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1 May 2015 Does the Coralline Alga Leptophytum foecundum (Kjellman) Capture Paleoenvironmental Variability in the Arctic Ocean?
Laurie Bougeois, Branwen Williams, Jochen Halfar, Brenda Konar, Walter Adey, Andreas Kronz, Ulrich G. Wortmann
Author Affiliations +
Abstract

Records of high resolution climate variability in the past are essential to understanding the climate change observed today. This is particularly true for Arctic regions, which are rapidly warming. Prior to instrumental data, proxy records can be extracted from high-latitude climate archives to provide critical records of past Arctic climate variability. Here, we investigate the feasibility of extracting records of climate and environmental variability from the skeleton of the crustose coralline alga Leptophytum foecundum from offshore the Sagavanirktok River in the Beaufort Sea. Although this alga forms an annually banded skeleton, age chronologies were established with difficulty due to the large uncalcified reproductive structures relative to low annual growth rates. Average measurements of skeletal Mg content, δ18Oalga values, and δ13Calga values were consistent among the analyzed specimens, but time series of these parameters only significantly correlated between two of the collected specimens for δ18Oalga. No clear trends in environmental variability explained the patterns in the skeletal geochemistry over time. This suggests that ambient seawater combined with freshwater from the Sagavanirktok River drives the geochemistry of L. foecundum at this site. Thus, coralline algal specimens located near variable sources of low-salinity waters are not ideal organisms to use as proxy archives.

Introduction

The impact of the industrial revolution on climate is a key issue for the global community. To understand recent changes and model future projections of temperature, we need to quantify climate variability during the last several centuries prior to and since the industrial revolution. Because of its importance in modulating climate through changes in albedo, carbon-sink feedbacks, and the Atlantic meridional overturning circulation (AMOC), Arctic paleoenvironments are particularly important for understanding climate variability (ACIA, 2005; Kennett et al., 2003; Kerr, 2010). Approximately 70% of the Arctic Ocean is ice-covered throughout the year, but recent global warming since the mid-19th century has diminished the sea ice extent, changing carbon uptake by the Arctic Ocean (ACIA, 2005; Bauch et al., 2000). The increased freshwater flux from both glacial melt and the melting sea ice reduces surface salinity and increases the solubility of CO2 (Arrigo et al., 2010). As the cold water from the Arctic Ocean contributes to the formation of the North Atlantic Deep Water (NADW), the current freshening of the Arctic Ocean may play a primary role in global climate through slowing the AMOC (Dickson et al., 2007; Jahn and Holland, 2013; Rennermalm et al., 2007). Thus, changes in carbon sink feedbacks and the strength of the AMOC linked to sea-ice melting in the Arctic could influence global climate evolution for the next decades through centuries (ACIA, 2005; Perovich et al., 2007).

Natural proxy archives that give indirect information on past climatic conditions extend environmental data in space and time. At high latitudes, most annual and decadal climate reconstructions are based on terrestrial proxies such as ice cores from glaciers, tree rings, or varved lake sediments (Kaufman et al., 2009; Overpeck et al., 1997; Steffensen et al., 2008) that do not provide information about marine environmental conditions. The majority of annually to decadally resolved surface ocean climate reconstructions are almost exclusively based on hermatypic shallow-water corals (Grottoli and Eakin, 2007), sclerosponges (Rosenheim et al., 2004), and bivalves (Schöne, 2013). However, hermatypic corals and sclerosponges are limited to tropical and subtropical seas, excluding the possibility of high-latitude climate reconstructions. Although bivalves provide the majority of extratropical near surface marine climate data (e.g., Wanamaker et al., 2011), they also have a limited biogeographical range (Dahlgren et al., 2000). Thus, little is known about the subannual to interannual evolution of the surface Arctic Ocean during the last several centuries, and reconstuctions of past climatic variability in the high latitudes would benefit from additional high resolution environmental archives.

