Shallow areas of drawdown reservoirs are often devoid of adequate fish habitat due to degradation associated with unnatural and relatively invariable cycles of exposure and flooding. One method of enhancing fish habitat in these areas is to sow exposed shorelines with agricultural plants to provide structure once flooded. It remains unclear if some plants may be more suitable than others to provide effective fish habitat. To determine the fish habitat potential of various crops, we performed a replicated tank experiment evaluating the selection of agricultural plants by prey and predator fishes with and without the presence of the other. We submerged diverse treatments of potted plants in outdoor mesocosms stocked with prey and/or predator fish and monitored selection of plant species, stem density, and stem height over 0.5-h trials. Prey fish selected the densest vegetation, and selection was accentuated when a predator was present. Predators selected the second highest stem density and were more active when prey were present. Prey schooling was increased by predation risk, suggesting that cover was insufficient to outweigh the advantages of increased group size. Our data indicate that the perception of cover quality is reciprocally context dependent on predator–prey interactions for both predator and prey. Applications of the two most selected plant treatments in this study could enhance structural habitat for both predator and prey fishes in reservoirs, adding to their already reliable functionality as supplemental forage crops for terrestrial wildlife.
","language":"English","publisher":"U.S. Fish and Wildlife Service","doi":"10.3996/JFWM-20-083","usgsCitation":"Coppola, G., Miranda, L.E., Colvin, M., Hatcher, H., and Lashley, M., 2021, Selection of habitat-enhancing plants depends on predator-prey interactions: Journal of Fish and Wildlife Management, v. 12, no. 2, p. 294-307, https://doi.org/10.3996/JFWM-20-083.","productDescription":"14 p.","startPage":"294","endPage":"307","ipdsId":"IP-121514","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":452137,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/jfwm-20-083","text":"Publisher Index Page"},{"id":396556,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-05-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Coppola, G.","contributorId":265335,"corporation":false,"usgs":false,"family":"Coppola","given":"G.","email":"","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":836399,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miranda, Leandro E. 0000-0002-2138-7924 smiranda@usgs.gov","orcid":"https://orcid.org/0000-0002-2138-7924","contributorId":531,"corporation":false,"usgs":true,"family":"Miranda","given":"Leandro","email":"smiranda@usgs.gov","middleInitial":"E.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":836400,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Colvin, M. E.","contributorId":265334,"corporation":false,"usgs":false,"family":"Colvin","given":"M. E.","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":836401,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hatcher, H. R.","contributorId":265333,"corporation":false,"usgs":false,"family":"Hatcher","given":"H. R.","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":836402,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lashley, M. A.","contributorId":265336,"corporation":false,"usgs":false,"family":"Lashley","given":"M. A.","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":836403,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70221286,"text":"70221286 - 2021 - Do crayfish affect stream ecosystem response to riparian vegetation removal?","interactions":[],"lastModifiedDate":"2021-06-30T19:04:39.950629","indexId":"70221286","displayToPublicDate":"2021-05-25T07:11:50","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1696,"text":"Freshwater Biology","active":true,"publicationSubtype":{"id":10}},"title":"Do crayfish affect stream ecosystem response to riparian vegetation removal?","docAbstract":"1. Riparian vegetation management alters stream basal resources, but stream ecosystem responses partly depend on top-down interactions with in-stream consumers. Large-bodied omnivores can exert particularly strong influences on stream benthic environments through consumption of food resources and physical disturbance of the benthos. Trophic dynamics studies conducted within the context of reach-scale riparian vegetation manipulations can provide insights into the interactions and relative importance of top-down and bottom-up controls that determine ecosystem response to riparian change. \n2. Here, we examine how top-down control by crayfish omnivores (Cambarus spp.) interacts with abiotic conditions created by reach-scale removal of riparian rhododendron (Rhododendron maximum) in the southern Appalachian Mountains. We conducted 32-day trophic experiments by nesting 5 pairs of electrified (crayfish excluded) and non-electrified (crayfish access) plots within each of two 300-m stream reaches (one control and one rhododendron-removed) for one year pre-removal and two years post-removal. \n3. Algal growth only responded positively to the reduced canopy cover (post-rhododendron removal) under low flow conditions and in the absence of top-down control by crayfish during the post-treatment year 2. Leaf decomposition rates were reduced by ~40% in the absence of crayfish, but higher inputs of rhododendron leaf litter during the summer following rhododendron removal reduced the effect of crayfish presence on decomposition. Riparian rhododendron removal also significantly increased benthic sediment and fine benthic organic matter, but macroconsumer exclusion did not affect these stream properties. \n4. Potential long-term reductions in crayfish abundance could reduce the top-down effects of crayfish and ultimately lead to higher algal growth and reduced leaf decomposition rates in streams where rhododendron is managed through removal.","language":"English","publisher":"Wiley","doi":"10.1111/fwb.13728","usgsCitation":"Dudley, M.P., Solomon, K., Wenger, S., Jackson, C.R., Freeman, M., Elliott, K.J., Miniat, C., and Pringle, C.M., 2021, Do crayfish affect stream ecosystem response to riparian vegetation removal?: Freshwater Biology, v. 66, no. 7, p. 1423-1435, https://doi.org/10.1111/fwb.13728.","productDescription":"13 p.","startPage":"1423","endPage":"1435","ipdsId":"IP-120584","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":386339,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","otherGeospatial":"Southern Appalachian Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.693603515625,\n 34.99850370014629\n ],\n [\n -82.9632568359375,\n 34.99850370014629\n ],\n [\n -82.9632568359375,\n 35.78662688467009\n ],\n [\n -84.693603515625,\n 35.78662688467009\n ],\n [\n -84.693603515625,\n 34.99850370014629\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"66","issue":"7","noUsgsAuthors":false,"publicationDate":"2021-05-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Dudley, Maura P. 0000-0001-9574-8844","orcid":"https://orcid.org/0000-0001-9574-8844","contributorId":236862,"corporation":false,"usgs":false,"family":"Dudley","given":"Maura","email":"","middleInitial":"P.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":817238,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Solomon, Kelsey","contributorId":260094,"corporation":false,"usgs":false,"family":"Solomon","given":"Kelsey","email":"","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":817239,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wenger, Seth J.","contributorId":177838,"corporation":false,"usgs":false,"family":"Wenger","given":"Seth J.","affiliations":[],"preferred":false,"id":817240,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jackson, C. Rhett","contributorId":236863,"corporation":false,"usgs":false,"family":"Jackson","given":"C.","email":"","middleInitial":"Rhett","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":817241,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Freeman, Mary 0000-0001-7615-6923 mcfreeman@usgs.gov","orcid":"https://orcid.org/0000-0001-7615-6923","contributorId":3528,"corporation":false,"usgs":true,"family":"Freeman","given":"Mary","email":"mcfreeman@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":817242,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Elliott, Katherine J.","contributorId":260095,"corporation":false,"usgs":false,"family":"Elliott","given":"Katherine","email":"","middleInitial":"J.","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":817243,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Miniat, Chelcy F.","contributorId":260097,"corporation":false,"usgs":false,"family":"Miniat","given":"Chelcy F.","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":817244,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Pringle, Catherine M.","contributorId":176292,"corporation":false,"usgs":false,"family":"Pringle","given":"Catherine","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":817245,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70221107,"text":"70221107 - 2021 - Establishment and survival of subalpine fir (Abies lasiocarpa) in meadows of Olympic National Park, Washington","interactions":[],"lastModifiedDate":"2021-06-02T12:33:22.297629","indexId":"70221107","displayToPublicDate":"2021-05-21T07:29:51","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2900,"text":"Northwest Science","onlineIssn":"2161-9859","printIssn":"0029-344X","active":true,"publicationSubtype":{"id":10}},"title":"Establishment and survival of subalpine fir (Abies lasiocarpa) in meadows of Olympic National Park, Washington","docAbstract":"Establishment of trees in subalpine meadows is a potential indicator of ecological effects of climate change. Tree establishment is a multi-year process including cone and seed production, germination, establishment, and growth, with each demographic step possibly sensitive to different climate limitations. While most studies have focused on one or a few steps, this study follows a cohort of individually marked saplings for 27 years beginning as seeds in two meadows on Hurricane Ridge, Olympic National Park. These meadows are examples of a south-facing tall sedge community type rather than the north-facing heath-shrub type where establishment has usually been observed. Results showed that mortality was high for the first few years, but number of saplings stabilized after the first decade. Seedling mortality during germination and establishment was directly related to weather that resulted in high air and soil temperatures and drought, while mortality of established saplings was indirectly related to weather through effects on growth. Growth was enhanced by longer growing season and warmer minimum temperatures; growth over three years and sapling height were predictive of mortality. Most sapling survival occurred in lichen (primarily Trapeliopsis granulosa) and Vaccinium deliciosum plant communities. Many saplings are growing at very low rates compared with the rate predicted from adult trees. It is also apparent that while microsite within meadow (e.g., relative snow depth) is important in determining sapling success, the landscape position of meadows (e.g., north versus south aspect) exerts a higher-level control over whether a subalpine meadow is likely to disappear with warming climate.
