During the last decades, soil organic carbon (SOC) attracted the attention of a much wider array of specialists beyond agriculture and soil science, as it was proven to be one of the most crucial components of the earth’s climate system, which has a great potential to be managed by humans. Soils as a carbon pool are one of the key factors in several Sustainable Development Goals, in particular Goal 15, “Protect, restore and promote sustainable use of terrestrial ecosystems, sustainably manage forests, combat desertification and halt and reverse land degradation and halt biodiversity loss” with the SOC stock being explicitly cited in Indicator 15.3.1.
This technical manual is the first attempt to gather, in a standardized format, the existing data on the impacts of the main soil management practices on SOC content in a wide array of environments, including the advantages, drawbacks, and constraints. This manual presents different sustainable soil management (SSM) practices at different scales and in different contexts, supported by case studies that have been shown with quantitative data to have a positive effect on SOC stocks and successful experiences of SOC sequestration in practical field applications
Volume 2 includes a description of hot spots of SOC stocks. This manual defines hot spots of SOC as areas that represent a proportionally little of the global land surface but on which SOC storage is highly effective; bright spots as large land areas with low SOC stocks per km2 that represent a potential for further carbon sequestration.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Recarbonizing global soils – A technical manual of recommended management practices","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"Food and Agriculture Organization of the United Nations","usgsCitation":"Tangen, B., and Bansal, S., 2021, Wetlands, 19 p.","productDescription":"19 p.","startPage":"36","endPage":"54","ipdsId":"IP-121703","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":389967,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.fao.org/documents/card/en/c/cb6378en/"},{"id":389968,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Tangen, Brian 0000-0001-5157-9882 btangen@usgs.gov","orcid":"https://orcid.org/0000-0001-5157-9882","contributorId":167277,"corporation":false,"usgs":true,"family":"Tangen","given":"Brian","email":"btangen@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":824243,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bansal, Sheel 0000-0003-1233-1707 sbansal@usgs.gov","orcid":"https://orcid.org/0000-0003-1233-1707","contributorId":167295,"corporation":false,"usgs":true,"family":"Bansal","given":"Sheel","email":"sbansal@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":824244,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70237360,"text":"70237360 - 2021 - Predicting water temperature dynamics of unmonitored lakes with meta-transfer learning","interactions":[],"lastModifiedDate":"2022-10-11T16:24:49.683141","indexId":"70237360","displayToPublicDate":"2021-07-01T11:21:09","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Predicting water temperature dynamics of unmonitored lakes with meta-transfer learning","docAbstract":"Most environmental data come from a minority of well-monitored sites. An ongoing challenge in the environmental sciences is transferring knowledge from monitored sites to unmonitored sites. Here, we demonstrate a novel transfer-learning framework that accurately predicts depth-specific temperature in unmonitored lakes (targets) by borrowing models from well-monitored lakes (sources). This method, meta-transfer learning (MTL), builds a meta-learning model to predict transfer performance from candidate source models to targets using lake attributes and candidates' past performance. We constructed source models at 145 well-monitored lakes using calibrated process-based (PB) modeling and a recently developed approach called process-guided deep learning (PGDL). We applied MTL to either PB or PGDL source models (PB-MTL or PGDL-MTL, respectively) to predict temperatures in 305 target lakes treated as unmonitored in the Upper Midwestern United States. We show significantly improved performance relative to the uncalibrated PB General Lake Model, where the median root mean squared error (RMSE) for the target lakes is 2.52°C. PB-MTL yielded a median RMSE of 2.43°C; PGDL-MTL yielded 2.16°C; and a PGDL-MTL ensemble of nine sources per target yielded 1.88°C. For sparsely monitored target lakes, PGDL-MTL often outperformed PGDL models trained on the target lakes themselves. Differences in maximum depth between the source and target were consistently the most important predictors. Our approach readily scales to thousands of lakes in the Midwestern United States, demonstrating that MTL with meaningful predictor variables and high-quality source models is a promising approach for many kinds of unmonitored systems and environmental variables.","language":"English","publisher":"Wiley","doi":"10.1029/2021WR029579","usgsCitation":"Willard, J., Read, J., Appling, A.P., Oliver, S.K., Jia, X., and Kumar, V., 2021, Predicting water temperature dynamics of unmonitored lakes with meta-transfer learning: Water Resources Research, v. 57, no. 7, e2021WR029579, 20 p., https://doi.org/10.1029/2021WR029579.","productDescription":"e2021WR029579, 20 p.","ipdsId":"IP-119147","costCenters":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"links":[{"id":451661,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2021wr029579","text":"Publisher Index Page"},{"id":436285,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9I00WFR","text":"USGS data release","linkHelpText":"Data release: Predicting Water Temperature Dynamics of Unmonitored Lakes with Meta Transfer Learning (Provisional Data Release)"},{"id":408165,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"57","issue":"7","noUsgsAuthors":false,"publicationDate":"2021-06-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Willard, Jared","contributorId":237808,"corporation":false,"usgs":false,"family":"Willard","given":"Jared","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":854261,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Read, Jordan 0000-0002-3888-6631","orcid":"https://orcid.org/0000-0002-3888-6631","contributorId":221385,"corporation":false,"usgs":true,"family":"Read","given":"Jordan","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":854262,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Appling, Alison P. 0000-0003-3638-8572 aappling@usgs.gov","orcid":"https://orcid.org/0000-0003-3638-8572","contributorId":150595,"corporation":false,"usgs":true,"family":"Appling","given":"Alison","email":"aappling@usgs.gov","middleInitial":"P.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":854263,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Oliver, Samantha K. 0000-0001-5668-1165","orcid":"https://orcid.org/0000-0001-5668-1165","contributorId":211886,"corporation":false,"usgs":true,"family":"Oliver","given":"Samantha","email":"","middleInitial":"K.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":854264,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jia, Xiaowei 0000-0001-8544-5233","orcid":"https://orcid.org/0000-0001-8544-5233","contributorId":237807,"corporation":false,"usgs":false,"family":"Jia","given":"Xiaowei","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":854265,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kumar, Vipin","contributorId":237812,"corporation":false,"usgs":false,"family":"Kumar","given":"Vipin","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":854266,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70248236,"text":"70248236 - 2021 - Exploring GPS observations of postseismic deformation following the 2012 MW7.8 Haida Gwaii and 2013 MW7.5 Craig, Alaska Earthquakes: Implications for viscoelastic Earth structure","interactions":[],"lastModifiedDate":"2023-09-05T15:18:59.650382","indexId":"70248236","displayToPublicDate":"2021-07-01T10:09:17","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Exploring GPS observations of postseismic deformation following the 2012 MW7.8 Haida Gwaii and 2013 MW7.5 Craig, Alaska Earthquakes: Implications for viscoelastic Earth structure","title":"Exploring GPS observations of postseismic deformation following the 2012 MW7.8 Haida Gwaii and 2013 MW7.5 Craig, Alaska Earthquakes: Implications for viscoelastic Earth structure","docAbstract":"The Queen Charlotte-Fairweather Fault (QC-FF) system off the coast of British Columbia and southeast Alaska is a highly active dextral strike-slip plate boundary that accommodates ∼50 mm/yr of relative motion between the Pacific and North America plates. Nine MW ≥ 6.7 earthquakes have occurred along the QC-FF system since 1910, including a MS(G-R)8.1 event in 1949. Two recent earthquakes, the October 28, 2012 Haida Gwaii (MW7.8) and January 5, 2013 Craig, Alaska (MW7.5) events, produced postseismic transient deformation that was recorded in the motions of 25 nearby continuous Global Positioning System (cGPS) stations. Here, we use 5+ yr of cGPS measurements to characterize the underlying mechanisms of postseismic deformation and to constrain the viscosity structure of the upper mantle surrounding the QC-FF. We construct forward models of viscoelastic deformation driven by coseismic stress changes from these two earthquakes and explore a large set of laterally heterogeneous viscosity structures that incorporate a relatively weak back-arc domain; we then evaluate each model based on its fit to the postseismic signals in our cGPS data. In determining best-fit model structures, we additionally incorporate the effects of afterslip following the 2012 event. Our results indicate the occurrence of a combination of temporally decaying afterslip and vigorous viscoelastic relaxation of the mantle asthenosphere. In addition, our best-fit viscosity structure (transient viscosity of 1.4–2.0 × 1018 Pa s; steady-state viscosity of 1019 Pa s) is consistent with the range of upper mantle viscosities determined in previous studies of glacial isostatic rebound and postseismic deformation.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021JB021891","usgsCitation":"Guns, K.A., Pollitz, F., Lay, T., and Yue, H., 2021, Exploring GPS observations of postseismic deformation following the 2012 MW7.8 Haida Gwaii and 2013 MW7.5 Craig, Alaska Earthquakes: Implications for viscoelastic Earth structure: Journal of Geophysical Research B: Solid Earth, v. 126, no. 7, e2021JB021891, 20 p., https://doi.org/10.1029/2021JB021891.","productDescription":"e2021JB021891, 20 p.","ipdsId":"IP-127502","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":420483,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Alaska, British Columbia","city":"Craig","otherGeospatial":"Haida Gwaii Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -134.04582537099918,\n 55.778120902444044\n ],\n [\n -134.04582537099918,\n 55.08543087867997\n ],\n [\n -132.168788545775,\n 55.08543087867997\n ],\n [\n -132.168788545775,\n 55.778120902444044\n ],\n [\n -134.04582537099918,\n 55.778120902444044\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -132.70446739512911,\n 53.158925565323756\n ],\n [\n -132.34949768033022,\n 52.76369069159804\n ],\n [\n -131.7793948050469,\n 52.469804491078975\n ],\n [\n -131.66107156678072,\n 52.29252484773727\n ],\n [\n -130.97264545323122,\n 51.88274035718925\n ],\n [\n -130.75751229274715,\n 51.94245878634544\n ],\n [\n -131.7471248309743,\n 53.33271351252088\n ],\n [\n -132.30647104823325,\n 53.16537474581318\n ],\n [\n -132.70446739512911,\n 53.158925565323756\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"126","issue":"7","noUsgsAuthors":false,"publicationDate":"2021-07-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Guns, Katherine A.","contributorId":329359,"corporation":false,"usgs":false,"family":"Guns","given":"Katherine","email":"","middleInitial":"A.","affiliations":[{"id":16619,"text":"UCSD","active":true,"usgs":false}],"preferred":false,"id":882060,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pollitz, Frederick 0000-0002-4060-2706 fpollitz@usgs.gov","orcid":"https://orcid.org/0000-0002-4060-2706","contributorId":139578,"corporation":false,"usgs":true,"family":"Pollitz","given":"Frederick","email":"fpollitz@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":882061,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lay, Thorne","contributorId":328838,"corporation":false,"usgs":false,"family":"Lay","given":"Thorne","affiliations":[{"id":6948,"text":"UC Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":882062,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yue, Han","contributorId":329362,"corporation":false,"usgs":false,"family":"Yue","given":"Han","email":"","affiliations":[{"id":13711,"text":"Caltech","active":true,"usgs":false}],"preferred":false,"id":882063,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70223240,"text":"70223240 - 2021 - National Park Service Vegetation Mapping Inventory Program: Great Smoky Mountains National Park vegetation mapping project","interactions":[],"lastModifiedDate":"2021-08-19T15:13:17.0885","indexId":"70223240","displayToPublicDate":"2021-07-01T10:01:38","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":53,"text":"Natural Resource Report","active":false,"publicationSubtype":{"id":1}},"seriesNumber":"2021/2285","title":"National Park Service Vegetation Mapping Inventory Program: Great Smoky Mountains National Park vegetation mapping project","docAbstract":"The National Park Service (NPS) Vegetation Mapping Inventory (VMI) Program is an effort to classify, describe, and map existing vegetation communities in national park units throughout the United States. The NPS VMI Program is managed by the NPS Natural Resource Stewardship and Science Inventory and Monitoring Program and provides baseline vegetation information to natural resource managers, researchers, and ecologists. The U.S. Geological Survey Upper Midwest Environmental Sciences Center, NatureServe, and NPS Great Smoky Mountains National Park (GRSM, also referred to as the “Park”) have completed vegetation classification and mapping of GRSM, including the Foothills Parkway, for the NPS VMI Program.
