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Marine Ecology Progress Series

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MEPS 530:1-14 (2015)  -  DOI:

Rapid monitoring of seagrass biomass using a simple linear modelling approach, in the field and from space

Mitchell Lyons1,*, Chris Roelfsema2, Eva Kovacs2, Jimena Samper-Villarreal3, Megan Saunders3, Paul Maxwell4, Stuart Phinn2

1Centre for Ecosystem Science, School of Biological, Earth and Environmental Sciences, University of New South Wales, Sydney 2052, Australia
2Biophysical Remote Sensing Group, School of Geography, Planning and Environmental Management, University of Queensland, Brisbane 4072, Australia
3Marine Spatial Ecology Lab, School of Biological Sciences, University of Queensland, Brisbane 4072, Australia
4School of Chemical Engineering, University of Queensland, Brisbane 4072, Australia
*Corresponding author:

ABSTRACT: Seagrass meadows are globally significant carbon sinks and increasingly threatened; and seagrass habitat provides critical ecosystem services, for which above-ground biomass is a key indicator. The capacity to quantify biomass in seagrass ecosystems is both critical and urgent, yet no methods exist to perform this at the large spatial scale required for management (e.g. regional/continental). We built linear model relationships between in situ above-ground biomass and seagrass percentage cover per seagrass species to estimate biomass from both point-based and landscape scale (>100 km2) seagrass data. First we used a set of linear models to estimate the biomass component of each seagrass species in over 20000 benthic photos. We then adapted this approach to estimate biomass from a time-series of remote sensing derived seagrass percentage cover and dominant species maps. We demonstrate accurate estimation of above-ground biomass using a set of methods that is not only more time and resource efficient than existing methods, but is sufficiently robust and generalisable for application at large spatial or temporal scales. Our method allows for quantification of above-ground biomass in seagrass ecosystems over spatial scales larger than can be tractably assessed using current site- and point-based measurement approaches, and at scales that are required to understand and manage seagrass systems to tackle anthropogenic climate change and other impacts.

KEY WORDS: Eelgrass · Satellite mapping · Remote sensing · Ground truth · Management · Halophila · Halodule · Zostera · Syringodium · Cymodocea

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Cite this article as: Lyons M, Roelfsema C, Kovacs E, Samper-Villarreal J, Saunders M, Maxwell P, Phinn S (2015) Rapid monitoring of seagrass biomass using a simple linear modelling approach, in the field and from space. Mar Ecol Prog Ser 530:1-14.

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