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Polar Biology ISSN 0722-4060Volume 34Number 11 Polar Biol (2011) 34:1713-1725DOI 10.1007/s00300-011-1001-6

Extended ecophysiological analysis ofGomphiocephalus hodgsoni (Collembola):flexibility in life history strategy andpopulation response

A. McGaughran, I. D. Hogg & P. Convey

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ORIGINAL PAPER

Extended ecophysiological analysis of Gomphiocephalus hodgsoni(Collembola): flexibility in life history strategy and populationresponse

A. McGaughran • I. D. Hogg • P. Convey

Received: 22 September 2010 / Revised: 21 March 2011 / Accepted: 22 March 2011 / Published online: 9 April 2011

� Springer-Verlag 2011

Abstract The springtail Gomphiocephalus hodgsoni

(Arthropoda: Collembola) has been the focus of extensive

ecophysiological and molecular genetic work and is now

arguably the most well-studied of the continental Antarctic

springtails. Here, we further the ecophysiological cata-

logue of this species. First, we provide experimental data

on G. hodgsoni from one summer season at Cape Bird

(Ross Sea Region) examining dispersal ability and desic-

cation tolerance. Next, we expand an existing metabolic

rate dataset that encompasses individual metabolic rate

measurements across both temporal and spatial scales in

southern Victoria Land, adding an additional season of

metabolic rate measurements taken at a cooler, drier

continental location (Garwood Valley). Our data show that

some G. hodgsoni individuals can survive at least ten days

of suspension on the surface of both fresh and sea water.

This, coupled with the presence of G. hodgsoni specimens

in air and pitfall traps suggests that dispersal over local

scales (i.e. metres) is possible for this species. Our meta-

bolic data show that different populations within the same

Antarctic region have different average metabolic rates at

both temporal and spatial scales, indicating that distinct

populations may respond differently to environmental

variables. We suggest that G. hodgsoni maintains a flexi-

ble life history strategy that allows its ecophysiological

response(s) to be dependent on local environmental con-

ditions. Accordingly, there may be no ‘typical’ response to

environmental changes—a factor that should be considered

in both future ecophysiological work and conservation

approaches.

Keywords Activity � Antarctica � Desiccation �Dispersal � Invertebrate � Metabolism � Physiology �Springtail

Introduction

The Antarctic terrestrial ecosystem consists of a large

expanse of seemingly inhospitable continental landscape.

However, within this cold, dry desert are small ice-free

pockets of accommodating habitat that collectively cover

some 0.34% (equating to a total of 46,200 km2; see

Table 1 in Convey et al. 2009) of an otherwise frozen

milieu. These ice-free areas contain remarkable micro-

habitats—home to a suite of largely endemic terrestrial

taxa that includes nematodes, rotifers, tardigrades, mites

and springtails (Pugh and Convey 2008).

This article is an invited contribution on Global Tipping Points

(Global Change and Antarctic Terrestrial Biodiversity) and part of the

SCAR EBA programme. I. Hogg and D. Wall (Guest Editors).

A. McGaughran

Allan Wilson Centre for Molecular Ecology and Evolution,

Massey University, Private Bag 11-222, Palmerston North,

New Zealand

I. D. Hogg

Centre for Biodiversity and Ecology Research, University

of Waikato, Private Bag 3105, Hamilton, New Zealand

P. Convey

British Antarctic Survey, Natural Environment Research

Council, High Cross, Madingley Rd, Cambridge CB3 OET, UK

Present Address:A. McGaughran (&)

Max Planck Institute for Developmental Biology,

Department for Evolutionary Biology, Spemannstrasse 37-39/IV,

72076 Tubingen, Germany

e-mail: ang.mcgaughran@gmail.com

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DOI 10.1007/s00300-011-1001-6

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Springtails, the largest microfauna of this group, are

nevertheless small in size (\1 mm), and collectively

dominate the Antarctic landscape in terms of diversity and

abundance (Wise and Gressitt 1965; Block 1994; Sinclair

et al. 2006). Springtail habitat in Antarctica is restricted to

moist ice-free areas such as lake and snow patch edges,

river beds, glacier foregrounds, and vegetated and other

damp soils (Kennedy 1993). At such sites, springtails

generally occur in the soil, vegetation, and/or on the

underside of rocks (Stevens and Hogg 2002). Within their

microhabitats, springtails are thought to feed on algae,

bacteria and fungal fragments, although few specific

studies have been completed (Davidson and Broady 1996;

Worland and Lukesova 2000).

