Climate drives long-term change in Antarctic Silverfish along the western Antarctic Peninsula

doi:10.21203/rs.3.rs-310839/v1

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Climate drives long-term change in Antarctic Silverfish along the western Antarctic Peninsula

https://doi.org/10.21203/rs.3.rs-310839/v1

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published 03 Feb, 2022

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Over the last half of the 20th century, the western Antarctic Peninsula has been one of the most rapidly warming regions on Earth, leading to substantial reductions in regional sea ice coverage. These changes are modulated by atmospheric forcing, including the Amundsen Sea Low (ASL) pressure system. We utilized a novel 25-year (1993–2017) time series to model the effects of environmental variability on larvae of a keystone species, the Antarctic Silverfish (Pleuragramma antarctica). Antarctic Silverfish use sea ice as spawning habitat and are important prey for penguins and other predators. We show that warmer sea surface temperature and decreased sea ice negatively impact larval abundance. Modulating both sea surface temperature and sea ice is ASL variability, where a strong ASL is associated with reduced larvae. These findings support a narrow sea ice and temperature tolerance for adult and larval fish. Further regional warming predicted to occur during the 21st century could displace fish populations, altering this pelagic ecosystem.

Climate Analysis and Modeling

Ecological Modeling

Oceanography

Regional Sea Ice Coverage

Amundsen Sea Low Pressure System

Keystone Species

Fish Populations

Pelagic Ecosystem

The Antarctic Silverfish (Pleuragramma antarctica; Notothenioidei) can comprise over 90% of adult and larval fish biomass in coastal areas of the Southern Ocean ^1,2, and is the only endemic Southern Ocean fish that maintains an entirely pelagic life history ³. Due to their abundance and availability within the upper water column, Antarctic Silverfish are important prey for higher predators, such as seals, and penguins and other seabirds ⁴. Antarctic Silverfish have a circumpolar distribution with populations having genetic connectivity along the continental shelf ⁵. However, weaker continental shelf circulation due to the absence of an Antarctic Slope Front Current in the western Antarctic Peninsula (WAP) region (Fig. 1) has isolated this Antarctic Silverfish population from other established areas of reproduction in the species ⁵.

The central role of Antarctic Silverfish in the WAP food web has led to concern over the health of this isolated population due to regional climate change. Physiological adaptations that allow endemic fishes (most notably, members of Notothenioidei) to survive in the cold waters surrounding Antarctica also make them susceptible to ocean warming. An increase of just 5°C can result in mortality ^6,7 and reduced food assimilation rate ⁸ in some notothenioid fishes. From 1945-2010, the mean ocean temperature at mid-depths (100-300m) along the WAP increased by 1°C ⁹ and annual mean air temperature increased by 3°C ¹⁰. Although this rapid warming likely caused no direct mortality in adult Antarctic Silverfish, it may have led to detrimental physiological responses at all life stages, especially in the less mobile larval stages ¹¹.

Regional warming in the WAP, and changes in winds, have also led to a decrease in sea ice, which plays a key and unique role in Antarctic Silverfish life history (they deposit their eggs within sea ice; ³. The total elapsed days between sea ice advance and retreat, or annual sea ice duration, is used to monitor trends in the cryosphere. Between 1979 and 2018, annual sea ice duration along the WAP decreased by about 2 months ¹². Therefore, recent declines in sea ice and thus spawning habitat has been implicated in diminished Antarctic Silverfish abundance in the WAP region ^11,13–19. However, abundance data of sufficient temporal and spatial scale for Antarctic Silverfish was previously unavailable to test this hypothesis.

Three atmospheric circulation patterns predominantly influence climate change in the WAP region – the Southern Annular Mode (SAM), El Niño Southern Oscillation (ENSO), and Amundsen Sea Low (ASL). Interconnections among these are complex, seasonally variable, and tied to anthropogenic impacts such as global greenhouse gas emissions ²⁰. The ASL, a climatological low-pressure center located in the Amundsen Sea (Fig. 1), has only recently been identified as a main factor behind WAP ocean warming ^21–23, sea ice loss ^24–26, and glacial retreat ^27,28 over the last century.

