© 2005 International Council for the Exploration of the Sea
The remarkable population size of the endangered clam Tridacna maxima assessed in Fangatau Atoll (Eastern Tuamotu, French Polynesia) using in situ and remote sensing data
a University of South Florida – College of Marine Science, Institute for Marine Remote Sensing 140, 7th Avenue South, St Petersburg, FL 33701, USA
b BP 140 094 Arue, Tahiti, French Polynesia
c BP 1658 Papeete, Tahiti, French Polynesia
d Service de la Pêche BP 20 Papeete, Tahiti 98713, French Polynesia
e Laboratoire Terre-Océan Université de la Polynésie Française BP 6570 Faaa-Aéroport, Tahiti, French Polynesia
f Centre de Recherches Insulaires et Observatoire de l'Environnement BP 1013, 98729, Papetoai, Moorea, French Polynesia
*Correspondence to S. Andréfouët: tel: +1 687 26 08 00; fax: +1 687 26 43 26. e-mail: andrefou{at}noumea.ird.nc.
Several lagoons of the Eastern Tuamotu Atolls (French Polynesia) are characterized by enormous populations of the clam Tridacna maxima, a species considered as endangered in many locations worldwide. This unique resource is virtually intact, until recently being impacted only by local consumption. Increasing exports to Tahiti's market (up to 50 tonnes of wet matter y–1), combined with the relatively small size of these lagoons (<50 km2), have raised significant concerns for agencies charged with management of lagoonal resources. In order to evaluate whether the current harvesting pressure threatens long-term sustainability of this resource, it is necessary to estimate the total number of individual clams present and also the fraction of that stock that is currently targeted by fishers, who generally collect clams in very shallow waters (<1 m), walking on the reef edges. Here, we present results for a pilot study evaluating this resource at Fangatau Atoll. Using a combination of data collected in situ and three remotely sensed images with different spatial resolution (1.5, 5.6, and 30 m), we estimate that the shallowest lagoonal areas (4.05 km2 at depth <6 m) harbour five classes of benthic habitat with significantly different clam areal covers and densities. Considering the cover/density values for each habitat class, 23.65 ± 5.33 million clams (mean ± 95% confidence interval) inhabit these 4.05 km2. Assuming that current harvesting techniques will be maintained in the future, the commercially available stock represents 44% of the population located on 1.18 km2 of the shallow lagoon. A comparison of results from the three remote sensing platforms indicates that high resolution, broadband multispectral sensors (e.g. IKONOS, Quickbird) should provide the best existing platforms to conduct similar assessments elsewhere.
Keywords: aerial photographs, astronaut photographs, coral reef, fishery, French Polynesia, giant clam, Landsat, marine resource management, remote sensing
Received 22 June 2004; accepted 19 April 2005.
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Introduction |
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 Top Introduction Material and methodsResultsDiscussionConclusionReferences |
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Several reports have highlighted the remarkable abundance and dominance of the tridacnid clam Tridacna maxima (Röding, 1798) in Eastern Tuamotu Atoll lagoons, in French Polynesia (Figure 1). For instance, Salvat (1967, 1971, 1972) estimated that 11 million individuals were present in Reao Atoll lagoon (43 km2), representing an average of
40 000 individuals ha–1 with densities as high as 224 individuals m–2 on the upper inner slope of the lagoon. In contrast, many locations worldwide, including lagoons of high islands of French Polynesia or Western Tuamotu Atolls, have much lower densities (Copland and Lucas, 1988; Lucas, 1994). For instance, Palmerston Atoll (Cook Islands) has 2900 individuals ha–1 along its 1380-ha outer reef flat (Preston et al., 1995). Rose Atoll in Samoa harbours an average of 5000 individuals ha–1, but with variations depending on habitat location (up to 8870 individuals ha–1 at the bases of pinnacles, (Green and Craig, 1999). High volcanic islands of Samoa are depleted of any T. maxima (Green and Craig, 1999). A maximum of 4.6 individuals m–2 is reported for the barrier reef of Moorea Island, but the average is almost nil when considering the entire reef (Richard, 1982). Kinch (2002) reports a density of 17.9 individuals ha–1 for Milne Bay in Papua New Guinea. Other past estimates for sites worldwide are available in Copland and Lucas (1988) and Lucas (1994).
