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Antarctic krill fishery effects over penguin populations under adverse climate conditions: Implications for the management of fishing practices

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Fast climate changes in the western Antarctic Peninsula are reducing krill density, which along with increased fishing activities in recent decades, may have had synergistic effects on penguin populations. We tested that assumption by crossing data on fishing activities and Southern Annular Mode (an indicator of climate change in Antarctica) with penguin population data. Increases in fishing catch during the nonbreeding period were likely to result in impacts on both chinstrap ( Pygoscelis antarcticus ) and gentoo ( P. papua ) populations. Catches and climate change together elevated the probability of negative population growth rates: very high fishing catch on years with warm winters and low sea ice (associated with negative Southern Annular Mode values) implied a decrease in population size in the following year. The current management of krill fishery in the Southern Ocean takes into account an arbitrary and fixed catch limit that does not reflect the variability of the krill population under effects of climate change, therefore affecting penguin populations when the environmental conditions were not favorable.
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Journal: Ambio
Print ISSN: 0044-7447
Online ISSN: 1654-7209
DOI: 10.1007/s13280-020-01386-w
Antarctic krill fishery effects over penguin populations under adverse climate conditions: implications
for the management of fishing practices
Lucas Krüger
1
*, Magdalena F. Huerta
2
, Francisco Santa Cruz
1
, César A. Cárdenas
1
1
Departamento Científico, Instituto Antártico Chileno
Plaza Muñoz Gamero 1055, Punta Arenas, Chile
2
Centro de Humedales Rio Cruces, Universidad Austral de Chile, Valdivia, Chile.
*Corresponding author: lkruger@inach.cl
MFH magdalenahuerta@gmail.com ; FSC fsantacruz@inach.cl ; CC ccardenas@inach.cl
Abstract
Fast climate changes in the western Antarctic Peninsula are reducing krill density, which along
with increased fishing activities in recent decades, may have had synergistic effects on penguin
populations. We tested that assumption by crossing data on fishing activities and Southern Annular
Mode (an indicator of climate change in Antarctica) with penguin population data. Increases in fishing
catch during the non-breeding period were likely to result in impacts on both chinstrap (Pygoscelis
antarcticus) and gentoo (P. papua) populations. Catches and climate change together elevated the
probability of negative population growth rates: very high fishing catch on years with warm winters and
low sea ice (associated with negative Southern Annular Mode values) implied a decrease in population
size in the following year. The current management of krill fishery in the Southern Ocean takes into
account an arbitrary and fixed catch limit that does not reflect the variability of the krill population
under effects of climate change, therefore affecting penguin populations when the environmental
conditions were not favorable.
Keywords: Antarctic Peninsula, chinstrap penguin, gentoo penguin, population growth rate,
southern annular mode
Introduction
The western Antarctic peninsula (WAP) is one of the areas most affected by climate change. Fast
warming in the last decades (Cook et al. 2016; Moffat and Meredith 2018) and the southward input of
warmer waters, are decreasing the seasonal sea-ice extent and duration (Stammerjohn et al. 2008;
Moffat and Meredith 2018). Climate change effects have also been observed in different macro-scale
atmospheric phenomena, such as the Southern Oscillation Index (SOI) and the Southern Annular Mode
(SAM) (Stammerjohn et al. 2008; Moffat and Meredith 2018). Specifically, warming in the WAP has been
related to strengthening a positive trend in the SAM, which describes atmospheric circulation patterns
associated to the belt of westerly wind surrounding Antarctica (Clem et al. 2016). The SAM has a strong
influence in the inter-annual variability around the WAP, driving changes in sea-ice formation and
melting, and the injection of meteoric water (combination of glacial discharge and precipitation) to the
Southern Ocean (Moffat and Meredith 2018).
Current climate change has had significant effects in the Antarctic ecosystem, particularly for
sea-ice dependent species, such as the Antarctic krill Euphausia superba. Several studies have shown
dramatic changes in Antarctic krill populations, including distributional range contraction (Atkinson et al.
2019), size reduction (Tarling et al. 2016), decreased recruitment (Atkinson et al. 2019; Perry et al. 2019)
and decreased density (Atkinson et al. 2009; Flores et al. 2012). Variability in regional sea-ice has been
identified as an important limitation for krill abundance (Flores et al. 2012). Sea ice cover can affect the
survival of krill larvae, due to their reliance on sea ice to feed and for shelter during winter (Meyer
2012). Predicted future environmental changes are expected to produce further changes associated
with seawater warming and reduced sea-ice cover having an impact on krill distribution and biomass
(Piñones and Fedorov 2016; Atkinson et al. 2019).
Krill is a keystone species in the Antarctic marine food web (Hofmann et al. 2011; Ballerini et al.
2014) and hence, it is expected that any negative effects on krill will not only affect its direct predators
but also will produce a cascade effect on the entire ecosystem. Whether climate-based reductions in
krill density continue at the predicted rate (Atkinson et al. 2009), it is expected that krill predator
populations will follow a steep decline (Trathan and Reid 2009). There have been widespread decreases
of penguin populations over the Antarctic Peninsula with climate change recognized as the main driver
(Lynch et al. 2012; Casanovas et al. 2015). The population trends in these species seems to be related to
a reduction in sea-ice cover and krill abundance (Forcada et al. 2006; Trivelpiece et al. 2011). Some
authors have supported the hypothesis that there is a direct relationship between the sea ice variations
and the penguin abundance, including contrasting trends for ice-loving” and “ice-avoiding” species
(Forcada et al. 2006). In this sense, it would be expected that sea-ice retreat and the resulting access to
ice-free foraging areas should benefit both chinstrap (Pygoscelis antarcticus) and gentoo (P. papua)
penguins, which have been identified as “ice-avoiding” species. However, although this is consistent
with the Gentoo penguin global population trends (yet local decreases of Gentoo Penguin abundance
exist in the South Shetland Islands; i.e. Petry et al. 2016; Petry et al. 2018) the evidence pointing to a
decline of chinstrap penguin populations throughout the WAP suggests that reduction in krill availability
could be playing a critical role to explain the population dynamics of this species (Trivelpiece et al. 2011;
Lima and Estay 2013).
