Geraldton beach wrack dynamics and quantification via Environmental photo- monitoring (Photomon)

Transcription

1 Geraldton beach wrack dynamics and quantification via Environmental photo- monitoring (Photomon) Caitlin Rae, Glenn Hyndes and Michael Payne School of Science, Edith Cowan University Northern Agricultural Catchments Council

2 Background: Drifting macrophytes consist of many species of seagrass and algae (Baring et al. 0). During storms or large swell events, seagrass and algae are often ripped from the seafloor by hydrodynamic forcing and either float to the surface and drift, or tumble along the seafloor (Baring et al. 0; NACC 0a). In South West Australia, this hydrodynamic forcing typically occurs during storm events during the period late autumn to early spring (NACC 0a). In the swash zone of sandy beaches, drifting macrophytes are pushed into the surf zone by wave, tidal and current forcing where they form dense accumulations before being washed ashore (Crawley & Hyndes 007; Crawley et al. 009). Drifting macrophytes may eventually be stranded on beaches and form large piles of beach- cast wrack which can then re- enter the surf zone with subsequent high tides (Ince et al. 007). Wrack has been shown to provide a range of important ecosystem services through stabilising beaches and dunes from erosion, recycling nutrients for their return to the marine environment and supply of nutrients to dune vegetation, and providing direct food sources for both marine and terrestrial invertebrates and indirect food sources for higher level consumers including fish and lizards (Crawley et al. 009; Mellbrand et al. 0). The specific role(s) that wrack plays on sandy beaches depends on the region, due to the different types of material that can be washed into surf zones and onto beaches (NACC 0a). Understanding the role of wrack in coastal ecosystems, therefore, requires an examination of the dynamics and ecology of wrack at the regional or local level. This is particularly important given the pressure by community and industry to remove wrack from beaches in some locations due to its odour, unsightliness, or interruption to facilities, such as launching ramps (NACC 0a). Additionally, in some areas, wrack is removed by the community for use as compost in gardens, or by coastal managers for dune stabilisation works (NACC, 0). Depending on the amount of wrack being removed, and its ecological role, the removal of such material could have consequences on the coastal ecosystem as it has been shown to influence fish and invertebrate communities, as well as drive food webs in those systems in the Perth region (Robertson & Lenanton 98; Lenanton & Caputi 989; Crawley & Hyndes 007; Ince et al. 007; Crawley et al. 009; Mellbrand et al. 0).

3 Wrack is a common feature of surf zones and beaches along the mid- west coast of Western Australia (NACC 0a), yet there is limited information on the ecological role of this material in the region. This study aims to determine the depth and biomass of wrack material becoming stranded on beaches in the Geraldton region, as well as establishing a photo point method (adapted from Kirkman 978; Mellors 99; McKechnie & Fairweather 00; Duong & Fairweather 0) and photo point criteria with the goal of being able to obtain estimates of total wrack depth, biomass and composition based on photo- monitoring. This will allow for the validation of the photo- monitoring programme (Photomon), initiated by the Northern Agricultural Catchment Council (NACC), carried out by the community. Materials and Methods: The photo- monitoring application, Photomon, was developed by NACC initially to assist community volunteers in Geraldton, Western Australia. It monitors changes in their local beaches and incorporates features aimed at simplifying the photo- monitoring process while increasing its accuracy. To validate this programme through the collection of wrack quantity and composition data, this study examined wrack deposits at a variety of beaches (sites) along Geraldton s urban coastline in August, September and December, 0. On each sampling occasion, five sites were determined based on sites already existing in the Photomon database, as well as where wrack was commonly deposited. At each site, photo points were established (point in the middle of the beach profile) and one photo was taken south and another taken north. A 0m transect running parallel to the shore was established south and north of these photo points. Along these parallel transects, three randomised transects running perpendicular to the shore were set up, with a fourth standardised transect at 0m to capture the Field- of- View (FOV) of the beach. Along each perpendicular transect, the depth (cm) of the wrack was measured using a marked stake every metre from where the wet wrack material was deposited across the width of the beach to the end of where dry wrack material had accumulated. To determine the wrack composition, a 0. x 0.m quadrat was randomly placed within the dry wrack line and wet wrack line within the Field- of- View of the photo point (established in

