This was set according to the number of days in a lunar month (i.e. irrespective of the original length, the data set for each sampled time was reduced to 4 weeks covering from new moon to new moon). Satellite pictures and underwater photos were used to select the areas in the bay representing the different habitats i.e., mangroves, seagrasses and corals. The three selected areas representing mangroves, seagrasses and corals were about the same size (≈7 km2) (Fig. 1). The delimitation of the different fishing grounds in the bay was also mapped in parallel

studies (Bergstén, 2004 and Hammar, 2005); all fishing grounds reported by fishers that were among the selected areas were considered in the analysis. From all information obtained in the market data collection sheets the following was selected and/or computed for further statistical analysis: CPUE (catch Epacadostat in vivo per unit effort) was similar for all boats since the fishers use the tidal circulation to facilitate navigation, this was about 6 h at the sea

which is equivalent to one fishing trip. Boat type correlated with gear used and was ruled out for further analysis and bait was not considered since it was not recorded for all gears known to use bait. The rest of the variables were used further (see below). Descriptive statistics were used to illustrate the main fishing features DOK2 in each habitat (number of fishers harvesting in each habitat, fish catch weight, Pexidartinib cost economic value of the fish catch, fishing pressure and dominating gears) (Table 1). The spatial distribution of the fishers in the different habitats was determined by counting the number of fishing trips done to the different selected areas i.e. mangroves, seagrasses and corals (Fig. 2). Total catches (fish fresh weight) and total economic value (fish price in the auction) for each habitat and sampled time (season) were computed. Since the data distribution was skewed for fish biomass (kg1 fisher−1 day−1) and income (TZS1 fisher−1 day−1) per capita median values, and minimum and maximum

were calculated in addition to the mean and standard deviation to gain an accurate picture of the fishery situation. The data was graphically illustrated using boxplots (Fig. 3 and Fig. 4). Two boxplot graphs were created to visualize the variation in fish biomass (kg1 fisher−1 day−1) and income (TZS1 fisher−1 day−1) for all different gears, habitats and seasons. Through the graphs data dispersion for each gear, habitat and time was obtained (IQR = Interquantile range = size of the box), together with median, minimum value, maximum observation (below upper fence), and points falling outside the maximum observation (see Appendix II, Supplementary Information, for interpretation of the boxplots used in this study).