An opportunistic investigation into ecosystem instability in Kachemak Bay (KBay), Alaska, has led us to investigate exposure to toxic algae in sea otters. We used gene expression to explore the physiological health of sea otters sampled in KBay in May 2019. We found altered levels of gene transcripts in comparison with reference sea otters from clinically normal, oil-exposed, and nutritionally challenged populations sampled over the past decade. KBay sea otters were markedly divergent from the other groups for five genes, which indicated the involvement of neurological, cardiac, immune, and detoxification systems. Further, analyses of urine and fecal samples detected domoic acid in the KBay sea otters. In combination, these results may point to chronic, low-level exposure to an algal toxin, such as domoic acid. With a warming climate, the frequency and severity of harmful algal blooms in marine environments is anticipated to increase, and novel molecular technologies to detect sublethal or chronic exposure to algal toxins will help provide an early warning of threats to the stability of populations and ecosystems.
","language":"English","publisher":"MDPI","doi":"10.3390/oceans3030027","usgsCitation":"Bowen, L., Knowles, S., Lefebvre, K., St Martin, M., Murray, M., Kloecker, K.A., Monson, D., Weitzman, B., Ballachey, B., Coletti, H., Waters-Dynes, S.C., and Cummings, C., 2022, Divergent gene expression profiles in Alaskan sea otters: An indicator of chronic domoic acid exposure?: Oceans, v. 3, no. 3, p. 401-418, https://doi.org/10.3390/oceans3030027.","productDescription":"18 p.","startPage":"401","endPage":"418","ipdsId":"IP-143428","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":446860,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/oceans3030027","text":"Publisher Index 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Ben","contributorId":252838,"corporation":false,"usgs":false,"family":"Weitzman","given":"Ben","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":854008,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ballachey, Brenda 0000-0003-1855-9171","orcid":"https://orcid.org/0000-0003-1855-9171","contributorId":264735,"corporation":false,"usgs":false,"family":"Ballachey","given":"Brenda","affiliations":[{"id":24583,"text":"former USGS employee","active":true,"usgs":false}],"preferred":false,"id":854009,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Coletti, Heather","contributorId":258849,"corporation":false,"usgs":false,"family":"Coletti","given":"Heather","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":854010,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Waters-Dynes, Shannon C. 0000-0002-9707-4684 swaters@usgs.gov","orcid":"https://orcid.org/0000-0002-9707-4684","contributorId":5826,"corporation":false,"usgs":true,"family":"Waters-Dynes","given":"Shannon","email":"swaters@usgs.gov","middleInitial":"C.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":854011,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Cummings, C","contributorId":297392,"corporation":false,"usgs":false,"family":"Cummings","given":"C","email":"","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":854012,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70238480,"text":"70238480 - 2022 - Reference genome of the California glossy snake, Arizona elegans occidentalis: A declining California Species of Special Concern","interactions":[],"lastModifiedDate":"2022-12-01T16:23:17.773293","indexId":"70238480","displayToPublicDate":"2022-08-08T07:24:51","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2333,"text":"Journal of Heredity","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Reference genome of the California glossy snake, Arizona elegans occidentalis: A declining California Species of Special Concern","title":"Reference genome of the California glossy snake, Arizona elegans occidentalis: A declining California Species of Special Concern","docAbstract":"The glossy snake (Arizona elegans) is a polytypic species broadly distributed across southwestern North America. The species occupies habitats ranging from California’s coastal chaparral to the shortgrass prairies of Texas and southeastern Nebraska, to the extensive arid scrublands of central México. Three subspecies are currently recognized in California, one of which is afforded state-level protection based on the extensive loss and modification of its preferred alluvial coastal scrub and inland desert habitat. We report the first genome assembly of A. elegans occidentalis as part of the California Conservation Genomics Project (CCGP). Consistent with the reference genome strategy of the CCGP, we used Pacific Biosciences HiFi long reads and Hi-C chromatin-proximity sequencing technologies to produce a de novo assembled genome. The assembly comprises a total of 140 scaffolds spanning 1,842,602,218 base pairs, has a contig NG50 of 61 Mb, a scaffold NG50 of 136 Mb, and a BUSCO complete score of 95.9%, and is one of the most complete snake genome assemblies. The A. e. occidentalis genome will be a key tool for understanding the genomic diversity and the basis of adaptations within this species and close relatives within the hyperdiverse snake family Colubridae.
","language":"English","publisher":"Oxford University Press","doi":"10.1093/jhered/esac040","usgsCitation":"Wood, D.A., Richmond, J.Q., Escalona, M., Marimuthu, M.P., Nguyen, O., Sacco, S., Beraut, E., Westphal, M.F., Fisher, R., Vandergast, A.G., Toffelmier, E., Wang, I., and Shaffer, H., 2022, Reference genome of the California glossy snake, Arizona elegans occidentalis: A declining California Species of Special Concern: Journal of Heredity, v. 113, no. 6, p. 632-640, https://doi.org/10.1093/jhered/esac040.","productDescription":"9 p.","startPage":"632","endPage":"640","ipdsId":"IP-143455","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":446864,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9923794","text":"External Repository"},{"id":409680,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.11935248282103,\n 32.53882373045977\n ],\n [\n -114.50243196034603,\n 32.72786950214554\n ],\n [\n -114.64233250350489,\n 33.1520790618809\n ],\n [\n -114.58470276618635,\n 33.51373515511381\n ],\n [\n -114.41452412993016,\n 34.10031267745222\n ],\n [\n -114.11907829718999,\n 34.32357161601179\n ],\n [\n -114.67741209652053,\n 35.09778131876418\n ],\n [\n -117.76088232794436,\n 37.33676457017539\n ],\n [\n -119.42981485345024,\n 35.62249205151011\n ],\n [\n -121.63638617466606,\n 38.725574279970715\n ],\n [\n -122.54328366670836,\n 38.42830074064648\n ],\n [\n -119.57711374079892,\n 34.87314120906966\n ],\n [\n -118.19555417338168,\n 34.27246184404002\n ],\n [\n -117.90704702548453,\n 33.82510987924552\n ],\n [\n -117.26765483662936,\n 32.80899171054767\n ],\n [\n -116.97534971889436,\n 32.510621812966775\n ],\n [\n -117.11935248282103,\n 32.53882373045977\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"113","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-08-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Wood, Dustin A. 0000-0002-7668-9911 dawood@usgs.gov","orcid":"https://orcid.org/0000-0002-7668-9911","contributorId":4179,"corporation":false,"usgs":true,"family":"Wood","given":"Dustin","email":"dawood@usgs.gov","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":857588,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Richmond, Jonathan Q. 0000-0001-9398-4894 jrichmond@usgs.gov","orcid":"https://orcid.org/0000-0001-9398-4894","contributorId":5400,"corporation":false,"usgs":true,"family":"Richmond","given":"Jonathan","email":"jrichmond@usgs.gov","middleInitial":"Q.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":857589,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Escalona, Merly","contributorId":299346,"corporation":false,"usgs":false,"family":"Escalona","given":"Merly","email":"","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":857590,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Marimuthu, Mohan P. 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A.","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":857591,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nguyen, Oanh","contributorId":299348,"corporation":false,"usgs":false,"family":"Nguyen","given":"Oanh","email":"","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":857592,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sacco, Samuel","contributorId":299349,"corporation":false,"usgs":false,"family":"Sacco","given":"Samuel","email":"","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":857593,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Beraut, Eric","contributorId":299352,"corporation":false,"usgs":false,"family":"Beraut","given":"Eric","email":"","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":857594,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Westphal, Michael F.","contributorId":192139,"corporation":false,"usgs":false,"family":"Westphal","given":"Michael","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":857595,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Fisher, Robert N. 0000-0002-2956-3240","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":51675,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":857596,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Vandergast, Amy G. 0000-0002-7835-6571","orcid":"https://orcid.org/0000-0002-7835-6571","contributorId":57201,"corporation":false,"usgs":true,"family":"Vandergast","given":"Amy","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":857597,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Toffelmier, Erin","contributorId":299356,"corporation":false,"usgs":false,"family":"Toffelmier","given":"Erin","email":"","affiliations":[{"id":12763,"text":"University of California, Los Angeles","active":true,"usgs":false}],"preferred":false,"id":857598,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Wang, Ian J","contributorId":299360,"corporation":false,"usgs":false,"family":"Wang","given":"Ian J","affiliations":[{"id":36942,"text":"University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":857599,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Shaffer, H. Bradley","contributorId":247762,"corporation":false,"usgs":false,"family":"Shaffer","given":"H. Bradley","affiliations":[{"id":12763,"text":"University of California, Los Angeles","active":true,"usgs":false}],"preferred":false,"id":857600,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70239138,"text":"70239138 - 2022 - RNA-seq reveals potential gene biomarkers in fathead minnows (Pimephales promelas) for exposure to treated wastewater effluent","interactions":[],"lastModifiedDate":"2022-12-29T13:16:42.17673","indexId":"70239138","displayToPublicDate":"2022-08-08T07:09:12","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9161,"text":"Environmental Science: Processes & Impacts","active":true,"publicationSubtype":{"id":10}},"displayTitle":"RNA-seq reveals potential gene biomarkers in fathead minnows (Pimephales promelas) for exposure to treated wastewater effluent","title":"RNA-seq reveals potential gene biomarkers in fathead minnows (Pimephales promelas) for exposure to treated wastewater effluent","docAbstract":"Discharged wastewater treatment plant (WWTP) effluent greatly contributes to the generation of complex mixtures of contaminants of emerging concern (CECs) in aquatic environments which often contain neuropharmaceuticals and other emerging contaminants that may impact neurological function. However, there is a paucity of knowledge on the neurological impacts of these exposures to aquatic organisms. In this study, caged fathead minnows (Pimephales promelas) were exposed in situ in a temperate-region effluent-dominated stream (i.e., Muddy Creek) in Coralville, Iowa, USA upstream and downstream of a WWTP effluent outfall. The pharmaceutical composition of Muddy Creek was recently characterized by our team and revealed many compounds there were at a low microgram to high nanogram per liter concentration. Total RNA sequencing analysis on brain tissues revealed 280 gene isoforms that were significantly differentially expressed in male fish and 293 gene isoforms in female fish between the upstream and downstream site. Only 66 (13%) of such gene isoforms overlapped amongst male and female fish, demonstrating sex-dependent impacts on neuronal gene expression. By using a systems biology approach paired with functional enrichment analyses, we identified several potential novel gene biomarkers for treated effluent exposure that could be used to expand monitoring of environmental effects with respect to complex CEC mixtures. Lastly, when comparing the results of this study to those that relied on a single-compound approach, there was relatively little overlap in terms of gene-specific effects. This discovery brings into question the application of single-compound exposures in accurately characterizing environmental risks of complex mixtures and for gene biomarker identification.
