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Climatically driven fluctuations in Southern Ocean ecosystems.

Murphy EJ, Trathan PN, Watkins JL, Reid K, Meredith MP, Forcada J, Thorpe SE, Johnston NM, Rothery P - Proc. Biol. Sci. (2007)

Bottom Line: This oceanographically driven variation in krill population dynamics and abundance in turn affects the breeding success of seabird and marine mammal predators that depend on krill as food.Such propagating anomalies, mediated through physical and trophic interactions, are likely to be an important component of variation in ocean ecosystems and affect responses to longer term change.Population models derived on the basis of these oceanic fluctuations indicate that plausible rates of regional warming of 1oC over the next 100 years could lead to more than a 95% reduction in the biomass and abundance of krill across the Scotia Sea by the end of the century.

View Article: PubMed Central - PubMed

Affiliation: British Antarctic Survey, Natural Environment Research Council, High Cross, Madingley Road, Cambridge, Cambridgeshire CB3 0ET, UK. e.murphy@bas.ac.uk

ABSTRACT
Determining how climate fluctuations affect ocean ecosystems requires an understanding of how biological and physical processes interact across a wide range of scales. Here we examine the role of physical and biological processes in generating fluctuations in the ecosystem around South Georgia in the South Atlantic sector of the Southern Ocean. Anomalies in sea surface temperature (SST) in the South Pacific sector of the Southern Ocean have previously been shown to be generated through atmospheric teleconnections with El Niño Southern Oscillation (ENSO)-related processes. These SST anomalies are propagated via the Antarctic Circumpolar Current into the South Atlantic (on time scales of more than 1 year), where ENSO and Southern Annular Mode-related atmospheric processes have a direct influence on short (less than six months) time scales. We find that across the South Atlantic sector, these changes in SST, and related fluctuations in winter sea ice extent, affect the recruitment and dispersal of Antarctic krill. This oceanographically driven variation in krill population dynamics and abundance in turn affects the breeding success of seabird and marine mammal predators that depend on krill as food. Such propagating anomalies, mediated through physical and trophic interactions, are likely to be an important component of variation in ocean ecosystems and affect responses to longer term change. Population models derived on the basis of these oceanic fluctuations indicate that plausible rates of regional warming of 1oC over the next 100 years could lead to more than a 95% reduction in the biomass and abundance of krill across the Scotia Sea by the end of the century.

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Correlations of anomalies of remotely sensed sea surface temperature (SST) with the SST anomaly variation at South Georgia (35.5°W, 53.5°S). Correlations at (a) 0-, (b) 12-, (c) 24- and (d) 36-month lags. The bar shows the correlation (r) colour scale. CIs (95%) calculated to take account of autocorrelation (Trenberth 1984) were from 0.33 to 0.35 between the ENSO region and the South Georgia series, 0.28 to 0.3 between the South Georgia series and the South Atlantic and southeast Pacific sectors and approximately 0.25 in the southwest Pacific sector. (e) The South Atlantic sector in detail and the approximate position of the major ocean fronts. SAF, Sub-Antarctic Front; PF, Polar Front; SACCF, Southern Antarctic Circumpolar Current Front; SB, Southern Boundary of the Antarctic Circumpolar Current. (a–d) Correlations of a time series of remotely sensed SST near South Georgia with correlations from all other areas in the world ocean. (a) is for zero lag, i.e. the instantaneous correlation. Note the region of high correlation around South Georgia, showing the spatial scale of the coherent oceanic anomalies. Note also the significant correlations with SST in the equatorial Pacific, indicative of the direct connection with the ENSO region. The Pacific–South American teleconnection pattern (alternating positive and negative anomalies extending to high latitudes in the Pacific) is clearly visible. (b–d) are with progressive yearly lags, and essentially track the anomalies back through time from the region around South Georgia ‘upstream’ into the Pacific. Twelve months before anomalies reach South Georgia, they occupy the southeast Pacific west of Drake Passage, the central South Pacific 24 months earlier and the area in the western South Pacific 36 months earlier.
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fig1: Correlations of anomalies of remotely sensed sea surface temperature (SST) with the SST anomaly variation at South Georgia (35.5°W, 53.5°S). Correlations at (a) 0-, (b) 12-, (c) 24- and (d) 36-month lags. The bar shows the correlation (r) colour scale. CIs (95%) calculated to take account of autocorrelation (Trenberth 1984) were from 0.33 to 0.35 between the ENSO region and the South Georgia series, 0.28 to 0.3 between the South Georgia series and the South Atlantic and southeast Pacific sectors and approximately 0.25 in the southwest Pacific sector. (e) The South Atlantic sector in detail and the approximate position of the major ocean fronts. SAF, Sub-Antarctic Front; PF, Polar Front; SACCF, Southern Antarctic Circumpolar Current Front; SB, Southern Boundary of the Antarctic Circumpolar Current. (a–d) Correlations of a time series of remotely sensed SST near South Georgia with correlations from all other areas in the world ocean. (a) is for zero lag, i.e. the instantaneous correlation. Note the region of high correlation around South Georgia, showing the spatial scale of the coherent oceanic anomalies. Note also the significant correlations with SST in the equatorial Pacific, indicative of the direct connection with the ENSO region. The Pacific–South American teleconnection pattern (alternating positive and negative anomalies extending to high latitudes in the Pacific) is clearly visible. (b–d) are with progressive yearly lags, and essentially track the anomalies back through time from the region around South Georgia ‘upstream’ into the Pacific. Twelve months before anomalies reach South Georgia, they occupy the southeast Pacific west of Drake Passage, the central South Pacific 24 months earlier and the area in the western South Pacific 36 months earlier.