Mappers, ecologists, and botanists collaborated to affirm vegetation types of GRSM and to determine how best to map the vegetation types by using aerial imagery. A vegetation classification developed in 2003 by NatureServe and the NPS served as a foundation to further classify and map the vegetation types of the Park. Data from an additional 10 vegetation plots supported vegetation types either rare or not documented in the 2003 classification. Data from 203 verification sites were collected to test the field key to vegetation types and the application of vegetation types to a sample set of map polygons. Furthermore, data from 972 accuracy assessment (AA) sites were collected (of which 966 were used to test accuracy of the vegetation map layer). This GRSM vegetation mapping project identified 112 vegetation types consisting of 105 association types in the U.S. National Vegetation Classification (USNVC), 2 “park-special” types, 1 “map-special” type, and 4 cultural types in the USNVC.
To map the vegetation and land cover of GRSM, 52 map classes were developed. Of these 52 map classes, 46 represent natural (including ruderal) vegetation types, most of which types are recognized in the USNVC. For the remaining 6 of the 52 map classes, 4 represent USNVC cultural types for agricultural and developed areas, and 2 represent non-USNVC types for nonvegetated open water and nonvegetated rock. Features were interpreted from viewing four-band digital aerial imagery using digital onscreen three-dimensional stereoscopic workflow systems in geographic information systems; digital aerial imagery was collected during September 23–October 30, 2015. The interpreted data were digitally and spatially referenced, thus making the spatial-database layers usable in a geographic information system. Polygon units were mapped to either a 0.5- or 0.25- hectare (ha) minimum mapping unit, depending on vegetation type.
A geodatabase containing several feature-class layers and tables provides the locations and data of USNVC vegetation types (vegetation map layer), vegetation plots, verification sites, AA sites, project boundary extent, and aerial image centers and flight lines.
Covering 210,875 ha, the feature-class layer and related tables for the vegetation map layer provide 34,084 polygons of detailed attribute data when special modifiers are not considered (average polygon size of 6.2 ha) and 36,589 polygons of detailed attribute data when special modifiers are considered (average polygon size of 5.8 ha). Each map polygon is assigned a map-class code and name and, when applicable, are linked to USNVC classification tables within the geodatabase. The vegetation map extent includes the administrative boundary for GRSM and the Foothills Parkway.
A summary report, generated from the vegetation map layer, concludes that the 46 map classes representing natural (including ruderal) vegetation types apply to 99.2% of polygons (33,797 polygons; average size of 6.2 ha) and cover 98.6% of the Park (207,971.4 ha). Further broken down, map classes representing natural vegetation types indicate that the Park is 97.7% forest and woodland (205,882.5 ha), 0.6% shrubland (1,174.6 ha), and 0.4% herbaceous (914.3 ha). Map classes representing cultural vegetation types apply to 0.8% of polygons (259 polygons; average size of 4.9 ha) and cover 0.6% of the Park (1,277.4 ha). Map classes representing nonvegetation open and flowing water and unvegetated rock apply to 0.08% of polygons (28 polygons; average size of 58.1 ha) and cover 0.8% of the Park (1,625.9 ha).
A thematic AA study was completed of map classes representing the natural (including ruderal) vegetation types of the Park. Initial AA results were discussed with NPS staff from the Park. Following input from NPS staff on how to handle map classes that fell below accuracy standards, adjustments were made to the vegetation map layer. Final results indicate an overall accuracy of 80.64% (kappa index of 79.96% for chance agreements) based on data from 966 of the 972 AA sites. Most individual map-class themes exceed the NPS VMI Program standard of 80% with a 90% confidence interval.
The GRSM vegetation mapping project delivers many geospatial and vegetation data products, including an in-depth project report discussing methods and results, which includes map classification and map-class descriptions. This suite of products also includes descriptions and a field key to vegetation types; a database of vegetation plots, verification sites, and AA sites; digital images of field sites; field data sheets; digital aerial imagery; hardcopy and digital maps; a geodatabase of vegetation and land cover (map layer), field sites (vegetation plots, verification sites, and AA sites), aerial imagery index, project boundary, and metadata; and a contingency table listing AA results. Geospatial products are projected in the Universal Transverse Mercator, Zone 17 North, by using the North American Datum of 1983. Information on the NPS VMI Program and completed mapping projects are on the internet at https://www.nps.gov/im/vegetation-inventory.htm.
","language":"English","publisher":"National Park Service","doi":"10.36967/nrr-2286888","usgsCitation":"Hop, K.D., Strassman, A.C., Sattler, S., White, R., Pyne, M., Govus, T., and Dieck, J., 2021, National Park Service Vegetation Mapping Inventory Program: Great Smoky Mountains National Park vegetation mapping project: Natural Resource Report 2021/2285, 220 p., https://doi.org/10.36967/nrr-2286888.","productDescription":"220 p.","ipdsId":"IP-120204","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":388150,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina, Tennessee","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.023681640625,\n 35.594785665487244\n ],\n [\n -83.09783935546875,\n 35.806676609227054\n ],\n [\n -83.40545654296875,\n 35.762114795721\n ],\n [\n -83.88336181640625,\n 35.68853320738875\n ],\n [\n -84.034423828125,\n 35.545635932499415\n ],\n [\n -83.90808105468749,\n 35.43605776486772\n ],\n [\n -83.5565185546875,\n 35.39800594715108\n ],\n [\n -83.30657958984375,\n 35.47409160773029\n ],\n [\n -83.023681640625,\n 35.594785665487244\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hop, Kevin D. 0000-0002-9928-4773 khop@usgs.gov","orcid":"https://orcid.org/0000-0002-9928-4773","contributorId":1438,"corporation":false,"usgs":true,"family":"Hop","given":"Kevin","email":"khop@usgs.gov","middleInitial":"D.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":821495,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Strassman, Andrew C. 0000-0002-9792-7181 astrassman@usgs.gov","orcid":"https://orcid.org/0000-0002-9792-7181","contributorId":4575,"corporation":false,"usgs":true,"family":"Strassman","given":"Andrew","email":"astrassman@usgs.gov","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":821496,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sattler, Stephanie 0000-0003-4417-2480 ssattler@usgs.gov","orcid":"https://orcid.org/0000-0003-4417-2480","contributorId":191016,"corporation":false,"usgs":true,"family":"Sattler","given":"Stephanie","email":"ssattler@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":821497,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"White, Rickie","contributorId":201063,"corporation":false,"usgs":false,"family":"White","given":"Rickie","email":"","affiliations":[],"preferred":false,"id":821498,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pyne, Milo","contributorId":201061,"corporation":false,"usgs":false,"family":"Pyne","given":"Milo","email":"","affiliations":[],"preferred":false,"id":821499,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Govus, Tom","contributorId":264417,"corporation":false,"usgs":false,"family":"Govus","given":"Tom","email":"","affiliations":[{"id":17658,"text":"NatureServe","active":true,"usgs":false}],"preferred":false,"id":821500,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dieck, Jennifer 0000-0002-4388-4534 jdieck@usgs.gov","orcid":"https://orcid.org/0000-0002-4388-4534","contributorId":149647,"corporation":false,"usgs":true,"family":"Dieck","given":"Jennifer","email":"jdieck@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":821501,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70229733,"text":"70229733 - 2021 - Context-dependent deep learning","interactions":[],"lastModifiedDate":"2022-05-03T15:07:59.274845","indexId":"70229733","displayToPublicDate":"2021-07-01T09:59:05","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10746,"text":"Modeling and Using Context","active":true,"publicationSubtype":{"id":10}},"title":"Context-dependent deep learning","docAbstract":"Explicitly representing an agent’s context has been shown to have many benefits, which should also apply to machine learning. In this paper, we describe an approach to do this called context-dependent deep learning (CDDL), which is based on earlier work in context-mediated behavior (CMB) that uses contextual schemas (c-schemas) to represent clas-ses of situations along with knowledge useful in them. These are then recalled, and they guide reasoning in the corre-sponding contexts. CDDL stores knowledge about deep neural network structure and weights in c-schemas, which al-lows context-specific learning. Our work is being developed in the domain of seabird detection in aerial images of islands for use by biologists.
