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... of a FAD float constructed of purse seine corks or a bamboo raft with additional corks added for flotation and underwater panels of netting attached to the float. Since 1999 (López, 2015), FADs may be equipped with satellite-linked echo-sounder buoys to allow easy location and remote determination of the presence and size of aggregations underneath them (López, 2015). Both types of DFADs (natural vs. man-made DFADs) have been defined and analysed in different oceans (Dagorn et al., 2013;Hall, 1998;Leroy et al., 2013). ...
... of a FAD float constructed of purse seine corks or a bamboo raft with additional corks added for flotation and underwater panels of netting attached to the float. Since 1999 (López, 2015), FADs may be equipped with satellite-linked echo-sounder buoys to allow easy location and remote determination of the presence and size of aggregations underneath them (López, 2015). Both types of DFADs (natural vs. man-made DFADs) have been defined and analysed in different oceans (Dagorn et al., 2013;Hall, 1998;Leroy et al., 2013). ...
... Thus, determining which factors can explain the diversity of the bycatch communities in purse seine fishing is of primary importance for appropriate management of the exploited resources and also for the conservation of the most vulnerable species. Up to now, most of the studies analysing the environmental preferences of pelagic tropical species have been based on catch data and effort of tuna fishing fleets, especially longline CPUE (Catch Per Unit of Effort) data, but very rarely on purse seine fishing (López, 2015;Montero et al., 2016) using observer data. Thus, a better understanding of the interactions between pelagic species and their environment must be developed to ensure the correct implementation of an Ecosystem-Based Fishery Management (EBFM) (Pikitch et al., 2004), before performing any conservation plan. ...
... In that sense, the GAM approach can contribute to understand the geographical and habitat preferences of these communities. The percentage of deviance explained by the models presented some similitudes with the work from (López 2015) about the distribution of the by-catch species in the Atlantic Ocean using similar environmental variables; however, the results and conclusions should be taken with caution, due to the low number of samples and coverage rate. ...
... The second most important variable was the chlorophyll content (18 days before). Fonteneau et al. (2008) found interesting relationships between chlorophyll-a peak levels 18 days before and free swimming tuna abundance in the Indian Ocean; however, these relationships have not been found yet in the Atlantic Ocean for tuna and non-tuna species (López 2015). In contrast, in this study we observed that diversity increase in water contents between 0 and 0, 5 mg/m 3 . ...
... In addition, the by-catch species can be aggregated to a FAD and thus, be attached to the movement of the FAD for a while (Fréon and Dagorn, 2000;Castro et al., 2002;Girard et al., 2004). However, as they are not always associated to the FAD, these species can leave the FAD when environmental conditions are not optimal (López, 2015). ...
By-catch species from tropical tuna purse seine fishery have been affected by fishery pressures since the last century; however, the habitat distribution and the climate change impacts on these species are poorly known. With the objective of predicting the potential suitable habitat for a shark (Carcharhinus falciformis) and a teleost (Canthidermis maculata) in the Indian, Atlantic and Eastern Pacific Oceans, a MaxEnt species distribution model (SDM) was developed using data collected by observers in tuna purse seiners. The relative percentage of contribution of some environmental variables (depth, sea surface temperature, salinity and primary production) and the potential impact of climate change on species habitat by the end of the century under the A2 scenario (scenario with average concentrations of carbon dioxide of 856 ppm by 2100) were also evaluated. Results showed that by-catch species can be correctly modeled using observed occurrence records and few environmental variables with SDM. Results from projected maps showed that the equatorial band and some coastal upwelling regions were the most suitable areas for both by-catch species in the three oceans in concordance with the main fishing grounds. Sea surface temperature was the most important environmental variable which contributed to explain the habitat distribution of the two species in the three oceans in general. Under climate change scenarios, the largest change in present habitat suitability is observed in the Atlantic Ocean (around 16% of the present habitat suitability area of C. falciformis and C. maculata, respectively) whereas the change is less in the Pacific (around 10 and 8%) and Indian Oceans (around 3 and 2%). In some regions such as Somalia, the Atlantic equatorial band or Peru's coastal upwelling areas, these species could lose potential habitat whereas in the south of the equator in the Indian Ocean, the Benguela System and in the Pacific coast of Central America, they could gain suitable habitat as consequence of global warming. This work presents new information about the present and future habitat distribution under climate change of both by-catch species which can contributes to the development of ecosystem-based fishery management and spatially driven management measures.
The spatial-temporal environmental preferences and biomass aggregation of tropical tuna from purse seine fishery in the Mozambique Channel (MZC) have barely been investigated. In this study, tuna biomass volume from Fish Aggregating Devices (FADs) and Free-Swimming Schools (FSC), collected by Spanish fishing logbooks during 2003–2013, were modelled separately as a function of a set of oceanographic variables (sea surface temperature, sea surface height, geostrophic currents, salinity, and chlorophyll-a) using Generalized Additive Models (GAMs). Temporal variables (natural day, month and year), and spatial variables (latitude and longitude) were included in the models to account for the spatio-temporal structure of dynamic biomass of tropical tuna volume gathering. Oceanographic, temporal and spatial effects on aggregated catches differed between fishing modes, even though some common aspects appeared along the area and the period of study. Fishable patches of tuna biomass accumulation were explained by sea surface temperature, productivity, sea surface height, geostrophic currents, and apart from the spatio-temporal variables interactions. Although the models predicted slight differences for tuna fishing spots preferences, both fishing modes partially overlapped. Goodness of fit for selected variables showed that models were able to predict tuna catches assembled patterns in the MZC reasonably well. These results highlight a connection between the biophysical state of the oceans and purse seine tuna catches in the MZC, and ultimately may contribute to the scientific advice for the appropriate management and conservation of the exploited resources by purse seine fleets in the area of MZC.
