vii-ix.","productDescription":"3 p.","startPage":"vii","endPage":"ix","ipdsId":"IP-118087","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":385201,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":376861,"type":{"id":15,"text":"Index Page"},"url":"https://link.springer.com/book/10.1007%2F978-981-15-6934-0#toc"}],"country":"India","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[77.83745,35.49401],[78.91227,34.32194],[78.81109,33.5062],[79.20889,32.99439],[79.17613,32.48378],[78.45845,32.61816],[78.73889,31.51591],[79.72137,30.88271],[81.11126,30.18348],[80.47672,29.72987],[80.08842,28.79447],[81.0572,28.4161],[81.99999,27.92548],[83.30425,27.36451],[84.67502,27.2349],[85.25178,26.7262],[86.02439,26.63098],[87.22747,26.3979],[88.06024,26.41462],[88.1748,26.81041],[88.04313,27.44582],[88.12044,27.87654],[88.73033,28.08686],[88.81425,27.29932],[88.83564,27.09897],[89.74453,26.7194],[90.37327,26.87572],[91.21751,26.80865],[92.03348,26.83831],[92.10371,27.45261],[91.69666,27.77174],[92.50312,27.89688],[93.41335,28.64063],[94.56599,29.27744],[95.4048,29.03172],[96.11768,29.4528],[96.58659,28.83098],[96.24883,28.41103],[97.32711,28.26158],[97.40256,27.88254],[97.05199,27.69906],[97.134,27.08377],[96.41937,27.26459],[95.12477,26.57357],[95.15515,26.00131],[94.60325,25.1625],[94.55266,24.67524],[94.10674,23.85074],[93.32519,24.07856],[93.28633,23.04366],[93.06029,22.70311],[93.16613,22.27846],[92.67272,22.04124],[92.14603,23.6275],[91.86993,23.62435],[91.70648,22.98526],[91.15896,23.50353],[91.46773,24.07264],[91.91509,24.13041],[92.3762,24.97669],[91.7996,25.14743],[90.87221,25.1326],[89.92069,25.26975],[89.83248,25.96508],[89.35509,26.01441],[88.56305,26.44653],[88.20979,25.76807],[88.93155,25.23869],[88.30637,24.86608],[88.08442,24.50166],[88.69994,24.23371],[88.52977,23.63114],[88.87631,22.87915],[89.03196,22.05571],[88.88877,21.69059],[88.2085,21.70317],[86.9757,21.49556],[87.03317,20.74331],[86.49935,20.15164],[85.06027,19.47858],[83.94101,18.30201],[83.18922,17.67122],[82.19279,17.01664],[82.19124,16.55666],[81.69272,16.31022],[80.792,15.95197],[80.3249,15.89918],[80.02507,15.13641],[80.23327,13.83577],[80.28629,13.00626],[79.86255,12.05622],[79.858,10.35728],[79.34051,10.30885],[78.88535,9.54614],[79.18972,9.21654],[78.27794,8.93305],[77.94117,8.25296],[77.5399,7.96553],[76.59298,8.89928],[76.13006,10.29963],[75.74647,11.30825],[75.3961,11.78125],[74.86482,12.74194],[74.61672,13.99258],[74.44386,14.61722],[73.5342,15.99065],[73.11991,17.92857],[72.82091,19.20823],[72.82448,20.4195],[72.63053,21.35601],[71.17527,20.75744],[70.47046,20.87733],[69.16413,22.0893],[69.64493,22.45077],[69.3496,22.84318],[68.17665,23.69197],[68.8426,24.35913],[71.04324,24.35652],[70.8447,25.2151],[70.28287,25.72223],[70.16893,26.49187],[69.51439,26.94097],[70.6165,27.9892],[71.77767,27.91318],[72.82375,28.96159],[73.45064,29.97641],[74.42138,30.97981],[74.40593,31.69264],[75.25864,32.27111],[74.45156,32.7649],[74.10429,33.44147],[73.74995,34.3177],[74.2402,34.74889],[75.75706,34.50492],[76.87172,34.65354],[77.83745,35.49401]]]},\"properties\":{\"name\":\"India\"}}]}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":139626,"corporation":false,"usgs":true,"family":"Royle","given":"J.","email":"aroyle@usgs.gov","middleInitial":"Andrew","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":794529,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70228230,"text":"70228230 - 2021 - Sibship reconstruction with SNPs illuminates the scope of a cryptic invasion of Asian Swamp Eels (Monopterus albus) in Georgia, USA","interactions":[],"lastModifiedDate":"2022-02-14T12:25:38.150683","indexId":"70228230","displayToPublicDate":"2020-11-03T11:28:23","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Sibship reconstruction with SNPs illuminates the scope of a cryptic invasion of Asian Swamp Eels (Monopterus albus) in Georgia, USA","title":"Sibship reconstruction with SNPs illuminates the scope of a cryptic invasion of Asian Swamp Eels (Monopterus albus) in Georgia, USA","docAbstract":"Cryptic invasive species are particularly problematic to study, manage, and control because of the difficulty detecting these species within their invaded habitats. Such is the case of the Asian Swamp Eel (Monopterus albus; ASE) where it is established in vegetated marshes along the Chattahoochee River, Georgia. Adult eels have been nearly impossible to detect or quantify with traditional sampling, although leaf-litter trapping of juvenile ASEs has been somewhat successful. In this study, we leveraged a collection of juveniles from the 2015 cohort and used single-nucleotide polymorphisms to reconstruct sibship among these juveniles in COLONY. Sibship reconstruction allowed us to learn about adult breeding behaviors and provided the first quantified estimates of breeder abundance. Pedigree reconstruction revealed that adults of both sexes were polygamous and likely traveled up to 0.5 km among marsh habitats during a single breeding season. Estimates of the number of breeding adults contributing to offspring (Ns) and the effective number of breeders (Nb) indicated an approximate minimum bound of 100 breeding adults in the marshes in 2015. Our study updated the invasion status of a cryptic population formerly riddled with uncertainty, highlighting that low captures of adult eels in the study area have been the result of low detectability, not low abundance. Given that low detectability would likely hinder removal efforts, our results suggest that future efforts could focus on suppression of ASE abundance when they are most vulnerable to capture and containing the spatial extent of the invasion.
