2 Southern Marine Science and Engineering Guangdong Laboratory, Guangzhou 511458, China;
3 Changing Ocean Research Unit, Institute for the Oceans and Fisheries, University of British Columbia, Vancouver V5K0A1, BC, Canada;
4 Department of Ecology and Evolutionary Biology Max Planck, Yale Center for Biodiversity Movement and Global Change, Yale University, New Haven 06501, CT, USA;
5 College of Marine Life Science, Ocean University of China, Qingdao 266003, China;
6 Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China
The impact of global climate change and other environmental problems on the Antarctic continent cannot be ignored (Bargagli, 2008; Turner et al., 2013; Convey and Peck, 2019). Many species have been threatened and record the effects on reproduction, habitat, and even survival (McMahon and Burton, 2005; Grémillet and Boulinier, 2009; Warwick-Evans et al., 2021). In the past few decades, studies on the ecological impacts of environmental change in Antarctica are mostly focused on the Antarctic Peninsula in southwest Antarctica, where the warming trend is the most obvious (Daniels and Lipps, 1982; Barbraud and Weimerskirch, 2001; Clarke et al., 2007; Schofield et al., 2010; Zhu et al., 2020). The research into Prydz Bay-Amery Ice Shelf (Prydz Bay-AIS) mostly focused on the influence mechanism of sea ice melting and Antarctic ocean currents (Williams et al., 2002; Post et al., 2007; Pritchard et al., 2012; Kusahara and Hasumi, 2013). Yet there is still a lack of research on the response of biological ecology to climate change.
Prydz Bay-AIS is one of the hot research areas in the world, where the Davis Station (Australia), Zhongshan Station (China), Law-racovita Base (Australia-Romania), and Progress II Station (Russia) are located nearby. The United States, Australia, France, and other countries have systematically observed the Prydz Bay and its adjacent waters since the 1950s (Zheng et al., 2011; Shadwick et al., 2013). In recent years, a series of international joint research projects have also carried out (Craven et al., 2011; Mangel, 2011). The data obtained from ice cores (Sowers, 2003; Mysak et al., 2008), marine sediments (O'Brien and Leitchenkov, 1997; Galton-Fenzi and Coleman, 2007), lake sediment core (Wagner et al., 2004; Hultzsch, 2007), have been successfully used to rebuild the history of environmental change in east Antarctica in different geological periods. However, the research on the mechanism of climate change based on organisms, especially for Antarctic fish and krill, is still blank.
The water mass near Prydz Bay-AIS is complex, which is closely related to the primary productivity of Antarctic marine ecosystem, Antaectic krill (Euphausia superba), Adelie penguin (Pygoscelis adeliae), seabirds, cetaceans, and other organisms(Amos, 1984; Harris and Woehler, 2004; Southwell, 2017; Bestley et al., 2018). Prydz Bay-AIS provides abundant food for all trophic species. In addition, AIS are the habitat and breeding ground for a variety of organisms (Ross and Quetin, 1991; Stirling, 1997; Meyer et al., 2002). The polynyas are also significantly correlated with the size of the breeding ground of the relevant biological populations (Arrigo and van Dijken, 2003). Therefore, it can be seen as a key area to ensure the normal operation of Antarctic ecosystem (Tynan, 1998; Dehnhard et al., 2020). Meanwhile, the change of fallback time and range in AIS will cause ※mismatch§ of energy and food supply at all nutrient levels, and it will also lead to the changes in low reproduction rate, low abundance and distribution area (Cherel, 2008; Jenouvrier et al., 2020). Hence, it is of great significance to study the response of biological and ecological to climate change in Prydz Bay-AIS. Furthermore, it can be used for planning Marine Protected Areas (MPAs), developing the policies for the protection of Antarctic marine biological resources and enriching scientific reference materials, which is also the main objective of this study.
The environment around Prydz Bay and AIS is changing rapidly, and the observation is difficult. The cost of collecting species abundance and distribution data is very high (Croxall and Nicol, 2004; Demer, 2004). Therefore, it is necessary to select a species distribution model to evaluate the spatiotemporal variation of fish species around the Prydz Bay-AIS as accurately as possible.
Considering the uncertainty and limitation of the prediction model, this research chose to use Dynamic Bio-climate Envelopment Model (DBEM). DBEM has been widely used in calculating the reaction of marine and terrestrial organisms to climate change (Mika, 2008; Cheung et al., 2010; Torres et al., 2013; Tanaka and Chen, 2016). In this model, the preference of species for various environmental parameters is determined by quantitative calculation, and the change of species biomass is quantified (Cheung et al., 2010, 2015). It overcomes the difficulties that other models cannot perform uncertainty analysis, and can only study a single species, a single scenario, or it is difficult to simulate changes in habitat distribution. The model takes the average of relative abundance of species life cycle in recent decades as an indicator to measure the current spatial geographical pattern of species. The calculation data is from Sea Around Us (Cheung et al., 2008; www.seaaroundus.org ). The required input data and habitat information comes from Fish Base (www.fishbase.org).
