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1 Algae Volume 23(1): 83-90, 2008 Zostera marina L. Using a Digital Echosounder to Estimate Eelgrass (Zostera marina L.) Cover and Biomass in Kwangyang Bay Keunyong Kim, Ju-hyoung Kim and Kwang Young Kim* Department of Oceanography, Chonnam National University, Gwangju , Korea Eelgrass beds are very productive and provide nursery functions for a variety of fish and shellfish species. Management for the conservation of eelgrass beds along the Korean coasts is critical, and requires comprehensive strategies such as vegetation mapping. We suggest a mapping method to spatial distribution and quantify of eelgrass beds using a digital echosounder. Echosounding data were collected from the northeast part of Kwangyang Bay, on the south of Korea, in March, A transducer was attached to a boat equipped with a DGPS. The boat completed a transect survey scanning whole eelgrass beds of 11.7 km 2 with a speed of m s -1 (3-4 knot). The acoustic reflectivity of eelgrass allowed for detection and explicit measurements of canopy cover and height. The results showed that eelgrass bed was distributed in depth from 1.19 to 3.6 m (below MSL) and total dry weight biomass of 4.1 ton with a vegetation area of 4.05 km 2. This technique was found to be an effective way to undertake the patch size and biomass of eelgrass over large areas as nondestructive sampling. Key Words: acoustic reflectivity, biomass, canopy cover, digital echosounder, eelgrass beds, Kwangyang Bay, vegetation mapping (Zostera marina L ) (Fortes 1986) (Duarte and Cebrián 1996) (Thayer et al 1984 Short and Neckles 1999) (Pergent-Martini et al 2006) 4% *Corresponding author (kykim@chonnam.ac.kr) 29% 11% (Duarte 1991 Dennison et al 1993) (Duarte 1995) (Livingston et al 1998) ( 2001 Kim and Choi 2004) (Kim and Choi 2004) (submersed aquatic vegetation SAV)

2 84 Algae Vol. 23(1), 2008 (Dennis 1984 Madsen 1993) (Sabol et al 2002) (landscape) (Mumford et al 1995) 1 m s -1 (Norris et al 1997) (Sabol et al Winfield et al 2007) GPS(global positioning system) (Sabol et al ) (Stent and Hanley 1985 Carbo and Molero 1997 Guan et al 1999 Sabol et al 2002) (SAV) (Sabol et al 2002 Komatsu et al 2003 Erhan 2005 Haga et al 2007 Kevin et al 2007) (2006) (patch) (edge) Fig. 1. Map showing the study area and three eelgrass vegetations. Fig. 2. Processing and reporting for survey in hypothetical vegetated area. Circles indicate bottom area of ping, brown circle for bare and yellow for bare (Sabol et al. 2002). (fragmentation) (Kim and Choi 2004)

3 Kim et al.: Echosounder to Estimate Cover and Biomass 85 Fig. 3. Example of echogram obtained from Biosonics echosounder in an eelgrass bed. Pictures show bottom along track, ping by ping (left) and oscilloscope display showing voltage return for ping # 2400 only (right). Eelgrass shoots are green on soft bottom (yellow). 9 km 17 km m (Zostera marina L ) ( 1) ( 2) ( 3) 3 (Fig 1) (Kim and Choi 2004) DT-X Digital Echosounder (Biosonics Inc USA) 420 khz (Single-beam) 6 (pulse width) 0 1 ms (pings rate) 5 pings s -1 (transducer) (Biofin dead weight towing vehicle Biosonics USA) 0 5 m m s -1 (3-4 knot) DGPS (Differential Global Positioning System) SAV (Mean Sea Level MSL) EcoSAV 1 0 (Biosonics USA) (canopy height) (cycle) 15 pings (Figs 2 3) (g DW m -2 ) 7 2 SCUBA 3 m cm 2 m 3 6 m EcoSAV 15 pings 1 5 ping 2 m s -1 6 m (g DW m -2 ) km 2 1 (MSL) m 60% 1 9 m (Fig 4A) m 2 5 m (Fig 4B) m 3 2 m (Fig 4C) km km km 2

