1
2
into
3
4 by F. Fripiat
1 -2 *
, D.M. Sigman
2
, S.E Fawcett
2
, P.A. Rafter
2
, M.A. Weigand
2
, & J.-
L. Tison
1
5
6
1
Department of Earth and Environmental Sciences, Université Libre de Bruxelles, Brussels,
Belgium.
7
2
Department of Geosciences, Princeton University, Princeton, New Jersey 08544, USA.
8
9
*Now at: Earth and System Sciences & Analytical and Environmental Chemistry, Vrije
Universiteit Brussel, Brussels, Belgium.
10
15
16
17
18
11
12
13
14
Each ice block was sequentially melted at ambient temperature in the dark [ Fripiat et al .,
2007], which enabled us to separate the different phases (brine vs. pure ice) by their melting point. This method relies on the fact that the salty brine melts faster than the pure ice crystal matrix (Fig. S2). Therefore, the interconnected brines (i.e., brine channels and feeder tubes) are drained first (Fig. S1). To collect the closed structures, the surrounding pure ice must melt. These brine fractions (i.e., brine pockets) are collected at the end (Figs. S1 and S2). The melted samples were collected at 10 ± 5, 23 ± 7, 46 ± 9, and 100 ± 0% of the cumulated volume (100% = everything was melted) and processed as described in section 3.1.
23
24
25
26
27
19
20
21
22
Here, we consider the intra-ice variability indicated by the sequential melting approach. For
SIMBA, no apparent trends with salinity were observed for the δ
15
N of the different nitrogen species (Fig. S3). The variability seemed to increase slightly with the closure of the brine network (low saline fraction). The greater homogeneity for the open brine structure is in agreement with greater permeability, enabling the mixing between heterogeneous microbial environments at smaller scales. SIMBA was characterized by the alternance of warm and cold periods, associated with changes in the wind direction and the continental/oceanic origin of air masses [ Vancoppenolle et al ., 2011]. Such periodic events should have opened and closed the brine network, implying no difference in the average trends between open and closed brine
1

28
29
30 structures. In addition during the cold periods, the highly concentrated brines at the surface melts the underl y ing warmer ice by forming brine tubes penetrating downward into the ice cover and homogenizing the different brine structures [ Brabant et al ., in prep].
40
41
42
43
36
37
38
39
31
32
33
34
35
ISPOL evolved more classically, with the brine pockets remaining more isolated and therefore, potentially, keeping their signatures. The less saline fractions were lower and higher in δ
15
N for particulate nitrogen and nitrate, respectively. For nitrate, such higher δ 15 N for the open brine structures was only observed in the bottom and surface layers, the latter being only the 9 th
December profile associated with additional seawater input (see section S2). Such close connection to a nitrate source can boost primary production and lead to a system more driven by nitrate assimilation. No trend was observed for DON+ NH
4
+
, being the largest pool and therefore the less reactive one. The higher PN for the less saline fractions could be related to a situation closer to SIMBA with low DON + NH
4
+
consumption/production ratio (see section 5.2), inherited from previous nitrate assimilation. The development of an efficient microbial loop in the connected brine structure should favor a regenerated production, attenuating (i) the initial imbalance in the DON + NH
4
+
production vs. consumption ratio and (ii) the isotopic difference between DON + NH
4
+
and PN δ
15
N (see section 5.2).
44
45
46
47
48
49
50
51
52
15
Here, we describe a new preparative concentration method that can be used prior to N isotope analysis of low nitrate concentration samples (tested down to 0.25 µmol l
-1
). The method is based on the fact that nitrate is extremely soluble in aqueous solutions and can thus be separated from other less soluble salts in seawater. Samples are evaporated to dryness via a parallel vortex evaporation technique, after which the nitrate is recovered by adding a smaller volume (1 ml) of deionized water. The δ 15
N of this nitrate is then analyzed using the denitrifier method (see section 3.2).
53
54
55
56
Acid-washed boro-silicate glass conical centrifugation vials (Corning, Product #99502-50) containing 10-20 ml of sample are connected to a vacuum manifold cover and inserted in a heated water bath (70°C) (BÜCHI, Multivapor P-12 Evaporator). Samples are evaporated and condensed by vacuum distillation. To increase the rate of evaporation, the samples are set in
2

