Effects of climate change and fisheries bycatch on Southern Ocean seabirds: A review

Abstract

Over the last century, major climate changes and intense human exploitation of natural living resources have occurred in the Southern Ocean, potentially affecting its ecosystems up to top marine predators. Fisheries may also directly affect seabirds through bycatch and additional food resources provided by discards. The past 20 yr of research has seen an increasing number of studies investigating the effects of climate change and fisheries activities on Southern Ocean seabirds. Here, we review these studies in order to identify patterns in changes in distribution, phenology, demography and population dynamics in response to changes in climate and fisheries bycatch. Shifts in distribution and breeding phenology were documented in parallel to increases in sea-surface temperatures and changes in sea-ice cover. Above all warm sea-surface temperatures negatively affected demographic parameters, although exceptions were found. Relationships suggest non-linear effects of sea-ice cover on demographic parameters and population dynamics, with optimum sea-ice cover conditions appearing to be the rule. Fishing efforts were mainly negatively related to survival rates, and only for a few species positively related to breeding success. A handful of studies found that chronic mortality of immature birds due to fisheries negatively affected populations. Climate factors and fisheries bycatch may simultaneously affect demographic parameters in a complex way, which can be integrated in population models to project population trajectories under future climate or fisheries scenarios. Needed are studies that integrate other environmental factors, trophic levels, foraging behaviour, climate-fisheries inter actions, and the mechanisms underlying phenotypic plasticity, such as some pioneering studies conducted elsewhere.

Full text

MARINE ECOLOGY PROGRESS SERIES
Mar Ecol Prog Ser
Vol. 454: 285– 307, 2012
doi: 10.3354/meps09616 Published May 21
INTRODUCTION
Several studies have shown that recent climate
change and variability have affected a wide range of
species (Walther et al. 2002, Parmesan & Yohe 2003,
Root et al. 2003, Parmesan 2006), including seabirds
(e.g. Montevecchi & Myers 1997, Kitaysky & Golu -
bova 2000, Kitaysky et al. 2000, Sydeman et al. 2001,
Frederiksen et al. 2004). A major challenge in eco -
logy and conservation is to predict the effect of future
climate change on populations, species’ distributions
and ecosystems. In the Southern Ocean, there has
been strong evidence for important climate changes
over the last century. Among the most im portant
changes that may have affected seabird distribution,
phenology and populations are:
© Inter-Research 2012 · www.int-res.com*Email: barbraud@cebc.cnrs.fr
Effects of climate change and fisheries bycatch on
Southern Ocean seabirds: a review
Christophe Barbraud1,*, Virginie Rolland1,2, Stéphanie Jenouvrier1, 3, Marie Nevoux1, 4,
Karine Delord1, Henri Weimerskirch1
1Centre d’Etudes Biologiques de Chizé, Centre National de la Recherche Scientifique, Villiers en Bois,
79360 Beauvoir-sur-Niort, France
2Department of Wildlife Ecology and Conservation, University of Florida, Gainesville, Florida 32611, USA
3Biology Department, MS-34, Woods Hole Oceanographic Institution, Woods Hole, Massachusetts 02543, USA
4Mammal Research Institute, Department of Zoology & Entomology, University of Pretoria, Pretoria 0002, South Africa
ABSTRACT: Over the last century, major climate changes and intense human exploitation of nat-
ural living resources have occurred in the Southern Ocean, potentially affecting its ecosystems up
to top marine predators. Fisheries may also directly affect seabirds through bycatch and additional
food resources provided by discards. The past 20 yr of research has seen an increasing number of
studies investigating the effects of climate change and fisheries activities on Southern Ocean
seabirds. Here, we review these studies in order to identify patterns in changes in distribution,
phenology, demography and population dynamics in response to changes in climate and fisheries
bycatch. Shifts in distribution and breeding phenology were documented in parallel to increases
in sea-surface temperatures and changes in sea-ice cover. Above all warm sea-surface tempera-
tures negatively affected demographic parameters, although exceptions were found. Relation-
ships suggest non-linear effects of sea-ice cover on demographic parameters and population
dynamics, with optimum sea-ice cover conditions appearing to be the rule. Fishing efforts were
mainly negatively related to survival rates, and only for a few species positively related to breed-
ing success. A handful of studies found that chronic mortality of immature birds due to fisheries
negatively affected populations. Climate factors and fisheries bycatch may simultaneously affect
demographic parameters in a complex way, which can be integrated in population models to pro-
ject population trajectories under future climate or fisheries scenarios. Needed are studies that
integrate other environmental factors, trophic levels, foraging behaviour, climate−fisheries inter -
actions, and the mechanisms underlying phenotypic plasticity, such as some pioneering studies
conducted elsewhere.
KEY WORDS: Seabirds · Bycatch · Population dynamics · Demography · Distribution · Phenology ·
Sea ice · Sea-surface temperature
Resale or republication not permitted without written consent of the publisher
Contribution to the Theme Section ‘Seabirds and climate change’
O
PEN
PEN
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Mar Ecol Prog Ser 454: 285–307, 2012
1. A large-scale change in the atmospheric circula-
tion of the high southern latitudes, the major mode of
variability being the southern annular mode (SAM).
Since the late 1970s, the SAM has become more pos-
itive, resulting in a 15 to 20% increase of westerly
winds around the Antarctic continent, an increase in
temperature and a decrease in sea ice in the coastal
region of West Antarctica, as well as changes in the
frequency and intensity of cyclones south of 40° S.
The change in SAM coincided with the development
of the ozone hole (Marshall 2003, Turner et al. 2009).
2. An increase in atmospheric temperatures for the
sub-Antarctic South Georgia, Macquarie, Kerguelen,
Heard and Marion Islands and on the Antarctic
Peninsula (British Antarctic Survey 1987, Adamson
et al. 1988, Frenot et al. 1997, Budd 2000, Smith 2002,
Meredith & King 2005, Solomon et al. 2007).
3. An increase in the frequency and intensity of
El Niño events, with some El Niño signals being
detected in the Antarctic (Solomon et al. 2007).
4. An increase of CO2concentration south of 20° S
in the southern Indian Ocean (Solomon et al. 2007,
Turner et al. 2009).
5. An increase in Antarctic air temperatures by
about 0.2°C on average since the late-nineteenth
century, with a particular increase in West Antarctica
since the early 1950s (Masson-Delmotte et al. 2003,
Vaughan et al. 2003, Turner et al. 2009).
6. A warming of the Antarctic Circumpolar Current
waters by 0.06°C decade−1 at depths of 300 to 1000 m
from the 1960s to 2000s, and by 0.09°C decade−1
since the 1980s (Levitus et al. 2000, Gille 2002). The
warming is more intense on the southern side of the
Antarctic Circumpolar Current than north of it.
7. An average increase of 2.3°C over the last 81 yr
in the upper 150 m of the waters around South Geor-
gia (Trathan et al. 2007).
8. An increase in sea-surface temperatures of the
southern Indian Ocean over the period 1960 to 1999
(Alory et al. 2007).
9. A decrease in sea-ice extent in the Bellings -
hausen Sea and an increase in sea-ice extent in the
Ross Sea from 1979 to 2006, and a decrease in sea-ice
extent in East Antarctica from the 1950s to 1970s
(Curran et al. 2003, de la Mare 2009, Ainley et al.
2010a).
10. A decrease of the sea-ice season duration (later
advance and earlier retreat of sea ice) in the Bellings -
hausen Sea and an increase (earlier advance and
later retreat of the sea ice) in the Ross Sea (Parkinson
2004).
These physical changes may have had profound
effects on several components of the Southern Ocean
ecosystems and across a range of trophic levels (For-
cada et al. 2006, Murphy et al. 2007, Nicol et al. 2007,
Trathan et al. 2007). For example, in the southern
Atlantic Ocean, long-term surveys suggest a 38 to
81% decline in krill stocks since the mid-1970s
(Atkinson et al. 2004). Although the causes (or pre -
dators) of this decline are still being debated (Hewitt
et al. 2003, Ainley et al. 2007), a significant negative
correlation between krill density and mean sea-sur-
face temperature at South Georgia has been found
for the period from 1928 to 2003, suggesting a large-
scale response of krill and of the entire open-ocean
ecosystem to climate change (Whitehouse et al.
2008). The length of the sea-ice season duration or
the timing of sea-ice advance or retreat may have
profound consequences on the structure of food webs
and their productivity as recently shown in the
Bering Sea (Hunt et al. 2011). In the Southern Ocean
it has been established that ice-edge blooms have a
productivity 4- to 8-fold that of open water (Smith &
Nelson 1986), and have high densities of krill (Brier-
ley et al. 2002, Nicol 2006).
Seabirds provide some of the best time series data
for Southern Ocean animals because of their accessi-
bility in land-based colonies where they can be stud-
ied. Although most seabird time series data may be
too short to provide evidence for climate change
effects on populations, several studies have found
significant changes in demographic and behavioural
parameters in relation to climate, such as sea-surface
temperature or sea-ice extent (e.g. Fraser et al. 1992,
Barbraud & Weimerskirch 2001a, Jenouvrier et al.
2003, Forcada et al. 2006, Trathan et al. 2006).
However, predicting population responses to pro-
jected climate change using population dynamics
theory and models remains challenging because
other environmental factors may affect individuals
and population dynamics (Fig. 1). Among these, the
accidental mortality of seabirds caused by fisheries
has been recognised as a main factor potentially
affecting seabird populations. Indeed, the high num-
bers of seabirds that are killed annually in fishing
gear (‘bycatch’; Perrin 1969, Weimerskirch & Jou-
ventin 1987, Brothers 1991) have focused attention
on the ecological effects of bycatch in industrial
fisheries (Brothers et al. 1999, Sullivan et al. 2006,
Watkins et al. 2008), and may act as a confounding
factor when trying to predict the population dynam-
ics under different scenarios of climate change. To
date it remains unclear to what extent simultaneous
changes in climate and bycatch have affected and
will affect seabird populations. Recently, several stud-
ies have investigated the effects of climate change
286