4 the Photomon). This was replicated another four times ( replicates in total) along parallel transects both south and north of the photo point. In each quadrat, percentage cover and wet scale (of where the wrack was deposited on the beaches) was noted and the wrack was sorted into the categories and then weighed: seagrass mix (Posidonia and Amphibolis), kelp (Ecklonia), brown algae mix (including Sargassum spp.), red algae mix and green algae mix. Quantification via the photo point method was used to estimate the surface wrack cover and depth in terms of classes (McKechnie & Fairweather, 00). Contrasting to McKechnie and Fairweather (00), who established cover (not depth) classes for their visual assessments, four class categories (depth and cover) were established for this study due to time constraints and feasibility. The classification was based on the amount of wrack present on the beach (Table. and Table.), in both north and south orientations. For each photo taken during each sampling occasion, and from the collection in Photomon, three assessors assigned a class for both depth and cover of wrack based on what was seen in the triangle (Fig. ). Assessors identified if wrack mounds were present or absent (Fig. ), assessed photos based on distribution and accumulation of wrack (in height) and assigned a class for cover and depth (Table & ). Table. Photo criteria for assessing depth of wrack (cm) based on photos (photo point method). Class Definition 0 No layer of wrack present Thin = <0cm Medium = 0-0cm High = 0-90cm Extreme = >90cm

5 Table. Photo criteria for assessing wrack cover (%) based on photos (photo point method). Class % Cover Definition 0 0 No layer of wrack present - Thin = large areas of bare sand, wrack present in small patches. 6-0 Medium = More than half the area (FOV) is bare sand, wrack present in medium patches. - 7 High = Less than half the area (FOV) is bare sand, wrack present in large patches. >7 Extreme = Little bare sand is evident, most wrack present in large mounds. Figure : Assessors assigned a class score for both wrack depth and coverage by considering wrack within the triangle indicated. Results: The average depth of wrack was low across all sites in August, with the greatest depth being.cm (Fig. a) at Kempton North. Average depths of wrack increased during September and December, with the largest averages occurring at Kempton North (. cm, Fig. b) and Separation Point South (.6 cm, Fig. c). Wrack cover across all sites in August 0 was highest at Southgates, with an average of 6.8% and.% cover north and south, respectively (Fig. a). The lowest average cover

6 during that time was recorded at Separation Point, where there was 0.% and 0.% cover going south and north. However, the average cover increased in September and December 0, with highest values at Southgates (86% South and.% North, Fig. b) and Separation Point (68% South and 7% North, Fig. c). The lowest average cover was recorded at Separation Point (7.% South and.9% North) during September, and at Drummonds during December 0 (8.8% South and % North). In August 0, the most abundant wrack category was brown algae mix, followed by seagrass mix, and the lowest was red algae (Fig. a). In September, brown algae mix was again the most dominant category, followed by seagrass mix, whereas in December 0, seagrass mix was the more dominant category followed by brown algae mix (Fig. b, c). Within these broad macrophyte groups, Amphibolis was the dominant seagrass and Sargassum spp. dominated brown algae (refer to Appendix ). Codium was also the most dominant genus of green algae (Appendix ). 6

7 Average wrack depth (cm) a) Average wrack depth (cm) b) Average wrack depth (cm) c) Sites (Photo points) Figure : Average depth of wrack (±SE) across sites during August (a), September (b) and December (c) 0. 7

8 Average wrack cover (%) a) Average wrack cover (%) b) Average wrack cover (%) c) Site (Photo point) Figure : Average percentage cover (%) (±SE) across sites in August (a), September (b) and December (c) 0. 8

9 Average biomass composison (%) a) Red algae mix Brown algae mix Green algae mix Seagrass mix Average biomass composison (%) b) Red algae mix Brown algae mix Green algae mix Seagrass mix Average biomass composison (%) c) Red algae mix Brown algae mix Green algae mix Seagrass mix Site (Photo point) Figure : Average biomass composition (%) (± SE) of red, brown and green algae and seagrass found across photo points during August (a), September (b) and December (c) 0. 9

