Antarctic Science 20 (1), 61–67 (2008) & Antarctic Science Ltd 2008 Printed in the UK
DOI: 10.1017/S0954102007000685
Influence of temperature and moisture availability on physical rock
weathering along the Victoria Land coast, Antarctica
CHRISTINE ELLIOTT
Department of Geography, University of Canterbury, Private Bag 4800, Christchurch 8140, New Zealand
[email protected]
Abstract: Rock weathering plays an important role in soil development. A better understanding of how
different temperature and moisture regimes impact on the rates of rock breakdown can thus contribute to
our knowledge of how rates of soil production might be affected by changes in climate. Laboratory
simulations using two temperature cycles determined from field data and three moisture levels were carried
out on samples of granite from three locations along the Victoria Land coast. Estimates of weathering rate
from these experiments were of the same order of magnitude as some other more field based studies
undertaken in similar environments. However, actual values for samples from the three locations varied
depending on the specific characteristics of the rock, especially grain size, porosity and extent of microcracking. Moisture availability was found to be an important factor in determining weight loss in the
samples from Gneiss Point but not in those from Terra Nova Bay or Teall Island with the moderate level
of moisture application having the greatest impact. Spring/autumn temperature cycles had a different effect
on the breakdown of the rock samples compared to summer cycles but the magnitude of the effect was
dependent on moisture level and rock characteristics, especially quartz content and the ability to absorb
heat and moisture. The samples of rock from Terra Nova Bay and Gneiss Point where no moisture had
been applied had significantly higher rates of breakdown under spring/autumn cycles than summer ones.
However, this effect was reversed in the Gneiss Point samples after moisture was added. A future climate
scenario using the weathering rates found in this research where there was, for example, a 10% increase in
summer temperature cycles and a corresponding decrease in spring/autumn cycles predicted that a
reduction in weathering would occur in conditions of little or no precipitation at Terra Nova Bay and
Gneiss Point but there would be limited effect under higher levels of moisture.
Received 9 February 2006, accepted 10 May 2007
Key words: freeze-thaw, Granite Harbour Intrusives, laboratory simulations, Latitudinal Gradient Project,
rock characteristics
Introduction
breakdown (e.g. Yoshikawa et al. 2000, Hall et al. 2002),
data on the effects of different moisture levels is scarce.
Current rock weathering rates are very slow in the Arctic
and Antarctic. For example, estimates of 0.3 mm a-1 in
Svalbard (Jahn 1976) or between 0.2 and 110-9 mm a-1
in the McMurdo Dry Valleys (Summerfield et al. 1999) are
similar to those found by André (1995) for crystalline
rocks in Scandinavian Lapland. However, it is not known
what effect changes in temperature and precipitation may
have on weathering rates.
This research used laboratory simulations to determine
rates of physical rock weathering of granite collected from
three locations on the Victoria Land coast. Laboratory
simulations are a common means of estimating weathering
rates (e.g. Hall & Hall 1996), but Goudie (2000)
recommends that they be based, as much as possible, on
field data and Robinson & Williams (1994) stressed that it
was the conditions of the rock rather than the atmosphere
that were important. Using data gathered in the field the
effects of two different rock temperature cycles and three
One of the aims of the Latitudinal Gradient Project (LGP) is
to investigate how soil development changes with latitude
and how this might, in turn, affect terrestrial ecosystems
(Peterson & Howard-Williams 2001, Howard-Williams
et al. 2006). This is especially important because Antarctic
soils are “particularly fragile” (Campbell et al. 1997 p. 45)
and least well developed in coastal areas (Bockheim 2002).
The weathering of rock provides materials and nutrients for
soil to form and so changes in the rate at which weathering
occurs may, through its effect on soils, influence the
development of Antarctic ecosystems.
The principal factors controlling rock weathering are the
rock itself, the climate and the length of time over which
the weathering has operated (Robinson & Williams 1994).
More recently, it has been recognized that it is the climate
at the grain surface that is most important, in particular
the temperature and moisture conditions (Warke 2000).
Although moisture conditions have been highlighted as
being significant in determining the rate at which rocks
61
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62
CHRISTINE ELLIOTT
Fig. 1. Location of field sites in Antarctica.
moisture levels on the rate of break down of samples of rock
from the three locations were investigated.