The strength and location of the ASL influences meridional winds east and west of the ASL center ²² (Fig. 1a, b); stronger (i.e., deeper or spun-up) ASL events in the Amundsen Sea, for example, increase warm northerly airflow over the WAP region (i.e., along the eastern limb of the clockwise rotating low-pressure center), which reduces sea ice extent and concentration (Fig. 1b) and increases temperature at the surface along the WAP ²⁴. In addition, the strength and location of the ASL influences zonal winds to the north and south of the ASL center. For example, an ASL that is centered southward (i.e., poleward) in the Amundsen Sea increases westerly wind anomalies near the continental shelf break ²³, enhancing the flow of warm Circumpolar Deep Water (CDW) southward onto the shelf ^27–29. Although less is known regarding the impact of the ASL on CDW intrusions in the Bellingshausen Sea, a similar relationship is probable ^30–33. While several studies examined the effects of SAM and ENSO oscillations on Antarctic phytoplankton and zooplankton ^34–36, no previous analyses focus on the potential impacts of the ASL strength or location on any organism.

We sorted, identified, and enumerated Antarctic Silverfish larvae (n = 7086) collected in a 25-year time series (1993 – 2017; Fig. 2a) of plankton net tows (see Materials and Methods) as part of the Palmer Antarctica Long-Term Ecological Research Program (Palmer LTER) and archived in the Nunnally Ichthyology Collection at the Virginia Institute of Marine Science. Zero-inflated Generalized Linear Mixed-Effects model predictions show the abundance of larvae during this period is closely tied to sea surface temperature, with higher abundance in colder water (p < 0.001; Fig. 2b). Approximately 45% of Antarctic Silverfish larvae were encountered at sea surface temperatures ranging from - 2° to 0°C, and 95% of larvae were sampled in waters colder than 1.5°C. With 95% confidence, we predict no larvae will occur at sea surface temperatures of 1.7°C or greater (see Materials and Methods).

Based on the time series, at least two consecutive years of anomalously cold surface temperatures are necessary to produce peaks in larval abundance (Fig. 2a). Palmer LTER net tows are deployed to a depth of 120 meters, encompassing the majority of habitat occupied by Antarctic Silverfish larvae ^19,37. Using CTD casts paired with net tows, we found Antarctic Silverfish abundance was significantly linked to colder temperatures averaged over the 120 m water column. However, sea surface temperature yielded optimal model performance (see Materials and Methods).

We next isolated the effects of sea ice dynamics and climatic variability on Antarctic Silverfish adults by lagging variables in the model ^35,38. Model results indicate the timing of sea ice advance during austral autumn (March to May) controls larval abundance in the following year (p < 0.001; Fig. 2c). Model performance (see Materials and Methods) was considerably reduced when sea ice advance lagged two years or sea ice advance immediately prior to the cruise (no lag) were evaluated as alternative parameters. To our knowledge, this is the first statistically significant relationship reported between sea ice and the long-term abundance of any Antarctic fish.

There are relatively sparse data on the reproductive biology of Antarctic Silverfish, especially in the WAP region ¹⁴. Adult fish likely spawn during late austral winter to early spring (July to September), eggs develop for approximately four months and hatch in November and December (Fig. 3a). Larvae are then sampled annually by the Palmer LTER during January and February. However, there is evidence from the Ross Sea that Antarctic Silverfish are skip spawners ³⁹. In austral autumn, adult fish migrate from their offshore pelagic habitat to coastal areas. Adults then improve their nutritional condition for a year before spawning the next season (Fig. 3a) ^14,39.

We suggest that adult Antarctic Silverfish select their spawning area along the WAP based partially on the presence of sufficient sea ice cover during austral autumn (Fig. 2a, Fig. 3b, c). An early sea ice advance in late April or early May (days 110 to 130 in Fig. 2c) acts as a positive cue for migrating adults and increases spawning habitat (Fig. 3b). If advance is delayed, spawning habitat is reduced (Fig. 3c) and could cause adults to travel elsewhere or continue to postpone spawning. We predict a sea ice advance beginning on day 157 or earlier is necessary for spawning to successfully occur in this region (see Materials and Methods). Seasonal sea ice variability during the last 20 million years in the Southern Ocean has led to a high level of life-history plasticity among Antarctic Silverfish ^3,13. However, given the sea ice dependence indicated by our model, it is likely that the acute reduction in sea ice during the 20th century has significantly decreased spawning in the northern WAP. Consequently, there has been a lower abundance of mature adults observed in the northern WAP for several decades ^14,15,40.

