1. NEWS & VIEWS RESEARCH
that drive movement within a system. accomplish analogous adaptive behaviours.
The rhythmic swelling and deswelling of Advances in this area could lead to multi-
a
gels has been harnessed to push micro­metre- functional systems that have one structure
sized particles and cells along a surface 6. and function in one environment, but another
Heat-responsive gels have also been used to shape and function under different condi-
drive micrometre-sized posts in and out of a tions. However, to undergo significant shape
bath of solution7: when the system was hot, changes, the material must be very flexible. It
the gel shrank, pulling the posts out of the might be that the introduction of just the right
bath, but when the system cooled down, the amount of loops within a polymer network
gel expanded and pushed the posts back in. could lead to robust, but sufficiently flexible,
This behaviour formed the basis of a homeo- shape-changing materials. With findings
static device that autonomously regulated from NDS, perhaps researchers will eventu-
b
the temperature of the system. For optimal ally establish effective routes for making gels
performance, such soft actuators need to be that act like cuttlefish. n
mechanically robust — which means that they
should not contain wasted loops. Anna C. Balazs is in the Chemical
On the other hand, because NDS can yield Engineering Department, University of
correlations between mechanical properties Pittsburgh, Pittsburgh, Pennsylvania 15261,
and the fraction of loops in a gel, it might help USA.
to provide design rules for exploiting loops, e-mail: balazs@pitt.edu
perhaps leading to the development of robust
materials that nonetheless are highly flexible. 1. Gong, J. P. Soft Matter 6, 2583–2590 (2010).
2. Zhou, H. et al. Proc. Natl Acad. Sci. USA 109,
Figure 1 | Primary loops in cross-linked polymer In particular, there is rapidly growing inter- 19119–19124 (2012).
networks. a, In an ideal polymer network, every est in reconfigurable materials that can dra- 3. Panyukov, S. & Rabin, Y. Phys. Rep. 269, 1–131
polymer strand forms connections to other matically change shape in response to external (1996).
strands, strengthening the resulting material. cues8–10. Examples abound in biology, because 4. Yashin, V., Kuksenok, O., Dayal, P. & Balazs, A. C.
b, Primary loops form if a strand closes on itself Rep. Progr. Phys. 75, 066601 (2012).
without connecting to other chains. The presence
such adaptive behaviour is vital for survival —
5. Cohen Stuart, M. A. et al. Nature Mater. 9, 101–113
of such loops reduces the strength of the material. consider, for example, the ability of octopuses (2010).
Zhou et al.2 report a method for quantifying the and cuttlefish to change their shape, colour and 6. Yoshida, R. Sensors 10, 1810–1822 (2010).
number of loops in the polymer network of a gel. texture in order to camouflage themselves in 7. He, X. et al. Nature 487, 214–218 (2012).
the presence of predators. Because gels can be 8. Guillet, P. et al. Soft Matter 5, 3409–3411 (2009).
9. Yashin, V. V., Kuksenok, O. & Balazs, A. C. J. Phys.
loops had formed, different degradation prod- made to shrink and swell controllably, they can Chem. B 114, 6316–6322 (2010).
ucts (with their own characteristic molecular be driven to change shape, and thus are ideal 10. Ueno, T., Bundo, K., Akagi, Y., Sakai, T. & Yoshida, R.
masses) would be obtained. By measuring the synthetic materials for creating systems that Soft Matter 6, 6072–6074 (2010).
masses of the actual degradation products and
comparing them to the predicted masses for
the ideal network, the authors could there- EA RTH SC I E N CE
fore determine the number of loops in the
system. They named this technique ‘network
disassembly spectrometry’ (NDS).
