Susanne Fietz: Recent and fossil phytoplankton pigments in Lake Baikal as markers for community structure and environmental changes |
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Recent and fossil phytoplankton pigments in Lake Baikal as markers for community structure and environmental changes
Dissertation
Zur Erlangung des akademischen Grades
doctor rerum naturalium
(Dr. rer. nat.)
im Fach Biologie
eingereicht an der
Mathematisch-Naturwissenschaftlichen Fakultät I
der Humboldt-Universität zu Berlin
von
Dipl.-Biol. Susanne
Fietz
geboren am 27.09.1973 in Berlin
Präsident der Humboldt-Universität zu Berlin
Prof. Dr. Jürgen Mlynek
Dekan: Dekan der Mathematisch-Naturwissenschaftlichen Fakultät I
Prof. Thomas Buckhout, PhD
Gutachter:
1. Prof. Dr. Andreas Nicklisch
2. Prof. Dr. Christian Steinberg
3. RNDr Viera Straškrábová DrSc
eingereicht: 16.02.2005
Tag der mündlichen Prüfung: 10.06.2005
Abstract (English)
Lake Baikal is the World´s oldest, deepest and largest (by volume) lake and contains many endemic species. Since 1996, after becoming a UNESCO World Heritage Area, the effects of global warming and local anthropogenic eutrophication on its unique ecosystem become a subject of international discussion. Recent and fossil phytoplankton pigments are being increasingly used to monitor recent and past changes of the phytoplankton composition and productivity that indicate changes of climatic and other environmental conditions in marine and freshwater systems. However, phytoplankton pigments were not yet investigated in the water column of Lake Baikal and only little in its sediment. The objective of this thesis was to assess whether and to which extent phytoplankton pigments of the water column and sediments in Lake Baikal can indicate recent and past phytoplankton community structure changes as well as climatic and other environmental changes.
The first task was to assess the phytoplankton pigment distribution in the water column. A three year-long intense phytoplankton monitoring programme was carried out from 2001 to 2003 as part of the EU-funded CONTINENT project in conjunction with a much longer-term monitoring programme (over 60 years) by the Irkutsk State University. HPLC-aided pigment analyses were combined with microscopic counts. Significant changes of the total chlorophyll a (ubiquitous in phytoplankton) as well as of characteristic marker pigments were found between near-shore regions, river inflow sites and open basins. The marker pigments allowed estimating phytoplankton chemotaxonomic group composition at all investigated sites. In situ fluorescence horizontal and depth profiles and satellite image analyses complemented the pigment-based monitoring. Canonical correlation analyses indicated a major influence of temperature and stratification on the phytoplankton composition even for the regional distribution. Phytoplankton pigments were shown to be useful proxies to determine the recent phytoplankton assemblage and its variations induced by environmental changes.
The second aim of this thesis was to determine the pigment flux through the water column and how the main phytoplankton groups were represented in the deposited material. It was assumed that strong degradation by grazing and oxidation affects the phytoplankton pigments during their sedimentation. In contrast to most other deep lakes, Lake Baikal is oxygen saturated throughout the water column even within the water-sediment interface. To study the pigment flux to the surface sediment, sediment traps were moored in the South and North basins. Heavy, non-edible Bacillariophyceae formed the main contribution to the settling material. Strong degradation processes controlled the sedimentation of small, light and edible phytoplankton. In the South, these processes took place within the upper 300 m of the water column (two-exponential regression models). In the North, strong degradation occurred down to the lake bottom (linear regression models). The pigment loss during settling through the water column was much higher in the North than in the South. Further strong degradation occurred within the oxidised surface sediment. The degradation was strongest in the North and lowest at the river inflows. The sedimentation out of the euphotic zone can be projected backward using regression models given in the present thesis.
A third task of this thesis was to examine whether phytoplankton pigments can be used to assess the phytoplankton response to natural climate changes in the pristine lake. To this end, the sedimentary phytoplankton pigments were analysed in cores covering the Holocene (last 10,000 years). The cores were taken from three main regions of Lake Baikal: South, North and Selenga Delta. Differential sequences were found for these regions with significantly the lowest chlorophyll a versus organic carbon ratios (indicating lowest production), but highest variability with time (indicating strongest climatic oscillations) in the North. Highest phytoplankton production was found during the early Holocene at approximately 9 kyr BP at the time of climate amelioration following the Younger Dryas (Boreal). Short phytoplankton production maxima occurred also during the late Atlantic and at the Subboreal/Subatlantic transition. Chlorophyll b plus its degradation products provided important additional information on the past development of Chlorophyceae, but most other sedimentary phytoplankton pigments were found to be unsuitable to determine past phytoplankton community structures in Lake Baikal, because their degradation products could not be definitely related to the parent pigments. Furthermore, the sedimentary pigment and organic carbon sequence of the Kazantsevo Interglacial (European Eemian, Marine Isotopic Stage 5e) was investigated. Higher production indicating warming at the time of the Kazantsevo was found when compared to the glacial periods. Strong climate oscillations occurred during the Kazantsevo and phytoplankton abundance was halved or doubled within centennial time scales. Sedimentary chlorophyll a in Lake Baikal was shown to be a reliable indicator of phytoplantonic response to published climate changes and may serve for validation of future climate models in continental regions.
Taken together, pigment-based analyses were shown to accurately reflect phytoplankton variation caused by environmental changes of natural or human origin in Lake Baikal. In conjunction with the EU project CONTINENT and the long-term monitoring in Irkutsk, the phytoplankton development determined from the last interglacial up until the early 21st century will be used for future research of climate changes as well as for the Lake Baikal’s protection.