Methodology
Field locations and data
Three field locations (Terra Nova Bay: 74841’S, 164807’E,
Gneiss Point: 77824’S, 163842’E and Teall Island: 79803’S,
161856’E) were selected along the Victoria Land coast
(Fig. 1). These sites were chosen because they all had
exposures of Granite Harbour Intrusives and they provided
a latitudinal variation of approximately 4.58. One rock
group was selected to minimize the potential influence of
rock characteristics on the results and within this rock group
outcrops of medium-coarse grained granite were targeted.
The surface temperatures of large outcrops of rock
were measured using 1 mm diameter copper-constantan
thermocouples which were attached to the surface using an
epoxy resin. Where practical the head of the thermocouple
was covered with a rock chip or rock flour to maintain
conditions as close as possible to those of the rock surface.
Surface moisture was measured using a sensor that detected
the presence of rainfall, dew, fog or snow. It consisted of a
continuous loop of aluminium on a flat, rectangular board
11.5 by 7.5 cm with a track spacing of 1 mm. The narrow
track spacing meant that the sensor could detect even the
smallest amounts of moisture reaching the rock surface.
The sensor responds to the presence of liquid water by
recording conductivity and a zero value was returned
when either no moisture was present or the surface was
frozen (Elliott 2004). The sensors and thermocouples were
connected to a Campbell CR10X datalogger which
scanned at intervals of 20 seconds and stored averages at 1
or 3 hours. Subsurface moisture at 45 mm and 90 mm
depths within the rock was recorded every four hours
during times of field visits using a Vaisala Relative
Humidity probe originally designed to measure moisture in
concrete. The tip of the probe was made of a moisture
sensitive polymer and the relative humidity, temperature,
and dewpoint temperature of the air pocket at the tip of the
probe were determined after the air in the pocket had been
allowed to equilibrate to the temperature of the vapour in
the rock. This was for at least 4 hours, and data recorded
over several weeks/months. An empirical formula suitable
for temperatures between 508C was then used to calculate
the vapour densities from the measured relative humidity
and temperatures (Lowe 1977). Relative humidity,
generally between 20% and 40%, was also collected during
field visits using a Kestrel 4000 (a hand held instrument
for measuring climatic variables).
The rock temperature and moisture levels were recorded
for two aspects (south and west) at each of the sites during
three summer seasons: 2002/03, 2003/04 and 2004/05
(Table I). Twelve month data was collected at Terra Nova
Bay and Teall Island west-facing sites between November
2003 and November 2004 as well as the south-facing Teall
Island site. Measurements on all four aspects and for all
three seasons would have been ideal but equipment and
Table I. Times, aspect and frequency of data collected in the field.
Location
2002/03
Gneiss Point
Terra Nova Bay
Teall Island
1
Dates of continuous data collection
2003/04
2004/05
25/10/02– 18/1/03
N/A
N/A
14/11/03–14/1/04
N/A
N/A
17/1/04–31/10/04
20/11/03– 18/11/04
Frequency of
collection1
Aspect for which
collected
1 hr
1 hr 2003/04
3 hr 2004/05
3 hr
S, W
S, W
W
S, W
One minute data was also collected during every visit.
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TEMPERATURE AND MOISTURE IN ROCK WEATHERING
Table II. Characteristics of the rock samples from each location.
Terra Nova Bay Gneiss Point Teall Is.
Physical properties
Grain size
Medium/large
fine
medium
Effective porosity (%)
1.3
0.5
1.0
2547
2629
2555
Density (kg cm-3 )
Thermal conductivity (Wm-1 K-1 )
4.0
3.4
2.9
Sorptivity1 (g hr-1=2 )
0.79 (0.74)
0.13 (0.07) 3.03 (1.54)
Mineralogy
Quartz (%)
36
36
29
Plagioclase feldspar (%)
26
39
2
Alkali feldspar (%)
20
11
60
Biotite (%)
15
14
9
Other (%)
2
Micro-cracking extent
extensive little evidence extensive
1
A measure of the ability of a rock to absorb moisture (Alexander et al.
1999). Measured both at room temperature and below zero (figures in
brackets).
logistic constraints meant this was not possible. South and
west aspects were chosen because it was anticipated that
these would usually produce the greatest contrasts in terms
of climatic conditions. However, Hall (1998) reported that
the northern aspect sometimes experienced the lowest rock
temperatures in his study on the Antarctic Peninsula. In
order to conserve battery life and memory capacity one
hour averages were calculated for summer measurements
and three hour averages for 12 month measurements.
Rock samples
Boulders of Granite Harbour Intrusives were gathered at each
field location and samples (1055 cm) were later cut
from these. The boulders had been examined visually for
soundness in the field before being selected but those
that showed significant internal weathering or cracking
during sample preparation were subsequently discarded.