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Such typically low densities are natural (Rosewater, 1965), but increasing fishing pressure also contributes to the decline of this delicacy which is harvested both for local consumption and for export (Green and Craig, 1999; Kinch, 2002). The consumption of T. maxima is actually so high on a global basis that it has been included in Appendix 2 of the Convention on the International Trade of Endangered Species (CITES). This means that T. maxima is not currently threatened with extinction, but that risks are real unless trade is regulated. Conservation actions include establishment of no-take areas, clam aquaculture development and, as in French Polynesia, a minimum shell length (12 cm) before harvest.
Thus far in the Tuamotu Atolls, only natural events have caused major mortalities in the T. maxima population. Such events include poor renewal rate of lagoon waters during abnormally low swell and wind conditions (Adjeroud et al., 2001; Andréfouët et al., 2001) and heat stress resulting in clam mantle bleaching (Addessi, 2001). In Eastern Tuamotu Atoll lagoons, T. maxima populations are currently not at critical levels. However, the situation may rapidly change in several key atolls where exports have increased following demand from the Tahiti Island market, the largest in French Polynesia. In 2002, sales of giant clams in the Tahiti market are estimated to be about 50 tonnes of wet matter per year by the French Polynesia Fisheries agency. Because of increasing demand, and because harvesting clams is less demanding and more lucrative than other traditional atoll activities, exploitation of this resource attracts many atoll villagers. With more villagers focused on clam harvesting, pressure on T. maxima populations is increasing.
It is unclear whether the high population densities of clams accumulated in limited shallow lagoonal areas of these atolls can support increased fishery activities. As a result, the Service de la Pêche de Polynésie Française, launched in 2002 a multi-disciplinary programme to assess the population size and structure, growth rates, genetics, and aquaculture potential of the population of T. maxima for a variety of atolls, starting with Fangatau Atoll. We present here the results on T. maxima population size for this pilot atoll. A companion paper currently under preparation will present the population structure for the same atoll, and subsequent papers will discuss and compare other atolls.
We also emphasize here the use of remote sensing data in order to better constrain the stock estimates. Remote sensing is increasingly considered a useful tool for resource assessment in tropical lagoons and coral reefs. It has been used for estimating Trochus niloticus stocks in New Caledonia and the Torres Strait (Bour et al., 1986; Long et al., 1993), seagrass standing crop in the Bahamas (Mumby et al., 1997), and the estimation of harvestable algal (Sargassum mangarevense and Turbinaria ornata) biomass in Tahiti (Andréfouët et al., 2004). Regarding T. maxima, Green and Craig (1999) used aerial photographs to digitize habitat zones and stratify data collection in Rose Atoll (Samoa), which provided a more realistic assessment than the initial study by Radtke (1985) (27 800 vs. 1 340 000 clams in Rose lagoon). In this study, we compared the usefulness of three different remote sensing systems (aerial photographs, high-resolution digital astronaut photographs, and Landsat 7 images) for estimating clam populations. Comparison of results will be useful in identifying the best remote sensing platform for T. maxima assessment at other atolls.
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Material and methods |
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Study site
Fangatau Atoll (Figure 1) is located at 15°50'S 140°22'W, at the far northeast of the Tuamotu Archipelago, which comprises 77 atolls. The atoll's size is 22.2 km2, including a 9.9-km2 lagoon. Fangatau is a semi-closed atoll, with several functional spillways. However, renewal rate is poor most of the time. The lagoon is shallow (maximum depth
20 m), dotted by numerous intertidal or subtidal carbonate structures locally called "mapiko," which are actually made of an accumulation of cemented or loose T. maxima shells. Corals are known to be builders of their own habitats in coral reefs. In Fangatau, T. maxima is so abundant that it is the primary builder of lagoonal structures, constructing remarkable mounds and ridges of hard substratum. The eastern part of the lagoon has a small enclosed lagoon separated from the main lagoon by a large mapiko. Another large mapiko surrounds most of the main lagoon, isolating on the shore side a narrow terrace where microbial mats are developing in the relatively calm environment. The village on the western side of the atoll harbours nearly 150 inhabitants. The atoll has virtually no tourism activities, and locals now divide their commercial between fishing, coconut grove maintenance for copra exportation, and T. maxima harvesting. It is estimated that nearly 4 tonnes of clam meat (muscle, mantle, and gonads) are shipped to Tahiti every year by the villagers, representing approximately 50 000 individuals harvested each year.
