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Experimental evidence that microbial activity lowers the albedo of glaciers

M. Musilova1,2,

1Bristol Glaciology Centre, School of Geographical Sciences, University of Bristol, Bristol BS8 1SS, UK
2Current address: Výskumný ústav potravinársky – NPPC and Slovak Organisation for Space Activities (SOSA), Bratislava, Slovakia

M. Tranter1,

1Bristol Glaciology Centre, School of Geographical Sciences, University of Bristol, Bristol BS8 1SS, UK

J.L. Bamber1,

1Bristol Glaciology Centre, School of Geographical Sciences, University of Bristol, Bristol BS8 1SS, UK

N. Takeuchi3,

3Department of Earth Sciences, Graduate School of Science, Chiba University, 1-33, Yayoicho, Inage-ku, Chiba-city, Chiba, 263-8522, Japan

A.M. Anesio1

1Bristol Glaciology Centre, School of Geographical Sciences, University of Bristol, Bristol BS8 1SS, UK

Affiliations  |  Corresponding Author  |  Cite as

Musilova, M., Tranter, M., Bamber, J.L., Takeuchi, N., Anesio, A.M. (2016) Experimental evidence that microbial activity lowers the albedo of glaciers. Geochem. Persp. Let. 2, 106-116.

Geochemical Perspectives Letters v2, n2  |  doi: 10.7185/geochemlet.1611
Received 8 October 2015  |  Accepted 27 January 2016  |  Published 11 March 2016




Figure 1 OC accumulated over (a) one simulated summer season and (b) over three simulated summer seasons. Surface reflection after (c) one simulated summer season and (d) three simulated summer seasons. ‘Light’ samples accumulated significantly more OC compared to ‘dark’ samples (two-way ANOVA p < 0.05 in (a) and p < 0.001 in (b). This was accompanied by a decrease in cryoconite sediment reflectivity by ~15.5 percentage points, from a starting 31.1 %, for the ‘light’ with NPC treatment samples in (c) and a further 1.8 percentage points in (d). Two-way ANOVA analyses showed a significant difference in spectral reflection between ‘light’ and ‘dark’ samples (p < 0.001), nutrient conditions (p < 0.001) and the interaction of nutrient and light settings (p < 0.01). There was a significant difference (p < 0.001) between samples NPC and blanks, NCP and NP (p < 0.05) and NP and blanks (p < 0.05), using Turkey Post-hoc analyses in (c-d). Standard errors were calculated as 1σ (n = 5).
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Table 1 Concentrations of PON, OP, IP and chla for each light and nutrient treatment, over one and three simulated summer seasons. The concentrations are the differences between the final and starting concentrations in each treatment. Significant differences (two-way ANOVA) are indicated between (a) ‘light’ and ‘dark’ samples, (b) nutrient treatments and (c) the interaction of nutrient and light settings.
Sample conditionsLightDarkTwo-way ANOVA analysis:
Sterile waterN and P additionsN, P and C additionsSterile waterN and P additionsN, P and C additions
One simulated summer seasonPON concentration (µg PON/g cryoconite sample)11.732.6100.4-3.1-6.6-2.4a (p < 0.01)
±3.8±21.4±26.7±6.0±4.4±10.2
OP concentration (µg OC/g cryoconite sample)-2.113.419.5-21.9-22-10a (p < 0.001)
±9.6±6.0±6.4±1.8±1.7±7.1b (p < 0.05)
IP concentration (µg OC/g cryoconite sample)-3.9-22-27.216.923.612.5a (p < 0.001)
±5.5±9.8±5.4±8.5±10.4±2.4
Chla concentration (in µg of chla/g of sample)1.63.13.811.11.1a (p < 0.001)
±0.2±0.1±0.2±0.1±0.1±0.0b (p < 0.01)






c (p < 0.01)
Three simulated summer seasonsPON concentration (µg PON/g cryoconite sample)149.6253.4680.551.267.361.4a (p < 0.001)
±31.7±42.9±51.1±19.2±14.2±18.1b (p < 0.001)






c (p < 0.001)
OP concentration (µg OC/g cryoconite sample)27.735.685.415.213.616.3a (p < 0.001)
±8.9±9.1±13.6±0.9±1.4±4.5b (p < 0.001)






c (p < 0.01)
IP concentration (µg OC/g cryoconite sample)-35.6-46.7-97.7-21.8-24.1-19.6a (p < 0.001)
±9.4±13.5±15.1±6.3±5.2±7.3b (p < 0.01)






c (p < 0.01)
Chla concentration (in µg of chla/g of sample)1.5 ± 0.22.0 ± 0.04.0 ± 0.51.0 ± 0.11.1 ± 0.21.1 ± 0.0a (p < 0.001)
b (p < 0.001)
c (p < 0.001)
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Figure 2 Microbial granule development in ‘light’ samples with nutrient additions. Images (a-c), (e) and (g) were taken using optical microscopy. Autofluorescence microscopy was performed to visualise photosynthetic autotrophs in images (d), (f) and (h). The initial mixture of inorganic dust with 10 % natural cryoconite (a and c) developed into samples rich in granules and filamentous cyanobacteria (b, e-h). Examples of cyanobacterial filaments and colonies (resembling black spheres) are indicated by arrows in images (b), (e-h).
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Figure 3 (a) Present biologically-induced GrIS potential increase in melt rate, in mm yr-1. (b) and (c) Future biologically-induced GrIS potential increase in melt rate, in mm yr-1. Melt days were derived for the period 2091-2100 for two different greenhouse gas trajectories, RCP4.5 (b) and RCP8.5 (c).
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