Fig 1.
Study area of the fishery community (Baía Formosa) on the Brazilian northeast coast.
Fig 2.
Interviewing methodology: Steps for interviewing methodology applied to register fisher knowledge aiming to select expert fishers and to fill the gaps in the scientific data needed for modeling.
Fig 3.
Modeling of trophic network by Ecopath with Ecosim for the fishing habitat of Baía Formosa (Brazil).
(A) Fisher knowledge model and (B) science-data model as input parameters. Black square: keystone groups.
Table 1.
Basic input for the EwE to the FK model and SC model.
B = biomass (wet weight–t*km-2); P/B = production/biomass (year-1); Q/B = consumption/biomass (year -1); EE = ecotrophic efficiency. Species aggregation in each compartment. FK model = fishers’ knowledge model; SC model = science-data model.
Table 2.
Average values of fishers’ knowledge for the maximum (Wmax) and modal (Wmodal) sizes, and amount of food required per biomass per year.
The weight-length relationships were used to estimate the length (L∞) from the related maximum weight. The values in the brackets refer to the standard deviation.
Table 3.
Trophic level, omnivory index, and keystone index position obtained by the FK and SC models.
The values did not differ between the models for the trophic levels (p = 0.92) and omnivory index (p = 0.15).
Table 4.
The parameters of the FK model and SC model to the fishing system modeled using EwE.