Image data sets and pre-processing
Three remote sensing images were utilized in this study.
- A digital mosaic of three aerial photographs acquired in November 1998, and georeferenced by the French Polynesia survey service (Service de l'Urbanisme). The image comprised three colour bands in the blue, green, and red regions of the spectrum without further details on the spectral characteristics of the emulsion. Image quality is variable depending on which of the three mosaic sections is considered, with the western section, near the village, most negatively affected by sun glint off the sea surface. Unfortunately, these effects cannot be easily corrected without a near infra red (NIR) spectral band (Hochberg et al., 2003). The scan provided a RGB image at 1.5-m resolution.
- A RGB digital photograph acquired on 21 May 2001 by astronauts on board the International Space Station (ISS) using a 400-mm lens and a 2x-extender mounted on a Kodak DCS460D camera set at maximum aperture (F5.6) and 1/500 shutter speed. The Fangatau image (reference ISS002-ESC-6362) was estimated to have 5.6-m spatial resolution after georectification (Andréfouët et al., 2003a).
- A 30-m spatial resolution Landsat 7 Enhanced Thematic Mapper Plus (ETM+) image acquired on 3 July 1999. The image was delivered directly resampled and georeferenced. The useful part of the Landsat data set comprised the first four bands (blue, green, red, and NIR).
- A RGB digital photograph acquired on 21 May 2001 by astronauts on board the International Space Station (ISS) using a 400-mm lens and a 2x-extender mounted on a Kodak DCS460D camera set at maximum aperture (F5.6) and 1/500 shutter speed. The Fangatau image (reference ISS002-ESC-6362) was estimated to have 5.6-m spatial resolution after georectification (Andréfouët et al., 2003a).
Figure 2 highlights the impact of different spatial resolutions on the perception of the lagoonal structures and mapikos. No atmospheric correction was necessary since each image was processed using relative radiometric statistics obtained from the images themselves.
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Stock assessment strategy through remotely sensed habitat maps
We utilized a method for stock assessment which is similar to that proposed by Green and Craig (1999). Aerial photographs (AP) were used to define locations of geomorphological zones where potentially different habitats with different clam densities could occur. Examination of the mosaic provided 23 different zones, capturing different image quality conditions, different depth zones along the inner reef flat (crests and flats), inner slope, mapiko (bases and tops), main deep lagoon, eastern enclosed lagoon, different exposure to wind and to oceanic waters input (spillway mouth), different distance of the village, and finally differences in hard and soft substrata (Figure 3).
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Ideally, these 23 zones should provide the basis for stratified field sampling. Due to logistical difficulties, only one week of fieldwork for five investigators could be dedicated in 2003 May. It was therefore impossible to conduct a thorough sampling effort in each of 23 zones. We adopted a procedure to ensure that data collection covered most of the lagoon without bias, visiting at least two random sites per zone. In all, 59 sites were surveyed. We assumed that if any unique zone was present in the lagoon, it should be captured by our stratification. Conversely, if no specificities were found a posteriori, then pooling the data could reduce the number of strata and increase the number of sites per zone.
Data collection included two types of surveys. First, for each site, two 20-m long transects provided benthic cover data. Cover of live clams, dead clams, rubble, live coral (genera level), dead corals, sponges, macroalgae, and encrusting coralline algae (species level) were noted using the line intersect transect method (English et al., 1997). Transect directions were random, within the sampled zone. Second, three 0.25-m2 quadrats were surveyed to assess the density of clams in areas of high clam occurrence. Quadrats were randomly placed within the zone and depth range represented by the transects. Quadrat data served both the population size assessment and also the population structure description, since the size of each clam present in each quadrat was measured (AG, ms in preparation). Quadrat area was limited to 0.25 m2 because of the impressive clam density (up to 500 individuals m–2, all sizes included). A team of scuba-divers collected data for sites between 2 and 10 m deep, while a snorkeling team collected data in the shallows along reef crests and mapiko edges. Note that most clam assessments will not be able to use cover estimates because other places likely don't have such high densities, so the quadrats work is of importance for cross comparison with most other work.