The Antarctic krill is target of an important fishery in the Southern Ocean, occurring mainly in
the Atlantic sector (FAO statistical subareas 48.1, 48.2 and 48.3). The Commission for the Conservation
of Marine Living Resources (CCAMLR) is the international organization responsible for the management
of the krill fishery and has successfully managed fishery based on a precautionary approach since its
creation in the early 1980s (Constable 2011). In recent years, there has been increasing concerns on how
climate-based changes and the current concentrated behavior of the krill fishery (Santa Cruz et al. 2018;
Krüger 2019) can affect synergistically the penguin colonies over the WAP. Moreover, krill catches have
been reaching values like those recorded in the 1990s before the adoption of a fixed catch (CCAMLR
2018). Although catches are considered to be low compared to the krill abundance
(catch limit is < 1% of
the total estimated biomass ≈ 60 million tones on Antarctic Peninsula alone, CCAMLR 2019), catch is
expected to keep increasing in the future with the development of new technologies and changes in
both fishing technologies and Antarctic environment. Contrasting to what fisheries did back in the
1990s, now the whole krill catches are concentrated on relatively small spots on the WAP and the South
Orkney Islands (Santa Cruz et al. 2018; Krüger 2019). While CCAMLR performance has been considered a
successfully sustainable managed practice (Nicol et al. 2012), under the current climate changes it is
likely that this may change (Hill et al. 2016) as signs of krill fishery decreasing performance of penguins
are becoming evident (Watters et al. 2020). This study aimed to evaluate the risk of the krill fishery to
populations of Pygoscelid penguins, testing if the population changes are proportional to changes in the
distribution of catches in WAP, and their synergistic relation with climate variability. We used 38 years
of fishing data to evaluate risk for both chinstrap and gentoo penguins and used mixed models to test
how population growth could have responded to the fishing pressure under contrasting Southern
Annular Mode conditions.
Methods
Penguin population data
All data on populations of chinstrap (Pygoscelis antarcticus) and gentoo (P. papua) penguins
breeding in the WAP area available at the Mapping Application for Penguin Populations and Projected
Dynamics MAPPPD (penguinmap.com, Humphries et al. 2017) between 1980 and 2017 were
downloaded (Fig. 1, Chinstrap = 197 colonies, Gentoo = 78 colonies). MAPPPD is a penguin population
databank, which puts together all available information about population counts of penguins on their
breeding colonies. Counts include different type of data: breeding pairs, adults and chicks. Only pair
counts made in November and December, matching the early breeding season and providing a better
picture of actual population size, were used. Temporal variation in colony-level population growth rate
was expressed as:
λ
std
= ((n
b
/n
a
)/years
b-a
)-1
where n is the number of breeding pairs counted in November or December of a given year (b)
and the number of breeding pairs counted in a previous year (a), divided by the number of years in
between b and a. This procedure allowed us to deal with differences in sampling size by smoothing any
too steep value resulting from a too large temporal gap in data, at the same time, providing population-
level temporal variability of each penguin colony. From this value then was subtracted 1, so that the
result varied from -1 (population extinction) to ∞, with posiQve values represenQng populaQon increase.
Each colony was classified based on CCAMLR Small-Scale Management Units: Elephant Island, Drake
East, Drake West, Bransfield East, Bransfield West and Antarctic Peninsula West, which we will refer as
Gerlache Strait because fishing in this area concentrated within the strait (Fig. 1). Small-Scale
Management Units are zones proposed in order to be a spatial tool for local monitoring of the krill
fishery and krill predators, and devised for spatially subdividing the krill catch limits (Constable and Nicol
2002). Most penguin colonies did not have data on the whole 38 years considered; majority of colonies
had less than 10 counts while 38 chinstrap and 45 gentoo colonies had at least two counts (enough for
calculating the λ
std
) (Fig. S1).
Krill fishery data
Haul-by-haul data of the fleet operations was obtained from the CCAMLR Secretariat database
for the period between 1980 and 2017 (38 years). The accumulated catch within a 30-km radius of each
colony was used to evaluate the risk of exposition of each colony to the changes in catch distribution.
During breeding season (when counts were made) foraging of pygoscelid penguins is more probable
within 30kms of the colonies (Warwick-Evans et al. 2018). We therefore assumed this to be the distance
where krill availability would be more important during key periods of the year cycle and competition
with fisheries would be more impacting. Each fishing event was classified based on important period of
the penguin intra-annual life cycle: chick-rearing (January to March), non-breeding (April to September)
and early breeding (October to December). Catch was accumulated within those periods for each year
(Fig. S2, Table S1) in order to better describe the periods when penguin are more at risk to experience
impacts from fishery, but catch was accumulated throughout the whole year to test statistically the
response of populations (below)
Climate data
The Southern Annular Mode SAM is the main large-scale pressure system driving climate in
Antarctica (Kwok and Comiso 2002; Doddridge and Marshall 2017). SAM is defined as the difference of
the normalized zonally mean sea level pressure of 40°S and 65°S (see Gong and Wang 1999 for details).
As SAM indicates differences, it can have negative and positive values: negative values mean air
pressure in Antarctic (65°S) is higher than in the subantarctic (40°S); positive values mean air pressure is
higher in subantarctic (40°S) than in Antarctic (65°S). Pressure differences reflects the large-scale
movements of air masses. By examining SAM values is possible to infer whether warmer currents from
the north intruded areas further south, therefore, SAM can accurately indicate trends of sea ice and
temperature anomalies in Antarctica (Marshall and Bracegirdle 2014; Doddridge and Marshall 2017).
Penguins (Forcada et al. 2006) and Antarctic krill (Flores et al. 2012; Meyer 2012) are knowingly
responsive to abrupt changes on temperature and ice conditions during winter. SAM monthly data was
downloaded from NOAA Earth System Research Laboratory ESRL (esrl.noaa.gov). Data on Fractional Sea
Ice Cover, Surface Level Temperature and Open Water Sensible Heat Flux were downloaded from NASA
Giovanni data browser (giovanni.gsfc.nasa.gov) per month.