Barbraud et al.: Southern Ocean seabirds, climate change, fisheries
(e.g. Peacock et al. 2000, Barbraud & Weimerskirch
2001b, Sydeman et al. 2001, Thompson & Ollason
2001, Ainley et al. 2005, Jenouvrier et al. 2005, For-
cada et al. 2006, Le Bohec et al. 2008, Wolf et al. 2010)
and bycatch (e.g. Oro et al. 1995, Tuck et al. 2003,
Cuthbert et al. 2003, Votier et al. 2004, Lewison et al.
2004, Véran et al. 2007, Frederiksen et al. 2008)
separately on seabirds worldwide, but few have
addressed both issues simultaneously (Frederiksen
et al. 2004, Rolland et al. 2009a). Here, we review
the current research on the effects of climate and
fisheries bycatch on Southern Ocean seabird demo -
graphy and population dynamics.
In the Southern Ocean, the twentieth century was
also characterised by intensive human exploitation
of natural resources, particularly whales and fishes
(Pauly et al. 1998, Myers & Worm 2003, Croxall &
Nicol 2004, Ainley & Blight 2008, Ainley et al. 2010b).
Although the relative importance of bottom-up or
top-down processes on the effect of fish and whale
harvesting on Southern Ocean top predators such as
seabirds are highly debated (Ainley et al. 2007, Nicol
et al. 2007, Ainley & Blight 2008, Barbraud & Cotté
2008, Ainley et al. 2010b), it is at present difficult to
quantify the effects of either process given the lack of
long-term data that incorporate both physical and
biological drivers of ecosystem processes. Better doc-
umented are the direct interactions between seabirds
and fisheries, and more particularly bycatch, which
may have been implicated in population declines of
several species of seabirds in the Southern Ocean
(e.g. Weimerskirch et al. 1997, Tuck et al. 2001).
However, the effect of bycatch on demographic para-
meters and population dynamics remains poorly
known for several populations, and even less is
known about the potential interactions between
bycatch and climate on seabird population dynamics.
Recent technological developments in tracking
devices (miniaturisation, memory capacity) have per-
mitted the tracking of seabirds year round and the
identification of foraging areas throughout the year
(Wilson et al. 2002, Weimerskirch 2007, Burger &
Schaffer 2008). This has allowed a better understand-
ing of the spatial and temporal interactions between
seabirds and fisheries, which was an important step
in developing more realistic models to test the effects
287
Fig. 1. Effects of fisheries activities and climate on demographic
parameters and populations of Southern Ocean seabirds. Dis-
cards may affect bycatch by attracting seabirds behind fishing
vessels. Climate directly affects vital rates or indirectly through
changes in foraging or breeding habitat, which in turn affect
foraging strategies, distribution and phenology. Climate may
affect disease outbreaks or population dynamics of introduced
predators. Climate may also affect fisheries distribution and ef-
fort. Grey dashed arrows indicate potential feedback on demo-
graphic parameters due to density dependence

Mar Ecol Prog Ser 454: 285–307, 2012
of bycatch and climate on population dynamics (Rol-
land et al. 2008). Simultaneously, the application
of the theory of exploited populations to seabird
bycatch (Lebreton 2005, Véran et al. 2007) has per-
mitted the development of a robust theoretical back-
ground to test for the effects of bycatch on seabird
demographics.
In the present paper, we first review the effects of
climate change on the distribution and phenology of
Southern Ocean seabirds. We then review Southern
Ocean studies on seabirds to determine how climate
variability, fisheries bycatch and effort affect their
demographic parameters and population dynamics.
We were more specifically interested in attempting
to determine whether general patterns are emerging
in the effect of climate and fisheries bycatch on vital
rates. In addition, we also consider how Southern
Ocean seabird populations may respond to future cli-
mate change in light of the recent modelling efforts
to tackle this question.
METHODS
This work is based on the analysis of contents from
research articles published before September 2011.
Research articles were selected with the ISI Web of
Knowledge (Thomson Reuters) search engine, using
the following search criteria:
Topic = (seabird* OR penguin* OR albatross* OR
petrel* OR fulmar* OR shearwater*) AND (southern
ocean OR Antarctic) AND (climate OR fisher* OR
bycatch).
Timespan = All Years.
These search criteria returned 409 papers to which
we added papers collected based on expert knowl-
edge. From these, only papers reporting data on
Southern Ocean seabird phenological, distributional,
or demographic changes and at least 1 climate
or fishery (effort or bycatch) associated variable
were retained. Although the Southern Ocean is often
defined as the ocean from the coast of Antarctica
north to 60° S (www.scar.org/articles/southernocean.
html), we here extended the northern limit of the
Southern Ocean to 30°S. This allowed us to include in
our review many studies that investigated the effects
of climate and bycatch on seabird species that breed
in the southern hemisphere and frequent the South-
ern Ocean and its vicinities. This yielded a total of 71
publications on which our review is based (Fig. 2).
We recognize that some relevant publications may
have been missed, but our review should be repre-
sentative of research in the field.
The following questions were used to characterize
the analyses presented in the reviewed manuscripts:
(1) What was the demographic, phenological, or dis-
tribution parameter analyzed? (2) What was the cli-
mate or fishery (effort, bycatch) variable used? (3)
What was the sign of the relationship between cli-
mate or fishery variables and seabird variables?
Responses to these questions were then summa-
rized in order to quantify the type of climate or fish-
ery variables affecting seabird variables and the sign
of the relationships. Most studies that investigated
statistical relationships between climate variables,
fishing effort or bycatch, and Southern Ocean sea -
bird demographic parameters (Appendix 1, Tables A1
& A2) focused on a handful of demographic para -
meters (mainly numbers of breeding pairs, breeding
success or adult survival). Few studies focused on
juvenile survival, recruitment, breeding proportions,
or dispersal. However, these parameters were in -
cluded in our review since we believe they will be
more extensively studied in the future given the
increasing number of long-term studies and the
development of adequate statistical tools to estimate
these parameters.
EFFECTS OF CLIMATE ON SOUTHERN OCEAN
SEABIRD PHENOLOGY, DISTRIBUTION,
DEMOGRAPHY AND POPULATION DYNAMICS
Distribution
Although, most observations worldwide of climate
change responses have involved changes in species’
phenology and distribution (Crick et al. 1997, Parme-
san et al. 1999, Hüppop & Hüppop 2003), particularly
for terrestrial species of the Northern Hemisphere
(Parmesan & Yohe 2003, Root et al. 2003, Gaston
et al. 2005), evidence remains scarce for Southern
Ocean seabirds.
From a historical perspective, there is paleological
evidence for major shifts in the distribution of Adélie
penguin Pygoscelis adeliae populations in the Ross
Sea during the Holocene, with 2 periods of large-
scale abandonment at 5000 to 4000 and 2000 to 1100
calendar yr BP corresponding to cooling episodes that
caused unfavourable marine conditions for breeding
penguins (Emslie et al. 2007). There is also evidence
for distributional changes in response to climate
change for this species at other localities in East
Antarctica (Emslie & Woehler 2005) and on the
Antarctic Peninsula (Baroni & Orombelli 1994, Sun
et al. 2000, Emslie 2001, Emslie & McDaniel 2002,
288