Zusammenfassung (Deutsch)
Der Baikalsee ist der älteste, tiefste und größte (gemessen am Volumen) See der Welt, mit vielen endemischen Arten. Er wurde 1996 zum UNESCO Weltnaturerbe deklariert. Doch auch dieses einzigartige Ökosystem könnte in Zukunft durch anthropogen bedingte Klimaänderungen und Nährstoff-Einträge gefährdet sein. Rezente und fossile Phytoplankton-Pigmente werden immer häufiger in Monitorings genutzt, um aktuelle und historische Änderungen der Phytoplankton-Produktivität und –Zusammensetzung zu bestimmen, welche Änderungen von klimatischen und anderen Umweltbedingungen anzeigen. Dennoch wurden im Baikal bislang keine rezenten und nur in wenigen Studien fossile Phytoplankton-Pigmente untersucht. Daher sollte geprüft werden, ob Phytoplankton-Pigmente im Wasser und Sediment des Baikals herangezogen werden können, um rezente und historische Änderungen der Phytoplankton-Gemeinschaft sowie von klimatischen und anderen Umweltbedingungen zu bestimmen.
Zunächst wurde die Phytoplankton-Pigment Verteilung in der Wassersäule bestimmt. Von 2001 bis 2003 wurde im Rahmen des CONTINENT Projektes und des Langzeit-Monitorings der Staatlichen Universität Irkutsk (Rußland) ein intensives Phytoplankton-Monitoring-Programm durchgeführt. Signifikante Änderungen des Chlorophylls a (welches allen Phytoplanktern gemein ist) und charakteristischer, gruppenspezifischer Pigmente wurden zwischen allen untersuchten Gebieten (2 Flussmündungen, 3 offene Becken) gefunden. Anhand der Marker-Pigmente konnte die Zusammensetzung der Phytoplankton-Gemeinschaft bestimmt werden. Der Eindruck der extremen Heterogenität der Phytoplankton-Abundanz und -Zusammensetzung, welcher in diesem Ausmaß einzigartig für einen See ist, wurde durch Fluoreszenz-Profile und Satelliten-Bild-Auswertung verstärkt. Temperatur und Schichtung waren von besonderer Bedeutung für die saisonale, aber auch regionale Entwicklung des Phytoplanktons. Es konnte gezeigt werden, dass Phytoplankton Pigmente als verlässliche Indikatoren angesehen werden können, um die rezenten Änderungen der Phytoplankton-Abundanz und -Zusammensetzung sowie den Einfluss von Umweltvariablen im Baikal zu bestimmen.
Des Weiteren wurden die Sedimentation und Degradierung der Phytoplankton-Pigmente im Wasser bestimmt. Es wurde angenommen, dass die Pigmente während ihrer Sedimentation über die bis zu 1,6 km tiefe, durchgehend oxische Wassersäule starken Degradierungs-Prozessen unterlagen. Analysen von Sedimentfallen-Material aus dem Nord- und Südbecken ergaben, dass sich im Baikal das sedimentierende Material v.a. aus schweren, nicht-fressbaren Kieselalgen zusammensetzte. Die Sedimentation der kleinen, leichten und fressbaren Phytoplankter wurde durch variable Degradierungs-Prozesse kontrolliert. Im Südbecken erfolgten diese Prozesse (Zooplanktonfraß und Oxidation) v.a. innerhalb der obersten 300 m der Wassersäule, der winddurchmischten Schicht im Baikal. Im Norden erfolgte starke Degradierung bis zum Seeboden in 900 m Wassertiefe. Eine weitere Degradierung erfolgte im oxidierten Oberflächen-Sediment. Die Pigment-Sedimentation kann in retrospektiven Analysen fossiler Pigmente anhand der hier dargelegten Regressions-Modelle berechnet werden.
Zuletzt wurde bestimmt, ob Phytoplankton-Pigmente genutzt werden können, um historische klimabedingte Änderungen des Phytoplanktons im Baikal zu rekonstruieren. Hierfür wurden die Änderungen der fossilen Pigmente während des Holozäns (seit ca. 10.000 Jahren) in drei Regionen des Baikals untersucht: Südbecken, Nordbecken und Selenga Delta. Im Norden wurde das niedrigste mittlere Verhältnis von Chlorophyll a pro organischen Kohlenstoff (welches niedrige Produktion andeutet) gefunden, aber die höchste Variabilität mit der Zeit (welche ausgeprägte Klima-Oszillationen andeutet). Höchste Produktion wurde während des frühen Holozäns (vor ca. 9000 Jahren) nach dem Gletscher-Rückzug bestimmt. Chlorophyll b (inklusive Degradierungsprodukte) lieferte wichtige Informationen zu Änderungen der Chlorophyta (Grünalgen), während die meisten anderen fossilen Pigmente nicht geeignet waren, historische Änderungen der Phytoplankton-Gemeinschaft zu erfassen, da die Degradierungsprodukte dieser Pigmente nicht definitiv ihren Ausgangs-Pigmenten zugeordnet werden konnten. Die fossilen Pigmente wurden des Weiteren während der letzten Warmzeit (Kazantsevo, beginnend vor ca. 129.000 Jahren) untersucht. Ausgeprägte Klima-Oszillationen erfolgten während des Kazantsevos, wobei die Phytoplankton-Produktion sich innerhalb weniger hundert Jahre halbierte oder verdoppelte. Fossiles Chlorophyll a ist daher ein geeigneter Indikator für die klimabedingte Änderung der Phytoplankton-Produktion im Baikal.
Schlussfolgernd läßt sich sagen, dass Pigment-basierte Analysen im Baikal verlässliche Aussagen über rezente und historische Phytoplankton-Variationen ermöglichen, welche durch Umwelteinflüsse (natürlichen oder menschlichen Ursprungs) induziert werden. Im Rahmen des EU-Projekts CONTINENT und des Langzeit-Monitorings der Staatlichen Universität Irkutsk werden die Ergebnisse zur Phytoplankton-Entwicklung seit der letzten Warmzeit bis zum Beginn des 21. Jahrhunderts den lokalen Naturschutz und globale Klimastudien unterstützen.
Abstract (Russian)
Основной целью диссертационной работы являлась проверка возможности использования данных о пигментном составе фитопланктона в водном столбе и в осадках оз. Байкал для оценки характера структурных изменений в сообществах фитопланктона, а также их связи с климатическими и другие изменения характеристик окружающей среды, происходящих в недавнем прошлом.
