Spatial and temporal variability across life's hierarchies in the terrestrial Antarctic

Abstract

Antarctica and its surrounding islands lie at one extreme of global variation in diversity. Typically, these regions are characterized as being species poor and having simple food webs. Here, we show that terrestrial systems in the region are nonetheless characterized by substantial spatial and temporal variations at virtually all of the levels of the genealogical and ecological hierarchies which have been thoroughly investigated. Spatial variation at the individual and population levels has been documented in a variety of genetic studies, and in mosses it appears that UV-B radiation might be responsible for within-clump mutagenesis. At the species level, modern molecular methods have revealed considerable endemism of the Antarctic biota, questioning ideas that small organisms are likely to be ubiquitous and the taxa to which they belong species poor. At the biogeographic level, much of the relatively small ice-free area of Antarctica remains unsurveyed making analyses difficult. Nonetheless, it is clear that a major biogeographic discontinuity separates the Antarctic Peninsula and continental Antarctica, here named the 'Gressitt Line'. Across the Southern Ocean islands, patterns are clearer, and energy availability is an important correlate of indigenous and exotic species richness, while human visitor numbers explain much of the variation in the latter too. Temporal variation at the individual level has much to do with phenotypic plasticity, and considerable life-history and physiological plasticity seems to be a characteristic of Antarctic terrestrial species. Environmental unpredictability is an important driver of this trait and has significantly influenced life histories across the region and probably throughout much of the temperate Southern Hemisphere. Rapid climate change-related alterations in the range and abundance of several Antarctic and sub-Antarctic populations have taken place over the past several decades. In many sub-Antarctic locations, these have been exacerbated by direct and indirect effects of invasive alien species. Interactions between climate change and invasion seem set to become one of the most significant conservation problems in the Antarctic. We conclude that despite the substantial body of work on the terrestrial biodiversity of the Antarctic, investigations of interactions between hierarchical levels remain scarce. Moreover, little of the available information is being integrated into terrestrial conservation planning, which lags far behind in this region by comparison with most others.

Figure 1

Division of populations of G. terranovae into northern, central and southern populations in Victoria Land on the basis of allozyme data. Adapted with permission from Fanciulli et al. (2001).

Figure 2

Body length variation across an altitudinal gradient in (a) Bothrometopus parvulus at Marion Island and (b) Ectemnorhinus viridis at Heard Island. Data are presented as mean, s.e. and 95% CI. Adapted with permission from Chown & Klok (2003).

Figure 3

Map of the ‘Gressitt Line’, a strong biogeographic region of separation between the biota of the Antarctic Peninsula and continental Antarctica.

Figure 4

Supercooling point (SCP) distributions in the springtail C. denticulata from (a) an ‘arbitrary’ field sample, (b) pre-moulting animals from the same main sample, (c) recently moulted animals and (d) recently moulted animals that had been fed for 1 day (10°C). Note the decline in SCP with moulting. Adapted with permission from Worland et al. (2006).

Figure 5

Autocorrelation plots for hourly microclimate temperatures recorded on Marion Island during (a) August 2002, (b) November 2002 and (c) June 2003, and for (d) August 2002, (e) November 2002 and (f) June 2003, for Lambert's Bay, South Africa. The dashed lines on each figure represent the 95% confidence intervals, while the values reported to the right of the lags on the y-axis are the autocorrelation coefficients and their standard errors. These figures indicate that microclimate temperatures are predictable from day-to-day in South Africa, but not at Marion Island. Adapted with permission from Deere & Chown (2006).

Figure 5

Autocorrelation plots for hourly microclimate temperatures recorded on Marion Island during (a) August 2002, (b) November 2002 and (c) June 2003, and for (d) August 2002, (e) November 2002 and (f) June 2003, for Lambert's Bay, South Africa. The dashed lines on each figure represent the 95% confidence intervals, while the values reported to the right of the lags on the y-axis are the autocorrelation coefficients and their standard errors. These figures indicate that microclimate temperatures are predictable from day-to-day in South Africa, but not at Marion Island. Adapted with permission from Deere & Chown (2006).