Although one rock group was selected differences in the
Fig. 2. Mean of the Terra Nova Bay and Teall Island three hourly
west-facing rock surface temperatures between November 2003
and November 2004 used to determine experimental temperature
cycles.
63
characteristics of the rocks between sites were evident. This
was particularly the case for grain size, porosity, thermal
conductivity and sorptivity (Table II).
Laboratory simulations
The laboratory simulations were conducted using a commercial
freezer that had been adapted for the purpose. The freezer had a
fan that circulated the air and holes were drilled (and
subsequently sealed) to enable four thermocouples and an
intake for dry air to be inserted. The freezer was programmed
to undertake temperature cycles that were estimated from
the rock surface temperatures gathered in the field. The
temperature cycles were determined using the average of the
surface temperatures from the west-facing aspect at each
location (Fig. 2). The west-facing aspect was chosen partly
because of its exposure to the Antarctic Ice Sheet and partly
because this was the aspect for which 12 month data was
available. Summer was deemed to occur between the
beginning of December and the end of January and spring/
autumn the two months of November and February.
Although an attempt was made to fit curves to the data using
Fourier series this was not particularly successful so the 75th
and 25th percentiles were calculated and the inter-quartile
range was used to estimate the temperature cycles to be used
in the simulations (Table III).
In order to complete the experiment in a reasonable time
frame it was necessary to accelerate time. This is a
common approach in rock weathering simulations.
Lautridou & Seppala (1986) for example, used a
temperature change of 3 – 48C hr-1 until temperatures
reached -58C and then 58C hr-1 thereafter whereas Hall
(1988) used a variety of rates of change from 18C hr-1 to
68C hr-1 . Six cycles per 24 hours provided a timescale that
was feasible within the time available for this experiment
and gave temperature gradients that were consistent with
Lautridou & Seppala (1986) and Hall (1988) (Table III).
The summer and spring/autumn temperature cycles only
were undertaken.
Three moisture levels were applied to five replicates from
each of the three locations. After investigating various methods
of wetting the rock samples, it was decided to moisten them by
soaking at room temperature at intervals of 3–4 days. A small
controlled experiment was undertaken to estimate potential
soaking times that would approximate ‘half’ and ‘full’
saturation of the least porous of the rocks (Gneiss Point,
Table II). Five replicates from each location were then soaked
for seven minutes to simulate ‘half’ saturation and another set
of five replicates soaked for one hour to simulate ‘full’
saturation. The exterior was patted dry using an absorbent
towel and the samples were re-weighed before being returned
to the freezer. One set of replicates received no soaking.
Within the freezer thermocouples were attached to the
surface of one rock sample from each of the locations and a
fourth was used to monitor the air temperature. The
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64
CHRISTINE ELLIOTT
Table III. Estimated rock surface temperatures used in the simulations and resultant freezer temperature of the air in the freezer.
Period
Summer (1/12– 31/1)
Spring/Autumn (1/11– 30/11 & 1/2–28/2)
Winter (1/3 –31/10)
No. of days
Inter-quartile
range
(8C)
Rate of change
of temperature
(8C hr-1 )
Freezer (air)
temperature
(8C)
Rate of change of
freezer (air) temperature
(8C)
62
58
245
þ6 to 0
þ2 to -6
-20 to -30
3
4
5
þ5 to -1.5
þ1 to -8
N/A
3.25
4.5
N/A
temperature of a thermocouple attached to one of the Gneiss
Point samples that was not to be soaked was used to switch
the freezer on and off and produce the required temperature
cycles (Table III). This meant that the air temperature in the
freezer was a response to the cycling of the surface of the
Gneiss Point rock rather than the other way round.
The actual as well as relative humidity of the freezer were
also recorded and dry air was pumped into the freezer when
the uppermost tolerance level for humidity was reached
(based on the relative humidity levels recorded in the
field). In practice this was rarely needed as the low
temperature levels of the freezer maintained the necessary
humidity levels.
values more than 3 box lengths from the upper or lower
edge of the box, where the box length is the interquartile range) and the extremes were excluded from the
subsequent statistical analysis to prevent the results from
becoming overly influenced by these values. One-sided
paired sample t-tests were conducted to compare weight
loss between the initial weights and those after each set of
temperature cycles. Analysis of variance was undertaken
when comparing means between moisture levels for the
three temperature cycles.
