The Black-necked Stilt (Himantopus mexicanus) is a migratory shorebird of temperate and tropical America. Declining wetland quality and associated declines in hydrological integrity may contribute to widespread habitat loss for stilts nesting on the upper Texas Gulf of Mexico coast of the USA, as both fresh and brackish marshes are converting to open water and saline marsh. Nests (n = 356) were monitored in three wetland types on the upper Texas coast from 21 April-30 June 2011-2012. Of these 356 nests, 151 were located in managed freshwater wetlands (16 in 2011 and 135 in 2012), 128 were located in managed intermediate wetlands (75 in 2011 and 53 in 2012), and 77 were located in rice fields (all in 2012). Collectively, nest success was 0.2% (0 in rice fields and as high as 4.3% in freshwater wetlands in 2012), among the lowest ever reported for the species. The most frequent cause of nest failure was predation by mammalian and avian predators (∼50%). Daily nest survival rate was positively related to mudflat nesting substrates and negatively related to colony size, rice field, and brackish coastal wetland habitats. Future efforts to minimize edge effects in managed wetlands may prove valuable to improve nest success of stilts and other species that nest in similar wetland types.
","language":"English","publisher":"The Waterbird Society","doi":"10.1675/063.042.0302","usgsCitation":"Riecke, T., Conway, W.C., Haukos, D.A., Moon, J.A., and Comer, C.E., 2019, Nest survival of Black-necked Stilts (Himantopus mexicanus) on the upper Texas coast, USA: Waterbirds, v. 42, no. 3, p. 261-271, https://doi.org/10.1675/063.042.0302.","productDescription":"11 p.","startPage":"261","endPage":"271","ipdsId":"IP-094016","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":396748,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","county":"Chambers County","otherGeospatial":"Anahuac National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.59709167480467,\n 29.561512529746743\n ],\n [\n -94.5703125,\n 29.570471069643638\n ],\n [\n -94.559326171875,\n 29.574054263095935\n ],\n [\n -94.54765319824219,\n 29.57106827738255\n ],\n [\n -94.5428466796875,\n 29.562707047643396\n ],\n [\n -94.53254699707031,\n 29.554942428835226\n ],\n [\n -94.52774047851562,\n 29.547774558769333\n ],\n [\n -94.52430725097656,\n 29.538216607905866\n ],\n [\n -94.49821472167969,\n 29.54419043309506\n ],\n [\n -94.49272155761719,\n 29.55076123308153\n ],\n [\n -94.47555541992188,\n 29.554942428835226\n ],\n [\n -94.46731567382812,\n 29.552553195302863\n ],\n [\n -94.45289611816406,\n 29.563304301294636\n ],\n [\n -94.42405700683594,\n 29.566290516578164\n ],\n [\n -94.41444396972656,\n 29.575248632655892\n ],\n [\n -94.41444396972656,\n 29.59375955382993\n ],\n [\n -94.39933776855469,\n 29.596147812456916\n ],\n [\n -94.38972473144531,\n 29.59435662378732\n ],\n [\n -94.37255859375,\n 29.6361427369564\n ],\n [\n -94.37461853027344,\n 29.6773149449586\n ],\n [\n -94.46868896484375,\n 29.67850809103362\n ],\n [\n -94.54421997070312,\n 29.660012735895606\n ],\n [\n -94.59846496582031,\n 29.676121784724305\n ],\n [\n -94.59709167480467,\n 29.561512529746743\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"42","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Riecke, Thomas V.","contributorId":171482,"corporation":false,"usgs":false,"family":"Riecke","given":"Thomas V.","affiliations":[],"preferred":false,"id":837061,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conway, Warren C.","contributorId":51550,"corporation":false,"usgs":true,"family":"Conway","given":"Warren","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":837060,"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":837062,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moon, Jena A.","contributorId":171483,"corporation":false,"usgs":false,"family":"Moon","given":"Jena","email":"","middleInitial":"A.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":837059,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Comer, Christopher E.","contributorId":166690,"corporation":false,"usgs":false,"family":"Comer","given":"Christopher","email":"","middleInitial":"E.","affiliations":[{"id":32360,"text":"Stephen F. Austin State University, Nacogdoches, TX","active":true,"usgs":false}],"preferred":false,"id":837058,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70210694,"text":"70210694 - 2019 - Detrital zircon geochronology along a structural transect across the Kahiltna assemblage in the western Alaska Range: Implications for emplacement of the Alexander-Wrangellia-Peninsular terrane against North America","interactions":[],"lastModifiedDate":"2023-11-03T16:04:37.674369","indexId":"70210694","displayToPublicDate":"2019-10-16T08:22:12","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Detrital zircon geochronology along a structural transect across the Kahiltna assemblage in the western Alaska Range: Implications for emplacement of the Alexander-Wrangellia-Peninsular terrane against North America","docAbstract":"The Kahiltna assemblage in the western Alaska Range consists of deformed Upper Jurassic and Cretaceous clastic strata that lie between the Alexander-Wrangellia-Peninsular (AWP) terrane to the south, and the Farewell and other peri-cratonic terranes to the north. Differences in detrital zircon populations and sandstone petrography allow geographic separation of the strata into two different successions, each consisting of multiple units, or petrofacies, with distinct provenance and lithologic characteristics. The northwestern succession was largely derived from older, inboard peri-cratonic terranes and correlates along strike to the southwest with the Kuskokwim Group. The southeastern succession is characterized by volcanic and plutonic rock detritus derived from Late Jurassic igneous rocks of the AWP terrane and mid to Late Cretaceous arc related igneous rocks and is part of a longer belt to the southwest and northeast, here named the Koksetna-Clearwater belt. The two successions remained separate depositional systems until the Late Cretaceous, when the northwestern succession overlapped the southeastern succession at about 81 Ma and they were deformed together by about 80 Ma by southeast-verging fold-and-thrust style deformation interpreted to represent final accretion of the AWP terrane along the southern Alaska margin. We interpret the tectonic evolution of the Kahiltna successions as a progression from forearc sedimentation and accretion in a south-facing continental magmatic arc to arrival and partial underthrusting of the backarc flank of an active, south-facing island arc system (AWP terrane). A modern analogue is the ongoing collision and partial underthrusting of the Izu-Bonin-Marianas island arc beneath the Japan Trench-Nankai Trough on the east side of central Japan.","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES02060.1","usgsCitation":"Box, S.E., Karl, S.M., Jones, J.V., Bradley, D., Haeussler, P., and O’Sullivan, P.B., 2019, Detrital zircon geochronology along a structural transect across the Kahiltna assemblage in the western Alaska Range: Implications for emplacement of the Alexander-Wrangellia-Peninsular terrane against North America: Geosphere, v. 15, no. 6, p. 1774-1808, https://doi.org/10.1130/GES02060.1.","productDescription":"35 p.","startPage":"1774","endPage":"1808","ipdsId":"IP-101587","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":459508,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges02060.1","text":"Publisher Index Page"},{"id":437306,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9JV5LM9","text":"USGS data release","linkHelpText":"U-Pb Isotopic Data and Ages of Titanite and Detrital Zircon from Selected Rocks from the Western Alaska Range, Alaska"},{"id":375663,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"western Alaska Range","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -154,\n 61\n ],\n [\n -150,\n 61\n ],\n [\n -150,\n 62.5\n ],\n [\n -154,\n 62.5\n ],\n [\n -154,\n 61\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","issue":"6","noUsgsAuthors":false,"publicationDate":"2019-10-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Box, Stephen E. 0000-0002-5268-8375 sbox@usgs.gov","orcid":"https://orcid.org/0000-0002-5268-8375","contributorId":1843,"corporation":false,"usgs":true,"family":"Box","given":"Stephen","email":"sbox@usgs.gov","middleInitial":"E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":790993,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Karl, Susan M. 0000-0003-1559-7826 skarl@usgs.gov","orcid":"https://orcid.org/0000-0003-1559-7826","contributorId":502,"corporation":false,"usgs":true,"family":"Karl","given":"Susan","email":"skarl@usgs.gov","middleInitial":"M.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":790994,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jones, James V. III 0000-0002-6602-5935 jvjones@usgs.gov","orcid":"https://orcid.org/0000-0002-6602-5935","contributorId":201245,"corporation":false,"usgs":true,"family":"Jones","given":"James","suffix":"III","email":"jvjones@usgs.gov","middleInitial":"V.