Figure 1. Distribution of chinstrap Pygoscelis antarcticus (a) and gentoo P. papua (b) penguins breeding
colonies (white crosses) along the western Antarctic Peninsula, overlapped with the Antarctic krill
accumulated fishing catch. Data on fishing catch represents all the catch in the area accumulated
between 1980 and 2017, it is, all the krill that was extracted from a given spatial cell in 38 years. Penguin
data from MAPPPD (penguinmap.org; Humphries et al. 2017).
Penguins, fishery, and climate
Considering the high correlation of the climate variables in WAP (Fig. S3), and correlation of
climate variables with SAM variability with a temporal lag from zero to three months (Fig 2), we used
SAM during the non-breeding period
together with accumulated catch within each year in a binomial
Generalized Linear Mixed Model using the ‘lmerTest’ R package (Kuznetsova et al. 2018) and the ‘sjPlot’
R package (Lüdecke et al. 2019) to plot models:
binλ
std
~
catch
y
* SAM + (1| colony id)
where binλ
std
is a binary estimate of the standardized growth rate λ
std
(positive values=0,
negative values =1) understood as the probability of population decreasing in a given year. Catch
y
is the
accumulated year krill catch, SAM is the southern annular mode during winter (non-breeding season).
We used mixed models which allows to control for the effects of lack of independence and sample size
differences within the structure of the data. We used the colony ID as a random term in the formula
accounting for the colony-level differences on the intercept of the response to the explanatory
variables. The effect of the random term was tested with a Likelihood Ratio Test using the function
‘ranova’. All data processing and analysis were done in R environment (R Development Core Team 2014)
using ‘raster’ (Hijmans 2013), ‘plyr’ (Wickham 2020) and ‘ggplot2’ (Wickham and Chang 2015) packages.
Maps were produced using ArcGis 10.4.
Figure 2. Lagged regression model (cross correlation function CCF) testing the temporal response of
Fractional Sea Ice Cover (FSIC), Open Water Sensible Heat Flux (HFLUX) and Sea Level Air Temperature
(TLML) at the Western Antarctic Peninsula to the variation of the Southern Annular Mode (SAM). Lag
interval is in months. Dashed blue line indicates where the correlation is significant at the P<0.05 level.
Analysis was done in the ‘astsa’ R package (Stoffer 2008).
Results
Changes of spatial catches distribution
Krill catches within the 30 km radius from colonies of both species occurred predominantly
during chick-rearing and non-breeding periods (Fig. 3). Although, catches after the mid-1990s decreased
or remained stable in Elephant Island and Drake Passage sectors, respectively (Fig. 2); catches in the
Bransfield Strait increased near colonies of both penguin species (Fig. 3). During the last decade, fleets
started to operate more intensively in the Gerlache Strait, increasing catches during both chick-rearing
and non-breeding periods near chinstrap colonies (Fig. 3).
Figure 3. Seasonal accumulated catch within 30-km radius around each breeding colony of chinstrap
(Pygoscelis antarcticus) and gentoo (P. papua) penguins during Chick Rearing CR (January-March), Non-
breeding NBR (April-September) and Early Breeding EBR (October-December) periods classified
according to Small Scale Management Unities SSMUs: Elephant Island, Drake Passage East and West,
Bransfield Strait East and West ; Gerlache Strait. See also Figure 1.
Trend of the penguin populations
Most of the λ
std
values for chinstrap penguins were negative (58.78% of cases) in the WAP (Fig.
S4). Gentoo penguins presented a mean growth trend bordering the stability (Fig. S4) with 50.72% of
negative cases of λ
std
.
Probability of chinstrap population decrease was related to catch
y
(F
155,3
=2.96, z=2.65, P=0.008)
and to the interaction catch
y
* SAM (F
155,3
=1.72, z=-1.63, P=0.055) , but not to SAM alone (F
155,3
=1.17,
z=1.50, P=0.133). Random factor was not significant for chinstrap penguins (LRT=0.15, P=0.910),
meaning population-level response was homogeneous throughout the WAP. For Gentoo populations,
the probability of decrease was marginally related to catch
y
(F
251,3
=0.76, z=1.47, P=0.090) and catch
y
*
SAM interaction (F
251,3
=1.70, z=-1.75, P=0.085), but not to SAM alone (F
251,3
=0.11, z=0.74, P=0.461), and
random effects were significant (LRT=5.95, P=0.014), therefore population-level variability was
important in the response of Gentoo penguins to fishing catches (Fig. S5). For both chinstrap (Fig. 4a)
and Gentoo (Fig. 4b) probability of decrease in a given year
std
) was constant with increasing fishing
catch during years of positive SAM, but increased with increasing catch during years of negative SAM. In
extreme negative SAM, fishing catches above ≈5 thousand tonnes meant a mean estimated probability
of decrease above 75% for both species (Fig. 4).
Figure 4. Estimated probability (trend lines) ±
standard deviation (shaded area) of chinstrap
Pygoscelis antarcticus (a) and gentoo P. papua (b)
penguins having a negative standardized
population growth rate as a response to fishing
catch within 30-km radius around colonies during
years of contrasting Southern Annular Mode SAM
values: negative (solid red line) and positive
(dashed blue line). The ‘sjPlot’ R package through
the function ‘plot_model’ allows visualizing the
estimated mean response to the extreme values of
the interacting variable, in this case maximum and
minimum SAM values.
Discussion
In the last two decades, krill catches have increased consistently near penguin colonies in the
Bransfield and Gerlache straits during chick-rearing and non-breeding periods, whereas in the Drake
Passage and Elephant Islands catches have remained stable or mostly decreasing. These patterns reflect
the southward expansion experienced by the fleet during the last decade, mentioned by previous works
(Nicol et al. 2012; Santa Cruz et al. 2018; Krüger 2019). Our findings also indicated that the relation
between the standardized penguin growth rate and cumulative fishing catch was contrasting depending
on SAM conditions. In this manner, in positive SAM values, the range of the probability of decreasing
varied largely, while in negative SAM values, there was a consistent rise in the probability of decreasing
for both chinstrap and gentoo penguins when fishing catches near colonies was very high (>≈5000 t).
