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Variation in the distribution of ocean shrimp ( Pandalus jordani ) recruits: links with coastal upwelling and climate change
Author(s) -
HANNAH ROBERT W.
Publication year - 2011
Publication title -
fisheries oceanography
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.016
H-Index - 80
eISSN - 1365-2419
pISSN - 1054-6006
DOI - 10.1111/j.1365-2419.2011.00585.x
Subject(s) - upwelling , oceanography , shrimp , sea surface temperature , geology , climatology , environmental science , fishery , biology
In this analysis, an atypical northward shift in the distribution of age‐1 ocean shrimp ( Pandalus jordani ) recruits off Oregon in 2000 and 2002–2004 was linked to anomolously strong coastal upwelling winds off southern Oregon (42°N latitude) in April–July of the year of larval release ( t −1). This is the first clear evidence that strong upwelling winds can depress local recruitment of ocean shrimp. Regression analysis confirmed a long‐term negative correlation between log e of ocean shrimp recruitment and April sea level height (SLH) at Crescent City, California, in the year of larval release, for both northern and southern Oregon waters. The regional pattern of ocean shrimp catches and seasonal upwelling winds showed that, although the timing of the spring transition as reflected in April SLH drives ocean shrimp recruitment success off Oregon generally, the strength and consistency of spring upwelling limits the distribution of large concentrations of ocean shrimp at the southern end of the northern California/Oregon/Washington area. A northward shift in 1999 and 2001–03 in the northern edge of this ‘zone of maximum upwelling’ is the likely cause of the weak southern Oregon recruitment and resulting atypical distribution of ocean shrimp observed off Oregon in 2000 and 2002–04, with a return to a more typical catch distribution as spring upwelling moderated in subsequent years. It is noted that a northward shift in the conditions that produce strong and steady spring upwelling winds is consistent with many predictions of global climate models under conditions of global warming.

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