","language":"English","publisher":"BioOne","doi":"10.3955/046.094.0304","usgsCitation":"Woodward, A., and Soll, J.A., 2021, Establishment and survival of subalpine fir (Abies lasiocarpa) in meadows of Olympic National Park, Washington: Northwest Science, v. 94, no. 3-4, p. 256-270, https://doi.org/10.3955/046.094.0304.","productDescription":"15 p.","startPage":"256","endPage":"270","ipdsId":"IP-107735","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":386116,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Olympic National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.49707031249999,\n 47.212105775622426\n ],\n [\n -122.81616210937499,\n 47.212105775622426\n ],\n [\n -122.81616210937499,\n 48.21735290928554\n ],\n [\n -124.49707031249999,\n 48.21735290928554\n ],\n [\n -124.49707031249999,\n 47.212105775622426\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"94","issue":"3-4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Woodward, Andrea 0000-0003-0604-9115 awoodward@usgs.gov","orcid":"https://orcid.org/0000-0003-0604-9115","contributorId":3028,"corporation":false,"usgs":true,"family":"Woodward","given":"Andrea","email":"awoodward@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":816782,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Soll, Jonathan A.","contributorId":259195,"corporation":false,"usgs":false,"family":"Soll","given":"Jonathan","email":"","middleInitial":"A.","affiliations":[{"id":52329,"text":"Portland Metro Regional Government, 600 N.E. Grand Avenue, Portland, OR","active":true,"usgs":false}],"preferred":false,"id":816783,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70241866,"text":"70241866 - 2021 - A small proportion of breeders drive American bullfrog invasion of the Yellowstone River floodplain, Montana","interactions":[],"lastModifiedDate":"2023-03-29T12:19:19.642504","indexId":"70241866","displayToPublicDate":"2021-05-21T07:16:32","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2900,"text":"Northwest Science","onlineIssn":"2161-9859","printIssn":"0029-344X","active":true,"publicationSubtype":{"id":10}},"title":"A small proportion of breeders drive American bullfrog invasion of the Yellowstone River floodplain, Montana","docAbstract":"The American bullfrog (Lithobates catesbeianus) is a non-native invader of aquatic habitats across the northwestern United States. It recently invaded the Yellowstone River, Montana, and has spread to over 140 km of floodplain habitat. We analyzed seven microsatellites in 528 tadpoles sampled across nearly the entire Yellowstone River invasion (about 140 river km) to characterize invasion genetics, compare our results with those of a recent mtDNA study (Kamath et al. 2016), and to inform control efforts. Microsatellite variation supports the mtDNA-based hypothesis of at least two independent introductions to the floodplain from genetically divergent populations in the midwestern United States, followed by massive range expansion. One introduction is associated with the upstream extent of the invasion near Park City, Montana and the other more broadly with downstream populations. All sites were characterized by small effective numbers of breeders (Nb; harmonic mean = 9.97), and therefore, a small proportion of highly successful adults may drive the invasion by producing large families. Microsatellites and mtDNA produced discordant estimates of genetic admixture between the upstream and downstream invasions, which may reflect small effective population size. Although we observed isolation by distance using both types of markers, microsatellites appear to reflect population structure resulting from secondary contact between the two introductions, as opposed to structure resulting from equilibrium between gene flow and genetic drift. Most sites showed evidence for genetic bottlenecks, which supports the recent history of invasion. Small Nb paired with known high localized extinction rates following colonization suggests focused removal of post metamorphic life stages at sites less likely to go extinct on their own could help limit invasion by bullfrogs.
Invasive species management typically aims to promote diversity and wildlife habitat, but little is known about how management techniques affect wetland carbon (C) dynamics. Since wetland C uptake is largely influenced by water levels and highly productive plants, the interplay of hydrologic extremes and invasive species is fundamental to understanding and managing these ecosystems. During a period of rapid water level rise in the Laurentian Great Lakes, we tested how mechanical treatment of invasive plant Typha × glauca shifts plant-mediated wetland C metrics. From 2015 to 2017, we implemented large-scale treatment plots (0.36-ha) of harvest (i.e., cut above water surface, removed biomass twice a season), crush (i.e., ran over biomass once mid-season with a tracked vehicle), and Typha-dominated controls. Treated Typha regrew with approximately half as much biomass as unmanipulated controls each year, and Typha production in control stands increased from 500 to 1500 g-dry mass m−2 yr−1 with rising water levels (~10 to 75 cm) across five years. Harvested stands had total in-situ methane (CH4) flux rates twice as high as in controls, and this increase was likely via transport through cut stems because crushing did not change total CH4 flux. In 2018, one year after final treatment implementation, crushed stands had greater surface water diffusive CH4 flux rates than controls (measured using dissolved gas in water), likely due to anaerobic decomposition of flattened biomass. Legacy effects of treatments were evident in 2019; floating Typha mats were present only in harvested and crushed stands, with higher frequency in deeper water and a positive correlation with surface water diffusive CH4 flux. Our study demonstrates that two mechanical treatments have differential effects on Typha structure and consequent wetland CH4 emissions, suggesting that C-based responses and multi-year monitoring in variable water conditions are necessary to accurately assess how management impacts ecological function.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2021.147920","usgsCitation":"Johnson, O.F., Panda, A., Lishawa, S., and Lawrence, B.A., 2021, Repeated large-scale mechanical treatment of invasive Typha under increasing water levels promotes floating mat formation and wetland methane emissions: Science of the Total Environment, v. 790, 147920, 10 p., https://doi.org/10.1016/j.scitotenv.2021.147920.","productDescription":"147920, 10 p.","ipdsId":"IP-124761","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":452187,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2021.147920","text":"Publisher Index Page"},{"id":386726,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan","otherGeospatial":"Northern Upper Peninsula","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.1220703125,\n 45.058001435398275\n ],\n [\n -84.19921875,\n 45.058001435398275\n ],\n [\n -84.19921875,\n 45.85941212790755\n ],\n [\n -85.1220703125,\n 45.85941212790755\n ],\n [\n -85.1220703125,\n 45.058001435398275\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"790","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Johnson, Olivia Fayne 0000-0002-6839-6617","orcid":"https://orcid.org/0000-0002-6839-6617","contributorId":223859,"corporation":false,"usgs":true,"family":"Johnson","given":"Olivia","email":"","middleInitial":"Fayne","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":818247,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Panda, Abha","contributorId":260635,"corporation":false,"usgs":false,"family":"Panda","given":"Abha","email":"","affiliations":[{"id":39062,"text":"School for Environment and Sustainability, University of Michigan","active":true,"usgs":false}],"preferred":false,"id":818248,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lishawa, Shane C.","contributorId":260636,"corporation":false,"usgs":false,"family":"Lishawa","given":"Shane C.","affiliations":[{"id":52628,"text":"School of Environmental Sustainability, Loyola University","active":true,"usgs":false}],"preferred":false,"id":818249,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lawrence, Beth A.","contributorId":217552,"corporation":false,"usgs":false,"family":"Lawrence","given":"Beth","email":"","middleInitial":"A.","affiliations":[{"id":36710,"text":"University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":818250,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70221155,"text":"70221155 - 2021 - Prototyping a methodology for long-term (1680-2100) historical-to-future landscape modeling for the conterminous United States","interactions":[],"lastModifiedDate":"2022-04-01T22:14:57.190942","indexId":"70221155","displayToPublicDate":"2021-05-19T08:12:42","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2596,"text":"Land","active":true,"publicationSubtype":{"id":10}},"title":"Prototyping a methodology for long-term (1680-2100) historical-to-future landscape modeling for the conterminous United States","docAbstract":"Land system change has been identified as one of four major Earth system processes where change has passed a destabilizing threshold. A historical record of landscape change is required to understand the impacts change has had on human and natural systems, while scenarios of future landscape change are required to facilitate planning and mitigation efforts. A methodology for modeling long-term historical and future landscape change was applied in the Delaware River Basin of the United States. A parcel-based modeling framework was used to reconstruct historical landscapes back to 1680, parameterized with a variety of spatial and nonspatial historical datasets. Similarly, scenarios of future landscape change were modeled for multiple scenarios out to 2100. Results demonstrate the ability to represent historical land cover proportions and general patterns at broad spatial scales and model multiple potential future landscape trajectories. The resulting land cover collection provides consistent data from 1680 through 2100, at a 30-m spatial resolution, 10-year intervals, and high thematic resolution. The data are consistent with the spatial and thematic characteristics of widely used national-scale land cover datasets, facilitating use within existing land management and research workflows. The methodology demonstrated in the Delaware River Basin is extensible and scalable, with potential applications at national scales for the United States.
