A numerical analysis of the mesoscale distribution patterns of vascular plants in the subarctic Kevo Nature Reserve, northern Finland

Different numerical techniques were used to detect and describe the major ecological-biogeographical patterns of vascular plant distributions at the meso-scale level in a subarctic region in Finland. The distribution patterns of 231 native taxa in 362 1 km² grid squares of the Kevo Nature Reserve were analysed by two-way indicator species analysis and detrended correspondence analysis, and were subsequently related to twenty-eight geographical, topographical, geological, and vegetational variables using simple discriminant functions and canonical correspondence analysis with associated Monte Carlo permutation tests.
The floristic variation detected reflects variations in environmental factors operative at the regional and local scales. No major broad-scale coherent geographical patterns were detected; instead, the spatial distribution of the grids with a similar floristic composition shows a scattered distribution. All the numerical techniques reveal a major gradient from alpine areas to lowland sites with rivers and rocky outcrops, and the most important explanatory variables for predicting the main floristic variation are all associated with altitude. The floristic patterns represented by the second ordination gradient mainly correlate with the abundance of mires. Partial ordinations indicate that both the geographical and geological variables explain relatively little of the species distributional patterns.
Although the meso-scale approach reveals much about the plant-environment relationships in the study area, the floristic variation appears to be determined mainly by fine-scale factors. In the most heterogeneous grids, the grid size used fails to detect accurately the ecological patterns of the species present.     

Water–energy,land‐cover and heterogeneity drivers of the distribution of plant species richness in a mountain region of the European Alps

Aim To evaluate the relative importance of water–energy, land‐cover, environmental heterogeneity and spatial variables on the regional distribution of Red‐Listed and common vascular plant species richness. Location Trento Province (c. 6200 km²) on the southern border of the European Alps (Italy), subdivided regularly into 228 3′ × 5′ quadrants. Methods Data from a floristic inventory were separated into two subsets, representing Red‐Listed and common (i.e. all except Red‐Listed) plant species richness. Both subsets were separately related to water–energy, land‐cover and environmental heterogeneity variables. We simultaneously applied ordinary least squares regression with variation partitioning and hierarchical partitioning, attempting to identify the most important factors controlling species richness. We combined the analysis of environmental variables with a trend surface analysis and a spatial autocorrelation analysis. Results At the regional scale, plant species richness of both Red‐Listed and common species was primarily related to energy availability and land cover, whereas environmental heterogeneity had a lesser effect. The greatest number of species of both subsets was found in quadrants with the largest energy availability and the greatest degree of urbanization. These findings suggest that the elevation range within our study region imposes an energy‐driven control on the distribution of species richness, which resembles that of the broader latitude gradient. Overall, the two species subsets had similar trends concerning the relative importance of water–energy, land cover and environmental heterogeneity, showing a few differences regarding the selection of some predictors of secondary importance. The incorporation of spatial variables did not improve the explanatory power of the environmental models and the high original spatial autocorrelation in the response variables was reduced drastically by including the selected environmental variables. Main conclusions Water–energy and land cover showed significant pure effects in explaining plant species richness, indicating that climate and land cover should both be included as explanatory variables in modelling species richness in human‐affected landscapes. However, the high degree of shared variation between the two groups made the relative effects difficult to separate. The relatively low range of variation in the environmental heterogeneity variables within our sampling domain might have caused the low importance of this complex factor.     

Mountain summer farms in Røldal,western Norway –; vegetation classification and patterns in species turnover and richness