57
58 rotation (290 rpm) and under increasing vacuum (with the pressure gradually decreasing from
500 to 20 mbar). 12 samples can be processed in a run, and the whole process takes roughly 1 hr.
59
60
61
62
63
64
65
66
Two internationally recognized nitrate reference materials, IAEA-N3 and USGS-34, were processed along with the samples in order to check the accuracy and the precision of the method.
We prepared and analyzed solutions (n = 86) of these standards with a nitrate concentration ranging from 0.25 to 1.2 µmol l -1 and a salinity ranging from 0 to 15 PSU (prepared by diluting with low-nitrate Gulf Stream seawater). The recovery of nitrate was 95 ± 5%, indicating no significant loss during the process (Fig. S4). The δ 15 N of IAEA-N3 (4.6 ± 0.1‰, n = 46) and
USGS-34 (-1.8 ± 0.1‰, n = 35) were indistinguishable from expected values [Fig. S4; Bohlke et al ., 2003].
67
72
73
74
75
68
69
70
71
One profile each for SIMBA and ISPOL, corresponding to the sampling dates of 16 th
of
October and 9 th
of December, have been removed from the weighted average calculation per depth, for both concentration and nitrogen isotopic composition (Fig. 2). At SIMBA, the 16 th
October profile exhibited: (i) much higher salinity normalized DON + NH
4
+
and PN concentration all across the ice floe, respectively, 65 to 132 and 73 to 113 µmol l
-1
(Fig. S5a); and (ii) heavier DON+ NH
4
+
δ
15 N (3.1 to 3.9‰; Fig. S5b). For ISPOL, the 9 th
December profile presented: (i) an increase of salinity normalized nitrate and DON + NH
4
+
concentration up to the top (Fig. S5c); and (ii) heavier NO
3
-
δ
15 N (6.0 to 11.4‰; Fig. S5d).
83
84
85
79
80
81
82
76
77
78
Snow ice for ISPOL first appeared at this station [presenting lower ice δ 18 O; Tison et al ., 2008].
Snow ice forms by the refreezing of slush at the snow-ice interface. This slush originates from the infiltration of seawater at the base of the snow pack when snow is deep enough to depress the ice surface below sea level [e.g. Maksym and Markus , 2008]. Tison et al . [2008] suggested, from brine/ice δ 18
O, that the infiltration of slush, by snow-ice melting, into the internal part of the floe occurred at the 9 th
December ISPOL profile. This infiltration would supply seawater nitrate, explaining the higher nitrate concentration (Fig. S5c), and would boost nitrate assimilation, leading to the observed increase in nitrate δ 15
N (Fig. S5d). In agreement with the flooding by seawater, this profile presented higher salinity normalized TN concentration and TN δ
15
N closer to the seawater input (Fig. S6).
3

91
92
93
94
95
96
97
98
99
86
87
88
89
90
The 16 th
October profile at SIMBA presented higher salinity normalized DON + NH
4
+ and PN concentration, and DON + NH
4
+
δ
15
N (Figs. S5a and S5b). As for ISPOL, lower Δ
15
N
PN-DON
(=
δ 15
N
PN
- δ
15
N
DON
) was observed. These observations suggest a larger organic N production and a better coupling between DON + NH
4
+
production and consumption processes (see section 5.2).
Larger salinity normalized TN concentration implies an additional input of nitrogen through brine convection (