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":790995,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bradley, Dwight 0000-0001-9116-5289 bradleyorchard2@gmail.com","orcid":"https://orcid.org/0000-0001-9116-5289","contributorId":2358,"corporation":false,"usgs":true,"family":"Bradley","given":"Dwight","email":"bradleyorchard2@gmail.com","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":790996,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Haeussler, Peter J. 0000-0002-1503-6247","orcid":"https://orcid.org/0000-0002-1503-6247","contributorId":219956,"corporation":false,"usgs":true,"family":"Haeussler","given":"Peter J.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":790997,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"O’Sullivan, Paul B.","contributorId":193544,"corporation":false,"usgs":false,"family":"O’Sullivan","given":"Paul","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":790998,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70227127,"text":"70227127 - 2019 - A mechanistic understanding of ecological responses to land-use change in headwater streams","interactions":[],"lastModifiedDate":"2021-12-30T14:08:03.519866","indexId":"70227127","displayToPublicDate":"2019-10-16T08:06:00","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"A mechanistic understanding of ecological responses to land-use change in headwater streams","docAbstract":"Anthropogenic activities, such as oil and natural gas development (ONGD), have significantly altered the landscape. It is often challenging to identify the mechanistic processes underlying ecological responses to land-use change (LUC). In aquatic ecosystems, alterations to habitat and food availability and water quality associated with increased LUC are key mechanistic pathways that deserve management consideration. We used structural equation modeling to evaluate how LUC associated with ONGD could influence macroinvertebrate and fish across 40 sites in six headwater streams in the Wyoming Range of the Upper Green River Basin, Wyoming. The most important mechanistic pathway varied, but responses were frequently driven by a direct effect of LUC or related to changes in food availability and water quality. Habitat complexity was the least important mechanistic pathway in our models. Our results also highlight that responses may reflect an organism's degree of habitat or resource specialization and/or sensitivity to changes in water quality. Habitat pathways were more important for habitat specialists (e.g., Mottled Sculpin, Cottus bairdii), food pathways were more important for food specialists (e.g., Colorado River Cutthroat Trout, Oncorhynchus clarki pleuriticus; Mountain Sucker, Catostomus platyrhynchus), and sensitivity to increased salinity was important for intolerant species (e.g., O. clarki, C. bairdii, and predatory macroinvertebrates). Continued identification of the specific mechanisms underlying species’ responses to increased LUC will aid in the conservation of ecologically and economically important species.
Director,
Arizona Water Science Center
U.S. Geological Survey
520 N. Park Avenue
Tucson, AZ 85719
Tumacácori National Historical Park (TUMA) in southern Arizona protects the culturally important Mission San José de Tumacácori, while also managing a part of the ecologically diverse riparian corridor of the Santa Cruz River. The quality of the water flowing through depends solely on upstream watershed activities, and among the water-quality issues concerning TUMA is the microbiological pathogens in the river introduced by human and animal sources that pose a significant human health risk to employees and visitors. The U.S. Geological Survey (USGS) conducted a 3-year study to understand the sources, timing, and distribution of the fecal-indicator bacteria Escherichia coli (E. coli) within TUMA and the upstream watershed.
The information provided in this investigation is a result of a comprehensive approach to quantify the spatial and temporal variability of E. coli and suspended sediment in the Upper Santa Cruz River Watershed. Several types of flow were sampled from base flow to flood flow and at high frequency intervals (rise, peak, and recession) to determine daily variability, as well as seasonal variability. Hydrologic data collection and estimation techniques were used to establish a hydrologic relation with E. coli and suspended sediment. Furthermore, source tracking was used to describe the potential sources of E. coli. Models were developed that are expected to be useful for predicting E. coli concentrations to help TUMA managers understand instantaneous conditions to keep the public and staff informed about potentially harmful water-quality conditions. In addition, the concentration, flux, and source information will provide more accurate data for other surface-water modeling and can be useful in the development of total maximum daily load standards. This will help TUMA describe the water-quality conditions at the park and waters flowing through the park, as well as prioritize and help carry out future best-management actions to address these issues.
Director,
Arizona Water Science Center
U.S. Geological Survey
520 N. Park Avenue
Tucson, AZ 85719
Floodplain systems in the Driftless Area have experienced widespread historical transformations in hydrologic and sediment characteristics as well as rates of hydrogeomorphic processes. These changes exceed natural variability experienced during the Holocene and are driven by nearly two centuries of major land-cover alterations coupled with shifting precipitation patterns. On the pre–Euro-American landscape, tributaries to the Upper Mississippi River had clear, constant base flow and low sedimentation rates due to a protective cover of prairie, oak savanna, and woodland. The Upper Mississippi River was sandy and braided, with geomorphologically diverse backwaters, side channels, and vegetated islands. Soil erosion and gullying caused by agriculture-related land clearance have had the largest historical effects on Upper Mississippi River tributary stream morphology and floodplain sedimentation. Floodplain sedimentation rates for tributaries and the Upper Mississippi River were 0.2 and 0.9 mm/yr, respectively, before Euro-American settlement, compared to 2–20 and 5–20 mm/yr after Euro-American settlement, respectively. The soil conservation movement had its birthplace in the Driftless Area in the 1920s because of the region’s widespread landscape degradation. As soil erosion decreased and gullies were stabilized in the middle to late twentieth century, land management efforts turned toward the lingering problem of fine-grained, phosphorus-rich sediment stored in tributary floodplains and channels. This trend has been complicated by a climatic shift in the late twentieth century toward increased annual precipitation, increased flood variability, and more floods in late fall and winter months, when bare fields are vulnerable to runoff. Floods are major contributors to channel erosion and deposition, and variability in magnitudes and frequency will likely continue in the early twenty-first century. Restoration efforts in tributaries have included reducing bank erosion, reconnecting floodplains, and adding trout habitat features. Lock and dam structures have altered sediment transport and erosion processes within the Upper Mississippi River, and restoration efforts there have focused on creation and rehabilitation of islands and protection of remnant off-channel backwater habitats.
Oyster reefs provide habitat for numerous fish and decapod crustacean species that mediate ecosystem functioning and support vibrant fisheries. Recent focus on the restoration of eastern oyster (Crassostrea virginica) reefs stems from this role as a critical ecosystem engineer. Within the shallow estuaries of the northern Gulf of Mexico (nGoM), the eastern oyster is the dominant reef building organism. This study synthesizes data on fish and decapod crustacean occupancy of oyster reefs across nGoM with the goal of providing management and restoration benchmarks, something that is currently lacking for the region. Relevant data from 23 studies were identified, representing data from all five U.S. nGoM states over the last 28 years. Cumulatively, these studies documented over 120,000 individuals from 115 fish and 41 decapod crustacean species. Densities as high as 2,800 ind m−2 were reported, with individual reef assemblages composed of as many as 52 species. Small, cryptic organisms that occupy interstitial spaces within the reefs, and sampled using trays, were found at an average density of 647 and 20 ind m−2 for decapod crustaceans and fishes, respectively. Both groups of organisms were comprised, on average, of 8 species. Larger-bodied fishes captured adjacent to the reef using gill nets were found at an average density of 6 ind m−2, which came from 23 species. Decapod crustaceans sampled with gill nets had a much lower average density, <1 ind m−2, and only contained 2 species. On average, seines captured the greatest number of fish species (n = 33), which were made up of both facultative residents and transients. These data provide general gear-specific benchmarks, based on values currently found in the region, to assist managers in assessing nekton occupancy of oyster reefs, and assessing trends or changes in status of oyster reef associated nekton support. More explicit reef descriptions (e.g., rugosity, height, area, adjacent habitat) would allow for more precise benchmarks as these factors are important in determining nekton assemblages, and sampling efficiency.
