Search

Aim: Conserving freshwater biodiversity in a rapidly changing world requires updated planning schemes and research efforts. Geodiversity — the diversity of Earth surface forms, materials and processes — and biodiversity are interlinked at a fundamental level. This relationship is being considered in a growing number of studies, yet research from freshwater environments is scarce. We used geodiversity (rock‐type, soil‐type and geomorphological richness), local and climatic variables to explore whether geodiversity can be used as a surrogate for aquatic plant species richness in lakes and rivers. Location: Finland. Taxon: Aquatic plants. Methods: We compared geodiversity variables (measured within 1‐km² grid cells) to well‐studied local (e.g. area, alkalinity) and climate (e.g. growing degree‐days) variables, and examined the patterns between habitat types (lakes and rivers) and among all taxa and major functional groups (helophytes and hydrophytes). We modelled lake (n = 145) and river (n = 146) plant species richness with generalized linear models, and further partitioned variation to measure the independent and shared contributions of the geodiversity, climate and local environmental variable groups. As a complementary analysis, and to identify single important variables explaining variation in aquatic plant species richness, we utilized boosted regression trees. Results: We found a positive relationship between aquatic plant species richness and catchment geodiversity variation with recurring patterns across two different freshwater habitat types and two aquatic plant functional groups. Higher variation in geodiversity (measured at landscape scale) supported higher freshwater biodiversity (measured at the local scale) of lakes and rivers. Main conclusions: Geodiversity can be a useful addition to biodiversity modelling, and it should be considered in conservation schemes and monitoring efforts, further supporting the principle of conserving nature’s stage. Yet, differences between habitats and functional groups suggest that more habitat‐specific approaches and multiple biodiversity measures should be considered. Our study is an important signpost guiding further studies on the biodiversity–geodiversity relationship in freshwater ecosystems.

Periglacial environments are characterized by highly dynamic landscapes. Freezing and thawing lead to ground movement, associated with cryoturbation and solifluction. These processes are sensitive to climate change and variably distributed depending on multiple environmental factors. In this study, we used multi-geometry Sentinel-1 Synthetic Aperture Radar Interferometry (InSAR) to investigate the spatial distribution of the mean annual ground velocity in a mountainous landscape in Northern Norway. Statistical modeling was employed to examine how periglacial ground velocity is related to environmental variables characterizing the diverse climatic, geomorphic, hydrological and biological conditions within a 148 km(2) study area. Two-dimensional (2D) InSAR results document mean annual ground velocity up to 15 mm/yr. Vertical and horizontal velocity components in the East-West plane show variable spatial distribution, which can be explained by the characteristics of cryoturbation and solifluction operating differently over flat and sloping terrain. Statistical modeling shows that slope angle and mean annual air temperature variables are the most important environmental factors explaining the distribution of the horizontal and vertical components, respectively. Vegetation and snow cover also have a local influence, interpreted as indicators of the ground material and moisture conditions. The results show contrasted model performance depending on the velocity component used as a response variable. In general, our study highlights the potential of integrating radar remote sensing and statistical modeling to investigate mountainous regions and better understand the relations between environmental factors, periglacial processes and ground dynamics.

The biodiversity of aquatic ecosystems is under threat and there is an urgent need to quantify the various facets of biodiversity to assess the conservation value of freshwater ecosystems. The effects of taxonomic relatedness have so far not been taken into account in biodiversity assessments of lake macrophytes. We therefore tested the response of species richness and average taxonomic distinctness (AvTD) of aquatic macrophytes along environmental gradients using linear regression models and Bayesian Information Criterion variable selection method. We selected data from four regions, each with 50–60 lakes, situated in northern Europe (Finland and Sweden) and northern America (Minnesota and Wisconsin). We separately studied all macrophyte species, hydrophytes and helophytes. Species richness and AvTD of aquatic macrophytes were generally negatively related in all regions, although it was not statistically significant. Both biodiversity measures responded to environmental gradients to various degrees among the studied macrophyte groups and regions. Species richness was best explained by alkalinity and lake area in Finland, by elevation, annual mean temperature and total phosphorus in Minnesota, and by alkalinity in Wisconsin. AvTD was best explained by alkalinity, annual mean temperature and total phosphorus in Finland and by alkalinity in Wisconsin. Very weak relationships were found in Sweden. Our findings strongly suggest that complementary indices are needed to indicate more comprehensively the effects of environmental conditions on freshwater biodiversity. Species richness was found to be a better measure than AvTD to account for conservation value in freshwaters. However, further research is required to evaluate the usefulness of AvTD to indicate conservation value (e.g. randomisation tests), because alternative measures are clearly needed for those freshwater taxa lacking complete information on true phylogenetic diversity.