This paper discusses vegetation types and diversity patterns in relation to environment and land-use at summer farms, a characteristic cultural landscape in the Norwegian mountains. Floristic data (189 taxa) were collected in 130 4-m² sample plots within 12 summer farms in Røldal, western Norway. The study was designed to sample as fully as possible the range of floristic, environmental, and land-use conditions. Vegetation types delimited by two-way indicator species analysis were consistent with results from earlier phytosociological studies. Detrended correspondence analysis and canonical correspondence analysis show that rather than being distinct vegetation types, the major floristic variation is structured along a spatial gradient from summer farm to the surrounding heathland vegetation. Species richness (alpha diversity) was modelled against environmental variables by generalized linear modelling and compositional turnover (beta diversity) by canonical correspondence analysis. Most environmental factors made significant contributions, but the spatial distance-to-farm gradient was the best predictor of both species richness and turnover. While summer farms reduce mean species richness at the plot scale, the compositional heterogeneity of the upland landscapes is increased, thereby creating ‘ecological room’ for additional vegetation types and species. Within an overall similarity across scales, soil variables (pH, base saturation, LOI, phosphate and nitrogen) differed considerably in their explanatory power for richness and turnover. A difference between ‘productivity limiting’ factors and ‘environmental sieves’ is proposed as an explanation. Species turnover with altitude is relatively low in grasslands as compared to heaths.     

Species response curves along environmental gradients. A case study from SE Norwegian swamp forests

Abstract. Vegetation science has relied on untested paradigms relating to the shape of species response curves along environmental gradients. To advance in this field, we used the HOF approach to model response curves for 112 plant species along six environmental gradients and three ecoclines (as represented by DCA ordination axes) in SE Norwegian swamp forests. Response curve properties were summarized in three binary response variables: (1) model unimodal or monotonous (determinate) vs. indeterminate; (2) for determinate models, unimodal vs. monotonous and (3) for unimodal models, skewed vs. symmetric. We used logistic regression to test the influence, singly and jointly, of seven predictor variables on each of three response variables. Predictor variables included gradient type (environmental or ecocline) and length (compositional turnover); species category (vascular plant, moss, Sphagnum or hepatic), species frequency and richness, tolerance (the fraction of the gradient along which the species occurs) and position of species along each gradient. The probability for fitting a determinate model increased as the main occurrence of species approached gradient extremes and with increasing species tolerance and frequency and gradient length. Appearance of unimodal models was favoured by low species tolerance and disfavoured by closeness of species to gradient extremes. Appearance of skewed models was weakly related to predictors but was slightly favoured by species optima near gradient extremes. Contrary to the results of previous studies, species category, gradient type and variation in species richness along gradients did not contribute independently to model prediction. The overall best predictors of response curve shape were position along the gradient (relative to extremes) and tolerance; the latter also expressing gradient length in units of compositional turnover. This helps predicting species responses to gradients from gradient specific species properties. The low proportion of skewed response curves and the large variation of species response curves along all gradients indicate that skewed response curves is a smaller problem for the performance of ordination methods than often claimed. We find no evidence that DCA ordination increases the unimodality, or symmetry, of species response curves more than expected from the higher compositional turnover along ordination axes. Thus ordination axes may be appropriate proxies for ecoclines, applicable for use in species response modelling.     

Exploring anthropogenic and natural processes shaping fern species richness along elevational gradients

Aim (1) To explore the impact of land use, climate and environmental heterogeneity on fern species richness along a complete elevational gradient, and (2) to evaluate the relative importance of the three groups of variables within different elevational intervals. Location A temperate mountain region (55,507 km²) of Italy on the southern border of the European Alps divided into a regular grid of 1476 cells (grain 35.7 km²). Methods We applied multiple regression (spatial and non‐spatial) to determine the relative influence of the three groups of variables on species richness, including variation partitioning at two scales. We considered the whole gradient (all 1476 cells) to explain the overall elevational pattern of species richness, and we grouped the cells into elevational intervals of 500 m in order to evaluate the explanatory power of the predictors within different zones along the gradient. Results Species richness showed a hump‐shaped pattern with elevation, forming a plateau between 800 and 1500 m. The lowest species richness was found in warm and relatively dry disturbed lowlands. Moving upwards, the greatest species richness was found in forest‐dominated mid‐elevations with high environmental heterogeneity. At high elevations dominated by open natural habitats, where temperature and precipitation were relatively low, species richness declined but less sharply than in the lowlands. Although it was impossible to separate the effects of the three groups of predictors along the whole gradient, the analysis of separate elevational intervals shed light on their relative importance. The decline of species richness within lowlands was mainly related to a combined effect of deforestation and low environmental heterogeneity. In the middle part of the gradient, habitat heterogeneity and topographic roughness were positively associated with species richness. The richness decline within high‐elevation areas was related mostly to climatic constraints. Main conclusions Human impact due to land‐use modifications strongly affects the elevational pattern of species richness. It is therefore increasingly important to adopt a multiple‐hypothesis approach, taking anthropogenic effects explicitly into account when describing ecological processes along elevational gradients.     

