1 R.S. Lingga
Estimating St. Mawes seagrass coverage using underwater videography Riahate S. Lingga* Claire Eatock** *Second year marine science student, Falmouth Marine School, Killigrew Street, Falmouth, Cornwall, TR11 3QS, UK **Project supervisor, Falmouth Marine School, Killigrew Street, Falmouth, Cornwall, TR11 3QS, UK
Abstract In order to estimate St. Mawes seagrass coverage, it was essential to map the study area. Once the outer limit of seagrass bed is established, non-random sampling positions were recorded using handheld global positioning system (GPS). Geographic information system (GIS) program was used to determine the measurement for both the sample and survey areas. The sampling for estimating the seagrass coverage from the sample area is achieved by using non-destructive sampling procedure. Random line transect is used to obtained data using underwater videography. DAFOR scale was use to subjectively measure the seagrass density. One of the advantages of underwater videography is the footages are permanent archives that can be utilize for further analysis other than seagrass. Keywords: Seagrass; Zostera marina; Seagrass beds; Underwater videography; Coverage; Fal estuary; St. Mawes; Line transect; DAFOR; GIS; Mapping
*Corresponding author. E-mail: riahate@yahoo.com, Tel: (44) 01326 310310, Fax: (44) 01326 310300 1 Present address: Falmouth Marine School, Killigrew Street, Falmouth, Cornwall, TR11 3QS, UK, e-mail: riahate.lingga547@live.coranwall.ac.uk
1. Introduction Zostera species are in the family Zosteracea where they live in intertidal and subtidal inshore waters, forming an important habitat and a basis of the food web (Moore and Short, 2006). They are characterised by monoecious with monopodial, creeping rhizomes that are usually perennial (Den Hartog, 1970 and Tomlison, 1982 cited Moore and Short, 2006 and Den Hartog and Kuo, 2006) and their shoots are characterized by both sexually reproductive stems and vegetative foliage (Moore and Short, 2006). Zostera marina is estimated to be originated in the Pacific between 8 and 20 million years ago, the same region with the highest genetic diversity occur (Olsen et al., 2004 cited Moore and Short, 2006). Zostera marina is the dominant species found in the coastal and estuarine areas in the North Atlantic (Short et al., 2007) and forms extensive beds from sheltered areas to exposed coasts (Moore and Short, 2006). They can grow from a depth of +2m to -12 m mean sea level (MSL) (Short et al., 1993a cited Moore and Short, 2006) and predominantly occur in a monoculture with occasional occurrence with a variety of species such as in the US, mid-Atlantic (Orth and Moore, 1983b and Ferguson et al., 1993 cited Moore and Short, 2006). The morphological characteristics of Zostera spp. are affected by substrate type, depth, temperature, location, light and nutrient availability and wave regimes (Short, 1983, Lee et al., 2000, Moore et al., 1996, Fonseca and Bell, 1998, Abal et al., 1994, Short et al., 1995, MarbĂ et al., 1996 and Koch and Beer, 1996 cited Moore and Short, 2006). Light availability
2 R.S. Lingga influenced density, productivity and shoots size, as the light availability became higher, the higher the density and productivity and the smaller the shoots of the zostera. Depth influenced the physical size of the zostera together with different level of nutrients within the sediments and the structures of the beds are affected by the physical factors such as current velocity and exposure to wave (Moore and Short, 2006). The phenology of Zostera spp. is strongly related to latitude and flowering sequence delayed as latitude increases (Philip et al., 1983, Silberhorn et al., 1983 and Walker et al., 2001 cited Moore and Short, 2006) and temperature can be an important factor affecting sexual reproduction (Moore and Short, 2006). There are three species of Zostera occur in the UK, viz Zostera noltii (dwarf eelgrass) found highest on the shore, zostera angustifolia (narrow-leaved eelgrass) on the mid to lower shore and Zostera marina (eelgrass) predominantly in the sublittoral (UKBAP). Zostera marina has the most extensive population in the UK and in Falmouth, Cornwall, Zostera marina can be found on both the Fal and Helford estuaries. 2. Method 2.1. Overview and study site The background of my research is the integration between visual images from the underwater video footages of St. Mawes seagrass bed and handheld GPS position. Data are collected by means of drift and straight line transects through the study area and appraised. Appraisal includes categorising seagrass presence and or absence and a subjective measure of seagrass density. All the data collected are recorded in a spreadsheet format compatible with ArcGIS program to create thematic maps and study and sample area measurement for statistical purpose. The study area is St. Mawes harbour the first harbour of the Fal estuary and denoted by the points of Carricknath to the South and St Mawes Castle to the North (St Mawes Pier and Harbour Company) (Figure1). It is located in the west of Falmouth harbour at 50° 9' 28.8972" N, 5° 0' 51.534" W (Figure 1).