","language":"English","publisher":"MDPI","doi":"10.3390/land10050536","usgsCitation":"Dornbierer, J., Wika, S., Robison, C., Rouze, G., and Sohl, T.L., 2021, Prototyping a methodology for long-term (1680-2100) historical-to-future landscape modeling for the conterminous United States: Land, v. 10, no. 5, 536, 31 p.; Data Release, https://doi.org/10.3390/land10050536.","productDescription":"536, 31 p.; Data Release","ipdsId":"IP-127950","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":452199,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/land10050536","text":"Publisher Index Page"},{"id":386174,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":397938,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93J4Z2W"}],"country":"United States","state":"Delaware, Maryland, New Jersey, New York, Pennsylvania","otherGeospatial":"Delaware River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.728759765625,\n 38.676933444637925\n ],\n [\n -75.333251953125,\n 38.46219172306828\n ],\n [\n -74.827880859375,\n 39.06184913429154\n ],\n [\n -75.025634765625,\n 39.38526381099774\n ],\n [\n -74.2236328125,\n 40.212440718286466\n ],\n [\n -74.696044921875,\n 40.78885994449482\n ],\n [\n -73.58642578125,\n 41.5579215778042\n ],\n [\n -74.278564453125,\n 42.27730877423709\n ],\n [\n -76.83837890625,\n 40.538851525354666\n ],\n [\n -75.728759765625,\n 38.676933444637925\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"5","noUsgsAuthors":false,"publicationDate":"2021-05-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Dornbierer, Jordan 0000-0003-2099-5095","orcid":"https://orcid.org/0000-0003-2099-5095","contributorId":213067,"corporation":false,"usgs":false,"family":"Dornbierer","given":"Jordan","affiliations":[{"id":38270,"text":"SGT Inc., contractor to USGS EROS","active":true,"usgs":false}],"preferred":false,"id":816876,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wika, Steve 0000-0001-9992-8973","orcid":"https://orcid.org/0000-0001-9992-8973","contributorId":213068,"corporation":false,"usgs":false,"family":"Wika","given":"Steve","affiliations":[{"id":38700,"text":"SGT Inc.","active":true,"usgs":false}],"preferred":false,"id":816877,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Robison, Charles 0000-0002-7623-2380","orcid":"https://orcid.org/0000-0002-7623-2380","contributorId":217916,"corporation":false,"usgs":false,"family":"Robison","given":"Charles","email":"","affiliations":[{"id":39714,"text":"SGT Inc. (USGS Contractor)","active":true,"usgs":false}],"preferred":false,"id":816878,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rouze, Gregory 0000-0002-3344-2708","orcid":"https://orcid.org/0000-0002-3344-2708","contributorId":259239,"corporation":false,"usgs":false,"family":"Rouze","given":"Gregory","email":"","affiliations":[{"id":52337,"text":"TSSC contractor to USGS EROS","active":true,"usgs":false}],"preferred":false,"id":816879,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sohl, Terry L. 0000-0002-9771-4231 sohl@usgs.gov","orcid":"https://orcid.org/0000-0002-9771-4231","contributorId":648,"corporation":false,"usgs":true,"family":"Sohl","given":"Terry","email":"sohl@usgs.gov","middleInitial":"L.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":816880,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70220861,"text":"70220861 - 2021 - Incorporating climate change in a harvest risk assessment for polar bears Ursus maritimus in Southern Hudson Bay","interactions":[],"lastModifiedDate":"2021-05-26T12:28:44.821314","indexId":"70220861","displayToPublicDate":"2021-05-19T07:26:46","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Incorporating climate change in a harvest risk assessment for polar bears Ursus maritimus in Southern Hudson Bay","docAbstract":"Arctic marine mammals are harvested by Indigenous people for subsistence and are socially and culturally important. For ice-dependent species like the polar bear Ursus maritimus, management and conservation require understanding interactions between harvest and sea-ice loss due to climate change. We developed a demographic model to evaluate harvest risk for polar bears in Southern Hudson Bay, Canada, where the annual ice-free season has increased by approximately one month in recent decades. The model was based on the theta-logistic equation and allowed for density-dependent changes (through carrying capacity [K]) and density-independent changes (through population growth rate [r]). Model parameters were estimated using a Bayesian Monte Carlo method that included capture-recapture, aerial survey, and harvest data. Harvest management followed a state-dependent approach under which new estimates of abundance were used to update the harvest level every five years. Under a middle-of-the-road environmental scenario that assumed K and r would decline in proportion to projected sea-ice declines, annual removal of 0.02–0.03 of females resulted in a 0.8 probability of maintaining subpopulation abundance above maximum net productivity level for three polar bear generations (~34 years), our primary criterion for sustainability. Under more pessimistic and optimistic environmental scenarios, comparable female harvest rates were 0.01 and 0.055, respectively. Our coupled modeling-management framework can be used to inform tradeoffs between protection and sustainable use for wildlife populations experiencing habitat loss.
The federally threatened American crocodile (Crocodylus acutus) is a flagship species and ecological indicator of hydrologic restoration in the Florida Everglades. We conducted a long-term capture-recapture study on the South Florida population of American crocodiles from 1978 to 2015 to evaluate the effects of restoration efforts to more historic hydrologic conditions. The study produced 10,040 crocodile capture events of 9,865 individuals and more than 90% of captures were of hatchlings. Body condition and growth rates of crocodiles were highly age-structured with younger crocodiles presenting with the poorest body condition and highest growth rates. Mean crocodile body condition in this study was 2.14±0.35 SD across the South Florida population. Crocodiles exposed to hypersaline conditions (> 40 psu) during the dry season maintained lower body condition scores and reduced growth rate by 13% after one year, by 24% after five years, and by 29% after ten years. Estimated hatchling survival for the South Florida population was 25% increasing with ontogeny and reaching near 90% survival at year six. Hatchling survival was 34% in NE Florida Bay relative to a 69% hatchling survival at Crocodile Lake National Wildlife Refuge and 53% in Flamingo area of Everglades National Park. Hypersaline conditions negatively affected survival, growth and body condition and was most pronounced in NE Florida Bay, where the hydrologic conditions have been most disturbed. The American crocodile, a long-lived animal, with relatively slow growth rate provides an excellent model system to measure the effects of altered hydropatterns in the Everglades landscape. These results illustrate the need for continued long-term monitoring to assess system-wide restoration outcomes and inform resource managers.
Ongoing climate change and human conversion of forests to other land uses alter regional evapotranspiration dynamics and, consequently, impact associated hydrological systems in Amazonia. We studied the effects of drought and fragmentation on forest evapotranspiration using the surface energy balance-based model METRIC (Mapping Evapotranspiration at high Resolution with Internalized Calibration) for a fragmented forest landscape in Brazil's Amazonian state of Rondônia.
Dry season (June-August) forest evapotranspiration estimates were produced for the 2009-2011 period that encompassed the 2010 drought event, one of the extreme droughts in the Amazon. METRIC evapotranspiration data were analyzed in relation to climate (monthly precipitation and cumulative water deficit) and forest fragmentation (edge distance from 100m to 1000m from forest edge and edge density). During the dry season of 2009, pre-drought, forest evapotranspiration did not fall below 110mm/month. However, the 2010 drought year showed a drastic decline in evapotranspiration by 32%, to 75mm/month, from July to August. In 2011, evapotranspiration rates were still depressed with August rates dropping as low as 85mm/month. Forest evapotranspiration dynamics were driven mainly by precipitation and corresponding water deficits in the drier years (2010 and 2011), although evapotranspiration deficits along the edges of forest fragments were locally significant, at the landscape scale. The forests near edges (to 100m) had progressively lower evapotranspiration levels than interior forests as dry seasons progressed and these differences were greatest in the 2010 drought year, reaching almost 5%.
Our results suggest that during the driest months, fragmentation exacerbated both the rate and extent of evapotranspiration reductions over forest areas up to 100m from edges, equivalent to ~20% of the forested landscape in our study area.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.agrformet.2021.108446","usgsCitation":"Numata, I., Khand, K.B., Kjaersgaard, J., Cochrane, M.A., and Silva, S.S., 2021, Forest evapotranspiration dynamics over a fragmented forest landscape under drought in southwestern Amazonia: Agricultural and Forest Meteorology, v. 306, 108446, 9 p., https://doi.org/10.1016/j.agrformet.2021.108446.","productDescription":"108446, 9 p.","ipdsId":"IP-122348","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":452208,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.agrformet.2021.108446","text":"Publisher Index Page"},{"id":385833,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Brazil","state":"Rondonia","otherGeospatial":"Amazon Rain Forest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -66.97265625,\n -2.4162756547063857\n ],\n [\n -56.6455078125,\n -2.4162756547063857\n ],\n [\n -56.6455078125,\n 6.18424616128059\n ],\n [\n -66.97265625,\n 6.18424616128059\n ],\n [\n -66.97265625,\n -2.4162756547063857\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"306","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Numata, Izaya","contributorId":219508,"corporation":false,"usgs":false,"family":"Numata","given":"Izaya","email":"","affiliations":[],"preferred":false,"id":816235,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Khand, Kul Bikram 0000-0002-1593-1508","orcid":"https://orcid.org/0000-0002-1593-1508","contributorId":242921,"corporation":false,"usgs":true,"family":"Khand","given":"Kul","email":"","middleInitial":"Bikram","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":816236,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kjaersgaard, Jeppe","contributorId":258261,"corporation":false,"usgs":false,"family":"Kjaersgaard","given":"Jeppe","email":"","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":816237,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cochrane, Mark A.","contributorId":20884,"corporation":false,"usgs":false,"family":"Cochrane","given":"Mark","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":816238,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Silva, Sonaira S.","contributorId":258262,"corporation":false,"usgs":false,"family":"Silva","given":"Sonaira","email":"","middleInitial":"S.","affiliations":[{"id":52266,"text":"Federal University of Acre","active":true,"usgs":false}],"preferred":false,"id":816239,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70220526,"text":"ofr20211032 - 2021 - Investigation of otolith microstructure and composition for identification of rearing strategies and associated Baker Lake sockeye salmon (Oncorhynchus nerka) smolt production, Washington, 2016–17","interactions":[],"lastModifiedDate":"2021-05-19T11:55:14.367922","indexId":"ofr20211032","displayToPublicDate":"2021-05-18T15:49:30","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-1032","displayTitle":"Investigation of Otolith Microstructure and Composition for Identification of Rearing Strategies and Associated Baker Lake Sockeye Salmon (Oncorhynchus nerka) Smolt Production, Washington, 2016–17","title":"Investigation of otolith microstructure and composition for identification of rearing strategies and associated Baker Lake sockeye salmon (Oncorhynchus nerka) smolt production, Washington, 2016–17","docAbstract":"Baker River (Washington, USA) sockeye salmon (Oncorhynchus nerka) are a recovering Puget Sound stock that are aided by trap-and-haul and hatchery programs to mitigate for the presence of a high head dam. The relative contribution of hatchery and natural adults to overall production of smolts and recruits is unknown. The ability to identify three different sockeye production groups (natural production, artificial incubation, and artificial spawning beach) within the Baker system is crucial to moving forward with management goals. The examination of otoliths was proposed as a technical tool for improved understanding and management of Baker sockeye rebuilding efforts. Otoliths were chosen as they provide a chronological record on an individual fish basis and have been shown to identify fish origin through both otolith microstructure and chemistry.