","language":"English","publisher":"Springer Link","doi":"10.1007/s10530-020-02384-5","usgsCitation":"Taylor, A., Bangs, M.R., and Long, J.M., 2021, Sibship reconstruction with SNPs illuminates the scope of a cryptic invasion of Asian Swamp Eels (Monopterus albus) in Georgia, USA: Biological Invasions, v. 23, p. 569-580, https://doi.org/10.1007/s10530-020-02384-5.","productDescription":"12 p.","startPage":"569","endPage":"580","ipdsId":"IP-109886","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":395634,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Georgia","otherGeospatial":"Chattahoochee River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.39371109008789,\n 33.9874951489\n ],\n [\n -84.36555862426758,\n 33.9874951489\n ],\n [\n -84.36555862426758,\n 34.0079888707242\n ],\n [\n -84.39371109008789,\n 34.0079888707242\n ],\n [\n -84.39371109008789,\n 33.9874951489\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"23","noUsgsAuthors":false,"publicationDate":"2020-11-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Taylor, A. T.","contributorId":274894,"corporation":false,"usgs":false,"family":"Taylor","given":"A. T.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":833486,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bangs, M. R.","contributorId":274895,"corporation":false,"usgs":false,"family":"Bangs","given":"M.","email":"","middleInitial":"R.","affiliations":[{"id":7092,"text":"Florida State University","active":true,"usgs":false}],"preferred":false,"id":833487,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Long, James M. 0000-0002-8658-9949 jmlong@usgs.gov","orcid":"https://orcid.org/0000-0002-8658-9949","contributorId":3453,"corporation":false,"usgs":true,"family":"Long","given":"James","email":"jmlong@usgs.gov","middleInitial":"M.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":833488,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70216442,"text":"70216442 - 2021 - A Bayesian Dirichlet process community occupancy model to estimate community structure and species similarity","interactions":[],"lastModifiedDate":"2021-03-05T21:58:59.699233","indexId":"70216442","displayToPublicDate":"2020-11-03T06:58:25","publicationYear":"2021","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":"A Bayesian Dirichlet process community occupancy model to estimate community structure and species similarity","docAbstract":"Community occupancy models estimate species‐specific parameters while sharing information across species by treating parameters as sampled from a common distribution. When communities consist of discrete groups, shrinkage of estimates towards the community mean can mask differences among groups. Infinite mixture models using a Dirichlet process (DP) distribution, in which the number of latent groups is estimated from the data, have been proposed as a solution. In addition to community structure, these models estimate species similarity, which allows testing hypotheses about whether traits drive species response to environmental conditions. We develop a community occupancy model (COM) using a DP distribution to model species‐level parameters. Because clustering algorithms are sensitive to dimensionality and distinctiveness of clusters, we conducted a simulation study to explore performance of the DP‐COM with different dimensions (i.e., different numbers of model parameters with species‐level DP random effects) and under varying cluster differences. Because the DP‐COM is computationally expensive, we compared its estimates to a COM with a normal random species effect. We further applied the DP‐COM model to a bird dataset from Uganda. Estimates of the number of clusters and species cluster identity improved with increasing difference among clusters and increasing dimensions of the DP; but the number of clusters was always overestimated. Estimates of number of sites occupied and species and community level covariate coefficients on occupancy probability were generally unbiased with (near‐) nominal 95% Bayesian Credible Interval coverage. Accuracy of estimates from the normal and the DP‐COM were similar. The DP‐COM clustered 166 bird species into 27 clusters regarding their affiliation with open or woodland habitat and distance to oil wells. Estimates of covariate coefficients were similar between a normal and the DP‐COM. Except sunbirds, species within a family were not more similar in their response to these covariates than the overall community. Given that estimates were consistent between the normal and the DP‐COM, and considering the computational burden for the DP models, we recommend using the DP‐COM only when the analysis focuses on community structure and species similarity, as these quantities can only be obtained under the DP‐COM.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.2249","usgsCitation":"Sollmann, R., Eaton, M.J., Link, W., Mulundo, P., Ayebare, S., Prinsloo, S., Plumptre, A.J., and Johnson, D., 2021, A Bayesian Dirichlet process community occupancy model to estimate community structure and species similarity: Ecological Applications, v. 31, no. 2, e2249, https://doi.org/10.1002/eap.2249.","productDescription":"e2249","ipdsId":"IP-090810","costCenters":[{"id":40926,"text":"Southeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":454310,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/eap.2249","text":"External Repository"},{"id":380583,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-01-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Sollmann, Rahel 0000-0002-1607-2039","orcid":"https://orcid.org/0000-0002-1607-2039","contributorId":244998,"corporation":false,"usgs":false,"family":"Sollmann","given":"Rahel","affiliations":[{"id":12711,"text":"UC Davis","active":true,"usgs":false}],"preferred":false,"id":805121,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eaton, Mitchell J. 0000-0001-7324-6333","orcid":"https://orcid.org/0000-0001-7324-6333","contributorId":213526,"corporation":false,"usgs":true,"family":"Eaton","given":"Mitchell","middleInitial":"J.","affiliations":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":805123,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Link, William 0000-0002-9913-0256","orcid":"https://orcid.org/0000-0002-9913-0256","contributorId":221718,"corporation":false,"usgs":true,"family":"Link","given":"William","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":805122,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mulundo, Paul","contributorId":245000,"corporation":false,"usgs":false,"family":"Mulundo","given":"Paul","email":"","affiliations":[{"id":13272,"text":"Wildlife Conservation Society","active":true,"usgs":false}],"preferred":false,"id":805124,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ayebare, Samuel","contributorId":245001,"corporation":false,"usgs":false,"family":"Ayebare","given":"Samuel","email":"","affiliations":[{"id":13272,"text":"Wildlife