Coastal marsh within Mediterranean climate zones is exposed to episodic watershed runoff and sediment loads that occur during storm events. Simulating future marsh accretion under sea level rise calls for attention to: (a) physical processes acting over the time scale of storm events and (b) biophysical processes acting over time scales longer than storm events. Using the upper Newport Bay in Southern California as a case study, we examine the influence of event-scale processes on simulated change in marsh topography by comparing: (a) a biophysical model that integrates with an annual time step and neglects event-scale processes (BP-Annual), (b) a physical model that resolves event-scale processes but neglects biophysical interactions (P-Event), and (c) a biophysical model that resolves event-scale physical processes and biophysical processes at annual and longer time scales (BP-Event). A calibrated BP-Event model shows that large (>20-year return period) episodic storm events are major drivers of marsh accretion, depositing up to 30 cm of sediment in one event. Greater deposition is predicted near fluvial sources and tidal channels and less on marshes further from fluvial sources and tidal channels. In contrast, the BP-Annual model poorly resolves spatial structure in marsh accretion as a consequence of neglecting event-scale processes. Furthermore, the P-Event model significantly overestimates marsh accretion as a consequence of neglecting marsh surface compaction driven by annual scale biophysical processes. Differences between BP-Event and BP-Annual models translate up to 20 cm per century in marsh surface elevation.
On the evening of 15 January 2022, the Hunga Tonga-Hunga Ha’apai volcano1 unleashed a violent underwater eruption, blanketing the surrounding land masses in ash and debris. The eruption generated tsunamis observed around the world. An event of this type last occurred in 1883 during the eruption of Krakatau, and thus we have the first observations of a tsunami from a large emergent volcanic eruption captured with modern instrumentation. Here we show that the explosive eruption generated waves through multiple mechanisms, including: (1) air–sea coupling with the initial and powerful shock wave radiating out from the explosion in the immediate vicinity of the eruption; (2) collapse of the water cavity created by the underwater explosion; and (3) air–sea coupling with the air-pressure pulse that circled the Earth several times, leading to a global tsunami. In the near field, tsunami impacts are strongly controlled by the water-cavity source whereas the far-field tsunami, which was unusually persistent, can be largely described by the air-pressure pulse mechanism. Catastrophic damage in some harbours in the far field was averted by just tens of centimetres, implying that a modest sea level rise combined with a future, similar event would lead to a step-function increase in impacts on infrastructure. Piecing together the complexity of this event has broad implications for coastal hazards in similar geophysical settings, suggesting a currently neglected source of global tsunamis.
Livestock predation can pose socio-economic impacts on rural livelihoods and is the main cause of retaliatory killings of carnivores in many countries. Therefore, appropriate interventions to reduce livestock predation, lower conflict and promote coexistence are needed. Livestock guarding dogs have been traditionally used to reduce predation, yet details regarding the use of dogs, especially the number of dogs per herd effectively required, are rarely studied. In this study, we assessed how the number and presence of guarding dogs in a herd can reduce livestock losses to leopard and wolf in corrals at night and on grazing grounds in day-time. Using systematic interview surveys (2016-2019), we documented sheep/goat losses per attack (predation rates) from 139 shepherds across 32 villages around Golestan National Park, Iran. We analysed the effects of the number of dogs, presence of dogs, presence of shepherds, seasons, corral quality, livestock number, dog size, distance to villages and distance to reserve on predation rates using generalized linear models. For the leopard model, dog presence significantly decreased (β = –1.80, 95% confidence interval –2.61 to –0.81) predation rates during day-time to 1.41 individuals per attack. For wolf attacks in corrals at night, predation rates significantly decreased (β = –0.29, –0.54 to –0.04) with increasing dog numbers. Also, shepherd presence (β = –0.56, –1.10 to –0.10) and herd size (β = –0.36, –0.60 to –0.12) significantly reduced predation rates. In the wolf day-time model, shepherd presence significantly decreased (β = –0.93, –1.74 to –0.10) predation rates. Our study suggests that (1) using dogs can reduce, but not eliminate, predation by leopards during day-time; (2) with every additional dog, predation rates by wolves in corrals at night are likely to decrease on average by 25.2%; and (3) the presence of shepherds in corrals at night and during day-time can reduce predation rates.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.baae.2022.08.001","usgsCitation":"Soofi, M., Soufi, M., Royle, A., Waltert, M., and Khorozyan, I., 2022, Numbers and presence of guarding dogs affect wolf and leopard predation on livestock in northeastern Iran: Basic and Applied Ecology, v. 64, p. 147-156, https://doi.org/10.1016/j.baae.2022.08.001.","productDescription":"10 p.","startPage":"147","endPage":"156","ipdsId":"IP-136891","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":446872,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.baae.2022.08.001","text":"Publisher Index Page"},{"id":408278,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Iran","otherGeospatial":"Azizabad No-Hunting Area, Golestan National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 55.52490234375,\n 37.18876668723709\n ],\n [\n 56.34063720703125,\n 37.18876668723709\n ],\n [\n 56.34063720703125,\n 37.694687703235914\n ],\n [\n 55.52490234375,\n 37.694687703235914\n ],\n [\n 55.52490234375,\n 37.18876668723709\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"64","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Soofi, Mahmood","contributorId":297883,"corporation":false,"usgs":false,"family":"Soofi","given":"Mahmood","email":"","affiliations":[{"id":64430,"text":"Department of Conservation Biology, University of Goettingen,","active":true,"usgs":false}],"preferred":false,"id":854546,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Soufi, Mobin","contributorId":297884,"corporation":false,"usgs":false,"family":"Soufi","given":"Mobin","email":"","affiliations":[{"id":64431,"text":"Department of the Environment, Faculty of Fishery and Environment, Gorgan University of Agriculture and Natural Resources, Gorgan, Iran","active":true,"usgs":false}],"preferred":false,"id":854547,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":854548,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Waltert, Matthias","contributorId":297885,"corporation":false,"usgs":false,"family":"Waltert","given":"Matthias","email":"","affiliations":[{"id":62110,"text":"Department of Conservation Biology, University of Goettingen","active":true,"usgs":false}],"preferred":false,"id":854549,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Khorozyan, Igor","contributorId":297886,"corporation":false,"usgs":false,"family":"Khorozyan","given":"Igor","email":"","affiliations":[{"id":62110,"text":"Department of Conservation Biology, University of Goettingen","active":true,"usgs":false}],"preferred":false,"id":854550,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70243220,"text":"70243220 - 2022 - New projections of 21st century climate and hydrology for Alaska and Hawaiʻi","interactions":[],"lastModifiedDate":"2023-05-04T11:52:28.55815","indexId":"70243220","displayToPublicDate":"2022-08-07T06:50:07","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5567,"text":"Climate Services","active":true,"publicationSubtype":{"id":10}},"title":"New projections of 21st century climate and hydrology for Alaska and Hawaiʻi","docAbstract":"In the United States, high-resolution, century-long, hydroclimate projection datasets have been developed for water resources planning, focusing on the contiguous United States (CONUS) domain. However, there are few statewide hydroclimate projection datasets available for Alaska and Hawaiʻi. The limited information on hydroclimatic change motivates developing hydrologic scenarios from 1950 to 2099 using climate-hydrology impact modeling chains consisting of multiple statistically downscaled climate projections as input to hydrologic model simulations for both states. We adopt an approach similar to the previous CONUS hydrologic assessments where: 1) we select the outputs from ten global climate models (GCM) from the Coupled Model Intercomparison Project Phase 5 with Representative Concentration Pathways 4.5 and 8.5; 2) we perform statistical downscaling to generate climate input data for hydrologic models (12-km grid-spacing for Alaska and 1-km for Hawaiʻi); and 3) we perform process-based hydrologic model simulations. For Alaska, we have advanced the hydrologic model configuration from CONUS by using the full water-energy balance computation, frozen soils and a simple glacier model. The simulations show that robust warming and increases in precipitation produce runoff increases for most of Alaska, with runoff reductions in the currently glacierized areas in Southeast Alaska. For Hawaiʻi, we produce the projections at high resolution (1 km) which highlight high spatial variability of climate variables across the state, and a large spread of runoff across the GCMs is driven by a large precipitation spread across the GCMs. Our new ensemble datasets assist with state-wide climate adaptation and other water planning.
