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

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

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

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…

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]

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

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

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

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!!!

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 …

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