FACULTY OF SCIENCES Master of Science in geology

Postglacial evolution of productivity in Lago Castor, northern Chilean Patagonia

Géraldine Fiers

Academic year 2015–2016

Master’s dissertation submitted in partial fulfillment of the requirements for the degree of Master in Science in Geology

Promotor: Prof. Dr. S. Bertrand Co-promotor: Dr. M. Van Daele Jury: Prof. Dr. M. De Batist, Prof. Dr. E. Verleyen

Cover image. View on Lago Castor (picture taken by Maarten Van Daele during the field expedition to Chile in 2011)

Acknowledgements

Before reading this thesis, I would like to seize the opportunity to thank some people who supported me during this master thesis.

First of all, I would like to thank my promotor, Sébastien Bertrand, who gave me the opportunity to work on the Lago Castor project. Your door was always open for any kind of advice and I really appreciate all your help, the many suggestions you made and the constructive discussions we had. I learned a lot from your scientific expertise and especially in the way of thinking like a real geologist. For that, I’m very grateful having you as promotor. The people who participated to the expedition to Chile and collected the composite core and additional samples are thanked because without them this study would not have been possible. I want to thank Maarten Van Daele for giving me all the information and data I needed of Lago Castor, for helping me working with global mapper and for revising my thesis.

I would also like to thank the people working at the Renard Centre of Marine Geology for helping me in the laboratory and the guidance with several software programs. I am especially grateful to Veerle Vandenhende from the laboratory staff of the Department of Geology for helping me in the laboratory and for performing the ICP analysis on my samples.

I would like to thank my fellow students who became real friends during our studentship. The great times we had during class, on field trips and other non-geological related activities are unforgettable and made the past five years a very pleasant studentship.

Finally, I would like to thank my family and my boyfriend for their great support and encouragement during my student years.

Thank you and enjoy reading!

Géraldine

Table of contents

List of figures List of tables 1. Introduction...... 1 1.1 State-of-the-art ...... 1 1.2 Research objectives ...... 2 2. Regional setting ...... 5 2.1 Location and site description ...... 5 2.2 Geological setting ...... 6 2.3 Late Quaternary evolution ...... 6 2.4 Present-day climate and vegetation ...... 7 3. Material and methods ...... 9 3.1 Previous research ...... 9 3.1.1 Core acquisition, logging and XRF scanning ...... 9 3.1.2 Chronology...... 10 3.1.3 Sedimentology ...... 11 3.1.4 Bulk organic geochemistry ...... 11 3.1.5 Pigment analysis ...... 12 3.1.6 quantification and paleoecology ...... 12 3.2 Biogenic silica analysis ...... 13 3.2.1 Introduction ...... 13 3.2.2 Alkaline extraction technique ...... 13 3.2.3 Scanning XRF ...... 15 4. Results ...... 17 4.1 Biogenic silica analysis: alkaline extraction technique ...... 17 4.1.1 Lithogenic correction factor ...... 17 4.1.2 Downcore results ...... 17 4.2 Scanning XRF ...... 17 4.3 composition...... 19 4.3.1 Components ...... 19 4.3.2 Smear slides ...... 20

5. Discussion ...... 23 5.1 Biogenic silica ...... 23 5.1.1 Comparison of the different biogenic silica proxies ...... 23 5.1.2 Comments on the calculation of the lithogenic correction factor ...... 24 5.1.3 Absolute diatom abundance versus diatom biovolume ...... 26 5.2 Variations in sediment composition ...... 27 5.3 Postglacial wind and precipitation variability ...... 30 5.3.1 Deglaciation ...... 32 5.3.2 Postglacial evolution of precipitation and westerly wind strength ...... 32 5.4 Postglacial changes in lake productivity ...... 34 5.4.1 Relations between opal and aquatic organic carbon ...... 34 5.4.2 Postglacial evolution of lake productivity ...... 34 5.4.3 Relations between climate change and lake productivity during the deglaciation ...... 36 5.4.4 Relations between climate change and lake productivity during the Holocene ...... 37 6. Conclusion ...... 39 References ...... 41 Appendix ...... 47

List of figures

Figure 1 Simplified vegetation map of northern Chilean Patagonia ...... 5

Figure 2 (a) Annual mean precipitation in Patagonia. (b) Correlation between monthly precipitation at Coyhaique Alto and zonal wind speed ...... 8

Figure 3 Present-day climatology of Coyhaique alto: monthly precipitation (1985-2010) and monthly temperature (1994-2010) ...... 8

Figure 4 Bathymetry map of Lago Castor with locations of composite core (CAST01), short core (CAS- 09; Elbert et al., 2013) and soil samples (SS) ...... 9

Figure 5 The age-depth model of the Lago Castor sedimentary record ...... 10

Figure 6 Bulk organic geochemical results of Granon (2015): C/N versus δ13C biplots of the core samples, sediment samples and suspended particulate matter (SPM) of river and lake samples ...... 11

Figure 7 Schematic illustration of silica released from and during the alkaline extraction process ...... 14

Figure 8 Lithology of sediment core CAST01, downcore biogenic silica concentrations obtained by the alkaline extraction method and scanning XRF Si/Al and Si/Ti ratios ...... 18

Figure 9 Lithology and downcore variations of the different sediment components ...... 19

Figure 10 Selected microscopic pictures showing common diatom species in the sediment core .... 20

Figure 11 Comparison of smear slides before and after alkaline extraction ...... 21

Figure 12 Pictures of the smear slides after alkaline treatment: (a) showing the presence of volcanic glass; (b) showing a diatom frustule not totally dissolved during the alkaline treatment . 22

Figure 13 Biplot of the XRF elemental ratio Si/Al with biogenic silica concentrations ...... 23

Figure 14 Comparison of the several biogenic silica proxies: biogenic silica, XRF Si/Al ratio, absolute abundance of diatoms and the concentration of the pigment fucoxanthin ...... 25

Figure 15 Bulk sediment composition versus composite core depth: lithology, aquatic and terrestrial organic carbon, opal concentrations and the detrital fraction ...... 27

Figure 16 Biplot of aquatic organic carbon with biogenic silica concentrations ...... 28

Figure 17 Comparison of the different postglacial wind and precipitation proxy records ...... 31

Figure 18 Comparison of the different lake productivity proxies with wind and sea surface temperature proxies...... 35

Figure 19 Comparison of the biogenic silica content in Lago Castor performed (a) in this study, displayed by the high-resolution XRF Si/Al ratio, and (b) in Elbert et al. (2013) ...... 37

List of tables

Table 1 Techniques to estimate the biogenic silica content of with important pioneering references ...... 13

Table 2 Pearson’s correlation coefficients between biogenic silica concentrations and the different biogenic silica proxies: scanning XRF elemental ratios Si/Al and Si/Ti, absolute abundance obtained by diatom counts and the concentration of diatom-derived pigments: diadinoxanthin, diatoxanthin, fucoxanthin, fucoxanthin-like ...... 23

1. INTRODUCTION

1.1 State-of-the-art

Over the last years, a lot of research has been done trying to understand past environmental and climatic variations in southern South America since the last deglaciation (Markgraf et al., 2007; Villa- Martínez and Moreno, 2007; Bertrand et al., 2010; Van Daele et al., 2016). In Patagonia, climate and environmental change is mainly controlled by the westerly winds, which are modified by the presence of the Andes, and related to changes in temperature. Variations in the latitudinal position and strength of these westerly winds is in turn responsible for changes in the amount of precipitation in the western Andes. Hence, reconstructing the evolution of Patagonian glaciers and the variations in westerly-driven precipitation are hot topics in southern South America and are frequently debated in the scientific literature (Markgraf et al., 2007; Glasser et al., 2008; Lamy et al., 2010; Moreno et al., 2010; Fogwill et al., 2015).

Reconstructing westerly wind variability is particularly important because they influence the large- scale circulation system and associated atmospheric CO2 variations (Moreno et al., 2010). The presence, nature and exact timing of cold events interrupting the deglaciation such as the Younger Dryas and Antarctic Cold Reversal at the mid-latitudes of the Southern Hemisphere, and more particularly in southern South America, is also an issue of debate. Some studies report a cold phase in Patagonia coeval with the northern hemisphere Younger Dryas (Moreno et al., 2001) while most marine studies do not reveal a reversal in sea surface temperature during the deglaciation period (Lamy et al., 2004). Other authors suggest a cold event that is chronologically located between the Younger Dryas and Antarctic Cold Reversal, i.e. the Huelmo/Mascardi event (Hajdas et al., 2003).

In addition to accurately reconstruct the deglacial evolution of Patagonia, understanding the factors controlling aquatic productivity in lakes, i.e. temperature, pH, availability of nutrients, etc., is important to accurately interpret the regional paleoenvironmental records (Meyers and Teranes, 2001) and to evaluate the efficiency of lakes as a potential sink for atmospheric CO2. More research of continental records is therefore necessary to resolve the above mentioned issues, especially because high- resolution paleoclimate studies in southern South America are still rare compared to paleoclimate studies in the Northern Hemisphere. Lake sediments are also an excellent archive to reconstruct past limnological and climatic changes on a high-resolution scale in southern South America. Their study can therefore provide important clues regarding the natural evolution of terrestrial ecosystems.

Only a few studies exist that investigate the postglacial evolution of biogenic silica productivity in southern South America (Sterken et al., 2008; Bertrand et al., 2010; Elbert et al., 2013). The main producers of biogenic silica are diatoms. These are unicellular, eukaryotic algae and form an important group of primary producers in lakes. Their cell wall is silicified to form a frustule and this leads to a good preservation of diatoms in lake sediments (Battarbee et al., 2001). Diatom species are extremely sensitive to physical (temperature, light, turbulence, …) and chemical (pH, nutrients, salinity, …) conditions and therefore provide a valuable tool in reconstructing past environmental conditions. Because diatoms are the main contributors to the biogenic silica content in sediments, the biogenic silica content is often used as a proxy for past diatom productivity (Conley and Schelske, 2001). Therefore, this thesis will focus on reconstructing changes in biogenic silica concentrations of a sedimentary record of Lago Castor, a glacigenic lake located at 46°S in northern Chilean Patagonia, in order to infer the postglacial evolution of biogenic silica productivity. Previous studies of short

1 Chapter 1 – Introduction sediment cores in Lago Castor have already demonstrated a clear relation between accumulation rates of biogenic silica (i.e. diatom productivity) and annual air temperature during the last century (Elbert et al., 2013). Through the application of a calibration-in-time approach to a short core from Lago Castor, these authors were able to reconstruct temperature variations for the last 1.5 kyr. In this thesis, this relation between temperature and biogenic silica productivity will be examined and tested on longer timescales, i.e. back to the last 20 kyr.

Lago Castor has already been studied quite well. During a geophysical survey in 2009, a network of high-resolution reflection-seismic profiles was acquired and in 2011, a 15.4 m long composite core was retrieved. The advantage of investigating this sediment core is that the sedimentary record is continuous and covers the entire Holocene and deglaciation. Subsequently core logging and XRF core scanning were performed. Radiocarbon dating was used to reconstruct an age-depth model. In this way accumulation rates were calculated and they will be used here to determine the accumulation rate of biogenic silica to infer the diatom productivity of the last 20 kyr. A lot of analyses have been performed on the sediment core including loss-on-ignition, grain size (Van Daele et al., 2016) and bulk organic geochemistry (C/N and δ13C) analyses (Granon, 2015). Additionally, pigments were analyzed (De Raeve, 2015) and the diatom characteristics and paleoecology has been investigated (Van Goethem, 2015).

More recently, Van Daele et al. (2016) studied the sedimentary infill of Lago Castor in order to discuss the postglacial changes in westerly wind strength at 46°S in northern Patagonia. The lake is located within the postglacial pathway of the core of the southern westerly wind belt (SWWB), which migrated from ~42°S during the Last Glacial Maximum (LGM) to ~52°S at present. Van Daele et al. (2016) demonstrated that the sedimentation in Lago Castor is predominantly controlled by the SWWB after ~17 cal kyr BP. These authors suggested a progressive increase in wind strength from 11.2 to 4.5 cal kyr BP, which supports the expansion/contraction mechanism proposed by Lamy et al. (2010). After 4.5 cal kyr BP, a slight weakening of the westerly winds occurred. These interpretations were based on two independent proxies: the drift-intensity parameter and the modified sortable index (SS’).