Root hemiparasitic plants both compete with and extract resources from host plants. By reducing the abundance of dominant plants and releasing subordinates from competitive exclusion, they can have an outsized impact on plant communities. Most research on the ecological role of hemiparasites is manipulative and focuses on a small number of hemiparasitic taxa. Here, we ask whether patterns in natural plant communities match the expectation that hemiparasites affect the structure of plant communities. Our data were collected on 129 national park units spanning the continental United States. The most common hemiparasite genera were Pedicularis, Castilleja, Krameria, and Comandra. We used null models and linear mixed models to determine whether hemiparasites were associated with changes in community richness and evenness. Hemiparasite presence did not affect community metrics. Hemiparasite abundance was positively associated with increasing evenness of herbaceous species, but not with species richness. The associations that we observed on a continental scale are consistent with evidence that the impacts of root hemiparasitic plants on evenness can be substantial and abundance dependent but that effects on richness are less pronounced. Hemiparasites mediate competitive exclusion in communities to facilitate species coexistence and merit consideration of inclusion in ecological theories of coexistence.
Surface and subsurface moored buoy, ship-based, remotely sensed, and reanalysis datasets are used to investigate thermal variability of northern Gulf of Alaska (NGA) nearshore, coastal, and offshore waters over synoptic to century-long time scales. NGA sea surface temperature (SST) showed a larger positive trend of 0.22 ± 0.10 °C per decade over 1970–2021 compared to 0.10 ± 0.03 °C per decade over 1900–2021. Over synoptic time scales, SST covariance between two stations is small (<10%) when separation exceeds 100 km, while stations separated by 500 km retain 50% of their co-variability for seasonal and longer fluctuations. Relative to in situ sensor data, remotely sensed SST data has limited accuracy in some NGA settings, capturing 60–70% of the daily SST anomaly in coastal and offshore waters, but often <25% nearshore. North Pacific and NGA leading modes of SST variability leave 25–50% of monthly variance unresolved. Analysis of the 2014–2016 Pacific marine heatwave shows that NGA coastal surface temperatures warmed contemporaneously with offshore waters through 2013, but deep inner shelf waters (200–250 m) exhibited delayed warming. Offshore surface waters cooled from 2014 to 2016, while shelf waters continued to warm from the combined effects of local air-sea and advective heat fluxes. We find that annually averaged Sitka air temperature is a leading predictor (r2 = 0.37, p < 0.05) for following-year NGA coastal water column temperature. Our results can inform future environmental monitoring designs, assist forward-looking projections of marine conditions, and show the importance of in situ measurements for nearshore studies that require knowledge of thermal conditions over time scales of days and weeks.
The lesser prairie-chicken (Tympanuchus pallidicinctus) is a species of prairie grouse that occupies grassland ecosystems in the Southern and Central High Plains of the Great Plains. Reduced abundance and occupied ranges have led to increased conservation efforts throughout the species’ range. Habitat loss is considered the predominant cause of these declines. In the Southern High Plains of Texas and New Mexico, lesser prairie-chicken habitat corresponds to the Sand Shinnery Oak Prairie Ecoregion, which is comprised of a mixture of sand shinnery oak (Quercus havardii)-dominated grasslands, sand sagebrush (Artemisia filifolia)-dominated grasslands, and mixed grasslands. In sand shinnery oak–grassland communities, conversion to row-crop agriculture, continuous unmanaged livestock grazing, restriction of natural fire, invasive plant species (e.g., mesquite (Prosopis spp.)), extensive use of herbicides, energy development, and a variety of other factors have also negatively affected ecosystem extent and function. We integrated historical maps and remote sensing-derived information to measure trends in the extent and geographical distribution of sand shinnery oak prairies in eastern New Mexico and northwest Texas. Potential lesser prairie-chicken habitat was reduced by 56% from a potential of 43,258 km2 to 18,908 km2 in ~115 years (since pre-settlement). Our assessment indicated both mixed grasslands and sand shinnery oak-dominated grasslands were transformed from large parcels of existing vegetation communities to urban settlements, row crops, roads, and industrial land uses by the 1970s. Currently, potential habitat is highly fragmented and restricted to isolated locations in Texas and New Mexico, with an increasing dominance in mixed grasslands, especially in the southeastern portion of the lesser prairie-chicken range. Sand shinnery oak-dominated grasslands have been declining rapidly, from 69% of its potential extent in 1985, 65% in 1995, 54% in 2005, to 42% in 2015. Mixed grasslands drastically declined to 50% of its potential distribution by 1985. Since then, it has been stable until the 2005–2015 period when it declined to 45% of its potential extent. Based on the 2015 assessment, the current potential habitat for lesser prairie chicken is estimated at 18,908 km2 (1,890,800 ha or 4.6 million acres), where 13,126 km2 corresponds to mixed grasslands and 5782 km2 corresponds to sand shinnery oak-dominated grasslands.
","language":"English","publisher":"MDPI","doi":"10.3390/rs14153780","usgsCitation":"Portillo-Quintero, C., Grisham, B., Haukos, D.A., Boal, C.W., Christian A. Hagen, Wan, Z., Subedi, M., and Menkiti, N., 2022, Trends of lesser prairie-chicken habitat extent and distribution on the Southern High Plains: Remote Sensing, v. 14, no. 15, 3780, 21 p., https://doi.org/10.3390/rs14153780.","productDescription":"3780, 21 p.","ipdsId":"IP-134001","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":446881,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs14153780","text":"Publisher Index Page"},{"id":429754,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico, Texas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -105.1173828305202,\n 34.97867213600597\n ],\n [\n -105.1173828305202,\n 31.262556094417107\n ],\n [\n -101.82148439302048,\n 31.262556094417107\n ],\n [\n -101.82148439302048,\n 34.97867213600597\n ],\n [\n -105.1173828305202,\n 34.97867213600597\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"14","issue":"15","noUsgsAuthors":false,"publicationDate":"2022-08-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Portillo-Quintero, Carlos","contributorId":198384,"corporation":false,"usgs":false,"family":"Portillo-Quintero","given":"Carlos","email":"","affiliations":[],"preferred":false,"id":902666,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grisham, Blake","contributorId":337771,"corporation":false,"usgs":false,"family":"Grisham","given":"Blake","affiliations":[{"id":36331,"text":"Texas Tech University","active":true,"usgs":false}],"preferred":false,"id":902870,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haukos, David A. 0000-0001-5372-9960 dhaukos@usgs.gov","orcid":"https://orcid.org/0000-0001-5372-9960","contributorId":3664,"corporation":false,"usgs":true,"family":"Haukos","given":"David","email":"dhaukos@usgs.gov","middleInitial":"A.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":902665,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boal, Clint W. 0000-0001-6008-8911 cboal@usgs.gov","orcid":"https://orcid.org/0000-0001-6008-8911","contributorId":1909,"corporation":false,"usgs":true,"family":"Boal","given":"Clint","email":"cboal@usgs.gov","middleInitial":"W.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":902671,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Christian A. Hagen","contributorId":217299,"corporation":false,"usgs":false,"family":"Christian A. Hagen","affiliations":[{"id":25426,"text":"OSU","active":true,"usgs":false}],"preferred":false,"id":902871,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wan, Zhanming","contributorId":211684,"corporation":false,"usgs":false,"family":"Wan","given":"Zhanming","email":"","affiliations":[],"preferred":false,"id":902669,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Subedi, Mukti","contributorId":337996,"corporation":false,"usgs":false,"family":"Subedi","given":"Mukti","email":"","affiliations":[],"preferred":false,"id":902872,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Menkiti, Nwasinachi","contributorId":337772,"corporation":false,"usgs":false,"family":"Menkiti","given":"Nwasinachi","email":"","affiliations":[{"id":40367,"text":"Utah Valley University","active":true,"usgs":false}],"preferred":false,"id":902670,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70236633,"text":"70236633 - 2022 - Landsat 9 geometric characteristics using underfly data","interactions":[],"lastModifiedDate":"2022-09-14T14:10:56.085395","indexId":"70236633","displayToPublicDate":"2022-08-06T09:07:54","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Landsat 9 geometric characteristics using underfly data","docAbstract":"The Landsat program has a long history of providing remotely sensed data to the user community. This history is being extended with the addition of the Landsat 9 satellite, which closely mimics the Landsat 8 satellite and its instruments. These satellites contain two instruments, the Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS). OLI is a push-broom sensor that collects visible and near-infrared (VNIR) and short-wave infrared (SWIR) wavelengths at 30 m ground sample distance, along with a panchromatic 15 m band. The TIRS sensor contains two long-wave thermal spectral channels centered at 10.9 and 12 µm. The data from these two instruments, on both satellites, are combined into a single Landsat product. The Landsat 5–9 satellites follow a 16 day repeat cycle designated as the Worldwide Reference System (WRS-2), which provides a global notional gridded mapping for identifying individual Landsat scenes. The Landsat 8 and 9 satellites are flown such that their orbital tracks are separated by 8 days in this 16 day cycle. During the commissioning period of Landsat 9, and during its ascent to its operational WRS-2 orbit, the Landsat 9 satellite’s orbital track went under and crossed over the orbital track of the Landsat 8 satellite. This produced a unique situation where nearly time-coincident imagery could be obtained from the instruments of the two spacecrafts. From a radiometric standpoint, this allowed for near-time cross-calibration between the instruments to be performed. From a geometry perspective, calibration is achieved through high-resolution reference imagery over specific ground locations, thus ensuring calibration of the instruments and for the instruments to be well cross-calibrated geometrically. Although these underfly data do not provide calibration of the instruments between the platforms from a geometric perspective, they allow for the verification of the calibration steps involving the instruments and spacecraft. This paper discusses the co-registration of this unique set of data while also discussing other geometric aspects of these data by looking at and comparing the differences in sensor viewing and sun angles associated with the collections from the two platforms for imagery obtained over common geographic locations. The image-to-image comparisons between Landsat 8 and 9 coincident pairs, where both datasets are precision terrain products, are registered to within 2.2 m with respect to their root-mean-squared radial error (RMSEr). The 2.2 m represents less than 0.1 of a 30 m multispectral pixel in misregistration between the L9 and L8 underfly products that will be available to the user community. This unique dataset will provide well-registered, near-coincident image acquisitions between the two platforms that can be a key to any calibration or application comparisons. The paper also presents that, for images for which one of the image pairs failed precision corrections and became a terrain-corrected only product type, a range of 8–14 m RMSEr could be expected in co-registration, while, in cases where both image pairs failed the precision correction step and both images became a terrain-corrected only product type, a 14 m RMSEr could be expected for co-registration.