Driven by RCP 2.6, RCP 8.5, and three earth system models (see Zhu et al., 2020 for the specific differences of GFDL, IPSL, and MPI), this research predicted the future range of 6 Antarctic representative species in the Prydz Bay-AIS from 1970 to 2060, so as to assess the extent to how much the marine ecosystem is disturbed by climate change. The global catch data is from the United Nations Food and Agriculture Organization (FAO). The environmental data of six Antarctic representative species are from Fish Base (www.fishbase.org), Sea Life Base (www.sealifebase.org), ※sea around us§ project (www. seaaroundus.org), and marine biogeographical information system (http://iobis.org); sea surface temperature observation data is from the sea ice and sea surface temperature data set of Met Office Hadley Center (HadISST2) (Zhu et al., 2020).2 MATERIAL AND METHOD 2.1 Study area and model
Prydz Bay (67°~45'S-69°~30'S, 70°~E-80°~E) is the third largest bay on the Antarctic continent. AIS (68.5°~S-70°~S, 70°~E-74°~E) is at the south of Prydz Bay (Fig. 1). It is connected to the Lampert Glacier, and it is the largest Ice Shelf in the southeast which has an area about 3×104 km2. Fourteen percent of the ice in the southeast reaches the sea through the AIS. On the east and west sides of Prydz Bay is Princess Elizabeth Land and Mac. Robertson Land respectively, in the northeast is Cape Darnley, the total area of the gulf is about 6×104 km2. Four Ladies Bank is located in the northeast of the bay mouth, and frame bank is located in the northwest. The two shoals form the inner bay area, which is the main exchange between the bay and the outside.2.2 DBEM
Close et al. (2006) proposed an algorithm to predict the spatiotemporal changes of each species from 1970 to 2000, and Jones et al. (2012) confirmed that the Dynamic Bioclimate Envelope Model (DBEM) has high prediction ability. Cheung et al. (2008) proposed that DBEM provides reasonable predictions for changes in the distribution range caused by climate change, and predicted changes in the abundance range of various organisms around the world on spatial and large temporal scales. DBEM is more reliable because it considers the population dynamics and the diffusion of young and adult fish. DBEM is selected in this study because of its significant advantages in solving the problem of multi species distribution change. Under different climate change scenarios, it can quantify the spatiotemporal changes of multi species population by identifying species* environmental preferences. DBEM is a rule driven database based method, which can automate the process of model construction and evaluation, and make effective use of many global databases.2.3 Measuring range shift
Given the slow growth rate and unique biology of six Antarctic representative species, Antarctic silverfish (Pleuragramma Antarctica), mackerel icefish (Champsocephalus gunnari), spiny icefish (Chaenodraco wilsoni), grey rockcod (Lepidonotothen squamifrons), blunt scalyhead (Trematomus eulepidotus) and Antarctic krill (Euphausia superba) were used as study species. According to the output of the model, the movement distance of the population gravity center in a certain period of time is calculated through the relative movement of the species distribution gravity center. For the research fish, the calculation method of latitudinal centroid (LC) is as follows:
where Li is the latitude coordinate of the center of the I geographical unit, and Abdi is the relative abundance of the Antarctic fishes. The relative abundance is the weighted average of marine organisms in every 30'℅30' geographical unit; n is the sum of species in Prydz Bay-AIS.
Then, the difference between the latitude center of mass between the forecast year and the reference year (DC) is calculated in kilometers (km):
where y1 is the forecast year and y2 is the reference year. The constant 6 378.2 is the orbital radius (km) on the equatorial plane. The rate of change among different species was calculated based on the slope of change from 1970 to 2060.
The Mean Temperature of Relative Abundance (MTRA) was used as the index of species combination change. The MTRA was calculated based on the average inferred temperature preferences in the literature of Cheung et al. (2013):
Ti: the temperature preference median of species i (℃); n: number of species.3 RESULT
Deterministic models and a series of sensitivity tests were used to preliminarily estimate the possible impact of climate on the future trend of population change. By default, the environmental characteristics of the study area were consistent and the distribution of fish species and krill was balanced. The median distribution of the preferred temperature of the six Antractic representative species is from -2 ℃ to 2 ℃ (Fig. 2). The median of the preferred temperature and the scope of the preferred temperature quantiles (based on the temperature of each species at 5% and 95% of the cumulative predicted relative abundance) showed a positive quadratic function (Fig. 3) (P=0.320 9, R= 0.050 6). The results show that the six species had strong response to the change of seawater temperature.
Under three earth system models and two climate emission scenarios, the simulation results of three earth system models show that the sea surface temperature (SST) and sea bottom temperature (SBT) show an upward trend during 1970-2060 (Fig. 3). However, the increase of SBT in RCP 8.5 (GFDL= 0.036 ℃/decade; IPSL=0.053 ℃/decade; MPI= 0.046 ℃/decade) was significantly larger than that in RCP 2.6 (GFDL=0.028 ℃/decade; IPSL=0.043 ℃/ decade; MPI=0.039 ℃/decade) (Fig. 3). If the simulation results of the three models are integrated, the SST increases at a rate of 0.007 ℃ and 0.012 ℃/decade under two scenarios, respectively (Fig. 3). The rising rates of SST and SBT east of 70°E and north of 70°S in Prydz Bay-AIS were more significant than those in the rest of the surrounding waters (Figs. 4-5).3.1 Abundance and distribution changes
Using species richness as an indicator, the future spatial and temporal distributions of six Antarctic representative species predicted by the models were calculated under three earth system models (GFDL, IPSL, MPI) and aggregate mean values, as well as under low emission scenarios (RCP 2.6) and high emission scenarios (RCP 8.5) (Fig. 6). The results showed that most species were expected to be stay in the western and northern parts of Prydz Bay-AIS, the ocean area at low latitudes of 70°S.
The relative abundance of species in each geographic unit is predicted according to DBEM, latitude gravity center (LC) is used to quantify the spatial variation of Antarctic representative species under different climate scenarios (Fig. 7). Generally, the changes of the geographical pattern of the species under low emission (RCP 2.6) and high emission (RCP 8.5) scenarios were similar, and the zonal centroid transition of the species studied is expected to shift poleward during 1970-2060 (Fig. 7). Specifically, in 1970-2060, driven by the GFDL, IPSL, and MPI earth system models respectively, the latitudinal centroid of six species is estimated to be 4.24±3.31 km/decade, 6.99±5.25 km/ decade, -3.88±3.71 km/decade moved towards higher latitudes (Fig. 7). Meanwhile, under the RCP 8.5 scenario, the corresponding latitude centroid is expected to move at an average rate of 5.25±4.25 km/decade, 5.25±5.71 km/decade, and -4.42±3.34 km/decade from 1970 to 2060 (Fig. 7). In contrast, in the same period, in RCP 2.6, the average zonal centroid of the three models will move at a rate of 2.13±2.11 km/decade, and in RCP 8.5, it will move at a rate of 5.95± 5.28 km/decade (Fig. 7). This is despite the fact that the overall average distance change rate under the high emission scenario is higher than the expected average velocity under the low emission scenario (P < 0.001 ANCOVA), the general tendency of the predicted longitude and latitude centroid moving toward higher latitudes is the same.