Based on transect data, field sites were clustered into different benthic habitats by principal component analysis (PCA) and subsequent hierarchical clustering performed on the PCA scores (Ward method). Both the AP and the ISS images were classified to obtain habitat maps using a supervised classification procedure (maximum likelihood algorithm). Training was based on the surveyed sites, complemented with sites added by photo-interpretation. The survey highlighted that most clams occurred above the 5-m isobath (Table 1). Importantly, different habitats were clearly discriminated by their spatial organization and occurred at different depth ranges, so no depth-correction technique was applied. Deep areas (>6 m) were masked out, so that only 4.05 km2 of lagoon was processed for both AP and ISS data. The Landsat ETM+ image was segmented to obtain a geomorphological map of the atoll in five classes defined a priori (enclosed lagoon, inner slope, mapiko, inner reef flat, deep lagoon). The 30-m spatial resolution did not allow habitat mapping based on benthic percentage cover, because of the patchy nature of the lagoon, with patch size less than the pixel resolution (Figure 2).
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Accuracy assessment of habitat maps was performed a posteriori. A survey by one of us (LY) in January 2004 focused on areas of higher ambiguities, around the 4–5-m isobaths, where the transition between algal-dominated and clam habitats occurs. In all, 31 sites were surveyed.
As in Green and Craig (1999), T. maxima population size on Fangatau Atoll was estimated by compiling the mean clam density in each habitat (in situ data), measuring the total area of each habitat (from the AP and ISS remote sensing maps), multiplying each area by the mean density for that habitat, and summing these totals for an overall population estimate. For Landsat, we used the same procedure, using mean clam density for each of the five geomorphological classes.
To estimate the stock that is available to current simple harvesting techniques (reef walkers gathering clams with their hands), we applied a mask along the approximate 1-m isobath following the edges of the mapiko and inner reef crests. The 1-m isobath was defined by thresholding the red band of the AP (one threshold for each individual image making the mosaic) in order to capture all the field sites that were above 1-m depth. Glinted areas, where thresholding was unreliable, were manually digitized. Deeper water clams were considered as an unutilized part of the total stock.
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Results |
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TopIntroductionMaterial and methodsResultsDiscussionConclusionReferences |
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The stratified survey revealed consistent patterns in types of benthic cover with few variations throughout the lagoon. Sites deeper than 5–6 m did not show any substantial clam cover and density. Therefore, the sites of the 23 zones were pooled for further analysis and to categorize the relevant habitats, except for the deep lagoon zones.
Five habitats were defined by hierarchical clustering, using 126 transects. Characteristics of these classes (generically named "Sand", "Algae", "Rubble", "Coral", and "Clams" based on their discriminant variables) are provided in Table 1. By pooling transect and quadrat data for each of these classes, we obtained statistics for clam cover and density for each class (Figure 4). We note that the "Coral" class was discriminated by it having the highest mean coral cover (mostly Acropora spp. and a few Porites spp.), but it is also the class with the highest clam cover and density (Figure 4). The class "Clams" was made of dense aggregates of both live and dead clams. The class "Algae" was characterized by high cover (mean ± s.d. = 31.6 ± 9.4%) of the green algae Caulerpa bikinensis, dominant below the 4–5-m isobath.
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Differences in clam cover and densities were tested by running an analysis of variance (ANOVA) and an a posteriori least square difference (LSD) test. ANOVA results were significant for density (ANOVA: F = 17.56, d.f. = 53, and p = 3x10–9) and cover (ANOVA: F = 14.52, d.f. = 54, and p = 3x10–8). LSD tests are presented in Table 2. In many instances, both cover and density are significantly different between groups (p < 0.05).
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The clam cover/density characteristics for each of the geomorphological classes mapped with Landsat imagery are presented in Figure 5. In contrast to habitat classes, geomorphological classes are ranked in different orders for cover and density of clams (Figure 5).