Scubar
Cable plug onto
Monitor unit
Camera head is suspended by pole, ± 1m2 frame
Start/end Recording
Deploy from the side of the vessel
Delta wing
Analyse
Cable plug onto
Excel 2007
ArcGIS 9. ArcCatalog version 9,2 and 9,3
Laptop computer
+
Mark GPS Position
Suspended by rope, ± 1m2 frame
Manually recorded the time, depth, GIS position, recording time, coverage, remarks and other on the project book GIS map, total study area (m2) and sample area (m2) for statistical purpose
Figure 1 Schematic diagram of the methodology
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Figure 2 GIS map of the Fal estuary
2.2. Survey equipment Surveys and data collection are conducted aboard non-research vessels, Chinnook, a 28-ft. open sport fishing vessel equipped with Garmin fishfinder 100 to measure the depth and Killigrew, Falmouth Harbour Commission vessel equipped with Raymarine C70 to measure the depth of the sample area. Vessel position, latitude, longitude, SW and BNG are acquired by two handhelds GPS, Garmin 12 and 60. The SW and BNG are the compatible coordinate with the ArcGIS program use to create thematic map. Garmin 12 is used to record the position in latitude and longitude and Garmin 60 recorded in SW and BNG. Underwater video footages are obtained from using two different underwater equipments, scubar and delta wing. Scubar is a portable and lightweight underwater digital video recorder system
4 R.S. Lingga consists of telescopic extension pole, adjustable camera head and monitor unit. Pole dimension is 1,5~4m and 1,5~10m. Camera head is adjustable and encapsulated within black anodysed aluminium case, acetol and 316 stainless wands and powers by 12VDC 120mA(LED OFF)/250mA(LED ON). It’s equipped with a fixed 6.00mm standard lens at a 120⁰ angle and 6 x white LED illumination. Monitor unit has 5.6” and 8.4” monitor screen and on/off/brightness/colour and recording functions and powered by 300mA. The recording media is SD card that can be play back instantly and copy onto another media or computer. The camera head is connected to one end of the pole and the other end is connected by pole cable to monitor unit. The head can be adjusted to the right position in order to capture the footage at the right angle. Delta wing is an underwater camera video system weighing approximately 20kg and utilise closed circuit television (CCTV) colour camera. The camera is encapsulated within waterproof polyvinyl chloride housing and equipped with 6,0mm lens at a 90⁰ angle and connected to laptop computer for visual imagery and recording. Both the scubar and delta wing are deployed directly on the side of the vessel (Figure 2). 2.3. Video footage sampling and mapping study area procedure Survey and data collection are started during low tide. Two types of line transects were used in collecting the video footage. The first was drift transect using the scubar. Randomly choose the starting point of the sample area within the study area, turn the vessel machine off, prepare the equipment, turn on the camera and the monitor, check equipment make sure the recording system work properly and deployed the scubar from the side of the vessel. At each start and end of each transect the following information were recorded manually, time, depth, GPS position or the mark number, recording time and remarks or searass coverage (percentage cover). Lower the scubar slowly until it reached the approximately distance that the field view is about 1m2 (frame) (Figure 1). As the vessel drift the person holding the pole raises and lower the pole to follow seabed contour as per the instruction from another person looking at the monitor. Every few minutes the time, depth, GPS position or the mark number, recording time and remarks were manually recorded. The same method of deployment and recording applied for delta wing. The only different was type of transect. In straight line transect, the vessel was moving at a constant speed in a straight line (vertical or horizontal) within the study area (Figure 3). Mapping the study area was done by deployed scubar in non-random point. Deployed the scubar at the outer limit of the seagrass bed and recorded the GPS position, depth and remarks. This technique is very time consuming but necessary to do in order to create a parameter of the study area.