","language":"English","publisher":"Frontiers","doi":"10.3389/fmars.2019.00666","usgsCitation":"LaPeyre, M.K., Marshall, D., Miller, L.S., and Humphries, A.T., 2019, Oyster reefs in northern Gulf of Mexico estuaries harbor diverse fish and decapod crustacean assemblages: A meta-synthesis: Frontiers in Marine Science, v. 6, 666, 13 p., https://doi.org/10.3389/fmars.2019.00666.","productDescription":"666, 13 p.","ipdsId":"IP-108692","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":459521,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmars.2019.00666","text":"Publisher Index Page"},{"id":379387,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama, Georgia, Florida, Louisianan, Mississippi, Texas","otherGeospatial":"Northern Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.140625,\n 25.085598897064752\n ],\n [\n -79.27734374999999,\n 25.085598897064752\n ],\n [\n -79.27734374999999,\n 31.42866311735861\n ],\n [\n -99.140625,\n 31.42866311735861\n ],\n [\n -99.140625,\n 25.085598897064752\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"6","noUsgsAuthors":false,"publicationDate":"2019-10-25","publicationStatus":"PW","contributors":{"authors":[{"text":"LaPeyre, Megan K. 0000-0001-9936-2252 mlapeyre@usgs.gov","orcid":"https://orcid.org/0000-0001-9936-2252","contributorId":585,"corporation":false,"usgs":true,"family":"LaPeyre","given":"Megan","email":"mlapeyre@usgs.gov","middleInitial":"K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":801598,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Marshall, D. A.","contributorId":243135,"corporation":false,"usgs":false,"family":"Marshall","given":"D. A.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":801599,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, L. S.","contributorId":243136,"corporation":false,"usgs":false,"family":"Miller","given":"L.","email":"","middleInitial":"S.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":801600,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Humphries, A. T.","contributorId":243137,"corporation":false,"usgs":false,"family":"Humphries","given":"A.","email":"","middleInitial":"T.","affiliations":[{"id":6922,"text":"University of Rhode Island","active":true,"usgs":false}],"preferred":false,"id":801601,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70215278,"text":"70215278 - 2019 - Morphodynamic resilience of intertidal mudflats on a seasonal time scale","interactions":[],"lastModifiedDate":"2020-10-14T20:24:23.359312","indexId":"70215278","displayToPublicDate":"2019-10-14T14:55:28","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7159,"text":"JGR Oceans","active":true,"publicationSubtype":{"id":10}},"title":"Morphodynamic resilience of intertidal mudflats on a seasonal time scale","docAbstract":"Intertidal mudflats are morphodynamic features present in many estuaries worldwide. Often located between vegetated shores and deep channels they comprise valuable ecosystems and serve to protect the hinterland by attenuating waves. Although mudflats are persistently present on yearly to decadal time scales, little is known on their morphodynamic adaptation to short‐term variations in forcing such as storms, spring‐neap tidal cycles, and sediment supply. This study aims to explore the morphodynamic resilience of mudflats to seasonal variations in forcing. First, we compare transects observed in South Bay, California, at 3‐ to 6‐monthly intervals. Second, we present the results of a process‐based, morphodynamic profile model (Mflat). Mflat is an open source, Matlab code that describes both cross‐shore and alongshore tidal hydrodynamics as well as a stationary wave model. An advection‐diffusion equation solves sediment transport while bed level changes occur by the divergence of the sediment transport field. Mflat reproduces the observed South San Francisco Bay profile in equilibrium with significant skill. Short‐term variations in hydrodynamic forcing and sediment characteristics disturb the profile mainly at the channel‐shoal edge. The modeled profile disturbance is consistent with observations. The modeled profile is remarkably resilient since it recovers to the equilibrium profile within weeks to months. The model results suggest that 3‐monthly observation intervals are probably too long to discriminate processes responsible for the profile disturbance. These processes may include variations in sediment supply, mudflat erodibility, and wave action as well as the spring‐neap tidal cycle.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019JC015492","usgsCitation":"Van der Wegen, M., Roelvink, D., and Jaffe, B.E., 2019, Morphodynamic resilience of intertidal mudflats on a seasonal time scale: JGR Oceans, v. 124, no. 11, p. 8290-8308, https://doi.org/10.1029/2019JC015492.","productDescription":"19 p.","startPage":"8290","endPage":"8308","ipdsId":"IP-110231","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":459523,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1029/2019jc015492","text":"External Repository"},{"id":379385,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.958984375,\n 37.125286284966805\n ],\n [\n -121.37695312499999,\n 37.125286284966805\n ],\n [\n -121.37695312499999,\n 38.30718056188316\n ],\n [\n -122.958984375,\n 38.30718056188316\n ],\n [\n -122.958984375,\n 37.125286284966805\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"124","issue":"11","noUsgsAuthors":false,"publicationDate":"2019-11-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Van der Wegen, Mick","contributorId":191095,"corporation":false,"usgs":false,"family":"Van der Wegen","given":"Mick","email":"","affiliations":[],"preferred":false,"id":801446,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roelvink, Dano","contributorId":139950,"corporation":false,"usgs":false,"family":"Roelvink","given":"Dano","email":"","affiliations":[{"id":13328,"text":"UNESCO-IHE","active":true,"usgs":false}],"preferred":false,"id":801447,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jaffe, Bruce E. 0000-0002-8816-5920 bjaffe@usgs.gov","orcid":"https://orcid.org/0000-0002-8816-5920","contributorId":2049,"corporation":false,"usgs":true,"family":"Jaffe","given":"Bruce","email":"bjaffe@usgs.gov","middleInitial":"E.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":801448,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70215282,"text":"70215282 - 2019 - Holocene Sea-Level Variability from Chesapeake Bay Tidal Marshes","interactions":[],"lastModifiedDate":"2020-10-14T19:46:59.518365","indexId":"70215282","displayToPublicDate":"2019-10-14T14:35:08","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1905,"text":"Holocene","active":true,"publicationSubtype":{"id":10}},"title":"Holocene Sea-Level Variability from Chesapeake Bay Tidal Marshes","docAbstract":"We reconstructed the last 10,000 years of Holocene relative sea-level rise (RSLR) from sediment core records in near Chesapeake Bay, eastern U.S.A., including new marsh records from the Potomac and Rappahannock Rivers, Virginia. Results show mean RSLR rates of 2.6 mm yr-1 from 10 to 8 kilo-annum (ka) due to combined final ice-sheet melting during deglaciation and glacio-isostatic adjustment (GIA subsidence). Mean RSLR rates from ~6 ka to present were 1.4 mm yr-1 due mainly to GIA, consistent with other east coast marsh records and geophysical models. However, a progressively slower mean rate (< 1.0 mm yr-1) characterized the last 1000 years when a multi-century-long period of tidal marsh development occurred during the Medieval Climate Anomaly (MCA) and Little Ice Age (LIA) in the Chesapeake Bay region and other East Coast marshes. This decrease was most likely due to climatic and glaciological processes and, correcting for GIA, represents a fall in global mean sea level (GMSL) at near the end of Holocene Neoglacial cooling. These pre-historical climate- and GIA-driven Chesapeake Bay sea-level changes contrast sharply with those based on Chesapeake Bay tide-gauge rates (3.1-4.5 mm yr-1) (back to 1903). After subtracting the GIA subsidence component, these rates can be attributed to long-term (millennial) global factors of accelerated ocean thermal expansion (~ 1.0 mm yr-1) and mass loss from alpine glaciers and Greenland and Antarctic Ice Sheets (1.5-2.0 mm yr-1).","language":"English","publisher":"SAGE Publications","doi":"10.1177/0959683619862028","usgsCitation":"Cronin, T.M., Clevenger, M.K., Tibert, N.E., Prescott, T., Toomey, M., Hubeny, J.B., Abbott, M.B., Seidenstein, J., Whitworth, H., Fisher, S., Wondolowski, N., and Ruefer, A., 2019, Holocene Sea-Level Variability from Chesapeake Bay Tidal Marshes: Holocene, v. 29, no. 11, p. 1979-1693, https://doi.org/10.1177/0959683619862028.","productDescription":"15 p.","startPage":"1979","endPage":"1693","ipdsId":"IP-102993","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":459524,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1177/0959683619862028","text":"Publisher Index Page"},{"id":379383,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, Maryland, Virginia","otherGeospatial":"Chesapeake Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.6845703125,\n 36.88401445049676\n ],\n [\n -75.7562255859375,\n 36.88401445049676\n ],\n [\n -75.7562255859375,\n 39.06184913429154\n ],\n [\n -76.6845703125,\n 39.06184913429154\n ],\n [\n -76.6845703125,\n 36.88401445049676\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"29","issue":"11","noUsgsAuthors":false,"publicationDate":"2019-07-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Cronin, Thomas M. 0000-0002-2643-0979 tcronin@usgs.gov","orcid":"https://orcid.org/0000-0002-2643-0979","contributorId":2579,"corporation":false,"usgs":true,"family":"Cronin","given":"Thomas","email":"tcronin@usgs.gov","middleInitial":"M.