AQUATIC CONSERVATION: MARINE AND FRESHWATER ECOSYSTEMS
Aquatic Conser6: Mar. Freshw. Ecosyst. 11: 123– 135 (2001) DOI: 10.1002/aqc.437
De7elopments in the application of photography to ecological monitoring, with reference to algal beds JEAN-PAUL A. DUCROTOYa,* and STEPHEN D. SIMPSONb a
The Uni6ersity of Hull, Centre for Coastal Studies, Scarborough, UK b Department of Biology, Uni6ersity of York, UK ABSTRACT
1. The potential for using photographic methods in ecological monitoring of intertidal rocky shores was investigated at two scales: the scale of a bay, and at sampling quadrat level. 2. The macroalgal beds at Selwicks Bay, Flamborough Head (north Humberside Coast, England) were used as a case study. 3. At each station on three 90 m transects, a photograph was taken of a 50 cm2 quadrat. These images were analysed using SigmaScan™ to measure the cover of algal species. These data were highly correlated with field data collected using a grid quadrat. 4. Ground techniques were developed for drawing a scaled overhead map of the bay. The potential for a quantitative survey of the extent of the algal beds using cliff top photographs was investigated. The photographs were merged, and rectified using Arc/Info™ (a Geographical Information System package) to produce scaled overhead images of the bay. 5. The two complementary methods developed are suitable for involving amateur naturalists into field-data collection. They were also designed to meet long-term statutory monitoring requirements. They are quick, so are well suited to intertidal areas where field sampling windows are limited. In long-term monitoring strategies, the use of photography produces interactive permanent records of the sample area for back reference. Reporting on the conservation status of sites of European interest could be greatly facilitated by such techniques. 6. There are obvious applications for overseas monitoring and base-line surveys, which demand large data sets to be collected in limited periods of time. Copyright © 2001 John Wiley & Sons, Ltd. KEY WORDS:
biological monitoring; classification; northeast England; photography; seaweeds
INTRODUCTION Following the 1992 Rio Earth Summit, the European Community passed the Habitats Directive (1992/EC192) (Bell, 1997) which places a requirement on member states to designate special areas of conservation (SACs). The establishment of the Natura 2000 network is an integrated approach to the designation of protected habitats to represent Europe’s environmental diversity, including SACs but also special protection areas (SPAs) designated under the Birds Directive. Once an area is assigned SAC status, the Habitats Directive (Article 17) requires that the member state government reports at regular year * Correspondence to: Dr Jean-Paul Ducrotoy, The University of Hull, Centre for Coastal Study, Filey Road, Scarborough, YO11 3AZ, UK. E-mail:
[email protected]
Copyright © 2001 John Wiley & Sons, Ltd.
Received 17 February 2000 Accepted 3 January 2001
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intervals on the conservation status of the habitats and of the species for which the site is designated (Ducrotoy, 1999). The information provided includes a broad scale assessment of the complete range of habitats and their associated communities and if they meet conservation objectives for the site. This endeavour demands that large geographical areas are surveyed at a broad scale in a short period of time, so methods for rapid sampling that produce sets of permanent baseline data are required. Permanent data sets are particularly important in marine ecology, a field where the criteria for the classification of habitats and areas of environmental importance are highly dynamic, both within and between conservation bodies (Sylvand and Ducrotoy, 1997). In the 1990s, in France and in the UK, classification systems have been proposed but with a different objective. The Zones Nationales d’Inte´reˆt Scientifique, Faunistique et Floristique (ZNISFF) have been developed in France (Dauvin et al., 1996) while, in the UK, the marine biotope classification was published by the Joint Nature Conservation Committee (JNCC) in the UK (Connor et al., 1997a,b). Those systems are presently considered as a potential basis to a Europe wide classification system to be put in palace by the European Union (EU) and the Oslo & Paris Commission (OSPAR) in the early 2000s. The application of such