Repeated measures analysis was used to investigate any
significant moisture-cycle interaction or main moisture or
temperature cycle effects (i.e. the effect of moisture over all
temperature cycles or the effect of temperature cycles over
all moisture levels). This technique has been used in
ecological studies and applies to situations where there are
a number of population groups each of which is measured
over either different time intervals or sets of treatments
(von Ende 1993). In this case the three moisture levels are
the population groups and the temperature cycles are the
second set of treatments, which are considered as
dependent variables.
Determination of weathering rates
The same set of samples were subjected to a simulated five
years of weathering using the calculated temperature cycles
(371 cycles between þ6 and 08C and 354 cycles between
þ2 and -68C) and moisture levels. Weathering effects were
then estimated by measuring changes in the dry weight of
the samples (e.g. Hall & Hall 1996). Prior to the start of
the temperature cycling the samples had been oven dried at
60 to 658C, weighed to an accuracy of three decimal
points of a gram and their effective porosity determined by
comparing dry and vacuum saturated weights. The samples
were oven dried slowly over two days at the end of each
set of temperature cycles and the weights recorded and the
cycles were run back to back.
Weight loss can be greatly influenced by the particular
micro-characteristics of the individual samples, particularly
grain size and extent of micro-cracking, and so within
group changes were examined at the end of each set of
temperature cycles using a series of box plots (McClave &
Sincich 2000). These identified both ‘outliers’ (defined as
cases with values between 1.5 and 3 box lengths from the
upper or lower edge of the box, where the box length is the
inter-quartile range) and ‘extremes’ (defined as cases with
Results
After simulation of five years of weathering weight loss (P ,
0.05) was recorded for the rock samples from all locations at
every moisture level (Table IV). A plot of proportional weight
loss (10-5 ) against location is given in Fig. 3. The greatest
weight loss at each moisture level was for the Terra Nova
Bay samples and within that group the greatest weight loss
was for those samples that had received most moisture. The
Gneiss Point samples experienced least weight loss,
regardless of moisture level, but within the Gneiss Point
and Teall Island samples it was the lower of the two
moisture levels where most loss occurred. However,
variability between replicates meant that a significant
moisture effect (P , 0.005) was found only in the Gneiss
Table IV. Weight loss following all temperature cycles (where n is the number of replicates and s.d. is the standard deviation of the samples).
Moisture level
n
No moisture
Half saturation
Full saturation
3
4
4
Terra Nova Bay
Mean (g)
s.d.
0.066
0.076
0.083
0.002
0.020
0.019
n
Gneiss Point
Mean (g)
s.d.
n
Teall Island
Mean (g)
s.d.
5
5
5
0.037
0.046
0.035
0.010
0.025
0.029
4
5
5
0.044
0.059
0.052
0.004
0.013
0.024
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TEMPERATURE AND MOISTURE IN ROCK WEATHERING
65
Estimates of weathering rates were made by calculating the
amount of surface lowering (dx) of the rock blocks using the
measured weight loss and the previously calculated density
of the blocks:
dx ¼ ½dm=ðr surface areaÞ=5 mm a-1
ð1Þ
Fig. 3. Proportional weight loss for the cumulative effect of all
temperature cycles. Error bars are 1 s.e. from the mean.
Point samples between the half saturation and no moisture and
the half saturation and full saturation samples (Fig. 3).
Following the þ5 to -1.58C temperature cycles, significant
weight loss (P , 0.05) occurred at the end of each set of
temperature cycles (Table V) with the exception of the
Terra Nova Bay no-moisture samples. Repeated measures
analysis indicated that there was a statistically significant
(P , 0.05) linear temperature cycle effect for the samples
from all three locations i.e. weight loss was affected by the
particular temperature cycle being undertaken. However,
the effect of the temperature cycle varied depending on the
levels of moisture used. In particular, the Terra Nova Bay
no-moisture samples experienced more than six times the
proportional weight loss as a result of the þ1 to -88C
cycles compared to the þ5 to -1.58C cycles. This was also
the case for the Gneiss Point samples where the þ1 to
-88C cycles had three times the effect of the þ5 to -1.58C
cycles. However, when moisture was applied to the Gneiss
Point samples the þ1 to -88C cycles could be less than
half as effective as the þ5 to -1.58C cycles (Table V).
Table V. Effect of different temperature cycles on proportional weight loss
of the replicates (see Table IV for numbers of replicates, weights and
standard deviations).
