A new method to describe seagrass habitat sampled during fisheries-independent monitoring

Jackson, Jered B.; Nemeth, Douglas J.

doi:10.1007/bf02782977

Cited by 4 publications

(4 citation statements)

References 16 publications

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“…The time needed for seagrass sampling depends greatly on whether in situ observations and plant harvesting are required, with sampling time reduced by avoiding need for observations by SCUBA and for processing large quantities of plant material (cf. Jackson and Nemeth 2007). Therefore, to minimize sampling time and associated costs, attributes monitored at tier 2 were limited to variables that could be measured either from a boat or by using snorkel.…”

Section: Measurable Attributesmentioning

confidence: 99%

Integrating Scales of Seagrass Monitoring to Meet Conservation Needs

Neckles

Kopp

Peterson

et al. 2011

Estuaries and Coasts

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We evaluated a hierarchical framework for seagrass monitoring in two estuaries in the northeastern USA: Little Pleasant Bay, Massachusetts, and Great South Bay/Moriches Bay, New York. This approach includes three tiers of monitoring that are integrated across spatial scales and sampling intensities. We identified monitoring attributes for determining attainment of conservation objectives to protect seagrass ecosystems from estuarine nutrient enrichment. Existing mapping programs provided large-scale information on seagrass distribution and bed sizes (tier 1 monitoring). We supplemented this with baywide, quadrat-based assessments of seagrass percent cover and canopy height at permanent sampling stations following a spatially distributed random design (tier 2 monitoring). Resampling simulations showed that four observations per station were sufficient to minimize bias in estimating mean percent cover on a bay-wide scale, and sample sizes of 55 stations in a 624-ha system and 198 stations in a 9,220-ha system were sufficient to detect absolute temporal increases in seagrass abundance from 25% to 49% cover and from 4% to 12% cover, respectively. We made highresolution measurements of seagrass condition (percent cover, canopy height, total and reproductive shoot density, biomass, and seagrass depth limit) at a representative index site in each system (tier 3 monitoring). Tier 3 data helped explain system-wide changes. Our results suggest tiered monitoring as an efficient and feasible way to detect and predict changes in seagrass systems relative to multi-scale conservation objectives.

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Section: Measurable Attributesmentioning

confidence: 99%

Integrating Scales of Seagrass Monitoring to Meet Conservation Needs

Neckles

Kopp

Peterson

et al. 2011

Estuaries and Coasts

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show abstract

“…The corresponding percent cover per sampling site was determined by getting the total percent cover of transects divided by the number of transects used for each sampling site. The percentage of seagrass cover of each sampling site was then categorized using the categories used by Jackson and Nemeth (2007), where poor = 0-25%, fair =26-50%, good = 51-75%, and excellent = 76-100%.…”

Section: Calculation Of Seagrass Coveragementioning

confidence: 99%

Seagrass Diversity and Distribution in Maribojoc Bay, Bohol, Philippines

MASCARIŇAS

2022

Am. J. Environ. Clim.

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Seagrasses are major parts of coastal and marine biodiversity. Unfortunately, these aquatic plants and their ecological values are virtually unknown to many Filipinos. This study assessed the seagrasses in Maribojoc Bay, particularly in the coastal areas of the three municipalities, namely Maribojoc, Dauis, Panglao, and the City of Tagbilaran. Ecological assessments were conducted to determine the composition, abundance, distribution, percent cover, diversity, dominance, and evenness of seagrass species. Eight sampling sites were surveyed from October to December 2020. Seven seagrass species were identified, with Thalassia hemprichii as the most abundant (52.79%). There was a significant difference (p>0.05) in seagrass species relative abundance. The Shannon diversity index implies low diversity (H’=1.40) of seagrass species. High dominance (2.98) and low evenness (0.72) were attributed to the high abundance of T. hemprichii in the seagrass beds. The seagrass coverage was characterized by patchy and continuous meadows, with percentage cover ranging from 17.45% (poor) – 60% (good). Maribojoc Bay had a seagrass percentage cover of 38.65%, which can be classified under “fair” conditions. Seagrass community structure implies sparse coverage and low diversity, probably due to the deterioration of once-continuous meadows. However, further studies concerning seagrass communities are recommended in order to implement rehabilitation program or improve current management in Maribojoc Bay.