Mentions: Signals of ENSO variability in the tropical Pacific are known to propagate to high latitudes through atmospheric teleconnection and oceanic processes (Kwok & Comiso 2002; Liu et al. 2002, 2004; White et al. 2002; Meredith et al. 2004, 2005, in press; Turner 2004). Over recent decades, ENSO-related variation throughout the South Pacific and Atlantic regions has been quasi-cyclic, with the periodicity varying approximately between 4 and 6 years, but with marked variation in anomaly intensity and duration on decadal and longer time scales (White & Peterson 1996; Trathan & Murphy 2002; Carleton 2003; Turner 2004). Southern Ocean atmosphere, ocean and sea ice systems are strongly coupled showing marked variation on time scales ranging from years to decades and between regions (Carleton 2003; Turner 2004). Spatial correlation analysis of the global SST anomaly field with variations at South Georgia in the South Atlantic reveals a wave-like progression (figure 1). As the anomalies propagate across the South Pacific and into the South Atlantic sectors, they are correlated with the changing phases of ENSO in the equatorial region of the Pacific. Changes in atmospheric circulation patterns across the southwest Pacific associated with ENSO variation provide a mechanism for the generation of SST anomalies in the Pacific sector of the Southern Ocean (Li 2000; White et al. 2002; Turner 2004). The propagating signal shows consistent correlations (r>0.5: 95% significance level for r is between approximately 0.25 and 0.33) meridionally across the Antarctic Circumpolar Current (ACC) and over more than 3000 km east–west (figure 1).


Climatically driven fluctuations in Southern Ocean ecosystems.

Murphy EJ, Trathan PN, Watkins JL, Reid K, Meredith MP, Forcada J, Thorpe SE, Johnston NM, Rothery P - Proc. Biol. Sci. (2007)

Correlations of anomalies of remotely sensed sea surface temperature (SST) with the SST anomaly variation at South Georgia (35.5°W, 53.5°S). Correlations at (a) 0-, (b) 12-, (c) 24- and (d) 36-month lags. The bar shows the correlation (r) colour scale. CIs (95%) calculated to take account of autocorrelation (Trenberth 1984) were from 0.33 to 0.35 between the ENSO region and the South Georgia series, 0.28 to 0.3 between the South Georgia series and the South Atlantic and southeast Pacific sectors and approximately 0.25 in the southwest Pacific sector. (e) The South Atlantic sector in detail and the approximate position of the major ocean fronts. SAF, Sub-Antarctic Front; PF, Polar Front; SACCF, Southern Antarctic Circumpolar Current Front; SB, Southern Boundary of the Antarctic Circumpolar Current. (a–d) Correlations of a time series of remotely sensed SST near South Georgia with correlations from all other areas in the world ocean. (a) is for zero lag, i.e. the instantaneous correlation. Note the region of high correlation around South Georgia, showing the spatial scale of the coherent oceanic anomalies. Note also the significant correlations with SST in the equatorial Pacific, indicative of the direct connection with the ENSO region. The Pacific–South American teleconnection pattern (alternating positive and negative anomalies extending to high latitudes in the Pacific) is clearly visible. (b–d) are with progressive yearly lags, and essentially track the anomalies back through time from the region around South Georgia ‘upstream’ into the Pacific. Twelve months before anomalies reach South Georgia, they occupy the southeast Pacific west of Drake Passage, the central South Pacific 24 months earlier and the area in the western South Pacific 36 months earlier.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2211519&req=5