1.2 Research objectives

The goal of this thesis is to reconstruct variations in biogenic silica productivity during the last 20 kyr, using samples from a 15.4 m long radiocarbon-dated sediment core that was collected in Lago Castor in 2011. The technique that will be used to determine the biogenic silica content is the alkaline extraction technique. Results from scanning XRF measurements (Willem Vandoorne, unpublished data) will be revised and elemental XRF Si/Al and Si/Ti ratios will be compared with my biogenic silica measurements obtained after alkaline extraction. This way the feasibility of using the higher resolution XRF data to estimate biogenic silica content will be examined.

In addition to my biogenic silica results, the bulk organic geochemical data from Granon will be revised. The C/N ratio and the carbon isotopic (δ13C) composition of bulk organic matter can be used to distinguish between aquatic and terrestrial sources of sedimentary organic matter (Meyers and Teranes, 2001). Here, we will mostly focus on reconstructing changes in accumulation rates of organic matter of aquatic origin as a proxy for paleoproductivity. Additionally, the C/N and δ13C values of sediment organic matter provide evidence of changes in watershed vegetation linked to variations in climatic conditions (Meyers and Teranes, 2001). This way, the relative contribution of C3 and C4 plants, i.e. plants with a different photosynthetic pathway, can be assessed (Powell et al., 2012).

2 Chapter 1 – Introduction

Thereafter the different proxies that can be used to estimate biogenic silica concentrations (XRF elemental ratios, diatom abundance obtained by point counting of diatoms and diatom-derived pigment concentrations measured with high-performance liquid chromatography) will be compared with my measured biogenic silica concentrations. Statistical analyses are performed to verify the correlation between these different proxies and my measured biogenic silica concentrations.

The wind proxies of Van Daele et al. (2016) will be compared with precipitation proxies to validate their results and eventually to reconstruct the postglacial evolution of precipitation and westerly wind strength in northern Patagonia. The most important question that this research will address is: what is (or are) the main driver(s) of the Holocene changes in biogenic silica productivity? Therefore, changes in accumulation rates of biogenic silica will be compared to other paleoproductivity proxies, such as accumulation rates of aquatic organic carbon. The different lake productivity proxies will be investigated and compared with different wind, precipitation and temperature records to ultimately resolve this research question.

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2. REGIONAL SETTING

2.1 Location and site description Lago Castor (45.6°S; 71.8°W) is a glacigenic lake located in the Aysén region of Chile on the leeside of the Patagonian Andes (Figure 1). It is situated about 20 km east of Coyhaique at an elevation of 725 m above sea level. The lake was formed by extensive glacial erosion from the Patagonian Ice Sheet (PIS) during the Quaternary (Van Daele et al., 2016). It has a maximal depth of 52 m, a relatively large surface area of 4.5 km² and a catchment area of 21 km² (Urrutia et al., 2002; Van Daele et al., 2016). The lake has no major inflow, but it is fed by several small inflows surrounding the lake. The outflow of the lake, Rio Pollux, is located in the southwest and drains into Rio Simpson and eventually through Aysén fjord into the Pacific Ocean (Elbert et al., 2013).

Figure 1. Simplified vegetation map (modified after Luebert and Pliscoff, 2006; Manzini et al., 2008; Vandekerkhove et al., 2016) of northern Chilean Patagonia with indication of the North Patagonian Icefield (NPI), main volcanoes and towns, the Coyhaique Alto weather station and Lago Castor (located within white rectangle). The Southern Volcanic Zone (SVZ) is indicated in inset map.

5 Chapter 2 – Regional setting

2.2 Geological setting The geology of the lake catchment consists mainly of Cretaceous volcanic rocks (mostly pyroclastic rocks, but also rhyolites and dacites) with in the western part some intrusive and subvolcanic diorites. Quaternary glacial deposits cover the bedrock in the northwestern and northeastern part of the lake catchment (De la Cruz et al., 2003). Lago Castor is located in the southern part of the southern volcanic zone (SVZ; see inset Figure 1) of the Andes where subduction of the oceanic Nazca Plate beneath the South American plate causes volcanic activity. Cay, Macá and Hudson are the nearest active volcanoes located in the vicinity of Lago Castor (Naranjo et al., 1998). A large number (more than 60) of explosive eruptions of various sizes of these southern SVZ volcanoes (especially Hudson volcano), documented in several lakes and terrestrial outcrops, have occurred since the glacial retreat at approximately 17.8 cal kyr BP (Naranjo and Stern, 2004; Weller et al., 2015). This high volcanic activity is confirmed by the sedimentary record of Lago Castor which contains 54 tephra layers over the last ~18 kyr (Van Daele et al., 2016).

According to Weller et al. (2015) and evidence from tephras from Pacific Ocean marine cores dating back prior to the Last Glacial Maximum (LGM) (Carel et al., 2011), the rate of explosive eruptions did not increase during the deglaciation, in agreement with Watt et al. (2013). The very large explosive eruptions in the early post-glacial period (e.g. Ho eruption of Hudson volcano around ~18 cal kyr BP; Weller et al., 2014; Stern et al., 2015) can be attributed to enhanced ponding of magma due to ice sheet cover during glaciation and eventually resulting in release upon deglaciation (Watt et al., 2013).

After the deglaciation of the lake basin and its catchment, no later than ~28 cal kyr BP, volcanic soils could develop in this region. As a result, the watershed of Lago Castor is covered by postglacial volcanic ash soils (andosols) with an average volcanic ash soil thickness of 1.15 m (Vandekerkhove et al., 2016). The andosol parent material is composed of high amounts of amorphous material (mostly volcanic glass), plagioclase, K- and pyroxene and reflects the typical andesitic basaltic signature of the regional volcanoes (Vandekerkhove et al., 2016).

2.3 Late Quaternary evolution During the Quaternary the North (NPI; Figure 1) and South (SPI) Patagonian Icefields expanded and contracted several times in response to climatic forcing. During glacial periods they connected and formed one large PIS (Glasser et al., 2008). This extensive glacial erosion formed the landscape of northern Chilean Patagonia which is characterized by many fjords and glacial lakes. During the post- LGM retreat of PIS glaciers, new drainage routes opened up and lake drainage shifted from initially eastward to westward into the Pacific Ocean (Glasser et al., 2016). Glasser et al. (2008) discussed the extension of the PIS between 38°S and 56°S before, during and after the LGM. However, the timing of maximum extent of the PIS east of the NPI is still under discussion, especially in the region around Lago Castor (Glasser et al., 2008 and references therein). Deglaciation of the Coyhaique Alto region, where Lago Castor is located, occurred during an early LGM across Patagonia as described by Fogwill et al. (2015). This is in agreement with Van Daele et al. (2016) who demonstrated that Lago Castor appeared to have been ice-free for at least the last 28 kyr. Afterwards, the strong orographic effect of the PIS- covered Andes and weaker westerly winds caused extremely dry conditions over the study area.

During the deglaciation, Lago Castor formed as a large proglacial lake. When the PIS outlet glaciers retreated far enough, the large paleo-lake Castor-Pollux-Frio drained possibly through an outburst flood, and desiccated. From ~20 cal kyr BP onwards, lake level rose due to an increased precipitation.

6 Chapter 2 – Regional setting

This increase in precipitation is due to a combination of a shrinking PIS and a southward shift of the southern westerly wind belt (SWWB). Lago Castor reached its modern lake level by ~17 cal kyr BP (Van Daele et al., 2016).

Climate fluctuations since the LGM in Patagonia are determined by variations in the latitudinal position and strength of the SWWB (Moreno et al., 2010; Lamy et al., 2010; Kilian and Lamy, 2012). Moreno et al. (2010) suggested that the SWWB coupled with the Southern Ocean system has an influence on multi-millennial CO2 variations during the Holocene, but according to Lamy et al. (2010) this influence is only true for the early Holocene. Also, the postglacial evolution of the SWWB is frequently debated. Van Daele et al. (2016) suggest a progressively increasing wind strength during the early and mid Holocene, supporting the expansion/contraction mechanism (Lamy et al., 2010). On the other hand, Moreno et al. (2010) argues that the entire wind belt weakened during the early Holocene and strengthened afterwards.

In northern Patagonia, most of the existing paleoclimate reconstructions are based on pollen records. These records have proven to be useful for reconstructing the position and strength of the westerly winds and the climate and vegetation history since the last deglaciation (Markgraf et al., 2007; de Porras et al., 2012; Villa-Martínez et al., 2012; de Porras et al., 2014). However, the timing and structure of vegetation and climate changes in these records are not always in agreement and a lot of uncertainties exist regarding the regional climate dynamics since the deglaciation. Markgraf et al. (2007) analysed a sediment core from a closed basin fen at Lago Pollux, i.e. Mallín Pollux, located at approximately 5 km of Lago Castor. The authors demonstrated the presence of a sparse shrub steppe associated with cold and dry conditions between 18 and 14 cal kyr BP. After 14 cal kyr BP, the vegetation shifted to a species-rich steppe indicating a moderate increase in moisture and temperature. Between 11 and 7.5 cal kyr BP, Nothofagus steppe-woodland developed suggesting increased precipitation and marked seasonality with summers drier than today. By 7.5 cal kyr BP, the Nothofagus forest was formed suggesting the establishment of a precipitation regime similar to the present-day climate. This is in accordance with de Porras et al. (2014) who documented a major rise in Nothofagus pollen around 11.2 cal kyr BP in the record from Mallín El Embudo (44°40’S, 71°42’W; located in the Río Cisnes valley) and the establishment of Nothofagus forests already since 9.5 cal kyr BP.

2.4 Present-day climate and vegetation Present-day precipitation in Patagonia is influenced by the westerly winds and strongly modified by the southern Andes. Very humid conditions prevail in western Patagonia due to the uplift of the westerly winds on the windward side of the Andes. On the contrary, downslope subsidence causes precipitation to decrease rapidly resulting in an arid climate in eastern Patagonia (Figure 2a; Garreaud et al., 2013). There is a strong positive correlation between precipitation in the Coyhaique Alto region and westerly wind speed (Figure 2b; Van Daele et al., 2016). Therefore, changes in precipitation amounts over Lago Castor are mostly related to the intensity of the southern westerly winds (Van Daele et al., 2016).

The present-day vegetation distribution in the southern Andes (Figure 1) reflects the decreasing west- east precipitation gradient (Garreaud et al., 2013). Vegetation changes from evergreen north Patagonian rainforests along the Pacific coast to shrubland and grass steppe in eastern Patagonia. The steppe vegetation is dominated by Poaceae. Conifer evergreen forests occur at the coast and interior in between the rainforests in the west. Deciduous forests composed of Nothofagus pumilio and

7 Chapter 2 – Regional setting

Nothofagus antarctica occur at higher altitudes. The main vegetation in the Lago Castor watershed consists of ‘temperate deciduous forested shrubland of Nothofagus antarctica and Berberis microphylla’ (Luebert and Pliscoff, 2006).

Figure 2. (a) Annual mean precipitation in Patagonia. The circles represent weather stations and the dashed line indicates the ridge of the Andes (Modified from Garreaud et al., 2013). (b) Correlation between monthly precipitation at Coyhaique Alto (~17 km to the NE of Lago Castor) and zonal wind speed at 700 hPa (1990-2010). The study region is indicated with a white rectangle (Modified from Van Daele et al., 2016).

The west-east temperature gradient is less pronounced than the precipitation gradient. Eastern Patagonia has an annual mean temperature around 5 °C and an austral winter-to-summer temperature amplitude of around 10 °C (Garreaud et al., 2013). The Coyhaique region has an annual mean temperature of 6.5 °C and a seasonal difference of around 8 °C for the period 1994-2010 (Figure 3). The region experiences a unimodal seasonal distribution of precipitation in which the highest precipitation occurs during austral late autumn and winter.

