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Lacustrine systems of Clearwater Mesa (James Ross Island, north-eastern Antarctic Peninsula): geomorphological setting and limnological characterization

Published online by Cambridge University Press:  09 May 2019

Matěj Roman*
Affiliation:
Department of Geography, Faculty of Science, Masaryk University, Kotlářská 2, 611 37, Brno, Czech Republic Department of Physical Geography and Geoecology, Faculty of Science, Charles University, Albertov 6, 128 43, Praha 2, Czech Republic
Linda Nedbalová
Affiliation:
Department of Ecology, Faculty of Science, Charles University, Viničná 7, 128 44, Praha 2, Czech Republic
Tyler J. Kohler
Affiliation:
Department of Ecology, Faculty of Science, Charles University, Viničná 7, 128 44, Praha 2, Czech Republic
Juan M. Lirio
Affiliation:
Instituto Antártico Argentino, 25 de Mayo 1143, San Martín, Prov. Buenos Aires, Argentina
Silvia H. Coria
Affiliation:
Instituto Antártico Argentino, 25 de Mayo 1143, San Martín, Prov. Buenos Aires, Argentina
Jiří Kopáček
Affiliation:
Biology Centre of the Czech Academy of Sciences, v.v.i., Institute of Hydrobiology, Na Sádkách 7, 370 05, České Budějovice, Czech Republic
Paula A. Vignoni
Affiliation:
Centro de Investigaciones en Ciencias de la Tierra (CICTERRA), CONICET/Universidad Nacional de Córdoba, Av. Vélez Sarsfield 1611, X5016CGA Córdoba, Argentina
Kateřina Kopalová
Affiliation:
Department of Ecology, Faculty of Science, Charles University, Viničná 7, 128 44, Praha 2, Czech Republic
Karina L. Lecomte
Affiliation:
Centro de Investigaciones en Ciencias de la Tierra (CICTERRA), CONICET/Universidad Nacional de Córdoba, Av. Vélez Sarsfield 1611, X5016CGA Córdoba, Argentina Facultad de Ciencias Exactas Físicas y Naturales, Universidad Nacional de Córdoba, Av. Vélez Sarsfield 1611, X5016CGA Córdoba, Argentina
Josef Elster
Affiliation:
Centre for Polar Ecology, Faculty of Science, University of South Bohemia, Na Zlaté stoce 3, 370 05, České Budějovice, Czech Republic
Daniel Nývlt
Affiliation:
Department of Geography, Faculty of Science, Masaryk University, Kotlářská 2, 611 37, Brno, Czech Republic
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Abstract

Lentic freshwater habitats are important centres of biodiversity within the infrequent ice-free oases across Antarctica. Given imminent climate changes, it is crucial to catalogue these habitats in order to provide baseline data for future monitoring and biological surveys. The lacustrine systems of Clearwater Mesa, a previously unexplored part of James Ross Island, north-eastern Antarctic Peninsula, are described here. We conducted basic geomorphological and limnological surveys over three Antarctic summers (2009–16) to characterize landscape evolution, infer the origin of lake basins and assess the variability in their water chemistry. Stable shallow lakes, formed in depressions between lava tumuli following the last deglaciation, were found to dominate the volcanic mesa, although several peripheral lakes in ice-proximal settings appear to have formed recently as a result of post-Neoglacial ice recession. We found large heterogeneity in conductivity (~10–7000 μS cm−1), despite the lithologically uniform substrate. This variability was shown to be related to lake type, basin type (open vs closed), meltwater source and proximity to the coast. Inter-annual differences were attributed to changes in sea spray influx and snow accumulation driven by variable weather conditions. Overall, the ion composition of lakes suggested that sea spray was the dominant source of ions, followed by the weathering of bedrock.

Information

Type
Biological Sciences
Copyright
Copyright © Antarctic Science Ltd 2019 
Figure 0

Fig. 1. Clearwater Mesa is located on a. the north-eastern side of the Antarctic Peninsula and b. in the north-central part of James Ross Island. c. Aerial orthophotograph that was used for mapping. d. The main geomorphological and hydrographical features of CWM overlain on the digital elevation model (created by the Polar Geospatial Center from DigitalGlobe, Inc. imagery). The wind rose diagram expresses the relative frequency of wind direction based on observations in the field camp during the 2016 summer campaign.

