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dc.contributor.authorHamilton, David P
dc.contributor.authorCarey, Cayelan C
dc.contributor.authorArvola, Lauri
dc.contributor.authorArzberger, Peter
dc.contributor.authorBrewer, Carol
dc.contributor.authorCole, Jon J
dc.contributor.authorGaiser, Evelyn
dc.contributor.authorHanson, Paul C
dc.contributor.authorIbelings, Bas W
dc.contributor.authorJennings, Eleanor
dc.contributor.authorKratz, Tim K
dc.contributor.authorLin, Fang-Pang
dc.contributor.authorMcBride, Christopher G
dc.contributor.authorMarques, David de Motta
dc.contributor.authorMuraoka, Kohji
dc.contributor.authorNishri, Ami
dc.contributor.authorQin, Boqiang
dc.contributor.authorRead, Jordan S
dc.contributor.authorRose, Kevin C
dc.contributor.authorRyder, Elizabeth
dc.contributor.authorWeathers, Kathleen C
dc.contributor.authorZhu, Guangwei
dc.contributor.authorTrolle, Dennis
dc.contributor.authorBrookes, Justin D
dc.date.accessioned2017-05-18T00:11:29Z
dc.date.available2017-05-18T00:11:29Z
dc.date.issued2015
dc.identifier.issn2044-2041
dc.identifier.doi10.5268/IW-5.1.566
dc.identifier.urihttp://hdl.handle.net/10072/337268
dc.description.abstractA Global Lake Ecological Observatory Network (GLEON; www.gleon.org) has formed to provide a coordinated response to the need for scientific understanding of lake processes, utilising technological advances available from autonomous sensors. The organisation embraces a grassroots approach to engage researchers from varying disciplines, sites spanning geographic and ecological gradients, and novel sensor and cyberinfrastructure to synthesise high-frequency lake data at scales ranging from local to global. The high-frequency data provide a platform to rigorously validate process-based ecological models because model simulation time steps are better aligned with sensor measurements than with lower-frequency, manual samples. Two case studies from Trout Bog, Wisconsin, USA, and Lake Rotoehu, North Island, New Zealand, are presented to demonstrate that in the past, ecological model outputs (e.g., temperature, chlorophyll) have been relatively poorly validated based on a limited number of directly comparable measurements, both in time and space. The case studies demonstrate some of the difficulties of mapping sensor measurements directly to model state variable outputs as well as the opportunities to use deviations between sensor measurements and model simulations to better inform process understanding. Well-validated ecological models provide a mechanism to extrapolate high-frequency sensor data in space and time, thereby potentially creating a fully 3-dimensional simulation of key variables of interest.
dc.description.peerreviewedYes
dc.languageEnglish
dc.language.isoeng
dc.publisherFreshwater Biological Association
dc.relation.ispartofpagefrom49
dc.relation.ispartofpageto56
dc.relation.ispartofissue1
dc.relation.ispartofjournalInland Waters
dc.relation.ispartofvolume5
dc.subject.fieldofresearchEcology not elsewhere classified
dc.subject.fieldofresearchPhysical Geography and Environmental Geoscience
dc.subject.fieldofresearchEnvironmental Science and Management
dc.subject.fieldofresearchEcology
dc.subject.fieldofresearchcode060299
dc.subject.fieldofresearchcode0406
dc.subject.fieldofresearchcode0502
dc.subject.fieldofresearchcode0602
dc.titleA Global lake ecological observatory network (GLEON) for synthesising high-frequency sensor data for validation of deterministic ecological models
dc.typeJournal article
dc.type.descriptionC1 - Articles
dc.type.codeC - Journal Articles
dc.description.versionVersion of Record (VoR)
gro.rights.copyright© 2015 International Society of Limnology. This is an electronic version of an article published in Inland Waters, Vol 5, No 1, Pages: 49-56 and DOI: 10.5268/IW-5.1.566. Inland Waters is available online at: www.fba.org.uk/journals with the open URL of your article.
gro.hasfulltextFull Text
gro.griffith.authorHamilton, David P.


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