The aggravation of ocean warming drives the change of the biogeographical pattern of Antarctic representative species, and the change of species distribution in the Antarctic marine ecosystem may lead to the change of species composition in Prydz Bay-AIS. The trend of local extinction rate is opposite to local invasion rate. In particular, the output results of IPSL and MPI show that the native invasion rate is expected to be significantly higher in the area west of 75°E in Prydz Bay-AIS than in the area east of 75°E (Fig. 8). At the same time, in all cases, the local extinction rate west of 75°E is expected to be lower than that east of 75°E in Prydz Bay-AIS (Fig. 9).3.2 Variation in abundance
From 1970 to 2060, under RCP 2.6, the mean temperature of the relative abundance (MTRA) of six Antarctic representative species are predicted to increase in the average speed of 0.022 ℃/decade, 0.054 ℃/decade, and 0.055 ℃/decade under GFDL, IPSL, and MPI models, respectively. The average overall change of MTRA under the three models was -0.107 ℃/decade. Under RCP 8.5, it is predicted that the average rate of MTRA of the six species will increase at -0.124 ℃/decade, -0.120 ℃/decade, and -0.123 ℃/decade under three models. The average overall change of MTRA under the three models was -0.122 ℃/decade (Fig. 10). In addition, in the low emission scenario (RCP 2.6) and the high emission scenario (RCP 8.5), the outputs of GFDL and MPI models showed that the species richness in the sea area west of 75°E in Prydz Bay-AIS was significantly higher than that east of 75°E (Fig. 11).4 DISCUSSION
Due to the special geographical location of Prydz Bay-AIS, it is difficult to investigate the long-term changes of the distribution of various species around it. Generally, oceanography or polar survey can only be carried out in a small area where a sample exists, and then infer the overall change of the whole large range according to the results of small-scale spatial sampling.
Many research results show that the impact of climate change on Antarctic sea ice will continue to increase in the future (Liu et al., 2004; Zhang, 2007; Turner et al., 2015). As an environmental factor in DBEM, sea ice changes increase the range of habitat conditions. The variation of population distribution may also be affected by the length of coastline. Historical studies have shown that the displacement direction was the longitudinal temperature gradient rather than the latitude gradient (Pinsky et al., 2013). The results also show that Marine species react to ocean warming by changing their latitude range and depth range (Alley et al., 2003; Hiddink and Ter Hofstede 2008; Cheung et al., 2009), driven by ocean warming, species are forced to move to an area with lower temperature (Figs. 6, 8, & 9). DBEM does not consider the impact of human activities, but overfishing by humans is a key driver of niche change for fish, and young fish in the general community may be more affected, but community changes are also affected by many other factors (Cheung et al., 2007). In addition, in DBEM, the environmental preferences of the species are based on the assumption that their current distribution is in equilibrium with the environment and that the characteristics of the species do not change with the change of environmental conditions. Experimental studies have shown that there may be fixed genetic variability that enables a species to evolve to adapt to warming, while cross-generational adaptation may also be possible for a few studied species.
DBEM has been used in 892 developed marine species and invertebrates that have proved to be representatives of total catch (Cheung et al., 2016). Considering the influence of many factors, there are some uncertainties in DBEM, including the equilibrium hypothesis of current species distribution, and the effects of environmental parameters not considered in the model, such as nutrition and species evolution. The AIS-water and the other complex ocean current systems near Prydz Bay and their changes in polynyas will affect the life history, community structure, and geographic distribution of Antarctic species (Hesse, 1924; Ross et al., 1988; Gille, 2002; Vacchi et al., 2004). However, our prediction model is consistent with recent observations and modeling of warming driven changes in Antarctic representative species (Poloczanska et al., 2013). In the past few decades, With the increase of sea temperature, the potential catch of species has decreased, representative species have changed, and the biogeographic distribution pattern has gradually shifted to the extreme (Jung et al., 2010; Branch et al., 2011; Fossheim et al., 2015; Pershing et al., 2015). As there is no significant difference in the distribution trend of six species resource density obtained by using DBEM in three different earth system models, the analysis results of this study should be robust.
Although the forecast and observation data are not exactly the same in terms of time, it is certain that if effective management is not carried out, Prydz Bay-AIS will face major climate changes in the future (Fig. 12).
A growing number of studies have shown that climate change can seriously threaten Antarctic marine biodiversity, and the accelerating rate of changes in species abundance and spatial geographical pattern driven by climate change will further adversely affect population survival (Root et al., 2003). There is little overlap between the current and predicted ranges for many species. In more severe cases, some species may suffer extinction due to the limited space in which they live, because there may be some limits on the ability of the species to adapt to the new environment, such as Antarctic fishes and krill, which can only move within the range of Antarctica (Rebelo et al., 2010). It may be an effective way to integrate future climate change into the marine biological protection research system. Using spatial analysis methods to protect and manage Antarctic fishes and krill can effectively mitigate the impacts of species diversity and spatial distribution under climate change.
Antarctic fish species such as Antarctic silverfish (Pleuragramma antarctica), mackerel icefish (Champsocephalus gunnari), and spiny icefish (Chaenodraco wilsoni) are common in Prydz Bay-AIS (Kock and Everson, 2003; Kock et al., 2004; Vacchi et al., 2017). Antarctic silverfish is abundant in resources and widely distributed in the continental shelf waters of East Antarctica (La Mesa and Eastman, 2012). Young Antarctic silverfish feed and grow in the ice, which may increase due to the decrease of sea ice extent and seasonal retreat southward of AIS (La Mesa et al., 2015). The analysis of the model output results showed that under the RCP 2.6 scenario, the geographical distribution pattern of Antarctic silverfish population changed, and under both high and low emission scenarios, the local species richness in Prydz Bay-AIS at high 70°S latitude was much lower than that in low 70°S latitude (Fig. 13).