an international system should offer an opportunity for use in marine SACs, but it would then be necessary to further refine the classification to ensure it is accurate enough for monitoring changes on the long-term. Therefore, in addition to the for a baseline survey for each SAC, there is a need for repeated surveys giving an idea of potential changes in the biotopes coverage. However, environmental and conservation budgets are tight, both in the public and private sector, and the limitations on skilled time available are further accentuated in the coastal zone, where the tidal cycle imposes relatively short sampling windows. Similarly, where skilled biologists are travelling to less developed countries to assist in or lead expeditions, the need for fast, effective techniques in sampling is paramount. It was the aim of this investigation to devise, through the use of photography, biological field study techniques which both reduce the time spent in the field and provide methods easily employed by volunteer amateur naturalists. The use of replicable photographic methods that require only a working knowledge of a camera is ideal for utilizing voluntary and unskilled assistance in biological monitoring. The algal communities of Selwicks Bay (Flamborough Head, England) were chosen as a case study because they are of conservation importance, being, inter alia, a candidate SAC. Since Flamborough Head is such an important site, it might be expected that good baseline information exists on algal communities which are good indicators of changes in marine ecosystems. Indeed, depletion in fucoid cover was noted in the upper shore of Selwicks Bay by heritage coast staff as early as 1995, and they were interested in the development of a rapid monitoring method, which could be reapplied at regular time intervals. The observed algal retreat had been linked with the effects of human trampling (the bay is popular with tourists and school groups), but attempts as yet to produce quantifiable data had been unsuccessful. The aims of this study are to propose a method suitable for gathering baseline data, and a method for the long-term monitoring of intertidal algal communities, which could be of use locally, but which could also be used as a reference for studies in other coastal areas. Consequently, the current study had two main objectives. Firstly, it involved calibrating a computerized image interpretation technique against a ‘classical’ inventory, involving species identification in the field. Secondly, it required rectifying and interpreting vantage point photographs taken from the cliff top, in order to assess the extent of the algal beds at the scale of the bay. Preliminary work started at the selected site in 1995, and the two first years of experimentation helped to set up a coherent approach to the two levels of study presented in this article. Secondary objectives included an assessment of the methodology for identifying biotopes. This paper is also concerned with the development of an easy tool for assessing changes in the intertidal zone in preparation of a long-term monitoring plan to help discriminating between local disturbances, linked to tourists visits for instance, and climatic perturbations at the regional or even the global scale. The ultimate objective would be a contribution to the long-term monitoring of biotopes, as defined in the new European classification, which is being developed (Davies and Moss, 1999). Copyright © 2001 John Wiley & Sons, Ltd.
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This paper first gives details on the site and on the methodology selected after several years of trial, focusing on the main aspect of the work: the use of photography for mapping intertidal communities. Results are then given in terms of a comparison between the photographic method and a classical approach using quadrats. The discussion looks at any necessary further work needed to develop the application of photography to ecological intertidal monitoring.
MATERIALS AND METHODS Study site The algal beds at Selwicks Bay (54°09.9%N – 00°13.6%W), Flamborough Head on the north Humberside Coast, England (Figure 1(a)) were used as the case study for this investigation. Flamborough Head
Figure 1. Location of the studied area. (a) Location of Flamborough Head in England. (b) Map of Flamborough Head, north Humberside, showing Selwicks Bay. Copyright © 2001 John Wiley & Sons, Ltd.