5 times seawater; Fig. S6). The partitioning of nitrogen amongst the fixed N species suggests that this input had been mainly assimilated into organic N at the time of the sampling. However, it is difficult to know if it is the result of spatial variability or temporal evolution. Several meteorological cycles of varying duration and intensity were observed during
SIMBA, associated with changes in the wind direction and the continental/oceanic origin of air masses [ Vancoppenolle et al ., 2011]. The singular profile was sampled at the end of the longest cooling cycle, presenting therefore the coldest ice temperature, the lowest ice porosity, and the highest brine salinity [ Lewis et al ., 2011]. Such alternance of warm and cold conditions should have promoted brine convection and the concomitant additional supply of N into the ice.
100
101
102
103
104
109
110
111
112
105
106
107
108
113
114
We use a time-dependent geochemical one box model of sea ice brine to constrain the relative rate of nitrification from the observed salinity normalized nitrate concentration and δ
15
N [see also Fripiat et al ., accepted, for δ 30 Si]. The model simulated the change in both nitrate concentration and δ 15
N in the brine in which initial conditions are inherited from the previous convective events, setting the brine to the underlying seawater composition [31 µmol l
-1
and 5‰;
DiFiore et al ., 2009]. We assume no external nitrate supply between two consecutive convective events. While this is a very good approximation of reality in the interior of the ice and in its surface layer [ Griewank and Notz , 2013], there will be some exchange of brine with the underlying ocean close to the ice-ocean interface. This exchange is, however, limited, since otherwise measured salinity normalized NO
3
-
in the bottom community should be very similar to that of the underlying seawater. N isotopes are consumed during nitrate assimilation with an isotope effect of 5‰ [
Difiore et al ., 2010], and nitrification produces new nitrate with a δ
15
N between -3.5
and -13‰ (see section 5.3 and Fig. 8). The mass and isotopic balance is given by :
4

115
116 dNO

3 dt

Nitr

NaU (S1) d
15
NO

3 dt

Nitr
 15
R
Nitr

NaU

15
NO

3
NO

3



 1


NaU
1000 


(S2)
117
118
119
120
121
122
123
124
125
126 where Nitr is nitrification (µmol l
-1 ), NaU nitrate assimilation (µmol l -1
),
15
R
NiO
the isotopic ratio of the nitrified nitrate, and ε
NaU
the isotopic effect of nitrate assimilation. The model is run for N time steps of length dt, consuming at each time step an amount of

NaU/N (=NaU) and nitrifying

Nitr/N (=Nitr), where

NaU and

Nitr are the integrated nitrate assimilation and nitrification, respectively. We solve model differential equations for varying NiO, NaU, and
15
R
NiO
(δ
15
N from -3.5
to 13‰; Fig. 8), aiming to find the best agreement between the observations {NO
3
-
(i), δ
15
N(i)} and the model counterparts {NO
3
(m), δ 15
N(m)}. To measure this agreement, we use the minimum cost function, searching for the lowest standardized residual
[SR; Elskens et a l., 2007]:
SR


NO

3
( i )


NO  
NO

3
2

3
( m )
2




15
N ( i )
  15
N ( m )



15 N

2
2

(S3)
131
132
133
134
127
128
129
130
135
136 where σ
NO3
and σ
δ15N
express the standard deviation. Standardized residuals account for the different scaling of the two variables, in this case, nitrate concentration and nitrate δ
15
N.
Standardized residuals for each combination of NaU and NiO, and for a given δ 15
N nitr
have been estimated (see Fig. S7 for the example of the bottom community at SIMBA). Satisfying solutions correspond to combinations of NaU and Nitr that result in a SR lower than 5 (Fig. S7d).
Satisfying solutions correspond to combinations of NaU and Nitr that fulfill this criterion are presented in Figs. S7a-c. We find simulated nitrate concentration and δ
15
N within the analytical error range of the observations (Figs. S7a and b). The sensitivity of the resulting nitrification on the Nitr:NaU ratio is shown in Fig. S7c, for the three different tested δ
15
N nitr
(-13‰, 8
‰, and -
3.5
‰).
5