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Figure 3 GIS map of the survey area
2.4. Processing data To make the video footage from each transect comparable, the overall transect duration for each transect was edited by removing the beginning or the ending of the footage that was either in poor quality (the image cannot be verify) or no seagrass was present (Shucksmith et al., 2006). Input all the GPS coordinates, depth, recording time (start and end) and remarks (percentage coverage) into an excel spreadsheet. Watch the raw video footage, edited and adding additional remark onto the spreadsheet. Linkages excel spreadsheet with the ArcGIS 9 program to create a map of the study area by connecting the outer points (Figure 2).
6 R.S. Lingga 3. Estimating coverage from underwater video footage 3.1. Results The first survey was conducted during the summer time in June and July 2010. The main objectives of these surveys were to establish the presence of Zostera marina within the study area followed by first non-recording transect line. Data collections were conducted five times over ten months period. The total of 26 transects were made through the study area using procedures described in section 2 of this paper. 10 out of 26 transects were recorded and only 8 can be use to estimate the study area (Table 2). The total recording time for all ten transects were more than 110 minutes of video footage. Approximately 175 GPS position were recorded, 18 of them were outside the study area and 12 points were used to mapped the survey area (St. Mawes seagrass bed) (Figure 2). The final video footage used was 95 minutes from 8 transects. All the recorded GPS position recorded onto the spreadsheet were linked to ArcGIS program to create a thematic map and measured the size of both the study and sample areas. The measurement of study area was approximately 195943 m2 (19,59 hectares or 48,42 acres) and sample area was 3486 m2. The mean seagrass coverage was 2,66 or between 19-20,5% and the index of dispersion was 1,03 > 1 = contagious or clumped. The standard error (S.E.) was 0,17 and the confidence intervals for 95% was between 11% and 50%, therefore the study area for 11% was approximately 21553,73 m2 and 50% was approximately 97971,15 m2. Table 1 Data scale measurement
Scale* 5 4 3 2 1 0
% Cover 76-100 51-75 26-50 11-25 1-10 0
f ** 18 19 10 15 27 6
*Ordinal scale = DAFOR (D=Dominant (5), A=Abundance (4), F=Frequent (3), O=Occasional (2), R=Rare (1) and Not present (0)) **f = frequency
Table 2 Summary of the underwater video transect data
Quad* 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Trans** 1 0 0 0 5 5 4 3 4 4 3 5
Trans 2 1 1 1 1
Trans 3 4 5 4 4 3 3 4 2 5 2 5 5
Trans 4 5 5 2 1 1
Trans 5 5 5 5 5 5 5 5 5 3 3 2 0
Trans 6 4 4 4 2 2 4 3 1 1 1 2 4 1 4 1
Trans 7 1 2 2 1 2 2 5 4 2 1 1 1 1 1 1
Trans 8 4 4 4 3 3 2 4 4 1 2 1 0 0
7 R.S. Lingga 16 17 18 19 20 21 22 Sum Mean S.D.a D.I.b S.E.c C.I.d
1 3 1 1 1 1 1 95 2,66 1,65 1,03 0,17 95% 2,66Âą0,33
*Quad = quadrat ** Trans = Transect
a=standard deviation c=standard error
b=dispersion of index d=confident interval
3.2. Analysis Seagrass coverage analysis from the video footage was conducted in scale equal to 1 m2 quadrat. To estimate percentage seagrass cover from the video footage, ordinal scale measurement was use. DAFOR scale is used to record seagrass coverage within the quadrat into the following (Fowler et al., 2003) and refer to table 1 for the percentage cover: Dominant Abundant Frequent Occasional Rare Not present
score 5 4 3 2 1 0
Video footage of seagrass recorded along the 8 line transects was played and frames selected for analysis using a random number table taken (McDonald et al., 2006) from Fowler et al., 2003, appendix 1. Visual (VIS) estimation technique is used. Individual randomly selected frame was paused, digitised using windows video maker program and analysed. Each frame can be stored as still photograph on a memory stick (Whorff and Griffing 1992). Each randomly selected frame was equal to 1 m2 quadrat and each quadrat was between the 60 seconds or 1 minute range, e.g. quadrat 1 was from footage 0-60 secs, quadrat 2 from min 1-1:59, quadrat 5 from min 6-6:59, etc. The longer the footage duration the bigger the number of the quadrat will be. The numbers of minute was equal to the number of quadrat and refer to table 2 for the data. In nature there are three general ways in which objects may be dispersed: regularly, randomly or contagiously (clumped or aggregated). The general tentative to distinguish them is by comparing the variance size with sample. Regular dispersion is when a sample count data with small variance or s2/sample mean<1. Random dispersion is when a sample of count data with intermediate variance or s2/sample meanâ&#x2030;&#x2C6;1. Contagious dispersal is when a sample count data with larger variance or s2/sample mean>1 (Fowler et al., 2003). From an index of dispersion seagrass dispersion within the St. Mawes was contagious or clumped dispersion.