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(Figure 1(b)) is highly regarded for its geology and biology, and is designated a site of special scientific interest (SSSI), SPA, sensitive marine area (SMA), and heritage coast status (George et al., 1988; Tittley, 1988; Wood, 1988; Bennett and Foster-Smith, 1998; Hiscock, 1998). In addition, Flamborough Head was selected by English Nature as one of Britain’s possible SACs, and is now a candidate site (cSAC) (Ducrotoy, 1999). Selwicks Bay is an exposed east-north-east facing bay, cut out from the tip of Flamborough Head. It consists of a wave-cut chalk platform, fringed by sand and gravel beds, and enclosed by steep chalk cliffs. The chalk platform is covered predominantly by a Fucus serratus Linnaeus macrocanopy which develops in the lower part of the shore; although a total of 58 algal species were found at Selwicks Bay, 111 have been recorded from around Flamborough Head as a whole (George et al., 1988). The biotope approach of the Marine Nature Conservation Review (MNCR) was adopted at Selwicks Bay, in order to direct the study towards the likely SAC monitoring strategy. The MNCR classification, used here, was developed as a contribution to BioMar, a project part-funded by the European Commission. It relies on the notion of biotope, which is defined as the habitat-the physical and chemical attributes of the site — together with its recurring associated community of species (Connor et al., 1997a). The biotopes were defined by JNCC as ‘Littoral rock with fucoids and barnacles’:
Bpat.Sem — Semibalanus balanoides and Patella spp. on exposed or moderately exposed eulittoral rock, FvesB — Fucus 6esiculosus and barnacle mosaic on moderately exposed mid eulittoral rock, and Ldig.Ldig — Laminaria digitata on exposed sublittoral fringe bedrock (Brazier et al., 1998).
Sampling methods Initial trials An attempt was made to use high and low altitude aerial images taken by the Ordnance Survey in September and October 1995 for mapping algal beds in Selwicks Bay. The exposures used in these images however prevented a clear distinction to be made between the sea and the exposed algal beds. This is why further initial studies, in 1996 and 1997, attempted to use cliff top photography and ground sampling methods to survey the southern part of the bay. The photographs were scanned, and analysed using a graphical image analyser (SigmaScan Pro™). The vantage point images were used to produce a sketch map of the bay showing algal coverage. The images lacked field calibration markers of known distances and were only roughly calibrated, so biotope areas generated were estimates. Moreover, there were difficulties in interpreting the ground proofing data which involved identifying and listing all species along selected transects. Because of the discrepancies in the methodology, it was not recognized as acceptable for monitoring purposes. An alternative ground sampling method to the exhaustive inventory used in preparation of the present study, in 1996 –1997, required a video camera to film along a random transect line. Still images, extracted any time a change was noticed, were assessed using six categories and an adapted Braun –Blanquet scale (Wratten and Fry, 1980; Williams, 1991). The definition obtained from video stills was found to be insufficient for the identification of individual species, although a general gradient of functional groups cover on the lower shore to bare rock on the upper shore was clearly observed. Thus, in the present study, it was decided to use still photographs, taken using an SLR camera to gain in definition, and scan them for computerized interpretation. Adopted sampling regime Learning lessons from the above experiences, a new strategy was set up and field studies were conducted in November and December 1998 that involved three steps: Copyright © 2001 John Wiley & Sons, Ltd.
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1. Mapping the bay To enable replicable monitoring of Selwicks Bay, a grid of nine balloons was laid at measured locations on the algal beds to provide visible non-permanent markers (Figure 2). To determine the co-ordinates of the balloons, it was necessary first to map the bay using compass bearings and ground measurements. A circumspective series of photographs was taken from the centre of the bay (station 5 on Transect 2 as shown on Figure 2). The photographs were scanned, and using a graphics processor (PaintShop Pro™), built up in layers and merged to produce a single 360° image of the site. The identifiable landmarks A to G and the old concrete steps (S) were labelled on the image. An overhead view sketch of the bay was drawn. The straight-line distances and compass bearings between points C, D, S and E were measured using a 30 m tape and an engineer’s compass and were marked on the sketch. The compass bearings to landmarks were measured from points D, S, E and F. The four points C, D, S and E were plotted on paper using a protractor and a pair of compasses at a scale of 10 m: 1 cm. The four sets of compass bearings were etched onto sheets of acetate and laid over their respective plots. The points at which the lines crossed were plotted as the other landmarks: A, B, F, G and H. Balloons 4, 5 and 6 were plotted on the map along the line of Transect 2, at 60° from the old steps (S), at 30m intervals. Transects 1 and 3 were plotted parallel to Transect 2 and at 30 m to either side. This grid of balloons defined the three transects, which were continued up to the cliffs, and provided visible markers in the cliff-top photographs. The map (Figure 2) was laid over a grid on a computer screen built on the derivation of a series of real world arbitrary co-ordinates. The co-ordinates were plotted in a graphics processor, and, using the panoramic image, the cliff boundary was drawn. The use of a global positioning system (GPS) allowed repositioning the balloons and transects day after day.