10 Figures to 9 illustrate the photographs taken North and South of each photo point at each site in August, September and December 0, and the depth profiles of the wrack across the beach. Where wrack was present, the distribution of the wrack across the beaches was highly variable. The depth of wrack across the beaches in August was higher towards the foredunes, with wrack being the deepest between 0 and metres from the swash zone (Figs - 9). In comparison, the average depth of wrack across the beach profile in September was deepest closer to the swash zone (Figs 0- ). Beaches at Swan Street (August & September), Kempton (August & September) and Smugglers (December) sites had an even distribution of wrack across the beach profile, which was reflected in the photo triangle (Figs 7, 8,, & 8). In comparison, beaches at Southgates (August & September), Separation Point & South Separation Point (December), Kempton (December) and Drummonds rock wall (August & September) had more clustered wrack accumulations and thus skewed interpretations of wrack distribution via the photo triangle (Figs, 9, 0,,, 6 & 7). South Separation Point had greater wrack accumulation and distribution in comparison to Separation Point, with 98% average cover in a northerly direction and in between 0-0cm deep for both North and South directions (Fig. ). However, the depth and coverage class assigned does not reflect these data, due to the photo triangle not able to capture the accumulated wrack (clustered). Overall, the wrack seen in the photo triangle used to assess each photograph only reflected the distribution of wrack when there was relatively even spread of wrack across the beach profile. In addition, where wrack was present, the composition of wrack (e.g. seagrass, brown algae) was difficult to determine from the photos (Figs 0,, 6 & 7). This was the case when wrack was thinly distributed or large accumulations. 0

11 Figure : Photos in North (a) and South (b) directions (respectively) from photo point at Southgates beach in Geraldton during August 0, and the depth profiles of wrack across the beach in north (c) and south (d) direction. Figure 6: Photos in North (a) and South (b) directions (respectively) from photo point at Separation Point beach in Geraldton during August 0, and the depth profiles of wrack across the beach in north (c) and south (d) direction.

12 Figure 7: Photos in North (a) and South (b) directions (respectively) from photo point at Kempton beach in Geraldton during August 0, and the depth profiles of wrack across the beach in north (c) and south (d) direction. Figure 8: Photos in North (a) and South (b) directions (respectively) from photo point at Swan Street beach

13 in Geraldton during August 0, and the depth profiles of wrack across the beach in north (c) and south (d) direction. Figure 9: Photos in North (a) and South (b) directions (respectively) from photo point at Drummond s rock wall beach in Geraldton during August 0, and the depth profiles of wrack across the beach in north (c) and south (d) direction.

14 Figure 0: Photos in North (a) and South (b) directions (respectively) from photo point at Southgates beach in Geraldton during September 0, and the depth profiles of wrack across the beach in north (c) and south (d) direction.

15 Figure : Photos in North (a) and South (b) directions (respectively) from photo point at Separation Point beach in Geraldton during September 0, and the depth profiles of wrack across the beach in north (c) and south (d) direction. Figure : Photos in North (a) and South (b) directions (respectively) from photo point at Kempton beach in Geraldton during September 0, and the depth profiles of wrack across the beach in north (c) and south (d) direction.

16 Figure : Photos in North (a) and South (b) directions (respectively) from photo point at Swan Street beach in Geraldton during September 0, and the depth profiles of wrack across the beach in north (c) and south (d) direction. 6

17 Figure : Photos in North (a) and South (b) directions (respectively) from photo point at Drummond s rock wall beach in Geraldton during September 0, and the depth profiles of wrack across the beach in north (c) and south (d) direction 7

18 Figure : Photos in North (a) and South (b) directions (respectively) from photo point at Separation Point beach in Geraldton during December 0, and the depth profiles of wrack across the beach in north (c) and south (d) direction. 8

19 Figure 6: Photos in North (a) and South (b) directions (respectively) from photo point at South Separation Point beach in Geraldton during December 0, and the depth profiles of wrack across the beach in north (c) and south (d) direction. Figure 7: Photos in North (a) and South (b) directions (respectively) from photo point at Kempton beach in Geraldton during December 0, and the depth profiles of wrack across the beach in north (c) and south (d) direction 9