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":801637,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clevenger, Megan K.","contributorId":243159,"corporation":false,"usgs":false,"family":"Clevenger","given":"Megan","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":801638,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tibert, Neil E.","contributorId":243160,"corporation":false,"usgs":false,"family":"Tibert","given":"Neil","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":801639,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Prescott, Tammy","contributorId":243161,"corporation":false,"usgs":false,"family":"Prescott","given":"Tammy","email":"","affiliations":[],"preferred":false,"id":801640,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Toomey, Michael 0000-0003-0167-9273 mtoomey@usgs.gov","orcid":"https://orcid.org/0000-0003-0167-9273","contributorId":184097,"corporation":false,"usgs":true,"family":"Toomey","given":"Michael","email":"mtoomey@usgs.gov","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":801641,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hubeny, J. Bradford","contributorId":197080,"corporation":false,"usgs":false,"family":"Hubeny","given":"J.","email":"","middleInitial":"Bradford","affiliations":[],"preferred":false,"id":801642,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Abbott, Mark B.","contributorId":97733,"corporation":false,"usgs":true,"family":"Abbott","given":"Mark","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":801643,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Seidenstein, Julia","contributorId":243162,"corporation":false,"usgs":false,"family":"Seidenstein","given":"Julia","affiliations":[],"preferred":false,"id":801644,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Whitworth, Hannah","contributorId":243163,"corporation":false,"usgs":false,"family":"Whitworth","given":"Hannah","email":"","affiliations":[],"preferred":false,"id":801645,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Fisher, Samuel R","contributorId":225265,"corporation":false,"usgs":false,"family":"Fisher","given":"Samuel R","affiliations":[{"id":41086,"text":"La Sierra University","active":true,"usgs":false}],"preferred":false,"id":801646,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Wondolowski, Nick","contributorId":243164,"corporation":false,"usgs":false,"family":"Wondolowski","given":"Nick","email":"","affiliations":[],"preferred":false,"id":801647,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Ruefer, Anna","contributorId":243165,"corporation":false,"usgs":false,"family":"Ruefer","given":"Anna","email":"","affiliations":[],"preferred":false,"id":801648,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70215273,"text":"70215273 - 2019 - River water-quality concentration and flux estimation can be improved by accounting for serial correlation through an autoregressive model","interactions":[],"lastModifiedDate":"2020-10-15T13:33:08.421308","indexId":"70215273","displayToPublicDate":"2019-10-14T14:25:04","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"River water-quality concentration and flux estimation can be improved by accounting for serial correlation through an autoregressive model","docAbstract":"Accurate quantification of riverine water‐quality concentration and flux is challenging because monitoring programs typically collect concentration data at lower frequencies than discharge data. Statistical methods are often used to estimate concentration and flux on days without observations. One recently developed approach is the Weighted Regressions on Time, Discharge, and Season (WRTDS), which has been shown to provide among the most accurate estimates compared to other common methods. The main objective of this work was to improve WRTDS estimation by accounting for the autocorrelation structure of model residuals using the first‐order autoregressive model (AR1). This modified approach, called WRTDS‐Kalman Filter (WRTDS‐K), was compared with WRTDS for six constituents including nitrate‐plus‐nitrite (NOx), total phosphorus, total Kjeldahl nitrogen, soluble reactive phosphorus, suspended sediment, and chloride. Near‐daily concentration records at nine sites were used to generate subsets through Monte Carlo sampling for five different sampling scenarios. Results show that WRTDS‐K provided generally better daily estimates of concentration and flux than WRTDS under these sampling scenarios for all constituents, especially NOx. The degree of improvement is strongly affected by the underlying sampling scenario, with WRTDS‐K gaining more advantage when more samples are available, and hence more residuals can be exploited. The performance of WRTDS‐K depends on the AR1 coefficient (ρ) and that relationship varies with constituents and sampling scenarios. These results provided recommendations on the optimal ρ for each constituent and sampling scenario. Overall, WRTDS‐K has the potential for broad applications to monitoring records elsewhere, as demonstrated by a pilot application to Chesapeake Bay tributaries.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019wr025338","usgsCitation":"Zhang, Q., and Hirsch, R.M., 2019, River water-quality concentration and flux estimation can be improved by accounting for serial correlation through an autoregressive model: Water Resources Research, v. 55, no. 11, p. 9705-9723, https://doi.org/10.1029/2019wr025338.","productDescription":"19 p.","startPage":"9705","endPage":"9723","ipdsId":"IP-110106","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":488944,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2019wr025338","text":"Publisher Index Page"},{"id":379382,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Ohio","otherGeospatial":"Lake Erie and Ohio River tributaries","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.7705078125,\n 40.58058466412761\n ],\n [\n -84.48486328124999,\n 40.01078714046552\n ],\n [\n -83.9794921875,\n 39.53793974517628\n ],\n [\n -83.3642578125,\n 39.90973623453719\n ],\n [\n -82.72705078125,\n 39.2832938689385\n ],\n [\n -82.37548828125,\n 41.04621681452063\n ],\n [\n -83.408203125,\n 40.896905775860006\n ],\n [\n -83.84765625,\n 41.178653972331674\n ],\n [\n -83.7158203125,\n 41.82045509614034\n ],\n [\n -84.3310546875,\n 41.918628865183045\n ],\n [\n -84.6826171875,\n 41.393294288784865\n ],\n [\n -85.1220703125,\n 41.16211393939692\n ],\n [\n -85.0341796875,\n 40.54720023441049\n ],\n [\n -84.7705078125,\n 40.58058466412761\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.9912109375,\n 41.72213058512578\n ],\n [\n -81.36474609375,\n 41.343824581185686\n ],\n [\n -81.82617187499999,\n 41.19518982948959\n ],\n [\n -81.5185546875,\n 40.93011520598305\n ],\n [\n -80.96923828125,\n 41.04621681452063\n ],\n [\n -80.6396484375,\n 41.45919537950706\n ],\n [\n -80.6396484375,\n 41.78769700539063\n ],\n [\n -80.9912109375,\n 41.72213058512578\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"55","issue":"11","noUsgsAuthors":false,"publicationDate":"2019-11-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Zhang, Qian 0000-0003-0500-5655","orcid":"https://orcid.org/0000-0003-0500-5655","contributorId":174393,"corporation":false,"usgs":false,"family":"Zhang","given":"Qian","email":"","affiliations":[{"id":38802,"text":"University of Maryland Center for Environmental Studies","active":true,"usgs":false}],"preferred":false,"id":801435,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hirsch, Robert M. 0000-0002-4534-075X rhirsch@usgs.gov","orcid":"https://orcid.org/0000-0002-4534-075X","contributorId":2005,"corporation":false,"usgs":true,"family":"Hirsch","given":"Robert","email":"rhirsch@usgs.gov","middleInitial":"M.","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":801436,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70218246,"text":"70218246 - 2019 - Infrasound from giant bubbles during explosive submarine eruptions","interactions":[],"lastModifiedDate":"2021-02-19T20:15:54.51462","indexId":"70218246","displayToPublicDate":"2019-10-14T14:11:45","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2845,"text":"Nature Geoscience","active":true,"publicationSubtype":{"id":10}},"title":"Infrasound from giant bubbles during explosive submarine eruptions","docAbstract":"Shallow submarine volcanoes pose unique scientific and monitoring challenges. The interaction between water and magma can create violent explosions just below the surface, but the inaccessibility of submerged volcanoes means they are typically not instrumented. This both increases the risk to marine and aviation traffic and leaves the underlying eruption physics poorly understood. Here we use low-frequency sound in the atmosphere (infrasound) to examine the source mechanics of shallow submarine explosions from Bogoslof volcano, Alaska. We show that the infrasound originates from the oscillation and rupture of magmatic gas bubbles that initially formed from submerged vents, but that grew and burst above sea level. We model the low-frequency signals as overpressurized gas bubbles that grow near the water–air interface, which require bubble radii of 50–220 m. Bubbles of this size and larger have been described in explosive subaqueous eruptions for more than a century, but we present a unique geophysical record of this phenomenon. We propose that the dominant role of seawater during the effusion of gas-rich magma into shallow water is to repeatedly produce a gas-tight seal near the vent. This resealing mechanism leads to sequences of violent explosions and the release of large, bubble-forming volumes of gas—activity we describe as hydrovulcanian.