2. Transect photography Transect photography was used to attempt defining the main algal communities at the site. To develop replicable ground sampling techniques suitable for use in a long-term monitoring strategy of the algal beds, the three transects formed by the grid of balloons and pointing out to sea were sampled. The transects were chosen to include the sand and gravel beds, the bare wave-cut platform, the middle shore with patchy algal distribution, through to the dense fucoid algal beds of the lower shore. Each transect
Figure 2. Map of Selwicks Bay, showing points of reference (A – G and S), transects used (1 – 3), and balloon locations ( 1 – 9). Copyright © 2001 John Wiley & Sons, Ltd.
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was treated as a belt, using four 50 cm-side quadrats sampled every 5 m at 18 stations. The quadrat size was adapted from earlier studies on the Yorkshire coast (Tobin et al., 1998), chosen to give representative samples of the study area. Such sized quadrats allow substantial data sets to be built in a short time period, essential in a broad-scale survey of an intertidal area. At each station, the 50 cm-side quadrats were firstly ground-truthed using a 5 cm grid. There was no manipulation of the quadrats, it was an entirely two dimensional survey, so that the data were comparable to the data collected from photographs. Algal species present in the quadrats were identified using appropriate keys (Hiscock, 1979; Irvine, 1983; Hiscock, 1986; Maggs and Hommersand, 1993; Irvine and Chamberlain, 1994), and their percentage covers within each quadrat estimated. The number of Patella 6ulgata Linnaeus was counted and the number of Semibalanus balanoides Linnaeus was estimated in terms of coverage of the substrate. Where P. 6ulgata specimens occurred on the outside lines, they were included. The percentage of bare substrate was estimated; gravel was distinguished from bare rock by a length of 5 cm for the maximum diameter of the pebbles. Secondly, at each station a 50 cm-side open quadrat was placed with its centre on the 5m interval of the tape. Overhead photographs were taken. Images were scanned into PaintShop Pro™ and were calibrated and analysed using Jandel SigmaScan 2.0™. The percentage cover of algal species and bare substrate was measured, and the number of visible P. 6ulgata recorded. The paired data from the two methods were compared to investigate the precision of the data collected by ground photography, and its potential use in biological monitoring, complementarily to cliff-top photography. The calibration of images of the quadrats would be used to extrapolate to broad scale images for mapping, taken from the top of the cliff.
3. Cliff top photography Cliff top photography was tested for mapping communities as defined using the above method. Promontories a, b, c and d (Figure 2) were selected at similar height, near to the beach, for taking cliff top images from; this avoided any obscuring of the beach by the cliffs. Using a 50 mm lens, a correct and an over-exposed set of photographs was taken of the grid of balloons from each promontory; the colour in the over exposed images was found most suitable for working with graphic processors. Between four and six shots were needed for each set from each promontory to cover the whole grid. The time of day (in the afternoon) was chosen carefully so that shadows cast by the cliffs would not affect the images. The images from each promontory were layered and merged using a graphics processor to produce a set of mosaic view images. Using the geographic information system (GIS) computer package Arc/Info 7.2.1™ (by Environmental Systems Research Institute), the mosaic view images and the co-ordinate locations of the balloons were used to rectify the original images to produce overhead images of the bay.