20 Figure 8: Photos in North (a) and South (b) directions (respectively) from photo point at Smugglers in Geraldton during December 0, and the depth profiles of wrack across the beach in north (c) and south (d) direction. 0

21 Figure 9: Photos in North (a) and South (b) directions (respectively) from photo point at Drummond s rock wall s in Geraldton during December 0, and the depth profiles of wrack across the beach in north (c) and south (d) direction. Relationships between the depth and cover classes assessors assigned, and the quantified wrack data (depth, percentage cover and total biomass) collected for each site over the three sampling occasions was constructed to determine the accuracy of the quantification via the photo point method. In regards to the depth classes assigned by each assessor for both the depth against depth data, the accuracy of the photo point method was low, as highlighted by the low R values (0. to 0., Fig. 0a). This reflects the high degree of variability in the wrack depth for each depth category for all three assessors, with examples of low categories assigned to deep wrack and vice versa. In terms of wrack cover, there was a stronger relationship between assigned cover categories and average cover, with R values from 0.7 to 0.8 (Fig. 0b). Similar to depth, there was a high degree of variability in the wrack cover for each assigned cover category. A separate evaluation was made demonstrating the variation between the assessors, however, with a larger independent dataset (Appendix. and.) than that illustrated in the Fig. 0. The plots indicated a difference in assessing the photos via the photo point method, particularly the depth categories for North Drummonds rock wall. Whilst North Drummonds rock wall coverage class and South Drummonds rock wall depth and coverage class had similar medians (depth and coverage class of ), the distributions of the plots from the medians demonstrated differing views in regards to categorisation of depth and coverage (Appendix. &.). There was also only a weak relationship between depth and cover classes with biomass determined from the survey (Fig. a,b). Based on the survey data collected on wrack depth and cover, the wrack volume was moderately (R = 0.) related to wrack biomass (Fig. ). There was a positive relationship between the two variables.

22 Figure 0: Scatterplot of the average wrack depth (a) and cover (b) versus the assigned depth and cover class for the three assessors at all sites and sampling times during 0. Regressions are shown for each assessor, with the R value.

23 Figure : Scatterplot of the average total biomass versus the assigned depth and cover class for the three assessors at all sites and sampling times during 0. Regressions are shown for each assessor, with the R value.

24 6000 Volume (m) of wrack material R² = Average total biomass (g/m) Figure : Scatterplot of the average total biomass versus the volume of wrack calculated from the depth and area or wrack at each site during 0. Regression line is shown with the R value. Discussion: The amount of wrack accumulating on the Geraldton beaches varied across sites and times during the study period. There were locations that consistently received large accumulations of wrack, for example Southgates beach and Kempton beach. There were also sites that received very minimal amounts of wrack, e.g. Separation Point and Drummonds rock wall. This differing input is primarily due to beach morphology and storm events (Duong & Fairweather 0; Porteus 0; Baring 0). There were no clear seasonal trends in wrack depth or cover, however, there was a greater accumulation in September and December months after two storm events in the mid- west region. The main aim of this study was to establish and validate a rapid visual assessment technique (adapted from Kirkman, 978; Mellors, 99; & McKechnie, 00) via photos from data collected during set sampling periods as well as from the Photomon program (Appendix ). The photo point method (Duong 008) aimed to provide an accurate, simple and rapid method for estimating the depth and cover of wrack on a range of sandy beaches in Geraldton. The photo point method showed limited capacity to be used to assess wrack