The goal of this pilot project was to determine the feasibility of assigning sockeye to their production source based on otolith analysis. A variety of methods were employed and compared for accuracy of group assignment. The maximum overall accuracy capable of attainment was 88.57 percent, however complete confidence (100 percent) in the separation of natural production from artificial production was reached through the analysis of trace elements alone. Some segregation of the two artificial production groups was reached through analysis of a few specific trace elements (magnesium, manganese, and zinc). This confidence in assignment for the artificial production groups was aided by a two-step process of combining trace elements with microstructure. The Sr isotope ratios supported the trace element findings but did not help to boost the overall level of confidence in the separation of production groups. Based upon the results from this preliminary investigation, one could choose a statistically sound, efficient, and cost-effective use of otoliths as a tool for discriminating between the sockeye production groups of the Baker Lake system.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211032","collaboration":"A Report to the Upper Skagit Indian Tribe per agreement # 17WNYD00SIT5545","usgsCitation":"Larsen, K.A., Wetzel, L.A., Stenberg, K.D., and Lind-Null, A.M., 2021, Investigation of otolith microstructure and composition for identification of rearing strategies and associated Baker Lake sockeye salmon (Oncorhynchus nerka) smolt production, Washington, 2016–17: U.S. Geological Survey Open-File Report 2021–1032, 15 p., https://doi.org/10.3133/ofr20211032.","productDescription":"vii, 16 p.","onlineOnly":"Y","ipdsId":"IP-091287","costCenters":[{"id":654,"text":"Western Fisheries Research 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\"}}]}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016
An important aspect of volcanic hazard assessment is determination of the level and character of background activity at a volcano so that deviations from background (called unrest) can be identified. Here, we compile the instrumentally recorded eruptive and noneruptive activity for 161 US volcanoes between 1978 and 2020. We combine monitoring data from four techniques: seismicity, ground deformation, degassing, and thermal emissions. To previous work, we add the first comprehensive survey of US volcanoes using medium-spatial resolution satellite thermal observations, newly available field surveys of degassing, and new compilations of seismic and deformation data. We report previously undocumented thermal activity at 30 volcanoes using data from the spaceborne ASTER sensor during 2000–2020. To facilitate comparison of activity levels for all US volcanoes, we assign a numerical classification of the Activity Intensity Level for each monitoring technique, with the highest ranking corresponding to an eruption. There are 96 US volcanoes (59%) with at least one type of detected activity, but this represents a lower bound: For example, there are 12 volcanoes where degassing has been observed but has not yet been quantified. We identify dozens of volcanoes where volcanic activity is only measured by satellite (45% of all thermal observations), and other volcanoes where only ground-based sensors have detected activity (e.g., all seismic and 62% of measured degassing observations). Our compilation provides a baseline against which future measurements can be compared, demonstrates the need for both ground-based and remote observations, and serves as a guide for prioritizing future monitoring efforts.
The St. Clair and Detroit rivers historically supported abundant fish populations. However, like many river systems, these rivers have been greatly altered through the creation of navigation channels and other anthropogenic disturbances, resulting in the loss of fish and wildlife habitat and declines in native fish populations. To ameliorate this environmental degradation, artificial fish spawning reefs were constructed in the St. Clair and Detroit rivers. One native species to potentially benefit from artificial reefs is the Northern Madtom Noturus stigmosus, a small ictalurid that is listed as endangered in the state of Michigan and the province of Ontario. Between 2016 and 2018, artificial reefs and nearby control sites were sampled in the St. Clair and Detroit rivers to compare the number of Northern Madtoms. In total, 171 Northern Madtoms were captured in 1,848 minnow traps with one of four bait types: cheese, dog food, worms, or control (no bait). Baited minnow traps successfully captured Northern Madtoms in the fast-flowing, deep water of the St. Clair–Detroit River system, and catch rates were significantly higher when traps were baited with worms. The number of Northern Madtoms captured was lower in the Detroit River than in the St. Clair River and increased with increasing water temperature and turbidity. Artificial reefs constructed in the St. Clair–Detroit River system are providing habitat for Northern Madtoms; however, use did not differ between reef sites and nearby control sites. This work provides insight regarding sampling strategies to target Northern Madtoms in large-river systems and highlights the importance of incorporating a temporal sampling strategy into survey design.
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Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":815842,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hessenauer, Jan-Michael","contributorId":257795,"corporation":false,"usgs":false,"family":"Hessenauer","given":"Jan-Michael","email":"","affiliations":[{"id":36986,"text":"Michigan Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":815843,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Roseman, Edward F. 0000-0002-5315-9838","orcid":"https://orcid.org/0000-0002-5315-9838","contributorId":217909,"corporation":false,"usgs":true,"family":"Roseman","given":"Edward F.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":815844,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70223428,"text":"70223428 - 2021 - Land conversion and pesticide use degrade forage areas for honey bees in America’s beekeeping epicenter","interactions":[],"lastModifiedDate":"2021-08-26T21:16:03.616536","indexId":"70223428","displayToPublicDate":"2021-05-13T16:02:29","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Land conversion and pesticide use degrade forage areas for honey bees in America’s beekeeping epicenter","docAbstract":"A diverse range of threats have been associated with managed bee declines globally. Recent increases of two known threats, land-use change and pesticide use, have resulted from agricultural expansion and intensification notably in the top honey producing state in the United States (U.S.): North Dakota. This study investigated the dual threat from land conversion and pesticide use surrounding ~14,000 registered apiaries in North Dakota from 2001 to 2014. We estimated the annual total insecticide use (kg) on major crops within 1.6 km of apiary sites. Of the eight insecticides, six showed significant increasing trends over the time period. Specifically, applications of the newly established neonicotinoids Chlothianidin, Imidacloprid and Thiamethoxam, increased annually by 1329 kg, 686 kg, 795 kg, respectively. Also, the use of Chlorpyrifos, which was well-established by 2001 and is highly toxic to honey bees, increased by ~8,800 kg annually from 6,500 kg in 2001 to 115,000 kg in 2014 on corn, soybeans and wheat. We further evaluated the relative quality changes of natural/semi-natural land covers surrounding apiaries in 2006, 2010 and 2014, a period of significant increases in cropland area. In areas surrounding apiaries, we observed changes in multiple indices of forage quality that reflect the deteriorating landscape surrounding registered apiary sites due to land-use change and pesticide-use increases. Overall, our results suggest that the application of foliar-applied insecticides, including pyrethroids and one organophosphate, increased surrounding apiaries when the use of neonicotinoid seed treatment surged and the area for producing corn and soybeans expanded. Spatially, these threats were most pronounced in southeastern North Dakota, a region hosting a high density of apiary sites that has recently experienced corn and soybean expansion. Our results highlight the values of natural and semi-natural land covers as sources of pollinator forage and providing refugia for bees against pesticide exposure. Our study provides insights for targeting conservation efforts to improve forage quality for benefiting managed pollinators.","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0251043","usgsCitation":"Dixon, D.J., Zheng, H., and Otto, C., 2021, Land conversion and pesticide use degrade forage areas for honey bees in America’s beekeeping epicenter: PLoS ONE, v. 16, no. 5, p. 1-15, https://doi.org/10.1371/journal.pone.0251043.","productDescription":"e0251043, 15 p.","startPage":"1","endPage":"15","ipdsId":"IP-124228","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":452267,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0251043","text":"Publisher Index Page"},{"id":388568,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North 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Dakota","active":true,"usgs":false}],"preferred":false,"id":822072,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Otto, Clint 0000-0002-7582-3525 cotto@usgs.gov","orcid":"https://orcid.org/0000-0002-7582-3525","contributorId":5426,"corporation":false,"usgs":true,"family":"Otto","given":"Clint","email":"cotto@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":822025,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70229235,"text":"70229235 - 2021 - Demographic responses to density-dependence by two populations of the Florida Tree Snail, Liguus fasciatus (Gastropoda: Orthalicidae), in Everglades National Park","interactions":[],"lastModifiedDate":"2022-03-03T17:51:10.639176","indexId":"70229235","displayToPublicDate":"2021-05-13T11:48:27","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3574,"text":"The Nautilus","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Demographic responses to density-dependence by two populations of the Florida Tree Snail, Liguus fasciatus (Gastropoda: Orthalicidae), in Everglades National Park","title":"Demographic responses to density-dependence by two populations of the Florida Tree Snail, Liguus fasciatus (Gastropoda: Orthalicidae), in Everglades National Park","docAbstract":"During May-October 1996, we captured and individually marked and released Florida Tree Snails, Liguus fasciatus, from two sites, a subclimax hammock and a large isolated wild tamarind tree, in the Long Pine Key region of Everglades National Park. Populations shared the same two dominant morphs, castaneozonatus and. cingulatus, both of which are strong colonizers. Monthly survivorship between the two sites were comparable, although annual survivorship was lower on the isolated tree. Intersite differences in growth rates were equivocal. The populations differed with respect to number of morphs, population size, and population structure. The hammock site was a subclimax hammock with a large and stable bell-shaped population structure comprising nine morphs. In contrast, the population structure of the single tree was highly skewed, with many young individuals produced, intermediate ages absent, and few large adults of larger asymptotic size present. Number of snails/m was higher on the isolated tree. Demographic studies of the Florida Tree Snail are uncommon. Our findings corroborate certain aspects of the ecology of this species and clarify two different demographic responses, one of stability, and one of apparent resource limitation whose demography represents opportunities for colonization.