Conservation Society","active":true,"usgs":false}],"preferred":false,"id":805125,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Prinsloo, Sarah","contributorId":245002,"corporation":false,"usgs":false,"family":"Prinsloo","given":"Sarah","email":"","affiliations":[{"id":13272,"text":"Wildlife Conservation Society","active":true,"usgs":false}],"preferred":false,"id":805126,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Plumptre, Andrew J.","contributorId":213154,"corporation":false,"usgs":false,"family":"Plumptre","given":"Andrew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":805127,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Johnson, D.S.","contributorId":245003,"corporation":false,"usgs":false,"family":"Johnson","given":"D.S.","affiliations":[{"id":17856,"text":"National Marine Fisheries Service, NOAA","active":true,"usgs":false}],"preferred":false,"id":805128,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70236889,"text":"70236889 - 2021 - Damping values derived from surface-source, downhole-receiver measurements at 22 sites in the San Francisco Bay Area of central California and the San Fernando Valley of southern California","interactions":[],"lastModifiedDate":"2022-09-21T11:58:20.742945","indexId":"70236889","displayToPublicDate":"2020-11-03T06:55:15","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Damping values derived from surface-source, downhole-receiver measurements at 22 sites in the San Francisco Bay Area of central California and the San Fernando Valley of southern California","docAbstract":"A method discussed in Gibbs, Boore, et al. (1994) was applied to surface‐source, downhole‐receiver recordings at 22 boreholes, in the San Francisco Bay area in central California and the San Fernando Valley of southern California, to determine the average damping ratio of shear waves over depth intervals ranging from about 10 m to as much as 245 m (at one site), with most maximum depths being between 35 and 90 m. The average damping values range from somewhat less than 1% to almost 8%, with little dependence on grain size for sites in sediments. Surprisingly, the average damping values for sites with average velocities greater than about
Atlantic salmon populations in Maine remain critically low despite extensive hatchery supplementation and habitat improvement efforts. In 2000, the Gulf of Maine Distinct Population Segment was listed as Endangered under the ESA with joint listing authority shared by the National Oceanic and Atmospheric Administration (NOAA) and the United States Fish and Wildlife Service (USFWS). Because, regulators, and tribal, federal and state managers operate with independent authorities, recovery decisions depend upon effective communication and coordination among groups. Using a mixed-methods approach, we surveyed (n = 41) and interviewed (n = 28) members of the Atlantic Salmon Recovery Framework (ASRF), the joint governance structure responsible for Atlantic salmon management in Maine. We used survey results to examine the communication between members of ASRF through communication network analysis. While there is a relatively high network density for individual communication (56 %), connections are decentralized, a characteristic that can be incompatible with some organizational structures. Challenges reported by members fit into three general categories; i. slow and ineffective decision-making, ii. confusion surrounding leadership and accountability, and iii. low adaptive capacity. Despite these challenges, participants reported a commitment to maintaining a collaborative governance structure and a long history of inter-organizational relationships. This introspective effort has led to a reorganization effort to optimize communication pathways.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsci.2020.10.001","usgsCitation":"Flye, M.E., Sponarski, C.C., Zydlewski, J.D., and McGreavy, B., 2021, Understanding collaborative governance from a communication network perspective: A case study of the Atlantic Salmon recovery framework: Environmental Science and Policy, v. 115, p. 79-90, https://doi.org/10.1016/j.envsci.2020.10.001.","productDescription":"12 p.","startPage":"79","endPage":"90","ipdsId":"IP-115322","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":454314,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envsci.2020.10.001","text":"Publisher Index Page"},{"id":395781,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maine","otherGeospatial":"Gulf of Maine","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.57617187499999,\n 42.69858589169842\n ],\n [\n -68.961181640625,\n 42.69858589169842\n ],\n [\n -67.181396484375,\n 43.36512572875844\n ],\n [\n -66.302490234375,\n 44.213709909702054\n ],\n [\n -66.961669921875,\n 44.96479793033101\n ],\n [\n -69.093017578125,\n 44.42593442145313\n ],\n [\n -70.77392578125,\n 43.42898792344155\n ],\n [\n -70.72998046875,\n 43.100982876188546\n ],\n [\n -70.57617187499999,\n 42.69858589169842\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"115","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Flye, Melissa. E.","contributorId":275664,"corporation":false,"usgs":false,"family":"Flye","given":"Melissa.","email":"","middleInitial":"E.","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":834202,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sponarski, Carly. C","contributorId":275665,"corporation":false,"usgs":false,"family":"Sponarski","given":"Carly.","email":"","middleInitial":"C","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":834203,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zydlewski, Joseph D. 0000-0002-2255-2303 jzydlewski@usgs.gov","orcid":"https://orcid.org/0000-0002-2255-2303","contributorId":2004,"corporation":false,"usgs":true,"family":"Zydlewski","given":"Joseph","email":"jzydlewski@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":834201,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McGreavy, Bridie","contributorId":275231,"corporation":false,"usgs":false,"family":"McGreavy","given":"Bridie","email":"","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":834204,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70217747,"text":"70217747 - 2021 - Transport and speciation of uranium in groundwater-surface water systems impacted by legacy milling operations","interactions":[],"lastModifiedDate":"2021-02-01T14:29:48.935866","indexId":"70217747","displayToPublicDate":"2020-11-02T06:35:59","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Transport and speciation of uranium in groundwater-surface water systems impacted by legacy milling operations","docAbstract":"Growing worldwide concern over uranium contamination of groundwater resources has placed an emphasis on understanding uranium