Figure 3. Present-day climatology of Coyhaique alto: monthly precipitation (blue bars, 1985-2010) and monthly temperature (1994-2010): average (orange line) and min-max range (ochre shading). (Source data: Chilean DGA, http://www.dga.cl)

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3. MATERIAL AND METHODS

3.1 Previous research 3.1.1 Core acquisition, logging and XRF scanning In 2011, a 15.4 m long composite sediment core, CAST01, was retrieved from the eastern part of the main, i.e. northeastern, subbasin of Lago Castor using a UWITEC piston coring system (Van Daele et al., 2016). The bottom of the sediment core (15.41–13.04 m) consists of layered clastic and grey clays. From 13.04–7.75 m, the sediment is composed of laminated clastic and clayey grey sediments. The top of the core (upper 7.75 m) consists of laminated organic- and diatom-rich green-brown sediments. The core contains 54 tephra layers especially present in the upper ~9 m and 3 turbidites (Van Daele et al., 2016). Additionally, short cores and several surface sediment samples were collected across the lake. Soil, and vegetation samples were collected at various locations in the lake catchment. Four river sediment samples were collected from the lake inflows. In addition, water samples from the lake and from the inflowing were collected and afterwards filtered. The bathymetry of Lago Castor and the locations of the composite sediment core and the soil samples used in this dissertation are displayed in Figure 4.

Figure 4. Bathymetry map of Lago Castor with locations of composite core (CAST01), short core (CAS-09; Elbert et al., 2013) and soil samples (SS) (modified from Van Daele et al., 2016).

Prior to this study, the composite sediment core was scanned on a Geotek multi-sensor core logger to measure gamma-ray bulk sediment density. After opening and description, photographs were taken. In order to construct the composite sequence, lithology, colour and magnetic susceptibility were

9 Chapter 3 – Material and methods combined to correlate overlapping core sections (Van Daele et al., 2016). The composite core was then sub-sampled in 1 cm-thick slices. This thesis makes use of one such samples every ~10 to 20 cm. During sample selection, tephra layers were avoided and the same samples were used for the sedimentological analysis, bulk organic geochemistry, pigment analysis, diatom analysis and eventually the biogenic silica analysis.

Scanning XRF was performed at the Royal Netherlands Institute for Sea Research (NIOZ) in Texel, using an Avaatech core scanner (Willem Vandoorne, unpublished data). The split cores were analysed in two runs with two different voltages. Using 30 kV voltage allows measurement of Fe, Zn, Cu, Br, Rb, Sr, Zr and Pb while with 10 kV voltage Al, Si, S, Cl, K, Ca, Ti, Cr and Mn can be measured. The split cores were analysed at a 5 mm resolution, with a measuring time of 10 s per interval.

3.1.2 Chronology The core chronology is based on 20 radiocarbon ages including 7 on terrestrial macroremains and 13 on bulk organic matter (Van Daele et al., 2016). To estimate the age offset of the bulk organic matter samples, all macroremains were paired with these samples. The radiocarbon ages were measured with Accelerator Mass Spectrometry (AMS) at NOSAMS (MA, USA) and are calibrated using the calibration curve for the Southern Hemisphere (SHCal13; Hogg et al., 2013). The final age model was constructed with the CLAM 2.2 software (Blaauw, 2010). The two thickest tephras in the composite core represent known well-dated explosive eruptions of Hudson volcano around ~18 cal kyr BP (Ho; Weller et al., 2014; Stern et al., 2015) and ~4 cal kyr BP (H2; Naranjo et al., 1998) and these events confirm the age model (Figure 5; Van Daele et al., 2016).

Figure 5. The age-depth model is based on 20 radiocarbon ages and takes into consideration the instantaneous deposition of 54 tephra layers (grey rectangles, purple (Ho) and orange (H2) rectangle) and 3 turbidites (brown rectangles). The resulting ages of Ho and H2 are projected on the age axis and are in agreement with the published ages for these tephra layers (grey rectangles) (Modified from Van Daele et al., 2016).

10 Chapter 3 – Material and methods

3.1.3 Sedimentology Grain size analysis of the terrigenous fraction was performed on a Malvern Mastersizer 3000 by Van

Daele et al. (2016). The terrigenous fraction was isolated by treating the samples with boiling H2O2, HCl and NaOH in order to remove organic matter, carbonates and biogenic silica, respectively. In addition, organic matter and carbonate contents were estimated using loss-on-ignition (LOI) at 550°C and 950°C, respectively.

3.1.4 Bulk organic geochemistry Bulk organic geochemistry analyses were performed by Granon (2015) in order to determine the carbon and nitrogen content and the stable isotopic composition of the composite sediment core, river sediments and water samples of the rivers and lake (Figure 6). Carbon and nitrogen weight percentages were determined simultaneously with an elemental analyser. C/N weight ratios were multiplied by 1.167 to derive the atomic C/N values because the latter reflect the biochemical stoichiometry (Meyers and Teranes, 2001). Subsequently these C/N ratios were used to estimate the fractions of terrestrial and aquatic organic carbon. Eventually, relative changes in the sources of sedimentary organic carbon and their contribution through time were estimated.

Figure 6. Bulk organic geochemical results of Granon (2015): C/N versus δ13C biplots of the core samples, river sediment samples and suspended particulate matter (SPM) of river and lake samples. The core samples are divided into three classes: the samples deposited before 11.7 cal kyr BP (i.e. Holocene samples), between 11.7–17.8 cal kyr BP and after 17.8 cal kyr BP. The representative C/N atomic ratio and carbon (δ13C) isotopic compositions of the three major groups of sedimentary organic matter (lacustrine algae, C3 and C4 land plants) are indicated in the coloured boxes. (C/N)Redfield represents the C/N atomic ratio derived from the Redfield ratio.

The C/N values of bulk sedimentary organic matter reflect the original proportions of aquatic and terrestrial material. C/N values of lacustrine algae lie between 4 and 10, whereas terrestrial plants produce organic matter that has C/N values of 20 and higher (Figure 6; Meyers and Teranes, 2001).

The fraction of terrestrial organic carbon (fT) can be estimated using the C/N values of the aquatic and terrestrial end-members in a mixing equation (Bertrand et al., 2010). Perdue and Koprivnjak (2007)

11 Chapter 3 – Material and methods demonstrated that mixing equations based on C/N data are always overestimating the terrestrial fraction of organic carbon because of the non-linearity of the C/N mixing lines. Therefore, N/C values are used in a simple linear mixing model: 푁 푁 푁 = 푓푇 ( ) + 푓퐴 ( ) 퐶 퐶 푇 퐶 퐴 where (N/C)T and (N/C)A stand for the terrestrial and aquatic N/C ratio, respectively. If we assume that the sum of the fractions of terrestrial and aquatic organic carbon equals 100% (fT + fA = 1), we can rewrite the former formula to calculate the terrestrial fraction:

(푁⁄퐶) − (푁⁄퐶)퐴 푓푇 = (푁⁄퐶)푇 − (푁⁄퐶)퐴 River sediment samples best represent the terrestrial end-member. Therefore a value of 0.0529

(Granon, 2015) was used for (N/C)T. The N/C ratio derived from the Redfield ratio, i.e. the atomic ratio of carbon, nitrogen and phosphorus found in plankton, is used for the aquatic end-member, namely

(N/C)A = 0.1509 (pink dot; Figure 6). Subsequently the terrestrial and aquatic fraction of the total organic carbon were calculated to ultimately estimate changes in the accumulation rates of terrestrial and aquatic organic carbon through time.

The carbon (δ13C) isotopic composition of organic matter can be used to estimate the content of 13 terrestrial and aquatic sources (Meyers and Teranes, 2001). For example, C3 plants have δ C values that range from -25‰ to -30‰, while C4 plants fall broadly within the range of -10‰ tot -15‰ (Figure 6; Meyers and Teranes, 2001). However, a precise quantification of the terrestrial and aquatic end- member is difficult because often the difference in δ13C is too small (Bertrand et al., 2010). The carbon isotopic composition of lake plankton is virtually the same as that of C3 plants. It is however also affected by lake productivity. Therefore it is more commonly used in the reconstruction of past lake productivity and changes in the availability of nutrients in surface waters (Meyers and Teranes, 2001). Phytoplankton consumes 12C and consequently 12C is removed from the surface water resulting in an enrichment in 13C. Therefore, an increase or decrease in δ13C of organic matter produced in the lake indicates a respective increased or decreased productivity.

3.1.5 Pigment analysis The pigments in Lago Castor were investigated by De Raeve (2015) using high-performance liquid chromatography (HPLC) and processed with CONISS cluster analysis. Different zones based on these pigments could be distinguished which were related with important climatic episodes (such as the Last Glacial Maximum, the Antarctic Cold Reversal, the Younger Dryas, the Holocene). The pigments diadinoxanthin (Diadino), diatoxanthin (Diato), fucoxanthin (Fuco) and fucoxanthin-like (Fuco-like) pigments are produced by diatoms, which are the main producers of biogenic silica. Therefore, the concentrations of these pigments will be compared with my results.

3.1.6 Diatom quantification and paleoecology The diatom analysis performed on the Lago Castor record by Van Goethem (2015) included sample and slide preparation, determination of the different diatoms species and a quantitative examination of all diatom taxa with corresponding calculated absolute abundances. The data was processed with CONISS and R cluster analysis. Additionally, the characteristics and ecology of the different diatom taxa was described.

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3.2 Biogenic silica analysis 3.2.1 Introduction By measuring the biogenic silica content of sediments, the siliceous microfossil abundance can be chemically estimated (Conley and Schelske, 2001). These siliceous microfossils are particularly diatoms and to a lesser extent radiolarians and sponge spicules. Their abundance is commonly used as a paleolimnological proxy for studying environmental change on a regional scale. Therefore, biogenic silica concentrations measured in lake sediments are often used as a proxy for diatom abundance and past diatom productivity, with the assumption that biogenic silica mostly originates from diatoms. Several techniques to estimate the biogenic silica content of sediments exist (Table 1).

Table 1. Techniques to estimate the biogenic silica content of sediments with important pioneering references. Techniques References - X-ray diffraction Goldberg (1958) - Point counting of diatoms Pudsey (1993) - Infrared analysis of sediments Fröhlich (1989) - Normative calculation technique Leinen (1977); Bertrand et al. (2005) - Alkaline extraction technique Mortlock and Froelich (1989); Bertrand et al. (2012); Bertrand et al. (2014b)

Point counting of diatoms was already done by Van Goethem (2015). In this thesis, biogenic silica concentrations will be measured using the alkaline extraction technique, and estimated at high resolution using a variant of the normative calculation approach.

3.2.2 Alkaline extraction technique

3.2.2.1 Extraction In this dissertation, biogenic silica concentration was measured using the alkaline extraction technique because it is the most precise technique. This technique corresponds to the procedure used in Bertrand et al. (2012) which was modified from Mortlock and Froelich (1989) and Carter and Colman (1994).

Prior to the analysis, all centrifuge tubes were washed with nitric acid (HNO3) in order to avoid leaching of elements from the centrifuge tubes. First, 50 mg of precisely weighed freeze-dried sediment was placed in 50 ml centrifuge tubes. Organic matter and carbonates were removed by adding 10% H2O2 and 1N HCl, respectively. When the reactions were finished, 20 ml of Milli-Q water was added in each centrifuge tube and the samples were centrifuged. After decanting, the solids were dried under an IR- lamp during a few days.

The next step in the procedure included the addition of a strong base (30 ml of 0.2N NaOH) to dissolve the biogenic silica. The centrifuge tubes were agitated with a vortex mixer and sonicated during 5 minutes, this procedure was repeated three times in order to fully disaggregate the sediment samples. Subsequently, the samples were placed in a heated bath at 92°C and agitated using a vortex mixer after 2 and 4 hours. After 5 hours, the samples were agitated one last time and centrifuged. Then 5 ml was pipetted to new acid-washed centrifuge tubes containing 35 ml 5% HNO3. The centrifuge tubes were sealed with Parafilm and refrigerated until analysis. Finally, the samples were analysed for Si and Al by ICP-AES. The measurement of Al content is necessary in order to correct the Si values for the lithogenic silica contribution.

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3.2.2.2 Lithogenic correction Beside biogenic silica, lake sediments also contain siliceous minerals which can also dissolve during the alkaline extraction. Dissolution of volcanic glass (Clymans et al., 2014) and clay minerals (Koning et al., 2002) affect the alkaline extraction the most. Figure 7 demonstrates a hypothetic case of the alkaline extraction process when for example diatoms and minerals are present. The diatoms dissolve rapidly, in less than 2 hours in this case, and any posterior increase in extracted Si is due to the dissolution of siliceous minerals. This results in an over-estimation of the biogenic silica content. Therefore a correction for lithogenic silica (Ohlendorf and Sturm, 2008) was performed on the measured silica concentrations: 푆푖 퐵푆푖 = 푆푖푡표푡 − 퐴푙 × ( ⁄퐴푙)푙𝑖푡ℎ표 This correction is based on the analysis of Al, which assumes that all extracted Al originates from the dissolution of siliceous minerals. The Si/Allitho ratio used for correction was measured on the soil samples prepared using the same technique. The soil samples were used because they constitute the dominant source of detrital particles that reaches the lake.

