Habitat mapping of the Atlantic bluefin tuna derived from satellite data: Its potential as a tool for the sustainable management of pelagic fisheries
Introduction
Bluefin tuna (BFT) populations (Atlantic, Pacific and southern species) have declined alarmingly over the past few decades mainly driven by the demand for sushi and sashimi. The largest stock of adults which spawn in the Mediterranean Sea is now (2006) at its lowest on record, ca. 40% of late 1950s’ biomasses [1], [2]. Both East and West Atlantic populations are classified as critically endangered (IUCN1 criterion) due to overfishing among which more than 1/3rd is illegal, undeclared or unreported (IUU, [1]). This fishery has most of the criterion for which the benefits of IUU fishing are a driver [3]: a high price, a high potential catch and catch by unit effort (up to 350 Mt in one day) and a high cost of fishing. The keystone of European Union Common Fisheries Policy (EU-CFP) is the control and enforcement in order to encourage compliance, deter fraud and ensure sustainable fishing. With many critical of the efficiency of the existing policy, the CFP has been and will further be reformed to better fight IUU fishing. The actual management measures put in place by the inter-governmental fishery organization responsible for the BFT conservation—the International Commission for the Conservation of Atlantic Tunas (ICCAT), are fishery closure, quotas, a minimum catch size and the prohibition of fish-spotting using airplanes.
This paper presents an innovative approach using earth observation data to locate the BFT habitat and guide the fishery management towards restricted grounds to (a) concentrate the fishing fleet for increasing the efficiency of control operations at sea and (b) better distribute the catches taking into consideration regional stock levels. Furthermore the habitat mapping will allow improving the scientific knowledge on BFT particularly related to migration patterns and triggers (not detailed herein).
Section snippets
The BFT habitat mapping
Two main behaviours are recognized in most fish: feeding and spawning. The corresponding habitats are generally separated as they correspond to distinct biological requirements and avoid the top predator's prey feeds on the top predator's larvae. Night Sea Surface Temperature (SST) and surface chlorophyll content from MODIS-Aqua sensor (NASA) have been used to compute daily habitats since July 2002. A horizontal resolution of 4.6 km is appropriate to describe the habitat since BFT can cover more
BFT behaviour and fishing effort
Purse seine nets are currently responsible for 60–80% of the bluefin tuna catch in the Mediterranean Sea. BFT fishery are guided by the occurrence of favourable spawning conditions for catching vulnerable-near surface shoals of large individuals to meet the demands of the Japanese market. Spawning of BFT occurs in the Mediterranean Sea from May to July where calm weather conditions create the surface mixed-layer. It generally occurs first in the eastern Mediterranean Sea in May and spreads
Discussion
In order to evaluate the performance of this management and control plan, a quantitative analysis of the benefits for the resource, for control authorities and for fishers was performed for both scenarios.
The processing of the 2003–2008 satellite data reveals that the reproductive habitat covers approximately 5% of the (cloud-free) Mediterranean Sea surface during the spawning season. The April to September mean coverage of the feeding habitat is approximately 9%. Comparatively, it was
Conclusion
The habitat-guided management and control of BFT fishery in the Mediterranean Sea offer a high degree of flexibility for adapting the level of fishing effort to regional stock size and for improving the efficiency of control operations by imposing or proposing restricted fishing grounds where a map of favourable habitat is delivered. The habitat mapping is likely to increase at least five-fold the encounter rate between fish and fishers. It would increase several folds the concentration of the
Acknowledgements
I wish to thank Jean-Marc Fromentin (IFREMER) for the constructive discussions, together with Maris Stulgis (EC-DG MARE) and John Anderson (JRC) for their valuable suggestions. The author thanks particularly the Ocean Biology Processing Group (Code 614.2) at the GSFC, Greenbelt, MD 20771, for the efficient production and distribution of ocean colour and sea surface temperature data.
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