В течение трехлетнего периода (2001-2003 гг.) была проведена программа интенсивного мониторинга фитопланктонных сообществ на Байкале. Проводимые исследования являлись частью проекта “КОНТИНЕНТ” финансируемого ЕС. Мониторинг был проведен в связке с программой длительной многолетней мониторинговой программы (более 60 лет) проводимой Научно-исследовательским институтом биологии при Иркутском Государственном Университете. В ходе работы современные методы анализа пигментов с использованием высокоэффективной жидкостной хроматографии были скомбинированы с традиционным микроскопическим подсчетом, флюометрией и дистанционным зондированием. Данный комплексный подход, базирующийся на пигментной оценке, зарекомендовал себя в качестве наиболее подходящего метода при мониторинге временных и сезонных изменений численности и структуры фитопланктонных сообществ, и их связи с характеристиками среды. Анализ пигментов из осадочных ловушек показал, что длительные пигмент-зависимые процессы разложения регулируют осаждение пигментов через всю толщу воды. Дальнейшее и наиболее сильное разложение связано с окисленными поверхностными осадками. Процессы седиментации за пределами эвтрофической зоны могут быть описаны с помощью регрессионной модели, представленной автором в данной диссертационной работе.Дополнительно к пигментам из фитопланктонных осадков были проанализированы Голоценовые слои (последние 10,000 лет), взятые из Южного и Северного районов Байкала, а также из дельты реки Селенга. Также были проанализированы осадковые слои, относящиеся к последнему ледниковому периоду (р-н Казанцево).
Хлорофил а из осадков, проявивший себя как наиболее подходящий индикатор, отражающий реакции фитопланктонных сообществ на известные климатические изменения, предложен для использования при дальнейшей оценке и построении климатических моделей континентальных регионов. Обобщенные результаты пигментного анализа показали изменения структур фитопланктонных сообществ на Байкале, вызванные причинами естественной или антропогенной природы.
List of the regions mentioned in this thesis
1 - Academician Ridge
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9 - North basin
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2 - Barguzin Bay
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10 - Olkhon Island
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3 - Bolshye Koti
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11 - Posolski Bank
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4 - Central basin
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12 - Selenga Delta
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5 - Continent Ridge
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13 - South basin
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6 - Irkutsk
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14 - Svyatoi Nos Peninsula
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7 - Listvianka (harbour)
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15 - Ushkanin Islands
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8 - Maloe More
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16 - Vidrino Shoulder
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Table of contents
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Preface
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1
Introduction
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1.1
Phytoplankton pigments as markers for community structure and environmental changes
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1.2 Phytoplankton and pigments in Lake Baikal
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1.3 International interest in paleoclimate and paleolimnologic research in Lake Baikal
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1.4 Outline of the thesis
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2 Materials, methods and site descriptions
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2.1
Lake Baikal
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2.2 Water samples
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2.2.1
Sample collection
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2.2.2 Phytoplankton qualitative and quantitative determination
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2.2.3 HPLC-aided pigment analysis in water samples
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2.2.4 Spectrophotometric data from long-term monitoring
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2.2.5 Fluorescence measurements
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2.3 Sediment traps
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2.3.1
Mooring and sampling
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2.3.2 HPLC-aided pigment analysis in sediment trap materials
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2.3.3 C/N –analysis
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2.4 Sediment
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2.4.1
Description of CONTINENT coring sites
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2.4.2 Short and piston core sampling
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2.4.3 Pigment and C/N-analyses in sediment samples
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2.4.4 Chronography
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2.5 Statistics used
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3 Results
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3.1
Recent spatial and seasonal phytoplankton and pigment distribution
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3.1.1
Regional distribution
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3.1.2 Vertical distribution
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3.1.3 Seasonal dynamics
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3.2 Pigment transfer through the water column and preservation in the surface sediment
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3.2.1
Transfer fluxes and composition of settling material (South 2001-2002)
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3.2.2 Regional and interannual differences of pigment sedimentation
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3.2.3 Degradation and preservation within the surface sediment
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3.3
High-resolution analysis of fossil phytoplankton pigments
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3.3.1
Holocene
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3.3.2 Last Interglacial (Kazantsevo)
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4 Discussion
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4.1
Recent phytoplankton pigments in Lake Baikal as markers for community structure and environmental changes
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4.1.1
Regional phytoplankton and pigment distribution and driving factors
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4.1.2 Pigments as markers for vertical changes during stratification and homothermy
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4.1.3 Seasonal dynamics of phytoplankton and pigments and driving factors
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4.1.4 Remote sensing
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4.1.5 Does a pigment-based approach accurately monitor phytoplankton community and environmental changes in Lake Baikal’s euphotic zone?
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4.2
Phytoplankton pigment transfer through the water column and preservation within the surface sediment
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4.2.1
Fluxes in Lake Baikal compared to marine and freshwater systems
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4.2.2 Degradation processes in the water column of the South basin
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4.2.3 Composition of the settling material in the South basin
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4.2.4 Comparison of the sedimentation and degradation between South and North
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4.2.5 Degradation within the surface sediment
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4.2.6 Do recently buried pigments reflect the phytoplankton standing crop?
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4.3 Reconstruction of past phytoplankton variations
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4.3.1
Holocene
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4.3.2 Last Interglacial (Kazantsevo)
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4.3.3 Do fossil pigments track past phytoplankton community structure and environmental changes?
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5 Conclusion
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List of frequently used abbreviations
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References
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Appendix A Fietz and Nicklisch (2004)
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Appendix B Fietz et al. (submitted)
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Appendix C Supplementary material
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Acknowledgements
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Curriculum vitae
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List of Publications
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Selbständigkeitserklärung
Tables
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Tab. 1. Overview of phytoplankton classes and higher plants along with selected photosynthetic pigments indicating the much greater pigment composition variability in phytoplankton compared to higher plants (after Kohl and Nicklisch 1988, Leavitt et al. 1993, Mackey et al. 1996).
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Tab. 2. Regional variation of diversity, functional groups and of the contribution to total biovolume. Only those species were listed here, which contributed more than 1 % at any of the sites.
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Tab. 3. Molar ratios of Chla vs. marker pigments and their respective statistics calculated by multiple linear regression (A) for the complete data set (July 2001, July 2002 and July 2003) and (B) regionally differentiated.
