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Individual Based Modeling of Green Turtle SpatialDynamics in the Southwest Indian Ocean

Mayeul Dalleau, Simon Benhamou, Stéphane Ciccione, Gilles Lajoie,Jean-Yves Georges, Jérôme Bourjea

To cite this version:Mayeul Dalleau, Simon Benhamou, Stéphane Ciccione, Gilles Lajoie, Jean-Yves Georges, et al.. Indi-vidual Based Modeling of Green Turtle Spatial Dynamics in the Southwest Indian Ocean. 7th WesternIndian Ocean Marine Science Association, Oct 2011, Mombasa, Kenya. 2011. �hal-02269030�

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AcknowledgmentsThe project is funded byDirection de l’Environnement, de l’Aménagement et du Logement - La RéunionTerres Australes et Antarctiques FrançaisesKélonia, l’observatoire des tortues marinesInstitut français de recherche pour l’exploitation de la mer - La Réunion

The PhD candidate is funded byRégion Réunion

The presentation is funded byKélonia, l’observatoire des tortues marinesWestern Indian Ocean Marine Science AssociationInternational Sea Turtle SocietyWestern Pacific Regional Fishery Management CouncilU.S. Fish and Wildlife ServiceU.S. National Marine Fisheries ServiceDisney Worldwide Conservation Fund

Mayeul Dalleaua,b,c,d, Simon Benhamoub, Stéphane Ciccionec, Gilles Lajoiea, Jean-Yves Georgese, Jérôme Bourjead

aCrégur - université de la Réunion, 15 avenue René Cassin, BP7151 97715 Saint-Denis Cedex9, La Réunion, FrancebCnrs - Cefe, 1919 route de Mende 34293 Montpellier Cedex 5, France

cKélonia, 46 rue du Général de Gaulle 97436 Saint-Leu, La Réunion, FrancedIfremer, rue Jean Bertho BP 60 97 822 Le Port Cedex, La Réunion, France

eCnrs - Iphc, 23 rue Becquerel 67087 Strasbourg, France

Contact: mayeuldalleau@kelonia.org

INDIVIDUAL BASED MODELING OF GREEN TURTLE SPATIAL DYNAMICSIN THE SOUTHWEST INDIAN OCEAN

IntroductionSouthwest Indian Ocean (SWIO) represents a noteworthy region to study green turtle Chelonia mydas spatial ecology. Indeed, spatial complexity of the region and presence of numerous nesting sites (mostly islands) as well as vast nesting areas (mostly East-Africa and Madagascar) is a unique opportunity to understand the role of space in turtle ecology. For more than twenty years now, a number of effective studies have been conducted locally in major ar-eas. Due to recent progress in wildlife tracking, movements of marine turtles between those sites are starting to be well-documented. Here, we propose an original approach to integrate this knowledge using a spatially explicit individ-ual-based model.

ObjectivesThe main objective of the model is to study the influence of SWIO topology to the reproductive potential of green turtle rookeries. As a matter of fact, spatial arrangement of nesting and feeding areas affects population viability. Proxim-ity and accessibility of feeding sites is likely to favor reproduction by reducing the cost of the migration. On the other side overpopulated feeding sites might delay reproduction event through food competition. Thus, population repro-ductive potential and therefore viability may be a resulting balance between the accessibility of the sites and the number of individuals that share this site.

Material and MethodsIndividual-based modelingIndividual-based or agent-based models (IBM) generically refer to models that infer the global dynamic of a system by modeling and simulating the constitu-ents of that system. In ecology, IBMs are models that derivate the properties of ecological systems from the properties of the individuals constituting these systems. This “bottom-up” approach allows the understanding of unexplained properties at population scale from a good knowledge of what is happening at individual scale. We used the publicly available platform NetLogo to imple-ment the model.

Individual cycleWe decided to consider only adult female migration cycle. Every turtle indi-vidual owns an energetic level. Similarly feeding sites is associated with a feed-ing quality. Turtle can intake energy only at feeding site simultaneously affect-ing the feeding quality of this site. While nesting or migrating every individual expends a relative amount of energy. Three different types of migration are implemented. pre- and post-nesting migrations are go and return movements between a feeding and a nesting site, foraging migration is a movement be-tween two feeding sites. When the energetic level of an individual reaches over a minimum threshold, it starts a pre-nesting migration. When the quality of a feeding site goes under a minimum threshold, the individual starts forag-ing migration.

Feeding and nesting sitesWe choose to study strategically located nesting sites. Those are the French Ep-arses islands and Mayotte. It should be noted that any nesting sites could eas-ily be added to the model. Feeding sites have been located according to expert knowledge of the region.

Reproductive potentialThe population reproductive potential was assess as the product of the number of nesting individuals by their energetic levels.

reproductive potential = number of nesting individuals x mean of energetic level at nesting

ResultsWith a few number of simulated scenarios, the model already exhibits inter-esting patterns regarding reproductive potential of green turtle rookeries in the SWIO. Under moderate site depletion, an island (e.g. Tromelin) located far from the feeding sites areas generally displayed a lower reproductive po-tential while islands (e.g. Mayotte, Glorieuses) closely surrounded by numer-ous feeding areas displayed a higher reproductive potential. This can easily be explained, the migration cost being higher when turtles have to swim long distances. Indeed, lowering the energetic expenditure due to migration tends to homogenize rookeries reproductive potentials. Remarkably increasing the impact of individuals on feeding site quality also tends to reduce these differ-ences. This is mainly because turtles from remote nesting islands make use of less frequented feeding sites. So our model suggests that longer reproductive migration can be compensated by a lower frequentation of the feeding areas. Further simulations should confirm these results and guide us in our under-standing of the influence of the SWIO spatial topology on green turtles popula-tion.

DiscussionsAlso this model showed very intuitive results, further investigation is needed at this stage to gain confidence in the results. Exploiting this model to its best requires a sensitivity analysis in particular to energetic parameters. Moreover, more individual variability could easily be implemented. We also plan to run more simulations under different case scenarios (e.g. altering local feeding sites quality). Oceanographic and environmental variables also play for sure an important role in the spatial dynamic of the green turtle in the SWIO and could be integrated.

feeding sitesnesting sites

INDIAN OCEAN

South Africa

Mozambique

Tanzania

Kenya

Europa

Juan de Nova

GlorieusesMayotte

Tromelin

La RéunionMadagascar

migration distance migration duration

nesting females number reproductive potential

FEEDINGSITE

FEEDINGSITE

NESTINGSITE

post-nesting migration

pre-nesting migration

foraging migration

energy intake

energy expenditure

energy threshold

pre-nesting migration

post-nestingmigrationnesting

foragingmigration

foraging

minimal energy for pre-nesting

foraging

food qualitythreshold

Fig. 1 : Map of the Soutwest Indian Ocean.

Fig. 2 : Individual energy budget cycle.

Fig. 3 : Spatial cycle of adult femaleFig. 5 : Model outputs

Fig. 5 : Model interface