Plant community composition and species richness in the High Arctic tundra: From the present to the future

Arctic plant communities are altered by climate changes. The magnitude of these alterations depends on whether species distributions are determined by macroclimatic conditions, by factors related to local topography, or by biotic interactions. Our current understanding of the relative importance of these conditions is limited due to the scarcity of studies, especially in the High Arctic. We investigated variations in vascular plant community composition and species richness based on 288 plots distributed on three sites along a coast‐inland gradient in Northeast Greenland using a stratified random design. We used an information theoretic approach to determine whether variations in species richness were best explained by macroclimate, by factors related to local topography (including soil water) or by plant‐plant interactions. Latent variable models were used to explain patterns in plant community composition. Species richness was mainly determined by variations in soil water content, which explained 35% of the variation, and to a minor degree by other variables related to topography. Species richness was not directly related to macroclimate. Latent variable models showed that 23.0% of the variation in community composition was explained by variables related to topography, while distance to the inland ice explained an additional 6.4 %. This indicates that some species are associated with environmental conditions found in only some parts of the coast–inland gradient. Inclusion of macroclimatic variation increased the model's explanatory power by 4.2%. Our results suggest that the main impact of climate changes in the High Arctic will be mediated by their influence on local soil water conditions. Increasing temperatures are likely to cause higher evaporation rates and alter the distribution of late‐melting snow patches. This will have little impact on landscape‐scale diversity if plants are able to redistribute locally to remain in areas with sufficient soil water.     

Plant species richness in Fennoscandia: evaluating the relative importance of climate and history

In Fennoscandia, the species richness of vascular plants in 75 × 75 km squares is highly correlated with geographical (latitude and longitude) and climatic variables (accumulated respiration sum, mean January temperature, and mean July temperature). When generalised additive models (GAM) are used, over 80% of the variation in richness can be statistically explained by geography and climate. Even though climate has such a high explanatory power we present several arguments for interpreting these results with care. Climate has no ecologically sound explanatory power when the variation due to latitude and longitude is accounted for, and the strongest latitudinal gradient in summer temperature is in an area where the latitudinal gradient in species richness is absent. We discuss the role that Holocene history might have on the variation in species richness, and argue that history and climate should be considered simultaneously when explaining the observed patterns in the geographical variation of species richness.     

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. This revised version was published online in November 2006 with corrections to the Cover Date.     

Determinants of species richness, endemism and turnover in European longhorn beetles

This study assessed the diversity patterns of a large family of beetles, Cerambycidae, in Europe and tested the following hypotheses: 1) richness gradients of this hyperdiverse taxon are driven by water and energy variables; 2) endemism is explained by the same factors, but variation between areas also reflects post‐glacial re‐colonization processes; and 3) faunal composition is determined by the same climatic variables and, therefore, beta diversity (species turnover) is related to richness gradients. Species richness, endemism and beta diversity were modelled using inventories of 37 European territories, built from a database containing the distributions of 609 species. Area, spatial position, and nine topographical and climatic variables were used as predictors in regression and constrained analysis of principal coordinates modelling. Species richness was mostly explained by a temperature gradient, which produced a south‐to‐north decreasing richness gradient. Endemism followed the same pattern, but was also determined by longitudinal variation, peaking in the southwestern and southeastern corners of the continent. Faunal turnover was explained by an important purely spatial pattern and a spatially structured environmental gradient. Thus, contrary to other groups, cerambycid richness was mostly explained by environmental energy, but not by water availability. Endemism was concentrated in the Iberian and Greek peninsulas, but not in Italy. Thus, the latter area may have been the major source of post‐glacial re‐colonization for European longhorn beetles or, otherwise, a poor refuge during glaciations. Turnover patterns were independent of the richness gradient, because northern faunas are nested in southern ones. Turnover, in contrast to richness, was driven by both the independent effects of climate and geographic constraints that might reflect dispersal limitation or stochastic colonization events, suggesting that richness gradients are more environmentally deterministic phenomena than turnover patterns.     