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The diversity of its avifauna reflects the heterogeneity of its landscape, with more than 500 species of birds recorded in the state. Species inhabiting primarily terrestrial habitats, known collectively as landbirds, constitute the largest and most ecologically diverse component of the Alaska avifauna. Habitats used by landbirds range from temperate rainforests in southeastern Alaska to Arctic tundra across much of northern Alaska. Most of these landbird species are migratory, and four major global migration flyways converge on rich breeding areas in Alaska.\n\nAlaska has one endemic landbird species, the McKay’s Bunting, and is home to an impressive number of landbird populations for which it hosts a large proportion of the regional, continental, or global population. Thus, Alaska has a significant stewardship responsibility for these particular landbird species and subspecies.\n\nHabitats in Alaska remain largely pristine due to the region’s remote nature, vast size, and small human population. Alaska’s growing population and attendant economic development, however, present many challenges that could affect all wildlife, including landbirds. Threats in Alaska are often considered to be less significant than those occurring elsewhere, where habitats are being altered by more rapidly increasing anthropogenic pressures, but they carry far-reaching consequences nonetheless. Habitats and ecosystem dynamics are changing rapidly due to the magnitude of climate warming at high latitudes. As such, effective landbird conservation in Alaska requires a broad, landscape-scale approach.\n\nConservation of landbirds over such an extensive and diverse landscape also demands that we integrate efforts in habitat management, population monitoring, research, education, and outreach at local, regional, continental, and international scales. Information on distribution and habitat requirements of landbirds should be incorporated into land-use planning decisions. Synthesizing information on distribution and population trends of landbirds is a critical, time-sensitive task. Such information should be provided in a form that is readily available to land managers and policy decision-makers.\n\nThe primary objectives of this plan are to (1) describe the region and Alaska’s landbird avifauna; (2) identify species of concern, important habitats, and key information needs; (3) highlight major conservation issues and threats to landbirds; and (4) identify potential conservation actions. We first examine landbird conservation at the statewide level within broad perspectives (regional, continental, and global), then take a detailed look at the specific issues, information needs, and potential conservation actions within each Bird Conservation Region in Alaska.","language":"English","publisher":"Boreal Partners in Flight","usgsCitation":"Booms, T.L., Cady, M.N., Carrothers, C.A., DeCicco, L.H., de Zeeuw, M.L., Flamme, M.J., Hagelin, J., Handel, C.M., Johnson, J., Kirchoff, M., Kissling, M.L., Lewis, S.B., Matsuoka, S.M., Nigro, D.A., Perkins, D.E., Renner, H.M., Savage, S.E., Sowl, K.M., Sharbaugh, S.M., Stenhouse, I.J., and Van Hemert, C.R., 2021, Alaska Landbird Conservation Plan (Version 2.0), x, 146 p.","productDescription":"x, 146 p.","ipdsId":"IP-070079","costCenters":[{"id":117,"text":"Alaska Science Center Biology 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However, classification decisions are liable to two errors: i) failing to classify a species as threatened or endangered that should be classified (underprotection), or ii) classifying a species as threatened or endangered when it is not warranted (overprotection). Recent surveys indicate threatened spectacled eider populations are increasing in western Alaska, prompting the U.S. Fish and Wildlife Service to reconsider the federal listing status. There are multiple criteria set for assessing spectacled eider status, and here we focus on the abundance and decision analysis criteria. We estimated population metrics using state-space models for Alaskan breeding populations of spectacled eiders. We projected abundance over 50 years using posterior estimates of abundance and process variation to estimate the probability of quasi-extinction. The decision analysis maps the risk of quasi-extinction to the loss associated with making a misclassification error (i.e., underprotection) through a loss function. Our results indicate that the Yukon Kuskokwim Delta breeding population in western Alaska has met the recovery criteria but the Arctic Coastal Plain population in northern Alaska has not. The methods employed here provide an example of accounting for uncertainty and incorporating value judgements in such a way that the decision-makers may understand the risk of committing a misclassification error. Incorporating the abundance threshold and decision analysis in the reclassification criteria greatly increases the transparency and defensibility of the classification decision, a critical aspect for making effective decisions about species management and conservation.
","language":"English","publisher":"PLoS","doi":"10.1371/journal.pone.0253895","usgsCitation":"Dunham, K., Osnas, E., Frost, C., Fischer, J., and Grand, J.B., 2021, Assessing recovery of spectacled eiders using a Bayesian decision analysis: PLoS ONE, v. 16, no. 7, e0253895, 17 p., https://doi.org/10.1371/journal.pone.0253895.","productDescription":"e0253895, 17 p.","ipdsId":"IP-118460","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":451667,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0253895","text":"Publisher Index Page"},{"id":432285,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","issue":"7","noUsgsAuthors":false,"publicationDate":"2021-07-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Dunham, K.D.","contributorId":287550,"corporation":false,"usgs":false,"family":"Dunham","given":"K.D.","email":"","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":908938,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Osnas, E.E.","contributorId":341825,"corporation":false,"usgs":false,"family":"Osnas","given":"E.E.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":908939,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Frost, C.","contributorId":336910,"corporation":false,"usgs":false,"family":"Frost","given":"C.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":908940,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fischer, J.B.","contributorId":341826,"corporation":false,"usgs":false,"family":"Fischer","given":"J.B.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":908941,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Grand, J. Barry 0000-0002-3576-4567 barry_grand@usgs.gov","orcid":"https://orcid.org/0000-0002-3576-4567","contributorId":579,"corporation":false,"usgs":true,"family":"Grand","given":"J.","email":"barry_grand@usgs.gov","middleInitial":"Barry","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908942,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70237231,"text":"70237231 - 2021 - Knowledge synthesis of Cape Sable Seaside Sparrow science","interactions":[],"lastModifiedDate":"2022-10-05T14:55:48.03111","indexId":"70237231","displayToPublicDate":"2021-07-01T09:42:25","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesNumber":"IAA 4500126696","title":"Knowledge synthesis of Cape Sable Seaside Sparrow science","docAbstract":"This report represents a literature review of science conducted on the Cape Sable Seaside Sparrow (Ammospiza maritima mirabilis, hereafter “CSSS” or “spar-row”). This information can be used as a foundation for the upcoming Species Status Assessment and for updating the CSSS Recovery Plan. This report focuses on areas of interest relative to CSSS management such as habitat, hydrology, fire, and population estimates. We include peer-reviewed scientific literature, synthesis reports, and some field reports. Many field reports to funding agencies and other documents exist beyond what is reviewed here; however, we include the most relevant documents relative to the focus of CSSS management. All documents reviewed are listed in the References section.
","language":"English","publisher":"U.S. Fish and Wildlife Service","usgsCitation":"Benscoter, A., Haider, S., Guilbeau, K.G., and Romanach, S., 2021, Knowledge synthesis of Cape Sable Seaside Sparrow science, v, 62 p.","productDescription":"v, 62 p.","ipdsId":"IP-132903","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":407962,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":407930,"type":{"id":15,"text":"Index Page"},"url":"https://ecos.fws.gov/ServCat/Reference/Profile/139083"}],"country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.65,\n 25\n ],\n [\n -80.6,\n 25\n ],\n [\n -80.6,\n 26\n ],\n [\n -81.65,\n 26\n ],\n [\n -81.65,\n 25\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Benscoter, Allison 0000-0003-4205-3808","orcid":"https://orcid.org/0000-0003-4205-3808","contributorId":216194,"corporation":false,"usgs":true,"family":"Benscoter","given":"Allison","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":853678,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haider, Saira M. 0000-0001-9306-3454","orcid":"https://orcid.org/0000-0001-9306-3454","contributorId":206253,"corporation":false,"usgs":true,"family":"Haider","given":"Saira","middleInitial":"M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":853679,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Guilbeau, Kelly G.","contributorId":297126,"corporation":false,"usgs":false,"family":"Guilbeau","given":"Kelly","email":"","middleInitial":"G.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":853680,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Romanach, Stephanie 0000-0003-0271-7825","orcid":"https://orcid.org/0000-0003-0271-7825","contributorId":220093,"corporation":false,"usgs":true,"family":"Romanach","given":"Stephanie","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":853681,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70216757,"text":"70216757 - 2021 - Economic geology and environmental characteristics of antimony deposits","interactions":[],"lastModifiedDate":"2021-10-01T14:40:56.858064","indexId":"70216757","displayToPublicDate":"2021-07-01T09:40:27","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"3","title":"Economic geology and environmental characteristics of antimony deposits","docAbstract":"Antimony is commonly listed as a critical mineral, particularly in the United States and European Union [1]. Its criticality, or supply risk, is derived from a combination of economic vulnerability, disruption potential of supply, and trade exposure [2].Disruption potential relates a country’s ability and willingness to supply a commodity. Commodities for which supply is concentrated in the fewest countries have the greatest potential for supply disruption, trade exposure, and economic vulnerability. In 2018, approximately 61% of the world production of antimony was mined from China, followed by Russia (20%) and Tajikistan (10%) [3] (Fig. 3.1). Several reviews of antimony as a critical mineral have been recently published [4, 5].
