Displaying Seagrass Community Change Using Remote Sensing

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Displaying Seagrass Community Change Using Remote Sensing Marc Slattery & Greg Easson University of Mississippi

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Seagrass Communities Worldwide-a standout amongst the most imperative marine biological communities: basic nursery living space for some waterfront & pelagic species monetary asset fisheries, tourism & biodiversity sustaining reason for naturally critical species bewilders for wave vitality and beach front disintegration crucial shelter for debilitated species

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Environmental Factors Controlling Seagrass Biomass/Abundance supplements H 2 O section light saltiness epiphytes temperature supplements silt August March July December Manatee-grass: Syringodium filiforme seagrass developing season Seagrass Biology Not all seagrasses are made equivalent… Turtle-grass: Thalassia testidinum species applicable to Grand Bay NERR… Shoal-grass: Halodule wrightii Widgeon-grass: Ruppia maritima

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Modeling Seagrass Communities Problem: administration of seagrass groups requires administration of seagrass populaces [=productivity]… P. Fong & M. Harwell, 1994. Displaying seagrass groups in tropical and subtropical coves and estuaries: a scientific amalgamation of flow theories. Notice of Marine Science 54:757-781. Biomass seagrass[t+1] = Biomass seagrass[t] + Productivity seagrass - Loss seagrass  [Loss f (senescence)] Productivity seagrass = Pmax seagrass (Salinity seagrass x Temperature seagrass x Light seagrass x supplements seagrass ) [productivity  assc w/ nutrients] [productivity  assc w/ light] [productivity  assc w/ temperature] [productivity  assc w/ salinity] Goals of this Project: 1. Evaluate the capacity of remote detecting stages to give information significant to the Fong & Harwell model of seagrass group efficiency. Contrast information from remote detecting stages and information gathered on the ground to figure out which approach gives a superior expectation of seagrass group efficiency. Contemplations: 1. Halodule & Ruppia have comparative wide/high resiliences to saltiness [McMillan & Moseley 1967; Murphy et al 2003]: surpasses the extremes of GBNERR-slighted… 2. Halodule & Ruppia have comparative high resistances to supplement levels [Thursby 1984; Pulich 1989]-since water section supplement levels are restricting, and epiphytes depend on these, this esteem impacts seagrasses more…

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Resource observing information Biomass Ruppia Halodule Fall '07 Fall '07 Spring '08 Spring '08 fleeting examining worldly inspecting Experimental Design Satellite-based information Light [MODIS-daily] Temperature [MODIS-daily] Nutrients (intermediary: Chl a ) [MODIS-daily] Ground-based information Biomass t+1 = Biomass t + Productivity - Loss [rearrange and fathom for misfortune utilizing satellite-based and ground-based parameters of profitability… ] insights on the two information sets… Light [Onset-ceaseless; & institutionalized to IL1700] Temperature [Onset-continuous] Nutrients [Hach-monthly]

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Grand Bay NERR Seagrass Ecosystem Middle Bay Grand Bay Jose Bay Pont Aux Chenes

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In Situ Data ANOVA: noteworthy time impact, site impact ANOVA: huge time impact, site impact ANOVA: huge site impact ANOVA: critical time impact, site impact

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Remote Sensing Data from In situ contemplates Nitrate [NO 3 ]: Y=0.255+7.557*X supplement Phosphate [PO 4 ]: Y=0.135-0.213*X Chl a

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Comparative Statistics Productivity seagrass = Pmax seagrass (Temperature seagrass x Light seagrass x supplements seagrass ) + species 2… In situ demonstrate 5 Remote model 0 - 5 Relative Seagrass Productivity hypothetical qualities - 10 - 15 09/07 10/07 11/07 12/07 01/08 02/08 03/08 Date Paired t - test: t-esteem = - 1.261 P = 0.2541 Remote-detecting model yields positive seagrass efficiency amid the developing season!!!

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Conclusions Remote detecting stages can be utilized, with a few contemplations, to populate parameters of the Fong & Harwell model of seagrass group efficiency. In situ information gave better scale determination of true conditions; yet transient coordinations may counterbalance some of this advantage. Agreeable work between satellite-based and ground-based information procurement groups seems to offer the best open doors for seagrass asset supervisors. Feasible arrangements Assess the Fong & Harwell display in St. Joseph's Bay, FL  framework is overwhelmed by Thalassia & Syringodium …

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Acknowledgments Anne Boettcher, USA Cole Easson, UM Brenna Ehmen, USA Deb Gochfeld, UM Justin Janaskie, UM Dorota Kutrzeba, UM Chris May, GBNERR Scotty Polston, UM Jim Weston, UM NASA Grant #: NNS06AA65D