Climate change and the marine ecosystem of the western Antarctic Peninsula

Abstract

The Antarctic Peninsula is experiencing one of the fastest rates of regional climate change on Earth, resulting in the collapse of ice shelves, the retreat of glaciers and the exposure of new terrestrial habitat. In the nearby oceanic system, winter sea ice in the Bellingshausen and Amundsen seas has decreased in extent by 10% per decade, and shortened in seasonal duration. Surface waters have warmed by more than 1 K since the 1950s, and the Circumpolar Deep Water (CDW) of the Antarctic Circumpolar Current has also warmed. Of the changes observed in the marine ecosystem of the western Antarctic Peninsula (WAP) region to date, alterations in winter sea ice dynamics are the most likely to have had a direct impact on the marine fauna, principally through shifts in the extent and timing of habitat for ice-associated biota. Warming of seawater at depths below ca 100 m has yet to reach the levels that are biologically significant. Continued warming, or a change in the frequency of the flooding of CDW onto the WAP continental shelf may, however, induce sublethal effects that influence ecological interactions and hence food-web operation. The best evidence for recent changes in the ecosystem may come from organisms which record aspects of their population dynamics in their skeleton (such as molluscs or brachiopods) or where ecological interactions are preserved (such as in encrusting biota of hard substrata). In addition, a southwards shift of marine isotherms may induce a parallel migration of some taxa similar to that observed on land. The complexity of the Southern Ocean food web and the nonlinear nature of many interactions mean that predictions based on short-term studies of a small number of species are likely to be misleading.

Figure 1

The Antarctic Peninsula. The 1000 m isobath marks the conventional transition from the continental shelf to the continental slope round Antarctica, and the 3000 m isobath marks an arbitrary transition from the slope to the abyssal plain.

Figure 2

Trends in ocean summer surface temperature over the period 1955–1998, for four different depth levels (surface 20, 50 and 100 m). Grid cells with no data are left white. Note that the marked warming trend observed close to the Antarctic Peninsula is strongly intensified towards the surface, and decays to almost 0 by 100 m depth. Reproduced, with permission, from Meredith & King (2005).

Figure 3

Conceptual diagram illustrating the variety of physical environmental factors forcing biological processes in the Southern Ocean, and emphasizing the central importance of sea ice to the western Antarctic Peninsula oceanic ecosystem. Only the key forcing factors are shown. Modified from Barange (2002).

Figure 4

Temperature limitation of physiological performance in Antarctic marine ectotherms. (a) Development rate in echinoderm embryos from polar, temperate and tropical locations (redrawn from Bosch et al. 1987 and Stanwell-Smith & Peck 1998). (b) Comparative rate of various locomotor activities in polar marine ectotherms compared with a range of temperate water relatives. Data are expressed as a ratio, such that a value of 1 indicates equality of rates in polar and temperate species, and a value less than 1 indicates a slower rate in the polar species. The size of the box indicates the range of values observed, and the midline indicates the mean (redrawn from Peck et al. 2004b).

Figure 5

The effect of temperature on performance in two Antarctic marine invertebrates. (a) The limpet Nacella concinna; data show the proportion of limpets capable of righting within 24 h when turned over. The different symbols indicate experiments undertaken in 2001 (open circles) and 2002 (filled circles). (b) The infaunal bivalve Laternula elliptica; data show the proportion of individuals capable of successfully reburying within 24 h when removed from the sediment. In both cases, the line shows the least-squares regression fitted following arcsine transformation of the data (redrawn from Peck et al. 2004a,b).

Figure 6

The basic structure of the Southern Ocean food web. Note that the fundamental topology is branched, with carbon fixed by primary producers being used by three principal and competing pathways (to zooplankton consumers, the microbial network and the benthos). The arrows show only the major routes for energy flow, with the size indicating the dominant pathways for the western Antarctic Peninsula (WAP) oceanic food web over the continental shelf in summer, based on the inverse modelling results of Ducklow et al. (2006). The major route for energy flow is from phytoplankton to zooplankton consumers (and predominantly Antarctic krill) and thereby to higher predators, with secondary pathways to the microbial network both directly from the primary producers and also from zooplankton via the detrital pathway. In the WAP area, flux to copepods and salps in the zooplankton, or directly to the benthos, are important but secondary. Note that in other areas of the Antarctic, and possibly at other times in the WAP area, the relative importance of the major pathways will be different. Modified from Clarke & Harris (2003).

Figure 7

Long-term variability in growth in three species of the erect bryozoan Cellarinella from the Weddell Sea. Growth determined from number of zooids produced annually, measured only in living colonies so growth can be ascribed to both colony age and calendar year, and relative growth rate and anomaly calculated using a standard exponential growth rate model for bryozoans. (a) Cellarinella watersi (black diamonds) and C. rogickae (open circles); data presented as relative growth rate anomaly, plotted as mean and s.e. In both species, the decline in growth rate since the 1990s is significant (model 1 least-squares regression, p<0.05), but there is no significant correlation between the two species in growth performance (p>0.05). Redrawn from Barnes et al. (under review). (b) Cellarinella nutti, with data presented as absolute growth anomaly. The overall increase in growth rate since the 1980s is significant (model 1 least-squares regression, p<0.05); note the strikingly strong growth performance in 2003. Redrawn from Barnes et al. (2006b).