LETTERS

Significant contribution of the 18.6 year tidal cycle to regional coastal changes N. GRATIOT1 *†, E. J. ANTHONY2 , A. GARDEL2 , C. GAUCHEREL3 , C. PROISY4 AND J. T. WELLS5 1

Laboratoire d’Ecologie Littorale, IRD Guyane, BP165, route de Montabo, Cayenne, 97323, French Guiana ˆ d’Opale, Laboratoire d’Oceanologie ´ ´ Universite´ du Littoral Cote et de Geosciences, CNRS, UMR 8187 LOG, 32, Avenue Foch, 62930 Wimereux, France 3 INRA, UMR AMAP, Boulevard de la Lironde, TA A51/PS2, 34398 Montpellier cedex 5, France 4 IRD, UMR AMAP, Boulevard de la Lironde, TA A51/PS2, 34398 Montpellier cedex 5, France 5 Virginia Institute of Marine Science, College of William and Mary, Box 1346, Gloucester Pt., Virginia 23062, USA *Present address: LTHE (UMR IRD-CNRS-UJF-INPG) 1025, rue de la piscine, BP 53, 38041 Grenoble, France † e-mail: [email protected]

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Published online: 17 February 2008; doi:10.1038/ngeo127

Although rising global sea levels will affect the shape of coastlines over the coming decades1,2 , the most severe and catastrophic shoreline changes occur as a consequence of local and regional-scale processes. Changes in sediment supply3 and deltaic subsidence4,5 , both natural or anthropogenic, and the occurrences of tropical cyclones4,5 and tsunamis6 have been shown to be the leading controls on coastal erosion. Here, we use satellite images of South American mangrove-colonized mud banks collected over the past twenty years to reconstruct changes in the extent of the shoreline between the Amazon and Orinoco rivers. The observed timing of the redistribution of sediment and migration of the mud banks along the 1,500 km muddy coast suggests the dominant control of ocean forcing by the 18.6 year nodal tidal cycle7 . Other factors affecting sea level such as global warming or El Ni˜no and La Ni˜na events show only secondary influences on the recorded changes. In the coming decade, the 18.6 year cycle will result in an increase of mean high water levels of 6 cm along the coast of French Guiana, which will lead to a 90 m shoreline retreat. The low-frequency tide constituent results from the rotation of the nodal points of the lunar orbit and the ecliptic (the solar orbit) with a periodicity of 18.6134 yr (refs 8,9). By modifying the tidal amplitude by about 3%, this predictable phenomenon modulates the mean high water level (MHWL) by several centimetres. A full investigation of the hypothesis that the nodal cycle significantly affects the evolution of the coastline7 requires the periodic update of shoreline positions over significant spatial scales, a task greatly facilitated by the development of the monitoring of Earth from space over the past several decades. It also requires working on pristine coastlines, a rare situation worldwide, but one perfectly met by the muddy Amazon–Orinoco coast, referred to as the Guyanas coast. This is especially true of French Guiana, which is completely devoid of shoreline defences and groundwater or petroleum extraction activities that could generate subsidence. Thus, the dramatic changes exhibited by this coast are solely under the influence of natural processes, the most significant of which is the migration of 1.0–1.5 × 108 tons of mud per year that moves as mud banks from the Amazon to the Orinoco10–12 (see Supplementary Information, Fig. S1). Another important attribute in terms of shoreline change is the flatness of this coast. With mean intertidal slopes ranging from 1:1,000 to 1:3,000, a mean