Moreover, the additional effect over krill recruitment caused by the decrease in sea ice coverage, due to
the key role played by this factor for the development of krill larvae, coupled with the increase in krill
catches in the areas near penguin colonies could generate a much more vulnerable scenario for these
species during the breeding season (i.e. Trivelpiece et al. 2011). Recovery of baleen whale populations
also have been suggested out as a potential explanation for current observed trends in penguin
populations, as whaling in the last century would have allowed for an increase in krill availability, the
krill surplus hypothesis, but so far, studies dealing with that hypothesis did not find solid evidences and
suggested environmental variability as more important to changes in krill biomass (Fraser et al. 1992;
Surma et al. 2014). Previous studies mentioned potential impacts of krill fishery on penguin populations
(i.e. Trivelpiece et al. 2011), and a recent paper (Watters et al. 2020) reached conclusions similar to ours
by applying a different method and evaluating population data at two sites. Our study, to our best
knowledge, is the first to reveal the effect of climate change and krill fishery on penguin population
declines looking explicitly at multi-population trends on the scale of the whole Antarctic Peninsula. It is
worth mentioning that a previous work by Che-Castaldo et al. (2017) tested whether krill fishery could
have an effect on Adelie penguin population dynamics; however, the spatial scale of the fishing data
used was too coarse to allow detecting strong local effects.
Considering what it is mentioned above, the next step from now on would be to move towards
the implementation of a new krill fishery management strategy (see further below), which could
consider new elements that are not currently included. Elements such as regular biomass estimations
and identification of the spatial scales of the impact of krill fishery on penguins, thus, identifying where
higher catches would have higher impact on penguins and other predators, and distributing catches
accordingly.
Risk of competition with krill fishery
Recent changes of the spatial distribution of the krill fishing fleet in the WAP (Santa Cruz et al.
2018; Trathan et al. 2018; Krüger 2019) can be linked to the general trend of decreasing winter sea-ice
extent and duration that has been reported for the area (Parkinson 2019). Increased ice-free conditions
allowing trawlers to continue their activities after the end of the Austral summer (Nicol et al. 2012)
explains the increasing catches near penguin colonies during the non-breeding season. While sensibility
of penguins to climate change is well known (Casanovas et al. 2015; Che-Castaldo et al. 2017), the
interaction of climate change with increasing catches may have a synergistic detrimental effect on
penguins. According to Doddridge and Marshall (2017), negative SAM anomalies precede higher
temperatures, low sea-ice and low krill productivity in the Southern Ocean, particularly in Antarctic
Peninsula, with effects being cascaded throughout the whole food web (Dahood et al. 2019).
Carry-over effects of the potential competition of penguins with the krill fishery during the non-
breeding season are still unknown, but given our results, cumulative catches within 30 km from colonies
seemed to impact negatively both Pygoscelis species in years when sea-ice was low. Although chinstrap
penguins tend to disperse from breeding grounds, it is evident that there is a large variability and part of
the population may remain nearby the breeding area (Trivelpiece et al. 2007; Hinke et al. 2015; Hinke et
al. 2017). On the other hand, Gentoo penguins tend to remain closer to the breeding grounds during
winter (Wilson et al. 1998; Thiebot et al. 2011; Hinke et al. 2017).
Winter distribution of fledgling and
immature stages of both penguin species is still unknown for most populations, but evidence suggests
penguin recruitment is an important population parameter explaining penguin population decrease in
the WAP, which has been also linked to decreased recruitment of krill (Hinke et al. 2007; Trivelpiece et
al. 2011; Atkinson et al. 2019). Penguin populations have been potentially affected by the krill fishery
(this study, Watters et al. 2020) in zones where intense fishing occurred in recent years (i.e. Santa Cruz
et al. 2018) which overlapped with important krill nursery and krill recruitment areas (Perry et al. 2019)
in the Bransfield and Gerlache straits.
We propose two hypotheses to explain our findings. Firstly, krill densities are declining and their
distributions are contracting southward (Atkinson et al. 2019), therefore, increased fishing activities in
areas with reduced krill availability increase competition between penguins and fishery, particularly in
periods of low productivity. Secondly, increased catches on years with low krill productivity decrease
availability of krill to penguin populations. Krill population rises and falls from year to year, with
potential recruitment cycles lasting five to six years (Reiss et al. 2008), mostly driven by food
competition (Ryabov et al. 2017; Walsh et al. 2020). Summer melting of sea ice accumulated during
winter can boost local productivity in the WAP (Eveleth et al. 2017b; Eveleth et al. 2017a), therefore,
during years of negative SAM (when winter sea ice cover is lower) krill could experience population
limitation due to low availability of food, and consequently low recruitment (i.e. Flores et al. 2012;
Meyer 2012). Under this scenario, increased fishing catches could mean a krill shortage for penguins in
the next breeding season if the krill caught is not recovered. The fishery would be extracting biomass
cumulatively from the same population before new adults arrive, temporarily depleting resources for
penguins.
Management consequences
CCAMLR manages the krill fishery following the principle of rational use of the marine living
resources, which implies both the precautionary and ecosystem-based approach. Since 1991 CCAMLR
has established catch limits for area 48 (WAP and Southern Scotia Arc), oftentimes updated depending
on the availability of new biomass estimations. So far, the current catch limit for area 48 is 620,000
tonnes (known as the trigger level, a value adopted entirely based on the previous highest catches).
Thereafter, trying to avoid potential concentration of the catches in small areas, and based on the
biomass distribution, the trigger level was split proportionally among the subareas, setting 155,000
tones for area 48.1 and 279,000 tones for subarea 48.2 (further details of this process see Nicol and
Foster 2016). Unfortunately, the catch limit is fixed and does not vary according to the variability of the
krill population, being particularly problematic in years of low productivity (i.e. environmentally-
impacted krill recruitment, Thorpe et al. 2019). Catch limits should be established based on seasonal krill
abundance estimates that also must include predator demands. For instance, CCAMLR is pursuing a
feedback management of krill fishery that would be achieved through an ecological risk assessment (i.e.