","language":"English","publisher":"Bailey-Matthews National Shell Museum","usgsCitation":"Meshaka, W.E., Rice, K.G., Bass, O., and Waddle, H., 2021, Demographic responses to density-dependence by two populations of the Florida Tree Snail, Liguus fasciatus (Gastropoda: Orthalicidae), in Everglades National Park: The Nautilus, v. 135, no. 1, p. 1-10.","productDescription":"10 p.","startPage":"1","endPage":"10","ipdsId":"IP-120151","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":396714,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.3482666015625,\n 25.095548539604252\n ],\n [\n -80.44464111328125,\n 25.095548539604252\n ],\n [\n -80.44464111328125,\n 25.9926124897092\n ],\n [\n -81.3482666015625,\n 25.9926124897092\n ],\n [\n -81.3482666015625,\n 25.095548539604252\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"135","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Meshaka, Walter E.","contributorId":215660,"corporation":false,"usgs":false,"family":"Meshaka","given":"Walter","email":"","middleInitial":"E.","affiliations":[{"id":39300,"text":"Section of Zoology and Botany, State Museum of Pennsylvania","active":true,"usgs":false}],"preferred":false,"id":837006,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rice, Kenneth G. 0000-0001-8282-1088 krice@usgs.gov","orcid":"https://orcid.org/0000-0001-8282-1088","contributorId":117,"corporation":false,"usgs":true,"family":"Rice","given":"Kenneth","email":"krice@usgs.gov","middleInitial":"G.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":837007,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bass, Oron L.","contributorId":287679,"corporation":false,"usgs":false,"family":"Bass","given":"Oron L.","affiliations":[],"preferred":false,"id":837008,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Waddle, Hardin 0000-0003-1940-2133","orcid":"https://orcid.org/0000-0003-1940-2133","contributorId":209861,"corporation":false,"usgs":true,"family":"Waddle","given":"Hardin","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":837009,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70230618,"text":"70230618 - 2021 - Rapid monitoring of the abundance and spread of exotic annual grasses in the western United States using remote sensing and machine learning","interactions":[],"lastModifiedDate":"2022-04-19T14:58:45.389206","indexId":"70230618","displayToPublicDate":"2021-05-13T09:53:22","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7751,"text":"AGU Advances","active":true,"publicationSubtype":{"id":10}},"title":"Rapid monitoring of the abundance and spread of exotic annual grasses in the western United States using remote sensing and machine learning","docAbstract":"Exotic annual grasses (EAG) are one of the most damaging agents of change in western North America. Despite known socio-environmental effects of EAG there remains a need to enhance monitoring capabilities for better informing conservation and management practices. Here, we integrate field observations, remote sensing and climate data with machine-learning techniques to estimate and assess patterns of historical (1985–2019; R2 = 0.86 ± 0.05; MAE = 6.7 ± 1.4%), present (2020), and future (2025–2040) EAG abundance (30-m) across much of the western United States. Trend analysis revealed that ∼8% and 1% of the landscape experienced significant rises and declines in historical EAG cover, respectively, with hotspots of invasion generally occurring near roads and along low-to-mid elevation gradients with warmer and drier conditions. Accurate simulations of the response of EAG to changing environmental conditions, disturbances and management treatments indicate that ecosystem resistance to invasion is largely controlled by long-term EAG abundance (surrogate for seed bank), time since and frequency of wildfire, and plant community interactions. Ecological thresholds associated with enhanced probabilities of wildfire occurrence and invasion rates indicate that relatively little (10%) EAG cover is needed to heighten these risks. Climate change is expected to push 8% of the landscape across invasion thresholds by 2040, impacting 6% of existing sage-grouse habitat, and we identify where fuel breaks may be placed to reduce wildfire risks and invasion. Spatially detailed, timely, and accurate depictions of past, present, and future EAG abundance are vital for the protection of life and property and the continued stewardship of sagebrush ecosystems.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020AV000298","usgsCitation":"Pastick, N., Wylie, B., Rigge, M.B., Dahal, D., Boyte, S., Jones, M.O., Allred, B.W., Parajuli, S., and Wu, Z., 2021, Rapid monitoring of the abundance and spread of exotic annual grasses in the western United States using remote sensing and machine learning: AGU Advances, v. 2, no. 2, e2020AV000298, 22 p., https://doi.org/10.1029/2020AV000298.","productDescription":"e2020AV000298, 22 p.","ipdsId":"IP-121974","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":452276,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2020av000298","text":"Publisher Index Page"},{"id":436365,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZN7BN8","text":"USGS data release","linkHelpText":"Modelled long-term wildfire occurrence probabilities in sagebrush-dominated ecosystems in the western US (1985 to 2019)"},{"id":436364,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Z85VET","text":"USGS data release","linkHelpText":"Historic and future trends in exotic annual grass (%) cover in the western US (1985 to 2019 and 2025 to 2040)"},{"id":399087,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Colorado, Idaho, Nevada, Oregon, Utah, Washington, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.150390625,\n 41.376808565702355\n ],\n [\n -103.88671875,\n 44.96479793033101\n ],\n [\n -110.74218749999999,\n 44.902577996288876\n ],\n [\n -112.8515625,\n 44.465151013519616\n ],\n [\n -114.2578125,\n 45.644768217751924\n ],\n [\n -114.345703125,\n 46.37725420510028\n ],\n [\n -116.71874999999999,\n 47.100044694025215\n ],\n [\n -117.861328125,\n 47.15984001304432\n ],\n [\n -117.861328125,\n 48.16608541901253\n ],\n [\n -121.46484375,\n 48.04870994288686\n ],\n [\n -122.78320312499999,\n 39.027718840211605\n ],\n [\n -121.904296875,\n 37.43997405227057\n ],\n [\n -114.345703125,\n 37.09023980307208\n ],\n [\n -111.796875,\n 37.16031654673677\n ],\n [\n -110.830078125,\n 40.17887331434696\n ],\n [\n -107.75390625,\n 39.70718665682654\n ],\n [\n -104.0625,\n 39.774769485295465\n ],\n [\n -104.150390625,\n 41.376808565702355\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"2","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-05-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Pastick, Neal 0000-0002-4321-6739","orcid":"https://orcid.org/0000-0002-4321-6739","contributorId":222683,"corporation":false,"usgs":true,"family":"Pastick","given":"Neal","email":"","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":false,"id":840909,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wylie, Bruce 0000-0002-7374-1083","orcid":"https://orcid.org/0000-0002-7374-1083","contributorId":201929,"corporation":false,"usgs":true,"family":"Wylie","given":"Bruce","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":840910,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rigge, Matthew B. 0000-0003-4471-8009 mrigge@usgs.gov","orcid":"https://orcid.org/0000-0003-4471-8009","contributorId":751,"corporation":false,"usgs":true,"family":"Rigge","given":"Matthew","email":"mrigge@usgs.gov","middleInitial":"B.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":840911,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dahal, Devendra 0000-0001-9594-1249 ddahal@usgs.gov","orcid":"https://orcid.org/0000-0001-9594-1249","contributorId":5622,"corporation":false,"usgs":true,"family":"Dahal","given":"Devendra","email":"ddahal@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":840912,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Boyte, Stephen P. 0000-0002-5462-3225","orcid":"https://orcid.org/0000-0002-5462-3225","contributorId":205374,"corporation":false,"usgs":true,"family":"Boyte","given":"Stephen P.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":840913,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jones, Matthew O.","contributorId":169805,"corporation":false,"usgs":false,"family":"Jones","given":"Matthew","email":"","middleInitial":"O.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":840914,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Allred, Brady W","contributorId":216378,"corporation":false,"usgs":false,"family":"Allred","given":"Brady","email":"","middleInitial":"W","affiliations":[{"id":39397,"text":"W.A. Franke College of Forestry and Conservation University of Montana, Missoula","active":true,"usgs":false}],"preferred":false,"id":840915,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Parajuli, Sujan 0000-0002-1652-3063","orcid":"https://orcid.org/0000-0002-1652-3063","contributorId":222684,"corporation":false,"usgs":true,"family":"Parajuli","given":"Sujan","email":"","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":840916,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wu, Zhuoting 0000-0001-7393-1832 zwu@usgs.gov","orcid":"https://orcid.org/0000-0001-7393-1832","contributorId":4953,"corporation":false,"usgs":true,"family":"Wu","given":"Zhuoting","email":"zwu@usgs.gov","affiliations":[{"id":498,"text":"Office of Land Remote Sensing (Geography)","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":840917,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70220492,"text":"70220492 - 2021 - Biogeography and ecology of Ostracoda in the U.S. northern Bering, Chukchi, and Beaufort Seas","interactions":[],"lastModifiedDate":"2021-05-17T12:47:37.844807","indexId":"70220492","displayToPublicDate":"2021-05-13T07:39:46","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Biogeography and ecology of Ostracoda in the U.S. northern Bering, Chukchi, and Beaufort Seas","docAbstract":"Ostracoda (bivalved Crustacea) comprise a significant part of the benthic meiofauna in the Pacific-Arctic region, including more than 50 species, many with identifiable ecological tolerances. These species hold potential as useful indicators of past and future ecosystem changes. In this study, we examined benthic ostracodes from nearly 300 surface sediment samples, >34,000 specimens, from three regions—the northern Bering, Chukchi and Beaufort Seas—to establish species’ ecology and distribution. Samples were collected during various sampling programs from 1970 through 2018 on the continental shelves at 20 to ~100m water depth. Ordination analyses using species’ relative frequencies identified six species, Normanicythere leioderma, Sarsicytheridea bradii, Paracyprideis pseudopunctillata, Semicytherura complanata, Schizocythere ikeyai, and Munseyella mananensis, as having diagnostic habitat ranges in bottom water temperatures, salinities, sediment substrates and/or food sources. Species relative abundances and distributions can be used to infer past bottom environmental conditions in sediment archives for paleo-reconstructions and to characterize potential changes in Pacific-Arctic ecosystems in future sampling studies. Statistical analyses further showed ostracode assemblages grouped by the summer water masses influencing the area. Offshore-to-nearshore transects of samples across different water masses showed that complex water mass characteristics, such as bottom temperature, productivity, as well as sediment texture, influenced the relative frequencies of ostracode species over small spatial scales. On the larger biogeographic scale, synoptic ordination analyses showed dominant species—N. leioderma (Bering Sea), P. pseudopunctillata (offshore Chukchi and Beaufort Seas), and S. bradii (all regions)—remained fairly constant over recent decades. However, during 2013–2018, northern Pacific species M. mananensis and S. ikeyai increased in abundance by small but significant proportions in the Chukchi Sea region compared to earlier years. It is yet unclear if these assemblage changes signify a meiofaunal response to changing water mass properties and if this trend will continue in the future. Our new ecological data on ostracode species and biogeography suggest these hypotheses can be tested with future benthic monitoring efforts.
