Spatial variation of climate and the impact of disturbances on local climate and forest recovery in northern Finland

The structure and function of northern ecosystems are strongly influenced by climate change and variability and by human-induced disturbances. The projected global change is likely to have a pronounced effect on the distribution and productivity of different species, generating large changes in the equilibrium at the tree-line. In turn, movement of the tree-line and the redistribution of species produce feedback to both the local and the regional climate. This research was initiated with the objective of examining the influence of natural conditions on the small-scale spatial variation of climate in Finnish Lapland, and to study the interaction and feedback mechanisms in the climate-disturbances-vegetation system near the climatological border of boreal forest. The high (1 km) resolution spatial variation of climate parameters over northern Finland was determined by applying the Kriging interpolation method that takes into account the effect of external forcing variables, i.e., geographical coordinates, elevation, sea and lake coverage. Of all the natural factors shaping the climate, the geographical position, local topography and altitude proved to be the determining ones. Spatial analyses of temperature- and precipitation-derived parameters based on a 30-year dataset (1971-2000) provide a detailed description of the local climate. Maps of the mean, maximum and minimum temperatures, the frost-free period and the growing season indicate that the most favourable thermal conditions exist in the south-western part of Lapland, around large water bodies and in the Kemijoki basin, while the coldest regions are in highland and fell Lapland. The distribution of precipitation is predominantly longitudinally dependent but with the definite influence of local features. The impact of human-induced disturbances, i.e., forest fires, on local climate and its implication for forest recovery near the northern timberline was evaluated in the Tuntsa area of eastern Lapland, damaged by a widespread forest fire in 1960 and suffering repeatedly-failed vegetation recovery since that. Direct measurements of the local climate and simulated heat and water fluxes indicated the development of a more severe climate and physical conditions on the fire-disturbed site. Removal of the original, predominantly Norway spruce and downy birch vegetation and its substitution by tundra vegetation has generated increased wind velocity and reduced snow accumulation, associated with a large variation in soil temperature and moisture and deep soil frost. The changed structural parameters of the canopy have determined changes in energy fluxes by reducing the latter over the tundra vegetation. The altered surface and soil conditions, as well as the evolved severe local climate, have negatively affected seedling growth and survival, leading to more unfavourable conditions for the reproduction of boreal vegetation and thereby causing deviations in the regional position of the timberline. However it should be noted that other factors, such as an inadequate seed source or seedbed, the poor quality of the soil and the intensive logging of damaged trees could also exacerbate the poor tree regeneration. In spite of the failed forest recovery at Tunsta, the position and composition of the timberline and tree-line in Finnish Lapland may also benefit from present and future changes in climate. The already-observed and the projected increase in temperature, the prolonged growing season, as well as changes in the precipitation regime foster tree growth and new regeneration, resulting in an advance of the timberline and tree-line northward and upward. This shift in the distribution of vegetation might be decelerated or even halted by local topoclimatic conditions and by the expected increase in the frequency of disturbances.

Phytoplankton ecology of subarctic lakes in Finnish Lapland

Climate is warming and it is especially seen in arctic areas, where the warming trend is expected to be greatest. Arctic freshwater ecosystems, which are a very characteristic feature of the arctic landscape, are especially sensitive to climate change. They could be used as early warning systems, but more information about the ecosystem functioning and responses are needed for proper interpretation of the observations. Phytoplankton species and assemblages could be especially suitable for climate-related studies, since they have short generation times and react rapidly to changes in the environment. In addition, phytoplankton provides a good tool for lake classifications, since different species have different requirements and tolerance ranges for various environmental factors. The use of biological indicators is especially useful in arctic areas, were many of the chemical factors commonly fall under the detection limit and therefore do not provide much information about the environment. This work brings new information about species distribution and dynamics of arctic freshwater phytoplankton in relation to environmental factors. The phytoplankton of lakes in Finnish Lapland and other European high-altitude or high-latitude areas were compared. Most lakes were oligotrophic and dominated by flagellated species belonging to chrysophytes, cryptophytes and dinoflagellates. In Finnish Lapland cryptophytes were of less importance, whereas desmids had high species richness in many of the lakes. In Pan-European scale, geographical and catchment-related factors were explaining most of the differences in species distributions between different districts, whereas lake water chemistry (especially conductivity, SiO2 and pH) was most important regionally. Seasonal and interannual variation of phytoplankton was studied in subarctic Lake Saanajärvi. Characteristic phytoplankton species in this oligotrophic, dimictic lake belonged mainly to chrysophytes and diatoms. The maximum phytoplankton biomass in Lake Saanajärvi occurs during autumn, while spring biomass is very low. During years with heavy snow cover the lake suffers from pH drop caused by melt waters, but the effects of this acid pulse are restricted to surface layers and last for a relatively short period. In addition to some chemical parameters (mainly Ca and nutrients), length of the mixing cycle and physical factors such as lake water temperature and thermal stability of water column had major impact on phytoplankton dynamics. During a year with long and strong thermal stability, the phytoplankton community developed towards an equilibrium state, with heavy dominance of only a few taxa for a longer period of time. During a year with higher windiness and less thermal stability, the species composition was more diverse and species with different functional strategies were able to occur simultaneously. The results of this work indicate that although arctic lakes in general share many common features concerning their catchment and water chemistry, large differences in biological features can be found even in a relatively small area. Most likely the lakes with very different algal flora do not respond in a similar way to differences in the environmental factors, and more information about specific arctic lake types is needed. The results also show considerable year to year differences in phytoplankton species distribution and dynamics, and these changes are most likely linked to climatic factors.

Maximum Loss Calculation using Scenario Analysis, Heavy Tails and Implied Volatility Patterns

The objective of this paper is to improve option risk monitoring by examining the information content of implied volatility and by introducing the calculation of a single-sum expected risk exposure similar to the Value-at-Risk. The figure is calculated in two steps. First, there is a need to estimate the value of a portfolio of options for a number of different market scenarios, while the second step is to summarize the information content of the estimated scenarios into a single-sum risk measure. This involves the use of probability theory and return distributions, which confronts the user with the problems of non-normality in the return distribution of the underlying asset. Here the hyperbolic distribution is used to describe one alternative for dealing with heavy tails. Results indicate that the information content of implied volatility is useful when predicting future large returns in the underlying asset. Further, the hyperbolic distribution provides a good fit to historical returns enabling a more accurate definition of statistical intervals and extreme events.