The sea area near Prydz Bay is also covered with ice floes in summer, so the climate is more continental. Although AIS currently shows no signs of disintegration (Doake and Vaughan, 1991; Rott et al., 1996), but the extent of sea ice is also decreasing under the influence of climate change. Scambos et al. (2003) proposed that if AIS experiences a warming trend similar to that occurring on the peninsula, it might collapse within a few decades. The gradual warming of the ocean directly leads to the decrease of krill abundance (Atkinson et al., 2004; Kawaguchi et al., 2010; Fan et al., 2014). Research shows that the distribution of krill moved southward by about 440 km in 90 years, which may be due to ocean warming and the reduction of sea ice cover( Atkinson et al., 2019). We predict that the ocean warming in Prydz Bay-AIS will further aggravate the changes of population phenology, survival and the southward migration of geographical pattern.
In the 1980s, the krill fishery was dominated by the Soviet Union*s large fleet in the South Indian Ocean and Pacific Ocean (zone 58-Prydz Bay-AIS) (Nicol and Endo, 1999). Krill not only dominates the diet of upper trophic predators (Murphy et al., 2016; Lowther et al., 2020), meanwhile, the coastal waters of Prydz Bay are the regular spawning sites of krill (Makarov and Menshenina 1989; Spiridonov, 2010). The habitat change caused by sea ice retreat in winter may be the main driving factor for the decline of krill population (Flores et al., 2012).
The pelagic lifestyle of Antarctic silverfish makes it a major dietary component of the top predators on the Antarctic coast (Eastman, 1985; Williams et al., 1995; Ainley, 2002; Zhu et al., 2020). The Prydz Bay area is one of the breeding areas of Antarctic silverfish (Van de Putte et al., 2010). Antarctic fish species, including grey rockcod and blunt scalyhead, have evolved for millions of years in a stable and cold environment (Policansky, 1994). Therefore, it is predicted that they are very responsive to environmental changes, especially ocean warming (Seebacher et al., 2005; Egginton and Campbell, 2016). In addition, sea ice is shrinking and the ocean temperature is rising, some Antarctic fish species will become extinct, mainly because their habitats will be more and more restricted by the Antarctic continent as the Antarctic moves southward (Cheung et al., 2008).
Since 1970, mackerel icefish (Champsocephalus gunnari) and spiny icefish (Chaenodraco wilsoni)have been the main fishery species (Kock, 2005). Spiny icefish has an important effect in the energy flow between marine predators and prey organisms, and is an important part of Antarctic krill fishery (Kock et al., 2008; Wu et al., 2020). In addition, Antarctic ice fishes are thermophilic animals, and ocean warming will significantly affect their metabolism (Policansky, 1994). Therefore, under RCP 2.6 and RCP 8.5, the local species richness in the high 70°S latitudes of Prydz Bay-AIS are much lower than that in the low 70°S latitudes.
Future climate change will pose a serious threat to the ecology of species now and for decades to come, leading to the change or reduction of species distribution (Wall and Smit, 2005; Reed, 2015). When a species migrates into an environment beyond its ability to adapt, the worst result, in terms of the population, would be the loss of species (Guisan and Thuiller, 2005; Hijmans and Graham, 2006). Climate change has brought great challenges to economic development and social operation (Ding et al., 2021), and rapid changes in the distribution of target representative species will cause setbacks to commercial fisheries. Therefore, it is feasible to expand the research on the biological ecology of species to the research on the potential impact on the economic development of marine fishery, and to formulate policies related to the changes in fishery distribution caused by climate change in the future (Dudley et al., 2021). In the past few decades, Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR) has established the method of perfecting the system in the relevant direction in various proposals, but whether it has been effectively implemented in practice still needs further discussion (Goldsworthy and Brennan, 2021). To protect marine species and ecosystems that pursue the capture of biological resources, it is necessary to ensure that sustainable production and adequate long-term protection are maintained appropriately (Margules and Presey, 2000). Prydz Bay-AIS, as an important ecological part of East Antarctica, should be given priority in the planning and construction of MPA system, so that krill, silverfish, and other biological resources can survive for a long time.5 CONCLUSION
Generally, in each earth system model from 2000 to 2060 under RCP 2.6 and RCP 8.5, the geographic distribution latitude pattern of six representative species outside Prydz Bay-AIS shifted to the pole, while their relative abundance tended to decrease. In addition, the local invasion rate in the west of 75°E of Prydz Bay-AIS was higher than that in the east of 75°E, and the trend of local extinction was opposite to that of local invasion rate. The reason is that the accelerated ocean warming has driven changes in the biogeographic pattern of six species, and the habitat range of krill, silverfish and other species have gradually been restricted. It could further lead to the change of species composition and the reduction of biomass in the Prydz Bay-AIS region.
In this study, we investigated the biogeographic patterns of the changes of six Antarctic representative species under the influence of ocean warming. The results indicate that climate change has affected the biological ecosystem of Prydz Bay-AIS region, and hopes to provide some ecological data for the planning and construction of Marine Protected Areas (MPAs) system in East Antarctica. It turns out that the ocean would continue to warm in the next decade. Therefore, the establishment of Antarctic Marine Protected Areas (AMPA) could be considered as one of the important methods to reduce the damage to the Antarctic marine ecosystem. Since 2012, the proposal of East Antarctica (including 58.4.2 area) has been one of the key topics discussed by CCAMLR. It is recognized by SC-CAMLR as the ※Best available scientific evidence§ at present, and the sponsors believe that they meet the requirements of conservation measure CM91-04. In addition, as a key intermediate species in Prydz Bay-AIS, The Antarctic sliverfish (Pleuragramma Antarctica) has a slow growth and relatively low fecundity. Therefore, when Antarctic silverfish populations suffer a certain amount of damage, recovery would be difficult. If it goes extinct, many high-nutrient species in the Antarctic chain could run out of important food. Antarctic silverfish should be monitored in the protected scientific reference area to record the feeding changes of high-grade fish species caused by the changes in the distribution of bait species, to obtain information about global change. The construction of AMPAs is key to protect the habitat of the Antarctic fishes.6 DATA AVAILABILITY STATEMENT
The data that support the findings of this study are openly available in Science at https://doi.org/10.1126/science.aag2331 (Cheung et al., 2016). The data that support the findings of this study are openly available in FishBase at https://www.fishbase.org, the Oceanic Biogeographic Information System at http://iobis.org, Sea Life Base at https://www.sealifebase.org, and Sea Around Us Project at https://www.seaaroundus.org.