Larval Antarctic Silverfish abundance was also significantly correlated with the ASL relative central pressure (RCP), an index of ASL strength, (p = 0.006; Fig. 4a) ²³ and the latitudinal location of the ASL (p = 0.005; Fig. 4b). We considered ASL RCP and latitude averaged over summer (DJF), autumn (MAM), winter (JJA), and spring (SON) months. Lagged ASL strength and latitude averaged over autumn produced optimal model AIC (see Materials and Methods). Longitudinal location of the ASL was not included in this analysis because it exhibits a strong negative correlation with RCP during most of the year ⁴¹. These relationships further support our hypothesis that adult Antarctic Silverfish are selecting their spawning habitat during autumn, when sea ice is also beginning to advance (Fig. 3a). Autumn seasons with stronger (more negative) RCPs (Fig. 4a) and a poleward ASL location (Fig. 4b) were associated with diminished spawning success reflected by lower abundance of the larvae sampled in the following year. There was no correlation between larvae and lagged ENSO indices during any season. We observed a non-significant negative relationship between lagged Marshall SAM index and larval abundance during autumn (p = 0.10) and summer (p = 0.09); larval abundance was higher following years with a more negative SAM. However, including the SAM index for any season did not improve model performance and thus was not included in the final model (see Materials and Methods).

The positive relationship between the lagged latitude of the ASL and larval abundance is suggestive of CDW intrusions impacting adult fish. Increased intrusions of CDW onto the Amundsen continental shelf that occur during a poleward shift in the ASL (Fig. 3c) are well below the thermocline ²⁹, with the CDW temperature maximum around 400 m ⁴². This warm layer of water, with temperatures approaching 2°C ⁴³, expands as more CDW is transported onto the shelf ²⁹. This water mass is well above the optimal thermal environment for Antarctic Silverfish, particularly as the physiological costs of spawning further impact their limited thermal tolerance ⁴⁴. Adult Antarctic Silverfish, which occupy a depth range of 0 to 900 m ³, might therefore delay spawning or attempt to relocate when oceanic and sea ice conditions are unfavorable in the Bellingshausen Sea due to ASL strength and location (Fig. 3c). However, additional ocean modeling is required to verify specific causes of the correlation between ASL strength, location, and adult fish.

Although there are connections between the West Antarctic cryosphere inclusive of the WAP and ASL ^24,25, there were no indications of collinearity between WAP ice advance, sea surface temperature, autumn ASL RCP, and the ASL latitudinal location in this analysis (see Materials and Methods). The positive correlation between ASL RCP and larval abundance is likely due to the warm northerly winds associated with strong (deep) RCPs reducing sea ice concentration in pathways that are not captured by the ice advance parameter.

Sea surface temperatures (< 20m) increased in the WAP region by approximately 2°C during the 20th century (1955 – 1998) ⁴⁵. Although this abrupt warming has recently slowed ¹⁰, it is expected to intensify in coming decades ^29,46. The altered near-surface winds associated with prolonged deepening and a poleward shift in the ASL, modulated by the SAM ⁴⁷ and Pacific variability ⁴⁸, contributes to past and future surface warming in the WAP region ²³. Therefore, we posit that long-term strengthening of the ASL creates unfavorable water temperatures for Antarctic Silverfish larvae in the WAP region (Fig. 3c) ^29,46.

In addition to sea surface temperature, larval Antarctic Silverfish abundance was positively correlated with chlorophyll concentration (p < 0.001; Fig. S1a), indicating bottom-up control in this food web. Phytoplankton are grazed by the early life stages of copepods (i.e., copepodites) which in turn are the primary prey of larval Antarctic Silverfish ³. While the focus of the present study is on modeling environmental variables, confounding influences of prey field dynamics due to a changing climate are also possible. The phytoplankton community shifts during warmer years with low sea ice ^12,49, potentially altering copepod abundance and composition ⁵⁰. In addition to the physiological cost of warmer waters on larval Antarctic Silverfish, climate change could cause their hatching period to become out of sync with peak abundances of their prey ^11,19,51.