137
138
139
140
Brabant, F., G. Carnat, I. Dumont, S. Becquevort, M. Vancoppenolle, S.F. Ackley, and J.-L.
Tison (2013), Thermally-forced DMS, DMSP, DMSO and biogeochemical cycling in Antarctic spring sea ice: a contrasting study. In preparation.
141
142
143
Böhlke, J.K., S.J. Mroczkowkski, and T.B. Coplen (2003), Oxygen isotope in nitrate: new reference materials for
18
O:
17
O:
16
O measurements and observations on nitrate-water equilibration, Rapid Commun. Mass Sp. 17, 1835-1846.
144
145
146
Elskens, M., A. de Brauwere, C. Beucher, R. Corvaisier, N. Savoye, P. Tréguer, and W.
Baeyens (2007), Statistical process control in assessing production and dissolution rates of biogenic silica in marine environment, Mar. Chem. 106, 272-286.
147
148
149
Fripiat, F., D. Cardinal, J.-L. Tison, A. Worby, and L. André (2007), Diatom-induced silicon isotopic fractionation in Antarctic sea ice, J. Geophys. Res. 112, G02001, doi:10.1029/2006JG000244.
150
151
152
Fripiat, F., J.-L. Tison, L. André, D. Notz, and B. Delille (2013), Biogenic silica recycling in sea ice inferred from Si-isotopes: Constraints from Arctic winter first-year sea ice, Accepted in
Biogeochemistry.
153
154
Griewank, P.J., and D. Notz (2013), Insights into brine dynamics and sea ice desalination from a 1-D model study of gravity drainage, J. Geophys. Res. Oceans, 118, doi:10.1002/jgrc.20247.
155
156
157
Lewis, M.J., J.-L. Tison, B. Weissling, B. Delille, S.F. Ackley, F. Brabant, H. Xie (2011), Sea ice and snow cover characteristics during the winter-spring transition in the Bellingshausen Sea:
An overview of SIMBA 2007, Deep-Sea Res. II 58, 1019-1038.
158
159
160
Maksym, T., and T. Markus (2008), Antarctic sea ice thickness and snow to ice conversion from atmospheric reanalysis and passive microwave snow depth, J. Geophys. Res. 113, C02S12, doi:10.1029/2006JC004085.
161
162
163
Tison, J.-L., A. Worby, B. Delille, F. Brabant, S. Papadimitriou, D. Thomas, J. de Jong, D.
Lannuzel, and C. Haas (2008), Temporal evolution of decaying summer first-year sea ice in the
Western Weddell Sea, Antarctica, Deep-Sea Res. II 55, 975-987.
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164
165
166
167
Vancoppenolle, M., R. Timmermann, S.F. Ackley, T. Fichefet, H. Goosse, P. Heil, K.C.
Leonard, J. Lieser, M. Nicolaus, T. Papkyriakou, and J.-L. Tison (2011), Assessment of radiation forcing data sets for large-scale sea ice models in the Southern Ocean, Deep-Sea Res. II 58,
1237-1249.
7

168
169
170
Supplementary figure 1: sketch showing the potential stages of the drainage process within a sea-ice sample as it is progressively warmed up [sequential melting; from Fripiat et al ., 2007].
171
8

40
30
20
10
ISPOL
SIMBA
172
0
0 10 20 30 40 50 60 70 80 90 100
Cumulated volume (%)
173
174
175
Supplementary figure 2: Salinity evolution during a sequential melting experiment as a function of the cumulated melted volume (100% = the whole ice block has been melted); saltier fractions are collected first and fresher fractions at the end.
9

15
0 a)
10
10
Salinity (g kg
-1
)
20 30 40 50 0 b)
5
Salinity (g kg
-1
)
10 15 20 25
15
10
5 5
0
-5
0
NO
3
-
PN
DON+NH
4
+
-5
176
177
178
179
180
181
Supplementary figure 3: δ 15 N of NO
3
(blue circles), DON+ NH
4
+ (purple empty circles), and
PN (green triangles) as a function of salinity, respectively for SIMBA (panel [a]) and ISPOL
(panel [b]). Each dot corresponds to an individual analysis (sequential fraction) and the larger connected dots show the weighted averages by sequential fractions. Seawater nitrate
 15
N is indicated by the blue dashed lines.
10