8 R.S. Lingga Following the standard procedure and using the Central Limit Theorem, standard error was use as a measure of confidence interval of the mean of sample area. The standard error is used as an indicator of how good an estimate of sample mean to study area. 95% confident intervals of study area lie within Âą 1,96 S.E (between sample mean - 1,96 S.E. and sample mean + 1,96 S.E.). All the measurements were done using the ArcGIS program. GPS position is the main key in using the ArcGIS as a measurement tool and this particular program fit perfectly with my project. By taking the GPS position of the outer limit of the seagrass bed, the study area can be measured. Sample area is measured by adding up all the line transects. 4. Discussion Seagrass coverage fluctuates over time and variation in cover is due to natural disturbance such as wind, current, storm and animals (McDonald et al., 2006). Underwater video footage can be used to monitor changes in the seagrass bed over time. This is a non-destructive sampling and monitoring system that the data can be used for further characterizes seagrass or other study. Another advantage of underwater videography is that the data collected, the footage provides permanent archives. The limitation of using underwater videography is mainly to do with the equipment availability and function. The poor or low quality of the footage from low light availability, water clarity, equipment faulty and current are some of the things that can have direct effect. Poor quality may or may not have direct impact on analyse thus effecting the result. GPS position accuracy with actual images cannot be 100%. This is simply because we are using two separate equipments that needed to be manually recorded. This however will not have a major impact the result. The use of big vessel will have limitation in sampling area near the shore or extremely shallow or turbid water. Once again this has not been serious limitation. A more serious limitation will be the subjective criteria to classify seagrass coverage. To limit bias or error, a standard measurement or guide in estimating the coverage is essential. Further study is needed in order to understand the sudden changes within the seagrass beds over several months. Mapping the distribution and density of existing seagrass beds are useful in order to detect changes in the seasgrass ecosystems (Short et al., 2006). My project was only the beginning of a long continuous study. I was only able to estimate seagrass coverage from one out of three seagrass beds within the Fal estuary. Finding and mapping seagrass beds were very time consuming especially when we can only work within a certain time period, during low tide. Using the available equipment, survey can only be done during low tide and the weather is good and has to stop when the tides are coming. A minimum of three people is needed in doing the survey using the same equipments. My recommendation for future work is to finish mapping the other two beds within the Fal estuary and compare the seagrass coverage between the beds. Find out if there is any different in dispersion distribution, biology and ecology between the seagrass beds. Measure the abundance by measuring the canopy height, cover, density and biomass. This can be an ongoing project that will need the cooperation between the school and Falmouth Harbour Commission (FHC) and Natural England (NE). The school will provide with person doing the survey and create a report that can be use by both the FHC and NE.