Aim: To explore the scale-dependency of relationships between novel geodiversity measures and 26 both native and alien vascular plant species richness. Location: Great Britain Time period: Data collected 1995-2015 Major taxa: Vascular plants Methods: We calculated terrestrial native and alien vascular plant species richness (6,932 species in total) across the island of Great Britain at 1km2 (N=219,964) and 100km2 (N=2,121) grain sizes and regional extents 25-250 km in diameter, centred around each 100km2 cell. We compiled geodiversity data on landforms, soils, hydrological and geological features using existing national datasets, and used a newly developed geomorphometric method to extract landform coverage data (e.g. hollows, ridges, valleys, peaks). We used these as predictors of species richness, alongside climate, commonly used topographic metrics, land-cover variety and human population. We analysed species richness across scales using boosted regression tree (BRT) modelling and compared models with and without geodiversity data. Results: Geodiversity significantly improved models over and above widely used topographic metrics, particularly at smaller extents and the finer grain size, and slightly more so for native species richness. For each increase in extent, the contribution of climatic variables increased and that of geodiversity decreased. Of the geodiversity variables, automatically extracted landform data added the most explanatory power, but hydrology (rivers, lakes) and materials (soil, superficial deposits, geology) were also important. Main conclusions Geodiversity improves our understanding of, and ability to model, the relationship between species richness and abiotic heterogeneity at multiple spatial scales by allowing us to get closer to the real-world physical processes that affect patterns of life. Greatest benefit comes from measuring the constituent parts of geodiversity separately, rather than one combined variable (as for most of the few studies to date). Automatically extracted landform data, the use of which is novel in ecology and biogeography, proved particularly valuable in our study.

Improved understanding of threatened species diversity is important for long-term conservation planning and natural area management, especially under ongoing global change. Geodiversity – the diversity of earth surface materials, forms and processes – may be a useful biodiversity surrogate for conservation planning, as well as having conservation value itself. Links between geodiversity and species richness have been demonstrated; establishing whether geodiversity also relates to threatened species’ diversity and distribution patterns is a logical next step for conservation biology. We used four geodiversity variables (rock type richness, soil type richness, geomorphological diversity, hydrological diversity), in addition to four climatic and topographic variables, to account for threatened species diversity across 31 of Finland’s national parks. We also analyzed rarity-weighted richness (a measure of site complementarity) of threatened vascular plants, fungi, bryophytes, and all species combined. Our 1km2-resolution dataset included 271 threatened species from 16 major taxa. We modeled threatened species richness (raw and rarity-weighted) using boosted regression trees. Commonly used climatic variables, especially the annual temperature sum above 5°C, dominated our models, consistent with the critical role of temperature in this boreal environment. Importantly, geodiversity added significant explanatory power, improving our understanding of threatened species. Greater geodiversity was consistently associated with increased threatened species richness across taxa; the combined effect of geodiversity variables was greater still in the rarity-weighted richness analyses (except for fungi). Geodiversity measures correlated most strongly with 3 species richness (raw and rarity-weighted) of threatened vascular plants and bryophytes; such correlations were weakest for molluscs, lichens, and mammals. While it is well known that simple measures of topography improve biodiversity modeling and conservation practice, our results suggest that geodiversity data relating to geology, landforms, and hydrology are also worth including. This reinforces recent arguments that ‘conserving Nature’s stage’ is an important principle in conservation.

A research-based understanding of permafrost distribution at a sufficient spatial resolution is important to meet the demands of science, education and society. We present a new permafrost map for Norway, Sweden and Finland that provides a more detailed and updated description of permafrost distribution in this area than previously available. We implemented the CryoGRID1 model at 1km2 resolution, forced by a new operationally gridded data-set of daily air temperature and snow cover for Finland, Norway and Sweden. Hundred model realisations were run for each grid cell, based on statistical snow distributions, allowing for the representation of sub-grid variability of ground temperature. The new map indicates a total permafrost area (excluding palsas) of 23 400km2 in equilibrium with the average 1981-2010 climate, corresponding to 2.2 per cent of the total land area. About 56 per cent of the area is in Norway, 35 per cent in Sweden and 9 per cent in Finland. The model results are thoroughly evaluated, both quantitatively and qualitatively, as a collaboration project including permafrost experts in the three countries. Observed ground temperatures from 25 boreholes are within±2°C of the average modelled grid cell ground temperature, and all are within the range of the modelled ground temperature for the corresponding grid cell. Qualitative model evaluation by field investigators within the three countries shows that the map reproduces the observed lower altitudinal limits of mountain permafrost and the distribution of lowland permafrost. (Less)