Barbraud et al.: Southern Ocean seabirds, climate change, fisheries
Emslie et al. 2003). Historical distributional changes
in response to the advance or retreat of the Antarctic
continental ice sheet are also documented for snow
petrels Pagodroma nivea (Hiller et al. 1988, Ver ku -
lich & Hiller 1994, Steele & Hiller 1997). More
recently, on centennial to decennial time scales, there
is evidence that open-ocean feeding penguins, the
chinstrap P. antarctica and the gentoo P. papua,
spread southward between 20 and 50 yr ago along
the Antarctic Peninsula, where the most rapid cli-
mate changes have been observed, with paleoevi-
dence that gentoo had been absent from the Palmer
region for 800 yr previously (Fraser et al. 1992,
Emslie et al. 1998).
By contrast, colonies of the pagophilic (i.e. ice de -
pendent) Adélie penguin situated at the northern
part of the Antarctic Peninsula have declined dra-
matically during the past decades in response to a
decrease in sea-ice extent and sea-ice season dura-
tion (Fraser et al. 1992, Ainley et al. 2005, Forcada et
al. 2006, Hinke et al. 2007, but see Trivelpiece et al.
2011). On the other hand, gentoo populations are
increasing, which has been interpreted in response
to sea ice too because this species needs ice-free
habitat around the colonies to breed (the sea-ice
hypothesis; Fraser et al. 1992). However, populations
of chinstrap penguins show contrasted responses,
with some colonies declining while southernmost
289
Fig. 2. Location of long-term monitoring studies where the effects of climate variability and fisheries bycatch on demography and
population dynamics of Southern Ocean seabirds were investigated. Studied species in parentheses. 1: Malgas Island (cape
gannet); 2: Marion & Prince Edward Islands (wandering albatross); 3: Showa (Adélie penguin); 4: Crozet Islands (king penguin,
wandering albatross, sooty albatross, light-mantled sooty albatross, southern giant petrel, northern giant petrel, white-chinned
petrel); 5: Kerguelen Islands (black-browed albatross, blue petrel, thin-billed prion, grey petrel); 6: Amsterdam Island (Amster-
dam albatross, indian yellow-nosed albatross, sooty albatross); 7: Casey (snow petrel); 8: Philipp Island (little penguin); 9: Albatross
Island (shy albatross); 10: Mewstone (shy albatross); 11: Pedra Branca (shy albatross); 12: Lord Howe (flesh footed-shearwater);
13: Dumont d’Urville (emperor penguin, Adélie penguin, Antarctic fulmar, snow petrel); 14: Macquarie Island (wandering alba-
tross, grey-headed albatross, black-browed albatross); 15: Campbell Island (rockhopper penguin); 16: Otago Peninsula &
Oamaru (yellow-eyed penguin, little penguin); 17: Coulman Island (Adélie penguin); 18: Ross Island (Adélie penguin); 19: Falk-
land Island/Islas Malvinas (thin-billed prion); 20: South Sandwich Islands (Adélie penguin, chinstrap penguin); 21: western
Antarctic Peninsula (Adélie penguin, chinstrap penguin, gentoo penguin); 22: South Orkney Islands (Adélie penguin, chinstrap
penguin, gentoo penguin); 23: South Georgia (king penguin, gentoo penguin, macaroni penguin, wandering albatross, black-
browed albatross, grey-headed albatross); 24: South Shetland Islands (Adélie penguin, chinstrap penguin); 25: Tristan de Cunha
(Atlantic yellow-nosed albatross); 26: Gough Island (Atlantic yellow-nosed albatross). Taxonomic names see Appendix 1

Mar Ecol Prog Ser 454: 285–307, 2012
colonies increase (Fraser et al. 1992, Hinke et al.
2007), which suggests much more complex mecha-
nisms than the sea-ice hypothesis.
Long-term changes in at-sea distribution of South-
ern Ocean seabirds are still poorly documented due
to the scarcity of long-term at-sea observations. In
the Prydz Bay area, at-sea observations conducted
between 1980 and 1992 by Woehler (1997) revealed a
decrease in abundance of 5 non-resident sub-Antarc-
tic species (wandering albatross Diomedea exulans,
black-browed albatross Thalassarche melanophrys,
light-mantled sooty albatross Phoebetria palpebrata,
northern giant petrel Macronectes halli, white-
chinned petrel Procellaria aequinoctialis). However,
these changes were not analysed in the light of cli-
mate changes in the region during the period of the
study. By contrast, in the southern Indian Ocean
southward shifts in the distributions of wandering
albatross and prions Pachyptila spp. between the
early 1980s and 2000s could be ascribed to species
redistribution or decrease in abundance due partly to
the warming of subtropical waters (Péron et al. 2010).
Surprisingly, the white-chinned petrel distribution
shifted northward, suggesting more complex mecha-
nisms, such as the expansion of fisheries activities in
subtropical waters since the 1980s (Tuck et al. 2003).
Péron et al. (2010) studied 12 seabird species and
showed that the greatest warming of sea-surface
waters was observed at 30 to 35° S. Their results sug-
gest that the abundance at sea of the northernmost
distributed species (those observed north of 38° S)
tended to decline contrary to the southernmost spe-
cies. Similar patterns and processes were docu-
mented elsewhere in other ocean basins (California
Current System: Hyrenbach & Veit 2003; Bay of
Biscay, North Atlantic: Hemery et al. 2008).
On shorter time scales, there is evidence that
migratory movements of seabirds are affected by
oceanographic conditions. Ballard et al. (2010) stud-
ied the migratory movement and wintering areas of
Adélie penguins breeding on Ross Island (Ross Sea,
Antarctica) during 3 consecutive years. They showed
that the wintering areas were situated at the edge of
the consolidated pack ice, well south of the large-
scale ice edge itself, and that the wintering area
shifted north in years of more extensive ice. Ballard
et al. (2010) further suggested that this would move
the penguins closer to the Antarctic Circumpolar
Current Southern Boundary, where there is less food
available. One can conjecture that this may increase
winter mortality or breeding proportions in the fol-
lowing breeding season, although this remains to be
quantified.
Phenology
Phenological changes were only recently docu-
mented for Southern Ocean seabirds. On a regional
scale, data on first arrival and laying of first eggs over
a 55 yr period for 9 species of Antarctic seabirds in
East Antarctica revealed a clear tendency toward
later arrival and laying (Barbraud & Weimerskirch
2006). On average, species now arrive at their colo -
nies 9 d later and lay eggs 2 d later than in the early
1950s. This tendency was unexpected and inverse to
most of those observed in the northern hemisphere
for terrestrial species. Interestingly, these delays
were partly linked to a decrease in sea-ice extent that
has occurred in East Antarctica, and possibly to an
increase in sea-ice season duration. Both factors may
have contributed to reduce the quantity and accessi-
bility of the food supplies available in early spring
and may partly explain the delays observed, with
seabirds needing more time to build up the reserves
necessary for breeding. However, more detailed
studies at an individual level are needed to under-
stand the proximate and ultimate drivers of Southern
Ocean seabirds breeding pheno logy and the effect of
phenological changes on fitness. The fitness and pop -
ulation consequences of these phenological changes
are currently unknown but could be serious for these
top predators if they become less synchonized with
the phenology of their food supplies. A brood that
hatches later than ex pected may suffer from higher
environmental deterioration, such as resource deple-
tion, competition, or predation risk for the offspring
(e.g. Lack 1968, Verhulst & Nilsson 2008). This could
potentially affect reproductive success or juvenile
survival. Although few studies have investigated the
fitness consequences of a change in the timing of
breeding in Southern Ocean seabirds, some observa-
tional and experimental studies suggest a decrease
in reproductive success in individuals breeding late
in the season (Barbraud et al. 2000a, Goutte et al.
2011).
Demography and population dynamics
The climate variables which were used for testing
relationships with demographic parameters included
large-scale climate indices (Southern Oscillation
Index [SOI], Southern Annular Mode [SAM], Indian
Ocean Dipole [IOD]) and local climate variables (sea-
surface temperature [SST], sea-ice extent [SIE], sea-
ice concentration [SIC], air temperature [T], sea-
surface height [SSH]). SOI is related to wind stress,
290

