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- Bigler, Christian, 1972-
(författare)
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Diatoms as indicators of Holocene climate and environmental change in northern Sweden
- 2001
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The objective of the thesis was to explore the potential of diatoms (Bacillariophyceae) as indicators of Holocene climate and environmental change in northern Sweden (Abisko region, 68°21'N, 18°49'E). A modern surface-sediment calibration set including 100 lakes was developed and lake-water pH, sedimentary organic content (assessed by loss-on-ignition) and temperature were identified as most powerful environmental variables explaining the variance within the diatom assemblages. Transfer functions based on unimodal species response models (WA-PLS) were developed for lake-water pH and mean July air temperature (July T), yielding coefficients of determination of 0.77 and 0.70, and prediction errors based on leave-one-out cross-validation of 0.19 pH units and 0.96 °C for lake-water pH and July T, respectively. The transfer functions were validated with monitoring data covering two open-water seasons (lake-water pH) and meteorological records covering the 20th century (July T). The good agreement between diatom-based inferences and measured monitoring data confirmed the prediction ability of the developed transfer functions. Analysing a Holocene sediment core from a lake nearby Abisko (Vuoskkujávri), diatoms infer a linearly decreasing July T trend (1.5 °C) since 6,000 cal. BP, which compares well with inferences based on chironomids and pollen from the same sediment core. The lake-water pH inference shows a pattern of moderate natural acidification (c. 0.5 pH units) since the early Holocene, reaching present-day pH values at c. 5,000 cal. BP. By fitting fossil diatom samples to the modern calibration set by means of residual distance assessment within canonical correspondence analysis (CCA), the early Holocene (between 10,600 and 6,000 cal. BP) was identified as a problematic time-period for diatom-based inferences and, consequently, reconstructions during this period are tentative. Pollen-based inferences also show 'poor' fit between 10,600 and 7,500 cal. BP and chironomids probably provide the most reliable July T reconstruction at Vuoskkujávri, with 'poor' fit only during the initial part of the Holocene (between 10,600 and 10,250 cal. BP). Possible factors confounding diatom-based July T inferences were investigated. Using detrended CCA (DCCA), Holocene sediment sequences from five lakes indicate that during the early Holocene, mainly physical factors such as high minerogenic erosion rates, high temperature and low light availability may have regulated diatom assemblages, favouring Fragilaria species. In all five lakes, diatom assemblages developed in a directional manner, but timing and scale of development differed substantially between lakes. The differences are attributed primarily to the geological properties of the lake catchments (with strong effects on lake-water pH), but other factors such as climatic change, vegetation, hydrologic setting and in-lake processes appear to regulate diatom communities in each lake differently. The influence of long-term natural acidification on diatom assemblages progressively declined during the Holocene with corresponding increase of the influence of climatic factors.
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| 2. |
- Bindler, Richard, et al.
(författare)
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Pre-industrial atmospheric pollution: Was it important for the pH of acid-sensitive Swedish lakes?
- 2002
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Ingår i: Ambio. - 0044-7447. ; 31:6, s. 460-465
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Tidskriftsartikel (refereegranskat)abstract
- Acid rain has caused extensive surface water acidification in Sweden since the mid-20(th) century. Sulfur emissions from fossil-fuel burning and metal production were the main sources of acid deposition. In the public consciousness acid deposition is strongly associated with the industrial period, in particular the last 50 years. However, studies of lake-water pH development and atmospheric pollution, based on analyses of lake sediment deposits, have shown the importance of a long-term perspective. Here, we present a conceptual argument, using the sediment record, that large-scale atmospheric acid deposition has impacted the environment since at least Medieval times. Sulfur sources were the pre-industrial mining and metal industries that produced silver, lead and other metals from sulfide ores. This early excess sulfur deposition in southern Sweden did not cause surface water acidification; on the contrary, it contributed to alkalization, i.e. increased pH and productivity of the lakes. Suggested mechanisms are that the excess sulfur caused enhanced cation exchange in catchment soils, and that it altered iron-phosphorus cycling in the lakes, which released phosphorus and increased lake productivity
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| 4. |
- Dåbakk, Eigil, et al.
(författare)
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Inferring lake water chemistry from filtered seston using NIR spectrometry
- 2000
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Ingår i: Water Research. ; 34:5, s. 1666-72
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Tidskriftsartikel (refereegranskat)abstract
- Near-infrared spectrometry (NIR) is a rapid, inexpensive and reagent-free technique, widely used in industry in areas such as quality control and process management. The technique has great potential for environmental monitoring of aqueous systems. This study assesses relationships, using PLS regression, between NIR spectra of seston collected on glass fibre filters and the following measured lake water parameters: total organic carbon (TOC), total phosphorus (TP), Abs420 and pH. Water samples were collected from 271 oligotrophic lakes during autumn 1995. The predictive model for TOC explained 68% of the variance (SEP=2.1 mg L-1, range 14.9 mg L-1), and that for colour 71% (SEP=0.04 A, range 0.36 A), while the explained variances for pH and TP were 72% (SEP=0.36 μg L-1, range 3.13 μg L-1) and 45% (SEP=4 μg L-1, range 41 μg L-1), respectively. A model correlating NIR spectra and the actual amount of phosphorus in the seston captured on filters explained 86% of the variance (SEP=0.044 μg/filter, range 0.47). Several pretreatments and regression techniques were used in an attempt to enhance modeling performance. However, straightforward PLS on raw data performed best in all cases.
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