The crustose coralline algae Clathromorphum sp. and Lithothamnion glaciale are ideal biogenic marine climate archives of the mid- to high latitude environmental variability because of their incremental growth pattern, longevity, preservation potential, and incorporation of changes in their ambient environment into the geochemistry and sclerochronology of their skeleton (Chan et al., 2011; Halfar et al., 2013, 2008; Hetzinger et al., 2013; Kamenos et al., 2008, 2012; Williams et al., 2011). Seasonal decreases in temperature and light during winter periods reduce the calcification rate of the algae. The skeletal anatomy changes from narrow and elongate cells with dense walls to wider and shorter cells with thinner walls resulting in growth increment demarcations in the fall to early winter in its high Mg-calcite skeleton (Adey et al., 2013). Furthermore, cavities in which the reproductive structures develop (i.e., sporangial conceptacles) form in fall and early winter (Adey, 1966) in Clathromorphum sp. Parts of the conceptacles intrude downward by decalcification, protuding into algal skeleton that has precipitated in the summer. Nevertheless, yearly layering of conceptacle cavities can provide a secondary marker for annual growth (Adey, 1966). Diagenesis resulting from the decalcification is limited to the skeleton within 1–2 microns of the conceptacles. In cases of minimal yearly growth, conceptacle bases can intrude into the previous year's growth (Moberly, 1968). Yet, to date, reconstructions derived from Clathromorphum sp. and L. glaciale in the Arctic Ocean are limited (Halfar et al., 2013; Kamenos, 2011) due to a lack of sufficient higher latitude specimens. Thus, additional studies are needed to increase the use of coralline algae to reconstruct Arctic climate change.

The high-latitude crustose coralline alga Leptophytum foecundum (Kjellman) may serve as a paleoenvironmental proxy to increase the number and spatial extent of records of environmental change in the Arctic Ocean. Thus, we measured growth rates and growth increment formation along with Mg/Ca, δ18O, and δ13C composition of the high-Mg calcitic skeleton in three specimens from the Beaufort Sea to evaluate the feasibility of extracting environmental signals from the skeleton of L. foecundum. If this alga proves to yield a reliable record of Arctic Ocean parameters, future studies may use longer-lived specimens in order to reconstruct the climate evolution of the Arctic Ocean during the past centuries during which we have no instrumental data.

Methods

STUDY AREA

Three specimens of the coralline alga Leptophytum foecundum (Kjellman) (BSA2, BSA3, and BSA7) were collected live from 5 m depth by SCUBA during a research cruise in the Beaufort Sea, close to Prudhoe Bay, off the Sagavanirktok River (Sag River) delta (70°20′N, 147°40′W) in July 2007 (Fig. 1). Sea surface temperatures (SSTs) derived from OBPG Aqua MODIS Ocean Color for the sampling site vary from -1.95 °C in the winter season (December through April/May) to 5 °C in July over the period of 2002–2008 (Acker and Leptoukh, 2007). On shore, the 289 km Sag River originates on the north slope of the Brooks Range in northern Alaska (Benke and Cushing, 2011) then flows across the Arctic Slope province before entering the Beaufort Sea in the Arctic Ocean (Fig. 1). It is principally fed by snowmelt with some groundwater and glacial influence (Benke and Cushing, 2011) and is frozen between September and May, thawing in late May to June. Surface temperatures for the Sag River have varied from 0 °C to 15 °C between 1990 and 2007 (temperatures provided by Mathew Schellekens [USGS]). Annual Sag River discharge and gage height vary from 28 to 69 m3 s-1 and 5 to 7 m, respectively, on interannual time scales (Fig. 2, parts a and d) (data from  http://waterdata.usgs.gov).

Leptophytum foecundum (KJELLMAN)

Leptophytum foecundum is an Arctic species that extends into the subarctic photic zone (Adey, 1970) and grows on pebbles and stones (Athanasiadis and Adey, 2006) (Fig. 3). It is a crustose species with no major surface irregularity, except those created by overgrowing over an irregular substrate (Athanasiadis and Adey, 2006). Overgrowth of one plant by another is rare in this species (Adey et al., 2001). Buried multiporate asexual conceptacles ranging from 220 to 500 µm in diameter and 140 to 250 µm in height are very frequent (L. foecundum var. sandrae) (Athanasiadis and Adey, 2006). Lateral growth rates based on specimens grown in laboratory experiments range from 1 to 9 µm day-1 (= 365 to 3285 µm yr-1), depending on ambient temperature and light (Adey, 1970).

FIGURE 1.

Study area in Beaufort Sea showing proximity to Prudhoe Bay and Sagavanirktok River, including the Sag River delta (inspired from Kline et al., 1998).

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FIGURE 2.