sea-level elevation of 10 cm can result in flooding of thousands of hectares of mangrove forest and may induce a shoreline retreat of 100–300 m. A last important characteristic of this coast is the rapid adaptation to changes. Avicennia germinans is the only mangrove species that has developed a strategy of colonization that is sufficiently rapid to take advantage of the substrate provided by the migrating mud banks. A. germinans tree communities can be wiped out extensively during interbank phases, but can reappear in the same proportions within a period of two years. The seaward limit of mangrove swamps makes a reliable ground-level marker because mangrove seedlings colonize the leading edge of the mud banks, at a preferential level controlled by tidal characteristics. It is the best estimate for the shoreline position. If the MHWL is fluctuating, the mangrove response should indicate this through large-scale progradation and erosion13 . Yet, there are clearly other processes than the nodal cycle at work, among which are the sealevel rise due to the expansion of the global ocean volume, the sea-level fluctuations under the influence of the El Ni˜no Southern Oscillation and the Amazon sedimentary discharge fluctuations. These major processes are considered here. Sixty satellite images covering 39 dates from 20 October 1986 to 15 January 2006 were used to assess shoreline dynamics in French Guiana (see Supplementary Information, Table S1). Following ref. 14, the shoreline boundary was conservatively considered to be the limit of mangrove vegetation to compensate for the effects of the 2–3 m semi-diurnal tide in the area. Data were interpolated linearly, using the method developed in ref. 15, to provide a data matrix regularly distributed in time and space (Fig. 1a). Cubic and nearest interpolators provide similar results (see Supplementary Information, Fig. S2). To extrapolate our approach at a regional scale, we generated three mosaics of the Guyanas coast for the years 1999, 1995 and 2006. This database is the most comprehensive one ever set up to study the coastal processes of the region. The shoreline of French Guiana exhibits five alternating sectors of mangrove colonization and erosion each 30–40 km long (Fig. 1a). These sectors tend to shift north-westward and constitute the fingerprint of mud banks in migration from Brazil to Surinam (at a rate of 1–3 km yr−1 ). The most dynamic spatial variations are observed between 570 km and 650 km from the Amazon. In this region, some areas suffered erosion of more than 2 km, whereas others prograded over more than 3 km in

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88 90 92 94 96 98 00 02 04 06 Year –37 MT yr –1

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Figure 1 Spatio-temporal fluctuations of the shoreline and of the tide levels in French Guiana. a, Relative shoreline position (RSP, cross-shore) of the coast of French Guiana using the year 2006 as the reference year. Blue and red areas are associated with progradation and erosion, respectively. Triangles indicate the positions of the main river mouths. Filled triangles and dashed lines delimit international borders. b, RSP when averaged over the 220-km-long area of survey. The thickness is representative of the accuracy (±20 m). c, Nodal cycles of the MHWL in Surinam and French Guiana. From 1958 to 1978, tidal gauge measurements in the mouth of the Surinam River7 ; from ´ 1979 to the present, data from the tidal model of the Service Hydrographique et Oceanographique de la Marine obtained from tidal gauge measurements on Devil’s Islands (French Guiana). The corresponding phases of overall erosion and colonization reported by previous studies18,19 and in this work are shown as red and green patches.

twenty years. Hot spots of shoreline changes also developed at the river mouths (Fig. 1a, triangles on right y axis) as a result of complex geomorphic adaptations to sea-level fluctuations and longshore sediment transport1,16–18 . As these river-mouth sectors correspond to only 5% of the coastline, we have included them in the calculation of the mean shoreline fluctuations over time (Fig. 1b). In the late 1980s, the mangrove fringe was wider and corresponded to an average distance seaward of 100–130 m relative to its current position. It then suffered severe erosion up to 1999–2000, at a rate of about 30 m yr−1 . This severe erosional phase was then followed by another spectacular period during which the coast prograded by about 200 m to attain its current position (Fig. 1b). Following the method proposed in ref. 10 and adapted in ref. 14, the quantitative erosion/accretion of mangrove surfaces shown in Fig. 1b can be converted to estimates of sediment volumes. Over the 1988–1999 period, the coastal sediment balance lacked approximately 37 million tons (MT) per year, so that the shoreline retreated. The trend has reversed since 2000 with an estimated excess in shoreline sediment of 35 MT yr−1 . This massive progradation event is not unique and a similar event was observed in neighbouring Surinam from 1966 to 1970 (ref. 19). More generally, it seems that periods of erosion and progradation monitored in refs 19 and 20 and the ones reported here indeed

correlate with the 18.6 yr nodal cycle and emphasize the plausibility of a causal link7 (Fig. 1c). Taking the analysis one step further requires examination of the main sources of forcing, among which is the Amazon River. Alone, it accounts for 10% of the total sediment discharge supplied by the world’s rivers to the oceans21 and almost all of the sediment along the coast of Guyanas22 . Since 2000, the suspended sediment discharge of the Amazon has increased by about 18% (compared with the 1996–1999 period of ref. 23). This increase will probably reinforce the sediment supply along the coast of French Guiana in the near future, but it is very unlikely to be responsible for the phase of colonization under progress since 2000. First, the Amazon sediment inputs are usually reworked on the continental shelf and sequestered along the coastal zones of the north of Brazil for several years before being transported north-westward24 . Second, even if the input to the mud bank system was instantaneous, it would have added only about 10–15 MT yr−1 if we assume a direct and proportional adjustment of the regional sediment fluxes11 . This value is five times lower than the 72 MT yr−1 that sparked the change from erosion to accretion in 2000 (Fig. 1b; Supplementary Information, Fig. S3). Finally, the migration rate of mud banks in French Guiana is in the range of 1–3 km yr−1 . If the increase in the Amazon discharge was the main factor explaining the