Ainley D G. 2002. The Adélie Penguin. Columbia University Press, New York.
Alley R B, Marotzke J, Nordhaus W D, et al. 2003. Abrupt climate change. Science, 299(5615): 2005-2010. DOI:10.1126/science.1081056
Amos A F. 1984. Distribution of krill (Euphausia superba)and the hydrography of the Southern Ocean: large-scale processes. Journal of Crustacean Biology, 4(5): 306-329. DOI:10.1163/1937240X84X00688
Arrigo K R, van Dijken G L. 2003. Phytoplankton dynamics within 37 Antarctic coastal polynya systems. Journal of Geophysical Research: Oceans, 108(C8): 3271. DOI:10.1029/2002JC001739
Atkinson A, Siegel V, Pakhomov E, et al. 2004. Long-term decline in krill stock and increase in Salps within the Southern Ocean. Nature, 432(7013): 100-103. DOI:10.1038/nature02996
Barbraud C, Weimerskirch H. 2001. Emperor penguins and climate change. Nature, 411(6834): 183-186. DOI:10.1038/35075554
Bargagli R. 2008. Environmental contamination in Antarctic ecosystems. Science of the Total Environment, 400(1-3): 212-226. DOI:10.1016/j.scitotenv.2008.06.062
Bestley S, Raymond B, Gales N J, et al. 2018. Predicting krill swarm characteristics important for marine predators foraging off east Antarctica. Ecography, 41(6): 996-1012. DOI:10.1111/ecog.03080
Branch T A, Jensen O P, Ricard D, et al. 2011. Contrasting global trends in marine fishery status obtained from catches and from stock assessments. Conservation Biology, 25(4): 777-786. DOI:10.1111/j.1523-1739.2011.01687.x
Cherel Y. 2008. Isotopic niches of emperor and Adélie penguins in Adélie Land, Antarctica. Marine Biology, 154(5): 813-821. DOI:10.1007/s00227-008-0974-3
Cheung W W L, Brodeur R D, Okey T A, et al. 2015. Projecting future changes in distributions of pelagic fish species of northeast Pacific shelf seas. Progress in Oceanography, 130: 19-31. DOI:10.1016/j.pocean.2014.09.003
Cheung W W L, Lam V W Y, Pauly D. 2008. Modelling Present and Climate-shifted Distribution of Marine Fishes and Invertebrates. Fisheries Centre, University of British Columbia, Vancouver.
Cheung W W L, Lam V W Y, Sarmiento J L, et al. 2009. Projecting global marine biodiversity impacts under climate change scenarios. Fish and Fisheries, 10(3): 235-251. DOI:10.1111/j.1467-2979.2008.00315.x
Cheung W W L, Lam V W Y, Sarmiento J L, et al. 2010. Large-scale redistribution of maximum fisheries catch potential in the global ocean under climate change. Global Change Biology, 16(1): 24-35. DOI:10.1111/j.1365-2486.2009.01995.x
Cheung W W L, Reygondeau G, Frölicher T L. 2016. Large benefits to marine fisheries of meeting the 1. 5 ℃ global warming target. Science, 354(6319): 1591-1594. DOI:10.1126/science.aag2331
Cheung W W L, Watson R, Morato T, et al. 2007. Intrinsic vulnerability in the global fish catch. Marine Ecology Progress Series, 333: 1-12. DOI:10.3354/meps333001
Cheung W W L, Watson R, Pauly D. 2013. Signature of ocean warming in global fisheries catch. Nature, 497(7449): 365-368. DOI:10.1038/nature12156
Clarke A, Murphy E J, Meredith M P, et al. 2007. Climate change and the marine ecosystem of the western Antarctic Peninsula. Philosophical Transactions of the Royal Society B: Biological Sciences, 362(1477): 149-166. DOI:10.1098/rstb.2006.1958
Close C, Cheung W, Hodgson S et al. 2006. Distribution Ranges of Commercial Fishes and Invertebrates. Fisheries Centre, University of British Columbia, Vancouver.
Convey P, Peck L S. 2019. Antarctic environmental change and biological responses. Science Advances, 5(11): eaaz0888. DOI:10.1126/sciadv.aaz0888
Craven M, Allison I, Fricker H A et al. 2011. The AMISOR (Amery Ice Shelf Ocean Research) Project: an Overview. IGS/FRISP, La Jolla, California, USA.
Croxall J P, Nicol S. 2004. Management of Southern Ocean fisheries: global forces and future sustainability. Antarctic Science, 16(4): 569-584. DOI:10.1017/S0954102004002330
Daniels R A, Lipps J H. 1982. Distribution and ecology of fishes of the Antarctic Peninsula. Journal of Biogeography, 9(1): 1-9. DOI:10.2307/2844726
Dehnhard N, Achurch H, Clarke J et al. 2020. High inter- and intraspecific niche overlap among three sympatrically breeding, closely related seabird species: generalist foraging as an adaptation to a highly variable environment? Journal of Animal Ecology, 89(1): 104-119, https://doi.org/10.1111/1365-2656.13078.