(a) Gage height with time; (b) gage height versus δ18O composition and (c) MgCO3 content. (D) Discharge data for Sagavanirktok River (data from  http://waterdata.usgs.gov) with time, (e) discharge data versus δ18O composition, and (f) MgCO3 content.

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FIGURE 3.

Anatomical characteristics of L. foecundum calcareous skeleton. (a) L. foecundum in life position growing on pebble (top view). (b) Cross section of L. foecundum (BSA2) perpendicular to growth direction showing growth direction, growth lines, and conceptacles.

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SAMPLE PREPARATION AND ANALYSIS

After collection, a dozen of L. foecundum specimens were air dried, separated from pebbles, and cut into 1-cm-thick slices perpendicular to the direction of growth using a circular diamond precision saw (Buehler IsoMet1000). Three specimens with the highest potential to record paleoenvironmental data based on largest vertical height and best developed growth lines were selected for further visual and geochemical analyses. These samples were epoxyed onto glass slides and machine polished to 1 µm with a Logitech CL50 using diamond-polishing suspensions with grit sizes of 9, 3, and 1 µm on a Buehler polishing disk. Polished sections were cleaned in an ultrasonic bath for 10 minutes with deionized water between each polishing step and dried overnight prior to sampling.

Digital images of the polished surface were produced using an Olympus reflected light microscope (VS-BX) attached to an automated sampling stage-imaging system equipped with geo.TS software (Olympus Soft Imaging Systems). This setup allows a two-dimensional mapping of the surfaces of the polished specimens using multiple images spliced together to generate one image. The resulting high resolution photomosaics enabled the identification of growth patterns over the entire sample and the subsequent selection of sampling locations (Fig. 4). The locations of conceptacles and annual growth increments were identified using the digital photomosaics.

Mg/Ca MEASUREMENTS

Mg/Ca values in specimens BSA3 and BSA7 were measured using a JEOL JXA 8900 RL electron microprobe at the University of Göttingen, Germany. For quantitative wavelength dispersive measurements, an acceleration voltage of 15 kV, a focused beam, and a beam current of 12 nA were used (see Hetzinger et al., 2009, for additional details). The electron beam was manually positioned on calcite within an individual algal cell. The sampling transects were preselected on the digital photomosaic images avoiding conceptacle cavities and recalcified portions of the skeleton (Fig. 4). Spot analyses were spaced 10 µm apart along a transect parallel to the direction of growth (Figs 4 and 5). Transects ranged in length from 890 µm (BSA3) to 1440 µm (BSA7). Counting statistics errors at the 99% confidence level varied between 0.035 and 0.087 mass % for MgO and between 0.33 and 0.40 mass % for CaO. The detection limit of MgO calculated from the background noise was100 µg g-1 at the 99% confidence level. Backscattered electron images obtained after the microprobe analysis documented the actual single point transects analyzed (Appendix Fig. A1).

The substitution of Ca by Mg in calcium carbonate is an endothermic reaction, thus it is favored by higher temperatures, providing the use of Mg/Ca ratio as a paleothermometer (Lear, 2002). Seasonally changing Mg content within annually banded coralline algae positively correlates to the sea surface temperatures (SSTs) of the water in which they formed (Chave, 1954; Adey, 1965 ; Chave and Wheeler Jr., 1965; Hetzinger et al., 2009; Kamenos et al., 2008), although light- and temperature-driven growth rates may also influence Mg content (Kolesar, 1978; Moberly, 1968). Using the Lithothamnion glaciale MgCO3-SST relationship established by Halfar et al. (2000) the mol% values measured here were converted to temperature:

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In addition, the MgO and CaO values measured here were translated into Mg/Ca values (mol/mol) and then converted to temperature using the Clathromorphum nereostratum Mg/Ca-SST relationship established by Williams et al. (2014 ) for a different genus of coralline algae:

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DEVELOPMENT OF CHRONOLOGY

Chronologies were generated first by counting annual growth lines on the mapped and digitized image of the specimens. All samples were live collected; hence the top layer was assigned the year of collection, 2007, and calendar years were assigned to annual growth increments starting from 2007 and extending back in time. In addition, yearly growth-increment widths were calculated from annual Mg/Ca-element cycle widths that were obtained by electron microprobe for two specimens (BSA3 and BSA7). Age models were established on the basis of the seasonal cycle in algal Mg/Ca: high Mg values within the skeleton were assigned to July, which is on average the warmest month, and minimum values were tied to February, which is on average the coolest month at the study site (Benke and Cushing, 2011). The algal Mg/Ca time series were linearly interpolated between these anchor points using the AnalySeries software (Paillard et al., 1996) to obtain an equidistant proxy time series with a monthly resolution. Because of possible growth discontinuities prior to the year 2001 in BSA3 and 1997 in BSA7, only data after those years were interpreted. Linear regression tested for statistical correlation of the monthly resolved time-series between the two specimens, and with instrumental records of environmental conditions. The developed chronologies were refined and cross-checked for possible errors in the age model by comparing annual extreme values in the Mg/Ca ratio time series to mapped growth increment patterns for each individual year of algal growth.

STABLE OXYGEN AND CARBON ISOTOPE ANALYSIS

Skeletal material for stable oxygen and carbon isotopes analyses was removed in specimens BSA2 and BSA7 by a high-precision, computer-driven New Wave Research Micromill attached to an x, y, and z stage using digitized milling path positions. Due to logistical constraints, we did not determine the isotopic composition of specimen BSA3. For specimens BSA2 and BSA7, sampling paths were defined using geo.TS software and transferred to the Micromill to mill 100 to 200 µg of calcite powder per sample resulting in a resolution of two to four samples per year. The sampling depth was 150 µm and sample path lengths averaged 1.30 cm for BSA2 and 1.15 cm for BSA7. Since skeletal material was bulk sampled to obtain sufficient material for analysis, conceptacles were not avoided. Material was removed from the outside edge of the specimen first, which represented the most recent growth followed by subsequent samples moving toward the oldest part of the sample. Using a razor blade, the milled powder was transferred into a glass vial used for the mass spectrometer. Sample amounts were 56 samples milled from BSA2 and 42 from BSA7.

Removed material was analyzed for δ18O and δ13C (‰ relative to Vienna Pee Dee Belemnite standard [VPDB]) using a Thermo-Finnigan MAT253 mass spectrometer connected to a gasbench and autosampler at the Geobiology Stable Isotope Lab oratory, University of Toronto. The international standard NBS-19 and two in-house standards (IAEA-CO-1 and IAEA-CO-2) were used for calibration of all samples. One standard deviation of the mean of duplicate measurements was ±0.08‰ for δ18O and ±0.16‰ for δ13C. Using the established chronology, a stable isotope time series was compiled for BSA2 and BSA7.

FIGURE 4.

Geo.TS images of (a and b) BSA2, (c) BSA7, and (e) BSA3 cross sections with selected transects for microprobe measurements for (d) BSA3 and (f) BSA7.

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Since stable oxygen isotope fractionation during calcification is temperature dependent, the δ18O composition of calcium carbonates serves as a paleothermometer (Urey, 1947). Here, seawater temperatures were reconstructed using the temperature-oxygen isotope calibration established by Anderson and Arthur (1983) with modifications to account for the high Mg content (Jiménez-López et al., 2004) and vital effects (Halfar et al., 2008):

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A δ18Osw value of -4.49‰ (Bedard et al., 1981; Schmidt et al., 1999) was used, which is consistent with end-member seawater values reported by Alkire and Trefry (2006) for seawater δ18O composition.

Results

CHRONOLOGY

The combination of a high number of large conceptacles and very low growth rates resulted in poorly delimited annual growth increments (Figs. 4 and 5). Despite this, image-based chronologies were established from 1997 to 2007 for BSA7, from 2000 to 2007 for BSA2, and 1998 to 2007 for BSA3. Average annual growth rates were 180 ± 26 µm yr-1 (max = 213 µm yr-1, min = 117 µm yr-1) for BSA2, 243 ± 49 µm yr-1 (max = 330 µm yr-1, min = 160 µm yr-1) for BSA7, and 190±50 µm yr-1 (max = 243 µm yr-1, min = 109 µm yr-1) for BSA3 (Table 1) (Fig. 6, part a).

Maxima in Mg/Ca were aligned with the center of each growth increment, and minima with growth increment lines in BSA3 and BSA7 resulting in ∼15 samples year-1 for BSA3 and ∼21 samples year-1 for BSA7 prior to interpolation. Using widths of the annual Mg/Ca cycle, annual growth rates averaged 215 ± 50 µm from 2001 to 2006 for BSA7 and 170 ± 47 µm from 2003 to 2006 for BSA3 (Table 1). The Mg/Ca-derived growth rates were comparable to the growth rates measured using the visual growth increments as a reference.