fig1: Correlations of anomalies of remotely sensed sea surface temperature (SST) with the SST anomaly variation at South Georgia (35.5°W, 53.5°S). Correlations at (a) 0-, (b) 12-, (c) 24- and (d) 36-month lags. The bar shows the correlation (r) colour scale. CIs (95%) calculated to take account of autocorrelation (Trenberth 1984) were from 0.33 to 0.35 between the ENSO region and the South Georgia series, 0.28 to 0.3 between the South Georgia series and the South Atlantic and southeast Pacific sectors and approximately 0.25 in the southwest Pacific sector. (e) The South Atlantic sector in detail and the approximate position of the major ocean fronts. SAF, Sub-Antarctic Front; PF, Polar Front; SACCF, Southern Antarctic Circumpolar Current Front; SB, Southern Boundary of the Antarctic Circumpolar Current. (a–d) Correlations of a time series of remotely sensed SST near South Georgia with correlations from all other areas in the world ocean. (a) is for zero lag, i.e. the instantaneous correlation. Note the region of high correlation around South Georgia, showing the spatial scale of the coherent oceanic anomalies. Note also the significant correlations with SST in the equatorial Pacific, indicative of the direct connection with the ENSO region. The Pacific–South American teleconnection pattern (alternating positive and negative anomalies extending to high latitudes in the Pacific) is clearly visible. (b–d) are with progressive yearly lags, and essentially track the anomalies back through time from the region around South Georgia ‘upstream’ into the Pacific. Twelve months before anomalies reach South Georgia, they occupy the southeast Pacific west of Drake Passage, the central South Pacific 24 months earlier and the area in the western South Pacific 36 months earlier.
Mentions: Signals of ENSO variability in the tropical Pacific are known to propagate to high latitudes through atmospheric teleconnection and oceanic processes (Kwok & Comiso 2002; Liu et al. 2002, 2004; White et al. 2002; Meredith et al. 2004, 2005, in press; Turner 2004). Over recent decades, ENSO-related variation throughout the South Pacific and Atlantic regions has been quasi-cyclic, with the periodicity varying approximately between 4 and 6 years, but with marked variation in anomaly intensity and duration on decadal and longer time scales (White & Peterson 1996; Trathan & Murphy 2002; Carleton 2003; Turner 2004). Southern Ocean atmosphere, ocean and sea ice systems are strongly coupled showing marked variation on time scales ranging from years to decades and between regions (Carleton 2003; Turner 2004). Spatial correlation analysis of the global SST anomaly field with variations at South Georgia in the South Atlantic reveals a wave-like progression (figure 1). As the anomalies propagate across the South Pacific and into the South Atlantic sectors, they are correlated with the changing phases of ENSO in the equatorial region of the Pacific. Changes in atmospheric circulation patterns across the southwest Pacific associated with ENSO variation provide a mechanism for the generation of SST anomalies in the Pacific sector of the Southern Ocean (Li 2000; White et al. 2002; Turner 2004). The propagating signal shows consistent correlations (r>0.5: 95% significance level for r is between approximately 0.25 and 0.33) meridionally across the Antarctic Circumpolar Current (ACC) and over more than 3000 km east–west (figure 1).

Bottom Line: This oceanographically driven variation in krill population dynamics and abundance in turn affects the breeding success of seabird and marine mammal predators that depend on krill as food.Such propagating anomalies, mediated through physical and trophic interactions, are likely to be an important component of variation in ocean ecosystems and affect responses to longer term change.Population models derived on the basis of these oceanic fluctuations indicate that plausible rates of regional warming of 1oC over the next 100 years could lead to more than a 95% reduction in the biomass and abundance of krill across the Scotia Sea by the end of the century.

View Article: PubMed Central - PubMed

Affiliation: British Antarctic Survey, Natural Environment Research Council, High Cross, Madingley Road, Cambridge, Cambridgeshire CB3 0ET, UK. e.murphy@bas.ac.uk

ABSTRACT
Determining how climate fluctuations affect ocean ecosystems requires an understanding of how biological and physical processes interact across a wide range of scales. Here we examine the role of physical and biological processes in generating fluctuations in the ecosystem around South Georgia in the South Atlantic sector of the Southern Ocean. Anomalies in sea surface temperature (SST) in the South Pacific sector of the Southern Ocean have previously been shown to be generated through atmospheric teleconnections with El Niño Southern Oscillation (ENSO)-related processes. These SST anomalies are propagated via the Antarctic Circumpolar Current into the South Atlantic (on time scales of more than 1 year), where ENSO and Southern Annular Mode-related atmospheric processes have a direct influence on short (less than six months) time scales. We find that across the South Atlantic sector, these changes in SST, and related fluctuations in winter sea ice extent, affect the recruitment and dispersal of Antarctic krill. This oceanographically driven variation in krill population dynamics and abundance in turn affects the breeding success of seabird and marine mammal predators that depend on krill as food. Such propagating anomalies, mediated through physical and trophic interactions, are likely to be an important component of variation in ocean ecosystems and affect responses to longer term change. Population models derived on the basis of these oceanic fluctuations indicate that plausible rates of regional warming of 1oC over the next 100 years could lead to more than a 95% reduction in the biomass and abundance of krill across the Scotia Sea by the end of the century.

Show MeSH
Related in: MedlinePlus