The uses of antimony can be divided into three main categories: metal products, non-metal uses, and flame retardants [5]. Most metallic antimony use is inlead-acid batteries. Antimony trioxide (Sb2O3) combined with halogenated com-pounds is used as a fire retardant in plastics, fabrics, and other applications. Other non-metallic uses include as a catalyst for plastics, and in the glass industry. Emerging uses include data storage and novel photovoltaic cells. Recycling of batteries represents an important reuse of antimony, but other uses of antimony do not lend themselves to recycling.
This chapter describes mineral deposit types that are primary sources of antimony, and environmental effects related to their mining. Antimony can be re-covered as either a primary commodity from some deposits or as a by product commodity from some gold or silver deposits. Environmental risks associated with antimony mining include those related to mining in general, such as the acid-generating potential of solid mine waste, and some issues specific to antimony, as described below.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Antimony","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"De Gruyter","doi":"10.1515/9783110668711-003","usgsCitation":"Seal,, R., 2021, Economic geology and environmental characteristics of antimony deposits, chap. 3 of Antimony, p. 49-72, https://doi.org/10.1515/9783110668711-003.","productDescription":"24 p.","startPage":"49","endPage":"72","ipdsId":"IP-123217","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":390119,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Seal,, Robert R. II 0000-0003-0901-2529 rseal@usgs.gov","orcid":"https://orcid.org/0000-0003-0901-2529","contributorId":141204,"corporation":false,"usgs":true,"family":"Seal,","given":"Robert R.","suffix":"II","email":"rseal@usgs.gov","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":806092,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70222561,"text":"70222561 - 2021 - Climate change scenario planning for resource stewardship at Wind Cave National Park","interactions":[],"lastModifiedDate":"2021-08-05T14:49:49.415903","indexId":"70222561","displayToPublicDate":"2021-07-01T09:38:32","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":53,"text":"Natural Resource Report","active":false,"publicationSubtype":{"id":1}},"seriesNumber":"NPS/NRSS/NRR—2021/2274","title":"Climate change scenario planning for resource stewardship at Wind Cave National Park","docAbstract":"This report explains scenario planning as a climate change adaptation tool in general, then describes how it was applied to Wind Cave National Park as the second part of a pilot project to dovetail climate change scenario planning with National Park Service (NPS) Resource Stewardship Strategy development.
In the orientation phase, Park and regional NPS staff, other subject-matter experts, natural and cultural resource planners, and the climate change core team who led the scenario planning project identified priority resource management topics and associated climate sensitivities. Next, the climate change core team used this information to create a set of four divergent climate futures—summaries of relevant climate data from individual climate projections—to encompass the range of ways climate could change in coming decades in the park. Participants in the scenario planning workshop then developed climate futures into robust climate-resource scenarios that considered expert-elicited resource impacts and identified potential management responses. Finally, the scenario-based resource responses identified by park staff and subject matter experts were used to integrate climate-informed adaptations into resource stewardship goals and activities for the park's Resource Stewardship Strategy. This process of engaging resource managers in climate change scenario planning ensures that their management and planning decisions are informed by assessments of critical future climate uncertainties.
","language":"English","publisher":"National Park Service","doi":"10.36967/nrr-2286672","usgsCitation":"Runyon, A., Schuurman, G.W., Miller, B.W., Symstad, A., and Hardy, A., 2021, Climate change scenario planning for resource stewardship at Wind Cave National Park: Natural Resource Report NPS/NRSS/NRR—2021/2274, ix, 114 p., https://doi.org/10.36967/nrr-2286672.","productDescription":"ix, 114 p.","ipdsId":"IP-122369","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true},{"id":40927,"text":"North Central Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":387718,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"South Dakota","otherGeospatial":"Wind Cave National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.49327087402344,\n 43.54008705264584\n ],\n [\n -103.41293334960938,\n 43.54008705264584\n ],\n [\n -103.41293334960938,\n 43.61544814581711\n ],\n [\n -103.49327087402344,\n 43.61544814581711\n ],\n [\n -103.49327087402344,\n 43.54008705264584\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2021-07-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Runyon, Amber N. 0000-0002-7282-1217","orcid":"https://orcid.org/0000-0002-7282-1217","contributorId":261745,"corporation":false,"usgs":false,"family":"Runyon","given":"Amber N.","affiliations":[{"id":52985,"text":"National Park Service Climate Change Response Program","active":true,"usgs":false}],"preferred":false,"id":820555,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schuurman, Gregor W. 0000-0002-9304-7742","orcid":"https://orcid.org/0000-0002-9304-7742","contributorId":147698,"corporation":false,"usgs":false,"family":"Schuurman","given":"Gregor","email":"","middleInitial":"W.","affiliations":[{"id":16909,"text":"U.S. National Park Service, Natural Resource Stewardship and Science, Fort Collins, CO, 80525, USA","active":true,"usgs":false}],"preferred":false,"id":820556,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, Brian W. 0000-0003-1716-1161","orcid":"https://orcid.org/0000-0003-1716-1161","contributorId":196603,"corporation":false,"usgs":true,"family":"Miller","given":"Brian","email":"","middleInitial":"W.","affiliations":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":820557,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Symstad, Amy 0000-0003-4231-2873 asymstad@usgs.gov","orcid":"https://orcid.org/0000-0003-4231-2873","contributorId":201095,"corporation":false,"usgs":true,"family":"Symstad","given":"Amy","email":"asymstad@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":820558,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hardy, Amanda","contributorId":261746,"corporation":false,"usgs":false,"family":"Hardy","given":"Amanda","email":"","affiliations":[{"id":52985,"text":"National Park Service Climate Change Response Program","active":true,"usgs":false}],"preferred":false,"id":820559,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70221875,"text":"70221875 - 2021 - A tale of two valleys: Endangered species policy and the fate of the giant gartersnake","interactions":[],"lastModifiedDate":"2021-07-13T09:58:24.914439","indexId":"70221875","displayToPublicDate":"2021-07-01T09:28:43","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":8958,"text":"California Fish and Wildlife","active":true,"publicationSubtype":{"id":10}},"title":"A tale of two valleys: Endangered species policy and the fate of the giant gartersnake","docAbstract":"By the mid-20th Century, giant gartersnakes (Thamnophis gigas) had lost more than 90% of their Central Valley marsh habitat and were extirpated from more than two-thirds of their range. This massive habitat loss led to their inclusion in the inaugural list of rare species under the California Endangered Species Act (CESA). Listing under the CESA provided giant gartersnakes legal protection and mechanisms for recovery, and subsequent listing under the U.S. Endangered Species Act (U.S. ESA) further fortified these protections. But how effective has listing under these endangered species acts (ESAs) been at achieving their goal of giant gartersnake recovery? Herein, we review relevant aspects of giant gartersnake ecology, illustrate how listing has benefitted giant gartersnakes and what challenges have been faced in slowing declines and recovering populations, and chart a course towardprovide options for improved conservation, management, and recovery of giant gartersnakes. Although listing as threatened under both state and federal ESAs has not yet achieved recovery of giant gartersnakes, the increased knowledge gained and mechanisms for protecting giant gartersnake habitat on private and public lands developed over the past 50 years has improved conservation of this endemic California snake.","language":"English","publisher":"California Department of Fish and Wildlife","doi":"10.51492/cfwj.cesasi.16","usgsCitation":"Halstead, B., Valcarcel, P., Kim, R., Jordan, A., Rose, J.P., Skalos, S., Reyes, G., Ersan, J., Casazza, M.L., Essert, A., and Fulton, A.M., 2021, A tale of two valleys: Endangered species policy and the fate of the giant gartersnake: California Fish and Wildlife, p. 264-283, https://doi.org/10.51492/cfwj.cesasi.16.","productDescription":"20 p.","startPage":"264","endPage":"283","ipdsId":"IP-123451","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":451670,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.51492/cfwj.cesasi.16","text":"Publisher Index Page"},{"id":387110,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Giant Gartersnake Range","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.431640625,\n 40.88029480552824\n ],\n [\n -122.84912109375,\n 40.463666324587685\n ],\n [\n -122.62939453125001,\n 38.89103282648846\n ],\n [\n -121.75048828124999,\n 37.50972584293751\n ],\n [\n -120.60791015625,\n 36.03133177633187\n ],\n [\n -118.93798828125,\n 34.831841149828655\n ],\n [\n -118.01513671875,\n 35.11990857099681\n ],\n [\n -118.5205078125,\n 36.10237644873644\n ],\n 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rkim@usgs.gov","orcid":"https://orcid.org/0000-0001-5891-0582","contributorId":204478,"corporation":false,"usgs":true,"family":"Kim","given":"Richard","email":"rkim@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":819157,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jordan, Anna 0000-0001-8834-4542 ajordan@usgs.gov","orcid":"https://orcid.org/0000-0001-8834-4542","contributorId":199340,"corporation":false,"usgs":true,"family":"Jordan","given":"Anna","email":"ajordan@usgs.gov","affiliations":[],"preferred":true,"id":819158,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rose, Jonathan P. 0000-0003-0874-9166 jprose@usgs.gov","orcid":"https://orcid.org/0000-0003-0874-9166","contributorId":199339,"corporation":false,"usgs":true,"family":"Rose","given":"Jonathan","email":"jprose@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":819159,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Skalos, Shannon 0000-0003-1229-8580 sskalos@usgs.gov","orcid":"https://orcid.org/0000-0003-1229-8580","contributorId":167191,"corporation":false,"usgs":true,"family":"Skalos","given":"Shannon","email":"sskalos@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":819160,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Reyes, Gabriel 0000-0001-9281-5300 greyes@usgs.gov","orcid":"https://orcid.org/0000-0001-9281-5300","contributorId":199338,"corporation":false,"usgs":true,"family":"Reyes","given":"Gabriel","email":"greyes@usgs.gov","affiliations":[],"preferred":true,"id":819161,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ersan, Julia 0000-0002-1549-7561","orcid":"https://orcid.org/0000-0002-1549-7561","contributorId":218034,"corporation":false,"usgs":true,"family":"Ersan","given":"Julia","email":"","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":819162,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"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":819163,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Essert, Allison 0000-0003-4408-5934 aessert@usgs.gov","orcid":"https://orcid.org/0000-0003-4408-5934","contributorId":199341,"corporation":false,"usgs":true,"family":"Essert","given":"Allison","email":"aessert@usgs.gov","affiliations":[],"preferred":true,"id":819164,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Fulton, Alexandria M","contributorId":260937,"corporation":false,"usgs":false,"family":"Fulton","given":"Alexandria","email":"","middleInitial":"M","affiliations":[{"id":39913,"text":"former WERC","active":true,"usgs":false}],"preferred":false,"id":819165,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70225734,"text":"70225734 - 2021 - 2020 Status of the Lake Ontario lower trophic levels","interactions":[],"lastModifiedDate":"2021-11-09T15:08:17.039839","indexId":"70225734","displayToPublicDate":"2021-07-01T09:04:48","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"2","title":"2020 Status of the Lake Ontario lower trophic levels","docAbstract":"Significant Findings for Year 2020: Note that due to covid-19 restrictions, offshore sampling was limited in 2020.