RESULTS The list of algal species sampled through the use of the 50 cm2 quadrat is given in Table 1. The list is presented here for readers to evaluate the type of environment, which was dealt with in this study. Species richness increased with distances along the transect, and then stabilized at about 50 m. Two main communities were found: the upper shore and the lower shore with an intermediate mid shore assemblage in between. There were fewer species at upper shore stations and areas of bare rock were found. A sudden rise in species number took place when the transect crossed rock pools. Rectified overhead views of the bay, which best represented the bay, were those created from the photographs taken from the central promontories, b and c. This is because the angular distortion from promontories a and d was greater. Anyhow, because of the distortion, the images were rectified according to the derived locations of the balloons. Copyright © 2001 John Wiley & Sons, Ltd.
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Table 1. Ground sampling data of seaweeds collected at Flamborough Head
Species
Upper shore
Lower shore
Audouinella floridula Ceramium nodulosum Ceramium rubrum agg. Ceramium shuttleworthianum Chondrus crispus Cladophora laete6irens Cladophora rupestris Corallina officinalis Dumontia contorta Ectocarpus sp. Enteromorpha sp. Fucus serratus Fucus spiralis Fucus 6esiculosus Laurencia pinnatifida Mastocarpus stellatus Palmaria palmata Phyllophora crispa Polysiphonia sp. Ul6a sp.
ã
ã ã ã ã ã ã ã ã
ã ã ã ã ã ã ã ã ã
ã ã
ã ã ã ã ã ã ã
The images showed the extent of the algal beds on the wave-cut platform in a form that could be quantified. However, shadows cast across the bay by the cliffs and underexposed photographs caused problems in the colour analysis of the images, since the package could not differentiate between the rock pools, algae and the wave-cut platform. Learning from those mistakes, it was finally possible to measure the algal beds from the images using SigmaScan™ as presented here. Further work is proposed to use colour and intensity classification to automate this part of the analysis. Using the data produced from both the 50 cm-side grid quadrat and from the photographs analysed using SigmaScan™ of the 50 cm-side open quadrat, the gradients of proportional algal cover to bare substrate were plotted for each transect (Figure 3(a –f)). The data collected by both methods show similar trends, with the edge of the algal beds clearly defined in each transect. The bare substrate seen in the lower shore stations, particularly on Transect 1 (Figure 3(a –b)), was due to the presence of rock pools. Multivariate factor analysis techniques were applied to the entire data sets for each transect obtained by ground sampling and photographic analysis. This enabled the assemblages sampled to be analysed at a community level, considering the relative proportion of each recorded species. A plot of the regression factor scores from the two principle components for each of the data sets was made (Figure 4(a –f)). The data were labelled on each graph in blocks of six quadrats to differentiate between the lower and higher shores. The scores for the data collected by both methods on Transect 1 (Figure 4(a –b)) suggested distinct assemblages in the lower, middle and upper shore. The switch in the location of the lower and middle shore scores between the methods is thought to be due to the incorrect identification of F 6esiculosus Linnaeus in the SigmaScan™ image processing, mistaking it for F. serratus. In which case, the mid-shore transition and the lower shore would have been even more similar in the photo analysis. The plots for Transect 2 (Figure 4(c – d)) are visually comparable, and suggest the communities described by the two data sets are similar. The plots for Transect 3 (Figure 4(e –f)) are again similar, though the slight spread of scores for the upper shore in the SigmaScan™ data compared to the ground survey scores, which are overlaid, is due to the post hoc distinction of bare rock and gravel, after that transect had been ground surveyed. Copyright © 2001 John Wiley & Sons, Ltd.