Trathan et al. 2018; Warwick-Evans et al. 2018. Lowther et al. in review) quantifying the amount of krill
required from top-predators on a spatial grid; fisheries would use that information plus continuously
updated information on krill density to guide when, where, and how much they should fish. Our results
support the need for implementing such kind of management approach, meaning that in years when
krill density is lower, catch limit should be lower than the currently being used. In addition, an increasing
concern is that precautionary catch limit was calculated for a regional scale, but our results as many
others (Hill et al. 2016; CCAMLR 2018; Santa Cruz et al. 2018; Krüger 2019) demonstrated that the
fishery is not a randomly distributed activity, rather catches occurs in a highly concentrated manner,
especially in Bransfield and Gerlache straits. This, coupled with the new evidences of the impacts
produced by climate change and krill fishery on penguin populations (Watters et al. 2020, this study),
creates concerns about whether the precautionary catch limit is still precautionary under the current
scenario.
CCAMLR is pursuing the implementation of a Marine Protected Area network as a tool to
protect Antarctic marine ecosystems and manage human activities, including fisheries (Brooks et al.
2016; Coetzee et al. 2017). In this regard, a large MPA in the Domain 1 (WAP) was proposed recently by
Argentina and Chile parties (
https://www.ccamlr.org/en/ccamlr-38/25-rev-1),
aiming to provide extra
protection for several conservation objectives, including krill; however, despite many countries have
strongly supported the proposal, a few have expressed their concerns voting against its adoption:
since
decision-making in the Commission is based on consensus, the proposal has not been adopted. The
current proposal includes general protection zones that precisely encompass the major locations of the
synergistically climate and fishery affected penguin colonies (and other krill-predators). Particularly,
around SOI, South Shetland Islands and the Gerlache strait, where evidences support that closures to
krill fishing would be beneficial for krill predators if fishing pressure increases (Klein and Watters 2020).
Examples of MPAs that allowed for increases in stocks of harvested species are abundant (Duffy et al.
2016; Chirico et al. 2017; Sala and Giakoumi 2018), even producing better fishing yields (Lynham et al.
2020). Therefore, it is a strategy with potential to not only protect top-predators and its resources, but
also to allow for a long-term fishery in the WAP.
CCAMLR has recognized the need for a more precautionary and dynamic approach taking into
account contemporary changes in the WAP, and its currently working on the development of a new
approach of the management of the krill fishery (CCAMLR 2019). Evidence such as the presented here
along with other new research and new monitoring plans will be crucial for implementation of a more
dynamic management strategy of the krill fishery that ensures the protection of krill dependent
predator under a changing environment in this unique ecosystem.
Acknowledgements
The authors would like to thank the CCAMLR Secretariat and co-originators/owners for
providing data access on krill fishery. The authors acknowledge the important contribution of the
MAPPPD resources towards the increasing knowledge of penguin species ecology. This study benefited
from the “Marine Protected Areas program” of the Instituto Antártico Chileno.
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Figure S1. Summary of number of breeding pair counts for chinstrap (Pygoscelis antarctius) and
gentoo (P. papua) penguins breeding along the western Antarctic Peninsula.
Figure S2. Example of variability of Antarctic Krill (
Euphausia superba
) fishing catch and sea
ice cover overlapped by the 30km radius around penguin breeding colonies in the Western
Antarctic Peninsula during the year 2010. Data accumulated by period of Pygoscelid penguins
breeding cycle, approximately as: Chick-Rearing (January to March), Non-breeding (April to
September) and Early Breeding (October to December).
Figure S3. Seasonal frequency distribution of Fractional Sea Ice Cover (FRSIC), Open Water
Sensible Heat Flux (HFLUX) and Sea Level Air Temperature (TLML) in the Western Antarctic
Peninsula, and Pearson Correlation (Cor) for each pair of variables.
Figure S4. Temporal variation of the standardized population growth rate for chinstrap
(
Pygoscelis antarctius
) and gentoo (
P. papua
) penguins breeding along the western Antarctic
Peninsula. Data is for several populations in time, therefore populations are repeated in time, and
this image does not reflect global trends of the species in the Western Antarctic Peninsula. The
black solid line is a linear trend and the dashed grey is a loess fit line.
Figure S5. Random effect of a Generalized Linear Mixed Model testing the probability of gentoo
penguin population decrease between years as a response to Antarctic Krill (
Euphausia superba
)
fishing and winter Southern Annular Mode SAM in the Western Antarctic Peninsula. Colony
level intercept ± standard deviation. Likelihood ratio test LRT=5.96, P=0.015. For colony names
check the MAPPPD application (http://www.penguinmap.com/), and colony geographical
positions on Supp. Table 1.
... Because the area of the Bransfield Strait is an area where smaller/younger krill occur, fishing there will certainly have a negative impact not only on Adélie penguin populations, but also on their congeners. Current management of krill resources in the Southern Ocean does not consider interannual changes in krill abundances resulting from, for example, differences in the winter sea ice cover, and Krüger et al. 55 reported that very high krill catches during years of low ice resulted in lower reproductive success of penguins in that region and that fisheries with a climatic fluctuations may have a synergistic effect. Considering that they are also affected by additional stress factors in the form of climate change and, as a result, the progressive reduction in sea ice, the disappearance of colonies in the northern areas of the South Shetland Islands is already being observed 56 ; however, new colonies of chinstrap penguins are simultaneously being observed, for example, in the areas of Deception Island and Low Island, as well as along the Danco Coast and David Coast 6 . ...
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... The krill fishery has grown substantially in recent decades, and has temporally and spatially concentrated its effort into small areas that overlap with krilldependent predators (Santa Cruz et al., 2018;Watters et al., 2020). Empirical observations indicate that, given natural variability in the system, such concentrated catches pose plausible risks to predator populations (Watters et al., 2020;Krüger et al., 2021). The current krill fishery management strategy is not adaptable based on changes in the ecosystem and has not been updated for over a decade. ...
