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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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(a) Interannual changes in krill biomass (solid black line, in g m−2, with 95% CIs) at South Georgia (British Antarctic Survey data) and numerical abundance (Atkinson et al. 2004) in the southwest Atlantic sector (grey dashed line, in N m−2). (b) Interannual changes in mean krill length in the diet of Antarctic fur seals at South Georgia in March (black solid line); CIs (95%) are shown for the mean krill length in March, based on weekly samples (Reid et al. 1999). The dashed line shows the model-estimated changes where recruitment of post-larval krill is driven by a functional relationship based on the sea surface temperature (SST) anomaly 2 years previously and the grey line is based on anomalies 1 year previously. (c) Relationship between the abundance of krill in the South Atlantic and the biomass of krill at South Georgia. (d) Relationship between the mean krill length (in mm) in the diet of Antarctic fur seals at Bird Island, South Georgia (in March) and the biomass of krill at South Georgia. (e) Relationship between the mean krill length in the diet of Antarctic fur seals at Bird Island, South Georgia (in March) and SST anomalies in the South Georgia region 13 months earlier (n=14, adjusted n=12.5; r=−0.85, rs=−0.86, r12,0.05=0.55, rs12,0.05=0.59). (f) As given for (e) but for 23 months earlier (n=14, adjusted n=12.9; r=0.60, rs=0.60, r12,0.05=0.55, rs12,0.05=0.59). (g) Relationship between the number of Antarctic fur seal pups produced and the mean length of krill (in mm) in the diet of adult Antarctic fur seals at Bird Island, South Georgia. (h) Relationship between the Antarctic fur seal pup weaning mass and the biomass of krill at South Georgia.
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fig3: (a) Interannual changes in krill biomass (solid black line, in g m−2, with 95% CIs) at South Georgia (British Antarctic Survey data) and numerical abundance (Atkinson et al. 2004) in the southwest Atlantic sector (grey dashed line, in N m−2). (b) Interannual changes in mean krill length in the diet of Antarctic fur seals at South Georgia in March (black solid line); CIs (95%) are shown for the mean krill length in March, based on weekly samples (Reid et al. 1999). The dashed line shows the model-estimated changes where recruitment of post-larval krill is driven by a functional relationship based on the sea surface temperature (SST) anomaly 2 years previously and the grey line is based on anomalies 1 year previously. (c) Relationship between the abundance of krill in the South Atlantic and the biomass of krill at South Georgia. (d) Relationship between the mean krill length (in mm) in the diet of Antarctic fur seals at Bird Island, South Georgia (in March) and the biomass of krill at South Georgia. (e) Relationship between the mean krill length in the diet of Antarctic fur seals at Bird Island, South Georgia (in March) and SST anomalies in the South Georgia region 13 months earlier (n=14, adjusted n=12.5; r=−0.85, rs=−0.86, r12,0.05=0.55, rs12,0.05=0.59). (f) As given for (e) but for 23 months earlier (n=14, adjusted n=12.9; r=0.60, rs=0.60, r12,0.05=0.55, rs12,0.05=0.59). (g) Relationship between the number of Antarctic fur seal pups produced and the mean length of krill (in mm) in the diet of adult Antarctic fur seals at Bird Island, South Georgia. (h) Relationship between the Antarctic fur seal pup weaning mass and the biomass of krill at South Georgia.

Mentions: Having established that interannual variation in Scotia Sea SST and sea ice extent depends significantly upon external forcing, we next examined the impact of these fluctuations on the krill population. We compared krill abundance across the South Atlantic with krill biomass estimates from local surveys at South Georgia (figure 3a). Although these data series are short, the pattern of fluctuations shows a delay between a change in numbers and biomass which is consistent with current views of krill population dynamics (Murphy et al. 1998; Murphy & Reid 2001). Krill abundance across the South Atlantic sector was lowest when biomass was also low at South Georgia (figure 3c). These low biomass periods were also observed when krill length was most variable (figure 3d). Animals were more consistent in size (approx. 46–49 mm) during periods of higher biomass.