Demer D. 2004. An estimate of error for the CCAMLR 2000 survey estimate of krill biomass. Deep Sea Research Part II: Topical Studies in Oceanography, 51(12-13): 1237-1251. DOI:10.1016/S0967-0645(04)00077-3
Ding Y J, Li C Y, Wang X M, et al. 2021. An overview of climate change impacts on the society in China. Advances in Climate Change Research, 12(2): 210-223. DOI:10.1016/j.accre.2021.03.002
Doake C S M, Vaughan D G. 1991. Rapid disintegration of the Wordie Ice Shelf in response to atmospheric warming. Nature, 350(6316): 328-330. DOI:10.1038/350328a0
Dudley P N, Rogers T L, Morales M M, et al. 2021. A more comprehensive climate vulnerability assessment framework for fisheries social-ecological systems. Frontiers Marine Science, 8: 678099. DOI:10.3389/fmars.2021.678099
Eastman J T. 1985. Pleuragramma antarcticum (Pisces, Nototheniidae) as food for other fishes in McMurdo Sound, Antarctica. Polar Biology, 4(3): 155-160. DOI:10.1007/BF00263878
Egginton S, Campbell H A. 2016. Cardiorespiratory responses in an Antarctic fish suggest limited capacity for thermal acclimation. Journal of Experimental Biology, 219(9): 1283-1286. DOI:10.1242/jeb.130963
Fan T T, Deser C, Schneider D P. 2014. Recent Antarctic sea ice trends in the context of southern ocean surface climate variations since 1950. Geophysical Research Letters, 41(7): 2419-2426. DOI:10.1002/2014GL059239
Flores H, Atkinson A, Kawaguchi S, et al. 2012. Impact of climate change on Antarctic krill. Marine Ecology Progress Series, 458: 1-19. DOI:10.3354/meps09831
Fossheim M, Primicerio R, Johannesen E, et al. 2015. Recent warming leads to a rapid borealization of fish communities in the Arctic. Nature Climate Change, 5(7): 673-677. DOI:10.1038/nclimate2647
Galton-Fenzi B K, Hunter J R, Coleman R. 2007. Modelling the circulation and melt/freeze beneath the Amery Ice Shelf, East Antarctica. In: AGU Fall Meeting Abstracts. AGU.
Gille S T. 2002. Warming of the Southern Ocean since the 1950s. Science, 295(5558): 1275-1277. DOI:10.1126/science.1065863
Goldsworthy L, Brennan E. 2021. Climate change in the Southern Ocean: is the commission for the convention for the conservation of Antarctic marine living resources doing enough?. Marine Policy, 130: 104549. DOI:10.1016/j.marpol.2021.104549
Grémillet D, Boulinier T. 2009. Spatial ecology and conservation of seabirds facing global climate change: a review. Marine Ecology: Progress Series, 391: 121-137. DOI:10.3354/meps08212
Guisan A, Thuiller W. 2005. Predicting species distribution: offering more than simple habitat models. Ecology Letters, 8(9): 993-1009. DOI:10.1111/j.1461-0248.2005.00792.x
Harris J W, Woehler E J. 2004. Can the important bird area approach improve the Antarctic protected area system?. Polar Record, 40(2): 97-105. DOI:10.1017/S0032247403003322
Hesse R. 1924. Tiergeographie auf Ökologischer Grundlage. Verlag Gustav Fischer, Jena. 613p.
Hiddink J G, Ter Hofstede R. 2008. Climate induced increases in species richness of marine fishes. Global Change Biology, 14(3): 453-460. DOI:10.1111/j.1365-2486.2007.01518.x
Hijmans R J, Graham C H. 2006. The ability of climate envelope models to predict the effect of climate change on species distributions. Global Change Biology, 12(12): 2272-2281. DOI:10.1111/j.1365-2486.2006.01256.x
Hultzsch N. 2007. Lacustrine Sediment Records of Late Quaternary Environmental Change in the Amery Oasis, East Antarctica, Ber. Polarforsch. Meeresforsch. 545.
Jenouvrier S, Holland M, Iles D, et al. 2020. The Paris agreement objectives will likely halt future declines of emperor penguins. Global Change Biology, 26(3): 1170-1184. DOI:10.1111/gcb.14864
Jones M C, Dye S R, Pinnegar J K, et al. 2012. Modelling commercial fish distributions: prediction and assessment using different approaches. Ecological Modelling, 225: 133-145. DOI:10.1016/j.ecolmodel.2011.11.003
Jung C A, Swearer S E, Jenkins G P. 2010. Changes in diversity in the fish assemblage of a southern Australian embayment: consistent spatial structuring at decadal scales. Marine and Freshwater Research, 61(12): 1425-1434. DOI:10.1071/MF10080
Kawaguchi S, Nicol S, Press A J. 2010. Direct effects of climate change on the Antarctic krill fishery. Fisheries Management and Ecology, 16(5): 424-427. DOI:10.1111/j.1365-2400.2009.00686.x
Kock K H. 2005. Antarctic icefishes (Channichthyidae): a unique family of fishes. A review, part I. Polar Biology, 28(11): 862-895. DOI:10.1007/s00300-005-0019-z
Kock K H, Everson I. 2003. Shedding new light on the life cycle of mackerel icefish in the Southern Ocean. Journal of Fish Biology, 63(1): 1-21. DOI:10.1046/j.1095-8649.2003.00150.x
Kock K H, Pshenichnov L, Jones C D, et al. 2004. JoinvilleD'Urville Islands (subarea 48. 1) -a former fishing ground for the spiny icefish (Chaenodraco wilsoni), at the tip of the Antarctic Peninsula-revisited. CCAMLR Science, 11: 1-20.
Kock K H, Pshenichnov L, Jones C D, et al. 2008. The biology of the spiny icefish Chaenodraco wilsoni Regan, 1914. Polar Biology, 31(3): 381-393. DOI:10.1007/s00300-007-0366-z
Kusahara K, Hasumi H. 2013. Modeling Antarctic ice shelf responses to future climate changes and impacts on the ocean. Journal of Geophysical Research: Oceans, 118(5): 2454-2475. DOI:10.1002/jgrc.20166
La Mesa M, Eastman J T. 2012. Antarctic silverfish: life strategies of a key species in the high -Antarctic ecosystem. Fish and Fisheries, 13(3): 241-266. DOI:10.1111/j.1467-2979.2011.00427.x
La Mesa M, Riginella E, Mazzoldi C, et al. 2015. Reproductive resilience of ice-dependent Antarctic silverfish in a rapidly changing system along the western Antarctic Peninsula. Marine Ecology, 36(2): 235-245. DOI:10.1111/maec.12140
Liu J P, Curry J A, Martinson D G. 2004. Interpretation of recent Antarctic sea ice variability. Geophysical Research Letters, 31(2): L02205. DOI:10.1029/2003GL018732
Lowther A D, Staniland I, Lydersen C, et al. 2020. Male Antarctic fur seals: neglected food competitors of bioindicator species in the context of an increasing Antarctic krill fishery. Scientific Reports, 10(1): 18436. DOI:10.1038/s41598-020-75148-9
Makarov R R, Menshenina L L. 1989. On the Distribution of Euphausiid Larvae in the Antarctic Waters. Okeanograficeskaja Komissija, Moskva.
