{"refrec":{"BRefID":294759,"RR":"<b>Daggers, T.D.; Kromkamp, J.C.; Herman, P.M.J.; van der Wal, D.</b> (2018). A model to assess microphytobenthic primary production in tidal systems using satellite remote sensing. <i>Remote Sens. Environ. 211</i>: 129-145. <a href=\"https://dx.doi.org/10.1016/j.rse.2018.03.037\" target=\"_blank\">https://dx.doi.org/10.1016/j.rse.2018.03.037</a>","BEntID":286829,"PublicFlag":1,"CheckedFlag":0,"wosflag":1,"vabbflag":1,"RefStringPartII":". <i>Remote Sens. Environ. 211</i>: 129-145. <a href=\"https://dx.doi.org/10.1016/j.rse.2018.03.037\" target=\"_blank\">https://dx.doi.org/10.1016/j.rse.2018.03.037</a>","DocTypID":8,"DocType":"Journal article","MarineFlag":1,"FreshFlag":1,"BrackishFlag":1,"TerrestrialFlag":0,"Authorstring":"Daggers, T.D.; Kromkamp, J.C.; Herman, P.M.J.; van der Wal, D.","OrigTitleTranslFlag":0,"Authorstringtrunc":"Daggers, T.D. <i>et al.</i>","Englishabstract":"Quantifying spatial variability in intertidal benthic productivity is necessary to guide management of estuaries and to understand estuarine ecological processes, including the amount of benthic organic carbon available for grazing, burial and transport to the pelagic zone. We developed a model to assess microphytobenthic (MPB) primary production using (1) remotely sensed information on MPB biomass and remotely sensed information on sediment mud content, (2) surface irradiance and ambient temperature (both from local meteorological observations), (3) directly-measured photosynthetic parameters and (4) a tidal model. MPB biomass was estimated using the normalized-difference vegetation index (NDVI) and mud content was predicted using surface reflectance in the blue and near-infrared, both from Landsat 8 satellite imagery. The photosynthetic capacity (maximum photosynthesis rate normalized to MPB chl-<i>a</i>) was estimated from ambient temperature, while photosynthetic efficiency and the light saturation parameter were derived from <i>in situ</i> fluorometry-based production measurements (PAM). The influence of tides (submergence by turbid water) on MPB production was accounted for in the model. The method was validated on several locations in two temperate tidal basins in the Netherlands (Oosterschelde and Westerschelde). Model based production rates (mg C m<sup>−2</sup> h<sup>−1</sup>) matched well with an independent set of <i>in situ</i> (PAM) measurement based production rates (Oosterschelde: RMSE = 9.7, mean error = 1.5, χ = 0.57; Westerschelde: RMSE = 46.7, mean error = −17.6, χ = 0.9). The relationship between photosynthetic capacity and temperature shows considerable variation and may be improved by using sediment surface temperature instead of ambient temperature. A sensitivity analysis revealed that emersion duration and mud content determine most of the variability in MPB production. Our results demonstrate that it is possible to derive a satellite remote sensing-based overview of average hourly and daily MPB primary production rates at the macro scale. As the proposed model is generic, the model can be applied to other tidal systems to assess spatial variability in MPB primary production at the macro scale after calibration at the site of interest. Model calibration, results and possible applications for regular monitoring of MPB production are discussed below.","AbstractOtherLang":null,"BibLvlCode":"AS","StandardTitle":"A model to assess microphytobenthic primary production in tidal systems using satellite remote sensing","OrigTitleLangCode":"en","OrigTitleLangCodeExtended":"eng","OrigTitleLangID":15,"DateLastModified":{"date":"2026-04-19 01:31:54.390830","timezone_type":1,"timezone":"+02:00"},"UserAccessRight":null,"UserAccID":null,"AuthorKeywords":"Microphytobenthos; Primary production; Tidal flats; Photosynthesis; Remote sensing; Multiple linear regression; Mapping","OtherDescriptors":null,"Notes":null,"AnaPub":2018,"MonPub":null,"DateUpdate":"2022-10-11","DateCreate":"2018-04-19","SecASFANote":null,"ConfID":null,"PeerRev":1,"VlizCoreFlag":1,"WoScode":"WOS:000433650700011","VABBcode":null,"OpenAcc":0,"DOI":"10.1016/j.rse.2018.03.037"},"refs":null,"anarec":{"AnaID":294759,"PubliDate":2018,"Pagination":"129-145","XtraPublOfAnaID":null,"ISBN":null,"Volume":"211","Issue":null,"BRefMon":null,"BRefMonRR":null,"BRefXtra":null,"BRefXtraRR":null,"SerBRefID":43865,"SerRR":"Remote Sensing of Environment. Elsevier: New York,.  ISSN 0034-4257; e-ISSN 1879-0704","StandardTitleSer":"Remote Sensing of Environment","ISSN":"0034-4257","AbbrevSer":"Remote Sens. Environ.","StandardTitleMon":null,"StartPage":129,"Pages":17,"ToPubliDate":null,"BRefBibLvlCode":"S","SerNotes":null},"monrec":null,"serrec":null,"relations":[{"YBRefID":312302,"RefStrFull":"<b>Daggers, T.D.; Kromkamp, J.C.; Herman, P.M.J.; van der Wal, D.</b> (2019). Corrigendum to “A model to assess microphytobenthic primary production in tidal systems using satellite remote sensing” [Remote Sens. Environ. 211 (2018) 129–145]. <i>Remote Sens. Environ. 230</i>: 111206. <a href=\"https://dx.doi.org/10.1016/j.rse.2019.05.025\" target=\"_blank\">https://dx.doi.org/10.1016/j.rse.2019.05.025</a>","RelID":4,"Relation":"Related to","StandardTitle":"Corrigendum to “A model to assess microphytobenthic primary production in tidal systems using satellite remote sensing” [Remote Sens. 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