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The panzootic high pathogenicity avian influenza strain H5N1 has decimated wildlife populations around the globe over the last three years, but has only reached Antarctica in the last few months. While some attention has been brought to the plight of birds in the region, almost none has been paid to Antarctic marine mammals. Seals and sea lions in particular are more vulnerable to this strain of avian flu, H5N1, than any before it. Within the last few months this virus has reached the Antarctic Peninsula putting millions of seals at risk, in particular, the imperiled South Shetland Antarctic fur seal. Since the beginning of the panzootic, many lessons have been learned by conservation managers, and a great deal of research has been done, particularly across South America in the last year. We briefly contextualize these pertinent issues and findings, provide timely guidance on vetted best practices to field practitioners and tour operators, and emphasize high-priority recommendations for Antarctic conservation managers for immediate next steps.
... On the other hand, in the terrestrial environment, the increase in snowfall can reduce the available nesting sites and breeding success (e.g., Boersma, 2008;Cimino et al., 2019;Hinke et al., 2012;Juáres et al., 2015), which could impact on the breeding population size . Moreover, this scenario further compounds when considering the effects of krill fishing during both breeding and non-breeding periods (Hinke et al., 2017a;Krüger et al., 2021;Watters et al., 2020). ...
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... In marine ecosystems, these climatic events described above can drastically change environmental conditions, with direct or indirect impacts on the abundance and distribution of top predator species, such as birds and marine mammals (Oliveira et al. 2006(Oliveira et al. , 2009Bost et al. 2015;Atiknson et al. 2019;Krüger et al. 2021). Acute and long-term exposure to warmer waters, for example, can impact species distribution through direct physiological and indirect ecological pathways (O'Connor et al. 2009). ...
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"Acesso ao artigo: https://link.springer.com/article/10.1007/s00300-023-03206-9 " This study presents the pattern of occurrence of sub-Antarctic fur seals (SAFS), Arctocephalus tropicalis, in the southern Brazilian coast and evaluate its association with climatic variability and anomalies in the concentration of chlorophytes and sea surface temperature in the reproductive colonies of Gough and Tristan da Cunha Islands. Date, sex, and age class of 254 stranded SAFS recorded between 1992 and 2013 were analyzed. Representative indexes of the patterns of climatic variability and environmental variables were obtained between four and fve months before the records, the assumed interval of displacement for species between their closest breeding colonies and the southern Brazilian coast. The species was observed in southern Brazil between May and November each year, and most individuals were adult males. The records of SAFS on the southern Brazilian coast were associated with low concentration of chlorophytes interacting with negative sea surface temperature anomalies, and positive events of South Annular Mode, South Atlantic Ocean Dipole and Indian Ocean Dipole. Climatic variability is infuencing the ecology SAFS, because it afects the environmental factors, that act as a driver of dispersion of the species. These variables had been interacting together in the region of the breeding colonies, and possibly during the fur seals’ journey towards the Brazilian coast. Considering the current scenario of global climate change, we expect that SAFS will continue to disperse to areas beyond their regular distribution, not only in the direction of the coasts of southern continents, but also further south, towards higher latitudes.
... With reduced prey availability, changes in foraging behavior and reproductive success of penguins are expected, such as those already observed by Cimino et al. (2023) on Anver Island in years with early sea ice retreat and by Salmerón et al. (2023) associated with winter sea ice scarcity and likely deepening of the mixed layer resulting from stronger winds. Recently, it has been suggested that the coupling of climatic events and fisheries may exacerbate local effects on krill availability, affecting penguin breeding populations (Watters et al. 2020;Krüger et al. 2021). Thus, in the WAP, identifying local foraging hotspots for krill-dependent predators, might be crucial for determining areas of ecological importance that require consideration in management measures. ...
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Adélie penguins are considered indicators of Antarctic ecosystems. Their populations have declined by more than 50% in the West Antarctic Peninsula, an area strongly affected by global warming, and that concentrates most of Antarctic krill harvesting. The use of high-resolution data to identify foraging areas regularly used by krill predators could provide valuable information for current discussions on the development of small-scale management and conservation measures for this region. We used information on the foraging trips of 57 individuals breeding in King George Island, tracked over 2019/2020, 2020/2021 and 2021/2022 breeding seasons during the chick-rearing stage, to identify their key foraging areas. Using an accelerometry-based latent behavioral analysis approach, we identified an area within 10 km of the colony consistently used by over 60% of the population throughout and between seasons. We also observed that almost 20% of the population uses the area near a seamount located 35 km from the colony for foraging, mainly during the late guarding phase when chick energy demands are highest or the effects of prey depletion might become more evident. The distances and duration of trips and the area explored increased as the season progressed and varied between seasons, consistent with annual differences in krill availability observed in the region. Foraging dives comprise roughly 40% of the dives performed during foraging trips, irrespective of the stage of the chick-rearing period, or the season analyzed. Our results emphasize the need to understand how variability in environmental conditions, prey availability, and energetic demands affect how predators use space, and the role that bathymetric features might play in providing reliable foraging grounds, for penguins, in a rapidly changing region.
... During the last decade, krill catches have doubled (SC-CAMLR, 2021). At the same time, there is a growing concern that global warming as well as the post-exploitation recovery of predator populations such as seals and whales (sensu the 'krill surplus hypothesis') might erode the ecological basis of krill as an exploitable resource with cascading effects through the ecosystem over the long term (Krüger et al., 2020;Watters et al., 2013Watters et al., , 2020. This is a concern also shared by the fishing industry, and it is expected that updates of the CCAMLR 2000 Krill Synoptic Survey of Area 48 coverage will provide feedback on ecosystem trends that will aid the evaluation of impacts on krill from long-term global trends, including the sustainability of its exploitation. ...
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The objective for this research was twofold: (i) to provide updated estimates of the biomass and distribution of krill in the Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR) Statistical Area 48, and (ii) to develop knowledge on the marine environment essential for the implementation of an adaptive management system for Antarctic krill. Survey design followed the transects of the CCAMLR 2000 Krill Synoptic Survey of Area 48 and of national surveys performed in the South Atlantic sector of the Southern Ocean by the People's Republic of China, the Republic of Korea, Norway, the United Kingdom and the United States of America. The survey also focused on high krill-density areas and employed state-of-the art methods and technology. The future management system will need standardised acoustic data from fishing vessels to be collected, processed and reported in near real-time as a measure of the available prey field. This information can be integrated with finer-scale knowledge of krill predator feeding strategies and updated through specific scientific studies at regular (multi-year) intervals. To aid such implementation and to encourage the development of future management tools, the survey took place during the austral summer of 2018/19. The work was coordinated by Norway and involved collaborative international efforts of six survey vessels provided by the Association of Responsible Krill harvesting companies Krafft et al.