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Tab. 4. Canonical correlation analysis of set one comprising the environmental variables, and set two comprising total calculated Chla and the respective percentage contribution of each phytoplankton group to the total calculated Chla. See text for calculation of the contributions.
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Tab. 5. As Tab. 2, but for seasonal variation.
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Tab. 6. Major lipophilic photosynthetic pigment fluxes into the 40 m trap and into the trap at the lake bottom. Values for the lake bottom (1400 m) were extrapolated from the curve fittings shown in Fig. 32 and Fig. 33 for all pigments with exponential decrease. For pheophytin a, pyropheophytin a and pheophytin b, which did not show a significant decrease with depth, 40 m and lake bottom values were calculated as averages of all traps. Chla included allo-, epimers and other derivates; pheophorbide a included all pheophorbide a derivates and pheophytin a all pheophytin a derivates.
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Tab. 7. Sedimentation and accumula-tion rates of the dry matter, total nitrogen and atomic C/N ratio in the 40 m trap and at the lake bottom. Values for the lake bottom (1400 m) were extrapolated from the curve fittings shown in Fig. 32 (see also Appendix C - Tab. 2. )
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Tab. 8. Ratios of Chla and its degradation products per organic carbon in the 40 m trap and at the lake bottom. Values for the lake bottom were extrapolated from the curve fittings (Fig. 34, Appendix C - Tab. 4.). Data for chlorophyllide a/ TOC and pheophorbide a/ TOC, which did not show significant depth trends, were calculated as averages of all traps
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Tab. 9. Fluxes and ratios of dry matter, organic carbon and Chlas in (A) the top traps and (B) the bottom traps of the four investigated moorings, and (C) in the top of cores from below the moorings.
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Tab. 10. Dry matter (DM) and TOC fluxes, C/N ratios, and Chlas fluxes and ratios in the core top (0-1 cm) of nine short cores. Medians from triplicate samples were calculated. The Chla concentrations in the respective regions in summer and the sedimentation rates are given to describe the sites. Abbreviations: B Bay - Barguzin Bay, S Delta - Selenga Delta. See Fig. 38 for locations, numbering refers to sites from South to North within a region.
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Tab. 11. Regression models for the decay of TOC/DM and pigments/TOC ratios within the upper, oxidised part of short cores.
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Tab. 12. Comparisons of mean C/N ratios, TOC contents and Chlas/TOC and Chlbs/TOC ratios and their variation within the Holocene until c. 5.1 kyr BP (the maximum reached at Vidrino, cf. Fig. 41). The upper 10 cm (oxidised layer) were excluded. Abbreviations: SD – standard deviation, CV – coefficient of variation.
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Tab. 13. Comparison of mean C/N ratios, TOC contents and Chlas/TOC ratio and Chlbs/TOC ratio and their variation during the Holocene and Kazantsevo Interglacial at Continent Ridge (North basin). Abbreviations: SD – standard deviation, CV – coefficient of variation.
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Table 1. Details of the seven main sample stations in Lake Baikal, where micro-, nano- and picoplankton were counted. Chlorophylls and carotenoids were analysed at these seven and from 21 additional stations.
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Table 2. List of pigments detected by HPLC in Lake Baikal in July 2001. Abundances were described by ”trace“, ”minor“ and ”major“ indicating means of <0.01 µg l-1, 0.01 - 0.03 µg l-1 and >0.03 µg l-1 respectively. Superscripts ”m“ indicate marker pigments of the respective algal classes.
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Table 3. (a) Chla vs. marker pigment ratios calculated by multiple linear regression through the origin and with the CHEMTAX program (n=89). Zea* is the cyanobacterial zeaxanthin only (see text). (b) Marker pigment vs. biovolume ratios calculated by simple linear regression through the origin. The contributions of the Bacillariophyceae plus Chrysophyceae (BacillChrys.) were divided by multiple linear regression based on the amount of total fucoxanthin and the biovolumes of Bacillariophyceae (Bacill.) and Chrysophyceae (Chrys.). (c) Chla vs. marker pigment ratios calculated by multiple linear regression and with the CHEMTAX program including Eustigmatophyceae as fourth group (n=89). Viola* is the eustigmatophycean violaxanthin only (see text).
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Table 1. Pigment content as % per Chla of selected strains isolated from Lake Baikal in July and March 2002. For the Eustigmatophyceae pigment contents in exponential growing cultures are given as well as in batch cultures with high biomasses in parenthesis. Abbrev.: Ant – antheraxanthin, ß-C – ß-carotene, Can – canthaxanthin, Ddx – diadinoxanthin, Dia – diatoxanthin, Ech – echinenon, Fuc – fucoxanthin, Lut – lutein, Neo – neoxanthin, Vau – vaucheriaxanthin, Vio – violaxanthin, Zea – zeaxanthin.
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Table 2. Matrix of similarity coefficients of three Nannochloropsis strains (baik03, baik43, baik85) from Lake Baikal, Nannochloropsis limnetica KR1998/3 from Germany and a sample of Phragmites australis from Germany derived from PCR fingerprinting analysis with primer (GACA)4 and M13 (see Figure 7).
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Table 3. Regional and vertical (July 2001, July 2002 and July 2003) as well as seasonal variation (2002/ 2003) of A) temperature, B) contribution of eukaryotic autotrophic picoplankton, which included Eustigmato-phyceae, to the total phyto-plankton biomass (in %) and C) contribution of Eustig-matophyceae to total Chla (in %). Mean values with 95 % C.I. are listed where normal distributed data sets were considered, and otherwise median values with minimum and maximum were given.
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Appendix C - Tab. 1. List of nano- and microphytoplankton species found in July 2002 and at 2.8 km offshore of Bolshye Koti from May 2002 to April 2003.
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Appendix C - Tab. 2. Regression models to Fig. 32: power (y = a xb) and two first order independent decay (y = a*exp(-bx) + c*exp(-dx)) models of the decrease in the dry matter (y= g m-2) as well as of the TOC and TN percentages (y = %) and the C/N ratio (y=mol mol-1) vs. water column depth; x designates the depth in (m), r² the respective squared correlation coefficient and P the significance; the mooring was deployed in the South basin from March 2001 to July 2002.
