Prediction of Holocene Mercury Accumulation Trends by Combining Palynological and Geochemical Records of Lake Sediments (Black Forest, Germany)
Abstract
:1. Introduction
2. Materials and Methods
2.1. Site Description
2.1.1. Coring
2.1.2. Chronology
2.2. Chemical Analysis
2.2.1. Carbon, Nitrogen and Sulphur
2.2.2. Major and Trace Elements
2.2.3. Mercury
2.3. Sedimentation Rates
2.4. Statistical Treatment
3. Results
3.1. Vegetation Changes and Land Use Practices
3.2. Holocene Records of Mercury and Lead Concentrations
3.3. Variation in Sediment Geochemistry Revealed from Principal Component Analysis
3.4. Prediction of Factors Controlling Mercury Accumulation Using Stepwise Regression Analysis
4. Discussion
4.1. Evolution of Mercury Concentration and Accumulation
4.2. Environmental Processes Controlling Sediment Geochemistry
4.3. Chronology of Factors Controlling Mercury Accumulation
4.3.1. Declining Soil Erosion in an Establishing Hazel-Dominated Shrubland (Section I)
4.3.2. Steady Fluxes of Soil Organic Matter in an Oak-Dominated Forest (Section II)
4.3.3. Warm Period Caused Enhanced Mercury Uptake in Lakes Surrounded by a Mixed Forest (Section III)
4.3.4. Distinct Traces of Grazing and Agriculture in a Mixed Forest (Section IV)
4.3.5. Pollution from Mining and Industrial Activities in a Mixed Forest (Section V)
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Schurmsee | Glaswaldsee | ||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Proxies | CP1 | CP2 | CP3 | CP4 | CP5 | CP6 | Proxies | CP1 | CP2 | CP3 | CP4 | CP5 | CP6 |
C | 0.91 | 0.15 | 0.11 | 0.17 | −0.09 | 0.18 | C | −0.83 | −0.26 | 0.00 | 0.32 | 0.04 | −0.23 |
N | 0.87 | 0.25 | 0.20 | 0.11 | 0.26 | 0.17 | N | −0.74 | −0.14 | 0.07 | 0.28 | −0.55 | −0.03 |
Zr | −0.83 | 0.41 | −0.05 | −0.18 | 0.08 | −0.09 | Zr | 0.86 | 0.19 | 0.02 | 0.06 | 0.10 | 0.25 |
Al | −0.89 | 0.27 | 0.24 | 0.01 | 0.08 | −0.06 | Al | 0.83 | 0.08 | 0.31 | −0.10 | −0.08 | −0.32 |
Ti | −0.79 | 0.42 | 0.33 | −0.02 | 0.09 | 0.01 | Ti | 0.80 | 0.30 | 0.46 | 0.03 | 0.01 | −0.13 |
Mn | 0.59 | 0.01 | 0.55 | 0.19 | 0.27 | 0.07 | |||||||
rye | −0.13 | 0.95 | 0.10 | −0.09 | 0.04 | −0.02 | rye | 0.12 | 0.92 | 0.08 | −0.07 | −0.10 | 0.01 |
ribwort | −0.14 | 0.89 | 0.25 | −0.07 | 0.11 | −0.04 | ribwort | 0.21 | 0.86 | 0.35 | 0.00 | 0.02 | 0.02 |
Pb | 0.00 | 0.91 | 0.18 | −0.10 | 0.05 | −0.02 | Pb | 0.13 | 0.88 | 0.05 | −0.20 | −0.20 | 0.06 |
spruce | −0.13 | 0.90 | −0.03 | −0.17 | 0.27 | 0.02 | spruce | 0.15 | 0.67 | 0.59 | −0.05 | 0.14 | 0.00 |
Mn | 0.05 | −0.82 | −0.35 | −0.19 | 0.12 | 0.12 | charcoal | 0.17 | 0.67 | 0.14 | 0.31 | 0.10 | 0.17 |
beech | 0.03 | 0.12 | 0.91 | −0.08 | 0.07 | −0.06 | beech | 0.22 | 0.17 | 0.85 | −0.24 | −0.11 | −0.18 |