Modelling the species richness distribution of French dung beetles (Coleoptera, Scarabaeidae) and delimiting the predictive capacity of different groups of explanatory variables

Aim To predict French Scarabaeidae dung beetle species richness distribution, and to determine the possible underlying causal factors. Location The entire French territory has been studied by dividing it into 301 grid cells of 0.72 × 0.36 degrees. Method Species richness distribution was predicted using generalized linear models to relate the number of species with spatial, topographic and climate variables in grid squares previously identified as well sampled (n = 66). The predictive function includes the curvilinear relationship between variables, interaction terms and the significant third‐degree polynomial terms of latitude and longitude. The final model was validated by a jack‐knife procedure. The underlying causal factors were investigated by partial regression analysis, decomposing the variation in species richness among spatial, topographic and climate type variables. Results The final model accounts for 86.2% of total deviance, with a mean jack‐knife predictive error of 17.7%. The species richness map obtained highlights the Mediterranean as the region richest in species, and the less well‐explored south‐western region as also being species‐rich. The largest fraction of variability (38%) in the number of species is accounted for by the combined effect of the three groups of explanatory variables. The spatially structured climate component explains 21% of variation, while the pure climate and pure spatial components explain 14% and 11%, respectively. The effect of topography was negligible. Conclusions Delimiting the adequately inventoried areas and elaborating forecasting models using simple environmental variables can rapidly produce an estimate of the species richness distribution. Scarabaeidae species richness distribution seems to be mainly influenced by temperature. Minimum mean temperature is the most influential variable on a local scale, while maximum and mean temperature are the most important spatially structured variables. We suggest that species richness variation is mainly conditioned by the failure of many species to go beyond determined temperature range limits.     

Spatial and environmental determinants of vascular plant species richness distribution in the Iberian Peninsula and Balearic Islands

Using an exhaustive data compilation, Iberian vascular plant species richness in 50 times 50 UTM grid cells was regressed against 24 explanatory variables (spatial, geographical, topographical, geological, climatic, land use and environmental diversity variables) using Generalized Linear Models and partial regression analysis in order to ascertain the relative contribution of primary, heterogeneous and spatially structured variables. The species richness variation accounted for by these variables is reasonably high (65% of total deviance). Little less than half of this variation is accounted for spatially structured variables. A purely spatial component of variation is hardly significant. The most significant variables are those related to altitude, and particularly maximum altitude, whose cubic response reflects the occurrence of the maximum number of species at the highest altitudes. This result highlighted the importance of Iberian mountains as hotspots of diversity and the relevance of large and small scale historical factors in contemporary plant distribution patterns. Climatic or energy-related variables contributed little, whereas geological (calcareous and acid rocks) and, to a lesser extent, environmental heterogeneity variables (land use diversity and altitude range) seem to be more important.     

Rotifer species richness along an altitudinal gradient in the Alps

Aim Biodiversity patterns along altitudinal gradients are less studied in aquatic than terrestrial systems, even though aquatic sites provide a more homogeneous environment independent of moisture constraints. We studied the altitudinal species richness pattern for planktonic rotifers in freshwater lakes and identified the environmental predictors for which altitude is a proxy. Location Two hundred and eighteen lakes of Trentino–South Tyrol (Italy) in the eastern Alps; lakes covered 98% (range 65–2960 m above sea level) of the altitudinal gradient in the Alps. Methods We performed: (1) linear regression between species richness and altitude to evaluate the general pattern, (2) multiple linear regression between species richness and environmental predictors excluding altitude to identify the most important predictors, and (3) linear regression between the residuals of the best model of step (2) and altitude to investigate any additional explanatory power of altitude. Selection of environmental predictors was based on limnological importance and non‐parametric Spearman correlations. We applied ordinary least squares regression, generalized linear, and generalized least squares modelling to select the most statistically appropriate model. Results Rotifer species richness showed a monotonic decrease with altitude independent of scale effects. Species richness could be explained (R²= 51%) by lake area as a proxy for habitat diversity, reactive silica and total phosphorus as proxies for productivity, water temperature as a proxy for energy, nitrate as a proxy for human influence and north–south and east–west directions as covariates. These predictors completely accounted for the species richness–altitude pattern, and altitude had no additional effect on species richness. Main conclusions The linear decrease of species richness along the altitudinal gradient was related to the interplay of habitat diversity, productivity, heat content and human influence. These factors are the same in terrestrial and aquatic habitats, but the greater environmental stability of aquatic systems seems to favour a linear pattern.     