4 86 Algae Vol. 23(1), 2008 Fig. 4. Combined presentation of cover (below, in percent) and height (above, in meters) of eelgrass. Site 1 (A), Site 2(B) and Site 3(C). 1 ( ) ( ) 7 (Fig 4A) 2 3 (Fig 4B) 3 (Fig 4C) EcoSAV 1 60% % 3% 20 40% 1 37% 40-60% 23% 60 80% 6 4% (Fig 5A) m (89%) m 32 6% m 1 6% (Fig 5B) 2 40% 20% 6% 20 40% 8% 40 60% 25% 60 80% 27% % 35% (Fig 5C) m 90% % m m 1 7 % (Fig 5D) % 32 3% 20% 12 3% 40 60% 18 5% 60 80% 23 1% % 13 8% (Fig 5E) m 87 1% m 1 4% (Fig 5F) (db) db EcoSAV 2 = (R 2 = 0 80) 5 ( %) % 30% kg DW (Table 1) 20 40% kg DW 1

5 Kim et al.: Echosounder to Estimate Cover and Biomass 87 Fig. 5. The distributions of cover (left column) and height (right column) of eelgrass in Site 1(upper), Site 2 (mid) and Site 3 (lower) (Table 1) % m kg DW (Table 1) % m kg DW % 28 9 kg DW (Table 1) 0 20% m kg DW (Pergent-Martini et al 2006)

6 88 Algae Vol. 23(1), 2008 Table 1. Area and biomass of eelgrass beds in each cover class in three sites of Kwangyang Bay derived from EcoSAV Site 1 Site 2 Site 3 Cover (%) class Area Biomass Area Biomass Area Biomass (m 2 ) (DW kg) (m 2 ) (DW kg) (m 2 ) (DW kg) Sum of biomass (DW ton) (DT-X Biosonics Inc USA) SAV(submerged aquatic vegetation) 60 g WW m -2 8 cm (Sabol et al 2002) 0 5 m (Sabol et al 2002) (Mohamed 2007) 0 1 m g WW m -2 DT-X 4 05 km % 3 9 Kim and Choi(2004) (2004) g DW m g DW m ( 2000) 1 sand 1 4% silt 34 4% clay 64 2% 2 sand 2 4% silt 84 3% clay 13 3% 3 sand 7 7% silt 42 4% clay 49 9% 3 Kim and Choi (2004) (Lee et al 2005 Short et al 2007)

7 Kim et al.: Echosounder to Estimate Cover and Biomass 89 (Kaldy and Lee 2007) m m 3 (Sanriku) 115 m 156 m 40 (Komatsu et al 2003) (Winfield et al 2007) (tracking) (rhipidia) 100 km (Källström et al 2008) 3 ( 2005) (threshold level) -130 db (Sabol et al 2002) 3 (Sabol et al 2002) (Seagrass Habitat) Ocean and Polar Res 28: ( ) 24: pp 2001 (Zostera marina L ) Korean J Environ Biol 19: J Kor Fish Soc 37: Carbo R. and Molero A.C Scattering strength of a Gelidium biomass bottom. Applied Acoustics 51: Dennis W.M Aquatic macrophyton sampling: An Overview. In: Dennis W.M. and Isom B.G. (eds), Ecological assessment of macrophyton: Collection, use, and meaning of data. ASTM Special Technical Publication 843, Philadelphia, Pennsylvania. pp Dennison W.C., Orth R.J., Moore K.A., Stevenson J.C., Carter V., Kollar S., Bergstron P.W. and Batiuk R.A Assessing water quality with submersed aquatic vegetation. Bioscience 43: Duarte C.M Seagrass depth limits. Aquat. Bot. 40: Duarte C.M Submerged aquatic vegetation in relation to different nutrient regimes. Ophelia 41: Duarte C.M. and Cebrián J The fate of marine autotrophic production. Limnol. Oceanogr. 41: Erhan M A comparison of the contribution of zooplankton and nekton taxa to the near-surface acoustic structure of three

