Updated analysis of flatfish recruitment response to climate variability and ocean conditions in the Eastern Bering Sea

Abstract This study provides a retrospective analysis of the relationship between physical oceanography, biology and recruitment of three Eastern Bering Sea flatfish stocks: flathead sole ( Hippoglossoides elassodon ), northern rock sole ( Lepidopsetta polyxystra ), and arrowtooth flounder ( Atheresthes stomias ) during the period 1978–2005. Stock assessment model estimates of recruitment and spawning stock size indicate that temporal patterns in productivity are consistent with decadal scale (or shorter) patterns in climate variability, which may influence marine survival during the early life history phases. Density-dependence (through spawning stock size) was statistically significant in a Ricker stock-recruit model of flatfish recruitment that included environmental terms. Wind-driven advection of northern rock sole and flathead sole larvae to favorable nursery grounds was found to coincide with years of above-average recruitment. Ocean forcing of Bristol Bay surface waters during springtime was mostly on-shelf (eastward) during the 1980s and again in the early 2000s, but was off-shelf (westerly) during the 1990s, corresponding with periods of good and poor recruitment, respectively. Finally, the Arctic Oscillation was found to be an important indicator of arrowtooth flounder productivity. Model results were applied to IPCC (Intergovernmental Panel on Climate Change) future springtime wind scenarios to predict the future impact of climate on northern rock sole productivity and indicated that a moderate future increase in recruitment might be expected because the climate trends favor on-shelf transport but that density-dependence will dampen this effect such that northern rock sole abundance will not be substantially affected by climate change.

[1]  G. Hunt,et al.  Increases in jellyfish biomass in the Bering Sea: implications for the ecosystem , 2002 .

[2]  A. Rijnsdorp,et al.  Recruitment in flatfish, with special emphasis on North Atlantic species: progress made by the Flatfish Symposia , 2000 .

[3]  C. Symon,et al.  Arctic climate impact assessment , 2005 .

[4]  Emanuele Di Lorenzo,et al.  Long-term forecast of oceanic conditions off California and their biological implications , 2006 .

[5]  Christian Möllmann,et al.  Resolving the effect of climate change on fish populations , 2009 .

[6]  L. Terray,et al.  A multi-model ensemble approach for assessment of climate change impact on surface winds in France , 2009 .

[7]  N. Bond,et al.  On the temporal variability of the physical environment over the south-eastern Bering Sea , 2001 .

[8]  James N. Ianelli,et al.  Expected declines in recruitment of walleye pollock (Theragra chalcogramma) in the eastern Bering Sea under future climate change , 2011 .

[9]  S. Schneider,et al.  Climate Change 2007 Synthesis report , 2008 .

[10]  David R. Anderson,et al.  Model selection and multimodel inference : a practical information-theoretic approach , 2003 .

[11]  R. Rosso,et al.  Wind control of storm‐triggered shallow landslides , 2007 .

[12]  P. Stabeno,et al.  Climate change and the control of energy flow in the southeastern Bering Sea , 2002 .

[13]  Gordon H. Kruse,et al.  Recruitment patterns of Alaskan crabs in relation to decadal shifts in climate and physical oceanography , 2000 .

[14]  R. Beamish,et al.  Effects of ocean variability on recruitment and an evaluation of parameters used in stock assessment models , 2004, Reviews in Fish Biology and Fisheries.

[15]  H. Akaike,et al.  Information Theory and an Extension of the Maximum Likelihood Principle , 1973 .

[16]  N. Bond,et al.  Decadal Variability of the Aleutian Low and Its Relation to High-Latitude Circulation* , 1999 .

[17]  James N. Ianelli,et al.  Evaluating management strategies for eastern Bering Sea walleye pollock (Theragra chalcogramma) in a changing environment , 2011 .

[18]  Jason S. Link,et al.  Changing spatial distribution of fish stocks in relation to climate and population size on the Northeast United States continental shelf , 2009 .

[19]  P. Sullivan,et al.  Decadal changes in growth and recruitment of Pacific halibut (Hippoglossus stenolepis) , 1999 .

[20]  C. Zhang,et al.  The effect of seasonal anomalies of seawater temperature and salinity on the fluctuation in yields of small yellow croaker, Pseudosciaena polyactis, in the Yellow Sea , 1997 .

[21]  M. Peck,et al.  Effects of climate change on fish and fisheries: forecasting impacts, assessing ecosystem responses, and evaluating management strategies , 2011 .

[22]  N. Bond,et al.  Larval fish abundance and physical forcing in the Gulf of Alaska, 1981–2003 , 2009 .

[23]  B. Norcross,et al.  Comparison of models for defining nearshore flatfish nursery areas in Alaskan waters , 1999 .

[24]  N. Bond,et al.  Rise and fall of jellyfish in the eastern Bering Sea in relation to climate regime shifts , 2008 .

[25]  Muyin Wang,et al.  The Arctic climate paradox: The recent decrease of the Arctic Oscillation , 2005 .

[26]  M. Alcaraz,et al.  Bakun, A. - 1996. Patterns in the Ocean. Ocean processes and marine population dynamics , 1997 .

[27]  Steven R. Hare,et al.  Effects of interdecadal climate variability on the oceanic ecosystems of the NE Pacific , 1998 .

[28]  G. Kruse,et al.  Relationship Between Wind and Year Class Strength of Tanner crabs in the Southeastern Bering Sea , 1998 .

[29]  R. Gibson Behaviour and the distribution of flatfishes , 1997 .

[30]  D. Cushing Marine ecology and fisheries , 1975, Environmental Biology of Fishes.

[31]  H. Akaike Likelihood of a model and information criteria , 1981 .

[32]  G. E. Walters,et al.  Flatfish recruitment response to decadal climatic variability and ocean conditions in the eastern Bering Sea , 2002 .

[33]  P. Spencer Density-independent and density-dependent factors affecting temporal changes in spatial distributions of eastern Bering Sea flatfish , 2008 .

[34]  Nicholas A. Bond,et al.  A framework for modelling fish and shellfish responses to future climate change , 2009 .

[35]  David R. Anderson,et al.  Multimodel Inference , 2004 .