1) May – Oct total phosphorus (TP) in 2020 was 10.6 µg/L (offshore) and 7.7 µg/L (nearshore), higher than the long-term (1995-2019) average in the offshore (6.2 µg/L) and close to average in the nearshore (7.8 µg/L); mean TP values for the past decade (2010-2019) were 6.0 µg/L and 7.9 µg/L in the offshore and nearshore, respectively. In 2020, TP concentrations were significantly higher (p=0.03) in the offshore compared to the nearshore. Note that offshore duplicate samples had high relative percent difference (average 54%. 6-117%) making inferences for the offshore in 2020 uncertain.
2) May – Oct epilimnetic chlorophyll-a was similar at nearshore (1.9 µg/L) and offshore (2.1 µg/L) sites. These values were slightly higher than the average for 1995 – 2019 (1.7 µg/L, offshore; 1.5 µg/L, nearshore) and higher than for the last decade (1.4 µg/L, both offshore and nearshore).
3) May – Oct Secchi depth ranged from 3.5 m to 10.4 m (11 ft to 34 ft) at individual sites and was not significantly different between nearshore (6.3 m; 20.7 ft) and offshore (6.5 m; 21.3 ft) locations. Long-term (1995-2019) average was 7.2 m in the offshore and 6.4 m in the nearshore; means for the last decade were 7.8 m in the offshore and 6.2 m in the nearshore.
4) Despite higher TP values in 2020 than in recent years, TP, chlorophyll-a and Secchi depth are indicative of oligotrophic conditions in the offshore of Lake Ontario.
5) Nearshore summer zooplankton biomass was 10.5 µg/L, near the all-time low (9.4 µg/L, 2017) since monitoring began in 1995. Offshore epilimnetic summer zooplankton biomass was 11.7 µg/L. These values are similar to biomass in the last decade (2010-2019).
6) Peak (July) epilimnetic biomass of Cercopagis was 3.0 µg/L in the nearshore and represented 25% of the zooplankton community at that time; Cercopagis was absent from the July offshore epilimnetic samples in 2020 but was present in whole water column samples taken in August by other agencies. Epilimnetic biomass of Bythotrephes peaked in late-September in both the nearshore (1.0 µg/L) and offshore (1.8 µg/L) and represented 10% and 18% of the zooplankton community at those times, respectively.
7) Summer nearshore and offshore epilimnetic zooplankton density and biomass declined significantly 1995 – 2020. The declines were due mainly to reductions in cyclopoid copepods in both habitats.
No abstract available.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings: Volume 67, part 1: Programs and abstracts","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Institute on Lake Superior Geology","usgsCitation":"Drenth, B.J., Cannon, W.F., Schulz, K., and Ayuso, R.A., 2021, Geophysical insights into Paleoproterozoic tectonics along the southern margin of the Superior Province, central Upper Peninsula, Michigan, in Proceedings: Volume 67, part 1: Programs and abstracts, v. 67, no. Part 1, p. 18-19.","productDescription":"2 p.","startPage":"18","endPage":"19","ipdsId":"IP-128448","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":413535,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":413332,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://digitalcollections.lakeheadu.ca/exhibits/show/ilsg/item/3063"}],"country":"United States","state":"Michigan","otherGeospatial":"Superior Province","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -88.25,\n 46.2\n ],\n [\n -88.25,\n 45.75\n ],\n [\n -87.5,\n 45.75\n ],\n [\n -87.5,\n 46.2\n ],\n [\n -88.25,\n 46.2\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"67","issue":"Part 1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Drenth, Benjamin J. 0000-0002-3954-8124 bdrenth@usgs.gov","orcid":"https://orcid.org/0000-0002-3954-8124","contributorId":1315,"corporation":false,"usgs":true,"family":"Drenth","given":"Benjamin","email":"bdrenth@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":864940,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cannon, William F. 0000-0002-2699-8118","orcid":"https://orcid.org/0000-0002-2699-8118","contributorId":201972,"corporation":false,"usgs":true,"family":"Cannon","given":"William","email":"","middleInitial":"F.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":864941,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schulz, Klaus 0000-0003-2967-4765","orcid":"https://orcid.org/0000-0003-2967-4765","contributorId":301874,"corporation":false,"usgs":false,"family":"Schulz","given":"Klaus","affiliations":[{"id":65356,"text":"GEM Emeritus","active":true,"usgs":false}],"preferred":false,"id":864942,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ayuso, Robert A. 0000-0002-8496-9534 rayuso@usgs.gov","orcid":"https://orcid.org/0000-0002-8496-9534","contributorId":2654,"corporation":false,"usgs":true,"family":"Ayuso","given":"Robert","email":"rayuso@usgs.gov","middleInitial":"A.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":864943,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70223671,"text":"70223671 - 2021 - Tools and technologies for quantifying spread and impacts of invasive species","interactions":[],"lastModifiedDate":"2022-04-13T20:13:00.752506","indexId":"70223671","displayToPublicDate":"2021-07-01T08:53:56","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"11","title":"Tools and technologies for quantifying spread and impacts of invasive species","docAbstract":"The need for tools and technologies for understanding and quantifying invasive species has never been greater. Rates of infestation vary on the species or organism being examined across the United States, and notable examples can be found. For example, from 2001 to 2003 alone, ash (Fraxinus spp.) mortality progressed at a rate of 12.97 km year −1 (Siegert et al. 2014), and cheatgrass (Bromus tectorum) is expected to increase dominance on 14% of Great Basin rangelands (Boyte et al. 2016). The magnitude and scope of problems that invasive species present suggest novel approaches for detection and management are needed, especially those that enable more cost-effective solutions. The advantages of using technologically advanced approaches and tools are numerous, and the quality and quantity of available information can be significantly enhanced by their use. They can also play a key role in development of decision-support systems; they are meant to be integrated with other systems, such as inventory and monitoring, because often the tools are applied after a species of interest has been detected and a threat has been identified. In addition, the inventory systems mentioned in Chap. 10 are regularly used in calibrating and validating models and decision-support systems. For forested areas, Forest Inventory and Analysis (FIA) data are most commonly used (e.g., Václavík et al. 2015) given the long history of the program. In non-forested systems, national inventory datasets have not been around as long (see Chap. 10), but use of these data to calibrate and validate spatial models is growing. These inventory datasets include the National Resources Inventory (NRI) (e.g., Duniway et al. 2012) and the Assessment Inventory and Monitoring program (AIM) (e.g., McCord et al. 2017). Similarly, use of the Nonindigenous Aquatic Species (NAS) database is growing as well (e.g., Evangelista et al. 2017). The consistent protocols employed by these programs prove valuable for developing better tools, but the data they afford are generally limited for some tools because the sampling intensity is too low.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Invasive species in forests and rangelands of the United States: A comprehensive science synthesis for the United States Forest Sector","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"U.S. Forest Service","doi":"10.1007/978-3-030-45367-1_11","collaboration":"U.S. Forest Service","usgsCitation":"Reeves, M., Ibanez, I., Blumenthal, D., Chen, G., Guo, Q., Jarnevich, C.S., Koch, J., Sapio, F., Schwartz, M.D., Meentemeyer, R.K., Wylie, B., and Boyte, S.P., 2021, Tools and technologies for quantifying spread and impacts of invasive species, chap. 11 of Invasive species in forests and rangelands of the United States: A comprehensive science synthesis for the United States Forest Sector, p. 243-265, https://doi.org/10.1007/978-3-030-45367-1_11.","productDescription":"23 p.","startPage":"243","endPage":"265","ipdsId":"IP-082001","costCenters":[{"id":222,"text":"Earth Resources Observation and Science 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Dana","contributorId":70686,"corporation":false,"usgs":true,"family":"Blumenthal","given":"Dana","affiliations":[],"preferred":false,"id":822330,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chen, Gang","contributorId":265128,"corporation":false,"usgs":false,"family":"Chen","given":"Gang","email":"","affiliations":[{"id":54601,"text":"UNCC","active":true,"usgs":false}],"preferred":false,"id":822271,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Guo, Qinfeng","contributorId":214263,"corporation":false,"usgs":false,"family":"Guo","given":"Qinfeng","email":"","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":822275,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jarnevich, Catherine S. 0000-0002-9699-2336 jarnevichc@usgs.gov","orcid":"https://orcid.org/0000-0002-9699-2336","contributorId":3424,"corporation":false,"usgs":true,"family":"Jarnevich","given":"Catherine","email":"jarnevichc@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":822276,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Koch, Jennifer","contributorId":210475,"corporation":false,"usgs":false,"family":"Koch","given":"Jennifer","email":"","affiliations":[{"id":38113,"text":"The University of Oklahoma","active":true,"usgs":false}],"preferred":false,"id":822277,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sapio, Frank","contributorId":265129,"corporation":false,"usgs":false,"family":"Sapio","given":"Frank","email":"","affiliations":[{"id":37389,"text":"U.S. Forest 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Center","active":true,"usgs":true}],"preferred":true,"id":822273,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Boyte, Stephen P. 0000-0002-5462-3225 sboyte@usgs.gov","orcid":"https://orcid.org/0000-0002-5462-3225","contributorId":139238,"corporation":false,"usgs":true,"family":"Boyte","given":"Stephen","email":"sboyte@usgs.gov","middleInitial":"P.","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":822331,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70229469,"text":"70229469 - 2021 - Development of aquaculture protocols and gonadal differentiation of red shiner","interactions":[],"lastModifiedDate":"2022-03-09T15:10:59.097275","indexId":"70229469","displayToPublicDate":"2021-07-01T08:53:00","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2885,"text":"North American Journal of Aquaculture","active":true,"publicationSubtype":{"id":10}},"title":"Development of aquaculture protocols and gonadal differentiation of red shiner","docAbstract":"Developing detailed rearing methods and describing the onset of gonadal differentiation in Red Shiners Cyprinella lutrensis could facilitate the development of novel techniques to control or enhance populations, enable toxicology studies, and help construct bioassays. In this study, we develop and report aquaculture practices for Red Shiner that ensure consistent year-round production in laboratory settings and evaluate the timing of sexual differentiation via histological gonad examinations. Our methods resulted in a mean of 56.00% (SD = 8.98%) survival through the larval stages of development, and we obtained spawns from captive-reared Red Shiners 138 d posthatch. Red Shiners are gonochoristic, and both ovaries and testes differentiate directly from undifferentiated gonads. Ovaries begin to differentiate in females 45 d posthatch, while testes begin differentiating in males 105 d posthatch. This study provides in-depth protocols for the closed-cycle aquaculture of Red Shiners and describes the gonadal differentiation and development of both sexes.
