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214L. F. D. FARACO ET ALLIand ecological, and internal or external to the system(Füssel 2007).Vulnerability should always be measured inrelation to specific environmental hazards, whichcan vary according to the specific characteristics ofthe setting under consideration. For the coastalpopulations and environments of our case study, wedefined three expected effects of climate change asthe main threats: relative sea-level rise, an increasein the frequency and intensity of extreme climaticevents, and an increase in uncertainty and variabilityrelated to the availability of fishing resources.Exposure to these threats is mainly relatedwith the characteristics of the sites where villagesand mangroves are located, especially theirproximity to the sea and the topography and slope ofthe terrain. Thus, for the analysis of this element adigital elevation model (DEM) of the coastal areaneeds to be constructed. This can be accomplishedthrough the use of remote sensing, with a highresolutionsatellite image of the region, or, ideally,with LIDAR (Light Detection and Ranging) data(Gesch 2009).To improve the quality of the model, theupper boundary of mangrove forests should bedelimitated and considered as equivalent to the meanhigh tide in the region. The DEM can then beconstructed through interpolation of existingelevation data, considering this high tide line and thefirst topographic contour available in local maps (10meters in the case of the Brazilian coast). To furtherimprove the accuracy of the model, the interpolationcan be fed with a series of elevation data pointsestablished along the margins of the estuary, in thearea between the sea and the first topographiccontour.This digital elevation model, even if notaccurate enough to produce detailed scenarios ofareas prone to future flooding, especially if LIDARdata is not available, will allow a classification ofthe coastline in categories representing differentlevels of exposure to sea-level rise and flooding. Themain goal is to identify the location and topographyof mangroves and villages and the land-use patternsin the low-lying areas, up to 10 meters above sealevel.This focus on topography and on the existenceof barriers to mangrove migration is justified by thelack of consistent data on local and regional sealevelrise. In this case, the analyzed factors work assurrogates or indirect indicators of this dynamics,producing information about the response of theseecosystems to climate change (Gilman et al. 2007).The last component of exposure to be measured isthe magnitude and frequency of occurrence ofextreme climatic events. Information on these eventscan be obtained both from meteorological andhistorical records and from interviews with localinhabitants. We suggest as a proxy for this themeasurement of the number of fishing days lost dueto bad weather conditions.For the analysis of exposure, we can alreadyidentify opposite effects on the social and naturalsubsystems. A gentle slope means a higher exposureto sea-level rise and storm surges, increasing thevulnerability of villages, considering that the flatterthe land the larger the area that would be flooded.But, for mangroves, a gentle slope in adjacentlandward areas means that they have available spaceto migrate towards the continent, although land-usepatterns may create barriers to this migration. In ourspecific setting, this spatial analysis of land adjacentto mangroves will also evaluate the situation of localfishing villages regarding their sensitivity to meansea-level rise and the impacts of protected areaswhich exclude human occupation. In this case, thefactor that will be analyzed is “coastal squeeze”, thatis, if a rise in sea-level will put pressure on humanoccupations and if these will be able to respond.Many villages in this region are placed between theocean and the PAs, being susceptible to coastalsqueeze if sea level rises.Still regarding sensitivity, which relates toeffects that hazards can have on the systems, thegeneral housing, health and food conditions ofhuman populations should be measured, togetherwith their dependency on climate-influencedresources (such as fish). For this, we propose, basedon the Livelihood Vulnerability Index methodology(Hahn et al. 2009), to focus on water and foodsources and storage capacity, the percentage ofhousehold members that lost work or school daysdue to health problems, and the distance to theclosest health service (Table I). For mangroves,mapping of the total area occupied by the ecosystemand the forest types potentially affected areindicators of this component.Following this analysis of exposure andsensitivity, some villages, and the mangrovesassociated to them, identified as potentially highlyvulnerable, can be chosen for a more detailedevaluation of factors affecting their adaptivecapacity. That is, besides exposure and sensitivity tobiophysical risk, the other main component ofvulnerability will be analyzed: the capacity of thesepopulations and ecosystems to cope and adapt tochange, the factors that contribute to it, and, in ourspecific case, how the existence of no-take PAsaffects these factors.This analysis of adaptive capacity can bedivided in two steps. The first one focuses on currentPan-American Journal of Aquatic Sciences (2010), 5(2): 205-223