... Catches taken by the commercial krill fishery around the northern Antarctic Peninsula and SSI have increased in recent decades to the highest levels ever recorded (Nicol et al. 2012, CCAMLR 2020. Further, the fishery is concentrating effort in smaller geographical areas over shorter time periods, which may limit the performance and population growth of krill-dependent predators via competition , Krüger et al. 2021. ...
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... Modern monitoring data also show that Adélie penguin breeding is closely linked to temperature (Croxall et al., 2002;Riaz et al., 2020;Watanabe et al., 2020), sea ice extent/concentration (Iles et al., 2020;Smith et al., 1999), and polynya size (Mezgec et al., 2017;Thatje et al., 2008). As crucial atmospheric-oceanic circulation patterns in Antarctica, ENSO and SAM also produce indispensably direct (e.g., winds) or indirect (e.g., polynya, ice cover, and SST) impacts on penguin ecology (i.e., survival rate and breeding; Croxall et al., 2002;Forcada and Trathan, 2009;Krüger et al., 2021;Wilson et al., 2001), especially in the Antarctic Peninsula (Barbraud et al., 2012;Henley et al., 2019;Hinke et al., 2014). Although previous studies have discussed the potential impacts of ENSO and SAM on modern penguin ecology based on observation data in Antarctica Peninsula and east Antarctica, they rarely cover the long-term influences of these circulations on penguin populations using geological proxies from sediments, particularly in the Ross Sea region (Forcada and Trathan, 2009). ...
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The atmospheric-oceanic circulation patterns, especially for the Southern Annular Mode (SAM) and El Niño-Southern Oscillation (ENSO), two major atmospheric circulation patterns in the Ross Sea region, have been reported to greatly affect climate and marine ecosystems. However, from a historical perspective, the influence of atmospheric-oceanic circulation patterns on penguin populations remains unclear in this region. Here, we analyzed two lacustrine sediment cores collected from abandoned penguin colonies at Inexpressible Island, Ross Sea, Antarctica, and by applying alternative geochemical indices, successfully reconstructed the populations of the Adélie penguins (Pygoscelis adeliae) over the past ∼1500 years. We found that penguin population peaked during 750–1350 AD at Inexpressible Island, potentially due to habitat expansion in the warmer climate. After comparing with historical records of penguin populations at Cape Bird, Dunlop Island, and Cape Adare, all were found to have a common increase during the 750-1350 AD period in the Ross Sea. The population trend also coincided with extreme activities of El Niño and SAM (+). We inferred that the SAM-ENSO might promote influxes of Circumpolar and Modified Circumpolar Deep Waters into the Ross Sea. The enhanced influx of nutrient-rich deep water, together with a warmer climate may jointly enhance polynya efficiency and population increase of Adélie penguins. Our study indicates the potentially significant roles of ENSO and SAM in the regulation of Antarctic ecosystems.
... Modern monitoring data also show that Adélie penguin breeding is closely linked to temperature (Croxall et al., 2002;Riaz et al., 2020;Watanabe et al., 2020), sea ice extent/concentration (Iles et al., 2020;Smith et al., 1999), and polynya size (Mezgec et al., 2017;Thatje et al., 2008). As crucial atmospheric-oceanic circulation patterns in Antarctica, ENSO and SAM also produce indispensably direct (e.g., winds) or indirect (e.g., polynya, ice cover, and SST) impacts on penguin ecology (i.e., survival rate and breeding; Croxall et al., 2002;Forcada and Trathan, 2009;Krüger et al., 2021;Wilson et al., 2001), especially in the Antarctic Peninsula (Barbraud et al., 2012;Henley et al., 2019;Hinke et al., 2014). Although previous studies have discussed the potential impacts of ENSO and SAM on modern penguin ecology based on observation data in Antarctica Peninsula and east Antarctica, they rarely cover the long-term influences of these circulations on penguin populations using geological proxies from sediments, particularly in the Ross Sea region (Forcada and Trathan, 2009). ...
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Winter sea-ice conditions are considered important for Antarctic krill Euphausia superba survival and recruitment, yet few broad-scale longitudinal studies have examined the underlying relationships between winter conditions and krill recruitment. We used data from a 4 yr winter study of krill condition (lipid content), diet (stable isotopes and fatty acids), and length distributions around the northern Antarctic Peninsula to examine relationships among environmental variables (annual sea-ice cover, water column chlorophyll a [chl a] , and upper mixed-layer water temperature), the condition and diet of krill, and recruitment success the following year. Diet indicators (lipid content, δ ¹⁵ N, δ ¹³ C, and the fatty acid ratios 16:1n-7/18:4n-3 and 18:1n-9/18:1n-7) in post-larvae were consistent among years regardless of sea-ice cover, suggesting that post-larval krill do not rely on sea-ice resources for overwinter survival. Diet indicators in larvae were more variable and suggest that larvae may feed on sea-ice resources when they are available but can still persist in the water column when they are not. Principal component analysis between environmental variables and diet indicators showed that water-column chl a was the only variable that significantly affected diet, regardless of annual changes in sea-ice cover. Extensive winter ice in one year did not translate into successful recruitment the following year. Krill demonstrate a high degree of flexibility with respect to overwinter habitat and diet, and the degree to which sea ice is important during different times of year and at different life stages may be more complex than previously thought.