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The a posteriori control of map accuracy and spatial patterns of benthic classes showed that the map derived from aerial photographs is accurate. Indeed, the shift from clam-dominated towards algae-dominated bottom is evidenced by the patterns of the patches (from isolated patches for clams towards connected networks for algae), and the image classification captured these patterns well (Figure 6). Located in the area in which we believed the highest misclassification rates lay (Figure 6), the 31 control points provide an overall accuracy of 74.7% (Table 3). This verification, and most importantly the clear spatial patterns, allows us to be confident of the accuracy of the AP-derived habitat map, but we acknowledge that we lack a full formal accuracy assessment stage. In theory, a minimum of 50 control sites is required for each class to obtain a statistically valid protocol (thus, 250 sites for Fangatau, considering five habitats) (Congalton and Green, 1999). We simply lacked time to obtain this ideal in situ data set, which is actually a relatively common failure in the expeditionary surveys typical of remote coral reef environments (Andréfouët et al., 2003b). For instance, Green and Craig (1999) do not discuss the accuracy of their habitat segmentation. Here, 74.7% accuracy for the most confounding zone is a good result, well in the range of other high-resolution habitat mapping results that have been compiled elsewhere (Andréfouët et al., 2003b).
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Other misclassifications were noted between "Rubble" and "Clams" zones on the upper slopes of the mapiko, with rubble margins being overestimated. Since both clam cover and density in the "Rubble" class are lower than that in "Clams" (Figure 4), the error leads to a conservative bias, and thus a possible underestimation of the stock.
The surface areas of each class differ in the AP and ISS derived maps (Figure 7). We have assumed that the highest resolution product provided the best accuracy and that discrepancies between products were errors due to estimates with reduced spatial resolution. This is a common trend in benthic habitat mapping: the higher the spatial resolution, the more accurate the products (Andréfouët et al., 2002, 2003a, b; Mumby and Edwards, 2002; Capolsini et al., 2003). This assumption allows for estimation of the degradation in stock estimates when changing spatial resolutions.
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The final estimated stocks are reported in Figure 8 for the three different sensors. Because of the different resolutions, the lagoon area of interest was 4.05 and 6.4 km2 for AP/ISS and Landsat, respectively. The reference value (AP, mean estimate ± 95% confidence interval) was 23.65 ± 5.33 million clams. ISS provided a slightly lower stock estimate (21.05 ± 4.59 million clams). Finally, Landsat provided an overestimate at 39.98 ± 8.45 million clams. The commercial stock, also reported in Figure 8, is estimated at 10.39 ± 2.72 million clams in an area covering 1.18 km2 of mapiko and reef flat edges.
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Discussion |
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TopIntroductionMaterial and methodsResultsDiscussionConclusionReferences |
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Population size assessment and comparisons with other Tuamotu Atolls
The method that we apply here does not generalize areas of high clam densities to depleted regions, since each habitat has its own weight, and these weights are quite different (Figure 4). Green and Craig (1999) made the same observation when discussing their own results vs. those of Radtke's (1985). For instance, the class "Sand", which covers 40% of the 4.05 km2 studied here (Figure 7), has a low mean clam density (1.6 individuals m–2). Thus, overestimation as a result of poor extrapolation does not introduce a bias explaining the extraordinarily high values reported here.
The total stock is divided mainly between the Clam and Coral classes in equal proportion (40% each). However, the most important class in terms of commercial stocks is the Coral class. This class harbours 75% of the commercial stock (7.79 million clams) while covering only 20% of the area commercially exploitable (Figure 9), the rest being mostly carbonate sediments on top of large mapikos.
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Table 4 reviews the previously estimated population sizes for various Tuamotu Atolls. Keeping in mind that different methods were used, there is a large range of population sizes and high clam densities are not necessarily the norm throughout the Tuamotus [e.g. Anaa Atoll, a raised shallow atoll dominated by sediments, with few hard-bottom patches (Pirazzoli et al., 1988)]. In addition, the history of Takapoto Atoll highlights the changing clam population. The stock along the atoll's lagoon margins (not the lagoonal pinnacles) was 9 million individuals in 1977 (Richard, 1982), 6.9 million in 1986 (Richard, 1989), 3.7 million in 1993 (Richard and Duval, 1993), 0.59 million in 1998 (Adessi, 1999), and 0.63 million in 2001 (Laurent, 2001). The highest variation (
80%) occurred in the wake of the 1998 El Niño Southern Oscillation event that created high positive sea surface temperature anomalies in the region, with lethal consequences to benthic communities (Mumby et al., 2001). A more severe decline was reported for the population size on the pinnacles (Laurent, 2001). The steady decrease observed before 1998 can be explained by local harvesting that was not compensated for by new recruitments.