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LETTERS a

cm

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54 48 42 36 30 24 18 12 6

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Sea-level rise Nodal + 1 mm yr –1 Nodal + 3 mm yr –1 F.Guiana erosion Colonization MHWL Guyanas coast

Cross-shore variations (m)

400 300 200 100

Figure 3 Predicted shifting of the MHWL under the 18.6 year nodal cycle for the next decade. (Adapted from the global map of tidal amplitude proposed by ref. 29 by considering a modulation of signal of 3%.) Grey areas correspond to locations of decrease or negligible rise. The black box (48W-62W-2N-12N) delimits the mud bank system of the Guyanas, South America.

0 –100 –200 1990

1995

2000

2005

2010

2015

Year

Figure 2 Measured and estimated shoreline fluctuations along the Guyanas coast. a, Temporal fluctuations of the MWL and of the MHWL as estimated from Ssalto/Duacs products. b, Measured (pink curve = erosional phase and green curve = accretional phase) and expected (grey and blue curves) shoreline fluctuations along French Guiana, using 2006 as the reference year. The white dots indicate the measured regional trend, when considering the 1,500-km-long Guyanas coast.

shoreline progradation observed in French Guiana over the past seven years, then major areas of pioneer mangroves should have developed to the east closer to the source. This major colonization is not observed in Fig. 1a. Three forcing mechanisms, namely the nodal cycle, sea-level rise by global warming and the El Ni˜no Southern Oscillation interact to modulate the MHWL. Considering the MHWL instead of the mean water level (MWL) significantly modifies our apprehension of the shoreline dynamics, as shown in Fig. 2a. The MHWL (Fig. 2a, blue curve) increases almost linearly up to 1996, and then undergoes strong fluctuations from 1997 to 1998. These fluctuations are the local signature of the major 1997–1998 El Ni˜no Southern Oscillation event. From the end of 1998 to early 2003, the MHWL decreases by about 4 cm. It rises again from that date. By making the assumption that the horizontal shoreline fluctuations correspond at such a timescale to a simple adjustment of the ecosystem to the cross-shore vertical fluctuations, and by considering a mean intertidal shoreline slope of 1:2,000, we can easily compare the measured shoreline fluctuations with those expected from long-term MHWL fluctuations (Fig. 2b, pink, green curves and the grey curve, respectively). We obtain an overall fit that confirms the predominant role played by the lunar 18.6 year nodal cycle7 . It is clear that the mean sea-level rise attributed to global warming (dashed line) contributes to shoreline fluctuations over time (coefficient of determination r 2 = 0.24 with a confidence level >99%), but to a lesser extent than the nodal cycle (r 2 = 0.68, with a CL > 99%). The two effects combined (sea-level rise of 2.3 mm yr−1 and nodal cycle) are nicely correlated to the French Guiana shoreline fluctuations (r 2 = 0.90, with a CL > 99%). Results are comparable when considering mean intertidal slopes