To tolerate large fluctuations in temperature (sometimes

of[30�C daily) and multiple freeze/thaw events, Antarctic

springtails employ a multi-faceted operational strategy

(Block 1981; Block et al. 1988; Block 1990). First, they

exploit above-zero temperatures during the short austral

summer—maximising activity, growth/development and

reproduction and, in some cases, elevating their metabolic

rates to enhance this strategy (Block and Tilbrook 1975,

1978; McGaughran et al. 2009). The characteristics of this

first approach collectively enable springtails to adapt to

their chronically cold environment. Second, they have

some capacity for cold tolerance, achieved by supercool-

ing—maintaining body fluids in the liquid phase below the

freezing point of water (Block 1990; Sinclair and Sjursen

2001).

In addition to cold adaptation/tolerance, springtails must

tolerate elevated UV radiation and long periods of low

water and nutrient availability (Convey 1996; Peck et al.

2006). With their permeable cuticles and large surface

area: volume ratio, springtails should be highly susceptible

to desiccation stress in particular, and early physiological

work has demonstrated this. For example, in field studies

on Cryptopygus antarcticus (Antarctic Peninsula), animals

tested at 4�C lost water at all relative humidities except

water saturation (Elnitsky et al. 2008). Earlier laboratory

and field-work on this species has also shown a limited

resistance to desiccation and no physiological control over

water loss (Block et al. 1990; Harrisson et al. 1991; Block

and Harrisson 1995; Worland and Block 2003). With the

probable restrictions this places on movement between

microhabitats, taxa-specific dispersal mechanisms likely

contribute heavily to distribution patterns of Antarctic

invertebrates. Indeed, springtails are presumed to stay

within the (moist) soil column during dispersal in order to

avoid exposure to desiccating conditions.

Evidence for springtail dispersal has been largely cir-

cumstantial (Coulson et al. 2002; Hayward et al. 2004;

Nolan et al. 2006), with just one study addressing local

dispersal ability in the springtail C. antarcticus on the

Antarctic Peninsula (Hawes et al. 2007). Analysis of pop-

ulation genetic structure amongst species has shown that

contemporary springtail populations retain genetic links

even over distances exceeding 100 km—and that this has

involved occasional long-distance dispersal events (e.g.

Stevens and Hogg 2003; McGaughran et al. 2008, 2010a).

In the face of desiccating and other dispersal-related

stresses, how have springtails achieved their current

widespread Antarctic distributions and maintained (albeit

limited) gene flow amongst locations?

In addition to questions about springtail dispersal abil-

ity, little is known about other responses springtails may

have to their local environmental conditions. An evolu-

tionary assumption is often made that Antarctic taxa must

respond optimally to favourable environmental conditions

on the basis that costs (and hence selection) will be

incurred if they do not (Worland and Convey 2001). While

it is likely that environmental characteristics of the Ant-

arctic environment (e.g. length of growing season) may

drive the evolution of certain aspects of an organism’s life

history (Convey 1996), differences amongst Antarctic

springtail taxa, or even populations at the local scale, are

largely unquantified. In fact, physiological and ecological

investigations of Antarctic springtails have been dominated

by research, mostly using a single species (C. antarcticus),

in the maritime Antarctic. Some variables, such as meta-

bolic rate, were until recently, not measured anywhere on

the Antarctic continent (McGaughran et al. 2009, 2010b).

However, the springtail Gomphiocephalus hodgsoni has

been the focus of extensive ecophysiological and molecular

genetic work and is now one of the best-studied Antarctic

springtails.

Here, we further the ecophysiological research on this

species. Because recent work has shown that G. hodgsoni

Table 1 Table of temperature measures (average (SD), maximum,

minimum and range, �C) in air, taken at various times from automatic

weather stations located at Cape Bird and Taylor Valley (see

McGaughran et al. 2009)

Location Period Taverage (SD) Tmaximum Tminimum Trange

Cape Bird Dec 2006 -2.7 (2.2) 7.1 -9.6 18.1

Jan 2007 0.6 (1.3) 7.5 -3.6 11.1

Nov 2007 -7.5 (4.7) 7.2 -31.6 38.8

Dec 2007 -1.2 (3.0) 7.9 -7.4 15.3

Jan 2008 -0.9 (2.0) 7.2 -11.6 18.8

Taylor Valley Dec 2006 -3.8 (2.8) 2.6 -10.2 12.9

Jan 2007 -0.2 (1.2) 5.5 -5.5 11.0

Dec 2007 -2.0 (3.4) 6.7 -10.2 16.9

See the relevant soil data in Table 3 to see how the under-rock

microhabitat is buffered from air temperatures

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(as well as other species) has persisted in Antarctica

through long evolutionary periods (e.g. Fanciulli et al.