Mangel M. 2011. An Assessment of Japanese Whale Research Programs Under Special Permit in the Antarctic (JARPA, JARPA II) as Programs for Purposes of Scientific Research in the Context of Conservation and Management of Whales.
Margules C R, Pressey R L. 2000. Systematic conservation planning. Nature, 405(6783): 243-253. DOI:10.1038/35012251
McMahon C R, Burton H R. 2005. Climate change and seal survival: evidence for environmentally mediated changes in elephant seal, Mirounga leonina, pup survival. Proceedings of the Royal Society B: Biological Sciences, 272(1566): 923-928. DOI:10.1098/rspb.2004.3038
Meyer B, Atkinson A, Stöbing D, et al. 2002. Feeding and energy budgets of Antarctic krill Euphausia superba at the onset of winter -I -Furcilia III larvae. Limnology and Oceanography, 47(4): 943-952. DOI:10.4319/lo.2002.47.4.0943
Mika A M. 2008. Proposed Improvements on Predicting Species' Distributions with Climate Change Using Bioclimatic Envelope Modelling. University of Guelph, Guelph.
Mintenbeck K, Barrera-Oro E R, Brey T, et al. 2012. Impact of climate change on fishes in complex Antarctic ecosystems. Advances in Ecological Research, 46: 351-426.
Murphy E J, Cavanagh R D, Drinkwater K F, et al. 2016. Understanding the structure and functioning of polar pelagic ecosystems to predict the impacts of change. Proceedings of the Royal Society B: Biological Sciences, 283(1844): 20161646. DOI:10.1098/rspb.2016.1646
Mysak L A. 2008. Glacial inceptions: past and future. Atmosphere Ocean, 46(3): 317-341. DOI:10.3137/ao.460303
Nicol S, Endo Y. 1999. Krill fisheries: development, management and ecosystem implications. Aquatic Living Resources, 12(2): 105-120. DOI:10.1016/S0990-7440(99)80020-5
O'Brien P E, Leitchenkov G. 1997. Deglaciation of Prydz Bay, east Antarctica, based on echo sounding and topographic features. In: Barker P F, Cooper A K eds. Geology and Seismic Stratigraphy of the Antarctic Margin, 2, Volume 71. American Geophysical Union, Washington. p. 109-126, https://doi.org/10.1029/AR071p0109.
Pershing A J, Alexander M A, Hernandez C M, et al. 2015. Slow adaptation in the face of rapid warming leads to collapse of the Gulf of Maine cod fishery. Science, 350(6262): 809-812. DOI:10.1126/science.aac9819
Pinsky M L, Worm B, Fogarty M J, et al. 2013. Marine taxa track local climate velocities. Science, 341(6151): 1239-1242. DOI:10.1126/science.1239352
Policansky D. 1994. Antarctic fish biology: evolution in a unique environment: by Joseph T. Eastman academic press, 1993. $74.95 hbk (xiii+322 pages) ISBN 0 12 228140 3.. Trends in Ecology & Evolution, 9(5): 194-195. DOI:10.1016/0169-5347(94)90090-6
Poloczanska E S, Brown C J, Sydeman W J, et al. 2013. Global imprint of climate change on marine life. Nature Climate Change, 3(10): 919-925. DOI:10.1038/nclimate1958
Post A L, Hemer M A, O'Brien P E, et al. 2007. History of benthic colonisation beneath the Amery Ice Shelf, east Antarctica. Marine Ecology Progress Series, 344: 29-37. DOI:10.3354/meps06966
Pritchard H D, Ligtenberg S R M, Fricker H A, et al. 2012. Antarctic ice-sheet loss driven by basal melting of ice shelves. Nature, 484(7395): 502-505. DOI:10.1038/nature10968
Rebelo H, Tarroso P, Jones G. 2010. Predicted impact of climate change on European bats in relation to their biogeographic patterns. Global Change Biology, 16(2): 561-576. DOI:10.1111/j.1365-2486.2009.02021.x
Reed D H. 2015. Impact of climate change on biodiversity. In: Chen W Y, Seiner J, Suzuki T et al. eds. Handbook ofClimate Change Mitigation. Springer, New York. p. 505-530, https://doi.org/10.1007/978-1-4419-7991-9_15.
Root T L, Price J T, Hall K R, et al. 2003. Fingerprints of global warming on wild animals and plants. Nature, 421(6918): 57-60. DOI:10.1038/nature01333
Ross R M, Quetin L B. 1991. Ecological physiology of larval euphausiids, Euphausia superba (Euphausiaceae). Memoirs-Queensland Museum, 31: 321-333.
Ross R M, Quetin L B, Kirsch E. 1988. Effect of temperature on developmental times and survival of early larval stages of Euphausia superba dana. Journal of Experimental Marine Biology and Ecology, 121(1): 55-71. DOI:10.1016/0022-0981(88)90023-8
Rott H, Skvarca P, Nagler T. 1996. Rapid collapse of northern Larsen Ice Shelf, Antarctica. Science, 271(5250): 788-792. DOI:10.1126/science.271.5250.788
Scambos T, Hulbe C, Fahnestock M. 2003. Climate-induced ice shelf disintegration in the Antarctic Peninsula. In: Domack E, Levente A, Burnet A et al. eds. Antarctic Peninsula Climate Variability: Historical and Paleoenvironmental Perspectives, Volume 79. American Geophysical Union, Washington. p. 79-92.