Mg CONTENT

The average MgCO3 content did not significantly differ between the specimens BSA3 and BSA7 (p = 0.36, n = 57; Table 1). Using monthly interpolated values, the MgCO3 content did not significantly correlate between the two specimens (p = 0.82, r2 = 0.03, n = 57; Fig. 6, part b).

Using Equation 1, reconstructed temperatures averaged −0.05 ± 2.0 °C (min = −3.9 °C, max = 3.9 °C) for BSA3 (period: 2001–2006) and −0.3 ± 1.9 °C (min = −4.5 °C, max = 4.5 °C) for BSA7 (period: 2000–2006; Fig. 7, parts b and c). Using Equation 2, reconstructed temperatures averaged 2.3 ± 2.1 °C (min = -1.7 °C, max = 6.6 °C) and 2.1 ± 2.0 °C (min = -2.4 °C, max = 7.2 °C) for BSA3 and BSA7, respectively, for the same periods as above (Fig. 7, parts b and c). Using annually averaged values, neither temperature reconstruction significantly correlated with satellite-derived SST (p = 0.37, r2 = 0.12, n = 57 and p = 0.55, r2 = 0.07, n = 72 for BSA3 and BSA7, respectively).

STABLE OXYGEN ISOTOPE VALUES

The δ18Oalga values did not significantly differ between the specimens BSA2 and BSA7 (p = 0.30, n = 7; Table 1). Using annually averaged values, the δ18Oalga values significantly correlated between the two specimens from 2000 to 2006 (p = 0.045, r2 = 0.59, n = 7; Fig. 6, part c). Neither of the annually averaged δ18Oalga records significantly correlated with growth rates or Sag River discharge or streamflow. The δ18Oalga record for specimen BSA7 significantly correlated with gage height from 1997 to 2006 (p = 0.03, r2 = 0.46, n = 10; Fig. 2, part b).

Using Equation 3, the oxygen isotopic composition of L. foecundum yielded average seawater temperatures of -0.22 ± 0.99 °C and -0.03 ± 1.12 °C for specimens BSA2 and BSA7, respectively (Fig. 7, parts d and e). Neither temperature reconstruction significantly correlated with satellite-derived SST (p = 0.74, r2 = 0.16, n = 7 and p = 0.76, r2 = 0.11, n = 10 for BSA2 and BSA7, respectively).

STABLE CARBON ISOTOPE VALUES

The average (±stdev) δ13Calga values significantly differed between the specimens BSA2 and BSA7 (-1.93‰ ± 0.18‰ and -1.59‰ ± 0.31‰, respectively) for the common period 2000–2006 (p = 0.0009, n = 14) (Fig. 6, part d). Using annually averaged values, the δ13Calga values did not significantly correlate between the two specimens, or with Sag River discharge or gage height. The annually averaged δ13Calga values significantly correlated with annual growth rates in specimens BSA2 (p = 0.014, r2 = 0.86, n = 7) but not BSA7.

Discussion

DEVELOPMENT OF CHRONOLOGY

The large conceptacles (140–250 µm diameter) relative to very low growth rates (180 to 240 µm yr-1) obscured the annual growth bands in some instances. In addition, not all growth increments identified in the digital images of each specimen were continuous laterally, and growth interruptions distorted the chronology because their duration was unknown (Fig. 5). Thus, chronologies prior to growth discontinuities in each specimen were not assigned (Table 1). Despite this, measured growth rates in the specimens were similar to thickness growth rates obtained for Arctic to Subarctic species of the climate archive Clathromorphum compactum (Adey et al., 2013). Cross dating of both algae using the same method as for tree rings (i.e., to correlate years with the same thickness of growth increments) was not possible because a variety of specimen-specific biotic factors alters growth, including shading of a specimen for an extended period, differential grazing, and/or other unknown factors. The chronology deduced from the width of annual Mg/Ca cycles was established with difficulty because of noise in the elemental signal (Fig. 6, part b), likely resulting from the small-scale variability in annual growth banding and the sometimes low seasonal variability in seawater surface temperatures (Fig. 7, part a). Despite this, growth rates determined from the annual cycle in Mg content were consistent with those determined from the optically measured growth increment widths. The difficulty in determining the growth increments and short lifespans in the specimens collected, along with restricted development of the perithallium (Adey et al., 2001), indicates that long-lived specimens of this species with clear chronologies may be difficult to find. Newer collections of this species from the Labrador Sea Coast, unaffected by freshwater influent appear more regular and may provide better climate archive data (Adey, specimens in herbarium US).