2001; Frati et al. 2001; Stevens and Hogg 2003; Convey

et al. 2008; McGaughran et al. 2008), we are particularly

interested in how, over time, this species has both: (1)

maintained links amongst isolated populations; and (2)

tolerated variable environmental conditions. Thus, we first

examined dispersal ability/desiccation tolerance in

G. hodgsoni during a season at Cape Bird, Ross Island (see

Fig. 1). Given the persistence of genetic relationships

amongst isolated populations, we expected that G. hodg-

soni would show some degree of dispersal ability. We

tested this hypothesis specifically by examining whether

individuals could survive periods of suspension on fresh or

sea water. We also monitored dispersal/activity-levels of

this species throughout the field season using aerial and

pitfall trapping. Next, in order to examine population

responses to environmental variables, we measured meta-

bolic rates of G. hodgsoni in Garwood Valley (Fig. 1),

which has both a cooler and drier climate than Cape Bird

(e.g. Table 1) (McGaughran et al. 2010b). We compared

these measurements to an existing metabolic rate dataset

that encompasses individual metabolic rate measurements

across both temporal and spatial scales in southern Victoria

Land (McGaughran et al. 2009, 2010b). Based on these

previous findings, we expected to see differences between

population metabolic rates measured across locations, due

to the variability of the environmental conditions they

experience.

Materials and methods

Study sites and animals

The work presented here covered two Antarctic field

seasons. During the first field season, ecophysiological

experiments were performed at Cape Bird (77�130S,

166�260E), an ice-free region at the northern tip of Ross

Island, Victoria Land, Antarctica (Fig. 1). All samples at

this location were collected under permit in Antarctic

Specially Protected Area (ASPA) 116 (http://www.era.

gs/resources/apa), which lies approximately 50 m south-

east of the Cape Bird research hut, during the periods:

12–23 November 2007 and 7–23 January 2008. During the

second field season, metabolic rate experiments were per-

formed at Garwood Valley (78�010S, 163�550E), a largely

ice-free inland southern Dry Valley (see Fig. 1), during the

period 22 December 2008–21 January 2009. The field site

was approximately 100 m east of the south-eastern outlet

of Lake Colleen, the main lake in Garwood Valley. In both

seasons, field periods incorporated the active period for G.

hodgsoni, and dates were further defined by logistical

constraints.

Microclimate measurements were taken at both study

sites using iButton thermochron temperature loggers

(DS1921; Dallas Semiconductors, Dallas, USA) placed

beneath rocks in vegetated areas around pitfall traps. These

logged temperature (±0.1�C) every 10 min throughout the

field seasons. Additional microclimate (temperature vari-

ables) data were used from McGaughran et al. (2009,

2010b), including both iButton data, and measures down-

loaded from automatic weather stations at Cape Bird and

Taylor Valley (see Table 1).

The springtail G. hodgsoni, endemic to Victoria Land,

was used for all analyses in this study. In all instances,

collections of large (presumed non-juvenile) animals were

made by either gently sweeping individuals off the

underside of small rocks into a collection vessel using a

very fine paintbrush, or by aspiration.

Cape Bird

We assessed dispersal ability in G. hodgsoni at Cape Bird

using three approaches. Our first approach was to assess

whether G. hodgsoni had any capacity for survival of the

likely timescales involved in local dispersal on water sur-

faces. We placed groups of ten springtails onto the water

surface of small containers (3 cm diameter; 5 cm depth),

filled with either freshwater (from melted snow) or sea-

water. In order to assess survival on the water surface at a

range of temperatures, five containers were placed at each

of three locations corresponding to: (1) an unheated room

inside the research hut (*13�C); (2) an auxiliary storageFig. 1 Study area showing the locations of Cape Bird and Garwood

Valley in southern Victoria Land, Antarctica

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hut (*4�C); and (3) an external space under the research

hut (*-3�C). Since no facility was available for precise

temperature control at this remote location, iButtons were

used to provide an estimate of the temperature ranges

experienced at each location. One container was removed

from each location every two days. Springtails were then

removed to damp filter paper and kept in a Petri dish, with

survival (the presence of directed movement) assessed

immediately, and at 24 h following removal. The con-

tainers from the external space froze overnight with

springtails still adhering to the surface, so these were also

used to determine whether springtails could potentially

survive contact with ice in this manner. This experiment

was performed in both the November and January field

periods.