","language":"English","publisher":"Wiley","doi":"10.1002/naaq.10176","usgsCitation":"Teal, C., Schill, D., Fogelson, S., and Bonar, S.A., 2021, Development of aquaculture protocols and gonadal differentiation of red shiner: North American Journal of Aquaculture, v. 83, no. 3, p. 145-154, https://doi.org/10.1002/naaq.10176.","productDescription":"10 p.","startPage":"145","endPage":"154","ipdsId":"IP-125476","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":396913,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Gila Box Riparian National Conservation Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.39945220947266,\n 32.95322410229271\n ],\n [\n -109.37799453735352,\n 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J.","contributorId":274498,"corporation":false,"usgs":false,"family":"Schill","given":"Daniel J.","affiliations":[{"id":56023,"text":"idfg","active":true,"usgs":false}],"preferred":false,"id":837559,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fogelson, Susan B.","contributorId":288200,"corporation":false,"usgs":false,"family":"Fogelson","given":"Susan B.","affiliations":[],"preferred":false,"id":837560,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bonar, Scott A. 0000-0003-3532-4067 sbonar@usgs.gov","orcid":"https://orcid.org/0000-0003-3532-4067","contributorId":3712,"corporation":false,"usgs":true,"family":"Bonar","given":"Scott","email":"sbonar@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":837557,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70225737,"text":"70225737 - 2021 - Bottom trawl assessment of benthic preyfish community in Lake Ontario","interactions":[],"lastModifiedDate":"2023-05-09T14:14:35.142575","indexId":"70225737","displayToPublicDate":"2021-07-01T08:52:11","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":5114,"text":"NYSDEC Lake Ontario Annual Report ","active":true,"publicationSubtype":{"id":2}},"chapter":"12","title":"Bottom trawl assessment of benthic preyfish community in Lake Ontario","docAbstract":"Since 1978, the Lake Ontario benthic preyfish survey has provided information on the status and trends of the benthic preyfish community related to Lake Ontario Fish Community Objectives that include understanding preyfish population dynamics and community diversity. Beginning in 2015, the benthic preyfish survey expanded from US-only to incorporate lake-wide sampling sites which drastically increased the survey’s spatial coverage. In 2020, the collaborative benthic preyfish survey completed 82 bottom trawl tows across main lake and embayment sites at depths from 6 to 226 m. Compared to previous years, the survey was largely confined to ports east of Rochester on the US side, and east of Wesleyville on the Canadian side due to COVID-19 travel constraints. In total, the survey sampled 109,315 fish from 32 species in 2020. Round goby was the most numerically abundant species comprising 59% of total catch, followed by alewife (27%), and deepwater sculpin (7%). Despite being a common species represented in historical catches, slimy sculpin comprised only 0.05% of the total catch, with only 53 fish sampled in 2020. Annual biomass indices were among the lowest reported for slimy sculpin across the entire time series, whereas deepwater sculpin biomass remained high but showed a decrease from values observed in 2019. Deepwater sculpin condition in 2020 was lower than in 2019 but similar to values observed in 2017-2018. Community diversity remained high relative to historically lower values when round goby and deepwater sculpin were not captured in trawl catches. Round goby biomass in 2020 was the highest on the US time series, but not on the lake-wide series, highlighting the need to resume lake-wide sampling to further understand how regional vs lake-wide sampling affects benthic preyfish population estimates.
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Conservation","active":true,"usgs":false}],"preferred":false,"id":826459,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Holden, Jeremy P.","contributorId":190415,"corporation":false,"usgs":false,"family":"Holden","given":"Jeremy","email":"","middleInitial":"P.","affiliations":[{"id":16762,"text":"Ontario Ministry of Natural Resources and Forestry","active":true,"usgs":false}],"preferred":false,"id":826460,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70224632,"text":"70224632 - 2021 - Restoration of mangrove forest","interactions":[],"lastModifiedDate":"2021-10-01T13:48:32.047331","indexId":"70224632","displayToPublicDate":"2021-07-01T08:45:37","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"14","title":"Restoration of mangrove forest","docAbstract":"Mangrove forests occur worldwide along tropical coasts in inundated soils where primary production and anaerobic conditions contribute to the building of soil organic matter (Also see Mangroves Hot-spot, Volume 2). Note that peat may accumulate in certain coastal mangrove (Middleton and McKee, 2001). The actual amount of soil organic matter stored in these wetlands depends on the balance between primary production and decomposition processes (Middleton and McKee, 2001; Kolka et al., 2018; Middleton, 2020). The restoration of mangroves can increase carbon stocks both in soil and aboveground biomass (Wickland et al., 2013; Chimner et al., 2017; Friess et al., 2019). While tropical inland peatland forests may have higher carbon sequestration rates than mangrove swamps, methane (CH4) emissions are generally lower in mangrove swamp, so that these wetlands have greater carbon sequestration potential (Kolka et al., 2018; Al-Haj and Fulweiler, 2020). Mangroves and forested boreal and temperate peatlands tend to store more carbon than non-forested peatlands (Kolka et al., 2018).","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Recarbonizing global soils – A technical manual of recommended management practices","largerWorkSubtype":{"id":3,"text":"Organization Series"},"language":"English","publisher":"Food and Agricultural Organization of the United Nations","doi":"10.4060/cb6606en","usgsCitation":"Middleton, B., and Ward, E., 2021, Restoration of mangrove forest, chap. 14 of Recarbonizing global soils – A technical manual of recommended management practices, v. 5, p. 190-198, https://doi.org/10.4060/cb6606en.","productDescription":"9 p.","startPage":"190","endPage":"198","ipdsId":"IP-120271","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":390116,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Middleton, Beth 0000-0002-1220-2326","orcid":"https://orcid.org/0000-0002-1220-2326","contributorId":216869,"corporation":false,"usgs":true,"family":"Middleton","given":"Beth","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":824449,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ward, Eric 0000-0002-5047-5464","orcid":"https://orcid.org/0000-0002-5047-5464","contributorId":221014,"corporation":false,"usgs":true,"family":"Ward","given":"Eric","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":824450,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70226458,"text":"70226458 - 2021 - Gopherus agassizii","interactions":[],"lastModifiedDate":"2021-11-18T14:41:18.5924","indexId":"70226458","displayToPublicDate":"2021-07-01T08:40:34","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9925,"text":"The IUCN Red List of Threatened Species 2021","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Gopherus agassizii","title":"Gopherus agassizii","docAbstract":"A provisional Red List Assessment of the widespread Desert Tortoise, Gopherus agassizii (sensu lato), was performed at a Desert Tortoise Council workshop in 2010 and updated by the IUCN Tortoise and Freshwater Turtle Specialist Group (TFTSG) in 2011, at which time the Mojave Desert subpopulation, now considered G. agassizii (sensu stricto) following taxonomic analysis and splitting into three separate species (G. agassizii, G. morafkai, and G. evgoodei), was assessed as Critically Endangered A2bce+A4bce based on population reduction (decreasing density), habit loss of over 80% over three generations (90 years), including past reductions and predicted future declines, as well as the effects of disease (upper respiratory tract disease / mycoplasmosis). Gopherus agassizii (sensu stricto) comprises tortoises in the most well-studied 30% of the larger range; this portion of the original range has seen the most human impacts and is where the largest past population losses had been documented. A recent rigorous range-wide population reassessment of G. agassizii (sensu stricto) has demonstrated continued adult population and density declines of about 90% over three generations (two in the past and one ongoing) in four of the five G. agassizii recovery units and inadequate recruitment with decreasing percentages of juveniles in all five recovery units. As such, we reaffirm the prior assessment of the taxonomically restricted Mojave Desert Tortoise, G. agassizii, as Critically Endangered, and add criterion “a” for direct population observations: CR A2abce+A4abce. The previously defined widespread species G. agassizii (sensu lato) was last assessed as Vulnerable on the IUCN Red List in 1996; a separate assessment currently in progress by the TFTSG for the Sonoran Desert Tortoise, G. morafkai (previously considered part of G. agassizii) has provisionally assessed that species as Vulnerable.