Mg/Ca-DERIVED SEA SURFACE TEMPERATURES

SSTs reconstructed using the L. glaciale-derived transfer function yielded similar average temperatures to the satellite SST data (≤0.7 °C difference, Fig. 7, parts a and b); however, the winter minima far exceeded satellite values (e.g., -3.9 °Calga and -4.5 °Calga vs. -1.8 °Csatellite). SSTs reconstructed using the C. nereostratum-derived transfer function yielded average reconstructed SSTs exceeding the satellite SST data (2.8–3.0 °C difference) due to overestimation of the summer maxima (e.g., 6.6 °Calga and 7.2 °Calga vs. 2.8 °Csatellite) (Fig. 7, parts a and b). Thus, the transfer functions developed for other coralline algal species cannot be applied successfully to L. foecundum, potentially due to taxa-specific vital effects or because of site-specific environmental variability. Such differences between SST and bottom temperature necessitate in situ calibrations for coralline algae or just a species-specific calibration. In addition, it is apparent from parallel studies of the high latitude climate archive C. compactum that growth can cease for a number of months in mid-winter, during the later phases of Arctic winter darkness, further complicating coralline archives from different latitudes.

FIGURE 5.

Chronologies for (a) BSA2, (b) BSA7, and (c) BSA3. Blue lines delimit annual growth increments. Calendar years were assigned to annual growth increments starting from the year of collection and extending back in time. Red lines underline a growth interruption across an entire year, and orange circles point to discontinuities where a section of growth is missing within a single year.

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TABLE 1

Calculated average growth rates, MgCO3 (Mol%), and δ18O and δ13C (‰, VPDB) values for each specimen. Mg/Ca was not measured in BSA2 and stable isotopes were not measured in BSA3.

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Salinity affects the incorporation of Mg into the skeleton of the alga C. nereostratum (Chan et al., 2011), hence a freshwater influence from the Sag River may alter the incorporation of Mg in the skeleton to changes in temperature. Recent studies of high-Mg calcite in echinoderm skeletons and foraminiferal tests field-collected or cultured in different salinities have demonstrated a clear negative effect of salinity on Mg/Ca ratios (Ferguson et al., 2008; Kısakürek et al., 2008). This effect might explain the cold temperatures calculated in this study using the L. glaciale-derived transfer function, as the salinity in Beaufort Sea is very low (between 15‰ and 30‰) and the Sag River contributes significant amounts of freshwater to the collection site. More experiments that monitor temperature and salinity would therefore be necessary to establish a new calibration linking MgCaO (mol%) and temperature in waters with low salinity. Regardless, our data indicate that without further exploration, L. foecundum cannot be used as a paleo-SST proxy in the Arctic Ocean using skeletal Mg content.

OXYGEN ISOTOPE VALUES

SSTs reconstructed from the algal-δ18O composition generated average seawater temperatures that were consistent with the satellite SST data (Fig. 7, parts a and d). Thus, seawater temperature is a primary control driving the δ18O composition of L. foecundum at this location. However, the algal-derived SSTs do not significantly correlate with the satellite SSTs at interannual timescales, nor do they vary seasonally as is evident in the satellite data. Thus, other factors in addition to seawater temperature drive the temporal variability in skeletal oxygen isotopic composition. Given that the oxygen isotopic record does not vary consistently subannually, seasonal freezing and melting of sea ice with isotopically light δ18O likely does not influence the oxygen composition of the algal skeleton. Indeed, even if seawater becomes enriched in 18O as it freezes, the isotopic fractionation observed in sea ice is typically small (Cooper et al., 2005). Instead, runoff from Sag River likely influences the isotopic composition off the delta, along with other factors. As the source of Sag River is located in the high altitudes of the Brooks Range in Alaska with a continental climate, the runoff is strongly depleted in 18O (Cooper et al., 2005). In addition, Sag River temperatures are significantly warmer than the Beaufort Sea (Fig. 7, part a). As such, enhanced Sag River runoff would be expected to drive negative deviations in the alga δ18O composition, which is not supported by the data here. Thus, while the δ18Oalga variations of the two specimens significantly correlate with each other, supporting a common environmental driver of alga δ18O composition and suggesting that specimen-specific variables such as diagenesis of the conceptacles is not a concern, seawater temperature and salinity, and fresh water from the Sag River likely combine to influence the oxygen isotopic composition. In addition, L. foecundum may integrate the ambient water δ18O signal over several years, further compounding the drivers of the alga's oxygen isotopic composition.