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Appendix C - Tab. 3. Regression models to Fig. 33: single exponential (y = a + b * exp(-x/c)), two exponential (y = a*exp(-x/b) + c*exp(-x/d)), two first order independent decay (y = a*exp(-bx) + c*exp(-dx)) models of the decrease of the distinct pigments vs. water column depth; y designate the pigment content in (µmol m-2), x the depth in (m), r² the respective squared correlation coefficient and P the significance; the mooring was deployed in the South basin from March 2001 to July 2002.
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Appendix C - Tab. 4. Regression models to Fig. 34: linear models for the Chla/ TOC, pheophytin a/ TOC and pyropheophytin a/ TOC ratios vs. depth (y= µmol g-1); x designates the depth in (m), r² the respective squared correlation coefficient and P the significance; the mooring was deployed in the South basin from March 2001 to July 2002.
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Appendix C - Tab. 5. Regression models to Fig. 36: single exponential and two exponential models of the Chla flux (representative of all labile pigments) and TOC/DM and Chlas/DM ratios at both sites (South and North) and during both deployment periods (2001-2002 and 2002-2003); x designates the depth in (m) and r² the respective squared correlation coefficient; superscript asterisks mark the significances with * P<0.05, **P < 0.005, and *** P<0.001.
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Appendix C - Tab. 6. Regression models to Fig. 37: linear or exponential models of pigment/TOC ratios (µmol g-1) vs. water depth in the South and North basins. Curve calculations were based on mean values of the two deployment periods to simplify the visualisation; types of models were similar for both deployment periods in the respective (South or North) basin; x designates the depth in (m) and r² the respective squared correlation coefficient; superscript asterisks mark the significances with * P<0.01, **P < 0.005, and *** P<0.001; N designate rate constant significantly (at 95 % CI) different to that of the North, idem S to South, and idem SD to Selenga Delta.
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Appendix C - Tab. 7. Regression models to Fig. 40: linear and exponential models for TOC/DM ratios (mg g-1 DM) and pigment/TOC ratios (µmol g-1) vs. depth of the oxidised layer of the surface sediment; x designates the depth in (m) and r² the respective squared correlation coefficient; superscript asterisks mark the significances with * P<0.01, **P < 0.005, and *** P<0.001; N designate rate constant significantly (at 95 % CI) different to that of the North, S to South, and SD to Selenga Delta.
Images
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Fig. 1. Phyto-plankton pigment production in re-lation to energy capture, grazing, sedimentation, and burial.
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Fig. 2. Methods used for investigating phytoplankton and their pigments in marine systems; adapted from Jeffrey et al. (1999).
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Fig. 3. Simplified scheme of Chla degradation. In most of the chlorophyll degradation products, the tetrapyrrol macrocycle remains intact. Magnesium is removed from chlorophylls in the presence of dilute acids (gut passage) and high-light intensities (photooxidation). One of these degradation products is, for instance, pheophytin, where the central Mg-atom is replaced by two H+. Chlorophyllide arises by dephytylation of Chla and Chlb by the ubiquitous catabolic enzyme, chlorophyllase. Chlc is already chlorophyllide-like and does not undergo this process. Pheophorbide arises by removing the central Mg-atom from a chlorophyllide (Llewellyn et al. 1990, Leavitt 1993, Matile et al. 1999). Steryl chlorin esters (SCE) are formed by esterification from chlorophyll degradation products during zooplankton gut passage, and are relatively stable compared to chlorophylls and other degradation products; however their formation and sedimentation processes are not clear at present (King and Repeta 1991, Prowse and Maxwell 1991, Talbot et al. 1999, Soma et al. 2001b).
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Fig. 4. Example of carotenoid (fucoxanthin) degradation by herbivore grazers (metabolism) and after sedimentation: Zooplankton herbivores and other heterotrophs hydrolyse carotenoid esters to free alcohols (fucoxanthin to fucoxanthinol) in the water column. Dehydration and epoxide rearrangement occur (fucoxanthinol to isofucoxanthinol 5´-dehydrate) in the surface sediment after burial (Repeta and Gagosian 1982, -1984).
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Fig. 5. Pathway of pigment production, transformation and degradation within the water column of a lake; scheme adapted from Leavitt and Hudgson (2001).
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Fig. 6. Regular phytoplankton monitoring in Lake Baikal (scan from Galazii 1993).
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Fig. 7. Map of Lake Baikal locating relevant regions for the present study and impressions of the respective surrounding regions.
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Fig. 8. Half-graben morphology from West to East: Maloe More, Olkhon Island, Central basin; from Kozhova and Izmest’eva 1998.
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Fig. 9. Research vessel “Vereshchagin” (left) and on board of the research vessel “M.M. Kozhov” (Bolshye Koti in the background) (right).
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Fig. 10. FluoroProbe vertical measurements.
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Fig. 11. Sediment trap deployment (left) and top traps after recovery (right)
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Fig. 12. Map locating the coring sites with lithological descriptions of the analysed segments.
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Fig. 13. Core CON01-603-3, segment 458-590 cm: shift from grey terrigenic material (glacial periods) towards brownish diatom-rich material (warm period).
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Fig. 14. Recovery of the c. 11 m long piston cores. Fotos from J. Klump (http://continent.gfz-potsdam.de/html/gallery).
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Fig. 15. Density along core CON01-603-2 used for dating, for pollen and for diatom analyses and along core CON01-603-3 used for pigment analyses. Both cores were taken from the same site (Continent Ridge) in the North basin. The highlighted rectangle marks the segment where photosynthetic pigments were analysed. Pollen and diatom analyses showed that the Kazantsevo Interglacial in core CON01-603-2 was between 6.10 m to 7.20 m (Granoszewski et al. 2005, Rioual and Mackay 2005). According to the density, this section corresponded to the section between 4.80 m and 5.60 m in core CON01-603-3.