Moisture level
and location
Terra Nova Bay
no moisture
half saturation
full saturation
Gneiss Point
no moisture
half saturation
full saturation
Teall Island
no moisture
half saturation
full saturation
Effect of þ5 to -1.58C
temperature cycles
(proportional weight
loss10-5 )
Effect of þ1 to -88C
temperature cycles
(proportional weight
loss10-5 )
Ratio
1.3
5.8
5.2
8.5
5.8
7.0
6.6
1.0
1.3
1.3
3.7
3.5
3.9
2.5
1.5
3.0
0.7
0.4
3.3
4.9
3.5
3.1
3.4
4.5
1.0
0.7
1.3
where dm is the relevant weight loss in grams and r is the
density in g mm-3
Across all samples the average rate of surface lowering was
0.1610-3 mm a-1 but, depending on the particular samples,
this ranged from 0.1110-3 mm a-1 (Gneiss Point) through
0.1610-3 mm a-1 (Teall Island) to 0.2310-3 mm a-1
(Terra Nova Bay).
Discussion
The estimated weathering rates found in this experiment were
of the same order as those found by Summerfield et al.
(1999) using cosmogenic isotope dating for the McMurdo
Dry Valleys and André (1995) for crystalline rocks in
northern Scandinavia using field methods. Spate et al.
(1995) found much higher estimates of weathering
rates using micro-erosion meters on the high quartz content
gneiss of the Larsemann and Vestfold hills, East
Antarctica. Samples of granite from each of the locations
investigated in this research were all subjected to the same
temperature and moisture conditions in the freezer and yet
produced markedly different weathering rates. The strength
of granite is affected by grain size and shape, quartz
content, porosity and extent of micro-cracking (Attewell &
Farmer 1976). Although smaller grain size increases rock
strength (because of greater inter-grain contact), the length
of contact between grains can decrease the strength as a
result of increasing susceptibility to weaknesses at grain
boundaries. In addition, the tensile strength of a rock is
inversely proportional to its quartz content so that the
greater the quantity of quartz the weaker the rock (Merriam
et al. 1970). Low porosity and high density rocks are also
stronger.
The Gneiss Point granite was fine grained, the least porous
and revealed little micro-cracking under thin section analysis
(Table II) supporting the lower of the weathering rate
estimates of 0.1110-3 mm a-1 . In contrast the Terra Nova
Bay granite had medium to large sized grains, the highest
level of porosity of the rocks investigated and showed
evidence of extensive micro-cracking resulting in a higher
weathering rate of 0.2310-3 mm a-1 . The Teall Island
rock had middle values of these characteristics and an
estimated weathering rate of 0.1610-3 mm a-1 . However,
both the Terra Nova Bay and the Gneiss Point rock had the
same proportion of quartz (36% as determined by modal
analysis) indicating that grain size and porosity had a
greater influence on the weathering rate of these rocks than
quartz content. Therefore, the specific combination of rock
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66
CHRISTINE ELLIOTT
Table VI. Predicted change in weathering following a 10% increase in summer temperature cycles (see Table IV for numbers of replicates, weights and standard
deviations).
Location
No moisture
Current
After 10% increase
in summer cycles
Terra Nova Bay
Gneiss Point
Teall Island
9.8
5.2
6.4
9.1
4.3
6.4
characteristics, even within the same rock group, can have an
important role in determining weathering rate.
Global Climate Models (GCMs) predict that the effects of
any future climate change will be greatest at the poles,
particularly in winter (Callaghan et al. 1999). Any change in
climate is likely to manifest itself as increased temperatures
(perhaps by as much as 2.58C by 2050) and precipitation,
although the effect on the latter is less clear (Fitzharris 1996).
Fountain et al. (1999) expected that even very small
variations in temperature and precipitation, because they can
lead to extreme variations in the hydrologic regime, would
have a potentially great impact in Antarctica.
The temperature of the freezer in this experiment can be
considered to be the air temperature for this part of the
Victoria Land coast and the two cycles considered
as proxy summer (þ5 to -1.58C) and spring/autumn (þ1
to -88C) air temperatures. The three moisture levels can
also be considered as proxies for three different
precipitation scenarios. The results of the effects of the two
temperature cycles and three moisture levels employed in
the laboratory simulations can then be used to infer what
may happen to rates of weathering of granite rocks from
these three locations should there be future shifts in
temperature and precipitation.