CARBON ISOTOPE VALUES

Intrinsic characteristics of each specimen may control the δ13Calga composition. Generally, more negative δ13Calga values are associated with faster rates of skeleton formation in other calcium carbonate marine organisms (Butler et al., 2011; Swart et al., 2010). In fact, the δ13Calga may reflect kinetic isotopic disequilibrium at high growth rates. During the years of relatively low growth rates, a relative increase in the proportion of metabolic carbon available for skeleton construction may deplete the skeletal 13C (Butler et al., 2011; Lorrain et al., 2004). Thus, an increase in extension rate is coupled with a decrease in δ13Calga and vice versa. However, growth rates positively correlate with δ13Calga in specimen BSA2, while no clear pattern is present in specimen BSA7 (Fig. 6, part d). Therefore, the source of variability in the skeletal δ13Calga values may not in fact be intrinsic to the coralline alga. Exploration of external factors driving δ13Calga, changes in the ambient dissolved inorganic carbon (DIC) that is the source of carbon to the algae, may thus be useful.

Anthropogenic burning of isotopically light fossil fuels is decreasing the isotopic composition of the carbon in the atmosphere and the oceans. This century-scale trend toward lighter carbon isotopes—the δ13C-Suess effect (Nozaki et al., 1978; Suess, 1953)—is recorded in calcareous skeletons of long-lived marine organisms (Swart et al., 2010). A decline in δ13C of -0.95‰ per decade for the 1990s was measured in coralline algae in the northern North Pacific Ocean/Bering Sea (Williams et al., 2011), and -0.9‰ from 1850 to 1987 in the Arctic Ocean in the polar planktic foraminifer Neogloboquadrina pachyderma (Bauch et al., 2000). These rates are high relative to values measured in other areas of the world oceans in low latitudes and may represent changes in ventilation of the surface waters (Bauch et al., 2000; Williams et al., 2011). Here, the clear absence of a decreasing trend for δ13Calga in BSA2 and BSA7 implies that anthropogenic carbon is either not being taken up by the ocean locally or the decreasing isotopic composition of the DIC is being offset by other processes. The Beaufort Sea is partly sea-ice covered all year round (Pabi et al., 2008), which could decrease the exchange between atmosphere and ocean and can explain the absence of an oceanic Suess effect in the Beaufort Sea. Alternatively, a potential increase in primary productivity in the Beaufort Sea (Pickart et al., 2013; Tremblay et al., 2011) may be offsetting the decline in skeletal δ13Calga.

FIGURE 6.

Measured (a) growth rates (µm yr-1), (b) MgCO3 (mol%), (c) δ18O (‰, VPDB), and (d) δ13C (‰, VPDB) for each specimen analyzed.

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The absence of decreasing δ13C values in L. foecundum also indicates that there has been no release of methane hydrates associated with decreasing subsea permafrost recorded by the δ13Calga composition (Rachold et al., 2007). The large amount of ancient organic matter contained in permafrost might be involved in current biogeochemical cycling due to thawing of the upper permafrost and restoration of the activity of viable methanogens preserved inside the permafrost (see Shakhova and Semiletov, 2007, and reference therein). However, the isotopic signatures of organic matter incorporating methane-derived carbon range from -60‰ to -65‰ (Dickens et al., 1995; Kvenvolden, 1993) relative to that of other oceanic and atmospheric carbon reservoirs with a δ13C = 0‰ ± 7‰ (Paull et al., 2002). Thus, if gas hydrate dissociation is observed on the East Siberian Arctic shelf (Heimann, 2010; Shakhova et al., 2010), no isotopic trace of such a phenomenon is recorded in the corallines of the Beaufort Sea Arctic shelf.