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In Fangatau, no recent mortality events were reported before the May 2003 survey; however, in February 2004, mortality occurred in the shallowest areas (<50 cm) due to abnormally low lagoon levels that left clams exposed above water for an extended period. Unfortunately, the total loss of clams could not be estimated. The primary cause of the mortalities was an extremely poor renewal time of lagoonal waters due to very calm seas and wind. For semi-closed atolls, significant wave height vs. water renewal time curves show a quick drop as soon as wave heights are reduced (e.g. Takapoto Atoll, Andréfouët et al., 2001). Calm conditions have also caused massive benthic and fish mortalities in other Tuamotu lagoons (Adjeroud et al., 2001).
Need for management decisions?
From the estimates given here and from the population structure, it can be computed that the available biomass is around 1162 ± 172 tonnes of meat for the 4 km2 of lagoon studied here. This estimate is based on a specific biomass–size relationship and complete assessment of the clam population structure for each habitat class. Considering that only 1.18 km2 of every shallow lagoon is currently harvested, the stock drops to 431 ± 104 tonnes of meat. However, an additional limitation comes from the current regulation that prohibits the collection of animals with shell length less than 12 cm. Therefore, the commercially available stock is 364 ± 86 tonnes. With the current Fangatau exportation rates of 4 tonnes y–1, it may appear that the stock is far from endangered. However, export of clam meat will certainly continue to rise in the near future, because other islands in French Polynesia export as much as seven times the Fangatau export volume. In addition, the consequences of the fishery on recruitment/growth rates and stability of the population need to be investigated since sustainability cannot be predicted only by standing stocks assessments. Even without accounting for the recent mortalities, the population size of T. maxima, and the commercially available stock as estimated here, suggests that conservation initiatives will soon be necessary. This may include definition of no-take zones (permanent or temporary), artificial re-introduction of young clams in heavily fished areas, or an increase in the minimum harvestable size.
What is the appropriate image source for T. maxima assessment?
Degradation in spatial resolution from 1.5 m down to 5.6 m made little change in the estimation of the clam population. AP and ISS produce estimates of 23.65 ± 5.33 and 21.9 ± 5.48 million clams, respectively. Shifting to Landsat with geomorphological zones and 30-m resolution produced an overestimate of the population and increased the uncertainty (39.98 ± 8.45 millions). Nevertheless, the estimates are reasonable, with less than a factor of two difference from the highest resolution data, while the ratio of area covered by a Landsat and AP pixel, respectively, is equal to 400 (=900/2.25). Thus, a geomorphological classification scheme, which requires a simplified processing procedure compared with habitat mapping, may lead to quick and useful results for preliminary estimates.
Aerial photographs have adequate spatial resolution, but lack of NIR bands precludes glint correction and makes difficult a precise segmentation of land areas. In addition, complete coverage of the atoll required a mosaic of three different images which were acquired in different conditions of wind, solar azimuth/elevation angles, and flight azimuth angle. This subsequently made consistent processing for the entire atoll problematic. Many Tuamotu Atolls cannot be easily covered by aerial photography because of their remoteness from Tahiti, and costs of stationing an aircraft locally to wait for optimal imaging conditions can be very high. A specific acquisition for an atoll like Fangatau could easily cost more than US$ 20 000. Georectification of the image required ground control points (GCP) which were fortunately available for Fangatau, but this may not be the case at other sites.
The ISS image also had suitable spatial resolution and provided the additional benefit of complete coverage in a single frame. The ISS image shared the AP problem of georectification and lack of a NIR band for glint correction. However, since ISS photographs are free of charge, they may prove to be an extremely useful alternative for developing countries who cannot afford expensive images, especially if they have some type of maps or GCP which could allow georectification of the digital photograph. Both AP and ISS data also present saturated areas, along the back-reef flat of the inner reef dominated by bright sediments, but where also clams occur, precluding adequate processing of these locations.
In contrast, Landsat data are both georeferenced and have a NIR band. Landsat also provides complete coverage within single images and has a high gain setting which prevents image saturation. As noted above, however, spatial resolution is too coarse for detailed habitat mapping, only allowing mapping of geomorphological classes, which results in an overestimation of the clam population by a factor of two.
