Coastal dynamics and its consequences for mangrove structure and functioning in French Guiana

F. Fromard EcoLab – Laboratoire d'écologie fonctionnelle - UMR 5245 (CNRS-UPS-INPT) 29 rue Jeanne Marvig 31055 Toulouse cedex (France) Tèl: : 33 5 62 26 99 72 fax: 33 5 62 26 99 99 email:[email protected]

C. Proisy Institut de Recherche pour le Développement (IRD), UMR AMAP Boulevard de la Lironde, TA A51/PS2, Montpellier cedex 5, F-34398 France Tél.: 33.467.617.545, Fax: 33.467.615.668 email: [email protected]

Huge quantities of sediment originating from the Andean mountain range collect in the Amazon River's vast catchment area and are discharged into the Atlantic Ocean. Carried north-westwards from Brazil by marine currents and trade winds, these materials flow to the coastlines of French Guiana, Surinam, and Guyana, and to the mouth of the Orinoco River in Venezuela. This 1,600 km coastal area is under the influence of what is termed the Amazonian Dispersal System. This system has characteristic dynamics: the sediments form into mobile mud banks that migrate at approximately 2 km per year along the coast, and undergo alternate phases of intense accretion and spectacular erosion. As they are subject to the tidal cycle and close to the equator, only mangrove vegetation can develop on these unstable substrates, and this occurs with very specific dynamics and functioning linked to the constant changes affecting the coastline (Allison et al. 2000, Baltzer et al. 2004). In French Guiana the mangrove forest covers an area of approximately 70,000 ha and colonizes recent and current marine deposits, spreading several kilometres inland to the limit of the tidal influence (Fig.1). As is typical of the whole Atlantic area, the mangroves of French Guiana exhibit limited biodiversity. Avicennia germinans is the dominant species 1

forming adult stands, which are often monospecific and even-aged. A. germinans forms pioneer stands on its own or in association with Laguncularia racemosa. Rhizophora racemosa and R. mangle are present in mixed mangrove swamp forest communities along riverbanks and at the limit of tidal influence. Although subjected to strong natural dynamics, the mangroves of French Guiana are also characterized by low anthropogenic pressure as a consequence of the very low population density (2.4 people/km2), even though the population is largely concentrated in the coastal region. Mangrove wood is not exploited for construction, charcoal, or domestic purposes, and while the wild shrimp fishery is an important economic activity for the country, shrimp aquaculture is not yet developed. The study of this pristine forest ecosystem is particularly valuable for developing an understanding of the structure of mangrove stands, and in modelling their natural dynamics and growth. Through a combination of field surveys and remote sensing techniques applied to different parts of the French Guiana coast, successive mangrove stages have been identified including pioneer and young stands, and adult, mature, mixed, and decaying formations. A combined model of Amazonian mangrove dynamics has been proposed that includes forest development and sedimentological processes (Fromard et al. 1998, 2004, Gratiot et al. 2007) (Fig 2). Key phases in the dynamics have been specifically analysed including the establishment of A. germinans propagules in relation to the emersion–immersion cycle of mud banks, and the structuring of pioneer mangrove stages. Also highlighted have been the very high growth rate of A. germinans seedlings, the early flowering and fruiting of individuals of this species (neoteny phenomena), and the timing of dispersal processes to coincide with favourable sedimentological conditions. These processes appear to be specific to the French Guiana populations of A. germinans, and are thought to confer a selective advantage in the very strongly constraining environment of the Amazonian coast. Whereas classical spatial approaches (aerial photographs and SPOT and Landsat scenes) have facilitated mapping of coastal and mangrove surface changes over the last 50 years (Fig.3), synthetic aperture radar images have demonstrated promise in assessing forest parameters and the biomass values of mangrove stands (Proisy et al. 2000, 2002; Lucas et al. 2007). The very high resolution data from Ikonos or Quickbird satellites also provide a high level of accuracy for mangrove studies. In this context, we recently proposed the innovative Fourier-based Textural Ordination (FOTO) method, which computes texture indices of canopy grain by performing a standardized principal component analysis on the Fourier spectra obtained for image windows (Proisy et al. 2007). We believe that FOTO texture maps can be very useful 2