A potential limitation of NDS is that one
How glaciers grow
must be able to predict the degradation
products in order to apply the technique. A state-of-the-art numerical model shows that the advance of glaciers in a
Never­theless, a broad range of polymers and cooling climate depends strongly on the pre-existing landscape, and that glacial
chemistries will be amenable to this ana- erosion paves the way for greater glacial extent in the future. See Letter p.206
lytical approach. What’s more, the technique
enables new fundamental studies to be made
of the dynamics of polymer-network forma- SIMON H. BROCKLEHURST the first time, the stark contrast in glacier
tion. For example, by using NDS at different development between modern alpine moun-
T
stages of their network’s formation, Zhou he growth of glaciers reflects the balance tain ranges and those that came before them.
et al. were able to probe the structural evolu- between the accumulation of snow They compare the legacy of numerous glacia-
tion of the gel. And by varying the reaction and its loss through melting. Given the tions during the Pleistocene epoch (between
conditions of network assembly, they could close association between altitude and tem- about 2.5 million and 10,000 years ago) with
control the fraction of loops that formed in perature1, the elevation and morphology of the the landscapes that would have been present
the system, and thus gain valuable insight into valley floor on which a glacier forms are key at the onset of these glaciations.
the factors that contribute to the formation of determinants of a glacier’s size and long­evity. It has long been recognized that glaciers
these ‘defects’. Glacial erosion has carved the spectacular and their surroundings share an intimate,
One application of NDS might be as a tool alpine landscapes of many mountain ranges, coupled relationship4,5. Shaded aspects and
for correlating the microstructure of gels with and these are characterized by extensive glacial large areas at high elevation promote glacier
their mechanical properties. This could be use- valley floors at elevations close to the long-term growth. In turn, glacial erosion strongly modi-
ful in the development of artificial muscles that snowline2. These landscapes contrast strongly fies the underlying landscape, widening valley
perform useful work4. For example, some gels with their precursors, which are generally floors and making hill slopes steeper. However,
controllably expand and contract in response steeper, narrower valleys sculpted by rivers given the efficiency of glaciers at reworking
to external stimuli (such as changes in pH, (Fig. 1). On page 206 of this issue, Pedersen and removing the evidence left by previous
illumination or heat)5 or internal chemical and Egholm3 use a state-of-the-art numeri- glacial cycles, direct insight into the relation-
reactions4, and so can function as actuators cal model of glacier dynamics to quantify, for ship between glaciers and topography during
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2. RESEARCH NEWS & VIEWS
SEAN BAGSHAW/SPL
JEFFREY YAP, JEFF RYAN STUDIO/GETTY
a b
Figure 1 | The morphological contrast between fluvial and glacial erosion before the onset of glaciations about 2.5 million years ago. The first
landscapes. As documented by Pedersen and Egholm3, the width and glaciers to develop in such fluvial landscapes will show an almost linear
downstream gradient of a valley floor determine how glaciers would relationship between temperature change and subsequent ice volume.
develop should the climate cool sufficiently. a, A fluvial landscape b, A glacial landscape: Yosemite Valley, California. Ice volume will increase
characterized by a narrow, steep valley: Taroko Valley, Hualien, Taiwan. dramatically if the temperature cools sufficiently for the glacier to occupy
Many of the world’s mountain ranges would have been dominated by fluvial the broad, shallow valley floor.
the initial phases of late Cenozoic glaciation glacial erosion is a complex, multi-faceted the appropriate numerical formulation for
(between about 2.5 million and 1 million years problem. As such, the first models of glacial the role of subglacial water is in its infancy12.
ago) has remained frustratingly elusive. landscape evolution have emerged only within Further progress will require numerical models
Numerical modelling offers the opportu- the past 15 years8. Egholm and co-authors3,9 that are robustly supported by a combination
nity to explore glacier growth during initial have led the field and achieved compellingly of careful observations of modern glaciers13
glaciation. Pedersen and Egholm demon- realistic results by introducing ice-dynamics and thermochronological evidence for how
strate an almost linear relationship between formulations that are more appropriate to glacial landscapes have evolved over the
the degree of climate cooling and ice volume valley glaciers — which descend the rela- longer timescales7 that are explored numeri-
when glaciers develop in fluvial landscapes. tively steep downstream gradient of the valley cally here. It will also require driving models
However, for landscapes previously occu- floor and interact with the valley sides —than with more-realistic climate representations10,14
pied and sculpted by glaciers, the equiva- earlier simplifications borrowed from ice-sheet than those currently considered, and will
lent relationship is highly nonlinear. Once models. probably depend on continuing advances in
the climate cools sufficiently, glaciers that Many considerations are involved in any computer power. ■
descend onto the wide, shallow valley floor attempt to numerically model glaciers and
carved by preceding glacial occupations glacial erosion. The amount of snow that falls Simon H. Brocklehurst is in the School
expand markedly. is strongly influenced by local climate, and is of Earth, Atmospheric and Environmental
Pedersen and Egholm also explore the full sensitive to changes in atmospheric moisture Sciences, The University of Manchester,
evolution of modern glacial landscapes by content, temperature and prevailing wind Manchester M13 9PL, UK.