","language":"English","publisher":"MDPI","doi":"10.3390/rs14153781","usgsCitation":"Choate, M.J., Rengarajan, R., Storey, J., and Lubke, M., 2022, Landsat 9 geometric characteristics using underfly data: Remote Sensing, v. 14, no. 15, 3781, 18 p., https://doi.org/10.3390/rs14153781.","productDescription":"3781, 18 p.","ipdsId":"IP-141262","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":446884,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs14153781","text":"Publisher Index Page"},{"id":406670,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"15","noUsgsAuthors":false,"publicationDate":"2022-08-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Choate, Michael J. 0000-0002-8101-4994","orcid":"https://orcid.org/0000-0002-8101-4994","contributorId":216866,"corporation":false,"usgs":true,"family":"Choate","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":851559,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rengarajan, Rajagopalan 0000-0003-1860-7110","orcid":"https://orcid.org/0000-0003-1860-7110","contributorId":242014,"corporation":false,"usgs":false,"family":"Rengarajan","given":"Rajagopalan","affiliations":[{"id":48475,"text":"KBR, Contractor to USGS EROS","active":true,"usgs":false}],"preferred":false,"id":851560,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Storey, James C. 0000-0002-6664-7232","orcid":"https://orcid.org/0000-0002-6664-7232","contributorId":242015,"corporation":false,"usgs":false,"family":"Storey","given":"James C.","affiliations":[{"id":48475,"text":"KBR, Contractor to USGS EROS","active":true,"usgs":false}],"preferred":false,"id":851561,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lubke, Mark 0000-0002-7257-2337","orcid":"https://orcid.org/0000-0002-7257-2337","contributorId":261911,"corporation":false,"usgs":false,"family":"Lubke","given":"Mark","email":"","affiliations":[{"id":53079,"text":"KBR, contractor to U.S. Geological Survey","active":true,"usgs":false}],"preferred":false,"id":851562,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70239382,"text":"70239382 - 2022 - A geospatial knowledge graph prototype for national topographic mapping","interactions":[],"lastModifiedDate":"2023-01-11T15:03:10.21326","indexId":"70239382","displayToPublicDate":"2022-08-06T08:58:31","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":12997,"text":"International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences","active":true,"publicationSubtype":{"id":10}},"title":"A geospatial knowledge graph prototype for national topographic mapping","docAbstract":"Knowledge graphs are a form of database representation and handling that show the potential to better meet the challenges of data interoperability, semi-automated information reasoning, and information retrieval. Geospatial knowledge graphs (GKG) have at their core specialized forms of applied ontology that provide coherent spatial context to a domain of information including non-spatial attributes. This paper discusses research toward the development of a prototype GKG based on national topographic databases of geospatial feature instances, attributes, properties, metadata, and annotations. The challenges are to capture and represent geographic semantics inherent in the source data, to align such graph models with standards where possible, to test logical computations, and to visualize the data using a cartographic user interface. Data integration from outside sources was tested through SPARQL and GeoSPARQL queries. Called the MapKB, the approaches applied in this prototype use a number of software components to build a system architecture aligned with those objectives and are composed entirely of free and open-source software. The system and ontology design were validated through reasoning and competency questions. Technical aspects of the prototype software succeeded, but customization was found to be needed for user-based design.
","language":"English","publisher":"International Society of Photogrammetry and Remote Sensing","doi":"10.5194/isprs-archives-XLVIII-4-W1-2022-511-2022","usgsCitation":"Varanka, D.E., 2022, A geospatial knowledge graph prototype for national topographic mapping: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, v. XLVIII-4/W1-2022, p. 511-516, https://doi.org/10.5194/isprs-archives-XLVIII-4-W1-2022-511-2022.","productDescription":"6 p.","startPage":"511","endPage":"516","ipdsId":"IP-120273","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":446887,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/isprs-archives-xlviii-4-w1-2022-511-2022","text":"Publisher Index Page"},{"id":411719,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"XLVIII-4/W1-2022","noUsgsAuthors":false,"publicationDate":"2022-08-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Varanka, Dalia E. 0000-0003-2857-9600 dvaranka@usgs.gov","orcid":"https://orcid.org/0000-0003-2857-9600","contributorId":1296,"corporation":false,"usgs":true,"family":"Varanka","given":"Dalia","email":"dvaranka@usgs.gov","middleInitial":"E.","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true},{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true}],"preferred":true,"id":861370,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70234564,"text":"70234564 - 2022 - Soil carbon consequences of historic hydrologic impairment and recent restoration in coastal wetlands","interactions":[],"lastModifiedDate":"2022-08-12T12:20:13.874057","indexId":"70234564","displayToPublicDate":"2022-08-06T08:20:00","publicationYear":"2022","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":"Soil carbon consequences of historic hydrologic impairment and recent restoration in coastal wetlands","docAbstract":"Coastal wetlands provide key ecosystem services, including substantial long-term storage of atmospheric CO2 in soil organic carbon pools. This accumulation of soil organic matter is a vital component of elevation gain in coastal wetlands responding to sea-level rise. Anthropogenic activities that alter coastal wetland function through disruption of tidal exchange and wetland water levels are ubiquitous. This study assesses soil vertical accretion and organic carbon accretion across five coastal wetlands that experienced over a century of impounded hydrology, followed by restoration of tidal exchange 5 to 14 years prior to sampling. Nearby marshes that never experienced tidal impoundment served as controls with natural hydrology to assess the impact of impoundment and restoration. Dated soil cores indicate that elevation gain and carbon storage were suppressed 30–70 % during impoundment, accounting for the majority of elevation deficit between impacted and natural sites. Only one site had substantial subsidence, likely due to oxidation of soil organic matter. Vertical and carbon accretion gains were achieved at all restored sites, with carbon burial increasing from 96 ± 33 to 197 ± 64 g C m−2 y−1. The site with subsidence was able to accrete at double the rate (13 ± 5.6 mm y−1) of the natural complement, due predominantly to organic matter accumulation rather than mineral deposition, indicating these ecosystems are capable of large dynamic responses to restoration when conditions are optimized for vegetation growth. Hydrologic restoration enhanced elevation resilience and climate benefits of these coastal wetlands.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2022.157682","usgsCitation":"Eagle, M.J., Kroeger, K.D., Spivak, A.C., Wang, F., Tang, J., Abdul-Aziz, O.I., Ishtiaq, K.S., O’Keefe Suttles, J.A., and Mann, A.G., 2022, Soil carbon consequences of historic hydrologic impairment and recent restoration in coastal wetlands: Science of the Total Environment, v. 848, 157682, 12 p., https://doi.org/10.1016/j.scitotenv.2022.157682.","productDescription":"157682, 12 p.","ipdsId":"IP-140249","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":446890,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2022.157682","text":"Publisher Index Page"},{"id":405111,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Cape Cod","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.56655883789062,\n 41.693424216151314\n ],\n [\n -69.96231079101562,\n 41.693424216151314\n ],\n [\n -69.96231079101562,\n 41.87262868373214\n ],\n [\n -70.56655883789062,\n 41.87262868373214\n ],\n [\n -70.56655883789062,\n 41.693424216151314\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"848","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Eagle, Meagan J. 0000-0001-5072-2755 meagle@usgs.gov","orcid":"https://orcid.org/0000-0001-5072-2755","contributorId":242890,"corporation":false,"usgs":true,"family":"Eagle","given":"Meagan","email":"meagle@usgs.gov","middleInitial":"J.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":848842,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kroeger, Kevin D. 0000-0002-4272-2349 kkroeger@usgs.gov","orcid":"https://orcid.org/0000-0002-4272-2349","contributorId":1603,"corporation":false,"usgs":true,"family":"Kroeger","given":"Kevin","email":"kkroeger@usgs.gov","middleInitial":"D.","affiliations":[{"id":41100,"text":"Coastal and Marine Hazards and Resources Program","active":true,"usgs":true}],"preferred":true,"id":848843,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Spivak, Amanda C.","contributorId":191376,"corporation":false,"usgs":false,"family":"Spivak","given":"Amanda","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":848844,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wang, Faming","contributorId":216959,"corporation":false,"usgs":false,"family":"Wang","given":"Faming","email":"","affiliations":[{"id":39553,"text":"The Ecosystems Center, Marine Biological Laboratory, Woods Hole, MA","active":true,"usgs":false}],"preferred":false,"id":848845,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tang, Jianwu","contributorId":174890,"corporation":false,"usgs":false,"family":"Tang","given":"Jianwu","email":"","affiliations":[{"id":27818,"text":"The Ecosystems Center, Marine Biological Laboratory. Woods Hole, MA 02543.","active":true,"usgs":false}],"preferred":false,"id":848846,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Abdul-Aziz, Omar I.","contributorId":192386,"corporation":false,"usgs":false,"family":"Abdul-Aziz","given":"Omar","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":848847,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ishtiaq, Khandker S.","contributorId":211669,"corporation":false,"usgs":false,"family":"Ishtiaq","given":"Khandker","email":"","middleInitial":"S.","affiliations":[{"id":38311,"text":"Department of Civil and Environmental Engineering, West Virginia University, PO Box 6103, Morgantown, WV 26506","active":true,"usgs":false}],"preferred":false,"id":848848,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"O’Keefe Suttles, Jennifer A. 0000-0003-2345-5633","orcid":"https://orcid.org/0000-0003-2345-5633","contributorId":202609,"corporation":false,"usgs":true,"family":"O’Keefe Suttles","given":"Jennifer","email":"","middleInitial":"A.