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Fig. 16. Regional variability of temperature, Chla, carotenoids, and biovolumes; bars represent means with 95 % C.I. and boxes medians with interquartile ranges (25-75 %). A map of Lake Baikal showing the sampling sites is given for orientation. The APP biovolume vs. total phytoplankton biovolume ratios as well as the sum of carotenoids vs. Chla are given as percentages. The number of samples (n) for temperature and pigments was 43 - 52 in each of the three open basins and at Selenga Delta (Sdelta), 22 at Barguzin Bay (Bbay) and 6 at Academician Ridge (Aridge) and Maloe More (MM). The number of samples (n) for biovolumes was 9 - 12 in each of the three open basins and Selenga Delta.
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Fig. 17. Map of Chla (left) and temperature (right) by nearest neighbouring interpolation from direct water samples taken from surface waters (0.5-5 m).
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Fig. 18. Horizontal Chla (green) and temperature (blue) profiles by underway measurements (c. 3 m water depth) in July 2002 (red) and July 2003 (yellow).
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Fig. 19. Regional variability of the marker pigment concentrations for (A) Bacillariophyceae+ Chrysophyceae (fucoxanthin and Chlc), (B) for Chlorophyta (lutein and Chlb), (C) for Cryptophyta (alloxanthin) and for Eustigmatophyceae (violaxanthin), and (D) for cyanobacterial APP (zeaxanthin and ß-carotene). Combined data set 2001-2003 (July) was used for the calculations. Error bars represent a 95 % C.I. Abbreviations: SDelta – Selenga Delta, BBay – Barguzin Bay, ARidge – Academician Ridge, MM – Maloe More. Lines do not indicate trends between two neighboured points, but serve to visualise regional differences.
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Fig. 20. Discriminance analysis separating the seven regions according to the pigment distri-bution. See Fig. 19 for abbreviations.
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Fig. 21. Contribution of main chemotaxonomic phytoplankton groups to total Chla. Abbreviations: ARidge – Academician Ridge, Bacill.Chrys. – Bacillariophyceae+Chrysophyceae, BBay – Barguzin Bay, Cyanob. – cyanobac-terial, Eustigmato. – Eu-stigmatophyceae, SDelta – Selenga Delta.
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Fig. 22. Interannual variability of Chlorophylls: (A) Chla; (B) Chlb, and (C) Chlc. Error bars represent a 95 % C.I. Abbreviation: S Delta – Selenga Delta.
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Fig. 23. Interannual variability of (A) eukaryotic and cyano-bacterial APP biovolume; (B) nano- and microphytoplankton biovolume; (C) contribution of chemotaxonomic groups to total Chla (see text for calculation); Abbreviations: Bacillarioph. – Bacillariophyceae, BacillChrys – Bacillariophyceae+Chrysophycea, Cyanob. APP – cyanobacterial APP, Eukary APP – eukaryotic APP, Eustigmato. – Eustigmato-phyceae, S Delta – Selenga Delta.
Note: see Appendix B for having considered Eustigmatophyceae to be a common member of the Baikalian phytoplankton.
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Fig. 24. Temperature and Chla depth profiles (0-250 m) from January 2001 to December 2003 showing mixing and stratification over the season and regions. Values at the time of ice break-up (April) have been interpolated. From Mid-April to end of August 2003 data below 50 m were not available (hatched rectangle).
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Fig. 25. Vertical variability of temperature, pigments (see Fig. 16 for bars and boxes). The APP biovolume vs. total phytoplankton biovolume ratios as well as the sum of carotenoids vs. Chla are given as percentages. The number of samples (n) for temperature and pigments was 21 at 0.5 m, 110 at 5 m, 43 at 10-20 m, 36 at 20-30 m and 6 at 45-85 m. The number of samples (n) for biovolumes was 10 - 18 at each depth.
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Fig. 26. Depth profiles (0-30 m) of (A) temperature, (B) Chla, and (C) conductivity.
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Fig. 27. Chla and temperature depth profiles assessed with the submersible fluorimeter in July 2002. Transect from near-shore to off-shore (from Barguzin Bay to eastern shore of Olkhon Island).
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Fig. 28. South to North transsects of Chla and temperature depth profiles in July 2002 (red circles, profiles on left side) and July 2003 (yellow circles, profiles on right side).
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Fig. 29. Depth profiles of Chla (green lines) and temperature (blue lines) in August 2002. See Fig. 28 for legend, whereby in August maximum measured depth was 100 m and maximum temperatures were 18°, 16° and 14° C in the South (including Selenga Delta), Centre and North, respectively.
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Fig. 30. Seasonal monitoring during May 2002 to June 2003 (at the long-term monitoring station of SRIB 2.8 offshore from Bolshye Koti, South Basin) of temperature, Secchi depth, biovolumes and selected pigments.(A) temperature at 5 m water depth and Chla integrated over 40 m water depth (the suggested euphotic zone) from January 2001 to December 2003. The highlighted area designate the period of the intensive monitoring, detailed in section (B): Intensive monitoring from May 2002 to June 2003. On the left side: Secchi depth, temperature, total APP biovolume (epifluorescence microscopic spot counts + light microscopic estimation), total nano- and microphytoplankton (NMP biovolume and cell abundance), reciprocal Shannon-Wiener diversity index, and composition of the phytoplankton community based on their share to total Chla (see text for calculations). On the right side: total Chla as well as marker pigments and biovolumes of the respective phytoplankton groups.
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Fig. 31. Typical fluorescence (410 nm / 670 nm excitation / detection wavelength, left side) and absorption (440 nm) chromatograms (right side) of (A) the water column, (B) the 40 m trap, (C) the 1400 m trap and (D) the top sediment slice below the mooring. Numbering of the peaks confers to pigments listed in Tab 6.
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Fig. 32. Vertical profiles of settling particles in the water column, showing (A) total mass fluxes (dw, g m-2), (B) organic carbon (C %), (C) total nitrogen (N %) and (D) atomic C/N ratios as well as vertical profiles of Chla, and its degradation products (µmol m-2). The traps were deployed for about 16 months. The respective regression equation and their coefficient of determinations (r²) are reported in Appendix C - Tab. 2, and Appendix C - Tab. 3. Abbreviations: Chlida – chlorophyllid a, Phbida – pheophorbide a, Pha – pheophytin a, PyroPha – pyropheophytin a.