transport dynamics and potential toxicity in groundwater-surface water systems. In this study, we utilized novel in-situ sampling methods to establish the location and magnitude of contaminated groundwater entry into a receiving surface water environment, and to investigate the speciation and potential bioavailability of uranium in groundwater and surface water. Streambed temperature mapping successfully identified the location of groundwater entry to the Little Wind River, downgradient from the former Riverton uranium mill site, Wyoming, USA. Diffusive equilibrium in thin-film (DET) samplers further constrained the groundwater plume and established sediment pore water solute concentrations and patterns. In this system, evidence is presented for attenuation of uranium-rich groundwater in the shallow sediments where surface water and groundwater interaction occurs. Surface water grab and DET sampling successfully detected an increase in river uranium concentrations where the groundwater plume enters the Little Wind River; however, concentrations remained below environmental guideline levels. Uranium speciation was investigated using diffusive gradients in thin-film (DGT) samplers and geochemical speciation modelling. Together, these investigations indicate uranium may have limited bioavailability to organisms in the Little Wind River and, possibly, in other similar sites in the western U.S.A. This could be due to ion competition effects or the presence of non- or partially labile uranium complexes. Development of methods to establish the location of contaminated (uranium) groundwater entry to surface water environments, and the potential effects on ecosystems, is crucial to develop both site-specific and general conceptual models of uranium behavior and potential toxicity in affected ground and surface water environments.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2020.143314","usgsCitation":"Byrne, P.A., Fuller, C.C., Naftz, D.L., Runkel, R.L., Lehto, N.J., and Dam, W., 2021, Transport and speciation of uranium in groundwater-surface water systems impacted by legacy milling operations: Science of the Total Environment, v. 761, 143314, 11 p., https://doi.org/10.1016/j.scitotenv.2020.143314.","productDescription":"143314, 11 p.","ipdsId":"IP-121496","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":454315,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.osti.gov/biblio/1776309","text":"Publisher Index Page"},{"id":382831,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","city":"Riverton","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.39832305908203,\n 43.00816202648563\n ],\n [\n -108.33995819091797,\n 43.00816202648563\n ],\n [\n -108.33995819091797,\n 43.03175685183966\n ],\n [\n -108.39832305908203,\n 43.03175685183966\n ],\n [\n -108.39832305908203,\n 43.00816202648563\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"761","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Byrne, Patrick A.","contributorId":247578,"corporation":false,"usgs":false,"family":"Byrne","given":"Patrick","email":"","middleInitial":"A.","affiliations":[{"id":49583,"text":"Liverpool John Moores University","active":true,"usgs":false}],"preferred":false,"id":809453,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fuller, Christopher C. 0000-0002-2354-8074 ccfuller@usgs.gov","orcid":"https://orcid.org/0000-0002-2354-8074","contributorId":1831,"corporation":false,"usgs":true,"family":"Fuller","given":"Christopher","email":"ccfuller@usgs.gov","middleInitial":"C.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - 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2021 - Thinking like a consumer: Linking aquatic basal metabolism and consumer dynamics","interactions":[],"lastModifiedDate":"2021-02-03T23:53:16.73024","indexId":"70216402","displayToPublicDate":"2020-10-31T08:26:40","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5456,"text":"Limnology and Oceanography Letters","active":true,"publicationSubtype":{"id":10}},"title":"Thinking like a consumer: Linking aquatic basal metabolism and consumer dynamics","docAbstract":"The increasing availability of high‐frequency freshwater ecosystem metabolism data provides an opportunity to identify links between metabolic regimes, as gross primary production and ecosystem respiration patterns, and consumer energetics with the potential to improve our current understanding of consumer dynamics (e.g., population dynamics, community structure, trophic interactions). We describe a conceptual framework linking metabolic regimes of flowing waters with consumer community dynamics. We use this framework to identify three emerging research needs: (1) quantifying the linkage of metabolism and consumer production data via food web theory and carbon use efficiencies, (2) evaluating the roles of metabolic dynamics and other environmental regimes (e.g., hydrology, light) in consumer dynamics, and (3) determining the degree to which metabolic regimes influence the evolution of consumer traits and phenology. Addressing these needs will improve the understanding of consumer biomass and production patterns as metabolic regimes can be viewed as an emergent property of food webs.
Global biodiversity is in unprecedented decline and on-the-ground solutions are imperative for conservation. Although there is a large volume of evidence related to climate change effects on wildlife, research on climate adaptation strategies is lagging. To assess the current state of knowledge in climate adaptation, we conducted a comprehensive literature review and evaluated 1,346 peer-reviewed publications for management recommendations designed to address the consequences of climate change on wildlife populations. From 509 publications, we identified 2,306 recommendations and employed both qualitative and quantitative methods for data analysis. Although we found an increase in the volume and diversity of recommendations since 2007, a focus on protected areas (26%, 596 of 2,306 recommendations) and the non-reserve matrix (12%, 276 of 2,306 recommendations) remained prominent in the climate adaptation literature. Common concepts include protected areas, invasive species, ecosystem services, adaptive management, stepping stones, assisted migration, and conservation easements. In contrast, only 1% of recommendations focused on reproduction (n = 26), survival (n = 14), disease (n = 26), or human-wildlife conflict (n = 24). Few recommendations reflected the potential for local-scale management interventions. We demonstrate limited advancement in preparing natural resource managers in climate adaptation at local, management-relevant scales. Additional research is needed to identify and evaluate climate adaptation strategies aimed at reducing the vulnerability of wildlife to contemporary climate change. © 2020 The Wildlife Society.