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)

(a) Interannual changes in krill biomass (solid black line, in g m−2, with 95% CIs) at South Georgia (British Antarctic Survey data) and numerical abundance (Atkinson et al. 2004) in the southwest Atlantic sector (grey dashed line, in N m−2). (b) Interannual changes in mean krill length in the diet of Antarctic fur seals at South Georgia in March (black solid line); CIs (95%) are shown for the mean krill length in March, based on weekly samples (Reid et al. 1999). The dashed line shows the model-estimated changes where recruitment of post-larval krill is driven by a functional relationship based on the sea surface temperature (SST) anomaly 2 years previously and the grey line is based on anomalies 1 year previously. (c) Relationship between the abundance of krill in the South Atlantic and the biomass of krill at South Georgia. (d) Relationship between the mean krill length (in mm) in the diet of Antarctic fur seals at Bird Island, South Georgia (in March) and the biomass of krill at South Georgia. (e) Relationship between the mean krill length in the diet of Antarctic fur seals at Bird Island, South Georgia (in March) and SST anomalies in the South Georgia region 13 months earlier (n=14, adjusted n=12.5; r=−0.85, rs=−0.86, r12,0.05=0.55, rs12,0.05=0.59). (f) As given for (e) but for 23 months earlier (n=14, adjusted n=12.9; r=0.60, rs=0.60, r12,0.05=0.55, rs12,0.05=0.59). (g) Relationship between the number of Antarctic fur seal pups produced and the mean length of krill (in mm) in the diet of adult Antarctic fur seals at Bird Island, South Georgia. (h) Relationship between the Antarctic fur seal pup weaning mass and the biomass of krill at South Georgia.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

fig3: (a) Interannual changes in krill biomass (solid black line, in g m−2, with 95% CIs) at South Georgia (British Antarctic Survey data) and numerical abundance (Atkinson et al. 2004) in the southwest Atlantic sector (grey dashed line, in N m−2). (b) Interannual changes in mean krill length in the diet of Antarctic fur seals at South Georgia in March (black solid line); CIs (95%) are shown for the mean krill length in March, based on weekly samples (Reid et al. 1999). The dashed line shows the model-estimated changes where recruitment of post-larval krill is driven by a functional relationship based on the sea surface temperature (SST) anomaly 2 years previously and the grey line is based on anomalies 1 year previously. (c) Relationship between the abundance of krill in the South Atlantic and the biomass of krill at South Georgia. (d) Relationship between the mean krill length (in mm) in the diet of Antarctic fur seals at Bird Island, South Georgia (in March) and the biomass of krill at South Georgia. (e) Relationship between the mean krill length in the diet of Antarctic fur seals at Bird Island, South Georgia (in March) and SST anomalies in the South Georgia region 13 months earlier (n=14, adjusted n=12.5; r=−0.85, rs=−0.86, r12,0.05=0.55, rs12,0.05=0.59). (f) As given for (e) but for 23 months earlier (n=14, adjusted n=12.9; r=0.60, rs=0.60, r12,0.05=0.55, rs12,0.05=0.59). (g) Relationship between the number of Antarctic fur seal pups produced and the mean length of krill (in mm) in the diet of adult Antarctic fur seals at Bird Island, South Georgia. (h) Relationship between the Antarctic fur seal pup weaning mass and the biomass of krill at South Georgia.
Mentions: Having established that interannual variation in Scotia Sea SST and sea ice extent depends significantly upon external forcing, we next examined the impact of these fluctuations on the krill population. We compared krill abundance across the South Atlantic with krill biomass estimates from local surveys at South Georgia (figure 3a). Although these data series are short, the pattern of fluctuations shows a delay between a change in numbers and biomass which is consistent with current views of krill population dynamics (Murphy et al. 1998; Murphy & Reid 2001). Krill abundance across the South Atlantic sector was lowest when biomass was also low at South Georgia (figure 3c). These low biomass periods were also observed when krill length was most variable (figure 3d). Animals were more consistent in size (approx. 46–49 mm) during periods of higher biomass.

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