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3.0 Conducting a Vulnerability AssessmentBiomass of the tree, plot and per hectare, can bedetermined by the use of allometric equations whichhave been derived experimentally from harvestingan area and by determining dry weight. There areequations available in the literature for mangrovetrees of different statures (Putz & Chan, 1986; Clough& Scott, 1989; Clough, 1992; Clough et al., 1997;Komiyama et al., 2008). This biomass conversion isnot required for a mangrove vulnerability assessment,but it demonstrates that these field data can be usedto assist with carbon sink calculations that may beuseful for mangrove REDD (Reducing Emissions fromDeforestation and Forest Degradation) or “wet carbon”projects.How to interpret vulnerabilityThe results of tree density, relative frequency, meanDBH, mean height, basal area and relative dominancecalculations can be interpreted by• comparison between plots across a transect• comparison from a transect at one site to atransect at another site• comparison over time, as shown in the case studybelow• comparison of results with published data frommangrove plot measurement that also uses thesestandard methods (Saenger & Snedaker, 1993;Devoe & Cole, 1998; Soares & Schaeffer-Novelli,2005; Krauss et al., 2006; Bouillon et al., 2008;Komiyama et al., 2008; Cavalcanti et al., 2009;Kauffman et al., 2011).Some mangrove forest structure data (Komiyamaet al., 2008; Cavalcanti et al., 2009; Kauffman et al.2011) reveal considerable differences in basal area perhectare across mangrove forests that reflect varyinglevels of human or natural disturbance impact.Although these studies were not designed to assessvulnerability as shown by basal area, they do includeuseful basal area data that are indicative of forestconditions. These have been compiled to produce ageneral indicator scale of forest condition (Table 8).From these studies, three levels of impact could bediscerned without over-extrapolating the data, andthe basal area for each show considerable differences,although statistical analysis was impeded by lack ofprimary data. The WWF pilot in the Douala Estuary,Cameroon, that focused on different scales of exploitedforest showed that this comparison is a useful way ofinterpreting forest condition. However, there will beSource Location What wasmeasuredKomiyama et al., 2008 Global, 54locationsBA m 2 per ha 25.3n=15Forest condition1 2 315.2n= 69.8n=4CommentsReview of other studiesCavalcanti et al., 2009Guanabara Bay,BrazilBA m 2 per hamean16.0±3.913.2±4.9Pellegrini 2000 & Chaves2001 in Cavalcanti et al.,2009Sepetiba Bay,BrazilBA m 2 per harange11.6-61.7Broad BA range attributed togood state of conservationbut strong human influencepersistingSoares 1999 inCavalcanti et al., 2009Tijuca Lagoon,BrazilBA m 2 per harange13.3–41.4Kauffman et al., 2011 Palau MeanBA m 2 per haacross zones34–43 Forest condition understoodto be near-pristineAjonina et al., 2011Yap 41–78Douala,CameroonBA m 2 per hamean31.1 10.3 3.9 WWF pilot site, CameroonTable 8. Compilation of basal area data relative to reported forest condition. Forest condition categories are:1: minimal impact with traditional use, good conservation, pristine or primary forest; 2: managed or having someconservation status, or secondary forest; 3: affected by natural or anthropogenic disturbance, or concession forest.24 | Climate Change Vulnerability Assessment and Adaptation Planning for Mangrove Systems
3.0 Conducting a Vulnerability AssessmentRank 1 2 3 4 5 SSensitivity factorsMangrove basal area (m 2 per hectare) >25 15–25 10–15 5–10
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4.0 Interpreting a Mangrove Vuneral
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5.0 Developing Adaptation MeasuresT
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6.0 ConclusionsClimate change, part
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7.0 ReferencesBosire, J. O., Dahdou
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7.0 ReferencesForbes, A. T., & Cyru
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7.0 ReferencesKovacs, J. M., Wang,
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7.0 ReferencesRogers, K., Saintilan
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8.0 GlossaryAbscission collar A reg
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8.0 GlossaryLiDAR Light Detection a
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Photo: Rob Anders
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Appendix: Data Sheets120 | Climate
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Appendix: Data SheetsData sheet for
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