in the range 1:1,500–1:2,500 (relative difference of 5% and 8%, respectively). At a regional scale, the shoreline dynamics exhibits the same trend, as highlighted by the agreement between the data from French Guiana and the three mosaics covering the Guyanas coast (circles). El Ni˜no phases also have visible impacts on the shoreline, enhancing erosion just after the 1997–1998 event and even after the 1991–1993 event, although to a much weaker extent (Fig. 2b). The 1997–1998 event caused one of the most severe droughts of the nineteenth century in the Guyanas, with major consequences on the ecosystem25–27 , while engendering unprecedented erosion of the few sandy pocket beaches in French Guiana28 . It is interesting to note that after a time of resiliency of about three years, the mean shoreline position resumes the trend defined by the coupled effect of the nodal cycle and sea-level rise by global warming. This study confirms the hypothesis that low tidal constituents are a major controlling factor in the evolution of the very gently sloping muddy coastal plain and shoreface of the Guyanas7 . Although tides have no effect on the long-term sea-level trend, they induce important fluctuations of the MHWL, when considering decadal timescales. As this timescale is particularly important for shoreline management and for policy makers, it is crucial to highlight the shoreline fluctuations associated with the 18.6 year cycle. From now to 2015, the coast of the Guyanas is expected to retreat by about 150 m, 60% of this retreat resulting from the effect of the low-frequency tide constituents and 40% from sea-level rise due to global change. The nodal tidal cycle has a predictable effect on the tidal amplitude everywhere. It modulates the tidal amplitude by about 3% so that regions experiencing macro-tidal regimes are particularly concerned. Over the next decade, many coastal areas in Australia, Canada, China, England and France will experience a sea-level rise of several tens of centimetres due to the 18.6 tidal cycle (Fig. 3). This rise will contribute significantly to coastal erosion generated by global sea-level rise. Received 5 November 2007; accepted 18 January 2008; published 17 February 2008. References 1. Pilkey, O. H. & Cooper, J. A. G. Society and sea level rise. Science 303, 1781–1782 (2004). 2. Zhang, K. Q., Douglas, B. C. & Leatherman, S. P. Global warming and coastal erosion. Clim. Change 64, 41–58 (2004). 3. Syvitski, J. P. M., Vorosmarty, C. J., Kettner, A. J. & Green, P. Impact of humans on the flux of terrestrial sediment to the global coastal ocean. Science 308, 376–380 (2005). 4. Dixon, T. H. et al. Subsidence and flooding in New Orleans. Nature 441, 587–588 (2006). 5. Ericson, J. P., Vorosmarty, C. J., Dingman, S. L., Ward, L. G. & Meybeck, M. Effective sea-level rise and deltas: Causes of change and human dimension implications. Glob. Planet. Change 50, 63–82 (2006). 6. Borrero, J. C. Field data and satellite imagery of tsunami effects in Banda Aceh. Science 308, 1596 (2005). 7. Wells, J. T. & Coleman, J. M. Periodic mudflat progradation, northeastern coast of South America; a hypothesis. J. Sedim. Petrol. 51, 1069–1075 (1981).

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LETTERS 8. Pugh, D. T. Tides, Surges and Mean Sea-Level (Wiley, Chichester, 1987). 9. Marchuk, G. I. & Kagan, B. A. Dynamics of Ocean Tides (Kluwer, Dordrecht, 1989). 10. Eisma, D., Augustinus, P. & Alexander, C. Recent and subrecent changes in the dispersal of Amazon mud. Neth. J. Sea Res. 28, 181–192 (1991). 11. Meade, R. H., Dunne, T., Richey, J. E., Santos, U. M. & Salati, E. Storage and remobilisation of suspended sediment in the lower Amazon River of Brazil. Science 228, 488–490 (1985). 12. Baltzer, F., Allison, M. & Fromard, F. Material exchange between the continental shelf and mangrove-fringed coasts with special reference to the Amazon–Guianas coast. Mar. Geol. 208, 115–126 (2004). 13. Blasco, F., Saenger, P. & Janodet, E. Mangroves as indicators of coastal change. Catena 27, 167–178 (1996). 14. Allison, M. A. & Lee, M. T. Sediment exchange between Amazon mudbanks and shore-fringing mangroves in French Guiana. Mar. Geol. 208, 169–190 (2004). 15. Gardel, A. & Gratiot, N. A satellite image-based method for estimating rates of mud bank migration, French Guiana, South America. J. Coast. Res. 21, 720–728 (2005). 16. Lefebvre, J. P., Dolique, F. & Gratiot, N. Geomorphic evolution of a coastal mudflat under oceanic influences: an example from the dynamic shoreline of French Guiana. Mar. Geol. 208, 191–205 (2004). 17. Fromard, F., Vega, C. & Proisy, C. Half a century of dynamic coastal change affecting mangrove shorelines of French Guiana. A case study based on remote sensing data analyses and field surveys. Mar. Geol. 208, 265–280 (2004). 18. Plaziat, J. C. & Augustinus, P. Evolution of progradation/erosion along the French Guiana mangrove coast: A comparison of mapped shorelines since the 18th century with Holocene data. Mar. Geol. 208, 127–143 (2004). 19. Augustinus, P. G. E. F. The Changing Shoreline of Surinam (South America). Thesis, Univ. Utrecht (1978). 20. Choubert, B. & Boy´e, M. Envasements et d´esenvasements du littoral en Guyane franc¸aise. C. R. Acad. Sci. 249, 145–147 (1959). 21. Kineke, G. C. Fluid Muds on the Amazon Continental Shelf. Thesis, Univ. Washington, Seattle (1993). 22. Gibbs, R. J. Amazon River sediment transport in Atlantic Ocean. Geology 4, 45–48 (1976).