9 R.S. Lingga Acknowledgements I am very grateful to Clive Pollitt and family. Thank you for all the helps from arranging the survey, collecting data and providing with the necessary underwater equipments. Thank you to Harriet and David from FHC, Yvonne for the GIS lesson, Tell and Collins for the help with my research, Bethany Gay and Josh for helping us with the survey and Louise Hockley for the inside on some of the methodology. I would like to acknowledge several meaningful email correspondents with Jim Norris (the corresponding author of the journal I am using as one of my main reference) and James Fourqurean (Florida International University). References Ackerman, J.D., 2006. Sexual Reproduction of Seagrasses: Pollination in the marine Context. In: Larkum, A.W.D., Orth, R.J., Duarte, C. M. (Eds.), Seagrass: Biology, ecology and conservation. The Netherlands: Springer, pp 89-109 [Online]. Available at: http://www.dawsonera.com/depp/reader/protected/external/EBookView/S9781402029837/S1 6 [Accessed: 29/4/11]. Den Hartog, C., Kuo, J., 2006. Taxonomy and biogeography of seagrasses. In: Larkum, A.W.D., Orth, R.J., Duarte, C. M. (Eds.), Seagrass: Biology, ecology and conservation. The Netherlands: Springer, pp 1-23 [Online]. Available at: http://www.dawsonera.com/depp/reader/protected/external/EBookView/S9781402029837/S1 6 [Accessed: 29/4/11]. Duarte, C.M., 2010. Seagrass meadows. The Encyclopedia of Earth [Online]. Available at: http://www.eoearth.org/article/Seagrass_meadows [Accessed: 29/4/11]. Fowler, J., Cohen, L., Jarvis, P., 2003. Practical statistics for field biology. Wiley, England, pp 1-95. Hemminga, M.A., Duarte, C.M., 2000. Seagrass Ecology. Cambridge: Cambridge University Press [Online]. Available at:. http://books.google.co.uk/books?id=MzpWBS_2CEcC&printsec=frontcover&dq=Seagrass+E cology&source=bl&ots=7bGhXmsX2z&sig=zxYGkFTkfL0bCJV_khiAU0zad0&hl=en&ei=NA_5TJEEce5hAezhansCA&sa=X&oi=book_result&ct=result&resnum=1&ved=0CCIQ6AEwAA#v=o nepage&q&f=false [Accessed: 29/4/11]. Magorrian, B.H., Service, M., 1998. Analysis of underwater visual data to identify the impact of physical disturbance on horse mussel (Modiolus modiolus) beds. Mar. Pol. Bul. 36, 354359. McDonald, J.I., Coupland, G.T., Kendrick, G.A., 2006. Underwater video as a monitoring tool to detect change in seagrass cover. Journal of Environmental Management. 80, 148-155. Meese, J., Tomich, P.A., 1992. Dots on the rocks: a comparison of percent cover estimation methods. J. Exp. Mar. Biol. Ecol. 165, 59-73. Moore, K. A., Short, F.T., 2006. Zostera: Biology, Ecology and Management. In: Larkum, A.W.D., Orth, R.J., Duarte, C. M. (Eds.), Seagrass: Biology, ecology and conservation. The Netherlands: Springer, pp 25-50 [Online]. Available at:
10 R.S. Lingga http://www.dawsonera.com/depp/reader/protected/external/EBookView/S9781402029837/S1 6 [Accessed: 29/4/11]. Norris, J.G., Wyllie-Echeverria, S., Mumford, T., Bailey, A., Turner, T., 1997. Estimating basal area coverage of subtidal seagrass beds using underwater videography. Aquat. Bot. 58, 269-287. Schultz, S.T., 2008. Seagrass monitoring by underwater videography: disturbance regimes, sampling design, and statistical power. Aquat. Bot. 88, 228-238. Short, F., Carruthers, T., Dennison, W., Waycott, M., 2007. Global seagrass distribution and diversity: a bioregional model. J. Exp. Mar. Biol. Ecol. 350, 3-20. Short, F.T., Mckenzie, L.J., Coles, R.G., Vidler, K.P., Gaeckle, J.L., 2006. SeagrassNet manual for scientific monitoring of seagrass habitat, Worldwide edition, University of New Hampshire Publication. pp. 5-75. Shucksmith, R., Hinz, H., Bergmann, M., Kaiser, M.J., 2006. Evaluation of habitat use by adult plaice (Pleuronectes platessa L.) using underwater video survey techniques. Journal of Sea Reseach. 56, 317-328. St Mawes Pier & Harbour Company. St Mawes Harbour [Online]. Available at: http://www.stmawesharbour.co.uk/ [Accessed: 25/4/11]. UK Biodiversity Action Plan (UK BAP). Seagrass bed [Online]. Available at: http://www.ukbap.org.uk/UKPlans.aspx?ID=35#1 [Accessed: 3/5/11]. Waycott, M., Procaccini, G., Les, D.H., Reusch, T.B.H., 2006. Seagrass Evolution, Ecology and Conservation: A Genetic Perspective. In: Larkum, A.W.D., Orth, R.J., Duarte, C.M. (Eds.), Seagrass: Biology, ecology and conservation. The Netherlands: Springer, pp 25-50 [Online]. Available at: http://www.dawsonera.com/depp/reader/protected/external/EBookView/S9781402029837/S1 6 [Accessed: 29/4/11]. Whorff, J.S. and Griffing, l., 1992. A video recording and analysis system used to sample intertidal communities. J. Exp. Mar. Biol. Ecol. 160, 1-12.