Item talk:Q259940
From geokb
{
"USGS Publications Warehouse": { "@context": "https://schema.org", "@type": "Article", "additionalType": "Journal Article", "name": "Warmer winters increase the biomass of phytoplankton in a large floodplain river", "identifier": [ { "@type": "PropertyValue", "propertyID": "USGS Publications Warehouse IndexID", "value": "70224929", "url": "https://pubs.usgs.gov/publication/70224929" }, { "@type": "PropertyValue", "propertyID": "USGS Publications Warehouse Internal ID", "value": 70224929 }, { "@type": "PropertyValue", "propertyID": "DOI", "value": "10.1029/2020JG006135", "url": "https://doi.org/10.1029/2020JG006135" } ], "journal": { "@type": "Periodical", "name": "Journal of Geophysical Research: Biogeosciences", "volumeNumber": "126", "issueNumber": "9" }, "inLanguage": "en", "isPartOf": [ { "@type": "CreativeWorkSeries", "name": "Journal of Geophysical Research: Biogeosciences" } ], "datePublished": "2021", "dateModified": "2021-10-06", "abstract": "Winters are changing rapidly across the globe but the implications for aquatic productivity and food webs are not well understood. In addition, the degree to which winter dynamics in aquatic systems respond to large-scale climate versus ecosystem-level factors is unclear but important for understanding and managing potential changes. We used a unique winter data set from the Upper Mississippi River System to explore spatial and temporal patterns in phytoplankton biomass (chlorophyll\u00a0a, CHL) and associated environmental covariates across 25\u00a0years and \u223c1,500 river km. To assess the role of regional climate versus site-specific drivers of winter CHL, we evaluated whether there were coherent long-term CHL dynamics from north to south and across lotic-lentic areas. We then estimated the degree to which these patterns were associated with climate variability (i.e., the Multivariate El Nino-Southern Oscillation Index), winter severity (freezing degree days), river discharge, or site-specific environmental variables (ice depth, snow depth, and nutrient concentrations). We found that winter CHL was typically highest in ice-free reaches and backwater lakes, occasionally exceeding summer values. We did not find highly synchronous CHL dynamics across the basin, but instead show that temporal trends were independent among river reaches and lotic-lentic areas of the river. Moreover, after accounting for these spatial dynamics, we found that CHL was most responsive to winter air temperature, being consistently higher in years with warmer winters across the basin. These results indicate that although productivity dynamics are highly dynamic within large river ecosystems, changes in the duration and severity of winter may uniformly increase wintertime productivity.", "description": "e2020JG006135, 21 p.", "publisher": { "@type": "Organization", "name": "American Geophysical Union" }, "author": [ { "@type": "Person", "name": "Smits, Adrianne P", "givenName": "Adrianne P", "familyName": "Smits", "identifier": { "@type": "PropertyValue", "propertyID": "ORCID", "value": "0000-0001-9967-5419", "url": "https://orcid.org/0000-0001-9967-5419" }, "affiliation": [ { "@type": "Organization", "name": "University of Washington" } ] }, { "@type": "Person", "name": "Schuerell, Mark D.", "givenName": "Mark D.", "familyName": "Schuerell", "affiliation": [ { "@type": "Organization", "name": "University of Washington, Seattle" } ] }, { "@type": "Person", "name": "Houser, Jeffrey N. jhouser@usgs.gov", "givenName": "Jeffrey N.", "familyName": "Houser", "email": "jhouser@usgs.gov", "identifier": { "@type": "PropertyValue", "propertyID": "ORCID", "value": "0000-0003-3295-3132", "url": "https://orcid.org/0000-0003-3295-3132" }, "affiliation": [ { "@type": "Organization", "name": "Upper Midwest Environmental Sciences Center", "url": "https://www.usgs.gov/centers/upper-midwest-environmental-sciences-center" } ] }, { "@type": "Person", "name": "Jankowski, Kathi Jo", "givenName": "Kathi Jo", "familyName": "Jankowski", "identifier": { "@type": "PropertyValue", "propertyID": "ORCID", "value": "0000-0002-3292-4182", "url": "https://orcid.org/0000-0002-3292-4182" }, "affiliation": [ { "@type": "Organization", "name": "Upper Midwest Environmental Sciences Center", "url": "https://www.usgs.gov/centers/upper-midwest-environmental-sciences-center" } ] } ], "funder": [ { "@type": "Organization", "name": "Upper Midwest Environmental Sciences Center", "url": "https://www.usgs.gov/centers/upper-midwest-environmental-sciences-center" } ], "spatialCoverage": [ { "@type": "Place", "additionalType": "country", "name": "United States", "url": "https://geonames.org/4074035" }, { "@type": "Place", "additionalType": "state", "name": "Minnesota" }, { "@type": "Place", "additionalType": "state", "name": "Missouri" }, { "@type": "Place", "additionalType": "state", "name": "Illinois" }, { "@type": "Place", "additionalType": "state", "name": "Iowa" }, { "@type": "Place", "additionalType": "state", "name": "Wisconsin" }, { "@type": "Place", "geo": [ { "@type": "GeoShape", "additionalProperty": { "@type": "PropertyValue", "name": "GeoJSON", "value": { "type": "FeatureCollection", "features": [ { "type": "Feature", "properties": {}, "geometry": { "type": "Polygon", "coordinates": [ [ [ -88.68164062500001, 37.23032838760387 ], [ -89.78027343750001, 39.97712009843961 ], [ -89.73632812500001, 41.11246878918086 ], [ -89.4287109375, 42.65012181368025 ], [ -90.17578125, 43.54854811091283 ], [ -90.35156249999999, 44.99588261816546 ], [ -91.58203125, 45.767522962149904 ], [ -92.68066406250001, 45.920587344733626 ], [ -94.5263671875, 46.40756396630065 ], [ -95.1416015625, 45.120052841530516 ], [ -94.3505859375, 43.64402584769947 ], [ -93.33984375000001, 41.508577297439324 ], [ -92.4609375, 39.33429742980725 ], [ -91.23046875000001, 37.82280243352756 ], [ -89.29687500000001, 36.98500309285591 ], [ -88.68164062500001, 37.23032838760387 ] ] ] } } ] } } }, { "@type": "GeoCoordinates", "latitude": 42.13043168155096, "longitude": -91.75174400703443 } ] } ] }
}