Patterns of woody plant species richness in the Iberian Peninsula: environmental range and spatial scale

Aim Climate‐based models often explain most of the variation in species richness along broad‐scale geographical gradients. We aim to: (1) test predictions of woody plant species richness on a regional spatial extent deduced from macro‐scale models based on water–energy dynamics; (2) test if the length of the climate gradients will determine whether the relationship with woody species richness is monotonic or unimodal; and (3) evaluate the explanatory power of a previously proposed ‘water–energy’ model and regional models at two grain sizes. Location The Iberian Peninsula. Methods We estimated woody plant species richness on grid maps with c. 2500 and 22,500 km² cell size, using geocoded data for the individual species. Generalized additive models were used to explore the relationships between richness and climatic, topographical and substrate variables. Ordinary least squares regression was used to compare regional and more general water–energy models in relation to grain size. Variation partitioning by partial regression was applied to find how much of the variation in richness was related to spatial variables, explanatory variables and the overlap between these two. Results Water–energy dynamics generate important underlying gradients that determine the woody species richness even over a short spatial extent. The relationships between richness and the energy variables were linear to curvilinear, whereas those with precipitation were nonlinear and non‐monotonic. Only a small fraction of the spatially structured variation in woody species richness cannot be accounted for by the fitted variables related to climate, substrate and topography. The regional models accounted for higher variation in species richness than the water–energy models, although the water–energy model including topography performed well at the larger grain size. Elevation range was the most important predictor at all scales, probably because it corrects for ‘climatic error’ due to the unrealistic assumption that mean climate values are evenly distributed in the large grid cells. Minimum monthly potential evapotranspiration was the best climatic predictor at the larger grain size, but actual evapotranspiration was best at the smaller grain size. Energy variables were more important than precipitation individually. Precipitation was not a significant variable at the larger grain size when examined on its own, but was highly significant when an interaction term between itself and substrate was included in the model. Main conclusions The significance of range in elevation is probably because it corresponds to several aspects that may influence species diversity, such as climatic variability within grid cells, enhanced surface area, and location for refugia. The relative explanatory power of energy and water variables was high, and was influenced by the length of the climate gradient, substrate and grain size of the analysis. Energy appeared to have more influence than precipitation, but water availability is also determined by energy, substrate and topographic relief.     

The Definition of British Water Beetle Species Pools (Coleoptera) and their Relationship to Altitude, Temperature, Precipitation and Land Cover Variables

Pooled water beetle species lists from 1826 British national grid 10-km squares were analysed using multivariate ordination and classification methods. The relationships of pool groups to the climate, altitude and land cover variables were assessed using constrained and partial ordinations. Ordination of the species pool data indicated a major trend between squares in the north-west of Scotland and those in southern England, illustrating differences in acid and basic water standing water. Secondary variation was from acid standing water to fast-flowing streams and rivers. Classification generated nine species pool groups. These showed a distinct north-west to south-east trend but there was no obvious coastal or brackish water effect on distribution. The climatic and land cover variables were all significantly related to each other, and to north-south variation in grid square location, but the constrained ordination results indicated that that the most important influence on water beetle species pool distribution was mean summer temperature. Although the amount of variation explained by the environmental variables was low, spatial variation in the environmental predictors was almost as important as the environmental variables themselves in determining species pool composition. Mean annual temperature was also strongly correlated with species pool distribution with two land cover variables slightly less important. Altitude and precipitation had the least influence. The water beetle national recording scheme database appears to be of sufficiently high quality for environmental investigations at the British scale. There is considerable potential for the synthesis of invertebrate species distribution, land cover and climate change predictions in the assessment of environmental change. The results, together with previous work on other invertebrate species, indicate that changing summer temperatures may have a considerable influence on the distribution British invertebrate species.     