Barbraud et al.: Southern Ocean seabirds, climate change, fisheries
sea-surface temperature and precipitation anomalies
worldwide (Trenberth 1984). SAM is the leading
mode of atmospheric circulation variability in the
Southern Hemisphere (Gong & Wang 1998). IOD is
related to wind stress, sea-surface temperature and
precipitation anomalies over the Indian Ocean (Saji
et al. 1999). Positive values of IOD are associated
with a warm SST anomaly over the western Indian
Ocean and a cold SST anomaly over the eastern trop-
ical Indian Ocean. Although measured in the north-
ern Indian Ocean, IOD also affects SST over the
southern Indian Ocean <35° S. We found a total of 35
published studies concerning 22 species of seabirds.
The types of relationships between climate vari-
ables and demographic parameters are indicated in
Table 1. Most relationships between demographic
parameters and sea-surface temperature were nega-
tive (~50%). This is consistent with positive relation-
ships between demographic parameters and SOI
(~32% of the relationships were positive, whereas
only ~16% were negative). Indeed, signals of El
Niño−Southern Oscillation (ENSO) variability in
the tropical Pacific are known to propagate to high
latitudes through atmospheric teleconnections and
oceanic processes (Kwok & Comiso 2002, White et al.
2002, Liu et al. 2004, Turner 2004). SOI and SST are
inversely correlated in most parts of the Southern
Ocean, with positive SOI globally corresponding to
negative SST anomalies (Murphy et al. 2007).
Negative effects of warm sea-surface temperature
anomalies on demographic parameters have also
been found for a number of seabird species world-
wide (e.g. North Atlantic Ocean: Kitayskiy & Golu -
bova 2000, Durant et al. 2003, Harris et al. 2005;
Pacific Ocean: Veit et al. 1997, Bertram et al. 2005). In
several coastal and oceanic ecosystems, and particu-
larly in upwelling and frontal areas, warm sea-sur-
face temperature anomalies are known to have neg-
ative effects on primary and secondary production
(Wilson & Adamec 2002, Behrenfeld et al. 2006).
Cooler temperatures and higher wind stress can pro-
duce deeper convective mixing and increased nutri-
ent supply to support higher spring and summer
chlorophyll concentrations, whereas warmer sea-
surface temperatures and reduced wind stress can
produce shallower mixed layers, leading to reduced
nutrient entrainment, and reduced spring and sum-
mer chlorophyll (Daly & Smith 1993). Therefore, the
negative relationships between demographic para-
meters and SST (positive for SOI) may reflect the
effects of limited food resources on the demographic
traits of seabirds. Although climatic fluctuations are
often suspected to affect seabird populations through
integration along the trophic web up to top pre -
dators, one may not exclude direct mechanisms. For
example, snowfall or atmospheric temperatures may
directly affect breeding success in some species
(Murphy et al. 1991, Chastel et al. 1993). A small pro-
portion of relationships between SST and demo-
graphic parameters were positive, as also detected in
other oceanic ecosystems (Sandvik et al. 2008), sug-
gesting the existence of local or regional oceano-
graphic processes (e.g. see Blain et al. 2001, Park et
al. 2008a,b for the Kerguelen plateau).
Although sample sizes were relatively small, the
effect of sea ice (SIE and SIC) was contrasted be -
tween demographic parameters, probably because
different mechanisms were involved (Table 1). About
44% of the relationships between SIE or SIC and
breeding success were negative (~25% were posi-
tive), whereas ~37% of the relationships between
SIE or SIC and adult survival were positive (~12%
were negative), and ~54% of the relationships
between SIE or SIC and breeding population size
were positive (~38% were negative). An increase in
SIE or SIC may reduce breeding success because it
directly affects the foraging habitat of pagophilic
species. When sea-ice extent is greater than normal
or when sea-ice concentration is particularly high,
Antarctic breeding species feeding within the pack
ice or at the edges of the pack ice may have to cover
greater distances between the nest and the foraging
grounds because they are central place foragers dur-
ing the breeding season. This would increase the
amount of time spent travelling and therefore de -
crease the feeding frequency of chicks during the
291
Effect
Positive Negative Null
Climate variables
SST 9 (20) 22 (50)013 (30)0
SOI 10 (32)05 (16) 16 (52)0
SIE or SIC 18 (37)016 (33)015 (30)0
SAM 2 (22) 5 (56) 2 (22)
T 3 (25) 6 (50) 3 (25)
IOD 1 (33) 0 (0)02 (67)
Effect of SIE or SIC on
Adult survival 3 (37) 1 (12) 4 (50)
Breeding success 4 (25) 7 (44) 5 (31)
Breeding pairs 7 (54) 5 (38) 1 (8)0
Table 1. Numbers and percentages (in parentheses) of posi-
tive, negative and null relationships between climate vari-
ables and demographic parameters found in the literature
review of Southern Ocean seabirds for all climate variables,
and for sea-ice variables for 3 demographic parameters. See
Appendix 1 for the definition of variables

Mar Ecol Prog Ser 454: 285–307, 2012
chick rearing period, or exceed the fasting capacity
of the incubating partner during incubation. Overall
this would lead to a de crease in breeding success.
This is typically the case for penguins such as the
emperor penguin Apteno dytes forsteri or the Adélie
penguin Pygoscelis adeliae (Ainley & LeResche 1973,
Ancel et al. 1992, Barbraud & Weimerskirch 2001a,
Massom et al. 2009).
Conversely, an increase in SIE or SIC may increase
(indirectly) adult survival because it positively affects
the Antarctic food web, more particularly its produc-
tivity. Sea-ice conditions are known to affect Antarc-
tic food webs, which may in turn affect demographic
parameters such as survival and breeding propor-
tions. Several studies suggest a positive relationship
between winter SIE or SIC and the abundance of key
species of the Antarctic ocean food web such as the
Antarctic krill Euphausia superba (Loeb et al. 1997,
Nicol et al. 2000). Therefore, we hypothesise that
extensive sea ice in winter may correspond to higher
levels of food resources for seabirds during spring
and summer, which may affect their adult survival
and their decision to breed (Barbraud & Weimers -
kirch 2001a, Jenouvrier et al. 2005). Indeed, it is well
known that in seabirds the proportion of individuals
engaging in reproduction depends in part on physi-
cal body condition, which might be directly affected
by the amount of food resources available (Drent &
Daan 1980, van Noordwijk de Jong 1986, Chastel et
al. 1995).
Eventually, these contrasted effects of sea ice on
different vital rates affect population size. Indeed,
breeding population size in a given year is the out-
come of the variations of lower level demographic
parameters such as survival, breeding success,
breeding proportions and recruitment. Therefore,
the effect of SIE or SIC on breeding population size
may be mediated through the effects of these climate
variables on lower level demographic parameters.
Table 1 shows that population size was often found to
be positively linked to SIE or SIC. This is not surpris-
ing for long-lived species for which the population
growth rate is extremely sensitive to adult survival.
However, breeding success can also play an impor-
tant role in population dynamics because it is more
variable than adult survival (Gaillard & Yoccoz 2003).
For example, the decrease in breeding success limits
the population recovery of an emperor penguin pop-
ulation in East Antarctica (Jenouvrier et al. 2009). In
addition, since population size in seabirds is often
measured by the number of breeders at a colony, the
amount of food available in a given year or the fol-
lowing winter may affect the number of birds attempt-
ing to breed in the following year, although there may
have been no actual change in the population size.
Recruitment and breeding proportions are also im -
portant parameters to take into account to under-
stand population responses to sea ice. For example,
in the Adélie penguin a negative effect of SIE on
breeding population size with a 5 to 6 yr lag is sus-
pected to result from negative effects of large SIE on
juvenile survival, which has an effect on breeding
population size when individuals recruit to the
breeding population at ~6 yr of age (Wilson et al.
2001, Jenouvrier et al. 2006). Extensive sea ice may
limit access of penguins to productive waters, with
starvation or increased predation disproportionately
affecting less-experienced birds.
The complex contrasted effects of sea ice (and to a
lesser extent sea-surface temperature) on demo-
graphic rates strengthen the importance of consider-
ing the entire life cycle to understand the effects of
climate on populations. The example of sea ice on
seabirds is particularly interesting because it sug-
gests the existence of optimal SIE or SIC conditions
which may maximise demographic parameters and
population growth rates of seabirds depending on a
sea-ice habitat. Ballerini et al. (2009) found a qua-
dratic relationship between Adélie penguin survival
and winter SIE and hypothesised that high SIE may
limit access to food resources, whereas low SIE may
limit abundance of food resources. Interestingly, an
increasing number of studies have found non-linear
relationships between seabird demographic para -
meters and climate variables (Gjerdrum et al. 2003,
Barbraud et al. 2011), suggesting the widespread
existence of optimal environmental conditions for
population growth rates. Such non-linear relation-
ships have also been proposed to explain the con-
trasted population trends of Adélie penguins in
Antarctica (Smith et al. 1999), with optimal popula-
tion growth corresponding to intermediate frequen-
cies of heavy sea-ice conditions (Fig. 3). This concep-
tual model of optimal environmental conditions may
help explain the contrasted responses observed
among different populations in the Southern Ocean
and other ocean basins (Sandvik et al. 2008).
Mainly documented are relationships between cli-
mate variables and breeding success, adult survival
and numbers of breeding pairs. The last 2 are the
most easily and cost effectively obtained in the field,
and statistical developments in capture-mark-recap-
ture methods during the last 3 decades have allowed
researchers to obtain robust estimates of adult sur-
vival (Williams et al. 2002). Very few studies have
investigated the effects of climate on juvenile sur-
292

