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SEABIRD ECOLOGY, EL NIñO ANOMALIES, AND PREDICTION OF SARDINE FISHERIES IN THE GULF OF CALIFORNIA
Author(s) -
Velarde Enriqueta,
Ezcurra Exequiel,
Cisneros-Mata Miguel A.,
LavÍn Miguel F.
Publication year - 2004
Publication title -
ecological applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.864
H-Index - 213
eISSN - 1939-5582
pISSN - 1051-0761
DOI - 10.1890/02-5320
Subject(s) - sardine , seabird , fishery , pelagic zone , overfishing , catch per unit effort , fishing , fisheries management , clupeidae , geography , apex predator , marine ecosystem , oceanography , ecology , trophic level , biology , ecosystem , predation , fish <actinopterygii> , geology
Small pelagic fish constitute 25–40% of the fisheries landings in Mexico. More than 70% of these landings, predominantly Pacific sardine ( Sardinops caeruleus ), are captured in the Gulf of California. Small pelagic fishes are a key component of the Gulf's ecosystem; they are eaten by seabirds, sea mammals, and other fishes. The sardine fishery within the Gulf has been showing signs of overfishing since the early 1990s. To contribute to the sustainable management of this fishery, we developed two statistical models that use oceanographic conditions and seabird breeding and feeding data to predict total fishery catch and catch per unit effort (CPUE) of Pacific sardine in the central Gulf. Total catch was predicted with an accuracy of 54% by a linear model incorporating the Southern Oscillation Index (SOI), the clutch size of Heermann's Gulls ( Larus heermanni ), and the proportion of sardine mass in the diet of Elegant Terns ( Sterna elegans ). CPUE was predicted with an accuracy of 73% by a model based on the proportion of sardines in the diet of Elegant Terns, the reproductive success of Heermann's Gulls, and the springtime sea surface temperature anomaly in the Gulf region. Our results show that the reproductive ecology of seabirds is coupled to the global and local oceanographic conditions and that this information can be used to predict in advance the outcome of fishing efforts. We propose the use of models of this kind to reduce the effort of the fleet in years when it can be anticipated that CPUE will be low.