Browsing by Author "Käkelä, Saara"

Due to global climate change there will be an increase in frequency of extreme temperatures. That will have an effect to species distribution regions. By adding extreme temperatures on a species distribution model based on the basic climatological variables we could improve the understanding of biological effect of climatic variability and extremes. The aim of this study is to develop a species distribution model for arctic-alpine and boreal vascular plant species and examine does the extremes improve predictions. The other question is, does vascular plant species from two different biogeographical distributions responds similarly to bioclimatic variables? A study area (26 000 square kilometre) is located in Northwestern Finland and it belongs to subarctic climate regime. A climate model is produced from the data of 61 climate stations from 1971–2000. Modeling was done with generalized additive model (GAM) by using geographical variables as explanatories (geographical location, elevation, the effect of the Arctic Ocean, lake and mire cover). Total sample of vascular plant species was 1182 of 1x1 km grids. The distribution model was done with three different statistical techniques (GLM, GAM, GBM). First a simple model was modeled with three baseline variables (a temperature of the coldest month, water balance, growing degree days) and then the extreme temperatures were added to compose a full model. The predictive power of the models was tested by calculating the area under the curve of a receiver operating characteristic plot (AUC) and the true skill statistic (TSS) for both models. Incorporating the extreme temperatures into the distribution model significantly improved the accuracy of distribution model of the both plant groups. The improvement was small but statistically significant. The relative importance of each predictor variable and the response of each bioclimatic variable to occurrence of species varied between the plant groups. The most significant explanatory variable to explain the arctic-alpine plant distribution is the temperature of the coldest month. The probability of occurrence increase with that variable as well as with water balance which is the second. The third significant variable is mean annual absolute minimum temperature (a negative response). For the boreal species the relative importance of climatic variables is more evenly distributed between predictor variables in the full model. The growing degree day is the most important variable (positive). Water balance (negative) and mean annual absolute maximum temperature (positive) have almost an equal variable importance. The main finding of the study is that the inclusion of extreme temperatures into distribution models of vascular plant species will improve occurrence predictions at the high-latitude study site. Secondly, arctic-alpine and boreal plant species have opposite responses on climate variables that have been used. The results could be solved in the planning of conservation areas and the climate change impact analyses.