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Low catch limits for forage species are often considered to be precautionary measures that can help conserve marine predators. Difficulties measuring the impacts of fisheries removals on dependent predators maintain this perspective, but consideration of the spatio-temporal scales over which forage species, their predators, and fisheries interact can aid assessment of whether low catch limits are as precautionary as presumed. Antarctic krill are targeted by the largest fishery in the Southern Ocean and are key forage for numerous predators. Current krill removals are considered precautionary and have not been previously observed to affect krill-dependent predators, like penguins. Using a hierarchical model and 30+ years of monitoring data, we show that expected penguin performance was reduced when local harvest rates of krill were ≥0.1, and this effect was similar in magnitude to that of poor environmental conditions. With continued climate warming and high local harvest rates, future observations of penguin performance are predicted to be below the long-term mean with a probability of 0.77. Catch limits that are considered precautionary for forage species simply because the limit is a small proportion of the species’ standing biomass may not be precautionary for their predators.
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Significance A newly completed 40-y record of satellite observations is used to quantify changes in Antarctic sea ice coverage since the late 1970s. Sea ice spreads over vast areas and has major impacts on the rest of the climate system, reflecting solar radiation and restricting ocean/atmosphere exchanges. The satellite record reveals that a gradual, decades-long overall increase in Antarctic sea ice extents reversed in 2014, with subsequent rates of decrease in 2014–2017 far exceeding the more widely publicized decay rates experienced in the Arctic. The rapid decreases reduced the Antarctic sea ice extents to their lowest values in the 40-y record, both on a yearly average basis (record low in 2017) and on a monthly basis (record low in February 2017).
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The pelagic ecosystems of the Western Antarctic Peninsula are dynamic and changing rapidly in the face of sustained warming. There is already evidence that warming may be impacting the food web. Antarctic krill, Euphausia superba, is an ice-associated species that is both an important prey item and the target of the only commercial fishery operating in the region. The goal of this study is to develop a dynamic trophic model for the region that includes the impact of the sea-ice regime on krill and krill predators. Such a model may be helpful to fisheries managers as they develop new management strategies in the face of continued sea-ice loss. A mass balanced food-web model (Ecopath) and time dynamic simulations (Ecosim) were created. The Ecopath model includes eight currently monitored species as single species to facilitate its future development into a model that could be used for marine protected area planning in the region. The Ecosim model is calibrated for the years 1996–2012. The successful calibration represents an improvement over existing Ecopath models for the region. Simulations indicate that the role of sea ice is both central and complex. The simulations are only able to recreate observed biomass trends for the monitored species when metrics describing the sea-ice regime are used to force key predator-prey interactions, and to drive the biomasses of Antarctic krill and the fish species Gobionotothen gibberifrons. This model is ready to be used for exploring results from sea-ice scenarios or to be developed into a spatial model that informs discussions regarding the design of marine protected areas in the region.
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High-latitude ecosystems are among the fastest warming on the planet¹. Polar species may be sensitive to warming and ice loss, but data are scarce and evidence is conflicting2–4. Here, we show that, within their main population centre in the southwest Atlantic sector, the distribution of Euphausia superba (hereafter, ‘krill’) has contracted southward over the past 90 years. Near their northern limit, numerical densities have declined sharply and the population has become more concentrated towards the Antarctic shelves. A concomitant increase in mean body length reflects reduced recruitment of juvenile krill. We found evidence for environmental controls on recruitment, including a reduced density of juveniles following positive anomalies of the Southern Annular Mode. Such anomalies are associated with warm, windy and cloudy weather and reduced sea ice, all of which may hinder egg production and the survival of larval krill⁵. However, the total post-larval density has declined less steeply than the density of recruits, suggesting that survival rates of older krill have increased. The changing distribution is already perturbing the krill-centred food web⁶ and may affect biogeochemical cycling7,8. Rapid climate change, with associated nonlinear adjustments in the roles of keystone species, poses challenges for the management of valuable polar ecosystems³.
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In the Southern Ocean, the at-sea distributions of most predators of Antarctic krill are poorly known, primarily because tracking studies have only been undertaken on a restricted set of species, and then only at a limited number of sites. For chinstrap penguins, one of the most abundant krill predators breeding across the Antarctic Peninsula, we show that habitat models developed utilizing the distance from the colony and the bearing to the shelf-edge, adjusting for the at-sea density of Pygoscelis penguins from other colonies, can be used to predict, with a high level of confidence, the at-sea distribution of chinstrap penguins from untracked colonies during the breeding season. Comparison of predicted penguin distributions with outputs from a high-resolution oceanographic model shows that chinstrap penguins prefer nearshore habitats, over shallow bathymetry, with slow-flowing waters, but that they sometimes also travel to areas beyond the edge of the continental shelf where the faster-flowing waters of the Coastal Current or the fronts of the Antarctic Circumpolar Current occur. In the slow-moving shelf waters, large penguin colonies may lead to krill depletion during incubation and chick-rearing periods when penguins are acting as central place foragers. The habitats used by chinstrap penguins are also locations preferentially used by the commercial krill fishery, one of the last under-developed marine capture fisheries any- where on the planet. As it develops, this fishery has the potential to compete with chinstrap penguins and other natural krill predators. Scaling our habitat models by chinstrap penguin population data demonstrates where overlap with the fishery is likely to be most important. Our results suggest that a better understanding of krill retention and krill depletion in areas used by natural predators and by the krill fishery are needed, and that risk management strategies for the fishery should include assessment of how krill movement can satisfy the demands of both natural predators and the fishery across a range of spatial and temporal scales. Such information will help regional management authorities better understand how plausible ecosystem-based management frameworks could be developed to ensure sustainable co-existence of the fishery and competing natural predators.
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Krill fisheries at Antarctica have concentrated their effort on the Western Antarctic Peninsula and Scotia Arc (WAP) in the last decades, following a steady increase in annual catch. Short-term shifts in habitat exploration may have occurred and may be the cause for the increasing catch. I compared habitat use and effort of Krill fisheries at the WAP during summer in the last five years and tested how habitat use and effort reflected in the catch. I detected a trend for an increase in fishing tow duration and depth of fishing, and also fish in deeper and colder waters. On the other hand, I found no association of the catch with the habitat explored, but catch was higher in years when the variability of explored habitat was lower. Finally, I discuss the relevance of these findings under the perspective of fisheries management and conservation of Antarctic Marine ecosystems.