","language":"English","publisher":"Nature Publications","doi":"10.1038/s41561-019-0461-0","usgsCitation":"Lyons, J.J., Haney, M.M., Fee, D., Wech, A., and Waythomas, C.F., 2019, Infrasound from giant bubbles during explosive submarine eruptions: Nature Geoscience, v. 12, p. 952-958, https://doi.org/10.1038/s41561-019-0461-0.","productDescription":"7 p.","startPage":"952","endPage":"958","ipdsId":"IP-104588","costCenters":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":383394,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Bogoslof volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -168.78295898437497,\n 53.1928702436326\n ],\n [\n -166.1737060546875,\n 53.1928702436326\n ],\n [\n -166.1737060546875,\n 54.08517342088679\n ],\n [\n -168.78295898437497,\n 54.08517342088679\n ],\n [\n -168.78295898437497,\n 53.1928702436326\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","noUsgsAuthors":false,"publicationDate":"2019-10-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Lyons, John J. 0000-0001-5409-1698 jlyons@usgs.gov","orcid":"https://orcid.org/0000-0001-5409-1698","contributorId":5394,"corporation":false,"usgs":true,"family":"Lyons","given":"John","email":"jlyons@usgs.gov","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":810690,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haney, Matthew M. 0000-0003-3317-7884 mhaney@usgs.gov","orcid":"https://orcid.org/0000-0003-3317-7884","contributorId":172948,"corporation":false,"usgs":true,"family":"Haney","given":"Matthew","email":"mhaney@usgs.gov","middleInitial":"M.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":810691,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fee, David","contributorId":251816,"corporation":false,"usgs":false,"family":"Fee","given":"David","affiliations":[{"id":6695,"text":"UAF","active":true,"usgs":false}],"preferred":false,"id":810692,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wech, Aaron 0000-0003-4983-1991","orcid":"https://orcid.org/0000-0003-4983-1991","contributorId":202561,"corporation":false,"usgs":true,"family":"Wech","given":"Aaron","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":810693,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Waythomas, Christopher F. 0000-0002-3898-272X cwaythomas@usgs.gov","orcid":"https://orcid.org/0000-0002-3898-272X","contributorId":640,"corporation":false,"usgs":true,"family":"Waythomas","given":"Christopher","email":"cwaythomas@usgs.gov","middleInitial":"F.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":810694,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70215283,"text":"70215283 - 2019 - Riverine turtles select habitats maintained by natural discharge regimes in an unimpounded large river","interactions":[],"lastModifiedDate":"2020-10-16T11:57:01.515094","indexId":"70215283","displayToPublicDate":"2019-10-14T14:04:23","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Riverine turtles select habitats maintained by natural discharge regimes in an unimpounded large river","docAbstract":"Turtle populations are imperiled worldwide, but limited ecological information from unaltered systems hampers science‐based management and conservation of some species, especially riverine turtles such as the spiny softshell (Apalone spinifera). We therefore investigated movements and spatial habitat selection of 54 A. spinifera in 633 river kilometres (rkm) of the least‐altered river in the conterminous United States—the Yellowstone River in Montana—from 2005 to 2009. Movement rates and home ranges were smaller than in fragmented, altered river systems because nesting and overwintering habitats were common and in close proximity. Habitat selection also differed. A. spinifera in the Yellowstone River overwintered in unaltered bluff pools and summered in complex reaches with side channels, islands, and diverse habitats. However, those in the highly altered Missouri River used deep alluvial pools for overwintering and flooded, inundated, or backwatered tributary mouths in spring and summer. Importantly, selected habitats in both rivers were functionally similar, including complex river reaches (with multiple channels, islands, and diverse habitats) and natural pool types. Unfortunately, these are the very habitats that are limited in rivers affected by dams, bank stabilization, and channelization. Therefore, preservation of natural and diverse riverine habitats—and the fluvial dynamics that maintain them—may enhance conservation of A. spinifera in large rivers.
Recent warming in the Arctic, which has been amplified during the winter1,2,3, greatly enhances microbial decomposition of soil organic matter and subsequent release of carbon dioxide (CO2)4. However, the amount of CO2 released in winter is not known and has not been well represented by ecosystem models or empirically based estimates5,6. Here we synthesize regional in situ observations of CO2 flux from Arctic and boreal soils to assess current and future winter carbon losses from the northern permafrost domain. We estimate a contemporary loss of 1,662 TgC per year from the permafrost region during the winter season (October–April). This loss is greater than the average growing season carbon uptake for this region estimated from process models (−1,032 TgC per year). Extending model predictions to warmer conditions up to 2100 indicates that winter CO2 emissions will increase 17% under a moderate mitigation scenario—Representative Concentration Pathway 4.5—and 41% under business-as-usual emissions scenario—Representative Concentration Pathway 8.5. Our results provide a baseline for winter CO2 emissions from northern terrestrial regions and indicate that enhanced soil CO2 loss due to winter warming may offset growing season carbon uptake under future climatic conditions.