Near-surface soil conditions can significantly alter the amplitude and frequency content of incoming ground motions – often with profound consequences for the built environment – and are thus important inputs to any ground-motion prediction. Previous soil-velocity models (SVM) have predicted shear-wave velocity profiles based on the time-averaged shear-wave velocity in the upper 30 m (VS30). This article presents a generic soil-velocity model that accounts both for near-surface conditions (VS30) and deeper geologic structure, as represented to the depth at which the profile reaches a velocity of 1.0 km/s (Z1.0). To demonstrate the advantages of our new SVM, we apply it to the Cascadia Region of North America, where numerous geologic basins and glaciated landscapes give rise to a wide range of VS30 and Z1.0 combinations. This soil velocity model yields good estimates of site response across all site conditions, and significantly improves upon a model calibrated using only VS30 data. In conjunction with existing models that describe the deep velocity structure of the region (e.g., (Stephenson et al., 2017) [27]; the proposed model is particularly suited for use in regional-scale predictions of site response, liquefaction, landslides, infrastructure damage, and loss. The proposed methodology is broadly applicable to the development of SVMs elsewhere, and with improved understanding of near-surface and deep velocity structures, can facilitate more accurate ground-motion predictions globally.
International efforts to restore degraded ecosystems will continue to expand over the coming decades, yet the factors contributing to the effectiveness of long‐term restoration across large areas remain largely unexplored. At large scales, outcomes are more complex and synergistic than the additive impacts of individual restoration projects. Here, we propose a cumulative‐effects conceptual framework to inform restoration design and implementation and to comprehensively measure ecological outcomes. To evaluate and illustrate this approach, we reviewed long‐term restoration in several large coastal and riverine areas across the US: the greater Florida Everglades; Gulf of Mexico coast; lower Columbia River and estuary; Puget Sound; San Francisco Bay and Sacramento–San Joaquin Delta; Missouri River; and northeastern coastal states. Evidence supported eight modes of cumulative effects of interacting restoration projects, which improved outcomes for species and ecosystems at landscape and regional scales. We conclude that cumulative effects, usually measured for ecosystem degradation, are also measurable for ecosystem restoration. The consideration of evidence‐based cumulative effects will help managers of large‐scale restoration capitalize on positive feedback and reduce countervailing effects.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/fee.2274","usgsCitation":"Diefenderfer, H.L., Steyer, G., Harwell, M.C., LoSchiavo, A.J., Neckles, H.A., Burdick, D.M., Johnson, G.E., Buenau, K.E., Trujillo, E., Callaway, J.C., Thom, R.M., Ganju, N., and Twilley, R.R., 2021, Applying cumulative effects to strategically advance large‐scale ecosystem restoration: Frontiers in Ecology and the Environment, v. 19, no. 2, p. 108-117, https://doi.org/10.1002/fee.2274.","productDescription":"10 p.","startPage":"108","endPage":"117","ipdsId":"IP-107430","costCenters":[{"id":5064,"text":"Southeast Regional Director's Office","active":true,"usgs":true}],"links":[{"id":454325,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/fee.2274","text":"Publisher Index Page"},{"id":385579,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Gulf of Mexico, San Francisco Bay/Sacramento Delta, Puget Sound, Gulf of Maine, Virginia Coastal Bays, Lower Columbia River and Estuary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.66796875,\n 25.562265014427492\n ],\n [\n -82.44140625,\n 25.562265014427492\n ],\n [\n -82.44140625,\n 30.372875188118016\n ],\n [\n -99.66796875,\n 30.372875188118016\n ],\n [\n -99.66796875,\n 25.562265014427492\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -67.1484375,\n 45.398449976304086\n ],\n [\n -70.400390625,\n 44.33956524809713\n ],\n [\n -74.35546875,\n 40.78054143186033\n ],\n [\n -77.16796875,\n 38.95940879245423\n ],\n [\n -76.728515625,\n 36.80928470205937\n ],\n [\n -74.1796875,\n 36.59788913307022\n ],\n [\n 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hneckles@usgs.gov","orcid":"https://orcid.org/0000-0002-5662-2314","contributorId":3821,"corporation":false,"usgs":true,"family":"Neckles","given":"Hilary","email":"hneckles@usgs.gov","middleInitial":"A.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":815458,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Burdick, David M.","contributorId":208047,"corporation":false,"usgs":false,"family":"Burdick","given":"David","email":"","middleInitial":"M.","affiliations":[{"id":37687,"text":"Jackson Estuarine Laboratory, Univesity of New Hampshire, Durham, NH","active":true,"usgs":false}],"preferred":false,"id":815459,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Johnson, Gary E.","contributorId":257982,"corporation":false,"usgs":false,"family":"Johnson","given":"Gary","email":"","middleInitial":"E.","affiliations":[{"id":52195,"text":"Pacific Northwest National 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0000-0002-7364-286X","orcid":"https://orcid.org/0000-0002-7364-286X","contributorId":205456,"corporation":false,"usgs":false,"family":"Callaway","given":"John","email":"","middleInitial":"C.","affiliations":[{"id":37110,"text":"Dept. of Environmental Science, University of San Francisco, 2130 Fulton St., San Francisco, CA 94117","active":true,"usgs":false}],"preferred":false,"id":815463,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Thom, Ronald M. 0000-0002-8639-6709","orcid":"https://orcid.org/0000-0002-8639-6709","contributorId":257985,"corporation":false,"usgs":false,"family":"Thom","given":"Ronald","email":"","middleInitial":"M.","affiliations":[{"id":52195,"text":"Pacific Northwest National Lab","active":true,"usgs":false}],"preferred":false,"id":815464,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Ganju, Neil K. 0000-0002-1096-0465","orcid":"https://orcid.org/0000-0002-1096-0465","contributorId":202878,"corporation":false,"usgs":true,"family":"Ganju","given":"Neil K.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":815465,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Twilley, Robert R.","contributorId":34585,"corporation":false,"usgs":false,"family":"Twilley","given":"Robert","email":"","middleInitial":"R.