Barbraud et al.: Southern Ocean seabirds, climate change, fisheries
vival or recruitment (Appendix 1). However, these
parameters may potentially be more sensitive to cli-
mate variability, since in such long-lived species,
juvenile survival is predicted to be less environmen-
tally canalised (canalisation here refers to a reduction
in the variability of a trait) against temporal variabil-
ity (and potentially environmental variability) than
adult survival (Pfister 1998, Gaillard & Yoccoz 2003).
In accordance with this prediction, some studies have
found stronger relationships between survival of
younger individuals and climate factors than with
older individuals (Nevoux et al. 2007).
The effects of climate variability on breeding dis-
persal of Southern Ocean seabirds have only recently
been investigated. Dugger et al. (2010) estimated
breeding dispersal of Adélie penguins between 3 dif-
ferent colonies in the south-western Ross Sea and
found that movement probabilities of breeding adults
from one year to the next were higher in years with
extensive sea ice or blockage to usual migration pat-
terns (Fig. 4).
Part of the contrasted responses within species may
be caused by the spatial variability in food webs of
the Southern Ocean (Trathan et al. 2007). Different
areas of the Southern Ocean are dominated by differ-
ent food webs. For instance, the lower trophic levels
of the Scotia Sea region are dominated by krill (Crox-
all et al. 1988, Murphy et al. 2007), whereas those of
the southern Indian Ocean are dominated by mycto -
phids (Pakhomov et al. 1996, Connan et al. 2008,
Cherel et al. 2008). Given the variation of habitat
preferences of the lower trophic levels we may thus
expect different effects of climate change in dif ferent
food webs and regions, and consequently contrasted
upper trophic level responses (Trathan et al. 2007).
The interspecific variability in trophic niche and
foraging strategies of seabirds (Weimerskirch 2007)
may also partly explain the observed contrasted re -
sponses. For instance, at South Georgia, warm sea-
surface temperature anomalies have positive effects
on the breeding success of black-browed albatrosses
Thalassarche melanophrys (Nevoux et al. 2010a) but
negative effects on the breeding success of gentoo
penguins Pygoscelis papua (Trathan et al. 2006).
Although several relationships between demo-
graphic parameters and climate variables were
found for a number of seabird populations in the
Southern Ocean, our understanding of the underly-
ing ecological mechanisms remains extremely lim-
ited. This is mainly because long-term time series of
abundance for prey species of Southern Ocean
seabirds are scarce due to sampling difficulties and
associated costs. This results in a poor understanding
of how biological and physical processes interact
across spatial and temporal scales. Perhaps best
understood are the demographic and behavioural
responses of seabirds breeding in the South Atlantic,
where the food webs of this region have been studied
since the beginning of the last century (Trathan et al.
2007). The food web of the South Atlantic and Scotia
Sea is highly dominated by krill. Atmospheric tele-
connections with ENSO generate anomalies in SST
in the South Pacific sector of the Southern Ocean
which are propagated eastward via the Antarctic Cir-
cumpolar Current and reach the South Atlantic with
several months lag. Changes in the South Atlantic
293
Fig. 3. Conceptual model adapted from Smith et al.
(1999) illustrating the consequences of sea-ice cover-
age variation on abundance and access to prey of
Antarctic seabirds, and its potential effect on seabird
demographic parameters. Dots show the hypotheti-
cal positions of populations of penguins. In the
Antarctic Peninsula, 1 emperor penguin colony was
recently reported as extinct probably as a conse-
quence of sea-ice disappearance during the last
decades (Barbrand & Weimerskirch 2001a). On the
Antarctic continent colonies appear to be stable dur-
ing the past 2 decades (Woehler & Croxall 1997,
Kooyman et al. 2007, Jenouvrier et al. 2009, Barbraud
et al. unpubl. data, Robertson et al. unpubl. data), al-
though major declines were reported during the late
1970s at some colonies (Barbraud & Weimerskirch
2001). The future trend in sea-ice coverage as pre-
dicted by IPCC scenarios and models is indicated,
and is expected to negatively affect the northernmost
penguin colonies (Jenouvrier et al. 2009, Ainley et al.
2010a). Taxonomic names see Appendix 1

Mar Ecol Prog Ser 454: 285–307, 2012
sector of SST and related fluctuations in SIE affect
the recruitment and dispersal of krill, which, in turn,
affects the breeding success and populations (Fig. 5)
of seabirds that depend on this prey species (Reid et
al. 2005, Forcada et al. 2006, Murphy et al. 2007).
Similar processes seem to occur south of Kerguelen
in the southern Indian Ocean. In this region SST
anomalies are also linked to ENSO through atmo -
spheric teleconnections and possibly eastward prop-
agation of SST anomalies generated in the South
Pacific (Guinet et al. 1998, Park et al. 2004, Murphy
et al. 2007). During warm SST anomalies the diet of
blue petrels Halobaena caerulea breeding at and
foraging south of the Kerguelen Islands is highly
skewed towards crustaceans (euphausiids and The -
misto gaudichaudii), whereas fishes (mainly myc-
tophids) constitute the main part of their diet during
normal years (Connan et al. 2008). Interestingly the
per capita energetic content of crustacean species
consumed during warm SST anomalies is less impor-
tant than the energetic value of fish species con-
sumed, and body condition, breeding probability and
success, and adult survival are all negatively affected
by warm SST and positive SSH anomalies south of
Kerguelen (Guinet et al. 1998, Barbraud & Weimer-
skirch 2003, 2005).
EFFECTS OF FISHERIES BYCATCH ON
DEMOGRAPHY AND POPULATION DYNAMICS
OF SOUTHERN OCEAN SEABIRDS
Although accidental bycatch of seabirds in fishing
gear has been an acknowledged problem for a rela-
tively long time (e.g. Perrin 1969, Weimerskirch &
Jouventin 1987, Brothers 1991), most studies examin-
ing the effects of fisheries bycatch on demographic
parameters and population dynamics are relatively
recent (Oro et al. 1995, Cuthbert et al. 2003, Tuck et
al. 2003, Lewison et al. 2004, Votier et al. 2004, Véran
et al. 2007, Barbraud et al. 2008, Frederiksen et al.
2008, Rolland et al. 2008, Véran & Lebreton 2008).
The species reported most frequently caught in long-
lines worldwide include albatrosses, petrels and
shear waters (Brothers et al. 1999), most of which
have highly unfavourable conservation status (Baker
et al. 2002). In the Southern Ocean, accidental mor-
tality in trawling fisheries may also be high (Sullivan
et al. 2006, Croxall 2008, Watkins et al. 2008).
Table 2 summarizes the studies that investigated
the effect of fisheries bycatch on 5 demographic
parameters of Southern Ocean seabirds. Although
some studies tested for explicit relationships and
others inferred an effect of bycatch on population
dynamics using population models including addi-
tive mortality effects, the majority of studies found
negative effects of fishing effort or bycatch rates on
demographic parameters (~64%). Despite positive
effects of fisheries activities on breeding success of
294
Fig. 4. Pygoscelis adeliae. Effect of sea-ice variability on an-
nual breeding dispersal probability of adult Adélie penguins
breeding in the south-western Ross Sea, from 1996 to 2007.
Movement probabilities differed between colonies but were
higher in years with extensive sea ice or when icebergs
were present serving as physical barriers and altering the
spring migration route of penguins. From Dugger et al. (2010)
Fig. 5. Pygoscelis spp. Representation of the diversity of pen-
guin population responses (interannual changes in numbers
of breeding pairs) to the environment at Signy Island, South
Orkney Islands. Responses may be linear or non-linear
depending on the species’ ecological requirements. From
Forcada et al. (2006)