23. Guyot, J. L., Filizola, N. & Laraque, A. Sediment Budgets 347–356 (IAHS Publ. 291, IAHS, Iguacu, 2005). 24. Allison, M. A., Lee, M. T., Ogston, A. S. & Aller, R. C. Origin of Amazon mudbanks along the northeastern coast of South America. Mar. Geol. 163, 241–256 (2000). 25. Gaucherel, C. A study of the possible extended influence of the ENSO phenomenon. Comptes Rendus Geosci. 336, 175–185 (2004). 26. Hammond, D. S. & ter Steege, H. Propensity for fire in Guianan rainforests. Conservation Biol. 12, 944–947 (1998). 27. Mol, J. H., Resida, D., Ramlal, J. S. & Becker, C. R. Effects of El Nino-related drought on freshwater and brackish-water fishes in Suriname, South America. Environ. Biol. Fish. 59, 429–440 (2000). 28. Anthony, E. J., Gardel, A., Dolique, F. & Guiral, D. Short-term changes in the plan shape of a sandy beach in response to sheltering by a nearshore mud bank, Cayenne, French Guiana. Earth Surf. Process. Land. 27, 857–866 (2002). 29. Simon, B. La Mar´ee Oc´eanique Cˆoti`ere (Institut Oc´eanographique, Paris, 2007).

Acknowledgements We wish to thank M. Nourtier, B. Simon and J. L. Guyot. This work has the financial support of the Programme National Environnement Coˆ tier, of the Research Council of the Universit´e du Littoral Cˆote d’Opale and of the Centre National des Etudes Spatiales and the Ecolab Association. Sea-level fluctuations were extracted from http://las.aviso.oceanobs.com/las/servlets/dataset merged product. ASAR/ENVISAT data are provided by ESA 2006, source SEAS-Guyane. Correspondence and requests for materials should be addressed to N.G. Supplementary Information accompanies this paper on www.nature.com/naturegeoscience.

Author contributions N.G. led the project on the basis of a hypothesis initially proposed by J.T.W; N.G., A.G., C.P., E.J.A. and N.G. analysed the remote sensing data and the shoreline dynamics; C.G. provided insights concerning regional El Ni˜no and La Ni˜na dynamics; N.G., E.J.A. & J.T.W. wrote the paper. Reprints and permission information is available online at http://npg.nature.com/reprintsandpermissions/

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Supplementary Information.

a

b

c

Figure 1. Sediment balance of the 1500 km-long muddy coast of South America between the Amazon and the Orinoco rivers. a, map of the Amazon-Orinoco sediment system. The black box delimits the area used to compute the Mean Sea Level Anomalies from the http://las.aviso.oceanobs.com /las/servlets/dataset merged product. The white bar delimits the mud bank system in French Guiana. The black bars and the white bar all together delimit the mud bank system of the Guyanas. b, delivery paths and sediment loads (in 106 T y -1) from the Amazon to the Guyanas 1. About 10-15% of the Amazon solid river flux contributes to the sediment budget of the Guyanas shelf and coast. c, Amazon sediment discharge at Obidos 2. The sediment discharge, averaged over four years before and after 2000, shows an increase of approximately of 18%, from 2.06 to 2.44 Tons per day. The contribution of the Amazon sediment discharge to the mud bank system being of the order of 10-15% 3, the increase observed would have added about 15-20 106 Tons of sediment per year to the mud bank system. 1. 2.

Allison, M. A., Nittrouer, C. A. & Kineke, G. C. Seasonal sediment storage on mudflats adjacent to the Amazon River. Marine Geology 125, 303-328 (1995). Guyot, J. L., Filizola N., Laraque A. 347-356. (IAHS, Iguacu, 2005).

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3.

Meade, R. H., Dunne, T., Richey, J. E., Santos, U. M. & Salati, E. Storage and remobilisation of suspended sediment in the lower Amazon River of Brazil. Science 228, 488-490 (1985).

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Supplementary Information.

Figure 2. Intercomparison of different interpolation techniques used to estimate the relative shoreline position when averaged over the 220 km long area of survey in French Guiana.