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":815466,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70216772,"text":"70216772 - 2021 - Evaluation of seismic hazard models with fragile geologic features","interactions":[],"lastModifiedDate":"2021-01-19T16:04:47.842953","indexId":"70216772","displayToPublicDate":"2020-10-28T09:20:35","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of seismic hazard models with fragile geologic features","docAbstract":"We provide an overview of a 2019 workshop on the use of fragile geologic features (FGFs) to evaluate seismic hazard models. FGFs have been scarcely utilized in the evaluation of seismic hazard models, despite nearly 30 yr having passed since the first recognition of their potential value. Recently, several studies have begun to focus on the implementation of FGFs in seismic hazard modeling. The workshop was held to capture a “snapshot” of the state‐of‐the‐art in FGF work and to define key research areas that would increase confidence in FGF‐based evaluation of seismic hazard models. It was held at the annual meeting of the Southern California Earthquake Center on 8 September 2019, and the conveners were Mark Stirling (University of Otago, New Zealand) and Michael Oskin (University of California, Davis). The workshop attracted 44 participants from a wide range of disciplines. The main topics of discussion were FGF fragility age estimation (age at which an FGF achieved its current fragile geometry), fragility estimation, FGF‐based evaluation of seismic hazard models, and ethical considerations relating to documentation and preservation of FGFs. There are now many scientists working on, or motivated to work on, FGFs, and more types of FGFs are being worked on than just the precariously balanced rock (PBR) variety. One of the ideas presented at the workshop is that fragility ages for FGFs should be treated stochastically rather than assuming that all share a common age. In a similar vein, new studies propose more comprehensive methods of fragility assessment beyond peak ground acceleration and peak ground velocity‐based approaches. Two recent studies that apply PBRs to evaluate probabilistic seismic hazard models use significantly different methods of evaluation. Key research needs identified from the workshop will guide future, focused efforts that will ultimately facilitate the uptake of FGFs in seismic hazard analysis.
The global climate has been changing over the last century due to greenhouse gas emissions and will continue to change over this century, accelerating without effective global efforts to reduce emissions. Ticks and tick-borne diseases (TTBDs) are inherently climate-sensitive due to the sensitivity of tick lifecycles to climate. Key direct climate and weather sensitivities include survival of individual ticks, and the duration of development and host-seeking activity of ticks. These sensitivities mean that in some regions a warming climate may increase tick survival, shorten life-cycles and lengthen the duration of tick activity seasons. Indirect effects of climate change on host communities may, with changes in tick abundance, facilitate enhanced transmission of tick-borne pathogens. High temperatures, and extreme weather events (heat, cold, and flooding) are anticipated with climate change, and these may reduce tick survival and pathogen transmission in some locations. Studies of the possible effects of climate change on TTBDs to date generally project poleward range expansion of geographical ranges (with possible contraction of ranges away from the increasingly hot tropics), upslope elevational range spread in mountainous regions, and increased abundance of ticks in many current endemic regions. However, relatively few studies, using long-term (multi-decade) observations, provide evidence of recent range changes of tick populations that could be attributed to recent climate change. Further integrated ‘One Health’ observational and modeling studies are needed to detect changes in TTBD occurrence, attribute them to climate change, and to develop predictive models of public- and animal-health needs to plan for TTBD emergence.
","language":"English","publisher":"Entomological Society of America","doi":"10.1093/jme/tjaa220","usgsCitation":"Ogden, N.H., Beard, C.B., Ginsberg, H., and Tsao, J.I., 2021, Possible effects of climate change on ixodid ticks and the pathogens they transmit: Predictions and observations: Journal of Medical Entomology, v. 58, no. 4, p. 1536-1545, https://doi.org/10.1093/jme/tjaa220.","productDescription":"10 p.","startPage":"1536","endPage":"1545","ipdsId":"IP-121581","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":454330,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/jme/tjaa220","text":"Publisher Index Page"},{"id":379905,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"58","issue":"4","noUsgsAuthors":false,"publicationDate":"2020-10-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Ogden, Nicholas H.","contributorId":147667,"corporation":false,"usgs":false,"family":"Ogden","given":"Nicholas","email":"","middleInitial":"H.","affiliations":[{"id":16890,"text":"Public Health Agency of Canada","active":true,"usgs":false}],"preferred":false,"id":803337,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beard, Charles B.","contributorId":148018,"corporation":false,"usgs":false,"family":"Beard","given":"Charles","email":"","middleInitial":"B.","affiliations":[{"id":16974,"text":"US Centers for Disease Control and Prevention (CDC)","active":true,"usgs":false}],"preferred":false,"id":803338,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ginsberg, Howard S. 0000-0002-4933-2466 hginsberg@usgs.gov","orcid":"https://orcid.org/0000-0002-4933-2466","contributorId":147665,"corporation":false,"usgs":true,"family":"Ginsberg","given":"Howard S.","email":"hginsberg@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":803339,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tsao, Jean I.","contributorId":140905,"corporation":false,"usgs":false,"family":"Tsao","given":"Jean","email":"","middleInitial":"I.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":803340,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70216439,"text":"70216439 - 2021 - Estimating the contribution of tributary sand inputs to controlled flood deposits for sandbar restoration using elemental tracers, Colorado River, Grand Canyon National Park, Arizona","interactions":[],"lastModifiedDate":"2021-05-14T11:50:15.092644","indexId":"70216439","displayToPublicDate":"2020-10-28T07:37:56","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1786,"text":"Geological Society of America Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Estimating the contribution of tributary sand inputs to controlled flood deposits for sandbar restoration using elemental tracers, Colorado River, Grand Canyon National Park, Arizona","docAbstract":"Completion of Glen Canyon Dam in 1963 resulted in complete elimination of sediment delivery from the upstream Colorado River basin to Grand Canyon and nearly complete control of spring snowmelt floods responsible for creating channel and bar morphology. Management of the river ecosystem in Grand Canyon National Park now relies on dam-release floods to redistribute tributary-derived sediment accumulated on the channel bed to higher-elevation sandbars. Here, we used multivariate mixing analysis of sediment elemental