Pteridophyte richness, climate and topography in the Iberian Peninsula: comparing spatial and nonspatial models of richness patterns

Aim To describe the spatial variation in pteridophyte species richness; evaluate the importance of macroclimate, topography and within‐grid cell range variables; assess the influence of spatial autocorrelation on the significance of the variables; and to test the prediction of the mid‐domain effect. Location The Iberian Peninsula. Methods We estimated pteridophyte richness on a grid map with c. 2500 km² cell size, using published geocoded data of the individual species. Environmental data were obtained by superimposing the grid system over isoline maps of precipitation, temperature, and altitude. Mean and range values were calculated for each cell. Pteridophyte richness was related to the environmental variables by means of nonspatial and spatial generalized least squares models. We also used ordinary least squares regression, where a variance partitioning was performed to partial out the spatial component, i.e. latitude and longitude. Coastal and central cells were compared to test the mid‐domain effect. Results Both spatial and nonspatial models showed that pteridophyte richness was best explained by a second‐order polynomial of mean annual precipitation and a quadratic elevation‐range term, although the relative importance of these two variables varied when spatial autocorrelation was accounted for. Precipitation range was weakly significant in a nonspatial multiple model (i.e. ordinary regression), and did not remain significant in spatial models. Richness is significantly higher along the coast than in the centre of the peninsula. Main conclusions Spatial autocorrelation affects the statistical significance of explanatory variables, but this did not change the biological interpretation of precipitation and elevation range as the main predictors of pteridophyte richness. Spatial and nonspatial models gave very similar results, which reinforce the idea that water availability and topographic relief control species richness in relatively high‐energy regions. The prediction of the mid‐domain effect is falsified.     

Climatic and geometric constraints as driving factors of butterfly species richness along a Neotropical elevational gradient

We tested the effects of temperature, humidity and geographical constraints upon butterfly species richness along an elevational gradient covering an altitude ranging from 117 to 3,104 m above sea level (m. a.s.l.), in Southern Mexico. Ten transect sites were sampled 219 times from May 2010 to May 2011, along the elevational gradient to estimate range and population abundance of butterfly species. The effects of temperature, humidity and geometric constraints (mid-domain effects) on species richness along the study gradient were assessed using ordinary least squares regression. A total of 7,005 specimens representing 193 species were recorded. Species richness was relatively higher at elevations between 117 and 1,000 m. a.s.l. with an observed decline in richness values as elevation increased. Butterfly species richness along the study environmental gradient was predominantly determined by climatic constraints, rather than geometric constraints—a mid-domain model fit well only for large-ranged Pieridae species. Temperature and humidity explained the variation species richness for the entire butterfly community and for the three families evaluated; however the effect of predictor variables varied according to the measure of species richness and taxonomic family. This discrepancy in the response of butterfly richness to temperature, humidity and geometric constraints emphasizes the need to evaluate the response of different taxa to elevational gradients, to establish general patterns that help us to prioritize conservation measures that reduce population declines and local extinctions predicted by climate change in highly diverse tropical mountain ecosystems.     

Statistical approaches to interpreting diversity patterns in the Norwegian mountain flora

The richness of Norwegian mountain plants in 75 grid squares is mapped from published distributional data for 109 species. Eleven explanatory variables representing bedrock geology, geography and topography, climate, and history (relative abundance of unglaciated areas) Tor each square are used in multiple regression analysis with associated Monte Carlo permutation tests to find statistically significant predictor variables for species richness. The variance in richness explained by the four major groups or explanatory variables is established by (partial) multiple regression analysis in which the groups of predictors are entered in different orders. The variance in species richness explained by the predictor variables is partitioned into four independent components. A predictive model for species richness using partial least squares regression and all explanatory variables has a coefficient of determination (R²) of 0.79. The statistical results consistently show that species-richness patterns are well explained by modern-day factors such as climate, geology, elevation, and geography without recourse to historical variables. The nunatak hypothesis of plant survival on unglaciated areas within Norway does not explain the observed richness patterns when modern ecological factors are considered first. The nunatak hypothesis thus appears to be redundant, a view supported by recent palaeobotanical. biosystematical, and evolutionary studies.     