Our second approach was to examine potential for local

near-surface wind dispersal. This was tested through the

use of aerial traps, deployed on 13 November 2007. Five

circular plastic containers (5 cm diameter; 10 cm depth)

were placed at each of two sites: a vegetated (moss) ‘val-

ley’ site known to harbour springtails and a nearby

(*10–20 m) shallow moraine ‘ridge’ site where springtails

are not known to be present. To exclude non-aerial matter

and to prevent springtails from crawling into the traps, a

ring of double-sided sticky tape was adhered to the top lip

of each trap. Each trap was held in place using large stones

and filled with a water-glycol mixture. Traps were sur-

veyed daily for evidence of wind-deposited springtails

during both the November and January field periods. Traps

were closed between the November and January periods

due to the absence of field personnel.

Our third assessment of dispersal (and activity), under-

taken in both the November and January periods, used

pitfall trapping. Ten small plastic containers (4.5 cm

diameter; 6 cm depth) were partially filled with glycol,

placed in a plastic (PVC) sleeve, and sunk into the ground

in the vegetated area on 13 November 2007. Each trap was

checked twice daily (at 0900 and 2100; encompassing the

period of direct sunlight at this site) for presence of

springtails (whereby presence in the trap indicated dis-

persal/activity of the species over the previous 12 h). Traps

were closed between the November and January periods

due to the absence of field personnel.

Garwood valley

Standard metabolic rates were measured at Garwood Val-

ley following the protocol used previously at Cape Bird

(see McGaughran et al. 2009, 2010b). In brief, this protocol

employed a fibre-optic oxygen sensing system (Ocean

Optics Inc., USA) to monitor oxygen partial pressure (pO2)

over time for individual animals in a closed respirometry

system with a 10-ll volume chamber. Oxygen partial

pressure was recorded continuously during each metabolic

run and completed partial pressure profiles were used to

calculate oxygen consumption rates on a per animal basis

for each individual, using the observed drop in pO2 over a

given time period in conjunction with the chamber volume.

Because accurate mass measurement was not possible at

this remote study location, individual animal mass was

calculated using a photographic technique (based on the

relationship between weight and length: W = 6.1894 L3.119

9 10-9, where W = weight (lg), L = length (mm), as

modelled for the similar sized maritime Antarctic springtail

C. antarcticus; see Block and Tilbrook 1975), and the

programme Screen Calipers ver. 3.3 (Iconico, Inc. 2006)

(see McGaughran et al. 2010b).

Following machine calibration, the above protocol was

employed over four successive five-day periods throughout

the field season (24 December 2008–19 January 2009) to

evaluate temporal variability in metabolic rates. Specifi-

cally, fresh animals were collected daily at a defined

location lying *100 m east of the camp site from the

underside of rocks and then stored for a *1-h acclimation

period in the tent alcove before metabolic measurement.

Each metabolic run was performed on groups of ten indi-

viduals, and lasted for a 2-h period, where the temperature

was maintained at 10�C (which is within the range expe-

rienced within the species’ typical microhabitats; see

McGaughran et al. 2010b), using a modified incubator

accurate to 0.1�C, and a 240 V generator as a power

source. Five runs (with ten fresh individuals per run) were

performed each day, such that each five-day period con-

sisted of 25 replicates (i.e. total n = 100). For consistency

with the literature, we present metabolic rates in units of

llO2 lg-1 hr-1. To achieve this, we divided the final result

of each metabolic run (i.e. the total drop in pO2) by the

calculated mass of the ten individuals in each run.

Following previously established quality control proce-

dures (see McGaughran et al. 2009, 2010b), blank runs

(n = 10) were completed during the experimental period

following the protocol above except without the addition of

animals to the measurement chamber. This provided an

estimate of the drift or ‘noise’ of the equipment used (data

not shown; see www.oceanoptics.com for information on

the resolution limits of the oxygen sensing system).

Statistics

All statistics were calculated using the programmes Mini-

tab (v. 14, Minitab Inc., Pennsylvania, United States) and

Microsoft Office Excel (v. 2003, Microsoft Corp., Wash-

ington, United States).

Specifically, paired t-tests were performed to evaluate

the difference in number of springtails caught per day in

pitfall traps between the two experimental periods at Cape

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Bird. An ANOVA was used to determine whether there

was any difference in average metabolic rate over the four

measurement periods at Garwood Valley. Significant dif-

ferences (P \ 0.05) in ANOVA were further analysed with

Tukey’s post hoc pairwise comparisons. Finally, regression

analyses were used to evaluate potential correlations

between both pitfall data (Cape Bird) and metabolic rate

(Garwood Valley), and environmental microclimate vari-

ables, including daily average, maximum, and minimum

temperature, and daily temperature range.