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Figure 3. Proportion of algal cover (black) to bare substrate (grey) on the three selected transects (Stations 1 – 18: every 5 m). (a) Transect 1, ground sampling data, (b) Transect 1, photograph analysis data, (c) Transect 2, ground sampling data, (d) Transect 2, photograph analysis data, (e) Transect 3, ground sampling data, (f) Transect 3, photograph analysis data.
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Figure 4. Multivariate factor analysis regression scores for the two principle components (LS: lower shore, MS: mid-shore, HS: high shore). (a) Transect 1, ground sampling data, (b) Transect 1, photograph analysis data, (c) Transect 2, ground sampling data, (d) Transect 2, photograph analysis data, (e) Transect 3, ground sampling data, (f) Transect 3, photograph analysis data.
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A paired sample correlation test and a paired sample t-test (null hypothesis H0 = there is no significant difference between the data sets) were applied to the ground sampling data and the photographic data for each transect. At that time, the confusion about the two species of Fucus on the photographs had deliberately not been corrected. Although the data were in percentages, they were continuous, and only had natural limits (0 and 100%), so parametric tests were used. The paired sample correlation tests found high correlations between the data sets collected by each method at each transect, and found no significant differences (p B0.01). The paired sample t-tests applied to the data sets found no significant differences (p \ 0.244, p \ 0.668, p \ 0.753) between the data sets from each method.
DISCUSSION This investigation was set out to develop biological monitoring methods that could overcome certain common sampling constraints, particularly time and availability of skilled manpower. For this, the use of photography was assessed on two complementary scales: cliff top images and ground sampling. The collection of photographic data in the field in turn required the development of techniques for their interpretation. The use of two powerful computer packages was found to enable this interpretation to be relatively fast and easy. The methods devised for making and relocating the grid of balloons using compass bearings and measurements were suitably accurate, and it was possible to lay the same grid down on several sampling visits, as confirmed through the use of a high resolution GPS equipment. Where the use of permanent markers such as metal pegs is forbidden, this balloon method is inexpensive, and highly suitable in a long-term monitoring strategy. The balloon locations give static points of reference that the algal beds may move relative to, and so enable quantitative assessments on the dynamics of the algal beds to be made. The plots of the gradients of proportional algal cover to bare substrate were similar for both the ground truthing and the photographic methods, and clearly define the edge of the algal beds. Since the transects were positioned according to the fixed grid of balloons, in a long-term monitoring strategy the stations would be static, so any movement in the edge of the algal beds (due to human trampling, for instance) would be detected. Nevertheless, algal bed extent can also change due to natural forces such as storms or the proliferation of grazers. Further work is needed to differentiate between direct anthropogenic interference and oceanic factors. Some photographic data were missing from some transect stations due to the photographs not being taken properly. This is clearly a limitation of the methods, since before the photographs have been developed, it is not known whether the data are complete. This limitation would be avoided by using a digital camera which allows each image to be checked when it is taken before it is stored. Multivariate factor techniques were applied to allow each transect to be analysed at a community level. By plotting the regression factor scores from the two principle components extracted from the analysis, distinct lower and upper shore zones were found, together with a mid shore transition. In the present work, rock pools were included, but it can be questioned whether rock pools should be ignored as unrepresentative anomalies of the surrounding area, or included to demonstrate the heterogeneity of the habitat as chosen here. The very lower part of the shore was not sampled and the sublittoral fringe, exposed at spring tides, does not appear in our results. Anyhow, the transect photographs proved effective in defining main algal communities on the part of the shore mostly used by tourists. The method is clearly usable for identifying biotopes as in the MNCR classification. The upper exposed part of the shore with very little algal coverage but with barnacles and grazers such as P. 6ulgata was easily recognised on the rectified overhead views of the bay. The images produced overhead views of the bay, which were suitable for quantitative analyses of the extent of the algal beds, in terms of comparing the fucoid cover extent to Copyright © 2001 John Wiley & Sons, Ltd.