Barbraud et al.: Southern Ocean seabirds, climate change, fisheries
some species, probably due to additional food
resources such as bait, offal, or discards (Northern
Hemisphere: Garthe et al. 1996, Oro et al. 1996;
Southern Hemisphere: Grémillet et al. 2008), most
studies reported negative effects on adult survival.
This may have severe consequences on populations
of long-lived species, whose population growth rate
is highly sensitive to small variations in adult mor -
tality (Lebreton & Clobert 1991).
For methodological reasons, very few studies have
investigated the effects of fisheries activities on juve-
nile survival or recruitment, and they also suggest
negative effects. Even if population growth rate of
seabirds is less sensitive to variations in these para-
meters, chronic mortality of the younger age classes
may in the long term have detrimental effects on
populations (Barbraud et al. 2008) as it would deplete
the pool of future breeders. Higher vulnerability of
younger individuals to fishing gear has been re-
ported in several seabird species (Murray et al. 1993,
Gales et al. 1998, Bregnballe & Frederiksen 2006).
Younger birds may (1) spend more time in areas with
high longline efforts than adult birds, (2) be less effi-
cient foragers than adults and may therefore attempt
to fish behind vessels more frequently, (3) be more
hungry than adults and take more risks behind
vessels, and (4) be less experienced than adults in
foraging behind vessels without getting hooked. For
a number of studies (~24%), no significant effect of
fishing effort on demographic parameters was found.
This may be due to a lack of statistical power or
methodological problems, or the implementation of
mitigation measures to limit bycatch. Indeed, mitiga-
tion measures (mainly within Exclusive Economic
Zones and in the Convention on the Conservation of
Antarctic Marine Living Resources area) have drasti-
cally reduced bycatch rates in some fisheries of the
Southern Ocean during the last decades (Croxall &
Nicol 2004, Robertson et al. 2006, SC-CCAMLR 2006,
Delord et al. 2010), and it was generally assumed that
the level of bycatch was proportional to the fishing
effort (Véran et al. 2007) because very little informa-
tion was available to directly estimate harvest rates.
Further modelling is needed to take into account and
specifically test whether the decrease in bycatch
following mitigation measures can be detected on
demographic parameters such as adult survival.
It is known that there are no detailed demographic
data for several species of Southern Ocean seabirds
affected by bycatch. This causes many difficulties in
estimating the impact of bycatch on these species.
The potential biological removal approach offers an
interesting alternative way for assessing the poten-
tial for populations to sustain additional mortalities
(Wade 1998, Taylor et al. 2000, Niel & Lebreton
2005). This method has recently been further devel-
oped and used to assess the potential effects of by -
catch on Southern Ocean seabirds (Hunter & Caswell
2005, Dillingham & Fletcher 2008).
The effect of fisheries on Southern Ocean seabird
populations through the harvest of intermediate
trophic level species remains largely unexplored
(Wagner & Boersma 2011). Studies using predator−
prey models or ecosystem models remain largely
theo retical (May et al. 1979) and often suffer from a
shortage of empirical data (Hill et al. 2006). Major
fisheries have operated in the Southern Ocean since
the early 1970s and have led to the overexploitation
of several species such as marbled rock cod Noto -
thenia rossi and icefish Champsocephalus gunnari
(Croxall & Nicol 2004), but their potential effect on
seabird population remains poorly known. However,
correlations between predator populations and fish
biomass in predator foraging areas suggest that sev-
eral predator populations including seabirds (gentoo
penguin, macaroni penguin, imperial shag Phalacro-
corax spp.) that feed extensively on exploited fish
species declined simultaneously during the 2 periods
(early 1970s and mid-1980s) of heavy fishing (Ainley
& Blight 2008).
The effect of the depletion of whale stocks during
the 1950s to 1960s on Southern Ocean seabirds
remains speculative, essentially because very few
monitoring and trophic studies were underway dur-
ing the whaling period (Ainley et al. 2010b). Given
the major role of cetaceans in the structuring of
Southern Ocean food webs (Balance et al. 2006), the
demise of large whale species in the Southern Ocean
may explain some changes in the population dynam-
ics of several seabird species, through a release of
trophic competition and the resulting krill surplus or
an effect of upper level predators though top-down
forcing (Ainley et al. 2010b).
295
Effect
Positive Negative Null
Adult survival 1 (5)014 (64)07 (31)
Juvenile survival 0 (0)02 (67) 1 (33)
Recruitment 0 (0)01 (100) 0 (0)0
Breeding success 3 (100) 0 (0)00 (0)0
Breeding pairs 0 (0)04 (100) 0 (0)0
Table 2. Numbers and percentages (in parentheses) of posi-
tive, negative and null relationships between fishing effort
(trawl and longline) and demographic parameters found in
the literature review of Southern Ocean seabirds

Mar Ecol Prog Ser 454: 285–307, 2012
Although the krill fishery has been the largest fish-
ery in the Southern Ocean since the late 1970s, its
impact on upper trophic levels, such as seabirds, is
still poorly understood and remains to be quantified.
There is evidence for ecosystem responses to the
regional warming of the West Antarctic Peninsula
that has occurred during the past 50 yr. In particular,
decreased sea-ice extent and duration altered the
phytoplankton and zooplankton communities and
had negative effects on krill recruitment and on top
predator populations such as Adélie and chinstrap
penguins (Ducklow et al. 2007, Hinke et al. 2007, and
references in Appendix 1). However, Trivelpiece et
al. (2011) recently suggested that, in addition to cli-
mate, fisheries may have played an important role
in shaping the population dynamics of penguins in
the West Antarctic Peninsula and the Scotia Sea. Ac -
cording to their scenario (Fig. 6), favourable climate
conditions and reduced competition for krill follow-
ing the massive and large-scale harvesting of seals,
whales, ice fishes and notothenioids from the early
1820s to the 1980s may have favoured Adélie and
chinstrap penguins whose populations increased.
Since the late 1970s climate changes (sea-ice loss),
increased competition for krill following the recovery
of marine mammal populations, and the expansion of
the krill fishery resulted in poor environmental con-
ditions for penguins (decrease in krill density), the
populations of which declined.
COMBINED EFFECTS OF CLIMATE AND FISH-
ERIES BYCATCH ON POPULATION DYNAMICS
Comparing the relative effects of climate factors
and bycatch levels on demographic parameters
remains a difficult task at present due to the hetero-
geneity of the methods used to estimate their respec-
tive effects. To be comparable, both effects need to
be tested within the same statistical and modelling
framework and the variables need to be standardised
(Grosbois et al. 2008). This was possible for a limited
number of studies on 4 albatross species of the south-
ern Indian Ocean (Rolland et al. 2010). The mean
± SE of the slopes of the relationships between adult
survival (which was found to be the parameter
affected by fishing effort) and the standardised fish-
ing effort (assumed to be proportional to bycatch)
was −0.237 ± 0.041. This mean was 0.162 ± 0.020 for
the relationships between breeding success (which
was found to be the parameter most frequently
related to climate variables) and the standardised cli-
mate variables. Although these mean slopes are not
statistically different at the 0.05 level (χ2= 0.172, p =
0.10), the mean effect of fishing effort is nevertheless
46.3% higher than the mean effect of climate vari-
ables. Because it mainly affects adult survival, one
might conclude that for these 4 albatross species the
population-level effect of fishing effort (and bycatch)
is probably more important than the influence of cli-
mate variability.
The effects of climate variability on the one hand
and of fisheries activities on the other were shown to
be related to several demographic parameters in
seabird populations in the Southern Ocean and other
ocean basins (Appendix 1, Tables A1 & A2). How-
ever, very few studies have combined both effects
into fully parameterized population models to under-
stand past population changes and to predict popula-
tion growth rates under several scenarios of climate
and fishing effort. In the North Sea, Frederiksen et al.
(2004) built a matrix population model integrating
the effect of SST on adult survival and breeding suc-
cess of the kittiwake Rissa tridactyla, which were also
negatively affected by the lesser sandeel Ammodytes
marinus fishery. Their model suggested that the ob -
served changes in the demographic parameters re -
lated to changes in SST and fisheries activities could
explain the observed change in population growth
rate of the kittiwake population. Furthermore, sto-
chastic modelling indicated that the population was
unlikely to increase if the fishery was active or SST
increased and that the population was almost certain
to decline if both occurred. The same approach was
used by Barbraud et al. (2008) on a population of the
most frequently killed Southern Ocean seabird spe-
cies by longline fisheries, the white-chinned petrel
Procellaria aequinoctialis. The present study showed
contrasted effects of fishing efforts, with a positive
effect of toothfish Dissostichus eleginoides fishing
effort on breeding success, and negative effects of
toothfish and hake Merluccius spp. fishing effort
on petrel recruitment. Climate (SOI) was found to
mainly affect adult survival in this species. The pop-
ulation trajectory of a population matrix model
explicitly integrating the relationships between envi-
ronmental parameters and demographic parameters
was very similar to the observed population growth
rate estimated from independent survey data. Popu-
lation modelling suggests that when fisheries are
operating (and assuming a proportional level of
bycatch), the population growth rate is more sensi-
tive to a decrease in the mean or to an increase in the
variance of SOI than to a change in the fishing effort.
If the fisheries continue to operate at current levels of
bycatch, it is likely that the population will probably
296