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Fig. 33. Depth profiles of marker pigments from Bacillariophyceae+Chrysophyceae (A), Chlorophyta (B), cyanobacterial picoplankton (C), Eustigmatophyceae and Cryptophyta (D). The traps were deployed for about 16 months. The respective regression equations and their coefficients of determination (r²) are reported inAppendix C - Tab. 3. Abbreviations: Allo – alloxanthin, ß-car – ß-carotene, Diato – diatoxanthin, Fuco – fucoxanthin, Phb – pheophytin b, Viola – violaxanthin, Zea – zeaxanthin.
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Fig. 34. Depth profiles of Chla/ TOC ratio (Chla/C), chlorophyllide a/ TOC ratio (Chlida/C), pheophorbide a/ TOC ratio (Phbida/C), pheophytin a/ TOC ratio (Pha/C) and pyropheophytin a/ TOC (PyroPha/C). The respective regression equations and their coefficient of determination (r²) are reported in Appendix C - Tab. >4.
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Fig. 35. Contribution to total Chla of the dominant phytoplankton groups in the sediment traps and in the surface sediment. Estimates based on the marker pigment vs. Chla ratios calculated by multiple linear regession (cf. Fietz and Nicklisch 2004, Appendix A for calculations). Abbreviations: BacChrys – Bacillariophyceae+Chrysophyceae, Chloro – Chlorophyceae, Cyano – cyanobacterial picoplankton.
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Fig. 36. Chla fluxes as as well as TOC/DM and Chlas/DM ratios for both sites and both investigated deployment periods. The respective regression equations and their coefficient of determination (r²) are reported in Appendix C - Tab. 5. The water depth at the mooring site in the North and South basins were c. 900 m and 1400 m, respectively; the upper traps of the North mooring 2001-2002 were lost due to technical disturbances.
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Fig. 37. Pigment/TOC ratios vs. depth through the water column of the South (A) and North (B) basins (see Fig.1 for locations). Curve calculations were based on mean values of the two deployment periods (2001-2002 and 2002-2003). The regression functions are given in Appendix C - Tab. 6. Mean values over the 15 (South) or 9 (North) traps were plotted for pigment/TOC ratios, where no significant decay or formation was found.
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Fig. 38. Composition of (A) Chlas and (B) carotenoids within the uppermost centimetre of the surface sediment gathered from nine coring sites across Lake Baikal in July 2001 and July 2002. Stars mark the coring sites of the associated composition diagrams.
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Fig. 39. Transition from upper oxydised layer (brownish) to the lower reduced layer (grey) of a short core from Continent Ridge (North basin). Core section span from core top (0 cm) to 25 cm depth.
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Fig. 40. TOC/DM ratio and pigment/TOC ratios vs. depth in the surface sediments of the (A) South basin, (B) North basin and (C) Selenga Delta. The regression functions are given in Appendix C - Tab. 7. Mean values over the 15 (South, Selenga Delta) or 12 (North) surface sediment slices were plotted for pigment/TOC ratios, where no significant decay or formation was found.
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Fig. 41. Holocene high-resolution analysis of lipophilic photosynthetic pigments and organic carbon at ´Vidrino´ coring site (South basin). Abbreviations: BP – before present, Chlas – sum of all forms of all chlorophyll a degradation products (same for Chlbs), TOC – total organic carbon.
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Fig. 42. Holocene high-resolution analysis of photosynthetic pigments and organic carbon at ´Posolski´ coring site (Selenga Delta). See Fig. 41 for abbreviations.
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Fig. 43. Holocene high resolution analysis of photosynthetic pigments and organic carbon at ´Continent Ridge´ coring site (North basin). See Fig. 41 for dating and abbreviations.
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Fig. 44. Comparison of temporal changes at three coring sites ´Vidrino´, ´Posolski´, and ´Continent Ridge´ for TOC content, Chlas/TOC ratio, Chlbs/Chlas ratio, and Chlc/Chlas ratio. See Fig. 41, Fig. 42, and Fig. 43 for dated data points and abbreviations. The periods between the dated depths were linearly interpolated. For TOC content, Chlas/TOC ratio, and Chlbs/Chlas ratio averages of two contiguous data points were plotted in order to minimise a possible analytical error; each peak was then supported by several data points. Single peaks for high-resolution contexts can be found in Fig. 41, Fig. 42, and Fig. 43. For Chlc/Chlas ratio data were not averaged because most peaks were detached (cf. Fig. 41-Fig. 43).
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Fig. 45. Typical HPLC-chromatogram of the Kazantsevo Interglacial showing the retention times of the main chlorophyll degradation products pheophorbide, pheophytin, pyropheophytin and steryl chlorin ester (SCE; refer to Fig. 3 for degradation pathway).
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Fig. 46. High resolution analysis of lipophilic photosynthetic pigments and organic carbon during the Kazantsevo Interglacial at ´Continent Ridge´ (North basin). See Method section for dating, and Fig. 41 for abbreviations. SCEs (steryl chlorin esters) were included within the term ´Chlas´ and ´Chlbs´.
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Fig. 47. High resolution analysis of different forms of pheopigments and SCEs (steryl chlorin esters) eluting at different retention times during (A) the Holocene (0-70 cm sediment depth) and (B) Kazantsevo plus transitions (440-580 cm sediment depth) at Continent Ridge (North basin). The numbers reflect the eluting time of the respective pheopigment or SCE form. Abbreviations: bida – pheophorbide a, Pha – pheophytin a, Pyroa – pyropheophytin a.
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Fig. 48. Temporal changes in perylene concentrations in the (A) Holocene (three sites) and (B) in the Kazantsevo Interglacial (one site). Perylene (in relative units) was normalised to one, whereby one is the highest content of perylene found within the respective core. The highest content of perylene in the Vidrino core was 25 fold higher than that of the Continent Ridge core and three fold higher than that of the Posolski core.
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Fig. 49. Horizontal fluorescence transects showing total Chla (black), contribution of Bacillariophyceae+Chrysophyceae+Pyrrophyta (brown), Chlorophyta (green) and cyanobacteria (blue). Data provided by A. Nicklisch (HU Berlin, Germany) from unpublished data sets.