","language":"English","publisher":"Nature Publishing Group","doi":"10.1038/s41558-019-0592-8","usgsCitation":"Natali, S.M., Watts, J.D., Potter, S., Rogers, B.M., Ludwig, S.M., Selbmann, A., Sullivan, P., Abbott, B., Arndt, K.A., Birch, L., Bjorkman, M., Bloom, A., Celis, G., Christiensen, T.R., Christiansen, C.T., Commane, R., Cooper, E.J., Crill, P., Czimczik, C., Davydov, S., Du, J., Egan, J.E., Elberling, B., Euskirchen, E.S., Friborg, T., Genet, H., Gockede, M., Goodrich, J.P., Grogan, P., Helbig, M., Jafarov, E.E., Jastrow, J., Kalhori, A., Kim, Y., Kimball, J., Kutzbach, L., Lara, M.J., Larsen, K.S., Loranty, M., Lund, M., Lupascu, M., Madani, N., Malhorta, A., McFarland, J., McGuire, D.A., Michelson, A., Minions, C., Oechel, W.C., Olefeldt, D., Parmentier, F., Pirk, N., Poulter, B., Quinton, W.L., Rezanezhad, F., Risk, D., Sachs, T., Schaefer, K., Schmidt, N.M., Schuur, E.A., Semenchuk, P.R., Shaver, G., Sonnentag, O., Starr, G., Treat, C.C., Waldrop, M.P., Wang, Y., Welker, J., Wille, C., Xu, X., Zhang, Z., Zhuang, Q., and Zona, D., 2019, Large loss of CO2 in winter observed across pan-arctic permafrost region: Nature Climate Change, v. 9, p. 852-857, https://doi.org/10.1038/s41558-019-0592-8.","productDescription":"6 p.","startPage":"852","endPage":"857","ipdsId":"IP-102596","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":459531,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/11250/2649468","text":"External Repository"},{"id":379379,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Antartica","otherGeospatial":"northern permafrost region","volume":"9","noUsgsAuthors":false,"publicationDate":"2019-10-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Natali, 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Qianlai","contributorId":207137,"corporation":false,"usgs":false,"family":"Zhuang","given":"Qianlai","email":"","affiliations":[{"id":13186,"text":"Purdue University","active":true,"usgs":false}],"preferred":false,"id":801596,"contributorType":{"id":1,"text":"Authors"},"rank":71},{"text":"Zona, Donatella","contributorId":217433,"corporation":false,"usgs":false,"family":"Zona","given":"Donatella","email":"","affiliations":[{"id":6608,"text":"San Diego State University","active":true,"usgs":false}],"preferred":false,"id":801597,"contributorType":{"id":1,"text":"Authors"},"rank":72}]}} ,{"id":70215285,"text":"70215285 - 2019 - Records of engagement and decision making for environmental and socio-ecological challenges","interactions":[],"lastModifiedDate":"2020-10-16T11:58:31.72146","indexId":"70215285","displayToPublicDate":"2019-10-14T13:16:26","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7160,"text":"EURO Journal on Decision Processes","active":true,"publicationSubtype":{"id":10}},"title":"Records of engagement and decision making for environmental and socio-ecological challenges","docAbstract":"We propose creating and maintaining records of engagement and decision-making (RoED) to help us and our communities better understand ourselves, our goals, our decisions, and the dynamic systems in which we all live. The purpose of RoED is to go well beyond noting that dialogue occurred or a decision was reached. The records should, in ways appropriate to the context and participants, document interactions and note biases, beliefs, emotions, behaviors, norms, and values. These crucial aspects are generally absent in academic papers and formal reports, yet they always play a role in decision-making processes. While not a panacea for addressing critical biophysical and social challenges, we propose that a comprehensive framework for promoting realistic, legitimate and inclusive engagement could enhance trust, establish institutional memory, and when and where appropriate, ensure greater transparency. The aim is to create and maintain RoED to collect significant information and share insights from multi-stakeholder decision-making processes from diverse institutions, contexts, and disciplinary domains. In the long-term RoED could promote more effective adaptive management or governance approaches. This paper describes an exploratory phase intended to catalyze collaborative efforts worldwide.
We examine the annual, seasonal, monthly, and diurnal climate responses to the land use change (LUC) in eastern United States and Cuba during four epochs (1650, 1850, 1920, and 1992) with ensemble simulations conducted with the RegCM4 regional climate model that includes the Biosphere Atmosphere Transfer Scheme (BATS1e) surface physics package (Dickinson et al., 1993). We derived the land use (LU) data sets by harmonizing a previous reconstruction (Steyaert & Knox, 2008) with updated observations and modeled potential vegetation. The eight‐member ensembles for each epoch were driven with randomly perturbed 1990–2002 atmospheric boundary conditions derived from the National Center for Environmental Prediction global reanalysis. LUC induces statistically significant climate responses across all epochs; the largest changes occur between 1850 and 1920 with the widespread conversion of forests in the United States and forests, grassland, and woody wetlands in Cuba to agriculture. The atmospheric feedback from the aggregated grid‐cell responses attributed to physical and biophysical parameters in BATS1e alters the circulation in the lower atmosphere, thereby propagating the LUC regionally. Depending on the season and location, the altered circulation reinforces, attenuates, or has little effect on surface responses. Relative to pre‐settlement (1650), the 1992 LU produces colder mean annual air temperature (−0.09 ± 0.16 °C) and increased precipitation (0.08 ± 0.09 mm day−1) over the United States, warmer (0.08 °C) and wetter (0.03 mm day−1) conditions over Florida, and warming (0.32 °C) and drying (−0.03 mm day−1) over Cuba, indicating that LUC has played a varying role in climate change over the region.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019jd030965","usgsCitation":"Hostetler, S.W., Reker, R., Alder, J.R., Loveland, T., Willard, D.A., Bernhardt, C.E., Sundquist, E.T., and Thompson, R., 2019, Application of a regional climate model to assess changes in the climatology of the Eastern US and Cuba associated with historic landcover change: JGR Atmospheres, v. 124, no. 22, p. 11722-11745, https://doi.org/10.1029/2019jd030965.","productDescription":"24 p.","startPage":"11722","endPage":"11745","ipdsId":"IP-106240","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":379374,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States, Cuba","state":"Florida","otherGeospatial":"Eastern United States, Cuba","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.603515625,\n 29.916852233070173\n ],\n [\n -92.98828125,\n 29.152161283318915\n ],\n [\n -89.736328125,\n 29.305561325527698\n ],\n [\n -87.5390625,\n 30.29701788337205\n ],\n [\n -84.19921875,\n 29.6880527498568\n ],\n [\n -82.177734375,\n 25.562265014427492\n ],\n [\n -80.5078125,\n 24.926294766395593\n ],\n [\n -79.62890625,\n 25.958044673317843\n ],\n [\n -81.38671875,\n 29.22889003019423\n ],\n [\n -81.123046875,\n 31.80289258670676\n ],\n [\n -75.9375,\n 35.96022296929667\n ],\n [\n -75.76171875,\n 37.50972584293751\n ],\n [\n -73.740234375,\n 39.50404070558415\n ],\n [\n -74.8828125,\n 41.705728515237524\n ],\n [\n -80.419921875,\n 41.96765920367816\n ],\n [\n -87.5390625,\n 41.64007838467894\n ],\n [\n -91.49414062499999,\n 40.51379915504413\n ],\n [\n -95.625,\n 40.64730356252251\n ],\n [\n -94.21875,\n 36.31512514748051\n ],\n [\n -94.306640625,\n 33.797408767572485\n ],\n [\n -93.603515625,\n 29.916852233070173\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.55078125,\n 21.861498734372567\n ],\n [\n -77.51953125,\n 19.476950206488414\n ],\n [\n -74.1796875,\n 19.559790136497412\n ],\n [\n -73.916015625,\n 21.289374355860424\n ],\n [\n -82.44140625,\n 24.126701958681668\n ],\n [\n -84.814453125,\n 22.998851594142913\n ],\n [\n -84.55078125,\n 21.861498734372567\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"124","issue":"22","noUsgsAuthors":false,"publicationDate":"2019-11-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Hostetler, Steven W. 0000-0003-2272-8302 swhostet@usgs.gov","orcid":"https://orcid.org/0000-0003-2272-8302","contributorId":3249,"corporation":false,"usgs":true,"family":"Hostetler","given":"Steven","email":"swhostet@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":801375,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reker, R 0000-0001-7524-0082","orcid":"https://orcid.org/0000-0001-7524-0082","contributorId":243028,"corporation":false,"usgs":false,"family":"Reker","given":"R","affiliations":[{"id":48618,"text":"ASRC Federal InuTeq, EROS","active":true,"usgs":false}],"preferred":false,"id":801376,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Alder, Jay R. 0000-0003-2378-2853 jalder@usgs.gov","orcid":"https://orcid.org/0000-0003-2378-2853","contributorId":5118,"corporation":false,"usgs":true,"family":"Alder","given":"Jay","email":"jalder@usgs.gov","middleInitial":"R.