Higher abundance of larvae also occurred in areas of lower surface salinity (p < 0.001; Fig. S1b). Surface freshwater inputs from melting sea ice and glaciers lead to a more stratified surface layer and increased chlorophyll ⁵²; such a stratified environment with ample food could be preferred by Antarctic Silverfish larvae. The relationship between salinity and larval abundance also points to the importance of sufficient sea ice cover. High-salinity brine is exported downwards in the water column during autumn sea ice growth and advance ^52,53. Consequently, surface salinity is fresher following winters with high sea ice extent ⁵³.

Slósarczyk ⁵⁴ found Antarctic Silverfish larvae were more abundant in areas of high salinity in the WAP region (34.1 to 34.6) ¹¹. However, their analysis used a single year of pelagic net tows, and the mean standard length (SL) of post-larval and juvenile Antarctic Silverfish they collected (75 mm) was over five times the mean SL of larvae used in our study (11.9 mm; Fig. S2). Osmoregulation functions change in fishes during their development ⁵⁵; therefore, post-larval Antarctic Silverfish could possess a greater ability to tolerate more saline water ¹¹. No experiments to date address the salinity thresholds of Antarctic Silverfish during any stage in their life history.

Sea ice and ocean temperatures, modulated by the ASL, impact Antarctic Silverfish spawning behavior, resulting in variability in their larval abundance along the WAP. Two anthropogenic forces jointly influence the prevailing circumpolar westerly winds and the strengthening/weakening of the ASL: the ozone hole located over Antarctica and greenhouse gas emissions; both tend to strengthen the westerly winds poleward and deepen the ASL ^23,56,57. However, Antarctic climate is characterized by high regional and seasonal variability, both natural and forced, making it challenging to identify attribution ²⁴. For example, a recent cooling along the WAP and increases in sea ice extent were attributed to Pacific decadal variability ⁵⁸, though other factors were likely also at play. Nonetheless, it is expected that the recent reversal in WAP climate trends will not persist with continued increases in greenhouse gas emissions. The Antarctic ozone hole is predicted to recover entirely by ~2100, while most scenarios predict increasing greenhouse gas emissions through 2100 ⁵⁹. High carbon dioxide emission scenarios will likely result in a prolonged trend of strong ASL events and atmospheric warming in the WAP region despite ozone recovery ^46,60. Antarctic Silverfish have encountered periods of cyclic warming during their evolutionary history ¹¹. However, with precipitous climate warming due to continuing greenhouse gas emissions, Antarctic Silverfish could disappear from the WAP region entirely, triggering changes in other components of the pelagic food web.

For the last 6,000 years, Antarctic Silverfish have dominated Adélie penguin diets in the WAP region during periods of especially cold temperatures ⁶¹. Furthermore, the substantial decline of Adélie penguins in the northern WAP ⁶² is coincident with a long-term decrease in Antarctic Silverfish in their diet ⁴⁰. While there are several causal mechanisms driving population changes in Adélie penguins ^63,64, these changes are likely exacerbated by diminished Antarctic Silverfish abundance resulting from recent warming and reduced sea ice ⁶³. Antarctic Silverfish, especially spawning adults, are high-energy prey items ^40,65. Penguins are known to switch to an entirely invertebrate-based diets (e.g., krill or squid) during warm periods ⁴⁰. However, the loss of lipid-rich Antarctic Silverfish in Adélie penguin chick diets induces low fledging weights, a vital determinant of future recruitment ^40,64. The sensitivity of Antarctic Silverfish to climate change reported herein adds to the list of documented or projected population shifts in the WAP region, including phytoplankton ^66,67, krill ⁶⁸, and seals ⁶⁹. This vulnerable pelagic ecosystem will likely continue to undergo significant alterations in the 21^st century.