driving a simplified version of their numerical direction. Falling snow can be redistributed by e-mail: shb@manchester.ac.uk
model — that is, without fluvial or hill-slope wind10 and avalanching before it reaches the
1. Stone, P. H. & Carlson, J. H. J. Atmos. Sci. 36,
erosion, or active tectonics — with tempera- glacier surface. Glacial-ice melt is influenced 415–423 (1979).
ture fluctuations representing the past 2 mil- by temperature change, shading and rock 2. Brozović, N., Burbank, D. W. & Meigs, A. J. Science
lion years. The mid-Pleistocene transition fall from the valley sides. Glacial ice deforms 276, 571–574 (1997).
3. Pedersen, V. K. & Egholm, D. L. Nature 493,
(MPT) about 950,000 years ago marked a under its own weight, and can also slide on its 206–210 (2013).
shift from 40,000-year glacial cycles accom- bed if liquid water is present. However, at this 4. Johnson, W. D. J. Geol. 12, 569–578 (1904).
panied by symmetrical periods of cooling point, this generic model still only describes 5. Gilbert, G. K. J. Geol. 12, 579–588 (1904).
6. Haeuselmann, P., Granger, D. E., Jeannin, P.-Y. &
and warm­­ to the protracted cooling and
ing ice accumulating, deforming and melting. Lauritzen, S.-E. Geology 35, 143–146 (2007).
rapid warming of the more recent 100,000- How would this moving ice (and water) erode 7. Valla, P. G., Shuster, D. L. & van der Beek, P. A.
year glacial cycles. The authors find much the landscape? Nature Geosci. 4, 688–692 (2011).
more extensive and erosive glaciers after As was recently noted11, models of glacial 8. Braun, J., Zwartz, D. & Tomkin, J. H. Ann. Glaciol. 28,
282–290 (1999).
the MPT than during the previous 1 million landscape evolution, including Pedersen and 9. Egholm, D. L., Knudsen, M. F., Clark, C. D. &
years. This result is consistent with geological Egholm’s, still rely on simple, empirical rela- Lesemann, J. E. J. Geophys. Res. 116, F02012
evidence for accelerated glacial erosion after tionships between glacier sliding velocity and (2011).
10. Anders, A. M., Roe, G. H., Montgomery, D. R. &
the MPT6,7. However, as Pedersen and Egholm glacial erosion rate, supported by modest Hallet, B. Geology 36, 479–482 (2008).
show, this accelerated erosion is not simply a field-data sets. There is little clear connection 11. Iverson, N. R. Geology 40, 679–682 (2012).
consequence of the changing climate; faster between these numerical relationships and 12. Herman, F., Beaud, F., Champagnac, J.-D., Lemieux,
J.-M. & Sternai, P. Earth Planet. Sci. Lett. 310,
glacial erosion post-MPT was preconditioned the quarrying of large bedrock blocks from 498–508 (2011).
by the landscape modifications made by the the glacier bed, which in most circumstances 13. Riihimaki, C. A., MacGregor, K. R., Anderson, R. S.,
preceding, smaller-scale glaciations. represents the primary process of glacial Anderson, S. P. & Loso, M. G. J. Geophys. Res. 110,
Pedersen and Egholm3 have taken on a erosion. The liquid water in the subglacial F03003 (2005).
14. Rowan, A. V., Plummer, M. A., Brocklehurst, S. H.,
considerable challenge. Numerical model- hydrological network is also known to have Jones, M. A. & Schultz, D. M. Geology http://dx.doi.
ling of landscape evolution resulting from a key role in glacial erosion, but determining org/10.1130/G33829.1 (2012).
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