Figure 7. Schematic illustration of silica released from minerals and diatoms during the alkaline extraction process (Modified from Conley and Schelske, 2001).

3.2.2.3 ICP-AES

Inductively coupled plasma atomic emission spectrometry (ICP-AES) is a widely used analytical technique for elemental analysis (Gill, 1997). The ICP-AES has three essential components: the source unit with the ICP plasma torch, the spectrometer, and the computer. A total of 136 samples including 124 composite core samples, 4 replicate samples and 8 soil samples were measured with a Varian 720-

ES ICP-AES. An aliquot of the solution of each sample containing 35 ml HNO3 and 5 ml NaOH was introduced into the plasma as an aerosol suspended in argon gas. In the spectrometer, the emitted light from the elements present in the plasma was separated into its different wavelengths. The intensity of emitted light at each wavelength was measured with charge coupled devices (CCDs) and is indicative of the concentration of the element within the sample. The comparison with standard samples with known concentrations of the elements allows element concentrations to be calculated.

The concentrations of Al and Si were measured in ppm at different wavelengths. The different wavelengths that were used for Al are 236.705, 237.312, 257.509, 308.215, 309.271, 394.401 and 396.152 nm and for Si 185.005, 212.412, 250.690, 251.611, 252.851 and 288.158 nm. Eventually the average value over this range of wavelengths was used for further calculations. Afterwards, the measured concentrations were corrected for instrument drift using the concentrations of lab control

14 Chapter 3 – Material and methods samples measured in-between every unknown sample. Subsequently, the concentrations were corrected for dilution. The exact dilution factor was calculated from the precise weight of sediment used for the alkaline extraction.

In order to obtain the biogenic opal content (SiO2.nH2O, wt. %), the biogenic silica concentrations were multiplied by 2.4 (Mortlock and Froelich, 1989). This factor was used because opal consist of ~40 % Si. Negative opal concentrations (e.g. between ~7.7 and 9 m) were set to zero. Eventually, the biogenic silica flux can be calculated by multiplying the biogenic silica concentrations with the dry bulk sediment mass accumulation rate (g/m2/yr).

3.2.2.4 Smear slides In order to check if the dissolution of biogenic silica was effectively completed, smear slides of the samples were made after dissolution of biogenic silica. They were compared with smear slides of the untreated sediment samples made by Willem Vandoorne. Smear slides were analysed with a Zeiss Imager A1 microscope accompanied with an Olympus camera and Axiovision 4.8 software program.

3.2.3 Scanning XRF The use of X-ray fluorescence measurements of Si, Ti and Al to estimate biogenic silica concentrations of lake sediments has already been demonstrated by several authors (e.g. Brown, 2015). Because Si can be present in both clastic and biogenic phases, and Al and Ti only occur in the clastic fraction of the sediment, the Si/Al and Si/Ti ratios generally reflect biogenic silica concentrations. However, the selection of an appropriate element (Al or Ti) for clastic sediments depends upon the particular depositional environment. Here, we revisited the XRF measurements made by Vandoorne and compared Si/Al and Si/Ti against our biogenic silica measurements obtained after alkaline extraction.

The advantage of using Si/Ti instead of Si/Al is that Ti can be more precisely measured by XRF than Al, due to its higher atomic weight (Tjallingii et al., 2007). However, a potential problem can arise using Ti elemental counts because its concentration often varies with grain size (Cuven et al., 2010) while Al is less dependent on grain-size. In order to validate the correlation between the ratios Si/Al and Si/Ti with biogenic silica concentrations, Pearson correlation coefficients were calculated with XLSTAT.

Prior to using the XRF data to estimate biogenic silica concentrations, the data associated with the deposition of tephra layers and turbidites were removed from the raw XRF data because they correspond to event deposits that interrupt the continuous paleoenvironmental record. To clean the dataset, the visual description of the tephra layers and turbidites and the Fe, Ti and Zr content, which are often used as indicator for tephra layers (Croudace and Rothwell, 2015), were combined. Since the XRF data of the upper 36 cm of the composite core were missing, the XRF data of short core CAST1A SC02 were merged with the long core dataset. In the discussion section, the focus will be placed on the upper ~8 m of the core, i.e. the last 17.2 kyr, were biogenic silica concentrations are significantly above zero.

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4. RESULTS

4.1 Biogenic silica analysis: alkaline extraction technique

4.1.1 Lithogenic correction factor The measured Si concentrations are corrected for lithogenic Si using the measured Al concentrations. Two different correction factors are used in this dissertation, one for the part 15.29 to 8.56 m (corresponding to samples 82 to 124) and one for the upper 8.56 m (corresponding to the first 81 samples). The boundary at 8.56 m depth corresponds to the top of Ho, i.e. the tephra deposit of the first large postglacial eruption of the Hudson volcano (Figure 5). After the Ho eruption, volcanic activity in the region became more frequent and volcanic ash soils developed (Vandekerkhove et al., 2016).

Therefore, a correction factor Si/Allitho of 6.2 was applied for the post-Ho eruption samples as determined by the values measured after alkaline dissolution of the volcanic ash soil samples. The pre- Ho eruption samples consist of proglacial sediments clearly distinct from the post-Ho sediments. For these samples, the correction factor was determined from the ICP-data obtained after alkaline extraction of the sediments between the Ho tephra and the deformed sediments which formed during the desiccation of the lake (9.19–12.29 m). For that part of the core, a correction factor Si/Allitho of 3.7 was calculated and applied.

4.1.2 Downcore results Eventually, biogenic silica concentrations are calculated (Figure 8; Appendix). The bottom of the core (15.29–7.75 m) shows very low (~0.1 wt. %) biogenic silica concentrations. This part of the core corresponds to proglacial sediments (laminated and layered clastic and clayey grey sediments, see lithology Figure 8). From 7.75 to 0 m, values oscillate between 0 and 31.8 wt. %. From 7.75 until 5.39 m, an increasing trend, interrupted by low values at 6.84–6.67m can be observed. Between 5.39–1.57 m, values are generally high (20.50±6.17 wt. %), except for an interval with low values right after the H2 tephra deposit (2.05–1.96 m). Then, values decrease and moderate values (14.73±5.45 wt. %) are present in the upper part of the core (1.57–0 m). Minor decreases in biogenic silica concentrations are observed in the vicinity of tephra layers, mostly above these. Because biogenic silica values are only significant in the upper ~8 m, corresponding to the last ~17.2 kyr, only this part of the core will be considered in the discussion.

4.2 Scanning XRF

The ratios Si/Al and Si/Ti compared with the biogenic silica concentrations are shown in Figure 8. The Si/Al ratio in the bottom of the core (below ~8 m) is very low just like the biogenic silica curve in that part. From ~8 m until the top of the core, Si/Al ratios are fluctuating in accordance with the biogenic silica curve. The Si/Ti ratio in the bottom of the core does not resemble the biogenic silica curve due variations in grain size and density (see Van Daele et al., 2016) that significantly affect the XRF Ti counts. The upper ~8 m of the Si/Ti curve again fluctuates more or less in accordance with the biogenic silica curve.

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Figure 8. Lithology of sediment core CAST01 (modified from Van Daele et al., 2016), downcore biogenic silica concentrations (in weight %, the error bar equals the size of the dot) obtained by the alkaline extraction method and scanning XRF Si/Al and Si/Ti ratios with a running average (window width: 15 points) in red and green, respectively. The XRF Si/Al and Si/Ti of short core CAST1A SCO2 (upper 42 cm) are presented in pink and light green, respectively. The dashed lines in the XRF curves represent Ho and H2, i.e. the two thickest tephra layers associated to large eruptions of the Hudson volcano (Naranjo et al., 1998; Weller et al., 2014; Stern et al., 2015).

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4.3 Sediment composition

4.3.1 Components

No carbonates were present in the sediment core based on the LOI950 measurements (performed by Willem Vandoorne) and therefore the components of the sediment are organic matter, biogenic opal and terrigenous particles. The downcore variations in these three components are shown together with the lithology in Figure 9. Results show that the bottom of the core (15.41–7.75 m) is mostly entirely composed of detrital particles (99.15±0.51 wt. %). Above 7.75 m, biogenic opal and organic matter concentrations increase (41.28±16.75 wt. % and 11.49±5.87 wt. %, respectively) and the amount of detrital particles decreases to 47.23±20.39 wt. %. These changes in sediment composition are reflected in the colour of the sediment (Figure 9). Variations in organic matter content roughly follow the same trend as changes in biogenic opal concentrations.

Figure 9. Lithology (modified from Van Daele et al., 2016) and downcore variations of the different sediment components.

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4.3.2 Smear slides Smear slides of bulk sediment samples from the composite core prior to any treatments indicate that below ~9 m, the sediment is dominated by angular and poorly sorted grains of different sizes. Towards the top of this unit (around 9.29 m), low amounts of diatoms were observed. From 7.75 m (sample 71) onwards, the amount of diatoms starts to increase significantly. The most common taxa in the smear slides are Aulacoseira granulata, Discostella stelligera and Staurosirella (Figure 10). The amount of diatoms observed in the smear slides is consistent with the measured biogenic silica concentrations, except for the interval 8.36–7.68 m (samples 70 until 76; see discussion section 5.1). In this interval, a quite high abundance of diatoms is observed while the results from the biogenic silica analysis indicate very low biogenic silica concentrations (0–4.7 wt. %). The samples after the Ho tephra, i.e. from 8.93 m (sample 84) onwards, all contain volcanic glass.

Figure 10. Selected microscopic pictures showing common diatom species in the sediment core: (a) Aulacoseira granulata (156.5 cm); (b) Discostella stelligera (156.5 cm); (c) Staurosirella species (683.5 cm); (d) Fragilaria species (776.5 cm); (e) Diploneis species (776.5 cm); (f) Cymbella species (156.5 cm). (Pictures taken by Géraldine Fiers)

20 Chapter 4 – Results

After the alkaline extraction, smear slides of the treated sediment samples were made. Generally, no diatoms are present in these smear slides, so we can conclude that the biogenic silica treatment was successful. A comparison of the smear slides at 3.59, 5.86 and 13.10 m depth before and after the alkaline treatment is shown in Figure 11. Volcanic glass parts are found in some smear slides demonstrating that the alkaline treatment was efficient at dissolving diatoms without being too aggressive toward volcanic glass (Figure 12a). The smear slide at 7.57 m (sample 69) contains one diatom species embedded in a mineral grain and in this way it was probably protected from the alkaline treatment. Still it is clear that the treatment was efficient at dissolving diatoms in general (Figure 12b).

Figure 11. Comparison of smear slides before (left) and after (right) alkaline extraction. Smear slides at 3.59 and 5.86 m depth have a high abundance of diatoms in accordance with the results of the alkaline extraction technique. The smear slide before alkaline extraction at 13.10 m depth, located in the lowest part of the core, does not contain any diatoms but a significant amount of mineral grains. (Pictures taken by Géraldine Fiers)

21 Chapter 4 – Results

Figure 12. Pictures of the smear slides after alkaline treatment: (a) at 7.77 m depth showing the presence of volcanic glass; (b) at 7.57 m depth showing a diatom frustule not totally dissolved during the alkaline treatment. (Pictures taken by Géraldine Fiers)

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5. DISCUSSION

5.1 Biogenic silica

5.1.1 Comparison of the different biogenic silica proxies The different biogenic silica proxies were statistically compared with the biogenic silica content measured using the alkaline extraction technique using XLSTAT (Table 2). Both XRF elemental ratios, Si/Al and Si/Ti, are significantly positively correlated to the measured biogenic silica concentrations, but the Si/Al ratio (r=0.742; p<0.001) has a higher correlation coefficient than the Si/Ti ratio (r=0.525; p<0.001). Additionally, a biplot in which the XRF elemental Si/Al ratio is compared with the biogenic silica concentrations was made to demonstrate the correlation (Figure 13). The absolute abundance of diatoms obtained by diatom counting is also significantly correlated with the biogenic silica content (r=0.475; p<0.001). Of the diatom-derived pigments, only fucoxanthin is significantly correlated with biogenic silica concentrations (r=0.419; p<0.001) and this pigment is even better correlated than the total amount of diatom-derived pigments.