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":848849,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Mann, Adrian G. 0000-0003-1689-8524 adriangreen@usgs.gov","orcid":"https://orcid.org/0000-0003-1689-8524","contributorId":4328,"corporation":false,"usgs":true,"family":"Mann","given":"Adrian","email":"adriangreen@usgs.gov","middleInitial":"G.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":848850,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70236944,"text":"70236944 - 2022 - Recent declines in genetic diversity with limited dispersal among coastal cactus wren populations in San Diego County, California","interactions":[],"lastModifiedDate":"2022-09-22T11:57:20.09399","indexId":"70236944","displayToPublicDate":"2022-08-06T06:55:38","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5803,"text":"Conservation Science and Practice","active":true,"publicationSubtype":{"id":10}},"title":"Recent declines in genetic diversity with limited dispersal among coastal cactus wren populations in San Diego County, California","docAbstract":"Habitat loss and fragmentation can lead to smaller and more isolated populations and reduce genetic diversity and evolutionary potential. Conservation programs can benefit from including monitoring of genetic factors in fragmented populations to help inform restoration and management. We assessed genetic diversity and structure among four major populations of the Cactus Wren (Campylorhynchus brunneicapillus) in San Diego County in 2011–2012 and again in 2017–2019, using 22 microsatellite loci. We found a significant decline in heterozygosity in one population (San Pasqual) and a decline in allelic richness and effective population size in another (Sweetwater). Genetic diversity in the remaining two populations was not significantly different over time. Local diversity declined despite evidence of dispersal among some populations. Approximately 12% of genetically determined family groups (parents, offspring, siblings) included one or more members sampled in different territories with distances ranging from 0.2 to 10 km. All but one inferred dispersal events occurred within the same genetic population. Population structure remained relatively stable, although genetic differentiation tended to increase in the later sampling period. Simulations suggest that at currently estimated effective sizes, populations of Cactus Wrens will continue to lose genetic diversity for many generations, even if gene flow among them is enhanced. However, the rate of loss of heterozygosity could be reduced with increased gene flow. Habitat restoration may help bolster local population sizes and allelic richness over the long term, whereas translocation efforts from source populations outside of San Diego may be needed to restore genetic diversity in the short term.
Genetic admixture is a biological event inherent to genetic rescue programs aimed at the long-term conservation of endangered wildlife. Although the success of such programs can be measured by the increase in genetic diversity and fitness of subsequent admixed individuals, predictions supporting admixture costs to fitness due to the introduction of novel deleterious alleles are necessary. Here, we analyzed nonsynonymous variation from conserved genes to quantify and compare levels of mutation load (i.e. proportion of deleterious alleles and genotypes carrying these alleles) among endangered Florida panthers and non-endangered Texas pumas. Specifically, we used canonical (i.e. non-admixed) Florida panthers, Texas pumas, and F1 (canonical Florida × Texas) panthers dating from a genetic rescue program and Everglades National Park panthers with Central American ancestry resulting from an earlier admixture event. We found neither genetic drift nor selection significantly reduced overall proportions of deleterious alleles in the severely bottlenecked canonical Florida panthers. Nevertheless, the deleterious alleles identified were distributed into a disproportionately high number of homozygous genotypes due to close inbreeding in this group. Conversely, admixed Florida panthers (either with Texas or Central American ancestry) presented reduced levels of homozygous genotypes carrying deleterious alleles but increased levels of heterozygous genotypes carrying these variants relative to canonical Florida panthers. Although admixture is likely to alleviate the load of standing deleterious variation present in homozygous genotypes, our results suggest that introduced novel deleterious alleles (temporarily present in heterozygous state) in genetically rescued populations could potentially be expressed in subsequent generations if their effective sizes remain small.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/jhered/esac037","usgsCitation":"Ochoa, A., Onorato, D.P., Roelke-Parker, M.E., Culver, M., and Fitak, R., 2022, Give and take: Effects of genetic admixture on mutation load in endangered Florida panthers: Journal of Heredity, v. 113, no. 5, p. 491-499, https://doi.org/10.1093/jhered/esac037.","productDescription":"9 p.","startPage":"491","endPage":"499","ipdsId":"IP-132513","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":430045,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"113","issue":"5","noUsgsAuthors":false,"publicationDate":"2022-08-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Ochoa, Alexander","contributorId":338607,"corporation":false,"usgs":false,"family":"Ochoa","given":"Alexander","affiliations":[{"id":81173,"text":"the Department of Biology and Genomics and Bioinformatics Cluster","active":true,"usgs":false}],"preferred":false,"id":903394,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Onorato, David P.","contributorId":338608,"corporation":false,"usgs":false,"family":"Onorato","given":"David","email":"","middleInitial":"P.","affiliations":[{"id":36335,"text":"Fish and Wildlife Research Institute","active":true,"usgs":false}],"preferred":false,"id":903395,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roelke-Parker, Melody E.","contributorId":338609,"corporation":false,"usgs":false,"family":"Roelke-Parker","given":"Melody","email":"","middleInitial":"E.","affiliations":[{"id":81174,"text":"Frederick National Laboratory of Cancer Research, Leidos Biomedical Research, Inc","active":true,"usgs":false}],"preferred":false,"id":903396,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Culver, Melanie 0000-0001-5380-3059 mculver@usgs.gov","orcid":"https://orcid.org/0000-0001-5380-3059","contributorId":197693,"corporation":false,"usgs":true,"family":"Culver","given":"Melanie","email":"mculver@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":903393,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fitak, Robert R.","contributorId":338610,"corporation":false,"usgs":false,"family":"Fitak","given":"Robert R.","affiliations":[{"id":81173,"text":"the Department of Biology and Genomics and Bioinformatics Cluster","active":true,"usgs":false}],"preferred":false,"id":903397,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70233932,"text":"70233932 - 2022 - Trends analysis of Rangeland Condition Monitoring Assessment and Projection (RCMAP) fractional component time series (1985–2020)","interactions":[],"lastModifiedDate":"2024-01-19T15:18:40.15331","indexId":"70233932","displayToPublicDate":"2022-08-05T11:36:29","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":8118,"text":"GIScience & Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Trends analysis of Rangeland Condition Monitoring Assessment and Projection (RCMAP) fractional component time series (1985–2020)","docAbstract":"Rangelands have a dynamic response to climate change, fire, and other anthropogenic disturbances. The Rangeland Condition, Monitoring, Assessment, and Projection (RCMAP) product aims to capture this response by quantifying the percent cover of eight rangeland components, associated error, and trends across the western United States using Landsat from 1985 to 2020. The current generation of RCMAP has been improved with more training data, regional-scale Landsat composites, and more robust change detection. We assess the temporal patterns in each component with a linear model and a structural change method that determines break points using an 8-year temporal moving window. The linear and structural change methods generally agreed on patterns of change, but the latter found breaks more often, with at least one break point in most pixels. The structural change model provides more robust statistics on the significant minority of pixels with non-monotonic trends, while detrending some interannual signal potentially superfluous from a long-term perspective. Although break point density within one year of fire and vegetation treatments was ~10× and ~4× that of unburned areas, respectively, break point detection in the correct year of fire was only moderately accurate. Climate responses in break points proved more robust, with strong spatiotemporal relation in break point density with both aridity index values and aridity index change. Break point density strongly responds to both increased and decreased aridity and is reflective of ecosystem resilience. Data provide spatiotemporal information on the occurrence of breaks, but even more importantly, attribute those change events to specific component(s).