8 90 Algae Vol. 23(1), 2008 Turkish seas. Mar. Ecol. 26: Fortes M.D Taxonomy and Ecology of Philippine Seagrass. Ph. D. Dissertation, University of Philippines. Diliman, Quezon City, Philippines, 254 pp. Guan W., Chamberlain R.H., Sabol, B.M. and Doering P.H Mapping submerged aquatic vegetation with GIS in the Caloosahatchee Estuary: Evaluation of different interpolation methods. Marine Geodesy 22: Haga H., Ohtsuka T., Matsuda M. and Ashiya M Echosounding observations of coverage, height, PVI, and biomass of submerged macrophytes in the southern basin of Lake Biwa, Japan. Jpn. Soc. Limnol. 8: Kaldy J.E. and Lee K-.S Factors controlling Zostera marina L. growth in the eastern and western Pacific Ocean: Comparisons between Korea and Oregon, USA. Aquat. Bot. 87: Källström B., Nyqvist A., Åberg P., Bodin M. and André C Seed rafting as a dispersal strategy for eelgrass (Zostera marina). Aquat. Bot. 88: Kevin M.B., Matthew P.W. and Charles A.W Hydroacoustics as a tool for assessing fish biomass and size distribution associated with discrete shallow water estuarine habitats in Louisiana. Estuaries and Coasts 30: Kim K.Y. and Choi T.S Variability in abundance and morphological attributes of Zostera marina L. from the southern coast of Korea. Bot. Mar. 47: Komatsu T., Igarashi C. Tatsukawa K., Sultana S. Matsuoka Y. and Harada S Use of multi-beam to map seagrass beds in Otsuchi Bay on the Sanriku coast of Japan. Aquat. Living Resour. 16: Lee S.Y., Choi C.I., Suh Y. and Mukai H Seasonal variation in morphology, growth and reproduction of Zostera caespitosa on the southern coast of Korea. Aquat. Bot. 83: Madsen J.D Biomass techniques for monitoring and assessing control of aquatic vegetation. Lake Reservoir Manage. 7: Mohamed A.A Modeling coupling between eelgrass Zoster marina and water flow. Mar. Ecol. Prog. Ser. 338: Mumford T.F. Jr., Wyllie-Echeverria S. and Norris J Inventory of eelgrass (Zostera spp.) in Washington State. In: Puget Sound Water Quality Authority, Puget Sound Research 95 Proceedings. Olympia, WA. pp Norris J.G., Wyllie-Echeverria S., Mumford T., Bailey A. and Turner T Estimating basal area coverage of subtidal seagrass beds using underwater videography. Aquat. Bot. 58: Pergent-Martini C., Pasqualini V., Ferrat L. and Pergent G Ecological data in integrated coastal zone management: Case study of Posidonia oceanica meadows along the corsican coastline (Mediterranean Sea). Environ. Manage. 38: Sabol B.M., Melton Jr. R.E., Chamberlain, R., Doering P.H. and Haunert K Evaluation of a digital echosounder system for detection of submersed aquatic vegetation. Estuaries 25: Short F.T. and Neckles A.H The effect of global climate change on seagrasses. Aquat. Bot. 63: Short F., Carruthers T. Dennison W. and Waycott M Global seagrass distribution and diversity: A bioregional model. J. Exp. Mar. Bio. Ecol. 350: Stent C.J. and Hanley S A recording echosounder for assessing submerged aquatic plant populations in shallow lakes. Aquat. Bot. 21: Winfield I.J., Onoufriou C., O Connel M.J., Godlewska M., Ward R.M., Brown A.F. and Yallop M.L Assessment in two shallow lakes of a hydroacoustic system for surveying aquatic macrophytes. Hydrobiologia 584: Received 5 January 2008 Accepted 20 February 2008

04김호걸(39~50)ok

04김호걸(39~50)ok Journal of Environmental Impact Assessment, Vol. 22, No. 1(2013) pp.39~50 Prediction of Landslides Occurrence Probability under Climate Change using MaxEnt Model Kim, Hogul* Lee, Dong-Kun** Mo, Yongwon*