Table 2. Pearson’s correlation coefficients between biogenic silica concentrations and the different biogenic silica proxies. From left to right: scanning XRF elemental ratios Si/Al and Si/Ti (cps), absolute abundance (x10³ diatoms/g dry wt.) obtained by diatom counts and the concentration (µg/mg) of diatom-derived pigments: diadinoxanthin (Diadino), diatoxanthin (Diato), fucoxanthin (Fuco), fucoxanthin-like (Fuco-like), abbreviations according to SCOR (Scientific Committee on Oceanic Research; Jeffrey et al., 1997). Values in bold are different from 0 with a significance level alpha = 0.001.

XRF ratio Absolute Diatom-derived pigments Variables Si/Al Si/Ti abundance Diadino Diato Fuco Fuco-like Total Biogenic silica 0.742 0.525 0.475 0.363 0.311 0.419 0.277 0.323 (wt. %)

Figure 13. Biplot of the XRF elemental ratio Si/Al (XRF cps) with biogenic silica concentrations (wt. %). The Pearson’s correlation coefficient (r) is 0.742 with a level of significance (p) less than 0.001. The black line represents the linear fit. In order to match the biogenic silica concentrations to the corresponding Si/Al values at certain depth, an average of 3 XRF measurements (corresponding to the 1-cm thick sample used for alkaline extraction analysis) was calculated.

23 Chapter 5 – Discussion

Because the XRF Si/Al ratio has the highest correlation coefficient of all biogenic silica proxies, only this proxy together with my biogenic silica results obtained by the alkaline extraction technique will be considered in further interpretations. Because of this high and significantly positive correlation, the higher resolution Si/Al ratio can also be used to estimate biogenic silica concentrations. The higher correlation coefficient between Si/Al and biogenic silica than between Ti/Al and biogenic silica can be explained by the fact that Si and Al, both light elements, are similarly influenced by the water film that is created under the plastic film at the surface of the core during XRF scanning. The heavier element Ti is less influenced by this water film because of the relatively deeper critical depth as a result of the stronger fluorescence energy emitted by heavier elements (Tjallingii et al., 2007). In addition, Al is known to represent the total lithogenic fraction better than Ti, which strongly varies with grain size (Bertrand et al., 2012). Although XRF scanning is less precise in determining biogenic silica than alkaline extraction, the advantage is that this technique is non-destructive, rapid and can be performed at high resolution (5 mm or lower). In this way, scanning XRF offers an alternative to laborious wet chemical techniques (Brown, 2015).

The several proxies for biogenic silica content versus composite depth are shown in Figure 14. It is clear that from 7.75 m onwards the biogenic silica content starts to increase in every proxy. A very clear correlation can be observed between the curves of the biogenic silica content and the Si/Al ratio, which illustrates the high correlation coefficient (r=0.742; p<0.001; Table 2) between the two variables. The trends in biogenic silica content are also reflected in the absolute diatom abundance and fucoxanthin concentration curves. The major peaks in the fucoxanthin concentration (e.g. at 7.57, 4.21 and 1.67 m) correspond to peaks or sudden increases in the biogenic silica content. Preservation issues for pigments, i.e. degradation through time, can explain the decreasing intensity of the peaks downcore.

5.1.2 Comments on the calculation of the lithogenic correction factor The biogenic silica values displayed above were calculated using a lithogenic correction factor of 6.2 above 8.56 m and of 3.7 below. This depth corresponds to 18 kyr BP, which represents the beginning of development of volcanic soils after the first postglacial eruption of Hudson volcano (Ho). Because volcanic ash stabilization in soils takes some time, the sources of sediment were very likely a mixture of glacial sediments and volcanic ash soils between 18 and the beginning of the Holocene, i.e. 11.7 cal kyr BP. Therefore, it may have been more judicious to use a transitional lithogenic correction factor in this period instead of an abrupt transition around 18 cal kyr BP. To test the impact of such a transitional lithogenic correction factor on the calculated biogenic silica concentrations, biogenic silica was recalculated using a correction factor transitioning from 3.7 to 6.2 between 18 and 11.7 cal kyr BP (Appendix; Figure 14). After 11.7 cal kyr BP, i.e. the onset of the Holocene, volcanic ash soils were well- developed and stable (Vandekerkhove et al., 2016) which justifies the use of a constant lithogenic correction factor (Si/Allitho = 6.2) for the Holocene samples.

Applying such a transitional correction factor results in a small but rather clear difference in the depth interval 8.56–5.56 m (Figure 14). The values calculated with the transitional correction factor are slightly higher than the biogenic silica values calculated using a constant correction factor of 6.2. Although this can partly explain the differences between the high amount of diatoms observed in the smear slides and the actual calculated biogenic silica concentrations, which were near zero in the interval 7.68–8.36 m, this different correction factor alone is not enough to fully explain these differences (see section 5.1.3).

24 Chapter 5 – Discussion

Figure 14. Comparison of the several biogenic silica proxies. From left to right: biogenic silica (wt. %), running average Si/Al ratio (window width: 15 points; XRF cps), absolute abundance of diatoms (x10³ diatoms/g dry wt.; Van Goethem, 2015) and the concentration of the pigment fucoxanthin (µg/mg; De Raeve, 2015). The light blue biogenic silica curve at 9.86–5.56 m represents biogenic silica concentrations calculated with the transitional correction factor. Only the upper 10 m is shown because there is no data for absolute abundance of diatoms and fucoxanthin concentration below 8.51 and 9.86 m respectively, and the values for biogenic silica are not significantly different from 0 below 10 m. No diatom and pigment analysis was done in the short core, i.e. the upper 0.42 m. 25 Chapter 5 – Discussion

From this test, we can conclude that it is important to subtract the lithogenic silica contribution when determining biogenic silica in paleoclimatological studies, which was not performed in routine before ~2005 and is still not in application in all laboratories. Moreover, our results show that it is crucial to use a lithogenic correction factor that faithfully represents Si/Al extracted from the dominant sediment source. This is clearly different than using the bulk Si/Al ratio of the sediment sources, which is frequently done in the literature (e.g. Elbert et al., 2013).

5.1.3 Absolute diatom abundance versus diatom biovolume When comparing the abundance of diatoms in the smear slides with the measured biogenic silica concentrations, one interval (7.68–8.36 m) did not match. The smear slides show a high diatom abundance while the biogenic silica analysis indicates very low biogenic silica concentrations in this interval. However, the absolute abundance of diatoms calculated by Van Goethem also seems to indicate a low amount of diatoms in this interval (Figure 14). This problem can be explained as follows.

Diatoms vary considerably in size and shape. Therefore, diatom concentrations (e.g. obtained by diatom point counting of Van Goethem) may significantly differ from biogenic silica concentrations (Battarbee et al., 2001). The diatom biovolume of Aulacoseira granulata, the most abundant species in the Holocene samples, is relatively large and therefore this species is more likely to drive total diatom productivity than other species with a smaller biovolume (Sterken et al., 2008). The abundance of diatoms with much smaller biovolumes at 7.68–8.36 m (Fragilaria, Staurosirella and some benthic species; Figure 26 of Van Goethem, 2015) explains why low biogenic silica concentration were measured even when a relatively high amount of diatoms was present in the smear slides.

We can conclude that the absolute abundance of diatoms and the actual measured biogenic silica concentration cannot be interpreted the same way. One way to confirm the biogenic silica measurements obtained by the alkaline extraction method is to calculate the diatom biovolume for each species and then quantify the biogenic silica from the diatom counts. This however requires measuring the size of each dominant species several times, which is time consuming and relatively imprecise. In addition, as clearly mentioned by Battarbee et al. (2001), it is the diatom biovolume (i.e. biogenic silica concentrations) that matter in paleoproductivity studies, not diatom counts.

26 Chapter 5 – Discussion

5.2 Variations in sediment composition

The core lithology shows a drastic change in sediment colour at 7.75 m (Figure 15). This colour change represents abrupt changes in sediment composition from organic-poor proglacial sediments below 7.75 m to organic-and diatom-rich sediments above 7.75 m. According to Van Daele et al. (2016), this change in sediment composition corresponds to a period when the lake level reached its present-day position around 16.8 cal kyr BP. From 7.75 m onward, opal concentrations and TOC (see aquatic and terrestrial organic carbon; Figure 15) start increasing indicating the onset of biological productivity in the lake and the development of the vegetation in its catchment.

Figure 15. Bulk sediment composition versus composite core depth: lithology (modified from Van Daele et al., 2016), aquatic and terrestrial organic carbon (geochemical data from Granon, 2015), opal concentrations and the detrital fraction. Grey and green lines indicate tephra layers and turbidites, respectively. The aquatic (light green) and terrestrial (dark green) organic carbon compose the total organic carbon (TOC).

Algal growth can be restricted by several climatic and environmental parameters (Reynolds, 1984). Since the major increase at 7.75 m occurs shortly after the Last Glacial Maximum (LGM), it was likely triggered by a warming pulse. This will be discussed in section 5.4. The increase in aquatic organic carbon represents an increase in aquatic productivity, particularly diatoms, as seen in the good correlation between opal and aquatic organic carbon concentrations (r=0.706; p<0.001). To demonstrate this correlation, a biplot in which the aquatic organic carbon is compared with the

27 Chapter 5 – Discussion biogenic silica (opal) concentrations was made (Figure 16). The terrestrial fraction of TOC, on the other hand, is likely linked to the development of vegetation in the lake watershed (see section 5.3).

Figure 16. Biplot of aquatic organic carbon (aqOC) with biogenic silica concentrations (wt. %). The Pearson’s correlation coefficient (r) is 0.706 with a level of significance (p) less than 0.001. The black line represents the linear fit.

Generally, the opal and TOC curves seem to show coeval short-term changes (Figure 15). Since the Castor sediment record is rich in tephra layers, the influence of these layers on the biogenic proxies needs to be evaluated prior to interpreting these proxies in terms of climate and environmental change. From Figure 15, it is clear that both opal and TOC concentrations rise gradually between 7.75 and 4.68 m. This rise is however interrupted around 6.68 m likely due to the presence of several tephra layers located between 6.83-6.67 m (cf. the increase in the detrital fraction), diluting the biogenic particles. The same process, although less pronounced, probably also applies to the low TOC and opal values at 5.31 and 4.84 m depth, which are also near tephra layers.

Between 4.68 and 1.57 m, opal concentrations are high and relatively stable, while TOC continues to rise gradually to maximum values around 2.58 m, mainly due to an increase in organic carbon of terrestrial origin. Several low peaks in TOC and opal, mostly corresponding with tephra layers, occur throughout this interval. Again, the input of volcanic material into the lake after volcanic eruptions dilutes the opal and TOC components. The end of this interval is characterized by a rapid decrease in opal and TOC concentrations right after the thick H2 tephra deposit (2.28-2.09 m) followed by a sudden increase of both components to values practically never observed before. A possible explanation for this sudden increase could be that after H2 eruption, a lot of nutrients gets into the lake and with no eruptions happening in the following 1200 years (0.55 m), diatoms and other aquatic organisms had time to develop and reach greater abundances. Above 1.57 m, concentrations remain stable with moderate values until the top of the core. A remarkable trend can be observed in the TOC values from ~4 m onwards. The aquatic organic carbon starts to decrease and remains low until the top of the core with punctual increases coeval with opal peaks. On the other hand, the terrestrial organic carbon starts to increase at this depth and seems to become the major contributor to the TOC until the top of the core. This could indicate the growing importance of vegetation development in the lake watershed and associated run-off into the lake probably due to a period with increased precipitation (see section 5.4).