compositions to evaluate the extent to which flood deposits derive from tributary-supplied sand compared to reworked, relict predam sediment. The concentrations of seven major and trace elements (Fe, Ca, K, Ti, Rb, Sr, and Zr) were measured in very fine−, fine-, and medium-grained sand from flood deposits using X-ray fluorescence and interpreted using a Bayesian mixing model to characterize the proportion of sand originating from the Paria River, the only major tributary within the study reach. Flood deposits from the 2013 and 2014 controlled floods contained 69% ± 16% and 84% ± 20% Paria River−derived material, respectively, with substantial variation among sites. Based on a sand mass balance, we calculated that under decreasing storage conditions since 1963, ∼77%−83% of the annual Paria River sand flux needs to be retained within the mass of active sand stored in Marble Canyon each year to reach the observed concentration of Paria River sand at sample locations. This finding suggests that the use of controlled floods may continue to be effective for sandbar maintenance, provided sand inputs from the Paria River do not decline.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/B35642.1","usgsCitation":"Chapman, K.A., Best, R.J., Smith, M.E., Mueller, E.R., Grams, P.E., and Parnell, R., 2021, Estimating the contribution of tributary sand inputs to controlled flood deposits for sandbar restoration using elemental tracers, Colorado River, Grand Canyon National Park, Arizona: Geological Society of America Bulletin, v. 133, no. 5-6, p. 1141-1156, https://doi.org/10.1130/B35642.1.","productDescription":"16 p.","startPage":"1141","endPage":"1156","ipdsId":"IP-116064","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":436648,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9C0IN56","text":"USGS data release","linkHelpText":"Tributary sand input data, Colorado River, Grand Canyon National Park, Arizona"},{"id":380590,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Grand Canyon National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.027099609375,\n 35.71083783530009\n ],\n [\n -111.258544921875,\n 35.71083783530009\n ],\n [\n -111.258544921875,\n 36.958671131530316\n ],\n [\n -114.027099609375,\n 36.958671131530316\n ],\n [\n -114.027099609375,\n 35.71083783530009\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"133","issue":"5-6","noUsgsAuthors":false,"publicationDate":"2020-10-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Chapman, Katherine A. kchapman@usgs.gov","contributorId":5368,"corporation":false,"usgs":true,"family":"Chapman","given":"Katherine","email":"kchapman@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":805134,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Best, Rebecca J.","contributorId":198804,"corporation":false,"usgs":false,"family":"Best","given":"Rebecca","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":805135,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, M. Elliot","contributorId":255572,"corporation":false,"usgs":false,"family":"Smith","given":"M.","email":"","middleInitial":"Elliot","affiliations":[],"preferred":false,"id":805136,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mueller, Erich R. 0000-0001-8202-154X emueller@usgs.gov","orcid":"https://orcid.org/0000-0001-8202-154X","contributorId":4930,"corporation":false,"usgs":true,"family":"Mueller","given":"Erich","email":"emueller@usgs.gov","middleInitial":"R.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":812614,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Grams, Paul E. 0000-0002-0873-0708 pgrams@usgs.gov","orcid":"https://orcid.org/0000-0002-0873-0708","contributorId":1830,"corporation":false,"usgs":true,"family":"Grams","given":"Paul","email":"pgrams@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":812615,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Parnell, Roderic A.","contributorId":41922,"corporation":false,"usgs":true,"family":"Parnell","given":"Roderic A.","affiliations":[],"preferred":false,"id":812616,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70216003,"text":"70216003 - 2021 - Carrying capacity of spatially distributed metapopulations","interactions":[],"lastModifiedDate":"2021-01-19T16:35:18.526261","indexId":"70216003","displayToPublicDate":"2020-10-28T07:32:27","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3653,"text":"Trends in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Carrying capacity of spatially distributed metapopulations","docAbstract":"Carrying capacity is a key concept in ecology. A body of theory, based on the logistic equation, has extended predictions of carrying capacity to spatially distributed, dispersing populations. However, this theory has only recently been tested empirically. The experimental results disagree with some theoretical predictions of when they are extended to a population dispersing randomly in a two-patch system. However, they are consistent with a mechanistic model of consumption on an exploitable resource (consumer–resource model). We argue that carrying capacity, defined as the total equilibrium population, is not a fundamental property of ecological systems, at least in the context of spatial heterogeneity. Instead, it is an emergent property that depends on the population’s intrinsic growth and dispersal rates.
Holocene crustal faulting in the northern Olympic Peninsula of Washington State manifests in a zone of west‐northwest‐striking crustal faults herein named the North Olympic fault zone, which extends for
Spatial and temporal patterns in low streamflows were investigated for 183 streamgages located in the Chesapeake Bay Watershed for the period 1939–2013. Metrics that represent different aspects of the frequency and magnitude of low streamflows were examined for trends: (1) the annual time series of seven‐day average minimum streamflow, (2) the scaled average deficit at or below the 2% mean daily streamflow value relative to a base period between 1939 and 1970, and (3) the annual number of days below the 2% threshold. Trends in these statistics showed spatial cohesion, with increasing low streamflow volume at streamgages located in the northern uplands of the Chesapeake Bay Watershed and decreasing low streamflow volume at streamgages in the southern part of the watershed. For a small subset of streamgages (12%), conflicting trend patterns were observed between the seven‐day average minimum streamflow and the below‐threshold time series and these appear to be related to upstream diversions or the influence of reservoir‐influenced streamflows in their contributing watersheds. Using multivariate classification techniques, mean annual precipitation and fraction of precipitation falling as snow appear to be broad controls of increasing and decreasing low‐flow trends. Further investigation of seasonal precipitation patterns shows summer rainfall patterns, driven by the Atlantic Multidecadal Oscillation, as the main driver of low streamflows in the Chesapeake Bay Watershed.