Sampling

Larval fishes were collected annually from 1993 through 2017 as part of the Palmer Antarctica Long-Term Ecological Research (Palmer LTER) program. Scientists on Palmer LTER cruises collect multidisciplinary data in a fixed-sampling grid in the Bellingshausen Sea along the western Antarctic Peninsula (WAP; Fig. 1). Zooplankton and larval fishes are sampled each year during austral summer (January to February) using a 2-m² frame Metro net (700-µm mesh) towed to ~120m depth. A General Oceanics flowmeter positioned in the center of the net mouth was used to calculate each tow volume. All organisms in the tows are identified to family-level, measured in volume, and preserved in a formaldehyde solution.

From 1993 to 2007, tows were conducted from the 600 grid line to the 200 grid line (Steinberg et al. 2015). In 2008, the ‘far south’ lines (100, 000, and -100) were added to the Palmer LTER grid (Fig. 1). The far south stations were included in this analysis and temporal autocorrelation was accounted for (see Model development). We included additional tows that were conducted from 1993 to 2017 at Process Study stations located between grid lines. We ran the final model without these Process Study and far south stations and the relationships were unchanged.

As larvae in this study are collected during the same fixed two-month period annually, it is important to note Antarctic Silverfish could be altering the timing of spawning during reduced sea ice conditions, resulting in modified hatching and subsequent peaks in larval abundance ¹³. However, there has been minimal deviation in the standard length of Antarctic Silverfish larvae during the Palmer LTER (Fig. S2) and no yolk-sac larvae have been sampled.

Identification

Antarctic Silverfish is among the most easily identified of the known larval fishes endemic to the Southern Ocean due to possession of two distinct dorsal pigment rows and a lack of abdominal pigmentation. All larvae in this study were identified based on Kellermann ⁷¹. The majority (>70%) were identified to species level by Andrew D. Corso, and the remaining fishes were identified by Dr. Peter Konstantinidis (OSU) and other scientists associated with the Virginia Institute of Marine Science (VIMS) Nunnally Ichthyology Collection.

Model development

The density (abundance divided by tow volume [in units of 1000 m³]) of Antarctic Silverfish for each tow from 1993 – 2017 was modeled against environmental variables. We considered ocean temperatures and salinity from near the sea surface (5 m depth), the bottom of the tow depth (120 m), and averaged from 120 m to the surface. All temperature and salinity measurements were collected using CTD casts that were spatially and temporally paired with net tows. Discrete measurements of Chlorophyll a concentration measured in water collected in CTD casts were integrated to 100 m and also paired spatially and temporally with net tows. Sea ice variables considered were derived from satellite imagery (Scanning Multichannel Microwave Radiometer and Special Sensor Microwave/Imager; SMMR-SSM/I) (⁷²) and included duration, extent, day of retreat, and day of advance.

Annual indices of climatic teleconnections (e.g., ENSO, SAM, and ASL) were included in the model. The ENSO index is based on sea surface temperatures (referred to as the multivariate ENSO index [MEI]; http://www.esrl.noaa.gov/psd/people/klaus.wolterlter/MEI/) and the SAM (http://www.antarctica.ac.uk/met/gjma/sam.html) index is based on sea level pressure. These climate indices are seasonally adjusted ⁷³. The RCP and latitudinal location of the ASL were obtained from Hosking et al. ⁷⁴. The RCPs from all four seasons (DJF, MAM, JJA, and SON) were evaluated. Multicollinearity between the conditional model parameters was tested for with the Variance Inflation Factor (VIF) and correlation coefficient ⁷⁵. All parameters in the final model had VIF values of less than 2, well under cutoff range for moderate correlation (5 – 10) ⁷⁶.

Zero-inflated Generalized Linear Mixed-Effects Models (GLMMs) following a Tweedie distribution ⁷⁷ were developed in R (R Core Team 2020) and used to model the relationships between environmental variables and larval abundances. Antarctic larval fishes primarily exist in the upper 300-m of the water column ¹⁹ and are incidentally captured by Palmer LTER trawls targeting zooplankton (e.g., krill, salps, copepods). Resultingly, there is significant overrepresentation of “zero fishes captured” each year at stations along the Palmer LTER sampling grid. Zero-inflated GLMMs were selected over zero-altered, as any of zeros in the larval Antarctic Silverfish time series are likely ‘false’, which are the result of an imperfect sampling design ⁷⁸.