28 Chapter 5 – Discussion

From the two paragraphs above, it seems that punctual decreases in opal concentrations and TOC are more or less related to the presence of tephra layers, even though samples were collected above or below tephra layers. The punctual decreases in TOC and opal are mostly located above the tephra layers. This indicates a strong influence of volcanic activity on the sediments that were deposited in the lake. The low opal and TOC concentrations close to the tephra layers can be due to either a decrease in diatom productivity caused by volcanic eruption (i.e. volcanic material gets into the lake and blocks light penetration), or to extra dilution by tephra material (i.e. reworking of tephra deposited in the lake watershed). Both processes are known from the literature (e.g. Cruces et al., 2006; Bertrand et al., 2014a) and both likely affect the Castor sediment record. In further discussion, no focus will be given on these low opal and TOC values since they are affected by tephra deposition. Additionally, accumulation rates of opal and aquatic organic carbon will be used because they best reflect productivity rates (see section 5.4). The accumulation rates of terrestrial organic carbon will be interpreted as vegetation density and river runoff (see section 5.3).

29 Chapter 5 – Discussion

5.3 Postglacial wind and precipitation variability

Van Daele et al. (2016) used the sediment record of Lago Castor to discuss postglacial changes in westerly wind speed in northern Patagonia. Their interpretation was based on two proxies that are independent of the relation between wind speed and precipitation: grain size (modified sortable silt index) and sediment drifts. The modified sortable silt index (SS’), an adaptation of the sortable silt index for volcanic ash-rich sediments, was used to estimate wind-driven bottom-current intensities. The drift-intensity parameter provided an indication of the degree to which the sediments are mounded. Their results showed an intensification of the westerly winds during the early and mid Holocene, supporting the hypothesis of Lamy et al. (2010) that the southern westerly wind belt broadened during this period, followed by a stabilization and slight weakening of the westerly winds during the late Holocene. Here, we compare additional proxies for wind and precipitation to those analysed by Van Daele et al. (2016).

The accumulation rate of terrestrial organic carbon in lake sediments generally reflects the abundance of vegetation in the lake watershed and the amount of precipitation and associated terrestrial run-off (Sifeddine et al., 2004). The accumulation rate of terrestrial organic carbon can therefore be used as a proxy for precipitation. In Lago Castor, the accumulation rate of terrestrial organic carbon (Figure 17b) seems to be in good agreement with the previously mentioned wind proxies of Van Daele et al. (2016) and with the precipitation-driven Nothofagus pollen record of Mallín Pollux near Lago Castor (Markgraf et al., 2007; Figure 17).

According to Figure 15, most of the organic carbon in the sediments of Lago Castor is of terrestrial origin (78.43±28.59 %). Therefore, the bulk organic δ13C signal mostly reflects changes in the type of vegetation in the lake watershed and it is likely not much affected by aquatic productivity. From Figure 17, it is clear that the δ13C signal is well related with the Nothofagus pollen record of Mallín Pollux, confirming that the bulk δ13C signal mostly reflects the dominant type of terrestrial vegetation. Less negative δ13C values correspond to periods dominated by Nothofagus (southern beech), while more negative δ13C values reflect a decrease in Nothofagus and an increase in Poaceae (grass; Markgraf et al., 2007). For the last 17.8 kyr, δ13C can therefore also be used as precipitation proxy. Prior to 17.8 kyr 13 cal BP, however, the δ C values are much higher than those of terrestrial C3 plants and of lake plankton (-24.25–-11.28 ‰; Meyers and Teranes, 2001). Another source of terrestrial organic matter must 13 therefore be at the origin of these high δ C values. The most likely source is C4 plants (see also Figure 6; Meyers and Teranes, 2001).

The precipitation reconstruction described above is driven by two different mechanisms before and after 17.8 cal kyr BP. Before, the environment is dry due to the PIS blocking the westerly winds while after, precipitation proxies reflect westerly wind strength at 46°S. The postglacial evolution of the different wind and precipitation proxies will be discussed in the following sections.

30 Chapter 5 – Discussion

Figure 17. Comparison of the different postglacial wind and precipitation proxy records: (a) bulk δ13C; (b) accumulation rate of terrestrial organic carbon (geochemical data from Granon, 2015); (c) Nothofagus pollen record from Mallín Pollux (Markgraf et al., 2007); (d) mean of modified sortable silt (i.e. 10–125 µm; SS’; Van Daele et al., 2016); (e) Box-Whisker plots of the drift-intensity parameter (for more details see Van Daele et al., 2016). The Nothofagus pollen record contains taxa of the Nothofagus dombeyi-type group, i.e. Nothofagus dombeyi, N. betuloides, N. pumilio, and N. Antarctica. The time-limits of the Holocene are according to Walker et al. (2012). Before 17.8 cal kyr BP, variability in the proxies are attributed to changes in ice sheets while the westerly wind strength mostly influences the proxies after 17.8 cal kyr BP.

31 Chapter 5 – Discussion

5.3.1 Deglaciation Before 17.8 kyr cal BP extremely dry conditions prevailed east of the Andes due to the blocking of the westerly winds by the PIS-covered Andes. This is evidenced by the high δ13C values (up to -11.3‰;

Figure 17a) in the period of 19.8–17.8 cal kyr BP indicating the presence of C4 plants which dominate in arid conditions. The C4 photosynthetic pathway occurs predominantly in grasses and these C4 plants survive better than C3 plants in high-temperature and high-light environments when sufficient moisture is present (Powell et al., 2012). For comparison, a mean value of -12.5 ‰ for C4 herbaceous cover in South America was assigned by Powell et al. (2012). The high accumulation rates of terrestrial organic carbon (Figure 17b) in this period can be explained by the extremely high bulk accumulation rates and poor precision on TOC. Because of the low values for TOC in general and the extremely high bulk accumulation rates, a small change in TOC will result in large changes in TOC accumulation rates. Therefore, it is not very clear if these accumulation rates of terrestrial organic carbon are real. Although there can be concluded that vegetation before 17.8 cal kyr BP was dominated by species adapted to arid conditions.

5.3.2 Postglacial evolution of precipitation and westerly wind strength From 17.8 cal kyr BP onwards, after significant reduction of the size of the PIS, the precipitation proxies more directly reflect the strength of the westerly winds at 46°S. Between 17.8–9.3 cal kyr BP, low accumulation rates of terrestrial organic carbon indicate less drier conditions than before 17.8 cal kyr BP (Figure 17b). This is further evidenced by low δ13C values (-26.45–-24.25‰; Figure 17a), suggesting the presence of C3 vegetation (Meyers and Teranes, 2001; Powell and Still, 2009) dominated by Poaceae (Figure 17c; Markgraf et al., 2007). This interpretation supports the conclusions of Van Daele et al. (2016), who observed low drift-intensity and low SS’ values indicating weak westerly winds over northern Chilean Patagonia (Figure 17d,e). The slightly higher mean SS’ (Figure 17d), suggesting windier conditions around 16 cal kyr BP, can be explained by the influence of the coarse and thick Ho deposit in the lake catchment and does not reflect an increase in wind strength (Van Daele et al., 2016). It is remarkable that none of the wind proxies seem to show any change in westerly wind strength during the ACR and YD events (Figure 17), likely due to a more southward position of the southern westerly wind belt in that time period.

From 9.3 cal kyr BP onwards, the accumulation rate of terrestrial organic carbon starts to increase, indicating an increasing precipitation until 2.7 cal kyr BP. This increase is coeval with the increase in 13 δ C values and Nothofagus pollen, reflecting the development of C3 vegetation typical of humid climates in the lake watershed (Figure 17a,b,c). After 7.5 cal kyr BP, the Nothofagus record remains stable indicating the establishment of a Nothofagus forest. Additionally, the drift-intensity parameter gradually increases reflecting increasing wind strength (Figure 17e) and the mean SS’ values progressively increase until 5 cal kyr BP (Figure 17d). Therefore, we can conclude that an increase in wind-driven moisture is present during the early and mid Holocene. This is also in agreement with Markgraf et al. (2007), who demonstrated that fire activity in the region decreased between ~7.5 to 4 cal kyr BP, suggesting the establishment of a precipitation regime similar to the present-day climate.

After a period of high accumulation rates of terrestrial organic carbon indicating wet conditions between 9.3–2.7 cal kyr BP, decreasing accumulation rates of terrestrial organic carbon during the last 2.7 kyr indicate a return to slightly drier conditions (Figure 17b). Similar changes in the δ13C signal and the Nothofagus record also suggest a return to vegetation indicative of slightly drier conditions (Figure 17a,c). Moreover, between 4–1.5 cal kyr BP, the Nothofagus record suggest a more open forest, i.e. a

32 Chapter 5 – Discussion lower amount of Nothofagus pollen indicating more Poaceae pollen. This is in agreement with the decreasing mean SS’ values, reflecting decreasing westerly wind strength, without however returning to early Holocene conditions (Figure 17d). The drift-intensity parameter, however, remains mostly high and stable during that time interval, which would indicate stable windy conditions over the region (Figure 17e). The apparent discrepancy between the drift-intensity parameter and the other proxies can however be explained by differential compaction of the sediments in the upper seismic units that affects the drift-intensity parameter but not the other proxies (Van Daele et al., 2016). Eventually, we can conclude that wind strength progressively decreased over northern Chilean Patagonia during the last 2.7 kyr.

33 Chapter 5 – Discussion

5.4 Postglacial changes in lake productivity

5.4.1 Relations between opal and aquatic organic carbon Different proxies linked to lake productivity for the last 18 kyr are presented in Figure 18. As mentioned in section 5.2, there is a high and positive correlation between opal and aquatic organic carbon (r=0.706; p<0.001; Figure 16) indicating that the general productivity in the lake is closely related to diatom productivity. The correlation is also demonstrated in the similarities between the curves of the accumulation rates of opal and aquatic organic carbon (Figure 18b,c). Although accumulation rates of opal are consistently above zero and thus indicate the presence of lake productivity for the last 17 kyr (Figure 18b), accumulation rates of aquatic organic carbon sometime goes to zero (e.g. in the last ~6 kyr; Figure 18c). This can be explained by the difficulty of determining the N/C values of the terrestrial and aquatic end-members because these end-members can change over time. In this dissertation, the Redfield ratio was used to define the N/C ratio for the aquatic end-member, namely, N/C = 0.1509. This ratio may however be different for Lago Castor. Although Granon (2015) analyzed filtrates of lake water to estimate the aquatic N/C end-member, the values were generally lower than the N/C ratio derived from the Redfield ratio, due to the inevitable presence of terrestrial organic matter suspended in the lake . Since diatom frustules are better preserved than organic matter in sediments in general, the interpretation in terms of productivity should mostly be based on opal accumulation rates.

5.4.2 Postglacial evolution of lake productivity From 17.8 cal kyr BP onwards, important changes occur in the lake productivity as is reflected in the abrupt increase of opal and aquatic organic carbon (Figure 18a,b,c). These important changes are related to the final establishment of the lake level of Lago Castor around 17 cal kyr BP. This lake level rise is likely the result of an increased precipitation due to a decreased blocking of the shrinking PIS accompanied by a southward shift of the southern westerly wind belt (Van Daele et al., 2016). Because the lake was already isolated from glaciers, lake temperature could increase and more light could penetrate the lake, favouring the development of lake productivity (e.g. diatom productivity). This timing corresponds to a first warming pulse that was recognized in marine and terrestrial records across Chilean Patagonia (Lamy et al., 2007; Bertrand et al., 2010).

Opal concentrations increase from 16.8–11.3 cal kyr BP indicating the development of diatoms in Lago Castor (Figure 18a). The early Holocene and the beginning of the mid Holocene are characterized by the highest opal concentrations indicating high abundances of diatoms followed by a decreasing trend from ~6 cal kyr BP onwards and moderate to high concentrations are observed until present. The exception to this general trend is the very low and immediately following very high opal concentrations between 4–2.7 cal kyr BP, i.e. right after H2 eruption (~4 cal kyr BP; Naranjo et al., 1998). Furthermore, the accumulation rates of opal and aquatic organic carbon increase simultaneous at 16.8 cal kyr BP but reach already relatively high rates around 15.8 cal kyr BP indicating high lake productivity (Figure 18b,c). Opal accumulation rates remain relatively stable and high until the beginning of the Holocene suggesting a high diatom productivity, and subsequent a slight decrease of diatom productivity throughout the Holocene with a major peak of diatom productivity at 3.2 cal kyr BP can be observed (Figure 18b). The accumulation rates of aquatic organic carbon start to decrease from 15.8 cal kyr BP onward until the beginning of the mid Holocene around 7.8 cal kyr BP (Figure 18c). Afterwards, they decrease drastically and remain very low at the end of the mid Holocene and late Holocene with major peaks of lake productivity around 5.4, 3.2 and 1.4 cal kyr BP and a rising trend until present.