Finally, riverine influx from the Sag River can influence the surface water δ13CDIC and might be recorded by the δ13Calga. As river waters tend to have a more negative carbon isotope signature than the ocean (Degens et al., 1991), we expect an anticorrelation with gage height or discharge in the δ13Calga recorded. However, no correlation between the variations of the river's regime and δ13Calga was noticed. The most likely explanation is that the proximity of the Sag River delta and sediment input in the study area disturb the record of the Beaufort Sea isotopic composition, although no clear external cause for the observed carbon isotopic record can be identified here.

FIGURE 7.

(a) Beaufort Sea (from Acker and Leptoukh, 2007) and Sagavanirktok River (from Mathew Schellekens [USGS]) water temperature; (b) seawater temperature reconstructed from Clathromorphum nereostratum Mg/Ca-SST relationship (top) and Lithothamnion glaciale MgCO3-SST relationship (bottom); (c) BSA3 versus BSA7 seawater temperature reconstructed from the MgCO3-SST relationship; (d) seawater temperature reconstructed from δ18O composition; (e) BSA2 versus BSA7 seawater temperature reconstructed from the δ18O composition.

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Conclusion and Prospects

Leptophytum foecundum forms a banded skeleton with large conceptacles relative to annual growth rates in the high Arctic, making image-based chronologies difficult to establish. In addition, potential growth discontinuities present in the skeleton limited the duration of paleoenvironmental records that could be extracted from the skeleton. A secondary method of dating, such as radiometric dating, is needed to verify algal age prior to the potential growth discontinuities but is difficult to do considering the young ages of the specimens. This, combined with the restricted development of the perithallium (Adey et al., 2001), limits the duration of records that are feasible to extract from L. foecundum.

The absence of significant correlation between L. foecundum skeletal geochemistry and environmental records further indicate the difficulties in generating paleoenvironmental records from the alga at this location. Average Mg content was similar between the two samples but varied differently over time. In addition, Mg content-derived reconstructed seawater temperatures using transfer functions developed for other taxa of coralline algae yielded temperatures that were inconsistent with satellite data. The location of the two specimens close to the discharge of the Sag River suggests a salinity influence in addition to temperature on the Mg content in L. foecundum. Alternatively the algal-Mg to SST transfer functions developed for other taxa are not applicable to L. foecundum or the satellite data do not accurately capture bottom temperatures that bath the coralline algae. Significant correlation of the δ18Oalga between the two specimens supports an external environmental driver of algal skeletal δ18O. This driver is likely a complex combination of Beaufort Sea seawater δ18O composition and temperature combined with Sag River freshwater δ18O composition and temperature during high flow periods. Average δ13C composition differed between the two specimens and over time. Documented changes in the source carbon to the region (e.g., δ13C-Suess effect) would cause a decline in skeletal δ13C values not present in the skeleton. As a result of this study, specimens of L. foecundum do not appear to provide a reliable new paleoenvironmental proxy for the Arctic Ocean, although studies of L. foecundum specimens removed from a freshwater influence might prove more useful.

Acknowledgments

Mathew Schellekens provided the data for Sag River. Hong Li assisted with the isotope analyses at the Geology Department at University of Toronto. Sophie Padié and Phoebe Chan provided assistance with data interpretation and statistical analyses. Analyses and visualizations of Beaufort Sea SST used in this paper were produced with the Giovanni online data system, developed and maintained by the U.S. National Aeronautics and Space Administration (NASA) Goddard Earth Sciences Data and Information Services Center (GES DISC). Funding was provided by a Natural Science and Engineering Research Council (Canada) Discovery Grant to Halfar.

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Appendices

APPENDIX

FIGURE A1.

Microprobe analysis and algal chronology. Red and green lines indicate position of measurement transects.

fA01_375.jpg
© 2015 Regents of the University of Colorado
Laurie Bougeois, Branwen Williams, Jochen Halfar, Brenda Konar, Walter Adey, Andreas Kronz, and Ulrich G. Wortmann "Does the Coralline Alga Leptophytum foecundum (Kjellman) Capture Paleoenvironmental Variability in the Arctic Ocean?," Arctic, Antarctic, and Alpine Research 47(2), 375-387, (1 May 2015). https://doi.org/10.1657/AAAR0014-061
Accepted: 1 December 2014; Published: 1 May 2015
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