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the proportion of bare substrate. The F. 6esiculosus and barnacle mosaic was therefore clearly delimited. Moreover, the method could differentiate between assemblages, which could be considered as possible ‘sub’-biotopes of the biotope FvesB – F. 6esiculosus and barnacle mosaic on moderately exposed mid eulittoral rock. It would be easy to quantify any changes in the proportion of the various assemblages described here on the long-term in comparing similar images taken at regular interval over a period of time. This technique provided an extremely powerful tool for quantifiable mapping of intertidal areas where the use of aerial photography is not possible (e.g. limited budget, remote tropical studies). Nevertheless, the use of vantage point photography is restricted to beaches overlooked by high cliffs, with a rather level top. Rectification of images could not be accurately applied to pictures taken from a few metres above the ground. The application of remote control model aircraft to the production of aerial images (Green and Morton, 1994) is currently under investigation for small-scale environmental projects, and the York Archaeological Trust have now been contacted as they have in the past used helium balloons for aerial photography. The limitation of low-resolution scanned images, which have large pixels, prevented zooming in for accurate species identification. If high-resolution images, with much smaller pixels, had been used with SigmaScan Pro™, it would have been possible to zoom in further on the images for more accurate species identification. The comparisons made between the data collected by each method suggest that photography combined with graphical image analysis can be useful for extrapolating quadrat information to the wider shore. The strength of the combined methods presented here resides in the potential for long-term monitoring where shifts in communities might be expected. This would be extremely powerful, as it could allow repeated surveys and cater for seasonal changes or even allow an assessment of changes after a storm or after some drastic change in the environmental conditions. As seen earlier, in a long-term monitoring strategy, the use of photography would be ideal in building a permanent data set. It was possible to store all the images used in this investigation on one single compact disc. This suggests an efficient means of building interactive data banks in surveys and monitoring strategies in the future, including the use of the World Wide Web. As a tool for sampling in studies with short field-study windows, such as intertidal work or overseas expeditions with limited time abroad, the photographic methodology allows large sets of raw data to be collected efficiently over short periods. It enables volunteers to be used to complete the fieldwork using photography, then limiting the use of experts in the data processing. The application of SigmaScan™ allowed each quadrat image to be processed very quickly (about 2 min). With a protocol, quadrat analysis using a computer was soon mastered. However, there are some limitations to the analysis of images using SigmaScan™. Firstly, the analysis is only two-dimensional. Without manipulation of the quadrat, this prevents study of the underflora, which on the lower shore at Selwicks Bay is significant. This introduces an obvious bias to the large branching algae, although in this study, it was predominantly the extent of the algal beds that was under investigation. Secondly, there is a bias to conspicuous species, picked up easily in SigmaScan™. This effectively excludes encrusting algae. Small animals are also excluded. For example, S. balanoides could not be counted precisely; only the percentage coverage was assessed and the numbers inferred. It was not even possible to distinguish between live and dead animals. The numbers of P. 6ulgata counted were consistently low and very likely underestimated. If grazing were an issue in a study, this could be overcome by making a count of P. 6ulgata when the photograph is taken. Despite its advantages, the proposed photographic methodology could not completely replace detailed ecological studies such as initial full scale surveys providing real data which will always been needed. Undeniably, distinguishing between biotopes using the MNCR classification does require a level of survey involving an accurate identification of assemblages with long lists of species being collected, at least at the initial stage. However, in some other types of ecological surveys, there is now a move away from species Copyright © 2001 John Wiley & Sons, Ltd.