Which image source is most appropriate for future work on other atolls? The aforementioned problems point to imagery that has not been used for Fangatau Atoll. Based on our experience with IKONOS images (Andréfouët et al., 2003b, 2004; Capolsini et al., 2003; Hochberg et al., 2003; Palandro et al., 2003), we conclude that IKONOS or Quickbird high-resolution multispectral images would provide the best basis for T. maxima stock assessment. These products are available commercially. As of early 2004, the cost of imagery is about US$15 km–2 for any site worldwide. Their spatial resolutions are 2.6–4 m, they have NIR, red, green, and blue bands, and all bands are calibrated independently of the commercial operator by NASA (Pagnutti et al., 2003). Accurate calibration is also useful for bathymetric correction when using libraries of the spectral diffuse attenuation coefficient. Their geodetic and geometric accuracies are well characterized (Dial et al., 2003; Helder et al., 2003), and are on the order of a few metres, independently of any GCP. Finally, their 11-bit dynamic range helps avoid saturation in bright areas. This conclusion has recently been confirmed through processing of a Quickbird image for the second atoll considered in this research programme, Tatakoto Atoll. An IKONOS image will also be used for fine-scale comparison purposes. These results will be presented elsewhere, but without any doubt, the efficiency and ease of the image-processing stages were considerably improved with these spaceborne data.
Methodological generalization to other sites
Fangatau Atoll is characterized by its enormous clam population that dominates the lagoon reefscape between the surface and 5–6 m. Fangatau is a best-case scenario for clam stock assessment using remotely sensed data because the resource is one of the main components of most of the mapped habitats and is directly visible on high-resolution images. It also simplifies fieldwork planning, since both habitat surveys and resource assessment can be performed simultaneously. In other sites with lower T. maxima densities, it may be necessary to modify in situ methods, and design a reef habitat survey first to gather data useful for image-processing, then to make a second pass on key habitats to provide population data for resource assessment. This is similar to the method followed by Andréfouët et al. (2004) for algal biomass assessment and Long et al. (1993) for Trochus niloticus assessment.
On the methodological image processing side, Fangatau also provides a best-case scenario because habitat was strongly dependent on depth. Therefore, the usual problems of radiometric signal attenuation due to water depth were actually an advantage, increasing spectral differences between habitats. This situation is not the norm. In Tatakoto Atoll, for instance, patterns of habitats are very different and depth attenuation algorithms may be needed to increase map accuracy (Andréfouët et al., 2003b).
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Conclusion |
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TopIntroductionMaterial and methodsResultsDiscussionConclusionReferences |
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Marine resources in South Pacific Island and atoll environments are generally limited and careful planning is a necessity. Planning requires accurate and precise estimation of available stocks. The assessment scheme we have proposed here, driven by high-resolution images, provided rapid and synoptic estimates of the current Tridacna maxima population in Fangatau Atoll. The assessment of Fangatau's clam population based on in situ and remote sensing data provided a series of parameters critical for the sustainable management of the atoll resources. The information is now in the hands of French Polynesia managers who should soon make recommendations in collaboration with the local population. In addition, this pilot study provides information on remote sensing methods that can help improve benthic resources assessment in atoll environments.
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Acknowledgements |
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This study has been funded by the Government of French Polynesia (Contrat de Développement Etat-Territoire, phase 2), under an agreement between the Ministry of Fisheries and Université de la Polynésie française. We are grateful to Julie Robinson (NASA, Johnson Space Center) and the ISS astronauts for having acquired and made available a suite of useful images for Tuamotu Atoll studies since 2001. The Fangatau digital aerial photograph was provided by Service de l'Urbanisme de Polynésie française (Didier Lequeux). Patrick Capolsini (Université de la Polynésie française) helped in the field. SA was funded by NASA award NAG5-10908. We acknowledge Sam Goward and Darrell Williams, Landsat Science Team leaders, for providing the Landsat image. Finally, we acknowledge the Fangatau mayor, city council, and inhabitants for their hospitality and support for this programme. This is IMaRS contribution 081.
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Footnotes |
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1 Present address of S. Andréfouët: Institut de Recherche pour le Développement, BP A5, 98848 Nouméa, New Caledonia.
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References |
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