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/15481603.2022.2104786","usgsCitation":"Shi, H., Rigge, M.B., Postma, K., and Bunde, B., 2022, Trends analysis of Rangeland Condition Monitoring Assessment and Projection (RCMAP) fractional component time series (1985–2020): GIScience & Remote Sensing, v. 59, no. 1, p. 1243-1265, https://doi.org/10.1080/15481603.2022.2104786.","productDescription":"23 p.","startPage":"1243","endPage":"1265","ipdsId":"IP-135462","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":446897,"rank":4,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/15481603.2022.2104786","text":"Publisher Index Page"},{"id":424623,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9SJXUI1","text":"USGS data release","linkFileType":{"id":5,"text":"html"},"linkHelpText":"Rangeland Condition Monitoring Assessment 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(Geography)","active":false,"usgs":true}],"preferred":true,"id":847707,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Postma, Kory 0000-0001-8058-498X","orcid":"https://orcid.org/0000-0001-8058-498X","contributorId":293879,"corporation":false,"usgs":false,"family":"Postma","given":"Kory","affiliations":[{"id":63548,"text":"KBRwyle, under contract to USGS","active":true,"usgs":false}],"preferred":false,"id":847708,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bunde, Brett 0000-0003-0228-779X","orcid":"https://orcid.org/0000-0003-0228-779X","contributorId":288364,"corporation":false,"usgs":false,"family":"Bunde","given":"Brett","affiliations":[{"id":61731,"text":"KBR","active":true,"usgs":false}],"preferred":false,"id":847709,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70234258,"text":"70234258 - 2022 - Understanding impacts of sea-level rise and land management on critical coastal marsh habitat","interactions":[],"lastModifiedDate":"2022-10-21T15:45:16.955892","indexId":"70234258","displayToPublicDate":"2022-08-05T10:39:33","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":7504,"text":"Final Report","active":true,"publicationSubtype":{"id":1}},"title":"Understanding impacts of sea-level rise and land management on critical coastal marsh habitat","docAbstract":"Coastal wetlands in the Louisiana Mississippi River Deltaic Plain (MRDP) experience some of the highest rates of relative sea-level rise (SLR) in the world, leading to elevated surface water salinity and prolonged flooding. Elevated salinity causes a shift toward more salt-tolerant vegetation communities, associated with changes in ecosystem function and services. As sea level continues to rise, even salt-tolerant plant communities succumb to impacts of excessive flooding through submergence and conversion to open water. To better characterize the impacts of SLR on coastal wetland health and sustainability, we focused on two key landscape transitions in this project: 1) freshwater marsh transition to saltwater marsh, and 2) saltwater marsh transition to open water. We investigated these transitions using data with greater spatial and temporal resolution than previous studies in this region, allowing us to identify the mechanisms underlying widely observed landscape changes.
","language":"English","publisher":"South Central Climate Adaptation Science Center","usgsCitation":"Stagg, C., 2022, Understanding impacts of sea-level rise and land management on critical coastal marsh habitat: Final Report, 20 p.","productDescription":"20 p.","ipdsId":"IP-143747","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":408614,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":404866,"type":{"id":15,"text":"Index Page"},"url":"https://cascprojects.org/#/project/4f8c652fe4b0546c0c397b4a/5f315e4482ceae4cb3ca5195"}],"country":"United States","state":"Louisiana","otherGeospatial":"Mississippi River deltaic plain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -89.50590005310218,\n 29.42101094649145\n ],\n [\n -89.50590005310218,\n 30.0568363860655\n ],\n [\n -90.26633984845733,\n 30.0568363860655\n ],\n [\n -90.26633984845733,\n 29.42101094649145\n ],\n [\n -89.50590005310218,\n 29.42101094649145\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Stagg, Camille 0000-0002-1125-7253","orcid":"https://orcid.org/0000-0002-1125-7253","contributorId":222386,"corporation":false,"usgs":true,"family":"Stagg","given":"Camille","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":848355,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70273794,"text":"70273794 - 2022 - Global review of the effects of small carnivores on threatened species","interactions":[],"lastModifiedDate":"2026-01-30T16:28:44.317532","indexId":"70273794","displayToPublicDate":"2022-08-05T10:24:10","publicationYear":"2022","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"21","title":"Global review of the effects of small carnivores on threatened species","docAbstract":"The absences of large carnivores from many ecosystems, human-induced landscape changes, and resource supplementation have been theorized to increase the abundance of small carnivore species around the world. Overabundant and/or unconstrained small carnivores can have significant effects on specific prey species that, in some cases, can cascade through entire ecosystems. Here, we review the effects of small carnivores on threatened species. We focus on four well-studied families (Procyonidae, Mephitidae, Mustelidae, and Herpestidae) and emphasize that this is a global conservation issue with consequences for biodiversity. We review and compare the impacts that small carnivores can have on a variety of prey taxa including small mammals, nesting avian and reptilian species, and rare invertebrates. We differentiate between native and exotic small carnivores because this is often an important distinction in terms of the impact severity and range of effects. In addition to direct lethal effects (i.e. predation), small carnivores can also impact threatened species as disease vectors and through competition or overexploitation, which can disrupt communities via ecological release or extinction. Furthermore, we explore other case studies in which small carnivores have had positive effects on threatened species and discuss studies that reveal other taxa responsible for exerting stronger negative effects on threatened prey. We offer some concluding remarks about global small carnivore conservation and emphasize the need for decision-analytic approaches and robust analyses that can improve our assessment of how populations of threatened species can be affected. To date, indirect effects are especially difficult to measure in the field and many studies have provided only anecdotal or correlative results, signalling a need for improving our scientific methodologies and management approaches.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Small carnivores: Evolution, ecology behaviour, and conservation","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Wiley","doi":"10.1002/9781118943274.ch21","usgsCitation":"Cove, M., and O’Connell, A.F., 2022, Global review of the effects of small carnivores on threatened species, chap. 21 of Small carnivores: Evolution, ecology behaviour, and conservation, p. 471-488, https://doi.org/10.1002/9781118943274.ch21.","productDescription":"18 p.","startPage":"471","endPage":"488","ipdsId":"IP-062662","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":499368,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2022-08-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Cove, Michael V.","contributorId":176507,"corporation":false,"usgs":false,"family":"Cove","given":"Michael V.","affiliations":[],"preferred":false,"id":954844,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O’Connell, Allan F. 0000-0001-7032-7023 aoconnell@usgs.gov","orcid":"https://orcid.org/0000-0001-7032-7023","contributorId":471,"corporation":false,"usgs":true,"family":"O’Connell","given":"Allan","email":"aoconnell@usgs.gov","middleInitial":"F.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":954845,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70234253,"text":"70234253 - 2022 - Microbial community response to a bioaugmentation test to degrade trichloroethylene in a fractured rock aquifer, Trenton, N.J","interactions":[],"lastModifiedDate":"2022-08-05T14:00:18.164559","indexId":"70234253","displayToPublicDate":"2022-08-05T08:46:55","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2729,"text":"Microbial Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Microbial community response to a bioaugmentation test to degrade trichloroethylene in a fractured rock aquifer, Trenton, N.J","docAbstract":"Bioaugmentation is a promising strategy for enhancing trichloroethylene (TCE) degradation in fractured rock. However, slow or incomplete biodegradation can lead to stalling at degradation byproducts such as 1,2-dichloroethene (cis-DCE) and vinyl chloride (VC). Over the course of 7 years, we examined the response of groundwater microbial populations in a bioaugmentation test where an emulsified vegetable oil solution (EOS®) and a dechlorinating consortium (KB-1®), containing the established dechlorinator Dehalococcoides (DHC), were injected into a TCE-contaminated fractured rock aquifer. Indigenous microbial communities responded within 2 days to added substrate and outcompeted KB-1®, and over the years of monitoring, several other notable turnover events were observed. Concentrations of ethene, the end product in reductive dechlorination, had the strongest correlations (P< .05) with members of Candidatus Colwellbacteria but their involvement in reductive dechlorination is unknown and warrants further investigation.DHC never exceeded 0.6% relative abundance of groundwater microbial communities, despite its previously presumed importance at the site. Increased concentrations of carbon dioxide, acetic acid, and methane were positively correlated with increasing ethene concentrations; however, concentrations of cis-DCE and VC remained high by the end of the monitoring period suggesting preferential enrichment of indigenous partial dechlorinators over bioaugmented complete dechlorinators. This study highlights the importance of characterizing in situ microbial populations to understand how they can potentially enhance or inhibit augmented TCE degradation.