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":801377,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Loveland, Thomas 0000-0003-3114-6646 loveland@usgs.gov","orcid":"https://orcid.org/0000-0003-3114-6646","contributorId":140611,"corporation":false,"usgs":true,"family":"Loveland","given":"Thomas","email":"loveland@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":801378,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Willard, Debra A. 0000-0003-4878-0942 dwillard@usgs.gov","orcid":"https://orcid.org/0000-0003-4878-0942","contributorId":2076,"corporation":false,"usgs":true,"family":"Willard","given":"Debra","email":"dwillard@usgs.gov","middleInitial":"A.","affiliations":[{"id":24693,"text":"Climate Research and Development","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":801634,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bernhardt, Christopher E. 0000-0003-0082-4731 cbernhardt@usgs.gov","orcid":"https://orcid.org/0000-0003-0082-4731","contributorId":2131,"corporation":false,"usgs":true,"family":"Bernhardt","given":"Christopher","email":"cbernhardt@usgs.gov","middleInitial":"E.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":801635,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sundquist, Eric T. 0000-0002-1449-8802 esundqui@usgs.gov","orcid":"https://orcid.org/0000-0002-1449-8802","contributorId":1922,"corporation":false,"usgs":true,"family":"Sundquist","given":"Eric","email":"esundqui@usgs.gov","middleInitial":"T.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":801380,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Thompson, Renee L. rthompson1@usgs.gov","contributorId":2933,"corporation":false,"usgs":true,"family":"Thompson","given":"Renee L.","email":"rthompson1@usgs.gov","affiliations":[],"preferred":true,"id":801636,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70215263,"text":"70215263 - 2019 - Dynamically triggered changes of plate interface coupling in Southern Cascadia","interactions":[],"lastModifiedDate":"2020-10-15T13:51:33.558951","indexId":"70215263","displayToPublicDate":"2019-10-14T11:47:45","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Dynamically triggered changes of plate interface coupling in Southern Cascadia","docAbstract":"In Southern Cascadia, precise Global Navigation Satellite System (GNSS) measurements spanning about 15 years reveal steady deformation due to locking on the Cascadia megathrust punctuated by transient deformation from large earthquakes and episodic tremor and slip events. Near the Mendocino Triple Junction, however, we recognize several abrupt GNSS velocity changes that reflect a different process. After correcting for earthquakes and seasonal loading, we find that several dozen GNSS time series show spatially coherent east‐west velocity changes of ~2 mm/yr and that these changes coincide in time with regional M > 6.5 earthquakes. We consider several hypotheses and propose that dynamically triggered changes in megathrust coupling best explain the data. Our inversions locate the coupling changes slightly updip of the tremor‐producing zone. We speculate that fluid exchange surrounding the tremor region may be important. Such observations of transient coupling changes are rare and challenging to explain mechanistically but have important implications for earthquake processes on faults.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019gl084395","usgsCitation":"Materna, K.Z., Bartlow, N., Wech, A., Williams, C., and Burgmann, R., 2019, Dynamically triggered changes of plate interface coupling in Southern Cascadia: Geophysical Research Letters, v. 46, no. 22, p. 12890-12899, https://doi.org/10.1029/2019gl084395.","productDescription":"10 p.","startPage":"12890","endPage":"12899","ipdsId":"IP-108740","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":459536,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2019gl084395","text":"Publisher Index Page"},{"id":379373,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Southern Cascadia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -126.0791015625,\n 39.45316112807394\n ],\n [\n -123.22265625000001,\n 39.45316112807394\n ],\n [\n -123.22265625000001,\n 42.00032514831621\n ],\n [\n -126.0791015625,\n 42.00032514831621\n ],\n [\n -126.0791015625,\n 39.45316112807394\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"46","issue":"22","noUsgsAuthors":false,"publicationDate":"2019-11-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Materna, Kathryn Z. 0000-0002-6687-980X","orcid":"https://orcid.org/0000-0002-6687-980X","contributorId":209697,"corporation":false,"usgs":false,"family":"Materna","given":"Kathryn","middleInitial":"Z.","affiliations":[{"id":13693,"text":"University of Colorado Boulder","active":true,"usgs":false}],"preferred":false,"id":801370,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bartlow, Noel 0000-0002-9961-5608","orcid":"https://orcid.org/0000-0002-9961-5608","contributorId":242895,"corporation":false,"usgs":false,"family":"Bartlow","given":"Noel","email":"","affiliations":[{"id":6773,"text":"University of Kansas","active":true,"usgs":false}],"preferred":false,"id":801371,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wech, Aaron 0000-0003-4983-1991","orcid":"https://orcid.org/0000-0003-4983-1991","contributorId":202561,"corporation":false,"usgs":true,"family":"Wech","given":"Aaron","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":801372,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Williams, Charles 0000-0001-7435-9196","orcid":"https://orcid.org/0000-0001-7435-9196","contributorId":243027,"corporation":false,"usgs":false,"family":"Williams","given":"Charles","email":"","affiliations":[{"id":36277,"text":"GNS Science","active":true,"usgs":false}],"preferred":false,"id":801373,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Burgmann, Roland","contributorId":192700,"corporation":false,"usgs":false,"family":"Burgmann","given":"Roland","affiliations":[],"preferred":false,"id":801374,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70206024,"text":"70206024 - 2019 - Quantifying source and sink habitats and pathways in spatially structured populations: A generalized modelling approach","interactions":[],"lastModifiedDate":"2019-10-18T06:31:20","indexId":"70206024","displayToPublicDate":"2019-10-14T11:24:15","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying source and sink habitats and pathways in spatially structured populations: A generalized modelling approach","docAbstract":"The ability to classify habitats and movement pathways as sources or sinks is an important part of the decision making process for the conservation of spatially structured populations. Diverse approaches have been used to quantify the importance of habitats and pathways in a spatial network, however these approaches have been limited by a lack of general applicability across life histories and movement strategies. In this paper we develop a generalized per-capita\ncontribution metric, the C-metric, for quantifying habitat and pathway quality. This metric is novel in that it can be applied broadly to both metapopulations and migratory species. It allows for any number of age and sex classes, unlimited number of seasons or time intervals within the annual cycle, and for density-dependent parameters. We demonstrate the flexibility of the metric\nwith four case studies: a hypothetical metapopulation, elk of the Greater Yellowstone Ecosystem, northern pintail ducks in North America, and the eastern population of the monarch butterfly. General computer code to calculate the per-capita contribution metric is provided. We demonstrate that the C-metric is useful for identifying source and sink habitats in a network and suggest that the C-metric could be supplemented by some measure of network structure for\na more robust description of habitat or pathway importance.","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2019.06.003","usgsCitation":"Diffendorfer, J., Sample, C., Beiri, J.A., Allen, B.L., Dementieva, Y., Carson, A., Higgins, C., Piatt, S., Qiu, S., Stafford, S., Mattsson, B., Semmens, D.J., and Thogmartin, W.E., 2019, Quantifying source and sink habitats and pathways in spatially structured populations: A generalized modelling approach: Ecological Modelling, v. 407, p. 1-10, https://doi.org/10.1016/j.ecolmodel.2019.06.003.","productDescription":"108715, 10p.","startPage":"1","endPage":"10","onlineOnly":"N","ipdsId":"IP-107928","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science 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Center","active":true,"usgs":true}],"preferred":true,"id":773325,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sample, Christine","contributorId":201060,"corporation":false,"usgs":false,"family":"Sample","given":"Christine","email":"","affiliations":[],"preferred":false,"id":773326,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Beiri, Joanna A","contributorId":219840,"corporation":false,"usgs":false,"family":"Beiri","given":"Joanna","email":"","middleInitial":"A","affiliations":[{"id":40077,"text":"Univ of Redlands","active":true,"usgs":false}],"preferred":false,"id":773327,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Allen, Benjamin