in assisting with field campaigns and will greatly contribute to research programs concerning mangrove forests. Moreover, the robust statistical relationship found between canopy texture and forest parameters points to a strong coupling between canopy aspect and the threedimensional dynamic processes of vertical growth, inter-tree competition, and self-thinning. Biomass mapping of unexplored and low accessibility mangroves may particularly benefit from this approach (Fig.4). . The Amazonian coastal area appears to be a unique environment for both studying mangrove dynamics and developing new methods and tools for modelling coastal changes. At the local scale, maritime transport is strongly impacted by the shifting of sediments. Access to harbours can involve costly daily dredging of mud. Prediction of rates of mud bank migration may thus enable better forecasting related to coastal management issues (Gardel and Gratiot 2005). Simulating mangrove dynamics and changes will also assist inshore fishing, ecotourism, and the regional economy, as mangroves are important feeding and nursery areas for many species of shrimps, fish, and birds. At the regional scale, the Amazonian Dispersal System, which is the driving force for mangrove establishment, is related to the dynamics of the Amazon River and its catchment area. Disturbances affecting the Amazonian Basin, such as rainfall anomalies or changes in land cover, could interfere with sedimentary processes and affect mangrove dynamics in French Guiana in the middle or long term (Ronchail et al 2002, Werth and Avissar 2002). At the global scale, recurring El Nino events and the expected sea level change are also likely to affect Amazonian coastal dynamics, and thus mangrove structure and function. Considering the flatness of the coastal plain of French Guiana, a mean sea level rise of a few centimetres could result in flooding of hundreds of hectares of mangrove forest and induce considerable shoreline retreat. Mangrove ecosystems of this pristine coast have evolved resilience to drastic environmental changes, a knowledge of which will undoubtedly be of interest to those involved in rehabilitation, preservation, and management of threatened coasts in the tropics. References Allison, M.A., Lee, M.T., Ogston, A.S. and Aller, R.C., 2000. Origin of Amazon mudbanks along the northern coast of South America. Marine Geology 163 : 241-256. 3

Baltzer, F., Allison, M. and Fromard, F., 2004. Material Exchange between the continental shelf and mangrove-fringed casts with special reference to the Amazon- Guianas coast. Marine Geology 208 : 115-126. Fromard, F., Puig, H., Mougin, E., Marty, G., Betoulle, J.L. and Cadamuro, L., 1998. Structure and above-ground biomass of mangrove ecosystems: New data from French Guiana. Oecologia 115: 39 - 53. Fromard, F., Vega, C. and Proisy, C., 2004. 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. Marine Geology, 208(2-4): 265-280. Gardel, A. and Gratiot, N., 2005. A satellite image-based method for estimating rates of mud bank migration, French Guiana, South America. Journal of Coastal Research, 21(4): 720-728. Gratiot, N., Gardel, A. and Anthony, E. J., 2007. Trade-wind waves and mud dynamics on the French Guiana coast, South America: Input from ERA-40 wave data and field investigations. Marine Geology, 236(1-2): 15-26. Lucas, R. M., Mitchell, A. L., Rosenqvist, A., Proisy, C., A., M. and Ticehurst, C., 2007. The potential of L-band SAR for quantifying mangrove characteristics and change: Case studies from the Tropics. Aquatic Conservation: Marine and Freshwater Ecosystems, 17(3): 245-264. Proisy, C., Couteron, P. and Fromard, F., 2007. Predicting and mapping mangrove biomass from canopy grain analysis using Fourier-based textural ordination of IKONOS images. Remote Sensing of Environment, 109(3): 379-392. Proisy, C., Mougin, E., Fromard, F. and Karam, M.A., 2000. Interpretation of polarimetric signatures of mangrove forest. Remote Sensing of Environment 71 : 56– 66. Proisy, C., Mougin, E., Fromard, F., Karam, M.A. and Trichon, V., 2002. On the influence of canopy structure on the polarimetric radar response from mangrove forest. International Journal of Remote Sensing 23(20): 4197– 4210 Ronchail, J., Cochonneau, G., Molinier, M., Guyot, J.L., De Miranda Chaves, A.G., Guimaras, V. and De Oliveira, E., 2002. Interannual rainfall variability in the Amazon Basin and sea-surface temperatures in the equatorial pacific and the tropical Atlantic oceans. International Journal of Climatology 22: 1663–1686. Werth, D. and Avissar, R., 2002. The local and global effects of Amazon deforestation. Journal of Geophysical Research 107 : D20.

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Figure captions Figure 1: The French Guiana coastal landscape with adult, homogeneous mangrove stands (A. germinans) in the foreground (right), riverine mangrove (Rhizophora spp.) along the river bank, and swamp forest (left). Bare mud banks in the background and mangrove islets separated from the main mangrove by erosion processes highlight Amazonian coastal dynamics. Figure 2: Sketch of French Guiana mangrove dynamics, driven by the alternate phases of accretion and erosion, and by the Amazonian Dispersal System. Ag : Avicennia germinans

Lr : Laguncularia racemosa

Rssp : Rhizophora mangle,

Rhizophora racemosa Figure 3: Example of mangrove landscape evolution through decades in the Sinnamary region, French Guiana. Maps have been interpreted from a time series of aerial photographs and SPOT satellite images (complete series in Fromard et al., 2004). Figure 4: FOTO-derived aboveground biomass map of the Kaw site, French Guiana (after Proisy et al., 2007).

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Sinnamary

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Sinnamary

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Rising mangrove Old mangrove

Swamp Flooded forest

Sinnamary

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Intertidal bare mud

Sinnamary

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Mud accretion Mud remobilization