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dc.contributor.authorKimball, ME
dc.contributor.authorConnolly, RM
dc.contributor.authorAlford, SB
dc.contributor.authorColombano, DD
dc.contributor.authorJames, WR
dc.contributor.authorKenworthy, MD
dc.contributor.authorNorris, GS
dc.contributor.authorOllerhead, J
dc.contributor.authorRamsden, S
dc.contributor.authorRehage, JS
dc.contributor.authorSparks, EL
dc.contributor.authorWaltham, NJ
dc.contributor.authorWorthington, TA
dc.contributor.authorTaylor, MD
dc.date.accessioned2021-05-11T00:38:08Z
dc.date.available2021-05-11T00:38:08Z
dc.date.issued2021
dc.identifier.issn1559-2723
dc.identifier.doi10.1007/s12237-021-00939-w
dc.identifier.urihttp://hdl.handle.net/10072/404271
dc.description.abstractOver the last 20 years, innovations have led to the development of exciting new technologies and novel applications of established technologies, collectively increasing the scale, scope, and quality of research possible in tidal marsh systems. Thus, ecological research on marshes is being revolutionized, in the same way as ecological research more generally, by the availability of new tools and analytical techniques. This perspective highlights current and potential applications of novel research technologies for marsh ecology. These are summarized under several themes: (1.) imagery — sophisticated imaging sensors mounted on satellites, drones, and underwater vehicles; (2.) animal tracking — acoustic telemetry, passive integrated transponder (PIT) tags, and satellite tracking, and (3.) biotracers — investigation of energy pathways and food web structure using chemical tracers such as compound-specific stable isotopes, isotope addition experiments, contaminant analysis, and eDNA. While the adoption of these technological advances has greatly enhanced our ability to examine contemporary questions in tidal marsh ecology, these applications also create significant challenges with the accessibility, processing, and synthesis of the large amounts of data generated. Implementation of open science practices has allowed for greater access to data. Newly available machine learning algorithms have been widely applied to resolve the challenge of detecting patterns in massive environmental datasets. The potential integration on digital platforms of multiple, large data streams measuring physical and biological components of tidal marsh ecosystems is an opportunity to advance science support for management responses needed in a rapidly changing coastal landscape.
dc.description.peerreviewedYes
dc.languageen
dc.publisherSpringer Science and Business Media LLC
dc.relation.ispartofjournalEstuaries and Coasts
dc.subject.fieldofresearchEarth sciences
dc.subject.fieldofresearchBiological oceanography
dc.subject.fieldofresearchEnvironmental sciences
dc.subject.fieldofresearchBiological sciences
dc.subject.fieldofresearchMarine and estuarine ecology (incl. marine ichthyology)
dc.subject.fieldofresearchcode37
dc.subject.fieldofresearchcode370801
dc.subject.fieldofresearchcode41
dc.subject.fieldofresearchcode31
dc.subject.fieldofresearchcode310305
dc.titleNovel Applications of Technology for Advancing Tidal Marsh Ecology
dc.typeJournal article
dc.type.descriptionC1 - Articles
dcterms.bibliographicCitationKimball, ME; Connolly, RM; Alford, SB; Colombano, DD; James, WR; Kenworthy, MD; Norris, GS; Ollerhead, J; Ramsden, S; Rehage, JS; Sparks, EL; Waltham, NJ; Worthington, TA; Taylor, MD, Novel Applications of Technology for Advancing Tidal Marsh Ecology, Estuaries and Coasts, 2021
dc.date.updated2021-05-09T23:22:05Z
gro.description.notepublicThis publication has been entered in Griffith Research Online as an advanced online version.
gro.hasfulltextNo Full Text
gro.griffith.authorConnolly, Rod M.


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