Implementation of a multiple indicator system for fisheries with limited information in a context of co-management, case study: Spiny lobster fishery in the Galapagos Marine Reserve

2018 ◽  
Vol 154 ◽  
pp. 20-25 ◽  
Author(s):  
Jorge Ramírez-González ◽  
Gonzalo Banda-Cruz ◽  
Jerson Moreno ◽  
Dan Ovando ◽  
Harry Reyes ◽  
...  
PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7278 ◽  
Author(s):  
Juan Carlos Murillo-Posada ◽  
Silvia Salas ◽  
Iván Velázquez-Abunader

Management of low-mobility or benthic fisheries is a difficult task because variation in the spatial distribution and population dynamics of the resources make the monitoring and assessment of these fisheries challenging. We assumed that environmental, spatial, and temporal factors can contribute to the variability of the relative abundance of such species; we used Generalized Additive Models for Location Scale and Shape (GAMLSS) to test this hypothesis using as a case study the lobster fishery (targeting two species) in the Galapagos Marine Reserve, Ecuador. We gathered data on each of the two species of lobster on a monthly basis over seven years, including: (a) onboard observers’ records of catch data, fishing effort, and ground location by trip, and (b) data from interviews undertaken with fishers at their arrival to port, recording the same type of information as obtained from onboard observers. We use this information to analyze the effect of the measured variables and to standardize the Catch per Unit Effort (CPUE) in each case, using the GAMLSS. For both species, the temperature, region, fishing schedule, month, distance, and the monitoring system were significant variables of the selected models associated with the variability of the catch rate. ForPanulirus penicillatus, CPUE was higher at night than during the day, and forPanulirus gracilisit was higher during the day. Increased temperature resulted in a decrease of CPUE values. It was evident that temporal, spatial scales and monitoring system can influence the variability of this indicator. We contend that the identification of drivers of change of relative abundance in low-mobility species can help to support the development of monitoring and assessment programs for this type of fisheries.


Marine Policy ◽  
2018 ◽  
Vol 88 ◽  
pp. 204-212 ◽  
Author(s):  
Salomé Buglass ◽  
Harry Reyes ◽  
Jorge Ramirez-González ◽  
Tyler D. Eddy ◽  
Pelayo Salinas-de-León ◽  
...  

2016 ◽  
Vol 177 ◽  
pp. 82-94 ◽  
Author(s):  
Cody S. Szuwalski ◽  
Mauricio Castrejon ◽  
Dan Ovando ◽  
Brandon Chasco

2020 ◽  
Vol 243 ◽  
pp. 106629
Author(s):  
Etienne Rastoin-Laplane ◽  
Jordan Goetze ◽  
Euan S. Harvey ◽  
David Acuña-Marrero ◽  
Pierre Fernique ◽  
...  

2008 ◽  
Vol 33 (1-2) ◽  
pp. 13-21 ◽  
Author(s):  
Benjamin M. Liu ◽  
Yitayew Abebe ◽  
Oloro V. McHugh ◽  
Amy S. Collick ◽  
Brhane Gebrekidan ◽  
...  

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Elisa Bonaccorso ◽  
Nicté Ordóñez-Garza ◽  
Diana A. Pazmiño ◽  
Alex Hearn ◽  
Diego Páez-Rosas ◽  
...  

AbstractShark fishing, driven by the fin trade, is the primary cause of global shark population declines. Here, we present a case study that exemplifies how industrial fisheries are likely depleting shark populations in the Eastern Tropical Pacific Ocean. In August 2017, the vessel Fu Yuan Yu Leng 999, of Chinese flag, was detained while crossing through the Galápagos Marine Reserve without authorization. This vessel contained 7639 sharks, representing one of the largest seizures recorded to date. Based on a sample of 929 individuals (12%), we found 12 shark species: 9 considered as Vulnerable or higher risk by the IUCN and 8 listed in CITES. Four species showed a higher proportion of immature than mature individuals, whereas size-distribution hints that at least some of the fishing ships associated with the operation may have been using purse-seine gear fishing equipment, which, for some species, goes against international conventions. Our data expose the magnitude of the threat that fishing industries and illegal trade represent to sharks in the Eastern Tropical Pacific Ocean.


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