Little information exists on the habitat use and feeding ecology of insectivorous bats in arid ecosystems, especially at and near uranium mines in northern Arizona, within the Grand Canyon watershed. In 2015–2016, we conducted mist-netting, nightly acoustic monitoring (>1 year), and diet analyses of bats, as well as insect sampling, at 2 uranium mines (Pinenut and Arizona 1) with water containment ponds. Because of physical barriers and limited general access to areas within the mine yard, mist-netting was limited to outside of the perimeter fence and away from the containment ponds. Mist-netting also occurred at 2 nearby sites that served as proxies to the mines. Bats captured directly at the mines included one pregnant Antrozous pallidus and 3 adult male Parastrellus hesperus. At the proxy sites, we captured 45 individuals identified as A. pallidus, Corynorhinus townsendii, Eptesicus fuscus, Euderma maculatum, Lasionycteris noctivagans, Myotis californicus, Myotis ciliolabrum, P. hesperus, and Tadarida brasiliensis. The nightly and seasonal presence of bats, as shown through acoustic recordings at each mine, coincided with the seasonal migratory and hibernation behaviors of the bat species. Statistical comparisons of acoustic recordings with precipitation data collected over one year show that seasonal monsoon rains generally had a negative effect on the nightly activity and presence of bats. Diets of P. hesperus from both mines were comprised mostly of coleopterans but also included smaller volumes of Hymenoptera, Hemiptera, Lepidoptera, Diptera, and Neuroptera. The diet of A. pallidus was comprised solely of Coleoptera. Diets of bat species from the proxy sites were characteristic of their known feeding ecology, which ranged from the consumption of soft-bodied insects (e.g., moths) by C. townsendii to the consumption of hard-bodied insects (e.g., beetles) by E. fuscus. Ultimately, the increased knowledge of the natural history of bats through multiple methods of data collection allows for a better understanding of complex arid ecosystems. It also provides resources needed for the management of habitat associated with alternative energy, such as uranium mining.
Pinyon and juniper expansion into sagebrush ecosystems is one of the major challenges facing land managers in the Great Basin. Effective pinyon and juniper treatment requires maps that accurately and precisely depict tree location and degree of woodland development so managers can target restoration efforts for early stages of pinyon and juniper expansion. However, available remotely sensed layers that cover a regional spatial extent lack the spatial resolution or accuracy to meet this need. Accuracy can be improved using object-based image analysis methods such as automated feature extraction, which has proven successful in accurately classifying land cover at the site-level but to date has yet to be applied to regional extents due to time and computational limitations. Using Feature Analyst™, we implement our framework with 1-m2 reference imagery provided by National Agricultural Imagery Program to classify conifers across Nevada and northeastern California. Our resulting binary conifer map has an overall accuracy of 86%. We discuss the advantages to accuracy and precision our framework provides compared to other classification methods
","language":"English","publisher":"Elsevier","doi":"10.1016/j.mex.2021.101379","usgsCitation":"Roth, C.L., Coates, P.S., Gustafson, K.B., Chenaille, M.P., Ricca, M.A., Sanchez-Chopitea, E., and Casazza, M.L., 2021, A customized framework for regional classification of conifers using automated feature extraction: MethodsX, v. 8, 101379, 16 p., https://doi.org/10.1016/j.mex.2021.101379.","productDescription":"101379, 16 p.","ipdsId":"IP-098781","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":452330,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.mex.2021.101379","text":"Publisher Index Page"},{"id":386335,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon, California, Nevada, Utah","otherGeospatial":"the Great Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.3671875,\n 41.44272637767212\n ],\n [\n -118.21289062499999,\n 43.99281450048989\n ],\n [\n -120.62988281249999,\n 44.5278427984555\n ],\n [\n -122.34374999999999,\n 41.934976500546604\n ],\n [\n -120.62988281249999,\n 38.51378825951165\n ],\n [\n -116.5869140625,\n 35.42486791930558\n ],\n [\n -115.31249999999999,\n 37.09023980307208\n ],\n [\n -114.0380859375,\n 36.4566360115962\n ],\n [\n -114.08203125,\n 38.06539235133249\n ],\n [\n -111.22558593749999,\n 38.09998264736481\n ],\n [\n -111.09374999999999,\n 42.09822241118974\n ],\n [\n -116.3671875,\n 41.44272637767212\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Roth, Cali L. 0000-0001-9077-2765 croth@usgs.gov","orcid":"https://orcid.org/0000-0001-9077-2765","contributorId":174422,"corporation":false,"usgs":true,"family":"Roth","given":"Cali","email":"croth@usgs.gov","middleInitial":"L.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":817208,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coates, Peter S. 0000-0003-2672-9994 pcoates@usgs.gov","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":3263,"corporation":false,"usgs":true,"family":"Coates","given":"Peter","email":"pcoates@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":817209,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gustafson, K. Benjamin 0000-0003-3530-0372 kgustafson@usgs.gov","orcid":"https://orcid.org/0000-0003-3530-0372","contributorId":166818,"corporation":false,"usgs":true,"family":"Gustafson","given":"K.","email":"kgustafson@usgs.gov","middleInitial":"Benjamin","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":817210,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chenaille, Michael P. 0000-0003-3387-7899 mchenaille@usgs.gov","orcid":"https://orcid.org/0000-0003-3387-7899","contributorId":194661,"corporation":false,"usgs":true,"family":"Chenaille","given":"Michael","email":"mchenaille@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":817211,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ricca, Mark A. 0000-0003-1576-513X mark_ricca@usgs.gov","orcid":"https://orcid.org/0000-0003-1576-513X","contributorId":139103,"corporation":false,"usgs":true,"family":"Ricca","given":"Mark","email":"mark_ricca@usgs.gov","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":817212,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sanchez-Chopitea, Erika 0000-0003-2942-8417 esanchez-chopitea@usgs.gov","orcid":"https://orcid.org/0000-0003-2942-8417","contributorId":199468,"corporation":false,"usgs":true,"family":"Sanchez-Chopitea","given":"Erika","email":"esanchez-chopitea@usgs.gov","affiliations":[],"preferred":true,"id":817213,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":817214,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70220388,"text":"70220388 - 2021 - Using the Landsat Burned Area products to derive fire history relevant for fire management and conservation in the state of Florida, southeastern USA","interactions":[],"lastModifiedDate":"2024-05-16T15:27:57.216807","indexId":"70220388","displayToPublicDate":"2021-05-08T06:59:24","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5678,"text":"Fire","active":true,"publicationSubtype":{"id":10}},"title":"Using the Landsat Burned Area products to derive fire history relevant for fire management and conservation in the state of Florida, southeastern USA","docAbstract":"Development of comprehensive spatially explicit fire occurrence data remains one of the most critical needs for fire managers globally, and especially for conservation across the southeastern United States. Not only are many endangered species and ecosystems in that region reliant on frequent fire, but fire risk analysis, prescribed fire planning, and fire behavior modeling are sensitive to fire history due to the long growing season and high vegetation productivity. Spatial data that map burned areas over time provide critical information for evaluating management successes. However, existing fire data have undocumented shortcomings that limit their use when detailing the effectiveness of fire management at state and regional scales. Here, we assessed information in existing fire datasets for Florida and the Landsat Burned Area products based on input from the fire management community. We considered the potential of different datasets to track the spatial extents of fires and derive fire history metrics (e.g., time since last burn, fire frequency, and seasonality). We found that burned areas generated by applying a 90% threshold to the Landsat burn probability product matched patterns recorded and observed by fire managers at three pilot areas. We then created fire history metrics for the entire state from the modified Landsat Burned Area product. Finally, to show their potential application for conservation management, we compared fire history metrics across ownerships for natural pinelands, where prescribed fire is frequently applied. Implications of this effort include increased awareness around conservation and fire management planning efforts and an extension of derivative products regionally or globally.