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Supplementary Information.

Figure 3. Quantitative shoreline erosion/accretion fluctuations over time, converted into sediment volumes. Black line represents estimate from the quantitative erosion/accretion of mangrove surfaces following the method proposed by

1

and adapted by 2. The

method is based on a linear adjustment of the mangrove-colonized area to erosion/accretion processes, these latter being considered as active in the range -3m to +1m above the shoreline fringe. As in the work of 2 , we consider a mean bulk density of 1.85 T m-3. The beginning of colonization (black line above zero) occurs in 2000 and is still under progress. Grey line and bold grey line are estimates of the annual input of sediment to the mud bank system, taking into considering the sediment balance presented in Sup Info, Fig. 1 b with the sediment input fluctuations observed at Obidos 3

(Sup Info Figure 1c). This estimate assumes an instantaneous transit of sediment.

When smoothed for seasonal fluctuations (grey bold line), the sediment supplied to the mud bank system has been negative since 2004, and is thus not sufficient to explain the phase of progradation observed along the Guyanas coast since 2000 (Fig. 3, black line). 1.

Eisma, D., Augustinus, P. & Alexander, C. Recent and Subrecent Changes in the Dispersal of Amazon Mud. Netherlands Journal of Sea Research 28, 181-192 (1991).

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2. 3.

Allison, M. A. & Lee, M. T. Sediment exchange between Amazon mudbanks and shore-fringing mangroves in French Guiana. Marine Geology 208, 169-190 (2004). Guyot, J. L., Filizola N., Laraque A. 347-356. (IAHS, Iguacu, 2005).

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Supplementary Information.

scene 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33

region Kourou Kourou Kourou Kourou Kourou Kourou Kourou Kourou Kourou Kourou Kourou Kourou Kourou Kourou Kourou Kourou Kourou Kourou Kourou Kourou Kourou Kourou Kourou Sinnamary Sinnamary Sinnamary Sinnamary Sinnamary Sinnamary Sinnamary Sinnamary Sinnamary Sinnamary

satellite SPOT SPOT SPOT SPOT SPOT SPOT SPOT SPOT SPOT SPOT SPOT SPOT SPOT SPOT SPOT SPOT Landsat SPOT SPOT SPOT SPOT SPOT SPOT SPOT Landsat SPOT SPOT SPOT Landsat SPOT SPOT SPOT Landsat

date 20 Oct 86 17 Nov 91 02 Oct 93 30 Aug 94 16 Oct 95 26 Oct 95 28 Sept 96 02 Sept 97 20 June 98 06 Sept 98 09 May 99 07 Feb 00 02 July 01 14 Oct 01 14 Dec 01 05 Aug 02 19 Sept 02 13 Aug 03 29 Aug 03 30 Aug 03 08 Sept 03 15 Sept 03 19 Sept 03 20 Aug 86 23 July 87 27 Oct 89 06 Sept 91 17 June 92 22 Sept 92 28 Oct 93 03 Aug 95 28 Sept 96 03 Aug 97

scene 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66

region satellite Sinnamary SPOT Sinnamary Landsat Sinnamary SPOT Sinnamary SPOT Sinnamary SPOT Sinnamary SPOT Sinnamary SPOT Sinnamary SPOT Mana Landsat Mana SPOT Mana Landsat Mana Landsat Mana SPOT Mana Landsat Mana SPOT Mana SPOT Mana SPOT Mana SPOT Kaw Landsat Kaw SPOT Kaw SPOT Kaw SPOT Kaw SPOT Kaw SPOT Kaw SPOT Kaw SPOT All Guianas mosaicASAR All guianas mosaicJERS Surinam Landsat Surinam Landsat Surinam Landsat Guyana Landsat Guyana Landsat

date 02 Sept 97 21 Nov 99 08 Feb 00 23 Nov 01 14 Dec 01 26 July 02 01 Oct 02 07 Oct 02 23 July 87 17 June 92 22 Sept 92 03 Aug 97 10 Aug 98 21 Nov 99 28 July 00 23 Sept 01 26 July 02 26 Aug 03 18 July 88 17 Nov 91 20 June 98 15 Aug 99 05 Dec 00 14 Dec 01 05 Aug 02 13 Aug 03 2006 1995 21 Nov 99 09 Sept 99 03 Nov 99 15 Aug 00 07 Sept 00

Table 1. The remote sensing database used to analyze shoreline evolution.

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