Barbraud et al.: Southern Ocean seabirds, climate change, fisheries
not recover from its past decline. However, due to
the additive effects of SOI and fishing effort on adult
survival, an increase in SOI (corresponding to a de -
crease in frequency and intensity of El Niño events)
may compensate for the negative effects of fisheries
bycatch.
For the black-browed albatross Thalassarche me -
lano phrys, whose adult survival and breeding suc-
cess are affected by SST and bycatch mortality,
population modelling indicated that population
equilibrium was precarious, resulting from multiple
factors and complex relationships between demo-
graphic parameters and environmental conditions
(Rolland et al. 2009a). If fishing effort (and bycatch)
stops over the wintering area of the studied popula-
tion, the population would increase at 3.5% yr−1, sug-
gesting that bycatch mortality probably currently
limits the growth of the black-browed albatross pop-
ulation at Kerguelen (Fig. 7). These studies illustrate
the importance of population models for quantifying
the effects of climate and fisheries activities on popu-
lations and for projecting the possible trajectories of a
population according to predicted climate change
and possible modifications in human activities.
SUMMARY AND CONCLUSIONS
Overall, our review suggests that climate fluctua-
tion mainly affected low elasticity demographic traits
(fecundity, productivity), contrary to bycatch which
mainly affects high elasticity traits (survival). Because
seabirds are long-lived organisms, bycatch repre-
sents a serious threat to several seabird populations
and mitigation strategies may be effective (decrease
fishing effort to preserve populations from the effect
of climate change, e.g. Igual et al. 2009). Population
models also suggest that climate can act synergisti-
cally with bycatch and accelerate population declines
or may partially counteract additional mortality.
297
Fig. 6. Pygoscelis adeliae, P.
antarctica. Diagram of ecosys-
tem perturbations in the Scotia
Sea. From the early 1820s to the
1980s climate conditions were
favourable for Adélie and chin-
strap penguins, and exploitation
of seals, whales and fin fishes re-
sulted in a reduced competition
for krill. From the 1970s, climate
conditions became progressively
unfavour able, and recovery of
marine mammal populations and
the expansion of the krill fishery
resulted in increased competi-
tion for krill. From Trivelpiece et
al. (2011)
Fig. 7. Thalassarche melanophrys. Interaction between the
effects of climate variability (sea-surface temperature anom-
alies [SSTA] in the foraging areas used during the breeding
period) and fisheries bycatch (long-lining effort in the area
used during the non-breeding period) on the population
growth rate of a black-browed albatross population at Ker-
guelen Island. The star represents the conditions of fisheries
and sea-surface temperature at the time the study was per-
formed, and solid lines are isoclines where population
growth rates are constant for different parameter values.
From Rolland et al. (2009a)

Mar Ecol Prog Ser 454: 285–307, 2012
Although climate factors that affect seabird demo-
graphic parameters are only to some extent within
human control, any policy changes aimed at revers-
ing the warming trend and decreasing trend in sea-
ice extent in the Southern Ocean will be slow to take
effects due to the inertia of the earth climate system.
The microevolutionary responses of Southern Ocean
seabirds to climate change are also limited due to the
long generation time of these species and the fast
environmental changes, although they probably can
track some environmental changes through pheno-
typic plasticity. For example, life-history theory pre-
dicts that an increase in adult mortality should select
for an earlier age at first reproduction and for an
increase in reproductive effort (Gadgil & Bossert
1970, Schaffer 1974, Law 1979, Charlesworth 1994).
Such responses have experimentally or empirically
been reported for a number of fish species (e.g.
Reznick et al. 1990, Rochet et al. 2000), and the
decrease in age at first reproduction observed in a
wandering albatross Diomedea exulans population
during a period of high adult mortality caused by
fisheries bycatch is consistent with this prediction
(Weimerskirch & Jouventin 1987). The decrease in
female age at sexual maturation in the crabeater seal
Lobodon carcinophagus through time is also possibly
linked to an increase in food availability following
the decline of baleen whales due to whaling (Bengt-
son & Siniff 1981). However, evolutionary constraints
specific to most Southern Ocean seabirds may limit
their response capacity to an increase in mortality
induced by fisheries bycatch. Clutch size is limited to
1 egg yr−1, breeding frequency is highly constrained
by the seasonality of the Southern Ocean, and size at
maturity is constrained in those species with finite
structural growth (Warham 1990).
Thus, it seems prudent and in accordance with the
precautionary principle to evaluate and quantify the
effect of fisheries bycatch and to apply mitigation
measures when necessary for those fisheries known
to interact with threatened populations. Population
models can help identify the demographic parame-
ters most affected by bycatch. The influence of other
environmental factors on Southern Ocean seabird
population dynamics also need to be assessed. For
example, the population growth rate of Indian yellow
nosed albatrosses Thalassarche carteri at Amsterdam
Island is known to be limited by outbreaks of avian
cholera causing high chick mortality rather than by
climatic conditions or fishery-induced bycatch (Rol-
land et al. 2009a). Introduced predators are known to
affect seabird demographic parameters and popula-
tion dynamics too (Marion Island: Cooper et al. 1995;
Possession Island: Jouventin et al. 2003; Réunion
Island: Dumont et al. 2010; cats: Nogales et al. 2004;
rats: Jones et al. 2008), and several Southern Ocean
islands host one or several species of introduced
predators. Southern Ocean seabirds are also increas-
ingly exposed to marine debris, pollutants and chem-
icals, which may also potentially affect their physio -
logy, behaviour and demography (Burger & Gochfeld
2002). For example, in common guillemots Uria aalge
breeding in the North Atlantic there was a doubling
of adult mortality associated with major oil spills in
the wintering areas of the birds, and recruitment was
higher in years following oil spills than following
non-oil-spill years, probably through reduced com-
petition and compensatory recruitment at the breed-
ing colony (Votier et al. 2008). Finally, increased fresh -
water input from melting glaciers and ice shelves
acts to increase stratification along coastal margins,
which, in turn, may affect phytoplankton blooms
(Moline et al. 2008) and release persistent organic
pollutants into the ecosystem where they may accu-
mulate in higher trophic level predators (Geisz et al.
2008).
FUTURE CHANGE AND RESEARCH NEEDED
Predictions from climatologists in the 4th IPCC
assessment can be used directly in population mod-
els to help determine the future of populations
(Jenouvrier et al. 2009, Hare et al. 2010, Wolf et
al. 2010, Barbraud et al. 2011). Future population
models may eventually need to consider potentially
important effects such as non-linear relationships
be tween demographic parameters and climate or
fishery variables (Mysterud et al. 2001, Gimenez &
Barbraud 2009), density dependence (Frederiksen
et al. 2001, Lima et al. 2002), synergistic effects with
other environmental factors (Brook et al. 2008), or
microevolutionary changes (Kinnison & Hairston
2007, Coulson et al. 2010, Ozgul et al. 2010). From a
methodological point of view recent developments
in capture-mark-recapture models per mit robust
estimates of juvenile survival, recruitment and dis-
persal (e.g. Lebreton et al. 2003). These methods are
particularly appropriate for seabirds with delayed
maturity, and we believe there will be an increasing
use in the near future. Future studies aimed at test-
ing the effects of climate factors on these demo-
graphic parameters (and others) should use robust
and standardised statistical methods so that future
results can be integrated into meta-analyses (Gros-
bois et al. 2008).
298