25 depth particularly, as there was a weak relationship between wrack depth and depth class. The assessment of wrack cover using the photo method is more promising, with a moderate relationship between average cover and cover class. This was partly related to high degree of variability in the depth and cover for each assigned depth and cover category fro each assessor and across assessors. This suggests that that the five levels for the depth and cover categories are insufficient to accurately assess wrack from the photos, and more levels need to be added. In addition, using the photo triangle to assess the wrack composition was difficult. Where wrack was present, it was either distributed sparsely or accumulated together, and was often distributed outside the triangle. The use of a more encompassing polygon to assess the wrack would help overcome this issue. The wrack survey showed that the composition of wrack mainly comprised seagrass or brown algae, similar to the Perth metro region (Crawley et al. 006, Ince et al. 007). In addition, the composition varied between sites and times. However, the photo method was unfeasible to distinguish the different forms of wrack, including seagrass and brown algae. If this is to be an objective of the photo monitoring program, closer and higher resolution photos of the wrack would be required. The photo point method was much faster (< % of the time required) than the transect method that was used to collect variables for depth, cover, and wrack biomass and composition. For each beach, the transect method took approximately hour for transects oriented perpendicular to the beach for North and South directions. The time taken varied, however, and depended on the amount and distribution (i.e. continuous vs. patchy) of the wrack deposits. Approximately - 0 minutes was also required for data entry and identification/processing of wrack material. Thus, the transect method required approximately hours per beach. In contrast, the photo point method required less than minutes per beach for both photo assessment and data entry. Thus, the rapidity of the photo point method has the ability to allow a greater number of sites or beaches to be sampled with little time and expense to the researcher, and can provide information that was previously difficult or unfeasible to obtain (Duong 008).

26 Recommendations and further studies As a quick and easy assessment of beach wrack, there are a few improvements that would make the photo point method a useful and valuable tool. We, therefore, make the following conclusions and recommendations.. McKechnie and Fairweather (00) scored photos into cover classes, but during this study the photo point method was used by only classing photos into classes, potentially affecting the accuracy of the photo point method. There were several photos that could have been put into another category, i.e. there were large differences between photos which were scored a class for depth and class for cover. To improve the accuracy of the photo point method, it will be more beneficial to use more class categories and very specific criteria for those classes.. The triangle assessment area and the type of camera used was not consistent/viable with wrack distributions seen, especially in regards to the photos assessed from the Photomon program. The use of a polygon that encompasses a greater area in the FOV of photo would overcome many of the issues related to the skewed distribution of wrack along the beach, and the inability of the triangle to capture the full distribution. In addition to wrack monitoring, NACC monitors beach erosion from the same point north and south of sites, however, based on the data presented here, this method does not seem suited for wrack monitoring (NACC 0a). A remedy for this in future would be to capture photographs halfway between the upper and lower drift lines of wrack deposition.. The inconsistency in terms of variation within the triangle assessment area and different fields of view (FoV) captured on different cameras made it difficult to identify if beach widths had varied/changed and if it was indeed the same photo point which was photographed previously (if sampling had occurred). Taking these issues into consideration, it made it challenging to assess the depth and coverage of wrack in the photos accurately. This could be improved by using a common and simple camera with a consistent FoV (i.e. smartphone/apple iphone camera) to take photos at the correct photo points, and continue using the guide photos established in the Photomon program, but adjust so guide photos capture between lower and upper zones of wrack deposition (NACC 0b). 6

27 . Wrack cover was assessed reasonably accurately from the photos (although see Pint for to improve this). However, depth and wrack composition was difficult to assess from the photos. Assessment of depth could be improved by adding a stake with a depth scale in the deepest section of wrack with the FOV. Wrack composition could be assessed by taking a series of higher resolution photos that cover a m area within the FOV. With a few improvements and specificity in regards to the criteria used, the photo point method, can be used to quickly and accurately estimate at least wrack cover on a range of sandy beaches, with the ability for a broader range of potential applications (Duong 008). The photo point technique requires little training or expertise, and can be carried out effectively by most people capable of using a camera. Scoring of photos is also relatively simple and can be done accurately with the assistance of reference material or a set of criteria. Photos also provide a permanent record of the beach (wrack cover as well as other characteristics) that can be used for further research (NACC 0a). Photo points have the potential to be used to inform managers of wrack cleaning and harvest activities, as well as assessing wrack stocks around the state, and possibly to identify unknown or unused resources. For example, Primary Industries and Resources South Australia (PIRSA) require that licence holders (to harvest wrack) provide data on wrack volume/cover before and after harvest (PRISA 00). Prior to establishing the photo point methods and adaptations since, there was no feasible way to do so. The photo point method could thus provide a useful tool for scientists, natural resource managers and community groups. References: Baring, R.J. (0). Faunal associations with drifting macrophytes and wrack accumulations in the nearshore of South Australian sandy beaches. Flinders University. Baring, R.J., Fairweather, P.G. & Lester, R.E. (0). Storm versus calm: Variation in fauna associated with drifting macrophytes in sandy beach surf zones. Journal of Experimental Marine Biology and Ecology, 6, Crawley, K.R. & Hyndes, G.A. (007). The role of different types of detached macrophytes in the food and habitat choice of a surf- zone inhabiting amphipod. Marine Biology,, -. Crawley, K.R., Hyndes, G.A., Vanderklift, M.A., Revill, A.T. & Nichols, P.D. (009). Allochthonous brown algae are the primary food source for consumers in a temperate, coastal environment. Marine Ecology Progress Series, 76, -. 7