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level surveys towards more broad-based classification (Davies and Foster-Smith, 1995). The use of photography would be ideal for this second type of survey of the intertidal zone, and for routine monitoring of changes in the distribution of identified MNCR biotopes. Nevertheless, the MNCR biotope classification was never devised as a monitoring tool per se and alternative and/or complementary methodologies will need to be introduced if certain designated sites need to be surveyed. The classification of algae into functional groups (Littler and Arnold, 1982) could be part of such an approach. When establishing and recognizing functional groups, relatively few species attributes are of importance in determining the structure of algal communities. Nevertheless, the categorization of algal species simply by body plan can give substantial insight into the community structure (Tobin et al., 1998). Attributes used to identify the groups are often shared between taxonomically distant species (Steneck and Dethier, 1994). This eliminates the noise at species level to give a more continuous description. Confirming unpublished work by the authors, a ground sampling method found an even distribution of functional groups (Littler and Arnold, 1982) on the lower shore at Selwicks Bay, dominated by algae with thick blades and branches (e.g. fucoids). A diverse underflora was found when the macroalgae was removed, dominated by delicately branching algae. The upper shore had a patchy distribution of functional groups with no dominant type. It remains to conciliate the photographic methodology with the conceptual framework of the functional groups. It is suggested here that the use of digital photographs and SigmaScan™ analysis might be ideal for community analysis at a functional group level. ACKNOWLEDGEMENTS The authors wish to thank Ed Rowe and Mary Barry for their efficient technical assistance. They express their gratitude to Dr. Kimo Evans for providing enlightening advice and useful practical information. REFERENCES Bell S. 1997. En6ironmental Law. Ashford Colour Press: Gosport. Bennett TL, Foster-Smith JL. 1998. South-east Scotland and north-east England (Dunbar to Bridlington) (MNCR Sector 5). In Marine Nature Conser6ation Re6iew. Benthic Marine Ecosystems of Great Britain and the north-east Atlantic, Hiscock K (ed.). Peterborough, Joint Nature Conservation Committee (Coasts and seas of the United Kingdom. MNCR series); 155–177. Brazier DP, Davies J, Holt RHF, Murray E. 1998. Marine Nature Conser6ation Re6iew Sector 5. South-east Scotland and north-east England: area summaries. Peterborough, Joint Nature Conservation Committee (Coasts and seas of the United Kingdom. MNCR series). 235 pp. Connor DW, Brazier DP, Hill TO, Northen KO. 1997a. Marine Nature Conservation Review: marine biotope classification for Britain and Ireland. Volume 1. Littoral biotopes. Version 97.06. JNCC Report 229. Connor DW, Dalkin MJ, Hill TO, Holt RHF, Sanderson WG. 1997b. Marine Nature Conservation Review: marine biotope classification for Britain and Ireland. Volume 2. Sublittoral biotopes. Version 97.06. JNCC Report 230. Dauvin J-C, Noe¨l P, Richard D, Maurin H. 1996. Inventaire des ZNIEFF — Mer et des espe`ces marines: e´le´ments indispensables a` la connaissance et a` l’ame´nagement des zones coˆtie`res. Journal de Recherche Oce´anographique 21: 16–20. Davies J, Foster-Smith B. 1995. A strategy for sub-tidal resource mapping and its usefulness in environmental decision making. In Directions in European Coastal Management, Healy H, Doody P (eds). Samsara Publishing: Timbuktu; 223–234. Davies CE, Moss D. 1999. EUNIS habitat classification. (Contractor: European Environment Agency, Copenhagen and European Topic Centre on Nature Conservation, Paris), Monks Wood, Institute of Terrestrial Ecology. Ducrotoy J-P. 1999. Protection, conservation and biological diversity in the North-East Atlantic. Aquatic Conser6ation: Marine and Freshwater Ecosystems 9: 313– 325. George JD, Tittley I, Price JH, Fincham AA. 1988. The macrobenthos of chalk shores in north Norfolk and around Flamborough Headland (North Humberside). Nature Conservancy Council, CSD Report, No. 833. Green DR, Morton DC. 1994. Acquiring environmental remotely sensed data from model aircraft for input to geographic information systems. Association for Geographic Information (conference proceedings), Hobbs, Southampton, 15.3.1–15.3.27. Copyright © 2001 John Wiley & Sons, Ltd.
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