Schofield O, Ducklow H W, Martinson D G, et al. 2010. How do polar marine ecosystems respond to rapid climate change?. Science, 328(5985): 1520-1523. DOI:10.1126/science.1185779
Seebacher F, Davison W, Lowe C J, et al. 2005. A falsification of the thermal specialization paradigm: compensation for elevated temperatures in Antarctic fishes. Biology Letters, 1(2): 151-154. DOI:10.1098/rsbl.2004.0280
Shadwick E H, Trull T W, Thomas H, et al. 2013. Vulnerability of polar oceans to anthropogenic acidification: comparison of arctic and Antarctic seasonal cycles. Scientific Reports, 3(1): 2339. DOI:10.1038/srep02339
Southwell C, Emmerson L, Takahashi A, et al. 2017. Largescale population assessment informs conservation management for seabirds in Antarctica and the Southern Ocean: a case study of Adélie penguins. Global Ecology and Conservation, 9: 104-115. DOI:10.1016/j.gecco.2016.12.004
Sowers T. 2003. Evidence for in-situ metabolic activity in ice sheets based on anomalous trace gas records from the Vostok and other ice cores. In: Proceedings of EGS-AGU-EUG Joint Assembly. Nice.
Spiridonov V A. 2010. A scenario of the Late-PleistoceneHolocene changes in the distributional range of Antarctic krill (Euphausia superba). Marine Ecology, 17(1-3): 519-541.
Stirling I. 1997. The importance of polynyas, ice edges, and leads to marine mammals and birds. Journal of Marine Systema, 10(1-4): 9-21. DOI:10.1016/S0924-7963(96)00054-1
Tanaka K, Chen Y. 2016. Modeling spatiotemporal variability of the bioclimate envelope of Homarus americanus in the coastal waters of Maine and New Hampshire. Fisheries Research, 177: 137-152. DOI:10.1016/j.fishres.2016.01.010
Torres R, Jayat J P, Pacheco S. 2013. Modelling potential impacts of climate change on the bioclimatic envelope and conservation of the maned wolf (Chrysocyon brachyurus). Mammalian Biology, 78(1): 41-49. DOI:10.1016/j.mambio.2012.04.008
Turner J, Barrand N E, Bracegirdle T J, et al. 2013. Antarctic climate change and the environment: an update. Polar Record, 50(3): 237-259.
Turner J, Hosking J S, Bracegirdle T J, et al. 2015. Recent changes in Antarctic Sea Ice. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 373(2045): 20140163. DOI:10.1098/rsta.2014.0163
Tynan C T. 1998. Ecological importance of the southern boundary of the Antarctic circumpolar current. Nature, 392(6677): 708-710. DOI:10.1038/33675
Vacchi M, La Mesa M, Dalu M, et al. 2004. Early life stages in the life cycle of Antarctic silverfish, Pleuragramma antarcticum in Terra Nova Bay, Ross Sea. Antarctic Science, 16(3): 299-305. DOI:10.1017/S0954102004002135
Vacchi M, Pisano E, Ghigliotti L. 2017. The Antarctic Silverfish: a Keystone Species in a Changing Ecosystem. Springer, Cham, Switzerland: 265-267. DOI:10.1007/978-3-319-55893-6
Van de Putte A P, Jackson G D, Pakhomov E, et al. 2010. Distribution of squid and fish in the pelagic zone of the Cosmonaut Sea and Prydz Bay region during the BROKE-West campaign. Deep-Sea Research Part II: Topical Studies in Oceanography, 57(9-10): 956-967. DOI:10.1016/j.dsr2.2008.02.015
Wagner B, Cremer H, Hultzsch N, et al. 2004. Late Pleistocene and Holocene history of Lake Terrasovoje, Amery Oasis, east Antarctica, and its climatic and environmental implications. Journal of Paleolimnology, 32(4): 321-339. DOI:10.1007/s10933-004-0143-8
Wall E, Smit B. 2005. Climate change adaptation in light of sustainable agriculture. Journal of Sustainable Agriculture, 27(1): 113-123. DOI:10.1300/J064v27n01_07
Warwick-Evans V, Santora J A, Waggitt J J, et al. 2021. Multiscale assessment of distribution and density of procellariiform seabirds within the Northern Antarctic Peninsula marine ecosystem. ICES Journal of Marine Science, 78(4): 1324-1339. DOI:10.1093/icesjms/fsab020
Williams M J M, Warner R C, Budd W F. 2002. Sensitivity of the Amery Ice Shelf, Antarctica, to changes in the climate of the Southern Ocean. Journal of Climate, 15(19): 2740-2757. DOI:10.1175/1520-0442(2002)015<2740:SOTAIS>2.0.CO;2
Williams T D, Wilson R P, Boersma P et al. 1995. The Penguins. Oxford University Press, Oxford.
Wu R J, Yang Q Y, Zhu G P. 2020. Fatty acid composition of spiny icefish (Chaenodraco wilsoni) in the Bransfield Strait, Antarctic during summer-autumn 2016 and its implication to diet. Chinese Journal of Polar Research, 32(1): 82-89. (in Chinese with English abstract) DOI:10.13679/j.jdyj.20190001
Zhang J I. 2007. Increasing Antarctic sea ice under warming atmospheric and oceanic conditions. Journal of Climate, 20(11): 2515-2529. DOI:10.1175/JCLI4136.1
Zheng S J, Shi J X, Jiao Y T, et al. 2011. Spatial distribution of ice shelf water in front of the Amery Ice Shelf, Antarctica in summer. Chinese Journal of Oceanology and Limnology, 29(6): 1325-1338. DOI:10.1007/s00343-011-0318-x
Zhu Y G, Zheng S Y, Reygondeau G, et al. 2020. Modelling spatiotemporal trends in range shifts of marine commercial fish species driven by climate change surrounding the Antarctic Peninsula. Science of the Total Environment, 737: 140258. DOI:10.1016/j.scitotenv.2020.140258