Item talk:Q299267
From geokb
{
"USGS Publications Warehouse": { "@context": "https://schema.org", "@type": "Article", "additionalType": "Journal Article", "name": "Confluences function as ecological hotspots: Geomorphic and regional drivers can help identify patterns of fish distribution within a seascape", "identifier": [ { "@type": "PropertyValue", "propertyID": "USGS Publications Warehouse IndexID", "value": "70227944", "url": "https://pubs.usgs.gov/publication/70227944" }, { "@type": "PropertyValue", "propertyID": "USGS Publications Warehouse Internal ID", "value": 70227944 }, { "@type": "PropertyValue", "propertyID": "DOI", "value": "10.3354/meps13088", "url": "https://doi.org/10.3354/meps13088" } ], "journal": { "@type": "Periodical", "name": "Marine Ecology Progress Series", "volumeNumber": "629", "issueNumber": null }, "inLanguage": "en", "isPartOf": [ { "@type": "CreativeWorkSeries", "name": "Marine Ecology Progress Series" } ], "datePublished": "2019", "dateModified": "2022-02-02", "abstract": "Quantifying heterogeneity in animal distributions through space and time is a precursor to addressing many important research and management issues. Obtaining these distributional data is especially difficult for mobile organisms that use broader geographic extents. Here, we asked if the merger between 2 research directions\u2014(1) quantifying spatial linkages between fish and geomorphic features (e.g. confluences) and (2) analyzing larger-scale, multi-metric organismal patterns\u2014can provide a broader geographic context for ecological issues that depend on understanding dynamic fish distribution. To address these objectives, we collected data from 59 tagged striped bass\u00a0Morone saxatilis\u00a0that were detected by a 26 acoustic receiver array deployed within Plum Island Estuary, MA, USA. We examined these telemetry data using generalized linear mixed models and chi-squared, cluster, and network analyses. Geomorphic site types informed the estuary-wide distribution of striped bass in that tagged fish spent the most time at confluence junctions; however, they did not spend the same amount of time at all junctions. Relative to integrating multiple metrics, number of tagged fish, residence time, and number of movements were not the same across all receivers. When all 3 metrics were considered together, 4 distinct clusters of distributional patterns emerged. Network analyses connected geomorphology and multi-metric seascape patterns. Confluence junctions in the Rowley and Middle regions were the most connected (high centrality) and most used sites (high residence time). Although confluence junctions function as ecological hotspots, researchers and managers will benefit from interpreting geomorphology within a larger geographic context.", "description": "16 p.", "publisher": { "@type": "Organization", "name": "Inter-Research Science Publisher" }, "author": [ { "@type": "Person", "name": "Gerber, Kayla", "givenName": "Kayla", "familyName": "Gerber", "affiliation": [ { "@type": "Organization", "name": "KY wr" } ] }, { "@type": "Person", "name": "Smith, Joseph", "givenName": "Joseph", "familyName": "Smith", "affiliation": [ { "@type": "Organization", "name": "NOAA" } ] }, { "@type": "Person", "name": "Taylor, Ryland", "givenName": "Ryland", "familyName": "Taylor", "affiliation": [ { "@type": "Organization", "name": "ksu" } ] }, { "@type": "Person", "name": "Mather, Martha E. mather@usgs.gov", "givenName": "Martha E.", "familyName": "Mather", "email": "mather@usgs.gov", "identifier": { "@type": "PropertyValue", "propertyID": "ORCID", "value": 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