Results

Cape Bird

The total number of G. hodgsoni individuals surviving

suspension on freshwater and seawater for 2, 4, 6, 8 and

10 days is presented in Fig. 2. The survival rate was gen-

erally highest across treatments on Day 2 (54 and 35%

average survival for November and January, respectively),

decreasing consistently through to Day 10 (9 and 8%

average survival). In total, at least one individual survived

the entire 10-day period in three of the experimental

treatments, all of which were in the January period (Fig. 2).

A total of nine live springtails were caught in aerial traps

on five separate days in the January period at Cape Bird.

This included seven individuals collected at the vegetated

‘valley’ site, and two individuals (on two separate occa-

sions) at the non-vegetated ‘ridge’ site, which is not known

to be inhabited by springtails (Table 2).

In Figs. 3, 4, average daily microclimate temperature

data are superimposed on pitfall counts. Overall, the

number of springtails caught per day varied as the season

progressed for both the November and January field peri-

ods. The number of springtails caught per day in January

(mean ± SD = 49 ± 38) was not significantly different

from that in November (51 ± 41) (t18 = -0.16;

P = 0.871), despite an increased microclimate temperature

in January (Table 3). Our regression analyses found no

relationship between pitfall count and any of the daily

average, maximum and minimum temperature, or daily

temperature range (regression data not shown, but see

Figs. 3, 4).

Microhabitat temperatures at Cape Bird increased from

November (mean ± SD = 0.0 ± 1.5�C) to January

(4.3 ± 1.6�C) (Table 1, 3). In addition, the increases in

maximum, minimum and average under-rock temperatures

between these periods were 3.5, 7.1 and 4.3�C, respectively

(Table 1, 3).

Fig. 2 Number of springtails surviving in rafting experiments

performed on Gomphiocephalus hodgsoni at Cape Bird during

November 2007 and January 2008. Experiments were performed on

groups of ten individuals at three different experimental temperatures

(13, 4 and -3�C) in freshwater (FW) and seawater (SW). Results

were taken at both 0 h and 24 h, but here we present the 24 h data

Polar Biol (2011) 34:1713–1725 1717

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Garwood valley

Metabolic rates measured at Garwood Valley were signif-

icantly different amongst the four, five-day measurement

periods (F3,96 = 45.47; P \ 0.001). In particular, mass-

specific metabolic rate increased as the season progressed,

with the highest average rate (0.00095 ± 0.00033 (SD)

llO2 lg-1 hr-1), measured in the third measurement per-

iod (8–12 January 2009), despite average microhabitat

temperatures decreasing over this time (Table 3, Figs. 5,

6). Regression analyses showed a degree of weak, but

significant, correlation between metabolic rate measure-

ments and average daily maximum temperature and daily

temperature range, but not minimum daily temperature

(Table 4).

The temperature profile measured at Garwood Valley

showed some differences to the temperatures previously

recorded at Cape Bird, although we unfortunately lack

directly comparable microclimate data (Table 1, 3). We

interpret the data available to suggest that daily minimum

temperatures may be slightly lower at Garwood Valley

than at Cape Bird (-1.8 and -3.2�C for Cape Bird, Jan-

uary 2008 and Garwood Valley, January 2009, respec-

tively; Table 3), with the range of temperature variability

slightly greater at Garwood Valley (17.8� and 19.7�C;

Table 3).

In addition to evaluating temporal variability in meta-

bolic rates at Garwood Valley, we used data from previous

field seasons (2006–2008; see McGaughran et al. 2009,

2010b) to evaluate the spatial and temporal variation

amongst metabolic rate measurements for all measures

made to date, with temperature variables superimposed

(Figs. 7; 8). These figures highlight the uncoupling of daily

mean temperature from springtail metabolic rate (e.g.

12–22 November 2007 at Cape Bird and 1–19 January

2009 at Garwood Valley; Fig. 7).

Discussion

Historically, authors have presumed that the dry Antarctic

atmosphere would cause desiccation of springtails during

any dispersal attempts (e.g. Gressitt et al. 1960; Frati et al.

2001). Genetic patterns seemed to counter this assumption,

finding support for occasional long-distance dispersal

amongst populations in southern Victoria Land (e.g.

Table 2 Results of aerial trapping observations performed at Cape

Bird

Date Location No. of springtails

10 Jan Valley 2

14 Jan Ridge 1

15 Jan Valley 2

17 Jan Valley 2

Ridge 1

19 Jan Valley 1

Fig. 3 Total numbers of

springtails ± SD collected

during pitfall trapping at Cape

Bird in: a November 2007; and

b January 2008. Superimposed

on the bar-graph is a line-graphshowing the daily average

temperature under rocks, as

measured by iButton

temperature loggers

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Stevens and Hogg 2002, 2003; McGaughran et al. 2008).