34 Chapter 5 – Discussion

Figure 18. Comparison of the different lake productivity proxies with wind and sea surface temperature proxies: (a) opal concentrations (solid line) and running average of XRF Si/Al ratio (window width: 15 points; dashed line); (b) accumulation rate of opal; (c) accumulation rate of aquatic organic carbon (geochemical data from Granon, 2015); (d) mean of modified sortable silt (SS’; Van Daele et al., 2016); (e) alkenone sea surface temperature (ODP Site 1233; Kaiser et al., 2005); relative abundances of planktonic (f), tychoplanktonic (g) and benthic (h) diatom species (Van Goethem, 2015). The time limits of the Holocene are according to Walker et al. (2012).

35 Chapter 5 – Discussion

The evolution of the different diatom taxa and paleoecology of the diatom community in Lago Castor can be found in Van Goethem (2015) and will not be discussed in detail, although several remarkable changes in the diatom community can be noted (Figure 18f,g,h; Figure 26 of Van Goethem, 2015). The diatom community of Lago Castor starts with predominantly benthic species, followed by an increase in tychoplanktonic species (Figure 18g,h). The benthic (such as Diploneis and Cymbella species; Figure 10e,f) and tychoplanktonic (such as Staurosirella and Fragilaria; Figure 10c,d) species suggest shallow lake levels and cold environmental conditions among other things. Tychoplanktonic species are abundant between 17.2–14.5 cal kyr BP but at the onset of the ACR abundances start to decrease again. The abundance of planktonic diatoms starts to increase at the beginning of the ACR and they remain dominant during the entire Holocene. Especially the planktonic species Aulocoseira granulata and Discostella stelligera (Figure 10a,b) become dominant indicating for example warmer and eutrophic conditions and higher nutrient availability in the lake. There are however some intervals (e.g. around 11.8, 8.1 and 1.9 cal kyr BP) where tychoplanktonic and benthic species gets more important and consequently cause a decrease in planktonic abundances (Figure 18f,g,h). Although, the benthic species remain relatively insignificant during the Holocene compared to the period 17.9–17 cal kyr BP.

5.4.3 Relations between climate change and lake productivity during the deglaciation The presence or absence of the Antarctic Cold Reversal (ACR), Younger Dryas (YD) or Huelmo/Mascardi cold reversal (HM) in southern South America is still a subject of debate (e.g. Kaiser et al., 2005). No change coeval with the ACR, YD or HM seem to occur in the accumulation rates of opal or aquatic organic carbon (Figure 18b,c). However, when looking at the diatom composition, a sudden decrease in tychoplanktonic species and coeval increase in planktonic species, could be linked to the ACR event (Van Goethem; 2015). This change might be reflected in the opal record and the accumulation rates of opal and aquatic organic carbon which show a sudden flattening of the trend during this time period (Figure 18a,b,c). A similar stabilization of surface temperature during the ACR was also observed in sediment cores from the southeast Pacific (ODP Site 1233; Figure 18e). The presence of the ACR in northern Patagonia is therefore not directly supported by our dataset.

At around 40°S, Hajdas et al. (2003) identified the HM event as a cold millennium overlapping the YD and ACR. Although our diatom productivity results show a minimum at about 12.3 cal kyr BP (Figure 18b), it is only based on one data point and it is not really visible in the high-resolution Si/Al XRF data (Figure 18a). This is in agreement with Sterken et al. (2008), who did not find clear evidence for the HM event in the diatom data of Lago Puyehue. Moreover, this small decrease in diatom productivity is almost immediately followed by an increase until the end of the northern hemisphere YD (Figure 18b). In addition, ocean records suggest a major SST increase of about 2°C in the southeast Pacific suggesting no cold phase during the HM or YD in this region (Figure 18e). We can conclude that the diatom paleoecological data seem to show the presence of the ACR, but there is no actual evidence present for the occurrence of a YD or HM event in the Lago Castor record.

When comparing the mean SS’, the proxy best representing wind strength at Lago Castor, with the lake productivity proxies, there is no real relation observed concluding that wind is not the cause for changes in lake productivity (Figure 18).

36 Chapter 5 – Discussion

5.4.4 Relations between climate change and lake productivity during the Holocene 5.4.4.1 Comparison with short core CAS-09 The analysis of short sediment core CAS-09 obtained by Elbert et al. (2013) in the southwestern part of the lake (Figure 4) demonstrated a positive correlation between the opal flux and the annual temperature data during the last century (AD 1900-2006), suggesting that biogenic silica accumulation rates could be used to reconstruct past atmospheric temperatures. Based on a calibration-in-time model, these authors predicted annual temperatures back to AD 400, the last 1.55 cal kyr BP, from the opal flux.

The biogenic silica concentrations of Elbert et al. (2013) compared to my biogenic silica results are shown in Figure 19. Because the XRF Si/Al ratio has proven to be a valid proxy for the estimation of biogenic silica content (see section 5.1.1), the higher resolution XRF data is used for this comparison. In Figure 19, the two curves are plotted in such a way that the depths in both cores corresponds to the same age, i.e. 68 cm in the CAS-09 core corresponds to 202.4 cm in the CAST01 core and both records represent the last 3.9 cal kyr BP. These differences in accumulation rates, approximately 3 times higher at site CAST01 than at CAS-09, is related to the limited river inflows in the proximity of site CAS-09 compared to site CAST01. The two curves show remarkable similarities (Figure 19). Therefore, we can apply the same statement of Elbert et al. (2013) and conclude that biogenic silica productivity at site CAST01 during the last millennia is also mainly driven by temperature.

Figure 19. Comparison of the biogenic silica content in Lago Castor performed (a) in this study, displayed by the high- resolution XRF Si/Al ratio, and (b) in Elbert et al. (2013). Locations of the composite core CAST01 (this study) and short core CAS-09 (Elbert et al., 2013) are shown in Figure 4. 68 and 202.4 cm in core CAS-09 and CAST01, respectively, cover the last 3.9 kyr.

5.4.4.2 Climatic drivers of Holocene changes in biogenic silica productivity The sudden increase in accumulation rate of opal from 16.8 cal kyr onwards is in accordance with an increased sea surface temperature (SST) in the southeast Pacific (ODP site 1233; Kaiser et al., 2005; Figure 18e). The SST suggests a warming pulse, already starting from 19 cal kyr BP onward, that probably marks the end of the LGM, and this could explain the increased lake productivity in Lago Castor. When comparing the accumulation rates of opal with the SST of the southeast Pacific during the Holocene (Figure 18b,e), both parameters show the same decreasing trend. Furthermore, the highest accumulation rates of opal, i.e. the highest diatom productivity, in the beginning of the Holocene, especially around 9.7 cal kyr BP, could possibly be linked to an early Holocene Climatic Optimum (HCO) as is also evidenced in the SST record (~11–9 cal kyr BP; Figure 18e). This is in

37 Chapter 5 – Discussion agreement with Heusser and Streeter (1980), whose pollen-based air temperature record shows the same decreasing trend during the entire Holocene. Therefore, it is likely that the main driver for Holocene changes in biogenic silica productivity is temperature, which means that the conclusions of Elbert et al. (2013) can be extended back in time.

In addition to temperature, wind could also affect diatom productivity through changes in nutrient input and water turbidity (i.e. light penetration). The increasing mean SS’ from 10 cal kyr BP onwards (Figure 18d) indicates increasing westerly wind strength during the early Holocene reaching maximum wind strength at the end of the mid Holocene. This could have caused more sediment suspended in the lake increasing water turbidity resulting in reduced light penetration into the lake. This process could explain the decreasing diatom productivity trend for the early and mid Holocene but cannot account for the changes in lake productivity observed during the late Holocene. An exception to the general decreasing trend in lake productivity is the period between 4–2.8 cal kyr BP, during which very high accumulation rates of opal can be observed (Figure 18b). A possible explanation for this huge increase in diatom productivity could be that a sudden decrease in westerly wind strength around 4 cal kyr BP (Figure 18d) enhanced lake productivity, and this together with the fact that no volcanic activity was present and the diatoms had time to develop. However, this increase does not correspond with a significant SST increase in the southeast Pacific (Figure 18e).

Based on the two comparisons above, the results of Elbert et al. (2013), the similar decreasing trends between the accumulation rate of opal and the SST of the southeast Pacific throughout the Holocene (Kaiser et al., 2005), and between the accumulation rate of opal and Holocene air temperature in southern Chile (Heusser and Streeter, 1980), we can conclude that temperature is the main driver of diatom, and thus biogenic silica, productivity during the Holocene.

38

6. CONCLUSION

In this thesis, the postglacial climatic evolution of northern Patagonia could be reconstructed by means of a multiproxy approach wherein the analysis of biogenic silica concentrations was the final step. By integrating the results obtained in this thesis with existing data from the same sediment core, we were able to reconstruct variations in the strength of the southern westerly winds and elucidate the main climatic driver of biogenic silica productivity in Lago Castor.

The alkaline extraction technique performed on samples of the Castor sediment core was successful and the subsequent measurements with ICP-AES of Si and Al concentrations on the extracted fraction allowed to calculate the biogenic silica content. Because siliceous minerals can also dissolve during the extraction process, it is necessary to apply a lithogenic correction to account for the non-biogenic silica. The correction factor was measured on the volcanic soil samples because they best represent the dominant source of detrital particles into the lake. Attention should be given to the correct calculation of the lithogenic correction factor especially in regions where the development of volcanic ash soils takes some time and the use of a transitional factor is more justified. This way, biogenic silica and opal concentrations could be successfully calculated. The efficiency of the diatom dissolution by the alkaline extraction technique was confirmed by analysis of the smear slides.

For the characterization of long-term trends in diatom productivity at high resolution, the chemical alkaline extraction technique should be combined with other techniques to estimate biogenic silica concentrations. The XRF elemental ratio Si/Al has proven to have the best correlation with my measured biogenic silica concentrations. Therefore, non-destructive XRF scanning can offer an alternative to the time-consuming alkaline extraction technique in order to estimate biogenic silica concentrations at high resolution. However, the correlation of XRF ratios with biogenic silica concentrations obtained by classical biogenic silica techniques should always be verified with statistical analyses. Furthermore, the calculated diatom abundance obtained by point counting and the concentrations of the diatom-derived pigment fucoxanthin also have a significant positive correlation. Ideally, diatom biovolumes should be calculated by combining diatom counts with size measurements of each dominant species in order to determine biogenic silica concentrations.

By comparing the different sediment components with the tephra layers mostly deposited during the last 18 kyr, we could conclude that minor variations in biogenic silica concentrations are due to either a decrease in diatom productivity caused by volcanic eruptions or to dilution by volcanic material. This indicates a strong influence of volcanic activity on the sedimentary record of Lago Castor.

The bulk organic geochemistry data provided important information about the terrestrial and aquatic sources of sedimentary organic matter. Accumulation rates of terrestrial and aquatic organic carbon were successfully used as indicators for precipitation and lake productivity, respectively. Moreover, a good correlation between opal concentrations and aquatic organic carbon content was observed, indicating that diatoms, and possibly a minor group of other biogenic silica organisms, are the main drivers of lake productivity. The carbon isotopic composition mostly represents the dominant type of terrestrial vegetation, Nothofagus versus Poaceae, and gives information about the C3 or C4 pathway of the vegetation in the lake watershed.

Eventually, the re-analysis of the bulk organic geochemical data of Granon (2015) led to a new precipitation proxy-record for lake Castor, which confirmed the results of Van Daele et al. (2016). By

39 Chapter 6 – Conclusion comparing the different wind, precipitation and lake productivity proxies and temperature records, the postglacial evolution of biogenic silica productivity could be reconstructed. The sudden rise in biogenic silica productivity at 16.8 cal kyr BP is attributed to the final establishment of the Lago Castor lake level and to the coeval warming step recorded in the sea surface temperature of the southeast Pacific. Glaciers were already retreated from Lago Castor, enabling the lake temperature to increase. The Lago Castor opal record does not show clear evidence for a postglacial cooling event at the time of the Antarctic Cold Reversal, the Huelmo/Mascardi event or the northern hemisphere Younger Dryas. The early Holocene and the beginning of the mid Holocene are characterized by the highest biogenic silica productivity rates, followed by a slight decreasing trend until present. The interpretation of the biogenic silica productivity is supported by the bulk organic geochemical data, especially the aquatic productivity inferred from the accumulation rates of aquatic organic carbon. The wind and precipitation proxies did not show a clear relation with the lake productivity proxies concluding that these were not the cause for changes in biogenic silica productivity. By comparing our biogenic silica accumulation rate record to regional sea surface temperature (Kaiser et al., 2005) and air temperature reconstructions (Heusser and Streeter, 1980), we can conclude that the main climatic driver for Holocene changes in biogenic silica productivity in Lago Castor is temperature, in agreement with the findings of Elbert et al. (2013) for the last century.