","language":"English","publisher":"Oxford University Press","doi":"10.1093/femsec/fiac077","usgsCitation":"Underwood, J.C., Akob, D., Lorah, M.M., Imbrigiotta, T.E., Harvey, R.W., and Tiedeman, C.R., 2022, Microbial community response to a bioaugmentation test to degrade trichloroethylene in a fractured rock aquifer, Trenton, N.J: Microbial Ecology, v. 98, no. 7, fiac077, 16 p., https://doi.org/10.1093/femsec/fiac077.","productDescription":"fiac077, 16 p.","ipdsId":"IP-136036","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":446899,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/femsec/fiac077","text":"Publisher Index Page"},{"id":435740,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RCWZPH","text":"USGS data release","linkHelpText":"Microbial community analyses of groundwater collected during an enhanced bioremediation experiment of trichlorethylene in a fractured rock aquifer, West Trenton, NJ (2008-2015)"},{"id":404875,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Jersey","city":"Trenton","otherGeospatial":"Naval Air Warfare Center","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.81015682220459,\n 40.26737800407964\n ],\n [\n -74.80513572692871,\n 40.27612061363972\n ],\n [\n -74.80620861053467,\n 40.27726656481315\n ],\n [\n -74.80620861053467,\n 40.277855903568465\n ],\n [\n -74.80582237243652,\n 40.27903456566876\n ],\n [\n -74.80449199676514,\n 40.28001676838985\n ],\n [\n -74.80384826660156,\n 40.28093347805573\n ],\n [\n -74.80393409729004,\n 40.28227578049736\n ],\n [\n -74.80462074279785,\n 40.28315972120923\n ],\n [\n -74.80582237243652,\n 40.283847222661024\n ],\n [\n -74.80753898620605,\n 40.28407638825784\n ],\n [\n -74.80955600738525,\n 40.28437102859794\n ],\n [\n -74.81015682220459,\n 40.28391269862511\n ],\n [\n -74.8119592666626,\n 40.28355258003785\n ],\n [\n -74.81316089630127,\n 40.28342162734864\n ],\n [\n -74.81380462646484,\n 40.283749008596\n ],\n [\n -74.81393337249756,\n 40.28443650405466\n ],\n [\n -74.81462001800536,\n 40.28515672989297\n ],\n [\n -74.81569290161133,\n 40.285385891050446\n ],\n [\n -74.81676578521729,\n 40.2853531537898\n ],\n [\n -74.81959819793701,\n 40.283847222661024\n ],\n [\n -74.8218297958374,\n 40.28122813209425\n ],\n [\n -74.82221603393555,\n 40.28057334359796\n ],\n [\n -74.82208728790283,\n 40.27978758903121\n ],\n [\n -74.82079982757568,\n 40.278641680585025\n ],\n [\n -74.82058525085449,\n 40.277757680799304\n ],\n [\n -74.82191562652588,\n 40.273304765410735\n ],\n [\n -74.82174396514893,\n 40.272813617082406\n ],\n [\n -74.82213020324707,\n 40.271765822059926\n ],\n [\n -74.82414722442626,\n 40.27058703325471\n ],\n [\n -74.82354640960693,\n 40.269735673006274\n ],\n [\n -74.8218297958374,\n 40.26858959420978\n ],\n [\n -74.8192548751831,\n 40.26580617913769\n ],\n [\n -74.81462001800536,\n 40.268098411637695\n ],\n [\n -74.81015682220459,\n 40.26737800407964\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"98","issue":"7","noUsgsAuthors":false,"publicationDate":"2022-06-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Underwood, Jennifer C. 0000-0002-2702-0410 jcunder@usgs.gov","orcid":"https://orcid.org/0000-0002-2702-0410","contributorId":294555,"corporation":false,"usgs":true,"family":"Underwood","given":"Jennifer","email":"jcunder@usgs.gov","middleInitial":"C.","affiliations":[{"id":37464,"text":"WMA - 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These critical hydrologic processes are thought to be influenced by the stream corridor bedrock contact depth (sediment thickness), a parameter often inferred from sparse hillslope borehole information, piezometer refusal and remotely sensed data. To investigate how local bedrock depth might control summer stream temperature and channel disconnection (dewatering) patterns, we measured stream corridor bedrock depth by collecting and interpreting 191 passive seismic datasets along eight headwater streams in Shenandoah National Park (Virginia, USA). In addition, we used multi-year stream temperature and streamflow records to calculate several baseflow-related metrics along and among the study streams. Finally, comprehensive visual surveys of stream channel dewatering were conducted in 2016, 2019 and 2021 during summer low flow conditions (124 total km of stream length). We found that measured bedrock depths along the study streams were not well-characterized by soils maps or an existing global-scale geologic dataset where the latter overpredicted measured depths by 12.2 m (mean) or approximately four times the average bedrock depth of 2.9 m. Half of the eight study stream corridors had an average bedrock depth of less than 2 m. Of the eight study streams, Staunton River had the deepest average bedrock depth (3.4 m), the coldest summer temperature profiles and substantially higher summer baseflow indices compared to the other study steams. Staunton River also exhibited paired air and water annual temperature signals suggesting deeper groundwater influence, and the stream channel did not dewater in lower sections during any baseflow survey. In contrast, Paine Run and Piney River did show pronounced, patchy channel dewatering, with Paine Run having dozens of discrete dry channel sections ranging from 1 to greater than 300 m in length. Stream dewatering patterns were apparently influenced by a combination of discrete deep bedrock (20+ m) features and more subtle sediment thickness variation (1–4 m) depending on local stream valley hydrogeology. In combination, these unique datasets show the first large-scale empirical support for existing conceptual models of headwater stream disconnection based on spatially variable underflow capacity and shallow groundwater supply.","language":"English","publisher":"Copernicus","doi":"10.5194/hess-26-3989-2022","usgsCitation":"Briggs, M., Goodling, P.J., Johnson, Z., Rogers, K., Hitt, N.P., Fair, J.H., and Snyder, C.D., 2022, Bedrock depth influences spatial patterns of summer baseflow, temperature and flow disconnection for mountainous headwater streams: Hydrology and Earth System Sciences, v. 26, no. 15, p. 3989-4011, https://doi.org/10.5194/hess-26-3989-2022.","productDescription":"23 p.","startPage":"3989","endPage":"4011","ipdsId":"IP-132407","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - 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2022 - Status of water-level altitudes and long-term water-level changes in the Chicot and Evangeline (undifferentiated) and Jasper aquifers, greater Houston area, Texas, 2021","interactions":[],"lastModifiedDate":"2022-08-19T14:18:51.913895","indexId":"sir20225065","displayToPublicDate":"2022-08-05T07:27:23","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":"2022-5065","displayTitle":"Status of Water-Level Altitudes and Long-Term Water-Level Changes in the Chicot and Evangeline (Undifferentiated) and Jasper Aquifers, Greater Houston Area, Texas, 2021","title":"Status of water-level altitudes and long-term water-level changes in the Chicot and Evangeline (undifferentiated) and Jasper aquifers, greater Houston area, Texas, 2021","docAbstract":"Since the early 1900s, groundwater withdrawn from the primary aquifers that compose the Gulf Coast aquifer system—the Chicot and Evangeline (undifferentiated) and Jasper aquifers—has been the primary source of water in the greater Houston area, Texas. This report, prepared by the U.S. Geological Survey in cooperation with the Harris-Galveston Subsidence District, City of Houston, Fort Bend Subsidence District, Lone Star Groundwater Conservation District, and Brazoria County Groundwater Conservation District, is one in an annual series of reports depicting the status of water-level altitudes and water-level changes in aquifers in the greater Houston area.
In contrast to previous reports, the Chicot and Evangeline aquifers are treated as a single hydrogeologic unit in this report. In 2021, shaded depictions of water-level altitudes for the Chicot and Evangeline aquifers (undifferentiated) ranged from 300 feet (ft) below the North American Vertical Datum of 1988 (NAVD 88) to 300 ft above NAVD 88. The largest decline in water-level altitudes indicated by the 1977–2021 long-term water-level-change map for the Chicot and Evangeline aquifers (undifferentiated) was in the north-central part of The Woodlands, Tex., whereas the 1990–2021 long-term water-level-change map for the Chicot and Evangeline aquifers (undifferentiated) depicts a large area of decline in water-level altitudes in northwestern Harris County, northwest of Jersey Village, Tex. The largest rise in water-level altitudes in the Chicot and Evangeline aquifers (undifferentiated) was observed in a relatively large area in southeastern Harris County for 1977–2021, whereas the largest rise in water-level altitudes for 1990–2021 was in a relatively large area in central Harris County.