Thus, we predicted that G. hodgsoni would show some

degree of dispersal ability in the face of environmental

conditions.

We showed this to be the case in our tests of the ability

of G. hodgsoni to survive suspension on both fresh and sea

water surfaces at different temperatures at Cape Bird. Our

experimental procedure at this remote location was unable

to control for relative humidity (RH) differences amongst

our treatments and we note that, as Antarctic springtails

tend to lose water rapidly at lower humidity levels (e.g.

Block et al. 1990; Harrisson et al. 1991; Block and

Harrisson 1995; Worland and Block 2003; Elnitsky et al.

2008), differences in RH between temperatures and treat-

ment locations may have affected survival. Despite possi-

ble RH effects, we showed that some G. hodgsoni

Fig. 4 Total numbers of springtails ± SD collected during pitfall

trapping at Cape Bird during November 2007 (grey bars) and January

2008 (black bars). Superimposed on the bar-graphs are line-graphs

showing the daily: (a, b) maximum, (c, d) minimum and (e, f) range,

of temperature under rocks, as measured by iButton temperature

loggers

Table 3 Average metabolic rate (llO2 lg-1 hr-1) and standard microclimate (temperature, �C) variable measurements for Gomphiocephalushodgsoni and various Antarctic locations over several time periods

Location Year Actual dates Metabolic rate (SD) a Taverage (SD) Tmaximum Tminimum Trange

Cape Bird 2006 24–31 Dec 0.0025 (0.0016) 2.4 (1.5) 11.2 -1.9 13.0

2007 1–23 Jan 0.0014 (0.0014) 4.9 (2.3) 17.1 -1.1 18.1

15–22 Nov 0.0027 (0.0015) 0.0 (1.5) 12.5 -8.9 21.4

2008 8–21 Jan 0.0105 (0.0025) 4.3 (1.6) 16 -1.8 17.8

18–21 Jan 0.0098 (0.0022)

Taylor Valley 2008 18–21 Jan 0.0134 (0.0067) 4.8 (1.7) 20.2 -4.2 24.4

Garwood Valley 2008 18–21 Jan 0.0166 (0.0052)

24–31 Dec 0.0004 (0.0001) 4.0 (1.8) 19.0 -2.0 21.0

2009 1–19 Jan 0.0007 (0.0003) 3.4 (1.5) 16.5 -3.2 19.7

Temperature variables were measured using iButton temperature data loggers placed in soil. In all cases, an absence of data means none was

available for the relevant perioda See McGaughran et al. 2009, 2010b

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individuals can survive suspension on both fresh and sea

water for at least ten days [see Hawes et al. 2008, for an

example of rafting in a springtail (Cryptopygus antarcti-

cus) from the Antarctic Peninsula], and that they can also

survive episodes of aerial dispersal at least over shorter

distances (e.g. up to *20 m; the distance from the main

springtail population location at Cape Bird to the site of our

aerial traps).

Surviving suspension on freshwater is likely to be ini-

tially important for dispersal of G. hodgsoni because

ephemeral glacial melt streams are common in the areas

they inhabit. A considerable number of individuals have

been shown to be swept away by such streams at Cape Bird

(Sinclair and Sjursen 2001). As many of these eventually

flow into the ocean, survival on seawater could be a sec-

ondary factor determining the success of any longer-dis-

tance dispersal episodes along the Antarctic coast. It is also

possible that individuals could reach the ocean by being

carried down-slope by wind, and we have shown here that

aerial dispersal, both of this nature, and in a lateral direc-

tion (towards moraine ridges) can occur. Thus, dispersal

methods may interact (e.g. wind transfer from water sur-

faces to ice-free habitats), as suggested by Hawes et al.

(2007). Depending on prevailing currents and surface

winds, survival for up to ten days of suspension on water

surfaces could be sufficient for springtails to occasionally

disperse successfully to other terrestrial sites within the

Ross Sea region (Fig. 1). This may be further enhanced by

the potential ability of an, albeit limited, number of

G. hodgsoni individuals to survive following adherence to

a frozen water surface as discovered here (see also Coulson

and Birkemoe 2000; Coulson et al. 2002).

Other studies have shown that, within the Dry Valleys,

viable soil invertebrates are dispersed by wind (Nkem et al.

2006) and that short-range dispersal occurs for springtails

on the Antarctic Peninsula (Hawes et al. 2007). Available

genetic evidence supports contact amongst populations

separated by up to 100 km (e.g. Fanciulli et al. 2001; Frati

et al. 2001; McGaughran et al. 2008). Such distances may

exceed the desiccation limits of these springtails for aerial

dispersal, but perhaps not their capacity for dispersal by

water, avifauna (such as the skuas that nest at Cape Bird),

or by some combination of these.