","language":"English","publisher":"IUCN","doi":"10.2305/IUCN.UK.2021-2.RLTS.T97246272A3150871.en","usgsCitation":"Berry, K.H., Allison, L.J., McLuckie, A., Vaughn, M., and Murphy, R.W., 2021, Gopherus agassizii: The IUCN Red List of Threatened Species 2021, HTML Document, https://doi.org/10.2305/IUCN.UK.2021-2.RLTS.T97246272A3150871.en.","productDescription":"HTML Document","ipdsId":"IP-125270","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":451679,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2305/iucn.uk.2021-2.rlts.t97246272a3150871.en","text":"Publisher Index Page"},{"id":391863,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California, Nevada, Utah","otherGeospatial":"Mojave Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.444580078125,\n 32.48196313217176\n ],\n [\n -113.64257812499999,\n 34.30714385628804\n ],\n [\n -113.499755859375,\n 34.768691457552706\n ],\n [\n -114.466552734375,\n 35.951329861522666\n ],\n [\n -113.291015625,\n 36.500805317604794\n ],\n [\n -112.950439453125,\n 37.51844023887861\n ],\n [\n -113.5986328125,\n 37.64903402157866\n ],\n [\n -114.14794921875,\n 37.64903402157866\n ],\n [\n -114.76318359375,\n 36.58024660149866\n ],\n [\n -115.11474609375001,\n 36.155617833818525\n ],\n [\n -116.56494140625001,\n 36.82687474287728\n ],\n [\n -118.09204101562501,\n 36.35052700542763\n ],\n [\n -117.48779296875,\n 34.88593094075317\n ],\n [\n -116.883544921875,\n 34.252676117101515\n ],\n [\n -115.49926757812499,\n 33.247875947924385\n ],\n [\n -115.3564453125,\n 32.759562025650126\n ],\n [\n -114.444580078125,\n 32.48196313217176\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Berry, Kristin H. 0000-0003-1591-8394 kristin_berry@usgs.gov","orcid":"https://orcid.org/0000-0003-1591-8394","contributorId":437,"corporation":false,"usgs":true,"family":"Berry","given":"Kristin","email":"kristin_berry@usgs.gov","middleInitial":"H.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":826969,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Allison, L. J.","contributorId":269368,"corporation":false,"usgs":false,"family":"Allison","given":"L.","email":"","middleInitial":"J.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":826970,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McLuckie, A. M.","contributorId":269369,"corporation":false,"usgs":false,"family":"McLuckie","given":"A. M.","affiliations":[{"id":49122,"text":"Utah Division of Wildlife Resources","active":true,"usgs":false}],"preferred":false,"id":826971,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vaughn, M.","contributorId":269372,"corporation":false,"usgs":false,"family":"Vaughn","given":"M.","email":"","affiliations":[{"id":55949,"text":"Turtle Conservancy","active":true,"usgs":false}],"preferred":false,"id":826972,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Murphy, R. W.","contributorId":269374,"corporation":false,"usgs":false,"family":"Murphy","given":"R.","email":"","middleInitial":"W.","affiliations":[{"id":7044,"text":"University of Toronto","active":true,"usgs":false}],"preferred":false,"id":826973,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70238599,"text":"70238599 - 2021 - Mineral Mapping of the Battle Mountain District, Nevada, USA, Using AVIRIS-Classic and SpecTIR Inc. AisaFENIX 1K Imaging Spectrometer Datasets","interactions":[],"lastModifiedDate":"2022-12-01T14:47:41.476167","indexId":"70238599","displayToPublicDate":"2021-07-01T08:39:03","publicationYear":"2021","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Mineral Mapping of the Battle Mountain District, Nevada, USA, Using AVIRIS-Classic and SpecTIR Inc. AisaFENIX 1K Imaging Spectrometer Datasets","docAbstract":"Coastal wetland restoration can be used to offset past wetland losses and/or reduce future losses due to land-use changes, rising sea levels, and accelerating climate change. However, there is a need for information regarding the restoration-relevant performance of foundation species like mangrove and marsh plants, including their responses to acute and chronic stressors that can affect restoration outcomes. Mangrove encroachment and poleward range expansion into marsh, facilitated by warming winters, has provided restoration practitioners in the northern Gulf of Mexico with a new foundation plant species to consider using during restoration. To evaluate the performance of transplanted mangroves and characterize restoration-relevant marsh–mangrove interactions, we planted nursery-raised black mangrove (Avicennia germinans) seedlings within different marsh cover treatments along an eroding marsh-dominated shoreline in Louisiana. Mangrove seedling survival increased with greater densities of marsh cover, indicating that marsh grass (Spartina alterniflora) may facilitate mangrove establishment. However, only 35% of transplanted mangrove seedlings established after 10 weeks, suggesting a low return on resources expended in raising seedlings for 1–3 years in greenhouse conditions. Moreover, a 2018 freeze event killed 100% of transplanted mangrove seedlings, while nearby naturally established mangroves suffered minor damage. Our results, along with those in the mangrove restoration literature, indicate that planting mangroves in the northern Gulf of Mexico may not be the most efficient use of limited resources. Rather, restoration efforts may benefit from focusing initially on the restoration of abiotic conditions (e.g. elevation and hydrologic regimes), followed by using marsh plants (rather than transplanted mangroves) to jump-start ecosystem development.
","language":"English","publisher":"John Wiley & Sons, Inc.","doi":"10.1111/rec.13373","usgsCitation":"Macy, A., Osland, M., Cherry, J.A., and Cebrian, J., 2021, Effects of chronic and acute stressors on transplanted black mangrove (Avicennia germinans) seedlings along an eroding Louisiana shoreline: Restoration Ecology, v. 29, no. 5, e13373, 8 p., https://doi.org/10.1111/rec.13373.","productDescription":"e13373, 8 p.","ipdsId":"IP-117905","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":397219,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","city":"Port Fourchon","otherGeospatial":"Bayou Lafourche","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.49163818359375,\n 29.045965338037213\n ],\n [\n -89.86061096191406,\n 29.045965338037213\n ],\n [\n -89.86061096191406,\n 29.398926652739164\n ],\n [\n -90.49163818359375,\n 29.398926652739164\n ],\n [\n -90.49163818359375,\n 29.045965338037213\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"29","issue":"5","noUsgsAuthors":false,"publicationDate":"2021-05-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Macy, Aaron","contributorId":218917,"corporation":false,"usgs":false,"family":"Macy","given":"Aaron","email":"","affiliations":[{"id":39936,"text":"Dauphin Island Sea Lab, Dauphin Island, AL USA","active":true,"usgs":false}],"preferred":false,"id":838419,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Osland, Michael 0000-0001-9902-8692","orcid":"https://orcid.org/0000-0001-9902-8692","contributorId":219805,"corporation":false,"usgs":true,"family":"Osland","given":"Michael","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":838420,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cherry, Julia A.","contributorId":195565,"corporation":false,"usgs":false,"family":"Cherry","given":"Julia","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":838421,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cebrian, Just","contributorId":218914,"corporation":false,"usgs":false,"family":"Cebrian","given":"Just","email":"","affiliations":[{"id":39936,"text":"Dauphin Island Sea Lab, Dauphin Island, AL USA","active":true,"usgs":false}],"preferred":false,"id":838422,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70225152,"text":"70225152 - 2021 - Using landscape metrics to characterize towns along an urban-rural gradient","interactions":[],"lastModifiedDate":"2021-10-14T12:33:11.708912","indexId":"70225152","displayToPublicDate":"2021-07-01T07:29:00","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Using landscape metrics to characterize towns along an urban-rural gradient","docAbstract":"Urban-rural gradients are useful tools when examining the influence of human disturbances on ecological, social and coupled systems, yet the most commonly used gradient definitions are based on single broad measures such as housing density or percent forest cover that fail to capture landscape patterns important for conservation.
We present an approach to defining urban–rural gradients that integrates multiple landscape pattern metrics related to ecosystem processes important for natural resources and wildlife sustainability.
