Literature DB >> 16359777

Underwater video as a monitoring tool to detect change in seagrass cover.

Justin I McDonald1, Grey T Coupland, Gary A Kendrick.   

Abstract

To date seagrass monitoring has involved the removal of seagrass from its environment. In fragile or highly disturbed systems, monitoring using destructive techniques may interfere with the environment or add to the burden of disturbance. Video photography is a form of non-destructive monitoring that does not require the removal of seagrass or interference with the environment and has the potential to be a valuable tool in monitoring seagrass systems. This study investigated the efficacy of video photography as a tool for detecting change in seagrass cover, using the temperate Australian species Amphibolis antarctica (Labill.) Sonder ex Aschers. Using visual and random point estimates of seagrass cover from video footage, it was possible to determine the minimum sample size (number of random video frames) needed to detect change in seagrass cover, the minimum detectable change in cover and the probability of the monitoring design committing a Type II error. Video footage was examined at three scales: transects (m apart), sites (km apart) and regions (tens of km apart). Using visual and random point estimation techniques, a minimum sample size of ten quadrats per transect was required to detect change in uniform and variable seagrass cover. With ten quadrats it was possible to identify a minimum detectable change in cover of 15% for uniform and 30% for variable seagrass cover. Power analysis was used to determine the probability of committing a Type II error from the data. Region level data had low power, corresponding to a high risk of committing a Type II error. Site and transect level data had high power corresponding to a low risk of committing a Type II error. Based on this study's data, managers using video to monitor for change in seagrass cover are advised to use data from the smaller scale, for example, site and transect level data. By using data from the smaller scale, managers will have a low risk of incorrectly concluding there has not been a disturbance when one has actually occurred.

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Year:  2005        PMID: 16359777     DOI: 10.1016/j.jenvman.2005.08.021

Source DB:  PubMed          Journal:  J Environ Manage        ISSN: 0301-4797            Impact factor:   6.789


  3 in total

1.  Seagrass (Posidonia oceanica) monitoring in western Mediterranean: implications for management and conservation.

Authors:  Cecilia Lopez y Royo; Gérard Pergent; Christine Pergent-Martini; Gianna Casazza
Journal:  Environ Monit Assess       Date:  2010-01-21       Impact factor: 2.513

2.  Evidence of macroalgal colonization on newly ice-free areas following glacial retreat in Potter Cove (South Shetland Islands), Antarctica.

Authors:  María Liliana Quartino; Dolores Deregibus; Gabriela Laura Campana; Gustavo Edgar Juan Latorre; Fernando Roberto Momo
Journal:  PLoS One       Date:  2013-03-04       Impact factor: 3.240

3.  Error, Power, and Blind Sentinels: The Statistics of Seagrass Monitoring.

Authors:  Stewart T Schultz; Claudia Kruschel; Tatjana Bakran-Petricioli; Donat Petricioli
Journal:  PLoS One       Date:  2015-09-14       Impact factor: 3.240

  3 in total

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