Barbraud et al.: Southern Ocean seabirds, climate change, fisheries
One additional uncertainty in the future concern-
ing the combined effects of fisheries and climate
on seabird populations is the effect of climate on
fisheries. Longline fisheries are large-scale mobile
fisheries the distribution and effort of which are influ-
enced by environmental factors and especially large-
scale climatic processes (Tuck et al. 2003, Lehodey et
al. 1997, 2006). Thus, future climate change will un -
doubtedly affect target species of large migratory
fishes such as tuna (Hobday 2010). Lacking are
model-based projections of the spatio-temporal dis-
tribution of fisheries activities in the Southern Ocean
that would help build more realistic scenarios for
Southern Ocean seabirds.
Consequently, fisheries distribution and effort, and
therefore future interactions, will be complex and
more difficult to predict. Intensive land- and at-sea-
based long-term studies remain the only source of
consistent data allowing evaluation of population
trends, dynamics and how they are affected by envi-
ronmental factors, and engaging in such studies
should be a high priority for research and manage-
ment (Clutton-Brock & Sheldon 2010). Additional
measurements on other trophic levels (abundance
of prey), foraging behaviour, climate−fishery inter -
actions, bycatch rates, and on the mechanisms
under lying phenotypic plasticity will increase the
comprehensive and predictive power of these long-
term studies (Visser 2008).
Studies combining seabird demographic, trophic,
behavioural (foraging) and physiological data will be
most promising in order to understand the mechanis-
tic responses of seabirds to climate change and to
improve our ability to build sound scenarios for the
effects of future climate changes. For example, in
the Northern Hemisphere, pioneering studies have
examined the links between food abundance, nutri-
tional stress (hormone corticosterone), reproduction
and survival of individuals of the kittiwake Rissa tri-
dactyla (Kitaysky et al. 2010). When possible, future
studies will also have to take into account potential
ecological processes of trophic cascades, competi-
tion, predation and facilitation when attempting to
address climate effects on Southern Ocean seabird
populations (Ainley et al. 2010b).
Acknowledgements. We thank the French Polar Institute
(IPEV), the Terres Australes et Antarctiques Françaises, the
Zone Atelier de Recherches sur l’Environnement Antarc-
tique et Subantarctique (Centre National de la Recherche
Scientifique — Institut Ecologie et Environnement), and the
program Behavioural and Demographic Responses of Indian
Ocean Marine Top Predators to Global Changes (REMIGE)
funded by ANR Biodiversity for their ongoing support and
assistance, and 3 anonymous reviewers.
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306
Species Sa Sj Re Pr Bs N Climate factor Region Reference
Emperor penguin Aptenodytes forsteri ✓✓✓✓SST, SIE, SIC, Adélie Land Barbraud & Weimerskirch
SOI, T, SAM (2001a), Ainley et al. (2005),
Jenouvrier et al. (2005),
Massom et al. (2009)
King penguin Aptenodytes patagonicus ✓✓SST, SOI South Georgia, Crozet Islands Olsson & van der Jeugd (2002),
Le Bohec et al. (2008),
Saraux et al. (2011)
Adélie penguin Pygoscelis adeliae ✓✓✓SST, SIE, SIC, T, Ross Sea, Adélie Land, Fraser et al. (1992), Wilson et
SOI, SAM Enderby Land, Antarctic Peninsula, al. (2001), Ainley et al. (2005),
Antarctica, Signy Islands Jenouvrier et al. (2006),
Emmerson & Southwell (2008)
Lescroël et al. (2009),
Ballerini et al. (2009),
Forcada & Trathan (2009)
Chinstrap penguin Pygoscelis antarctica ✓✓ SIE, T, SAM Antarctic Peninsula, Signy Islands Forcada et al. (2006),
Forcada & Trathan (2009)
Gentoo penguin Pygoscelis papua ✓✓ SST, SIE, T, SAM South Georgia, Antarctic Peninsula Forcada et al. (2006),
Trathan et al. (2006),
Forcada & Trathan (2009)
Yellow-eyed penguin Megadyptes antipodes ✓✓✓SST New Zealand Peacock et al. (2000)
Rockhopper penguin Eudyptes chrysocome ✓SST New Zealand Cunningham & Moors (1994)
Macaroni penguin Eudyptes chrysolophus ✓SAM South Georgia Forcada & Trathan (2009)
Little penguin Eudyptula minor ✓SST, SOI New Zealand, Australia Perriman et al. (2000),
Chambers (2004)
Wandering albatross Diomedea exulans ✓✓✓SST, SOI Crozet Islands Inchausti et al. (2003),
Delord et al. (2008),
Rolland et al. (2010)
Amsterdam albatross Diomedea amsterdamensis ✓✓ ✓✓ SST, IOD Amsterdam Island Rivalan et al. (2010),
Barbraud et al. (2011)
Black-browed albatross Thalassarche melanophrys ✓✓✓ ✓ SST, SOI Kerguelen Islands, South Africa, Pinaud & Weimerskirch (2002),
South Georgia, South Australia Inchausti et al. (2003),
Nevoux et al. (2007, 2010a,b),
Rolland et al. (2008, 2009a),
Barbraud et al. (2011)
Atlantic yellow-nosed albatross ✓✓✓✓SOI Tristan da Cunha, Gough Cuthbert et al. (2003)
Thalassarche chlororhynchos
Indian yellow-nosed albatross Thalassarche carteri ✓✓SST, SOI Amsterdam Island Rolland et al. (2009b)
Sooty albatross Phoebetria fusca ✓✓✓SST, SOI Crozet Islands, Amsterdam Island Inchausti et al. (2003),
Delord et al. (2008),
Rolland et al. (2010)
Light-mantled sooty albatross Phoebetria palpebrata ✓✓ SST, SOI Crozet Islands Inchausti et al. (2003),
Delord et al. (2008)
Southern giant petrel Macronectes giganteus ✓SOI Crozet Islands Delord et al. (2008)
Northern giant petrel Macronectes halli ✓SOI Crozet Islands Delord et al. (2008)
Antarctic fulmar Fulmarus glacialoides ✓✓✓✓✓ SIC, SST Adélie Land Jenouvrier et al. (2003)
Snow petrel Pagodroma nivea ✓✓ ✓✓✓ SIE, SIC, T Adélie Land, Wilkes Land Barbraud et al. (2000b),
Barbraud & Weimerskirch
(2001b), Jenouvrier et al.
(2005), Olivier et al. (2005),
Barbraud et al. (2011)
Blue petrel Halobaena caerulea ✓SST, SSH, SOI Kerguelen Islands Guinet et al. (1998), Inchausti
et al. (2003), Barbraud &
Weimerskirch (2003),
Barbraud & Weimerskirch
(2005)
Thin-billed prion Pachyptila belcheri ✓✓SST, SIC Kerguelen Islands, Falkland Islands Nevoux & Barbraud (2005),
Quillfeldt et al. (2007)
White-chinned petrel Procellaria aequinoctialis ✓✓✓ SST, SOI Crozet Islands Barbraud et al. (2008)
Grey petrel Procellaria cinerea ✓✓✓ SST, SOI Kerguelen Islands Barbraud et al. (unpubl. data)
Appendix 1. Table A1. Studies that investigated the effects of climate factors on demographic parameters of Southern Ocean seabirds. ✓: demographic parameters inves-
tigated (Sa: adult survival; Sj: juvenile or immature survival; Re: recruitment; Pr: breeding proportions; Bs: breeding success; N: number of breeding pairs); SST: sea-sur-
face temperature; SIE: sea-ice extent; SIC: sea-ice concentration; T: air temperature; SSH: sea-surface height; SOI: Southern Oscillation Index; SAM: Southern Annular
Mode; IOD: Indian Ocean Dipole

Barbraud et al.: Southern Ocean seabirds, climate change, fisheries 307
Table A2. Studies that investigated the effects of fisheries activities (mainly fishing effort) on demographic parameters of Southern Ocean seabirds. ✓: demographic
parameters investigated (Sa: adult survival; Sj: juvenile/immature survival; Re: recruitment; Bs: breeding success; N: number of breeding pairs)
Species Sa Sj Re Bs N Type of fishery Region Reference
Wandering albatross Diomedea exulans ✓✓ ✓ Longline Southern Ocean, Weimerskirch et al. (1997), Tuck et al. (2001), Nel et
South Atlantic, al. (2003), Terauds et al. (2006), Delord et al. (2008),
South Indian Rolland et al. (2010)
Amsterdam albatross Diomedea amsterdamensis ✓Longline South Indian Rivalan et al. (2010)
Black-browed albatross Thalassarche melanophrys ✓✓Longline, trawl South Pacific, Terauds et al. (2005), Arnold et al. (2006), Sullivan et
Tasman Sea, al. (2006), Rolland et al. (2008, 2009a)
Kerguelen Islands,
South Atlantic
White-capped albatross Thalassarche steadi ✓✓ Longline South Pacific, Baker et al. (2007)
South Atlantic
Shy albatross Thalassarche cauta ✓✓ Longline South Pacific, Baker et al. (2007)
South Atlantic
Grey-headed albatross Thalassarche chrysostoma ✓Longline South Pacific Terauds et al. (2005)
Atlantic yellow-nosed albatross ✓Longline South Atlantic Cuthbert et al. (2003)
Thalassarche chlororhynchos
Indian yellow-nosed albatross Thalassarche carteri ✓Longline South Indian Rolland et al. (2009b)
Sooty albatross Phoebetria fusca ✓✓Longline South Indian Delord et al. (2008), Rolland et al. (2010)
Light-mantled sooty albatross Phoebetria palpebrata ✓Longline South Indian Delord et al. (2008)
Southern giant petrel Macronectes giganteus ✓Longline South Indian Delord et al. (2008)
Northern giant petrel Macronectes halli ✓Longline South Indian Delord et al. (2008)
White-chinned petrel Procellaria aequinoctialis ✓✓✓ Longline, trawl South Indian Barbraud et al. (2008)
Grey petrel Procellaria cinerea ✓✓✓ Longline, trawl South Indian Barbraud et al. (unpubl. data)
Flesh-footed shearwater Puffinus carneipes ✓Longline Australia Baker & Wise (2005)
Cap gannet Morus capensis ✓Trawl South Atlantic Grémillet et al. (2008)
Submitted: March 31, 2011; Accepted: January 22, 2012 Proofs received from author(s): April 19, 2012