Figure 1

Fig. 2. Geomorphological features of the CWM area. a. General aerial view of the mesa looking from the west, with basaltic horizontal topsets and inclined foresets of hyaloclastite breccia distinguishable on the vertical Stark Point profile. Note the distinct changes of lake water colour across small distances. b. Wind-polished and striated glacial erratic boulder. c. Well-developed sorted polygon in saturated depressions. d. Strandlines of glacier-dammed palaeolake Florencia from the past high stand.

Figure 2

Table I. Location and morphometric parameters of CWM lakes. Water samples for chemical analyses were taken from lakes indicated by bold font. Conductivity and pH denote ranges of multiple measurements taken in situ during the 2015 and 2016 summer seasons.

Figure 3

Fig. 3. Lake types of CWM. a. Type 1: stable, shallow lake Ludmila on the volcanic surface of the mesa. b. Type 2: moraine-dammed lake Malvina (right) and type 3: ice-contact (terminoglacial) lake Rosa (left) in the young glacial deposits. c. Type 3: ice-contact lake Florencia with floating icebergs and remnants of ice cover (some of which were heavily loaded with debris from the nearby scree slope). d. Kettle lake Tambucho; a large ice lens of the ice-cored moraine was found adjacent to the north side of the lake.

Figure 4

Fig. 4. The inferred hydrological system of CWM comprises several sub-catchments formed around the main lakes Katerina, Norma and Trinidad–Tatana. Lake conductivity (averaged for all measurements taken over the 2015 and 2016 summer seasons, if available) is represented on a colour scale. Conductivity changes between 2015 and 2016 (where difference was > ±10% and at least two readings per season were available) are denoted below the lake name. Note that not all snow banks (feeding lakes with mostly low conductivity) observed during the field campaigns are pictured in this map, which is based on an aerial image from 2014.

Figure 5

Fig. 5. Box and whisker plots showing the water conductivity of different lakes classified according to: a. basin type (open vs closed), b. lake type (generalized to old and young lakes) and c. source of the meltwater for the lake. Medians (bars), 25% and 75% quartiles (boxes) and 10% and 90% percentiles (whiskers) are shown; note that different y-axis scales are given for greater clarity. Differences among lake categories were tested using Mann–Whitney or Kruskal–Wallis tests with a Dunn's multiple comparison test; lower-case letters above the plots (a, b) indicate significant differences.

Figure 6

Fig. 6. Mean lake water conductivity (on a log10 scale) plotted against the distance to the coastline. Lakes are classified according to the hydrological connectivity of their catchment (open basins – filled symbols; closed basins – open symbols) and water source (no large snow bank nor glacier present in catchment – circles; snow bank-fed lakes – squares; glacier-fed lakes – triangles). The exponential regression computed for all lakes explains 33% of the variability.

Figure 7

Fig. 7. Comparison of lake water conductivity between the summers of 2015 and 2016. Line 1:1 denotes no change in conductivity between the years. If the point lies above the line, conductivity increased. Lakes are classified as having open (black) or closed basins (white), with snow banks present in a substantial part of the lake catchment (squares) or mostly absent (circles). Of the glacier-fed lakes, only Florencia was measured in both years, showing a dramatic decline between the two years (from 130 to 27 μS cm−1).

Figure 8

Table II. Minimum, median and maximum values of basic chemical characteristics of the 29 lakes analysed during 2009–16 (detailed values are presented in Tables III & S1).

Figure 9

Table III. Detailed chemical characteristics of five lakes sampled in 2009.

Figure 10

Fig. 8. The PCA of the chemical parameters of a. CWM and b. CWM and Ulu Peninsula lake datasets combined. The two lakes with the highest conductivities (Adriana and Erminda) were excluded from the second analysis due to their disproportionate effects on the PCA projection. Additional CWM lake characteristics (lake area, distance from the sea, basin type and main meltwater source) were added as supplementary variables in a. and are visualised as dashed grey arrow lines. The data of the Ulu Peninsula lakes are from Nedbalová et al. (2013). For sample acronyms, see Tables III and S1.

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