","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12892","usgsCitation":"Fleming, B.J., Archfield, S.A., Hirsch, R.M., Kiang, J.E., and Wolock, D.M., 2021, Spatial and temporal patterns of low streamflow and precipitation changes in the Chesapeake Bay Watershed: Journal of the American Water Resources Association, v. 57, no. 1, p. 96-108, https://doi.org/10.1111/1752-1688.12892.","productDescription":"13 p.","startPage":"96","endPage":"108","ipdsId":"IP-108281","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":454337,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1752-1688.12892","text":"Publisher Index Page"},{"id":436650,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9J8Y8OE","text":"USGS data release","linkHelpText":"Low-streamflow and precipitation trends for 183 U.S. Geological Survey 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jkiang@usgs.gov","orcid":"https://orcid.org/0000-0003-0653-4225","contributorId":2179,"corporation":false,"usgs":true,"family":"Kiang","given":"Julie","email":"jkiang@usgs.gov","middleInitial":"E.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":809462,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wolock, David M. 0000-0002-6209-938X","orcid":"https://orcid.org/0000-0002-6209-938X","contributorId":219213,"corporation":false,"usgs":true,"family":"Wolock","given":"David","email":"","middleInitial":"M.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":809463,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70228427,"text":"70228427 - 2021 - Habitat modelling locates nesting areas of the endangered Black-capped Petrel Pterodroma hasitata on Hispaniola and identifies habitat loss","interactions":[],"lastModifiedDate":"2022-02-10T15:43:03.162133","indexId":"70228427","displayToPublicDate":"2020-10-26T09:37:21","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1048,"text":"Bird Conservation International","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Habitat modelling locates nesting areas of the endangered Black-capped Petrel Pterodroma hasitata on Hispaniola and identifies habitat loss","title":"Habitat modelling locates nesting areas of the endangered Black-capped Petrel Pterodroma hasitata on Hispaniola and identifies habitat loss","docAbstract":"The Black-capped Petrel or Diablotin Pterodroma hasitata has a fragmented and declining population estimated at c.1,000 breeding pairs. On land, the species nests underground in steep ravines with dense understorey vegetation. The only confirmed breeding sites are located in the mountain ranges of Hispaniola in the Caribbean, where habitat loss and degradation are continuing threats. Other nesting populations may still remain undiscovered but, to locate them, laborious in situ nest searches must be conducted over expansive geographical areas. To focus nest-search efforts more efficiently, we analysed the environmental characteristics of Black-capped Petrel nesting habitat and modeled suitable habitat on Hispaniola using openly available environmental datasets. We used a univariate generalized linear model to compare the habitat characteristics of active Black-capped Petrel nests sites with those of potentially available sites (i.e. random pseudo-absences). Elevation, distance to coast, and the influence of tree cover and density emerged as important environmental variables. We then applied multivariate generalized linear models to these environmental variables that showed a significant relationship with petrel nesting activity. We used the top performing model of habitat suitability model to create maps of predicted suitability for Hispaniola. In addition to areas of known petrel activity, the model identified possible nesting areas for Black-capped Petrels in habitats not previously considered suitable. Based on model results, we estimated the total area of predicted suitable nesting habitat for Black-capped Petrels on Hispaniola and found that forest loss due to hurricanes, forest fires, and encroachment from agriculture had severely decreased availability of predicted suitable habitat between 2000 and 2018.
","language":"English","publisher":"Cambridge University Press","doi":"10.1017/S0959270920000490","usgsCitation":"Satge, Y.G., Rupp, E., Brown, A.J., and Jodice, P.G., 2021, Habitat modelling locates nesting areas of the endangered Black-capped Petrel Pterodroma hasitata on Hispaniola and identifies habitat loss: Bird Conservation International, v. 31, no. 4, p. 573-590, https://doi.org/10.1017/S0959270920000490.","productDescription":"18 p.","startPage":"573","endPage":"590","ipdsId":"IP-115786","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":454339,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1017/s0959270920000490","text":"Publisher Index Page"},{"id":436651,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FWJPBD","text":"USGS data release","linkHelpText":"Nesting habitat suitability for the Black-capped Petrel Pterodroma hasitata on Hispaniola, Supplementary Material"},{"id":395771,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Dominican Republic, Haiti","otherGeospatial":"Hispaniola","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -68.09326171875,\n 18.823116948090494\n ],\n [\n -69.2138671875,\n 19.621892180319374\n ],\n [\n -71.136474609375,\n 20.159098270646936\n ],\n [\n -72.916259765625,\n 20.24158281954221\n ],\n [\n -73.71826171874999,\n 19.766703551716976\n ],\n [\n -74.92675781249999,\n 18.396230138028827\n ],\n [\n -73.201904296875,\n 17.602139123350838\n ],\n [\n -71.47705078125,\n 17.45547257997284\n ],\n [\n -68.79638671875,\n 17.90556881196468\n ],\n [\n -68.21411132812499,\n 18.3336694457713\n ],\n [\n -68.09326171875,\n 18.823116948090494\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"31","issue":"4","noUsgsAuthors":false,"publicationDate":"2020-10-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Satge, Y. G.","contributorId":275774,"corporation":false,"usgs":false,"family":"Satge","given":"Y.","email":"","middleInitial":"G.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":834273,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rupp, E.","contributorId":265431,"corporation":false,"usgs":false,"family":"Rupp","given":"E.","email":"","affiliations":[],"preferred":false,"id":834274,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brown, A. J.","contributorId":197185,"corporation":false,"usgs":false,"family":"Brown","given":"A.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":834275,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jodice, Patrick G.R. 0000-0001-8716-120X","orcid":"https://orcid.org/0000-0001-8716-120X","contributorId":219852,"corporation":false,"usgs":true,"family":"Jodice","given":"Patrick","middleInitial":"G.R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":834276,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}