fir | 0.02 | 0.22 | 0.83 | 0.03 | 0.03 | 0.06 | fir | 0.17 | 0.20 | 0.84 | −0.21 | −0.01 | −0.22 |
hazel | 0.16 | −0.36 | −0.65 | 0.13 | −0.21 | −0.30 | hazel | 0.03 | −0.29 | −0.80 | −0.23 | 0.25 | 0.16 |
oak | 0.25 | −0.03 | −0.21 | 0.83 | 0.04 | 0.21 | oak | −0.42 | −0.08 | −0.45 | 0.68 | −0.27 | 0.05 |
Fe | −0.02 | 0.39 | −0.39 | −0.60 | 0.25 | 0.33 | |||||||
C:N | 0.13 | −0.27 | −0.33 | 0.11 | −0.84 | 0.00 | C:N | 0.08 | −0.16 | −0.14 | −0.05 | 0.91 | −0.25 |
Zn | 0.21 | −0.12 | −0.35 | 0.43 | 0.55 | 0.40 | |||||||
Cu | 0.37 | −0.16 | 0.17 | 0.13 | 0.05 | 0.80 | Cu | −0.13 | 0.04 | −0.16 | 0.00 | −0.22 | 0.90 |
Zn | 0.04 | 0.01 | −0.24 | 0.16 | −0.19 | 0.86 | |||||||
Fe | 0.38 | 0.20 | −0.03 | −0.17 | 0.23 | 0.79 | |||||||
eigv. | 3.15 | 4.04 | 2.87 | 1.50 | 1.29 | 1.12 | eigv. | 4.19 | 3.70 | 3.48 | 1.05 | 1.59 | 2.62 |
var. | 20 | 25 | 18 | 9 | 8 | 7 | var. | 22 | 19 | 18 | 6 | 8 | 14 |
CP1 | CP2 | CP3 | CP4 | CP5 | CP6 | R | Error | |
---|---|---|---|---|---|---|---|---|
model 1a SCHURMSEE | ||||||||
reg. coef. | −0.20 | 0.73 | 0.11 | −0.26 | 0.33 | 0.08 | 0.88 | 0.49 |
t-value | −4.55 | 16.83 | 2.47 | −6.02 | 7.50 | 1.90 | ||
p-value | <0.001 | <0.001 | <0.05 | <0.001 | <0.001 | <0.1 | ||
model 1b SCHURMSEE | ||||||||
reg. coef. | −0.21 | 0.67 | 0.36 | −0.07 | 0.37 | − | 0.87 | 0.50 |
t-value | −4.59 | 14.90 | 8.16 | −1.62 | 8.25 | − | ||
p-value | <0.001 | <0.001 | <0.001 | <0.1 | <0.001 | − | ||
model 2a GLASWALDSEE | ||||||||
reg. coef. | − | 0.68 | 0.44 | − | 0.11 | − | 0.82 | 0.59 |
t-value | − | 10.81 | 6.92 | − | 1.74 | − | ||
p-value | − | <0.001 | <0.001 | − | <0.1 | − | ||
model 2b GLASWALDSEE | ||||||||
reg. coef. | − | 0.70 | 0.09 | −0.17 | − | − | 0.80 | 0.62 |
t-value | − | 10.50 | 5.06 | −2.55 | − | − | ||
p-value | − | <0.001 | <0.001 | <0.05 | − | − |
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Schütze, M.; Tserendorj, G.; Pérez-Rodríguez, M.; Rösch, M.; Biester, H. Prediction of Holocene Mercury Accumulation Trends by Combining Palynological and Geochemical Records of Lake Sediments (Black Forest, Germany). Geosciences 2018, 8, 358. https://doi.org/10.3390/geosciences8100358
Schütze M, Tserendorj G, Pérez-Rodríguez M, Rösch M, Biester H. Prediction of Holocene Mercury Accumulation Trends by Combining Palynological and Geochemical Records of Lake Sediments (Black Forest, Germany). Geosciences. 2018; 8(10):358. https://doi.org/10.3390/geosciences8100358
Chicago/Turabian StyleSchütze, Martin, Gegeensuvd Tserendorj, Marta Pérez-Rodríguez, Manfred Rösch, and Harald Biester. 2018. "Prediction of Holocene Mercury Accumulation Trends by Combining Palynological and Geochemical Records of Lake Sediments (Black Forest, Germany)" Geosciences 8, no. 10: 358. https://doi.org/10.3390/geosciences8100358