Phytoplankton species composition is strongly affected by seasons, which should be taken into account in palaeolimnological studies. Although chrysophyte cysts and diatoms are widely used as palaeobioindicators in palaeolimnological studies, only recently have attempts been made to use their modern deposition from sediment trap data to provide more detailed, seasonal-based environmental reconstructions. In this study sediment traps were used to record seasonality of chrysophyte cysts and diatoms during two climatically different years 2009 and 2010 in an annually laminated Lake Nautajärvi, Finland, and this seasonal data was then compared with the fossil record derived from the surface sediment of the lake. The overall changes in cyst and diatom assemblages between years and seasons are subtle. For both groups, no clear connection to any particular season could be detected in the sediment surface. Despite the climatological differences between the study years, the inter-annual accumulation rates of both algal groups were surprisingly similar, whereas the intra-annual accumulation rates differed substantially. This and the high amount of taxa occurring during all seasons in the trap samples implies that primary producers are more dependent on prevailing seasonal limnological conditions than on rapid, shortly lived episodes. Redundancy analysis (RDA) revealed that chrysophyte cyst assemblages from the spring sediment trap are mainly controlled by the spring discharge intensity, a surrogate variable of spring weather conditions, whereas precipitation and air temperature have the strongest impact on the summer assemblages. However, only discharge explains statistically significantly the variance in the cyst data. Precipitation and air temperature have the strongest impact on the diatom summer samples, whereas the spring sediment trap sample of the snowy and harsh winter of 2010 was strongly correlated with the spring discharge. However, none of the measured environmental variables explains the variance in the diatom data statistically significantly. The similarity between the algae found in the sediment traps and surface sediment sample suggests that within small and shallow lakes without any extreme environmental settings the surface sediment sample represents well the lake's overall algal composition and can thus be used in palaeolimnological studies.
Acid sulphate soil and sulphide-bearing sediments cause various challenges in construction projects and land use planning, as well as harmful environmental effects. Fine-grained sulphide sediments were mainly formed in coastal areas during the Litorina Sea water phase at approximately 7000 BP in the capital region of Finland, but not all these sediments contain sulphide clay. In this study, environmental and material property variables related to the depositional conditions of sulphide clay were selected for statistical analyses to find their association with the occurrence of sulphide. The datasets consisted of sulphide investigations by the City of Espoo, the City of Helsinki, and the Geological Survey of Finland. Statistically significant associations were found in the study area between the occurrence of sulphide and enumerative variables (i.e., sediment organic content, total clay depth, topographic class in the Litorina Sea phase, and water depth) in the Litorina Sea phase. Locations where sulphide clay is especially likely to occur consist of organic-rich (≥ 2%) thick clay (≥ 15 m) deposits in a topographically narrow depression with deep Litorina water (≥ 30 m), or where there is a moderate depth clay (3–5 m) in a local depression with shallow Litorina water (10–20 m). The best individual predictor for sulphide clay occurrence in the study area was found to be the sediment organic content, and, together with sediment water content, these variables very accurately predicted the occurrence of sulphide clay. In addition, clay depth is a very good predictor and, together with the topographic class narrow depression and the Litorina water depth or current elevation, can be used to predict sulphide occurrence.
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