","language":"English","publisher":"MDPI","doi":"10.3390/fire4020026","usgsCitation":"Teske, C., Vanderhoof, M.K., Hawbaker, T., Noble, J., and Hires, J.K., 2021, Using the Landsat Burned Area products to derive fire history relevant for fire management and conservation in the state of Florida, southeastern USA: Fire, v. 4, no. 2, 26, 21 p., https://doi.org/10.3390/fire4020026.","productDescription":"26, 21 p.","ipdsId":"IP-126697","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":452347,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/fire4020026","text":"Publisher Index Page"},{"id":385562,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Florida Panhandle","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.64892578125,\n 29.554345125748267\n ],\n [\n -83.43017578125,\n 29.554345125748267\n ],\n [\n -83.43017578125,\n 30.939924331023445\n ],\n [\n -87.64892578125,\n 30.939924331023445\n ],\n [\n -87.64892578125,\n 29.554345125748267\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"4","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-05-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Teske, Casey","contributorId":224732,"corporation":false,"usgs":false,"family":"Teske","given":"Casey","email":"","affiliations":[{"id":36874,"text":"Tall Timbers Research Station","active":true,"usgs":false}],"preferred":false,"id":815369,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vanderhoof, Melanie K. 0000-0002-0101-5533 mvanderhoof@usgs.gov","orcid":"https://orcid.org/0000-0002-0101-5533","contributorId":168395,"corporation":false,"usgs":true,"family":"Vanderhoof","given":"Melanie","email":"mvanderhoof@usgs.gov","middleInitial":"K.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":815372,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hawbaker, Todd 0000-0003-0930-9154 tjhawbaker@usgs.gov","orcid":"https://orcid.org/0000-0003-0930-9154","contributorId":568,"corporation":false,"usgs":true,"family":"Hawbaker","given":"Todd","email":"tjhawbaker@usgs.gov","affiliations":[{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":815371,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Noble, Joe","contributorId":257938,"corporation":false,"usgs":false,"family":"Noble","given":"Joe","email":"","affiliations":[{"id":36874,"text":"Tall Timbers Research Station","active":true,"usgs":false}],"preferred":false,"id":815370,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hires, J. Kevin","contributorId":257941,"corporation":false,"usgs":false,"family":"Hires","given":"J.","email":"","middleInitial":"Kevin","affiliations":[{"id":36874,"text":"Tall Timbers Research Station","active":true,"usgs":false}],"preferred":false,"id":815373,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70220449,"text":"70220449 - 2021 - Stopover ecology of red knots in southwestern James Bay during southbound migration","interactions":[],"lastModifiedDate":"2021-06-30T18:53:10.924923","indexId":"70220449","displayToPublicDate":"2021-05-06T07:57:55","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Stopover ecology of red knots in southwestern James Bay during southbound migration","docAbstract":"Many shorebirds rely on small numbers of staging sites during long annual migrations. Numerous shorebird species are declining and understanding the importance of these staging sites is important for successful conservation. We surveyed endangered rufa red knots (Calidris canutus rufa) staging in James Bay, Ontario, Canada, during southbound migration in 2017 and 2018. We used mark‐resight data and count data in an integrated Bayesian analysis to quantify migration phenology, estimate passage population size, and model the age structure of the stopover population. Many adult red knots arrived in James Bay in a single wave in early August in 2017, whereas adult red knots arrived in multiple smaller waves in July and mid‐August in 2018. These waves may correspond with breeding phenology where more red knots bred successfully and arrived in one large event in 2017 and the higher number of earlier arrivals in July 2018 may have been failed breeders. We included a binomial generalized linear model in the integrated analysis to estimate that 20% and 10% of staging red knots were juveniles in 2017 and 2018, respectively. In future applications, this method could provide a metric to assess breeding performance and develop our understanding of its role in population declines. Overall, we estimated that up to 23% of the estimated rufa red knot population staged in southwestern James Bay for an average of 10–12 days. The region is a key staging site for endangered red knots and could be included in conservation planning.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.22059","usgsCitation":"MacDonald, A., Smith, P., Friis, C., Lyons, J., Aubry, Y., and Nol, E., 2021, Stopover ecology of red knots in southwestern James Bay during southbound migration: Journal of Wildlife Management, v. 85, no. 5, p. 932-944, https://doi.org/10.1002/jwmg.22059.","productDescription":"13 p.","startPage":"932","endPage":"944","ipdsId":"IP-123446","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":385641,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada","otherGeospatial":"James Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.8369140625,\n 51.17934297928927\n ],\n [\n -77.2998046875,\n 51.17934297928927\n ],\n [\n -77.2998046875,\n 55.229023057406344\n ],\n [\n -82.8369140625,\n 55.229023057406344\n ],\n [\n -82.8369140625,\n 51.17934297928927\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"85","issue":"5","noUsgsAuthors":false,"publicationDate":"2021-05-06","publicationStatus":"PW","contributors":{"authors":[{"text":"MacDonald, Amie 0000-0002-6424-7761","orcid":"https://orcid.org/0000-0002-6424-7761","contributorId":258022,"corporation":false,"usgs":false,"family":"MacDonald","given":"Amie","email":"","affiliations":[{"id":36679,"text":"Trent University","active":true,"usgs":false}],"preferred":false,"id":815564,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Paul","contributorId":147639,"corporation":false,"usgs":false,"family":"Smith","given":"Paul","affiliations":[],"preferred":false,"id":815565,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Friis, Christian","contributorId":194605,"corporation":false,"usgs":false,"family":"Friis","given":"Christian","email":"","affiliations":[],"preferred":false,"id":815566,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lyons, James E. 0000-0002-9810-8751","orcid":"https://orcid.org/0000-0002-9810-8751","contributorId":210574,"corporation":false,"usgs":true,"family":"Lyons","given":"James E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":815567,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Aubry, Yves","contributorId":202279,"corporation":false,"usgs":false,"family":"Aubry","given":"Yves","email":"","affiliations":[],"preferred":false,"id":815568,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nol, Erica","contributorId":216259,"corporation":false,"usgs":false,"family":"Nol","given":"Erica","email":"","affiliations":[{"id":36679,"text":"Trent University","active":true,"usgs":false}],"preferred":false,"id":815569,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70221165,"text":"70221165 - 2021 - When a typical jumper skips: Itineraries and staging habitats used by Red Knots (Calidris canutus piersmai) migrating between northwest Australia and the New Siberian Islands","interactions":[],"lastModifiedDate":"2021-10-06T14:56:44.934507","indexId":"70221165","displayToPublicDate":"2021-05-06T07:07:45","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1961,"text":"Ibis","active":true,"publicationSubtype":{"id":10}},"title":"When a typical jumper skips: Itineraries and staging habitats used by Red Knots (Calidris canutus piersmai) migrating between northwest Australia and the New Siberian Islands","docAbstract":"The ecological reasons for variation in avian migration, with some populations migrating across thousands of kilometres between breeding and non-breeding areas with one or few refuelling stops, in contrast to others that stop more often, remain to be pinned down. Red Knots Calidris canutus are a textbook example of a shorebird species that makes long migrations with only a few stops. Recognizing that such behaviours are not necessarily species-specific but determined by ecological context, we here provide a description of the migrations of a relatively recently described subspecies (piersmai). Based on data from tagging of Red Knots on the terminal non-breeding grounds in northwest Australia with 4.5- and 2.5-g solar-powered Platform Terminal Transmitters (PTTs) and 1.0-g geolocators, we obtained information on 19 route-records of 17 individuals, resulting in seven complete return migrations. We confirm published evidence that Red Knots of the piersmai subspecies migrate from NW Australia and breed on the New Siberian Islands in the Russian Arctic and that they stage along the coasts of southeastern Asia, especially in the northern Yellow Sea in China. Red Knots arrived on the tundra breeding grounds from 8 June onwards. Southward departures mainly occurred in the last week of July and the first week of August. We documented six non-stop flights of over c. 5000 km (with a maximum of 6500 km, lasting 6.6 days). Nevertheless, rather than staging at a single location for multiple weeks halfway during migration, piersmai-knots made several stops of up to a week. This was especially evident during northward migration, when birds often stopped along the way in southeast Asia and ‘hugged’ the coast of China, thus flying an additional 1000–1500 km compared with the shortest possible (great circle route) flights between NW Australia and the Yellow Sea. The birds staged longest in areas in northern China, along the shores of Bohai Bay and upper Liaodong Bay, where the bivalve Potamocorbula laevis, known as a particularly suitable food for Red Knots, was present. The use of multiple food-rich stopping sites during northward migration by piersmai is atypical among subspecies of Red Knots. Although piersmai apparently has the benefit of multiple suitable stopping areas along the flyway, it is a subspecies in decline and their mortality away from the NW Australian non-breeding grounds has been elevated.