As noted earlier, under the same temperature conditions,
more physical weathering occurred in the Terra Nova Bay
samples than either Teall Island or Gneiss Point regardless of
moisture level but the presence of additional moisture
appeared to enhance the weathering effect (Fig. 3). However,
a significant moisture effect was only found in the Gneiss
Point samples between the half saturation and no moisture
and the half saturation and full saturation samples indicating
that moderate levels of moisture were more effective in
producing weight loss in these rocks than either low or high
levels. The lack of a significant moisture effect in the Terra
Nova Bay and Teall Island samples implies that, at least
under the moisture conditions used here, increased
precipitation would have little influence on weathering rate.
The finding of a significant temperature cycle effect for the
samples from all three locations indicates that a change in
the ratio of summer (þ58C to -1.58C) to spring/autumn
(þ1 to -88C) temperatures could produce a change in
weathering rate (Table V). For instance, a climate scenario
where there was a change in air temperature sufficient to
Proportional weight loss (10-5 )
Half saturation
Current
After 10% increase
in summer cycles
11.6
6.2
8.2
11.6
6.3
8.4
Full saturation
Current
After 10% increase
in summer cycles
12.2
5.0
7.9
12.0
5.2
7.8
produce a 10% increase in the number of summer cycles
(and a corresponding 10% decrease in spring/autumn
cycles) is given in Table VI. Winter rock temperatures
were so much lower (-20 to -308C) than either the summer
or spring/autumn temperatures that it was assumed any
moderate increase in air temperature would be insufficient
to affect the number of winter cycles.
Because the effect of the two temperature cycles differed
depending on moisture level (Table V) a 10% change in
the ratio of spring/autumn to summer temperature cycles
was only noticeable in the no moisture samples from Terra
Nova Bay and Gneiss Point (Table VI). The much greater
influence of the spring/autumn (þ1 to -88C) temperature
cycles in producing rock breakdown resulted in a reduction
in proportional weight loss in the samples. This implies
that a change in air temperature sufficient to increase the
number of summer (þ5 to -1.58C) temperature cycles, and
a similar reduction in the spring/autumn ones, is more
important than the levels of moisture in determining rates
of weathering. However, the magnitude of this effect was
dependent on the particular rock samples so that those
from Terra Nova Bay and Gneiss Point that had the higher
levels of quartz and thermal conductivity but lower levels
of sorptivity were affected the most and these differences
appeared to override other differences such as porosity and
grain size (Table II). Consequently, when investigating
weathering rates under different temperature regimes the
proportion of quartz in the rock, together with the ability of
the rock to absorb heat and moisture should be considered.
Conclusions
Estimates of weathering rates following a simulated five
years of weathering were of the same order of magnitude
as those found in other studies but varied according to the
particular characteristics of the rock, especially grain size,
porosity and extent of micro-cracking. Rates, as determined
by measured weight loss, were greatest in the Terra Nova
Bay samples and least in the Gneiss Point samples,
regardless of moisture level. However, a significant
moisture effect was only found between the half saturated
and no moisture and the half saturated and full saturation
Gneiss Point samples, implying that lower levels of
moisture were more effective than higher ones in producing
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TEMPERATURE AND MOISTURE IN ROCK WEATHERING
weight loss. The temperature cycle used had a significant
effect on the rates of breakdown of samples from all the
locations but the magnitude of this effect varied with
moisture level. For instance, the Terra Nova Bay no
moisture samples experienced more than six times
the weight loss following the spring/autumn cycles (þ1 to
-88C) than the summer ones (þ5 to -1.58C). The spring/
autumn cycles also produced more weight loss in the
Gneiss Point no moisture samples but the addition of
moisture reversed this effect so that the spring/autumn
cycles could be as much as 40% less effective than
the summer ones. When comparing weathering rates
under different temperature regimes quartz content,
thermal conductivity and sorptivity were the important
characteristics of this rock type. The different effect of the
temperature cycles indicated that under a future climate
scenario where there was, for example, a 10% increase
in the number of summer temperature cycles and a
corresponding decrease in the spring/autumn ones little
change in weathering rate would occur at Teall Island
regardless of increases in moisture. However, weathering
rate decreased in the samples from Terra Nova Bay and
Gneiss Point that had no moisture added.
Acknowledgements
Grateful thanks to my supervisors; Ian Owens, Barry
Fahey and Bryan Storey and to the Department of
Geography and Gateway Antarctica at the University of
Canterbury. Also to Antarctica New Zealand for their
financial, logistical and other support and to the Italian
Antarctic Programme for their patience, support and
hospitality during the time spent at Terra Nova Bay. I
would also like to thank the reviewers whose comments on
the initial draft have made this a much improved paper and
to Megan Balks from the University of Waikato for reading
and commenting on this draft.
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