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Fig. 50. FluoroProbe depth profiles (lines) showing total Chla as well ascontributions of selected phytoplankton groups to the total Chla. Measured (by HPLC) total Chla and contributions are given as well as the estimated total Chla based on marker pigments (see Appendix A and chapter 3.1 for marker pigment based calculations). Letters in quotations refer to Fig. 18. Data provided by A. Nicklisch (HU Berlin, Germany; from unpublished data set).
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Fig. 51. Quasi-true colour SeaWifs for 6 August 2001 (Heim pers. comm.). The blue colour indicate more oligotrophic water; turquoise colouring indicate cyanobacterial picoplankton-rich water; yellow and brownish colours indicate terrigenous and more productive regions.
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Fig. 52. SeaWiFS Chla time series (June-September 2001and 2002). Diamonds represent the ultra-oligotriophic gyre in which the northern mooring was situated; rectangles represent the Continent Ridge coring site; triangles represent Academician Ridge; crosses represent the Central basin; stars represent the Posolski area (Selenga Delta); circles represent the central South basin in which the southern mooring was situated. (B. Heim pers. comm.)
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Fig. 53. Schematic diagram of degradation in the water column from the euphotic zone to the sediment surface.
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Figure 1. Diagram of Lake Baikal locating the sample stations for pigment analyses.
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Figure 2. Boxplots of the biovolume of (a) total phytoplankton (>3µm) and (b) total APP. Boxes represent the median with interquartile ranges (25% to 75%), minima and maxima and extremes (asterisk). Variances aroused from combining different depths and and stations within each basin.
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Figure 3. Relative algal class distribution determined by light- and epifluorescence microscopy: (a) phytoplankton (>3µm) and (b) APP. Abbreviations: Bacillarioph. = Bacillariophyceae, Chrysoph. = Chrysophyceae, Dinoph. = Dinophyceae, Cryptoph. = Cryptophyceae, Chloroph. = Chlorophyceae, Cyanob. = Cyanobacteria, Cy APP = cyanobacterial APP, Eu APP = eucaryotic APP
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Figure 4. Chla concentration in Lake Baikal in July 2001. Error bars represent a 95% C.I., n=92.
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Figure 5. Contribution of the different phytoplankton groups - considering all samples, which were also microscopi-cally analysed – (a) to the total Chla, based on fac-tors calculated by MLR (shown in Table 3a), (b) to the total Chla, based on factors calculated by CHEMTAX (shown in Table 3a), (c) to the total biovolume based on fac-tors calculated by simple linear regres-sion (shown in Table 3b), (d) to the total biovolume based on cell counts ta-king into account the phytoplankton (>3µm) and the APP (see also Fig. 2 & 3). Abbreviations: Bacill. = Ba-cillariophyceae, Chrys. = Chrysophy-ceae, Chloroph. = Chlorophyceae, Cyanob. = Cyanobacteria.
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Figure 6. Comparison of Chla vs. marker pigment ratios from European strains, Baikal strains and Baikal water samples: (a) Chla vs. zeaxanthin: Comparison of 5 cyanobacterial APP strains from European lakes, new isolated cyanobacterial APP strains from Lake Baikal and Baikal water. The cyanobacterial APP of Lake Baikal were differentiated into Phycocyanin (PC) and Phycoerythrin (PE) containing cells. Baikal cultures that experienced nutrient deficiency or high light stress during growth were reported too. (b) Chla vs. marker pigments for Chlorophyceae: Comparison of 15 Chlorophyceae strains from European lakes, new isolated Chlorophyceae strains of Lake Baikal (chlorophycean APP and Monoraphidium sp.), new isolated Eustigmatophyceae and Baikal water samples.
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Figure 1. Light microscopic pictures (interference contrast) of new strains of Nannochloropsis and a chlorophycean picoplankton strain (baik90) isolated from Lake Baikal. (a) baik03 with giant cells, (b) baik85, (c) baik90. Scale bar, 10 µm.
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Figure 2. Epifluorescent microscopic pictures of (a) autofluorescence of chloroplasts, (b) DAPI-staining and (c) staining with Fluorescent Brightner 28 (Calcofluor White) – two cells show a stained cell wall and the others the red autofluorescence of chloroplasts. Scale bar, 10 µm
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Figure 3. Ultrastructure of the Nannochloropsis strains isolated from Lake Baikal. (a) TEM images of strain baik03, (b) strain baik03 with the chloroplast endoplasmatic reticulum connected to the nuclear envelope (arrow), (c) strain baik43 with a lamellate vesicle, (d) a cell with lipid droplets. Abbreviations: C – chloroplast, G – Golgi body, LV – lamellate vesicle, L –lipid droplets, M – mitochondrium, N – nucleus, PG – plastoglobulus, PY – pyrenoid-like bodies , cm – cell membrane, cw – cell wall, cwp – cell wall papilla. Scale bar, 1 µm.
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Figure 4. Strain baik43 cells with badly fixed thick cell walls (a and b) and with a germinating (assumed resting) cell (c). Abbreviations: B – bacteria cell. Scale bar, 1 µm
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Figure 5. Specific growth rates of the new strains of Nannochloropsis limnetica at 10 and 15° in comparison to the reference strain KR 1998/3 and a chloro-phycean picoplankter (baik90). C.I.: confi-dence interval
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Figure 6. Fluorescence and in vivo absorption cross section of different strains isolated from Lake Baikal; (A) Fluorescence of Bacillariophyceae (strains baik03, baik43 and baik85) and Chlorophyceae, (B) Fluorescence of Eustigmatophyceae and Xanthophyceae. (C) Absorption of (strains baik03, baik43 and baik85) Bacillariophyceae and Chlorophyceae, (D) Absorption of Eustigmatophyceae and Xanthophyceae. Results are means for 5 to 20 samples taken at different times during culturing.
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Figure 7. PCR fingerprints of Nanochloropsis strains, primed with (GACA). Lane1 and 7: 1 kb DNA-ladder, lane 2-4 from the left to the right: strains baik03, baik43 and baik85, lane5: KR1998/3, lane 6: Phragmites australis.
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