28 Duong, H.L.S. & Fairweather, P.G. (0). Effects of sandy beach cusps on wrack accumulation, sediment characteristics and macrofaunal assemblages. Austral Ecology, 6, 7-7. Duong, S.H.L. (008). Investigating the ecological implications of wrack removal on South Australian sandy beaches. School of Biological Sciences, Faculty of Science and Engineering, Flinders University. Ince, R., Hyndes, G.A., Lavery, P.S. & Vanderklift, M.A. (007). Marine macrophytes directly enhance abundances of sandy beach fauna through provision of food and habitat. Estuarine, Coastal and Shelf Science, 7, Kirkman, H. (978). Decline of seagrass in northern areas of Moreton Bay, Queensland. Aquatic Botany,, Lenanton, R.C.J. & Caputi, N. (989). The roles of food supply and shelter in the relationship between fishes, in particular Cnidoglanis macrocephalus (Valenciennes), and detached macrophytes in the surf zone of sandy beaches. Journal of Experimental Marine Biology and Ecology, 8, McKechnie, J.M. & Fairweather, P.G. (00). Ecological implications for the management of wrack on South Australian sandy beaches: A report to the coast protection board. School of Biological Sciences, Flinders University. Mellbrand, K., Lavery, P.S., Hyndes, G.A. & Hambäck, P.A. (0). Linking land and sea: Different pathways for marine subsidies. Ecosystems,, 7-7. Mellors, J.E. (99). An evaluation of a rapid visual technique for estimating seagrass biomass. Aquatic Botany,, NACC (0a). Geraldton Beach Wrack Quantification Study. NACC (0b). Using Photomon for monitoring environmental change: User Manual Porteus, R. (0). Geraldton volunteer beach monitoring manual. PRISA (00). Draft management plan for harvesting beach- cast seagrass and marine algae, Primary Industries and Resources South Australia, Australia. South Australian Fisheries Management Series. Robertson, A.I. & Lenanton, R.C.J. (98). Fish community structure and food chain dynamics in the surf- zone of sandy beaches: The role of detached macrophyte detritus. Journal of Experimental Marine Biology and Ecology, 8,

29 Appendices: Appendix : Biomass composition (%) illustrating each Division found at each Photo point within each replicate, as well as individual Genera found. Site/Photo point (for Photomon) Replicate Seagrass mix Halophila Zosteratas matica Biomass Composition (%) Syringodium Amph Posidonia ibolis Green algae mix Codi um Caulerp a Brown algae mix Ecklonia Sargassu m Red algae mix Solanacea spp. (terrestrial plant) Aug- Southgates South Southgates North Separation Pt South Separation

30 Pt North Kempton South Kempton North Swan St South Swan St North

31 Sep- Drummond South Drummond North Southgates South Southgates North Separation Pt South

32 Separation Pt North Kempton South Kempton North Swan St South Swan St North

33 Dec- Drummond South Drummond North Separation Pt South Separation Pt North South SepoPt

34 South South SepoPt North Kempton South Kempton North Smugglers South

35 Smugglers North Drummond s South Drummond s North

36 Appendix : Figure.: Box plots showing the variation between assessors categorisation for depth and coverage at Drummonds rock wall North via the photo point method/criteria (Table. &., pp. - ). 6

37 Figure.: Illustrates the variation between assessors categorisation for depth and coverage at Drummonds rock wall South via the photo point method/criteria (Table. &., pp. - ). 7