Methods to derive absolute temperatures from lake sediments are not straightforward. This is demonstrated by the analysis of oxygen isotope composition of diatom frustules (Leng and Barker, 2006), for example, which requires samples that are almost pure diatomite. Because the extraction technique will liberate oxygen from all the components in the sediment, any proportion of contaminants will consequently have a significant influence on the oxygen isotope value. A more promising method for reconstructing past lake temperatures is the investigation of the TEX86 temperature proxy (Powers et al., 2004; Kaiser et al., 2015). TEX86 stands for the tetraether index of glycerol dialkyl glyceryl tetraethers, i.e. membrane lipids of archae and bacteria, consisting of 86 carbon atoms. Although initially this proxy was developed for the reconstruction of sea surface temperature in marine systems, Powers et al. (2004) demonstrated the application of the TEX86 proxy in lake environments and the validation as a continental paleotemperature tool.

40

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45

APPENDIX

Sample numbers, downcore depth (m), age (cal kyr BP), elemental concentrations of Al and Si (ppm) measured with the ICP- AES, and calculated biogenic silica concentrations with 2 different sets of lithogenic correction factors.

Sample Downcore Age (cal Al Si Correction Biogenic Correction Biogenic number depth (m) kyr BP) (ppm) (ppm) 1 silica 1 2 silica 2 1 0.005 -0.050 0.622 19.630 6.23 15.75 6.23 15.75 3 0.185 0.309 0.434 20.619 6.23 17.91 6.23 17.91 4 0.305 0.548 0.842 16.969 6.23 11.72 6.23 11.72 5 0.405 0.742 0.406 22.738 6.23 20.21 6.23 20.21 6 0.505 0.942 0.392 20.733 6.23 18.29 6.23 18.29 7 0.675 1.274 0.582 22.292 6.23 18.67 6.23 18.67 8 0.715 1.339 0.471 7.357 6.23 4.42 6.23 4.42 9 0.735 1.378 0.765 22.418 6.23 17.65 6.23 17.65 10 0.905 1.683 0.802 23.192 6.23 18.19 6.23 18.19 11 1.045 1.921 0.934 9.286 6.23 3.47 6.23 3.47 12 1.145 2.115 0.708 20.797 6.23 16.38 6.23 16.38 13 1.285 2.373 0.685 15.410 6.23 11.14 6.23 11.14 14 1.465 2.732 0.588 21.368 6.23 17.70 6.23 17.70 15 1.565 2.936 0.845 33.110 6.23 27.84 6.23 27.84 16 1.67 3.154 0.521 32.924 6.23 29.68 6.23 29.68 17 1.86 3.558 1.041 27.038 6.23 20.55 6.23 20.55 18 1.96 3.776 0.884 15.765 6.23 10.26 6.23 10.26 19 2.03 3.915 1.113 13.172 6.23 6.24 6.23 6.24 20 2.05 3.960 1.176 15.668 6.23 8.33 6.23 8.33 21 2.37 4.244 0.481 22.396 6.23 19.40 6.23 19.40 22 2.58 4.642 0.599 21.287 6.23 17.55 6.23 17.55 23 2.78 5.113 0.768 25.097 6.23 20.31 6.23 20.31 24 2.88 5.353 0.588 26.692 6.23 23.03 6.23 23.03 25 2.985 5.589 0.542 27.147 6.23 23.77 6.23 23.77 26 3.095 5.840 0.444 26.961 6.23 24.19 6.23 24.19 27 3.195 6.085 0.657 27.787 6.23 23.69 6.23 23.69 28 3.395 6.579 0.345 27.408 6.23 25.26 6.23 25.26 29 3.495 6.828 0.443 28.534 6.23 25.77 6.23 25.77 30 3.59 7.065 0.576 24.558 6.23 20.97 6.23 20.97 31 3.69 7.315 0.837 29.234 6.23 24.02 6.23 24.02 32 3.78 7.540 0.588 27.619 6.23 23.96 6.23 23.96 33 3.79 7.566 0.726 23.737 6.23 19.21 6.23 19.21 34 3.83 7.666 0.681 25.155 6.23 20.91 6.23 20.91 35 3.88 7.792 0.841 19.158 6.23 13.91 6.23 13.91 36 4.02 8.055 0.735 25.312 6.23 20.73 6.23 20.73 37 4.21 8.521 0.541 28.222 6.23 24.85 6.23 24.85 38 4.22 8.546 0.783 26.519 6.23 21.64 6.23 21.64 39 4.34 8.854 0.743 16.727 6.23 12.10 6.23 12.10 40 4.48 9.068 0.991 21.738 6.23 15.56 6.23 15.56 41 4.59 9.354 1.026 17.356 6.23 10.96 6.23 10.96

47 Appendix

42 4.68 9.589 0.346 33.911 6.23 31.76 6.23 31.76 43 4.78 9.851 0.515 27.487 6.23 24.28 6.23 24.28 44 4.885 10.097 0.693 14.849 6.23 10.53 6.23 10.53 45 4.895 10.124 0.554 26.151 6.23 22.70 6.23 22.70 46 5.095 10.659 0.454 27.395 6.23 24.57 6.23 24.57 47 5.205 10.957 0.554 25.508 6.23 22.05 6.23 22.05 48 5.365 11.274 0.801 24.122 6.23 19.13 6.23 19.13 49 5.385 11.329 0.633 31.887 6.23 27.94 6.23 27.94 50 5.455 11.522 0.501 27.936 6.23 24.81 6.23 24.81 51 5.555 11.799 0.532 26.593 6.23 23.28 6.15 23.32 52 5.755 12.344 0.522 20.104 6.23 16.85 6.08 16.93 53 5.855 12.621 0.547 23.649 6.23 20.24 6.00 20.37 54 5.975 12.853 0.587 24.007 6.23 20.35 5.92 20.54 55 6.165 13.375 0.559 19.303 6.23 15.82 5.84 16.04 56 6.175 13.402 0.873 19.923 6.23 14.48 5.76 14.90 57 6.275 13.673 0.582 19.791 6.23 16.16 5.68 16.49 58 6.375 13.940 0.531 19.174 6.23 15.86 5.60 16.20 59 6.475 14.203 0.512 19.155 6.23 15.96 5.52 16.33 60 6.575 14.462 0.722 20.391 6.23 15.89 5.44 16.46 61 6.625 14.590 0.664 18.312 6.23 14.17 5.36 14.75 62 6.645 14.641 0.697 16.781 6.23 12.43 5.29 13.10 63 6.665 14.691 0.966 9.233 6.23 3.21 5.21 4.20 64 6.685 14.716 0.954 5.547 6.23 0.00 5.13 0.66 65 6.835 14.918 0.722 9.025 6.23 4.52 5.05 5.38 66 7.035 15.397 0.669 14.188 6.23 10.02 4.97 10.86 67 7.235 15.848 0.583 15.019 6.23 11.38 4.89 12.17 68 7.435 16.244 0.850 15.253 6.23 9.96 4.81 11.16 69 7.565 16.471 0.635 11.437 6.23 7.48 4.73 8.43 70 7.675 16.676 0.705 9.124 6.23 4.73 4.65 5.84 71 7.745 16.805 1.291 5.694 6.23 0.00 4.57 0.00 72 7.765 16.841 1.209 6.281 6.23 0.00 4.50 0.85 73 7.885 17.026 0.714 4.680 6.23 0.23 4.42 1.53 74 7.985 17.195 0.648 3.604 6.23 0.00 4.34 0.79 75 8.117 17.360 0.745 3.847 6.23 0.00 4.26 0.67 76 8.357 17.704 0.683 2.798 6.23 0.00 4.18 0.00 77 8.437 17.814 0.953 3.813 6.23 0.00 4.10 0.00 78 8.447 17.827 1.005 4.250 6.23 0.00 4.02 0.21 79 8.457 17.841 0.595 2.346 6.23 0.00 3.94 0.00 80 8.537 17.936 1.589 6.398 6.23 0.00 3.86 0.26 81 8.557 17.961 1.373 5.619 6.23 0.00 3.79 0.42 82 8.727 17.987 1.605 6.341 3.71 0.39 3.71 0.39 83 8.827 17.987 1.793 7.043 3.71 0.40 3.71 0.40 84 8.927 17.987 1.792 7.006 3.71 0.36 3.71 0.36 85 9.187 18.011 0.560 2.020 3.71 0.00 3.71 0.00 86 9.287 18.123 0.619 2.123 3.71 0.00 3.71 0.00 87 9.397 18.239 0.575 2.077 3.71 0.00 3.71 0.00

48 Appendix

88 9.66 18.504 0.669 2.142 3.71 0.00 3.71 0.00 89 9.76 18.596 0.723 2.186 3.71 0.00 3.71 0.00 90 9.86 18.682 0.539 1.969 3.71 0.00 3.71 0.00 91 10.05 18.825 0.568 2.066 3.71 0.00 3.71 0.00 92 10.06 18.833 0.728 2.452 3.71 0.00 3.71 0.00 93 10.26 18.972 0.564 2.129 3.71 0.04 3.71 0.04 94 10.36 19.034 0.573 2.029 3.71 0.00 3.71 0.00 95 10.46 19.093 0.616 2.346 3.71 0.06 3.71 0.06 96 10.56 19.149 0.538 2.389 3.71 0.40 3.71 0.40 97 10.76 19.250 0.606 2.474 3.71 0.23 3.71 0.23 98 10.86 19.296 0.701 2.654 3.71 0.06 3.71 0.06 99 10.94 19.331 0.661 2.582 3.71 0.13 3.71 0.13 100 10.96 19.340 0.591 2.485 3.71 0.30 3.71 0.30 101 11.06 19.381 0.608 2.443 3.71 0.19 3.71 0.19 102 11.263 19.434 0.645 2.686 3.71 0.30 3.71 0.30 103 11.363 19.472 0.776 2.929 3.71 0.05 3.71 0.05 104 11.463 19.508 0.728 2.837 3.71 0.14 3.71 0.14 105 11.663 19.577 0.717 2.650 3.71 0.00 3.71 0.00 106 11.863 19.644 0.623 2.192 3.71 0.00 3.71 0.00 107 11.943 19.671 0.744 2.703 3.71 0.00 3.71 0.00 108 12.093 19.721 0.793 2.827 3.71 0.00 3.71 0.00 109 12.293 19.788 0.797 2.637 3.71 0.00 3.71 0.00 110 13.096 41.080 0.876 2.848 3.71 0.00 3.71 0.00 111 13.216 41.086 0.848 2.822 3.71 0.00 3.71 0.00 112 13.296 41.090 1.117 3.167 3.71 0.00 3.71 0.00 113 13.496 41.101 1.283 3.467 3.71 0.00 3.71 0.00 114 13.596 41.106 1.192 3.351 3.71 0.00 3.71 0.00 115 13.796 41.116 1.327 3.536 3.71 0.00 3.71 0.00 116 13.896 41.121 1.187 3.389 3.71 0.00 3.71 0.00 117 13.996 41.127 0.773 3.383 3.71 0.52 3.71 0.52 118 14.191 41.137 0.809 3.461 3.71 0.46 3.71 0.46 119 14.391 41.147 0.982 3.810 3.71 0.17 3.71 0.17 120 14.791 41.168 1.007 3.826 3.71 0.09 3.71 0.09 121 14.991 41.178 0.984 4.085 3.71 0.44 3.71 0.44 122 15.091 41.183 0.702 3.082 3.71 0.48 3.71 0.48 123 15.191 41.189 0.851 3.407 3.71 0.26 3.71 0.26 124 15.291 41.194 0.998 4.149 3.71 0.45 3.71 0.45

49