In addition to aquatic and aerial dispersal, pitfall trap-

ping demonstrates the ability of G. hodgsoni to disperse

locally through or over the soil surface at Cape Bird. Here,

we found that G. hodgsoni were present in pitfall traps

throughout the field season. Despite distinct differences in

the microclimate between the November (2007) and Jan-

uary (2008) periods (Table 3), there were no significant

differences in the number of springtails caught in pitfall

traps as the season progressed. Our regression analyses

between pitfall counts and microclimate temperature also

found no significant linear correlation between these vari-

ables. This suggests that G. hodgsoni maintains the ability

to disperse throughout the active period of the austral

summer and, to some extent, regardless of local environ-

mental temperature. While our experimental set-up pre-

cludes mechanistic evaluation of our pitfall data, it is worth

noting that springtails are clearly capable of soil dispersal

in the face of environmental constraints. We postulate that

the energetic demands of the summer season, during which

life history functions, such as reproduction and the

replenishment of nutritional status must take place

(cf. Wise and Spain 1967), may therefore override environ-

mental considerations in some instances (e.g. Clarke 1993).

Fig. 5 Mean metabolic

rate ± SD of Gomphiocephalushodgsoni over four five-day

sampling periods at Garwood

Valley, Antarctica.

Superimposed on the bar-graphis a line-graph showing the

daily average temperature under

rocks, as measured by iButton

temperature loggers

Table 4 Results of regression analyses of metabolic rate against

environmental (microhabitat) temperature measures (average, maxi-

mum, minimum and range) for Gomphiocephalus hodgsoni at Gar-

wood Valley

Taverage Tmaximum Tminimum Trange

16.32* 23.31* 0.27 24.87*

48.3 56.4 1.5 58.0

-0.00006 -0.00003 -0.00003 -0.00003

Measurements were made between 24 December 2008 and 19 January

2009. The upper value in the table is the F-test value (df = 1,18 in all

cases), the middle value is the regression coefficient (r2) and the lower

value is the regression slope (b); ‘*’ indicates P \ 0.05

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Previous work measuring temporal variation in meta-

bolic rates of G. hodgsoni at Cape Bird (McGaughran et al.

2009, 2010b) showed that metabolism is also to some

extent decoupled from the local microclimate—decreases

in mass-specific metabolic rates were demonstrated during

later season measurements at Cape Bird, while average

microhabitat temperatures increased over the same period.

Our study also confirms that variability in metabolic rate is

only partially linked to environmental variability for

G. hodgsoni at Garwood Valley. Here, the highest average

mass-specific metabolic rates were measured in the third

five-day measurement period, while microhabitat temper-

atures were highest in the first and second measurement

periods. This again supports the notion that systematic

metabolic rate variation in terrestrial Antarctic taxa may be

related to intrinsic energy requirements rather than solely

to environmental conditions (see McGaughran et al. 2009).

It is also clear from previous work that springtails are

able to exploit small thermal increments within micro-

habitats through an opportunistic elevation of metabolic

rate. For example, McGaughran et al. (2009) demonstrated

that average metabolic rate in populations of G. hodgsoni

can alter significantly over periods as short as ten days, and

substantial variation in annual metabolic rates of this spe-

cies was shown to be a largely environmental response

(McGaughran et al. 2010b). Here, we show that average

metabolic rate in this species can vary between periods as

short as five days.

As well as being temporally variable, metabolic rates of

G. hodgsoni populations have been shown to be spatially

Fig. 6 Mean metabolic

rate ± SD of Gomphiocephalushodgsoni over four five-day

sampling periods at Garwood

Valley, Antarctica.

Superimposed on the bar-

graphs are line-graphs showing

the daily: a maximum,

b minimum and c range, of

temperature under rocks, as

measured by iButton

temperature loggers

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variable (McGaughran et al. 2010b). This finding was

confirmed here, as metabolic rates of G. hodgsoni at inland

Garwood Valley were again different from those measured

previously at other sites. McGaughran et al. 2010b found

that populations from cooler, drier inland locations (Taylor

and Garwood Valleys) had higher metabolic rates than

those at the warmer coastal Cape Bird. This was not the

case here, as metabolic rates at Garwood Valley in

2008/2009 were shown to be the lowest measured to date

(see Fig. 5). This is possibly due to the artificial mea-

surement environment required during January 2008

(samples could not be processed in the field, and so were

returned to Scott Base for measurements; see McGaughran

et al. 2010b). In addition, samples would not have been

collected from precisely the same locations across seasons.