Multiple environmental determinants of regional species richness and effects of geographic range size

Understanding patterns of species richness at broad geographic extents remains one of the most challenging yet necessary scientific goals of our time. Many hypotheses have been proposed to account for spatial variation in species richness; among them, environmental determinants have played a central role. In this study, we use data on regional bat species richness in the New World to study redundancy and complementarity of three environmental hypotheses: energy, heterogeneity and seasonality. We accomplish this by partitioning variation in species richness among components associated with unique and combined effects of variables from each hypotheses, and by partitioning the overall richness gradient into gradients of species with varying breadths of geographic distribution. These three environmental hypotheses explain most variation in the species richness gradient of all bats, but do not account for all positive spatial autocorrelation at short distances. Although environmental predictors are highly redundant, energy and seasonality explain different and complementary fractions of variation in species richness of all bats. On the other hand, heterogeneity variables contribute little to explain this gradient. However, results change dramatically when richness is estimated for groups of species with different sizes of geographic distribution. First, the amount of variation explained by environment decreases with a decrease in range size; this suggests that richness gradients of small‐ranged species can not be explained as easily as those of broadly distributed species, as has been implied by analyses that do not consider differences in range size among species. Second, the relative contribution of environmental predictors to explained variation also changes with change in range size. Seasonality and energy are good predictors of species with broad distributions, but they loose almost all explanatory power for richness of species with small ranges. In contrast, heterogeneity, which is a relatively poor predictor of richness of species with large ranges, becomes the main predictor of richness gradients of species with restricted distributions. This suggests that range size is a different dimension on which heterogeneity and other environmental characteristics are complementary to each other. Our results suggest that determinants of species richness gradients might be complex, or at least more complex than many studies have previously suggested.     

The distribution and diversity of Chironomidae (Insecta: Diptera) in western Finnish Lapland, with special emphasis on shallow lakes

Aim Predictions of aquatic ecosystem change with global warming require basic data that accurately reflect the environmental conditions underlying species distributions. However, in remote arctic areas such baseline data are scarce. We assess the influence of environmental variables on chironomid distribution and taxon richness in shallow, isothermal lakes in a poorly studied arctic region. We pay particular attention to community variation along the treeline ecotonal zone where many environmental variables change abruptly in a relatively small area. Location Lake transect in Finnish Lapland spanning from boreal coniferous forest to arctic tundra. Methods Chironomid assemblages were determined from surface‐sediment samples of 50 shallow (< 10 m) natural lakes. Abundance and taxon richness data were related to 24 limnological variables using canonical ordination techniques (DCA, CCA, RDA). A Monte Carlo permutation procedure was used to assess the explanatory power of single variables. Between‐vegetation zone differences of richness were tested for statistical significance using one‐way anova . Results In total, 7771 chironomid head capsules were identified, consisting of 13 species, 10 species groups, four subgenera, 41 genera, four genus groups, five types and three with uncertain taxonomic affiliation. A hump‐shaped relationship between taxon richness and elevation was noted along the study transect with a peak in taxon richness occurring in mountain birch woodland lakes at middle elevations, decreasing then towards both warmer and colder ends of the elevation/temperature gradient. Of the individual parameters, sediment organic content, total organic carbon, pH, and lake‐specific air temperature accounted for the greatest amount of variation in the chironomid data. Main conclusions Maximum taxon richness occurred at mid‐elevations where aquatic algae also reached their maximum diversity. This area coincides with an ecotonal transitional zone, which seems more likely to account for the peak in species richness. Our study demonstrates that the factors most strongly affecting chironomids in Finnish Lapland (i.e. temperature, and ecosystem features) are those that with great probability will also change as a result of future climate change. This will likely have an effect on the distribution of chironomids in subarctic and arctic areas.