4
-1
6
5
IAEA-N3 = 4.7
 0.2‰
-2
USGS34 = -1.8
 0.2‰
-3
80 90
Evaporation Recovery (%)
100 110
182
183
184
185
186
Supplementary figure 4: Nitrate recovery (%) and δ
15
N of evaporated standards (circles, n =
86), IAEA-N3 and USGS34, with a starting nitrate concentration between 0.25 and 1.2 µmol l
-1
.
The full lines represent the published values of Bohlke et al . [2003] and the associated uncertainties (2sd = 0.2‰; dashed lines).
11

0
1
SIMBA
20
40
60
10 100 -4 -2 0 2 4 6 8 10 12 14 16
0
SIMBA Seawater NO
3
-
Seawater DON
NO
3
DON+NH
4
+
PN
20
40
60
80 a)
100
0
ISPOL
20 b)
ISPOL
other profiles
16 th
October
80
100
0
20
40 40
187
188
189
190
191
192
193
194
195
60
80
100
1 c)
10 salinity normalized Conc ( umol l-1)
-1
100 other profiles
9 th
December
60
80 d)
-4 -2 0 2 4 6 8 10 12 14 16
100
15 N (‰)
Supplementary figure 5: Panels (a) and (c): Salinity normalized concentration for NO
3
-
(blue),
DON+ NH
4
+ (purple), and PN (green) in function of depth (depth %), respectively for SIMBA
(a) and ISPOL (c). Panels (b) and (d): δ
15
N values for NO
3
-
(blue), DON + NH
4
+
(purple), and
PN (green) in function of depth (depth % = mid-depth of the ice block/ice thickness * 100), respectively for SIMBA (b) and ISPOL (d). Each empty circle corresponds to a weighted bulk measurements (= ice block) for the singular profiles of SIMBA (a) and (b), and ISPOL (c) and
(d). The filled circles represent the depth weighted averages for the remaining profiles (Fig. 2).
The seawater nitrate is given by the blue dashed lines and the seawater DON by the purple dashed-dotted lines.
12

0
20
40
SIMBA
ISPOL
0
Other profiles
Singular profiles
20
40
60 60
80
100
0 a)
40 80 120 160 200 240 280 salinity normalized T umol l-1
-1
)
-4 b)
-2 0 2 4 6
15 N (‰)
80
8 10 12
100
196
197
198
199
200
201
202
203
Supplementary figure 6: Salinity normalized concentration of total fixed nitrogen (panel [a]) and its δ
15
N (panel [b]) in function of depth (depth % = mid-depth of the ice block/ice thickness
* 100). SIMBA is in blue and ISPOL in red. Each empty circle corresponds to a weighted bulk measurements (= ice block) for the removed profiles from the depth weighted calculation: the
16th October profile (SIMBA, blue) and the 9th profile (ISPOL, red). The larger connected circles the depth weighted averages for the remaining profiles (Fig. 3). The seawater total fixed nitrogen is given by the black dashed line.
13

35
30
25
20
15
10
35
30
25
20
15 a)
10 c) c)
Reaction progress 
-3.5‰
-8‰
-13‰
Reaction progress 
5.25
5.25
5.2 0
5.15
5.1 0
5.05
5.2 0
5.15
5.1 0
5.05
5 .00
b)
4.95
5 .00
4.95
d) nitrification δ 15 N = 8‰
204
205
206
207
208
209
210
211
212
213
214
Supplementary figure 7: Example of optimization for the bottom community at SIMBA. Panel
(a) normalized nitrate concentration for the model best fit (full line), the model envelope corresponding to the simulations with a standard residual lower than 5 (thin lines), and the observations (dot with error bars). Panel (b) δ
15
N for the model best fit (full line), the model envelope corresponding to the simulations with a standard residual lower than 5 (dashed lines), and the observations (dot with error bars). Panel (c) nitrification:assimilation ratio corresponding to the simulations with a standard residual lower than 5 (dashed lines) and for the model best fit
(cross). The different colors represent different optimization with three different δ 15 N for nitrification (-13, -8, and 3.5
‰). Panel (d) Standard residuals (color bar) for each pair of nitrate assimilation and nitrification, with δ
15
N for nitrification at -8‰.
14