We develop a set of land cover composition and configuration metrics and then use them as inputs to a cluster analysis process that, in addition to grouping towns with similar attributes, identifies exemplar towns for each group. We compare the outcome of the cluster-based urban-rural gradient typology to outcomes for four commonly-used rule-based typologies and discuss implications for resource management and conservation.
The resulting cluster-based typology defines five town types (urban, suburban, exurban, rural, and agricultural) and notably identifies a bifurcation along the gradient distinguishing among rural forested and agricultural towns. Landscape patterns (e.g., core and islet forests) influence where individual towns fall along the gradient. Designations of town type differ substantially among the five different typologies, particularly along the middle of the gradient.
Understanding where a town occurs along the urban-rural gradient could aid local decision-makers in prioritizing and balancing between development and conservation scenarios. Variations in outcomes among the different urban-rural gradient typologies raise concerns that broad-measure classifications do not adequately account for important landscape patterns. We suggest future urban-rural gradient studies utilize more robust classification approaches.
","language":"English","publisher":"Springer","doi":"10.1007/s10980-021-01287-7","usgsCitation":"Kaminski, A.R., Bauer, D.M., Bell, K., Loftin, C., and Nelson, E., 2021, Using landscape metrics to characterize towns along an urban-rural gradient: Landscape Ecology, v. 36, p. 2937-2956, https://doi.org/10.1007/s10980-021-01287-7.","productDescription":"20 p.","startPage":"2937","endPage":"2956","ipdsId":"IP-105928","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":451686,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10980-021-01287-7","text":"Publisher Index Page"},{"id":390516,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Connecticut. 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Maine","active":true,"usgs":false}],"preferred":false,"id":825176,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Loftin, Cyndy 0000-0001-9104-3724 cyndy_loftin@usgs.gov","orcid":"https://orcid.org/0000-0001-9104-3724","contributorId":146427,"corporation":false,"usgs":true,"family":"Loftin","given":"Cyndy","email":"cyndy_loftin@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":825173,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nelson, Erik","contributorId":267713,"corporation":false,"usgs":false,"family":"Nelson","given":"Erik","affiliations":[{"id":33315,"text":"Bowdoin College","active":true,"usgs":false}],"preferred":false,"id":825177,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70223829,"text":"70223829 - 2021 - Time-evolving surface and subsurface signatures of Quaternary volcanism in the Cascades Arc: Reply","interactions":[],"lastModifiedDate":"2021-09-09T12:23:31.81675","indexId":"70223829","displayToPublicDate":"2021-07-01T07:22:12","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1796,"text":"Geology","active":true,"publicationSubtype":{"id":10}},"title":"Time-evolving surface and subsurface signatures of Quaternary volcanism in the Cascades Arc: Reply","docAbstract":"No abstract available.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/G49192Y.1","usgsCitation":"O'Hara, D., Karlstrom, L., and Ramsey, D.W., 2021, Time-evolving surface and subsurface signatures of Quaternary volcanism in the Cascades Arc: Reply: Geology, v. 49, no. 7, e526, 1 p., https://doi.org/10.1130/G49192Y.1.","productDescription":"e526, 1 p.","ipdsId":"IP-128958","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":451688,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/g49192y.1","text":"Publisher Index Page"},{"id":388991,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"49","issue":"7","noUsgsAuthors":false,"publicationDate":"2021-07-01","publicationStatus":"PW","contributors":{"authors":[{"text":"O'Hara, Daniel","contributorId":265508,"corporation":false,"usgs":false,"family":"O'Hara","given":"Daniel","affiliations":[{"id":54700,"text":"Vrije Universiteit Brussel","active":true,"usgs":false}],"preferred":false,"id":822821,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Karlstrom, Leif","contributorId":265509,"corporation":false,"usgs":false,"family":"Karlstrom","given":"Leif","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":822822,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ramsey, David W. 0000-0003-1698-2523 dramsey@usgs.gov","orcid":"https://orcid.org/0000-0003-1698-2523","contributorId":3819,"corporation":false,"usgs":true,"family":"Ramsey","given":"David","email":"dramsey@usgs.gov","middleInitial":"W.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":822823,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70232405,"text":"70232405 - 2021 - The distribution of anadromy in steelhead / rainbow trout in the Eel River, northwestern California","interactions":[],"lastModifiedDate":"2022-07-04T17:12:05.965896","indexId":"70232405","displayToPublicDate":"2021-07-01T06:58:26","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10946,"text":"California Fish and Wildlife Journal","active":true,"publicationSubtype":{"id":10}},"title":"The distribution of anadromy in steelhead / rainbow trout in the Eel River, northwestern California","docAbstract":"To inform management and conservation of the species, we investigated the distribution of anadromy and residency of steelhead/rainbow trout (Oncorhynchus mykiss) in the Eel River of northwestern California. We determined maternal anadromy versus residency for 106 juvenile O. mykiss using otolith microchemistry. To attempt to relate patterns of anadromy with environmental factors known to influence its distribution in O. mykiss in other places, fish were collected from 52 sites throughout the drainage covering a range of stream size (0.1–7.7 m3/s estimated mean annual run-off) and distance from the ocean (23–219 km). Sixty-one of 91 fish sampled below prospective barriers had anadromous mothers, while 1 of 15 fish sampled above barriers had an anadromous mother. We did not detect any influence of stream size or distance from the ocean on the occurrence of anadromy. Fish with resident mothers were found at 21 of 46 sites below barriers. The current broad distribution of fish with resident mothers indicates the importance of maintaining freshwater conditions suitable for resident adults and juveniles age-1 and older, such as preserving dry-season streamflows.
","language":"English","publisher":"California Department of Fish and Wildlife","doi":"10.51492/cfwj.107.7","usgsCitation":"Harvey, B.C., Nakamoto, R.J., Kent, A.J., and Zimmerman, C.E., 2021, The distribution of anadromy in steelhead / rainbow trout in the Eel River, northwestern California: California Fish and Wildlife Journal, v. 107, no. 2, p. 77-88, https://doi.org/10.51492/cfwj.107.7.","productDescription":"12 p.","startPage":"77","endPage":"88","ipdsId":"IP-129368","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":451690,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.51492/cfwj.107.7","text":"Publisher Index Page"},{"id":402802,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.76074218749999,\n 37.89219554724437\n ],\n [\n -121.06933593749999,\n 37.89219554724437\n ],\n [\n -121.06933593749999,\n 41.11246878918088\n ],\n [\n -124.76074218749999,\n 41.11246878918088\n ],\n [\n -124.76074218749999,\n 37.89219554724437\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"107","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-08-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Harvey, Bret C.","contributorId":292678,"corporation":false,"usgs":false,"family":"Harvey","given":"Bret","email":"","middleInitial":"C.","affiliations":[{"id":62967,"text":"U.S. Forest Service, Pacific Southwest Research Station","active":true,"usgs":false}],"preferred":false,"id":845439,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nakamoto, Rodney J.","contributorId":292679,"corporation":false,"usgs":false,"family":"Nakamoto","given":"Rodney","email":"","middleInitial":"J.","affiliations":[{"id":62967,"text":"U.S. Forest Service, Pacific Southwest Research Station","active":true,"usgs":false}],"preferred":false,"id":845440,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kent, Adam J.R.","contributorId":292680,"corporation":false,"usgs":false,"family":"Kent","given":"Adam","email":"","middleInitial":"J.R.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":845441,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zimmerman, Christian E. 0000-0002-3646-0688 czimmerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3646-0688","contributorId":410,"corporation":false,"usgs":true,"family":"Zimmerman","given":"Christian","email":"czimmerman@usgs.gov","middleInitial":"E.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":845442,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70223163,"text":"70223163 - 2021 - Conspecific and congeneric interactions shape increasing rates of breeding dispersal of northern spotted owls","interactions":[],"lastModifiedDate":"2021-10-06T15:55:10.235775","indexId":"70223163","displayToPublicDate":"2021-07-01T06:45:57","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Conspecific and congeneric interactions shape increasing rates of breeding dispersal of northern spotted owls","docAbstract":"Breeding dispersal, the movement from one breeding territory to another, is rare for philopatric species that evolved within relatively stable environments, such as the old-growth coniferous forests of the Pacific Northwest. Although dispersal is not inherently maladaptive, the consequences of increased dispersal on population dynamics in populations whose historical dispersal rates are low could be significant, particularly for a declining species. We examined rates and possible causes of breeding dispersal based on a sample of 4,118 northern spotted owls (Strix occidentalis caurina) monitored in seven study areas over 28 yr, 1990–2017, in Oregon and Washington, USA. Using a multistate mark–resight analysis, we investigated the potential impacts of an emergent congeneric competitor (barred owl Strix varia) and forest alteration (extrinsic factors), and social and individual conditions (intrinsic factors) on 408 successive and 1,372 nonsuccessive dispersal events between years. The annual probability of breeding dispersal increased for individual owls that had also dispersed in the previous year and decreased for owls on territories with historically high levels of reproduction. Intrinsic factors including pair status, prior reproductive success, and experience at a site, were also associated with breeding dispersal movements. The percent of monitored owls dispersing each year increased from ˜7% early in the study to ˜25% at the end of the study, which coincided with a rapid increase in numbers of invasive and competitively dominant barred owls. We suggest that the results presented here can inform spotted owl conservation efforts as we identify factors contributing to changing rates of demographic parameters including site fidelity and breeding dispersal. Our study further shows that increasing rates of breeding dispersal associated with population declines contribute to population instability and vulnerability of northern spotted owls to extinction, and the prognosis is unlikely to change unless active management interventions are undertaken.