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“…Satellite images provide with detailed information on seagrass canopy and other environmental indicators [41]. Various research papers report successful application of the image processing for the seagrass mapping [20,26,38,47,62,64,68,78,82,83,99,112,111,109,117,120,122,129,138].…”

Section: Research Problemmentioning

confidence: 99%

Seagrass Mapping and Monitoring Along the Coasts of Crete, Greece

Lemenkova¹

2019

Preprint

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Type: Master's Thesis (M.Sc.).School: University of Twente, Faculty of Geo-Information Science and Earth Observation (ITC).Supervisors: Albertus G. (Bert) Toxopeus, Valentijn Venus. Location: Netherlands, Enschede (Overijssel Province).The seagrasses, a unique group of aquatic plants, create complex, extremely diversified and productive ecological systems in the littoral coastal zones. The only flowering plant in the world that is able to live completely submerged, seagrasses play vital role in the marine ecosystems of the World Ocean. Seagrasses are the most important component in the environmental food chain of the coastal ecosystems, being a vital food source for various marine species (e.g. fish, dugongs, turtles, swans), and a producer of organic matter, which is the very basis of the food web. The P.oceanica seagrass is an endemic for the Mediterranean region, and a main species in the marine coastal environment of Greece. Meadows of P.oceanica are subjected to the human activities, because they occur in coastal areas, where they are affected both by anthropogenic and by climatic and environmental factors. Nowadays P.oceanica is in the alarming state of regression, because of the deterioration of the environment in the Mediterranean Sea. Due to these reasons, P.oceanica is a protected species since 1988 in some European countries (France). Monitoring P.oceanica is therefore an important contribution to the saving and protecting the environment of Mediterranean region. The current MSc thesis focuses on the monitoring of seagrass P.oceanica along the northern coasts of Crete Island, Greece, and investigates the application of the remote sensing techniques for the seagrass mapping. This research was articulated in two parts, where the first one involves an ecological approach to the seagrass distribution in various regions around the globe and the experience of seagrass monitoring nowadays. The second part of this work has technical character and investigates the application of the remote sensing techniques towards seagrass mapping. It, furthermore, focuses on the optical properties of the P.oceanica and other seafloor cover types, and studies distinguishability of various seafloor cover types. Studies of the optical characteristics of separate seafloor cover types were made with purpose to clarify, whether their spectral properties change with varying environmental conditions.Special attention has been drawn on the role of environmental factors on the distribution of P.oceanica along the coasts of Crete, and in particular, how the optical properties of the seafloor cover types, i.e. spectral reflectance, are being changed under varying external conditions, e.g. water column, amount of suspended particles and sediments in the seawater, and water temperature. For this purpose we studied differences in the spectral reflectance of P.oceanica and other bottom cover types at three distinct depths. The diverse spectral values entail variations in optical properties of the seafloor cover types at changing environmental conditions. We applied WASI Water Color Simulator (WASI) simulation techniques for the modelling of the optical parameters of various seafloor cover types by various spaceborne imaging spectrometers (MEdium Resolution Imaging Spectrometer (MERIS), Sea-viewing Wide Field-of-view Sensor (SeaWiFS), Coastal Zone Color Scanner (CZCS) and MODerate resolution Imaging Spectroradiometer (MODIS)), in order to understand their suitability and possible limitations for the seagrass mapping. Fieldwork research sites were presented by separate locations on the northern coast of Crete region (Ligaria, Agia Pelagia, Xerocampos). The additional measurements of the reflectance spectra of the seawater with and without sediments have been made in aquarium tank in 2009 by means of Trios-RAMSES spectroradiometer. Parallel to the collection of spectra signatures, we captured the imagery for the seagrass mapping, which consists of the aerial images from the Google Earth website and the satellite Landsat TM and ETM+ scenes.

show abstract

A new method to describe seagrass habitat sampled during fisheries-independent monitoring

Cited by 4 publications

References 16 publications

Integrating Scales of Seagrass Monitoring to Meet Conservation Needs

Integrating Scales of Seagrass Monitoring to Meet Conservation Needs

Seagrass Diversity and Distribution in Maribojoc Bay, Bohol, Philippines

Seagrass Mapping and Monitoring Along the Coasts of Crete, Greece

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