In 2021, shaded depictions of water-level altitudes for the Jasper aquifer ranged from 250 ft below NAVD 88 to 300 ft above NAVD 88. The 2000–21 long-term water-level-change map for the Jasper aquifer depicts water-level declines throughout most of the study area where water-level-altitude data from the Jasper aquifer were collected, with the largest decline in northern Harris County southwest of The Woodlands.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225065","collaboration":"Prepared in cooperation with the Harris-Galveston Subsidence District, City of Houston, Fort Bend Subsidence District, Lone Star Groundwater Conservation District, and Brazoria County Groundwater Conservation District","usgsCitation":"Braun, C.L., and Ramage, J.K., 2022, Status of water-level altitudes and long-term water-level changes in the Chicot and Evangeline (undifferentiated) and Jasper aquifers, greater Houston area, Texas, 2021 (ver. 1.1, August 19, 2022): U.S. Geological Survey Scientific Investigations Report 2022–5065, 25 p., https://doi.org/10.3133/sir20225065.","productDescription":"Report: iv, 25 p.; Data Releases; Dataset","numberOfPages":"34","onlineOnly":"Y","ipdsId":"IP-127697","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":405340,"rank":9,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2022/5065/versionHist.txt","text":"Version History","size":"1 kB","linkFileType":{"id":2,"text":"txt"}},{"id":405339,"rank":8,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5065/sir20225065.pdf","text":"Report","size":"13.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022–5065"},{"id":405338,"rank":7,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5065/coverthb2.jpg"},{"id":404816,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9T8FJWO","text":"USGS data release","linkHelpText":"Groundwater-level altitudes and long-term groundwater-level changes in the Chicot and Evangeline (undifferentiated) and Jasper aquifers, greater Houston area, Texas, 2021"},{"id":404817,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":404815,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9R6CX2T","text":"USGS data release","linkHelpText":"Depth to groundwater measured from wells completed in the Chicot and Evangeline (undifferentiated) and Jasper aquifers, greater Houston area, Texas, 2021"},{"id":404813,"rank":2,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5065/images"},{"id":404812,"rank":1,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5065/sir20225065.XML"},{"id":404820,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20225064","text":"Scientific Investigations Report 2022–5064","linkHelpText":"—Treatment of the Chicot and Evangeline aquifers as a single hydrogeologic unit and use of geostatistical interpolation methods to develop gridded surfaces of water-level altitudes and water-level changes in the Chicot and Evangeline aquifers (undifferentiated) and Jasper aquifer, greater Houston area, Texas, 2021"}],"country":"United States","state":"Texas","otherGeospatial":"Greater Houston area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.185302734375,\n 28.82061274169944\n ],\n [\n -94.757080078125,\n 28.82061274169944\n ],\n [\n -94.757080078125,\n 30.590637026892917\n ],\n [\n -96.185302734375,\n 30.590637026892917\n ],\n [\n -96.185302734375,\n 28.82061274169944\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: August 5, 2022; Version 1.1: August 19, 2022","contact":"Director, Oklahoma-Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754–4501
The greater Houston area of Texas includes approximately 11,000 square miles and encompasses all or part of 11 counties (Harris, Galveston, Fort Bend, Montgomery, Brazoria, Chambers, Grimes, Liberty, San Jacinto, Walker, and Waller). From the early 1900s until the mid-1970s, groundwater withdrawn from the three primary aquifers that compose the Gulf Coast aquifer system—the Chicot, Evangeline, and Jasper aquifers—had been the primary source of water for the greater Houston area. The withdrawal of groundwater was unregulated prior to 1975, resulting in land-surface subsidence caused by large water-level declines in the greater Houston area.
This report, prepared by the U.S. Geological Survey in cooperation with the Harris-Galveston Subsidence District, City of Houston, Fort Bend Subsidence District, Lone Star Groundwater Conservation District, and Brazoria County Groundwater Conservation District, describes updates to the ways in which water-level altitudes and water-level changes in the greater Houston area are presented relative to previous U.S. Geological Survey reports. The first update involves presenting water-level altitudes and water-level changes as a combined (undifferentiated) representation of the Chicot and Evangeline aquifers. The second update concerns the methods used to depict water-level altitudes and water-level changes in the greater Houston area in interpretive reports, with geostatistical interpolation methods replacing manual contouring methods.
The Chicot and Evangeline aquifers have historically been described as distinct hydrogeologic units for the purpose of water-level mapping. A confining unit does not separate these two aquifers in the study area, and water-level data from colocated wells screened in these aquifers indicate that there is likely a substantial degree of hydrogeologic connection. From a groundwater-flow perspective, these two aquifer units predominantly function as a single unit. Hence, the decision was made to combine the Chicot and Evangeline aquifers into a single, undifferentiated hydrogeologic unit for the purposes of assessing water-level altitudes and water-level changes over time. The 2020 water-level altitudes for the Chicot, Evangeline, and Jasper aquifers were re-created in this report from computer algorithms of the contoured datasets as gridded surfaces to demonstrate the similarity of results from geostatistical interpolation methods to those from manual contouring methods.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225064","collaboration":"Prepared in cooperation with the Harris-Galveston Subsidence District, City of Houston, Fort Bend Subsidence District, Lone Star Groundwater Conservation District, and Brazoria County Groundwater Conservation District","usgsCitation":"Ramage, J.K., Braun, C.L., and Ellis, J.H., 2022, Treatment of the Chicot and Evangeline aquifers as a single hydrogeologic unit and use of geostatistical interpolation methods to develop gridded surfaces of water-level altitudes and water-level changes in the Chicot and Evangeline aquifers (undifferentiated) and Jasper aquifer, greater Houston area, Texas, 2021: U.S. Geological Survey Scientific Investigations Report 2022–5064, 51 p., https://doi.org/10.3133/sir20225064.","productDescription":"Report: vi, 51 p.; Data Release; Dataset","numberOfPages":"62","onlineOnly":"Y","ipdsId":"IP-134432","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":404777,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":404775,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5064/images"},{"id":404774,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5064/sir20225064.XML"},{"id":404821,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20225065","text":"Scientific Investigations Report 2022–5065","linkHelpText":"—Status of water-level altitudes and long-term water-level changes in the Chicot and Evangeline (undifferentiated) and Jasper aquifers, greater Houston area, Texas, 2021"},{"id":404776,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9R6CX2T","text":"USGS data release","linkHelpText":"Depth to groundwater measured from wells completed in the Chicot and Evangeline (undifferentiated) and Jasper aquifers, greater Houston area, Texas, 2021"},{"id":404771,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5064/coverthb.jpg"},{"id":404772,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5064/sir20225064.pdf","text":"Report","size":"23.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022–5064"}],"country":"United States","state":"Texas","otherGeospatial":"Greater Houston area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.185302734375,\n 28.82061274169944\n ],\n [\n -94.757080078125,\n 28.82061274169944\n ],\n [\n -94.757080078125,\n 30.590637026892917\n ],\n [\n -96.185302734375,\n 30.590637026892917\n ],\n [\n -96.185302734375,\n 28.82061274169944\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oklahoma-Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754–4501
Channelized lava flows are commonly produced during the early stages of basaltic eruptions. These channels usually maintain their morphology until the eruption ends or discharge is diverted. In some instances, narrower channels can roof over, developing into lava tubes. We report here on a channelized flow erupted at Kīlauea volcano in 2007 that evolved into a “perched lava channel” composed of a string of interconnected, elongate lava pools, forming a lava channel/lava pool hybrid. The lava channel, which had a time-averaged discharge rate of ~3–9 m3/s, initially fed a series of flow branches that exhibited cooling-limited and volume-limited controls on flow length, sometimes with each process controlling a different morphological aspect of a single flow branch. The perched lava channel grew vertically primarily by overplating of the channel levees from frequent overflows, forming a compound flow field. This vertical growth only occurred when the distal end of the channel was blocked. When levee failure at the distal end of the channel caused the lava level in the channel to drop below the levee rim, no vertical growth occurred. Seeps of spiny lava and slabby pāhoehoe were common, erupting from uplift scarps on the channel levees, apparently fed by sills from denser, relatively crystal-rich material filling the bottom of the channel. We infer that lava in the channel was stratified in vesicularity and velocity, with foamy, vesicular, faster-moving lava at the top of the lava stream and denser, relatively outgassed, slower-moving lava filling the bottom of the channel. The channel levees were unstable, failing on several occasions, perhaps triggered by the levee seeps. The appearance of seeps, therefore, is one way of assessing the collapse potential of similar perched lava structures.
Today’s societal challenges, such as climate change and global pandemics, are increasingly complex and require collaboration across scientific disciplines to address. Scientific teams bring together individuals of varying backgrounds and expertise to work collaboratively on creating new knowledge to address these challenges. Within a scientific team, there is inherent diversity in disciplinary cultures and preferences for interpersonal collaboration. Such diversity contributes to the potential strength of the created knowledge but can also impede progress when teams struggle to collaborate productively. Facilitation is a professional practice-based form of interpersonal expertise that supports group members to do their best thinking. Although facilitation has been demonstrated to support group functioning in a wide range of contexts, its role in supporting scientific teams has been largely overlooked. This essay defines scientific facilitation as a form of interactional expertise and explains how facilitating scientific teams requires skills in managing interpersonal interactions as well as understanding how different types of disciplinary knowledge integrate in the creation of new knowledge. Next, it explains how this science facilitation expertise may be developed through metacognition. Finally, it provides examples of how scientific facilitation could be more widely incorporated into research by describing three pathways to expand the use of facilitation theory and techniques in collaborative scientific research: developing facilitation skills among scientists leading teams, using broadly trained facilitators, and using specialised science facilitators. The strengths and risks of each path are discussed, and criteria are suggested for selecting the right approach for a given team science project.
As marine ecosystems respond to climate change and other stressors, it is necessary to evaluate current and past hybridization events to gain insight on the outcomes and drivers of such events. Ancestral introgression within the gadids has been suggested to allow cod to inhabit a variety of habitats. Little attention has been given to contemporary hybridization, especially within cold-water-adapted cod (Boreogadus saida Lepechin, 1774 and Arctogadus glacialis Peters, 1872). We used whole-genome, restriction-site associated, and mitochondrial sequence data to explore the degree and direction of hybridization between these species where previous hybridization had not been reported. Although nearly identical morphologically at certain life stages, we detected very distinct nuclear and mitochondrial lineages. We detected one potential hybrid with a Arctogadus mitochondrial haplotype and Boreogadus nuclear genotype, but no early generational hybrids. The presence of a late generation hybrid suggests that at least some hybrids survive to maturity and reproduce. However, a historical introgression event could not be excluded. Contemporary gene flow appears asymmetrical from Arctogadus into Boreogadus, which may be due to overlap in timing of spawning, environmental heterogeneity, or differences in population size. This study provides important baseline information for the degree of potential hybridization between these species within Alaska marine environments.
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