Risto K. Heikkinen

New insights into butterfly–environment relationships using partitioning methods

Variation partitioning and hierarchical partitioning are novel statistical approaches that provide deeper understanding of the importance of different explanatory variables for biodiversity patterns than traditional regression methods. Using these methods, the variation in occupancy and abundance of the clouded apollo butterfly (Parnassius mnemosyne L.) was decomposed into independent and joint effects of larval and adult food resources, microclimate and habitat quantity. The independent effect of habitat quantity variables (habitat area and connectivity) captured the largest fraction of the variation in the clouded apollo patterns, but habitat connectivity had a major contribution only for occupancy data. The independent effects of resources and microclimate were higher on butterfly abundance than on occupancy. However, a considerable amount of variation in the butterfly patterns was accounted for by the joint effects of predictors and may thus be causally related to two or all three groups of variables. Abundance of the butterfly in the surroundings of the focal grid cell had a significant effect in all analyses, independently of the effects of other predictors. Our results encourage wider applications of partitioning methods in biodiversity studies.

On the recovery of mountain birch after Epirrita damage in Finnish Lapland, with a particular emphasis on reindeer grazing

Abstract:The effectiveness of recovery of mountain birch forests defoliated by Epirrita autumnata in 1965 in Inari Lapland, northern Finland, was studied by monitoring seedling and basal sprout formation in eight fenced areas and corresponding control plots, 400 m2 each. The number of seedlings and the abundance of basal sprouts were measured in 1973, 1979, 1982, 1987 and 1990/1991. The results indicate that tree recovery from seeds is in theory possible in the damaged birch forests almost everywhere in the study area, and that the changes occurring in the undergrowth after the damage may actually support the development of seedlings. However, in practice this process is disturbed by the adverse effect of reindeer grazing on seedling establisment. The formation of sprouts from dormant basal buds in damaged trees is not so greatly affected by reindeer grazing, but sprouting has been successful and the forest will totally recover only in a few areas where sprouting was abundant soon after the Epirrita damag...

Species richness of vascular plantsin the subarctic landscape of northern Finland:modelling relationships to the environment

This paper presents models based on empirical data which can be used to predict the patterns of species richness of vascular plants at the poorly explored mesoscale. Using generalized linear modelling, multiple regression models of species richness in the Kevo Nature Reserve, North Finland, are built with a training set of 257 grid squares and 33 environmental variables. We validated the accuracy of the derived models with an independent test set of 100 grid squares. Two different modelling approaches are used: one where species richness is treated straightforwardly as the response variable, and another where it is tentatively stratified into two groups according to taxon types, i.e. alpine taxa versus wide-spread and silvine (forest) taxa. However, the latter approach only marginally improved the accuracy of the predictions of total number of species. Linear altitudinal variables were among the best predictors of vascular plant richness at the mesoscale. As variables involving altitude are crude surrogates for energy-related factors, the results support the available energy hypothesis and advocate its significance in richness-environment relationships. Other important predictors of species richness included length of rivers and brooks, abundance of cliff walls, occurrences of steep-sided gorges and valleys, and relative abundance of gabbro in bedrock. However, the accuracy of the predictions in the derived models is relatively modest. This points towards the necessity of field work as a final guarantee to identify local hotspots of vascular plant species in a subarctic landscape.

PREDICTING PATTERNS OF VASCULAR PLANT SPECIES RICHNESS WITH COMPOSITE VARIABLES : A MESO-SCALE STUDY IN FINNISH LAPLAND

This paper is an attempt, using statistical modelling techniques, to understand the patterns of vascular plant species richness at the poorly studied meso-scale within a relatively unexplored subarctic zone. Species richness is related to floristic-environmental composite variables, using occurrence data of vascular plants and environmental and spatial predictor variables in 362 1 km2 grid squares in the Kevo Nature Reserve. Species richness is modelled in two different way. First, by detecting the major floristic-environmental gradients with the ordination procedure of canonical correspondence analysis, and subsequently relating these ordination axes to species richness by generalized linear modelling. Second, species richness is directly related to the composite environmental factors of explanatory variables, using partial least squares regression. The most important explanatory variables, as suggested by both approaches, are relatively similar, and largely reflect the influence of altitude or altitudinally related variables in the models. The most prominent floristic gradient in the data runs from alpine habitats to river valleys, and this gradient is the main source of variation in species richness. Some local environmental variables are also relatively important predictors; the grid squares rich in vascular plant taxa are mainly located in the lowlands of the reserve and are characterised by rivers and brooks, as well as by abundant cliff walls. The two statistical models account for approximately the same amount of variation in the species richness, with more than half of the variation unexplained. Potential reasons for the relatively modest fit are discussed, and the results are compared to the characteristics of the diversity-environment relationships at both broader- and finer-scales.

Can richness patterns of rarities be predicted from mesoscale atlas data? A case study of vascular plants in the Kevo Reserve

Abstract This paper presents an empirical model of the mesoscale patterns of the number of rare vascular plant taxa in a Finnish subarctic landscape. A multiple regression model relating the species richness of rarities to several environmental variables is developed using generalized linear models and data from 362 1 × 1 km grid squares. The final model accounts for 60% of the variation in the species data. The results suggest that the local hotspots of rare flora (squares with ⩾- 3 rare taxa) are mainly found in topographically heterogeneous grid squares, where high cliffs occur in deep gorges. However, it seems that the empirical models derived from mesoscale atlas data and environmental variables can provide only moderately accurate surrogates for extensive field surveys and fine-scale observations on the distributions of rare taxa. The squares with neither-recorded-nor-expected rarities coincide best, and half of the observed and predicted rarity hotspots match. Predictions are least accurate in squares where one or two rare species have been recorded or are predicted to occur. Potential reasons for the moderate performance of the model and the ecology and habitats of the species in concern are discussed.

An Ordination Study of Esker Forest Vegetation in Southern Finland

Eskers are glaciofluvial formations which consist of soil material sorted by glacial meltwaters. They are often ridges over 20 meters high which are more variable in terms of ecological site factors than the surrounding forest on flatter ground (3, 6). The aim of this study was to determine the main environmental factors governing the vegetational change in esker forests.