","language":"English","publisher":"Wiley","doi":"10.1111/ibi.12964","usgsCitation":"Piersma, T., Kok, E., Hassell, C.J., Verkuil, Y.I., Lei, G., Peng, H., Rakhimberdiev, E., Howey, P., Tibbitts, T., Chan, Y., and Karagicheva, J., 2021, When a typical jumper skips: Itineraries and staging habitats used by Red Knots (Calidris canutus piersmai) migrating between northwest Australia and the New Siberian Islands: Ibis, v. 163, no. 4, p. 1235-1251, https://doi.org/10.1111/ibi.12964.","productDescription":"17 p.","startPage":"1235","endPage":"1251","ipdsId":"IP-122078","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":452387,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ibi.12964","text":"Publisher Index Page"},{"id":386193,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Australia, China, Russia, Vietnam","otherGeospatial":"New Siberian Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 120.234375,\n -19.973348786110602\n ],\n [\n 127.79296875,\n -13.581920900545844\n ],\n [\n 151.69921875,\n 74.86788912917916\n ],\n [\n 137.98828125,\n 76.14295846479848\n ],\n [\n 125.33203125,\n 73.32785809840696\n ],\n [\n 106.171875,\n 11.695272733029402\n ],\n [\n 120.234375,\n -19.973348786110602\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"163","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-05-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Piersma, Theunis 0000-0001-9668-466X","orcid":"https://orcid.org/0000-0001-9668-466X","contributorId":203123,"corporation":false,"usgs":false,"family":"Piersma","given":"Theunis","email":"","affiliations":[{"id":36570,"text":"NIOZ Royal Netherlands Institute for Sea Research","active":true,"usgs":false}],"preferred":false,"id":816922,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kok, Eva","contributorId":225537,"corporation":false,"usgs":false,"family":"Kok","given":"Eva","email":"","affiliations":[{"id":36570,"text":"NIOZ Royal Netherlands Institute for Sea Research","active":true,"usgs":false}],"preferred":false,"id":816944,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hassell, Chris J.","contributorId":127818,"corporation":false,"usgs":false,"family":"Hassell","given":"Chris","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":816942,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Verkuil, Yvonne I.","contributorId":194622,"corporation":false,"usgs":false,"family":"Verkuil","given":"Yvonne","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":816945,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lei, Guangchun","contributorId":259278,"corporation":false,"usgs":false,"family":"Lei","given":"Guangchun","email":"","affiliations":[],"preferred":false,"id":816946,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Peng, He-Bo","contributorId":218155,"corporation":false,"usgs":false,"family":"Peng","given":"He-Bo","email":"","affiliations":[{"id":39765,"text":"University of Groningen, the Netherlands; Royal Netherlands Institute for Sea Research; Fudan University, Shanghai, China","active":true,"usgs":false}],"preferred":false,"id":816943,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rakhimberdiev, Eldar","contributorId":209701,"corporation":false,"usgs":false,"family":"Rakhimberdiev","given":"Eldar","email":"","affiliations":[{"id":36570,"text":"NIOZ Royal Netherlands Institute for Sea Research","active":true,"usgs":false}],"preferred":false,"id":816948,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Howey, Paul","contributorId":225538,"corporation":false,"usgs":false,"family":"Howey","given":"Paul","email":"","affiliations":[{"id":41157,"text":"Microwave Telemetry Ltd","active":true,"usgs":false}],"preferred":false,"id":816949,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Karagicheva, Julia","contributorId":209703,"corporation":false,"usgs":false,"family":"Karagicheva","given":"Julia","email":"","affiliations":[{"id":36570,"text":"NIOZ Royal Netherlands Institute for Sea Research","active":true,"usgs":false}],"preferred":false,"id":816947,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Tibbitts, T. Lee 0000-0002-0290-7592","orcid":"https://orcid.org/0000-0002-0290-7592","contributorId":224104,"corporation":false,"usgs":true,"family":"Tibbitts","given":"T. Lee","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":816923,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Chan, Ying-Chi","contributorId":167762,"corporation":false,"usgs":false,"family":"Chan","given":"Ying-Chi","email":"","affiliations":[{"id":24822,"text":"Department of Marine Ecology, NIOZ Royal Netherlands Institute for Sea Research","active":true,"usgs":false}],"preferred":false,"id":816924,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70231639,"text":"70231639 - 2021 - Geomorphic expression and slip rate of the Fairweather fault, southeast Alaska, and evidence for predecessors of the 1958 rupture","interactions":[],"lastModifiedDate":"2022-05-17T11:54:18.758519","indexId":"70231639","displayToPublicDate":"2021-05-06T06:46:51","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Geomorphic expression and slip rate of the Fairweather fault, southeast Alaska, and evidence for predecessors of the 1958 rupture","docAbstract":"Active traces of the southern Fairweather fault were revealed by light detection and ranging (lidar) and show evidence for transpressional deformation between North America and the Yakutat block in southeast Alaska. We map the Holocene geomorphic expression of tectonic deformation along the southern 30 km of the Fairweather fault, which ruptured in the 1958 moment magnitude 7.8 earthquake. Digital maps of surficial geology, geomorphology, and active faults illustrate both strike-slip and dip-slip deformation styles within a 10°–30° double restraining bend where the southern Fairweather fault steps offshore to the Queen Charlotte fault. We measure offset landforms along the fault and calibrate legacy 14C data to reassess the rate of Holocene strike-slip motion (≥49 mm/yr), which corroborates published estimates that place most of the plate boundary motion on the Fairweather fault. Our slip-rate estimates allow a component of oblique-reverse motion to be accommodated by contractional structures west of the Fairweather fault consistent with geodetic block models. Stratigraphic and structural relations in hand-dug excavations across two active fault strands provide an incomplete paleoseismic record including evidence for up to six surface ruptures in the past 5600 years, and at least two to four events in the past 810 years. The incomplete record suggests an earthquake recurrence interval of ≥270 years—much longer than intervals <100 years implied by published slip rates and expected earthquake displacements. Our paleoseismic observations and map of active traces of the southern Fairweather fault illustrate the complexity of transpressional deformation and seismic potential along one of Earth's fastest strike-slip plate boundaries.
Preserving biodiversity and its many components is a priority of conservation science and how to efficiently allocate resources to preserve healthy populations of as many species, habitats, and ecosystems as possible. We used the U.S. Geological Survey (USGS) Gap Analysis Project (GAP) species models released in 2018, which identify predicted habitats for terrestrial vertebrates in the conterminous United States, to illustrate hotspots of biodiversity for the major taxonomic groups. This collection represents the first complete compilation of terrestrial vertebrate species models for the conterminous United States (U.S. Geological Survey (USGS), 2018a). We used the species models but not the available subspecies models; this resulted in the inclusion of 282 amphibian models, 621 bird models, 365 mammal models, and 322 reptiles in our analysis. We also used population trend information and made spatial queries to characterize species in three dimensions: geographic range (small or large), habitat breadth (narrow or wide), and population trend (decreasing vs stable or increasing). This characterization allowed us to divide the species into eight groups (A-H) with similar characteristics. Group A species (large geographic range, wide habitat breadth, and stable or increasing population trend) are species that are common now with no indication of becoming rare. Species B-H have theoretical or known characteristics that could lead them to become rare with the H species exhibiting small geographic range, narrow habitat breadth, and decreasing population trend. Finally, we evaluated the prevalence of mapped habitat on protected lands for each species, exploring the patterns of representation in the rare species groups by ecoregion. The species we identified with population and habitat use characteristics that potentially predispose them to being or becoming rare represented a large percentage of each taxon. Potentially rare species were widely distributed among ecoregions. Of the 20 ecoregions in the country, 14 have a greater number of rare species than the national average for at least one taxon. Protection of the habitat for the majority of these rare species is below that recommended (17% of available habitat) by the Convention on Biological Diversity (CBD). The Everglades ecoregion was the only ecoregion that protected more than half of its rare or potentially rare species.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.gecco.2021.e01598","usgsCitation":"Davidson, A., Dunn, L., Gergely, K., McKerrow, A., Williams, S.G., and Case, M., 2021, Refining the coarse filter approach: Using habitat-based species models to identify rarity and vulnerabilities in the protection of U.S. biodiversity: Global Ecology and Conservation, v. 28, e01598, 19 p., https://doi.org/10.1016/j.gecco.2021.e01598.","productDescription":"e01598, 19 p.","ipdsId":"IP-101927","costCenters":[{"id":38128,"text":"Science Analytics and Synthesis","active":true,"usgs":true}],"links":[{"id":452441,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gecco.2021.e01598","text":"Publisher Index Page"},{"id":386468,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -127.61718749999999,\n 25.16517336866393\n ],\n [\n -63.984375,\n 25.16517336866393\n ],\n [\n -63.984375,\n 51.83577752045248\n ],\n [\n -127.61718749999999,\n 51.83577752045248\n ],\n [\n -127.61718749999999,\n 25.16517336866393\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"28","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Davidson, Anne","contributorId":197967,"corporation":false,"usgs":false,"family":"Davidson","given":"Anne","email":"","affiliations":[],"preferred":false,"id":817517,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dunn, Leah","contributorId":217944,"corporation":false,"usgs":false,"family":"Dunn","given":"Leah","email":"","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":817518,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gergely, Kevin 0000-0002-4379-2189","orcid":"https://orcid.org/0000-0002-4379-2189","contributorId":208371,"corporation":false,"usgs":true,"family":"Gergely","given":"Kevin","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":817519,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McKerrow, Alexa 0000-0002-8312-2905 amckerrow@usgs.gov","orcid":"https://orcid.org/0000-0002-8312-2905","contributorId":127753,"corporation":false,"usgs":true,"family":"McKerrow","given":"Alexa","email":"amckerrow@usgs.gov","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":817520,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Williams, Steven G. 0000-0003-3760-6818","orcid":"https://orcid.org/0000-0003-3760-6818","contributorId":215501,"corporation":false,"usgs":false,"family":"Williams","given":"Steven","email":"","middleInitial":"G.","affiliations":[{"id":39268,"text":"North Carolina State University, NC Cooperative Fish & Wildlife Research Unit","active":true,"usgs":false}],"preferred":false,"id":817521,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Case, Mackenzie 0000-0002-5657-9133","orcid":"https://orcid.org/0000-0002-5657-9133","contributorId":260200,"corporation":false,"usgs":false,"family":"Case","given":"Mackenzie","email":"","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":817522,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70220307,"text":"70220307 - 2021 - Understanding sea lamprey populations in the Great Lakes prior to broad implementation of sea lamprey control","interactions":[],"lastModifiedDate":"2022-01-06T17:49:10.604273","indexId":"70220307","displayToPublicDate":"2021-05-03T07:21:10","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Understanding sea lamprey populations in the Great Lakes prior to broad implementation of sea lamprey control","docAbstract":"Control of invasive sea lamprey in the Great Lakes with a selective pesticide (lampricide) that targeted larval sea lamprey began in the late 1950's and continues to be one of the main methods for control. Although the Great Lakes Fishery Commission, which was formed with the mandate of controlling sea lamprey, often expresses the success of the sea lamprey control program in terms of percent reduction from lake-wide pre-lampricide control adult sea lamprey abundances, there remains a large amount of uncertainty surrounding these estimates. In this study, we gathered historical data on adult sea lamprey captures from trapping efforts from the mid-1950's through the late 1970's to better understand pre-control abundance. We used this information to estimate lake-wide population abundances of adult sea lamprey using a weighted linear regression that includes environmental and lampricide treatment predictor variables. We varied trapping efficiency for early trapping data to evaluate the uncertainty in abundance estimates. Pre-control adult sea lamprey abundances in all lakes were much greater than current population sizes, but estimates were quite sensitive to trapping efficiency. In Lake Superior, declines in abundance aligned with increases in control efforts, but in other lakes, declines were occurring prior to the onset of lampricide application, perhaps because of a loss of prey. We suggest that previous estimates of pre-control adult sea lamprey abundance may have been underestimated unless trapping efficiency was greater than what is currently achieved in the basin.