Using an autocorrelation function (ACF) and partial autocorrelation function (PACF), temporal autocorrelation was observed, likely due to the fixed-sampling grid design ⁷⁹. An autoregressive covariance is used in the GLMMs to accommodate the temporal autocorrelation between contiguous years ⁸⁰. There are no indications of spatial autocorrelation in the time-series, although “nuggets” detected using variograms suggest fine-scale spatial variation and measurement noise ⁸¹. Palmer LTER sampling stations were treated as a random effect to account for unobserved spatial heterogeneity ⁸². Generalized Additive Mixed-Effects Models (GAMMs) were also considered as several environmental variables exhibit marginal non-linearity. However, the lack of combined zero-inflation and autocorrelation structures for GAMMs limited their performance compared to GLMMs that account for these complexities ⁸³. The final model (Fig. S3; Table S1) was selected based on hypothesis testing, parsimony, and minimizing AIC ⁸⁴.

Predicted values (or estimated marginal means) were developed using the ggeffects package⁷⁰ in R⁸⁵. The predicted values of larval density were conditioned on the fixed effects, zero-inflation, and random effects components of the final model (i.e., “re.zi”) ⁷⁰. The 95% prediction intervals surrounding the predictions consider the mean random effect variance and are generally larger than confidence intervals due to this additional level of uncertainty ^70,86,87. Predictions of environmental cutoff values where no larvae would occur were determined when the upper 95% prediction interval included 0.000 larvae / 1000 m³.

Figure development

Figure 1. Monthly sea ice concentration anomalies are derived from the Scanning Multi-channel Microwave Radiometer-Special Sensor Microwave/Imager (SMMR/SSM/I) satellite time series based on the Goddard Space Flight Center (GSFC) Bootstrap algorithm ^88,89. The sea ice concentration data are gridded to 25 km and are provided by the EOS Distributed Active Archive Center (DAAC) at the National Snow and Ice Data Center (NSIDC, University of Colorado at Boulder, http://nsidc.org). The numerically-analyzed monthly 10-m height winds and sea-level pressure anomalies are from the fifth generation European Centre for Medium Range Weather Forecasts (ECMWF) Reanalysis (ERA-5) ⁹⁰ and are provided by the Climate Data Store (CDS, https://cds.climate.copernicus.eu/).

Figure 2. Sea surface temperatures for the Palmer LTER study region were determined by the NOAA optimal interpolation (OI) sea surface temperature analysis (version Reyn_SmithOI.v2) using in situ and satellite sea surface temperatures ⁹¹, plus sea surface temperatures simulated by sea ice cover. Annual anomalies of larval density and sea surface temperature were standardized by subtracting the sample mean then dividing by the sample standard deviation.

Acknowledgements

We would like to thank Joseph Cope (VIMS) for assisting in the collection of fishes and data analysis. We also thank: Sarah Huber (VIMS) and Peter Konstantinidis (Oregon State University) for their contributions to the identification of fishes; Adena Schonfeld (VIMS) and Robert Latour (VIMS) for their assistance in statistical analysis; Carlos Moffat (University of Delaware), Scott Hosking (British Antarctic Survey), William Fraser (Polar Oceans Research Group), and Christopher Jones (NOAA SWFC) for their aid in the interpretation of results. We are grateful for the multiple contributions of Marino Vacchi (Institute of Marine Sciences – National Research Council) and his colleagues regarding the life history of the Antarctic Silverfish. We thank the captains, crew, and support staff of the R/V Polar Duke and ASRV Laurence M. Gould, the support of personnel at Palmer Station, Antarctica, and the Leidos Antarctic Support Contractors. This work was funded by the National Science Foundation Antarctic Organisms and Ecosystems Program (PLR-1440435 for specimen and environmental data collection) and Division of Biological Infrastructure (DBI-1349327 for specimen preservation and analysis), and the VIMS John Olney Fellowship. This is contribution No. XXXX of the Virginia Institute of Marine Science, William & Mary.

Author contributions

D.K.S. led the collection of fishes; E.J.H. oversaw the preservation and identification of fishes; All authors conceived the ideas; A.D.C. and S.E.S. analyzed the data; all authors interpreted the results. A.D.C. wrote the manuscript; all authors edited the manuscript.

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Climate drives long-term change in Antarctic Silverfish along the western Antarctic Peninsula

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