Finally, differences in microclimate amongst the locations

warrant further investigation. In particular, the lack of

correlation between metabolic rate and minimum daily

field temperature in G. hodgsoni from Garwood Valley is

in striking contrast to the results from Cape Bird, where

this correlation was the strongest measured (r2 = 37.6%

and 70.3% for two seasons at Cape Bird, respectively;

McGaughran et al. 2009, 2010b). While metabolic rates in

G. hodgsoni were highest during the third measurement

period at Garwood Valley (when daily average and maxi-

mum temperature, and daily temperature range were all

decreasing; Table 3, Fig. 4), this period also had the

highest minimum temperature (6b). In this context, daily

minimum microclimate temperature may still be the most

relevant local temperature variable for springtail responses.

Overall, our metabolic rate evaluation of G. hodgsoni

supports our hypothesis that population metabolic rates are

not only potentially flexible within seasons but also across

seasons and locations. Population differentiation in meta-

bolic rates has also been shown recently in the sub-Ant-

arctic springtail Cryptopygus antarcticus travei

(McGaughran et al. 2010c). This study underscored the

importance of considering metabolic rate differences

amongst populations in the context of underlying popula-

tion-genetic and geographic history alongside environ-

mental differentiation (McGaughran et al. 2010c).

In G. hodgsoni, life cycle differences between popula-

tions living at high and low altitudes have also been

demonstrated (Janetschek 1967). Coupled with our results,

this further suggests that, despite common life history

constraints, the physiological response of springtails may

be unique amongst specific environments. It is clear that

springtails such as G. hodgsoni have an impressive array of

life history characteristics enabling them to tolerate sub-

zero temperatures, freeze–thaw events, partial desiccation,

low nutrient availability and extreme variation in light

regimes (Janetschek 1967; Block 1990; Peck et al. 2006).

At a broad (seasonal) scale, many of these factors are

predictable. On shorter time scales, most are unpredictable

in both timing and duration (Peck et al. 2006). When

considered in this light, metabolic flexibility may exem-

plify an elegant strategy in springtails to cope with envi-

ronmental unpredictability (see also Block and Tilbrook

1975, 1978; McGaughran et al. 2009). Indeed, plasticity is

common amongst springtails, and in many tropical and

temperate habitats, springtails are also able to quickly

respond to changes in nutrient status and resource inputs

(e.g. Zinkler 1966; Testerink 1983; Addo-Bediako et al.

2002).

Through dispersal and metabolic rate measurements, we

have shown that G. hodgsoni populations in southern

Victoria Land are sustained by a flexible life history

strategy that is to some extent uncoupled from the local

microhabitat temperature profile. We suggest that the

demand to complete essential life history functions over the

brief austral summer may override environmental con-

straints in this context. Our approach also highlights the

Fig. 7 Spatial and temporal

metabolic rate variation in

Gomphiocephalus hodgsoni at

various locations and times in

southern Victoria Land.

Superimposed on the bar-

graphs are line-graphs showing

the daily average temperature

under rocks, as measured by

iButton temperature loggers.

Data for the periods December

2006–January 2008 were

recalculated from McGaughran

et al. 2009, 2010b

1722 Polar Biol (2011) 34:1713–1725

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unique nature of G. hodgsoni at both the individual and

population levels—a characteristic that may also be true for

other terrestrial Antarctic taxa. When developing

conservation strategies for G. hodgsoni and other Antarctic

biota, this lack of representativeness of any one population

should be taken into account.

Fig. 8 Spatial and temporal

metabolic rate variation in

Gomphiocephalus hodgsoni at

various locations and times in

southern Victoria Land.

Superimposed on the bar-

graphs are line-graphs showing

the daily: a maximum,

b minimum and c range, of

temperature under rocks, as

measured by iButton

temperature loggers. Data for

the periods December 2006–

January 2008 were recalculated

from McGaughran et al. 2009,

2010b

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Acknowledgments We thank Laurie Beth Connell and two anon-

ymous reviewers for their constructive comments on an earlier ver-

sion of the manuscript. We are also grateful to Antarctica New

Zealand for their logistical support. Funding for this project was

provided by a New Zealand Tertiary Education Commission Top

Achiever Doctoral Scholarship and a Sir Robin Irvine Doctoral

Scholarship to AM, with the latter also supporting PC’s fieldwork;

and by a New Zealand Foundation for Research Science and Tech-

nology Grant (UOWX0710) to IH. This paper forms a contribution to

SCAR’s Evolution and Biodiversity in the Antarctic (EBA), Antarc-

tica New Zealand’s Latitudinal Gradient Project (LGP), and British

Antarctic Survey’s Polar Science for Planet Earth (PSPE) research

programmes.

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