L.","contributorId":193210,"corporation":false,"usgs":false,"family":"Allen","given":"Benjamin","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":773328,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dementieva, Yulia","contributorId":219841,"corporation":false,"usgs":false,"family":"Dementieva","given":"Yulia","email":"","affiliations":[{"id":35881,"text":"Emmanuel College","active":true,"usgs":false}],"preferred":false,"id":773329,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Carson, Alyssa","contributorId":219842,"corporation":false,"usgs":false,"family":"Carson","given":"Alyssa","email":"","affiliations":[{"id":35881,"text":"Emmanuel College","active":true,"usgs":false}],"preferred":false,"id":773330,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Higgins, Connar","contributorId":219843,"corporation":false,"usgs":false,"family":"Higgins","given":"Connar","email":"","affiliations":[{"id":35881,"text":"Emmanuel College","active":true,"usgs":false}],"preferred":false,"id":773331,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Piatt, Sadie","contributorId":219844,"corporation":false,"usgs":false,"family":"Piatt","given":"Sadie","email":"","affiliations":[{"id":35881,"text":"Emmanuel College","active":true,"usgs":false}],"preferred":false,"id":773332,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Qiu, Shirley","contributorId":219845,"corporation":false,"usgs":false,"family":"Qiu","given":"Shirley","email":"","affiliations":[{"id":35881,"text":"Emmanuel College","active":true,"usgs":false}],"preferred":false,"id":773333,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Stafford, Summer","contributorId":219846,"corporation":false,"usgs":false,"family":"Stafford","given":"Summer","email":"","affiliations":[{"id":36213,"text":"University of Redlands","active":true,"usgs":false}],"preferred":false,"id":773334,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Mattsson, Brady J.","contributorId":171612,"corporation":false,"usgs":false,"family":"Mattsson","given":"Brady J.","affiliations":[{"id":26928,"text":"Univ. of Vienna","active":true,"usgs":false}],"preferred":false,"id":773335,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Semmens, Darius J. 0000-0001-7924-6529 dsemmens@usgs.gov","orcid":"https://orcid.org/0000-0001-7924-6529","contributorId":1714,"corporation":false,"usgs":true,"family":"Semmens","given":"Darius","email":"dsemmens@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":773336,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":773337,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70215261,"text":"70215261 - 2019 - Global ecological predictors of the soil priming effect","interactions":[],"lastModifiedDate":"2020-10-16T13:57:57.156401","indexId":"70215261","displayToPublicDate":"2019-10-14T11:16:55","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2842,"text":"Nature Communications","active":true,"publicationSubtype":{"id":10}},"title":"Global ecological predictors of the soil priming effect","docAbstract":"Identifying the global drivers of soil priming is essential to understanding C cycling in terrestrial ecosystems. We conducted a survey of soils across 86 globally-distributed locations, spanning a wide range of climates, biotic communities, and soil conditions, and evaluated the apparent soil priming effect using 13C-glucose labeling. Here we show that the magnitude of the positive apparent priming effect (increase in CO2 release through accelerated microbial biomass turnover) was negatively associated with SOC content and microbial respiration rates. Our statistical modeling suggests that apparent priming effects tend to be negative in more mesic sites associated with higher SOC contents. In contrast, a single-input of labile C causes positive apparent priming effects in more arid locations with low SOC contents. Our results provide solid evidence that SOC content plays a critical role in regulating apparent priming effects, with important implications for the improvement of C cycling models under global change scenarios.
","language":"English","publisher":"Nature","doi":"10.1038/s41467-019-11472-7","usgsCitation":"Bastida, F., Garcia, C.M., Fierer, N., Eldridge, D.J., Bowker, M.A., Abades, S.R., Alfaro, F.D., Berhe, A., Cutler, N.A., Gallardo, A., Garcia-Velazquez, L., Hart, S.C., Hayes, P.E., Hernandez, T., Hseu, Z., Jehmlich, N., Kirchmair, M., Lambers, H., Neuhauser, S., Pena-Ramirez, V.M., Perez, C.A., Reed, S.C., Santos, F., Siebe, C., Sullivan, B., Trivedi, P., Vera, A., Williams, M., Moreno, J.M., and Delgado-Baquerizo, M., 2019, Global ecological predictors of the soil priming effect: Nature Communications, v. 10, 3481, 9 p., https://doi.org/10.1038/s41467-019-11472-7.","productDescription":"3481, 9 p.","ipdsId":"IP-102199","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":459540,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41467-019-11472-7","text":"Publisher Index 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Mark","contributorId":214696,"corporation":false,"usgs":false,"family":"Williams","given":"Mark","affiliations":[],"preferred":false,"id":801940,"contributorType":{"id":1,"text":"Authors"},"rank":28},{"text":"Moreno, Jose M.","contributorId":150464,"corporation":false,"usgs":false,"family":"Moreno","given":"Jose","email":"","middleInitial":"M.","affiliations":[{"id":18029,"text":"D Ciencias Ambientales, U Castilla La Mancha, Toledo, Spain","active":true,"usgs":false}],"preferred":false,"id":801941,"contributorType":{"id":1,"text":"Authors"},"rank":29},{"text":"Delgado-Baquerizo, Manuel","contributorId":214645,"corporation":false,"usgs":false,"family":"Delgado-Baquerizo","given":"Manuel","email":"","affiliations":[{"id":39101,"text":"Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO 80309, USA","active":true,"usgs":false}],"preferred":false,"id":801942,"contributorType":{"id":1,"text":"Authors"},"rank":30}]}} ,{"id":70212818,"text":"70212818 - 2019 - Remote sensing of dryland ecosystem structure and function: Progress, challenges, and opportunities","interactions":[],"lastModifiedDate":"2024-05-16T14:56:12.436485","indexId":"70212818","displayToPublicDate":"2019-10-14T08:20:20","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Remote sensing of dryland ecosystem structure and function: Progress, challenges, and opportunities","docAbstract":"Drylands make up roughly 40% of the Earth's land surface, and billions of people depend on services provided by these critically important ecosystems. Despite their relatively sparse vegetation, dryland ecosystems are structurally and functionally diverse, and emerging evidence suggests that these ecosystems play a dominant role in the trend and variability of the terrestrial carbon sink. More, drylands are highly sensitive to climate and are likely to have large, non-linear responses to hydroclimatic change. Monitoring the spatiotemporal dynamics of dryland ecosystem structure (e.g., leaf area index) and function (e.g., primary production and evapotranspiration) is therefore a high research priority. Yet, dryland remote sensing is defined by unique challenges not typically encountered in mesic or humid regions. Major challenges include low vegetation signal-to-noise ratios, high soil background reflectance, presence of photosynthetic soils (i.e., biological soil crusts), high spatial heterogeneity from plot to regional scales, and irregular growing seasons due to unpredictable seasonal rainfall and frequent periods of drought. Additionally, there is a relative paucity of continuous, long-term measurements in drylands, which impedes robust calibration and evaluation of remotely-sensed dryland data products. Due to these issues, remote sensing techniques developed in other ecosystems or for global application often result in inaccurate, poorly constrained estimates of dryland ecosystem structural and functional dynamics. Here, we review past achievements and current progress in remote sensing of dryland ecosystems, including a detailed discussion of the major challenges associated with remote sensing of key dryland structural and functional dynamics. We then identify strategies aimed at leveraging new and emerging opportunities in remote sensing to overcome previous challenges and more accurately contextualize drylands within the broader Earth system. Specifically, we recommend: 1) Exploring novel combinations of sensors and techniques (e.g., solar-induced fluorescence, thermal, microwave, hyperspectral, and LiDAR) across a range of spatiotemporal scales to gain new insights into dryland structural and functional dynamics; 2) utilizing near-continuous observations from new-and-improved geostationary satellites to capture the rapid responses of dryland ecosystems to diurnal variation in water stress; 3) expanding ground observational networks to better represent the heterogeneity of dryland systems and enable robust calibration and evaluation; 4) developing algorithms that are specifically tuned to dryland ecosystems by utilizing expanded ground observational network data; and 5) coupling remote sensing observations with process-based models using data assimilation to improve mechanistic understanding of dryland ecosystem dynamics and to better constrain ecological forecasts and long-term projections.