1. Metacommunity research relies largely on proxies for inferring the effect of dispersal on local community structure. Overland and watercourse distances have been typically used as such proxies. A good proxy for dispersal should, however, take into account more complex landscape features that can affect an organism's movement and dispersal. The cost distance approach does just that, allowing determining the path of least resistance across a landscape. 2. Here, we examined the distance decay of assemblage similarity within a subarctic stream insect metacommunity. We tested whether overland, watercourse and cumulative cost distances performed differently as correlates of dissimilarity in assemblage composition between sites. We also investigated the effect of body size and dispersal mode on metacommunity organization. 3. We found that dissimilarities in assemblage composition correlated more strongly with environmental than physical distances between sites. Overland and watercourse distances showed similar correlations to assemblage dissimilarity between sites, being sometimes significantly correlated with biological variation of entire insect communities. In metacommunities deconstructed by body size or dispersal mode, contrary to our expectation, passive dispersers showed a slightly stronger correlation than active dispersers to environmental differences between sites, although passive dispersers also showed a stronger correlation than active dispersers to physical distances between sites. The strength of correlation between environmental distance and biological dissimilarity also varied slightly among the body size classes. 4. After controlling for environmental differences between sites, cumulative cost distances were slightly better correlates of biological dissimilarities than overland or watercourse distances between sites. However, quantitative differences in correlation coefficients were small between different physical distances. 5. Although environmental differences typically override physical distances as determinants of the composition of stream insect assemblages, correlations between environmental distances and biological dissimilarities are typically rather weak. This undetermined variation may be attributable to dispersal processes, which may be captured using better proxies for the process. We suggest that further modifying the measurement of cost distances may be a fruitful avenue, especially if complemented by more direct natural history information on insect dispersal behaviour and distances travelled by them.

Geodiversity--the variability of Earth's surface materials, forms, and physical processes-is an integral part of nature and crucial for sustaining ecosystems and their services. It provides the substrates, landform mosaics, and dynamic physical processes for habitat development and maintenance. By determining the heterogeneity of the physical environment in conjunction with climate interactions, geodiversity has a crucial influence on biodiversity across a wide range of scales. From a literature review, we identified the diverse values of geodiversity; examined examples of the dependencies of biodiversity on geodiversity at a site-specific scale (for geosites

Because conservation planners typically lack data on where species occur, environmental surrogates--including geophysical settings and climate types--have been used to prioritize sites within a planning area. We reviewed 622 evaluations of the effectiveness of abiotic surrogates in representing species in 19 study areas. Sites selected using abiotic surrogates represented more species than an equal number of randomly selected sites in 43% of tests (55% for plants) and on average improved on random selection of sites by about 8% (21% for plants). Environmental diversity (ED) (42% median improvement on random selection) and biotically informed clusters showed promising results and merit additional testing. We suggest 4 ways to improve performance of abiotic surrogates. First, analysts should consider a broad spectrum of candidate variables to define surrogates, including rarely used variables related to geographic separation, distance from coast, hydrology, and within-site abiotic diversity. Second, abiotic surrogates should be defined at fine thematic resolution. Third, sites (the landscape units prioritized within a planning area) should be small enough to ensure that surrogates reflect species' environments and to produce prioritizations that match the spatial resolution of conservation decisions. Fourth, if species inventories are available for some planning units, planners should define surrogates based on the abiotic variables that most influence species turnover in the planning area. Although species inventories increase the cost of using abiotic surrogates, a modest number of inventories could provide the data needed to select variables and evaluate surrogates. Additional tests of nonclimate abiotic surrogates are needed to evaluate the utility of conserving nature's stage as a strategy for conservation planning in the face of climate change.

Water quality is the outcome of numerous landscape factors in the catchment. In addition to land use, soil deposits, bedrock and topography are central in different catchment processes and thus important in predicting water quality. In this study, we explored the influence of geomorphological factors at the catchment scale on water quality in 32 boreal rivers in Finland. Water quality was studied through total phosphorus, total nitrogen, pH and water colour, whereas geomorphological factors covered variables from topography, bedrock and surficial ground material (Quaternary soil deposits). Spearman's rank correlation test was used to study the correlations between variables. The relationship between water quality and geomorphology was analysed using novel multivariate methods by fitting of geomorphological vectors and smooth surfaces onto a non-metric multidimensional scaling (NMDS) scattergram. Hierarchical partitioning (HP) was used to assess the relative importance of geomorphological variables on water quality. Quaternary soil deposits, especially the covers of clay-silt and till soils, were important factors in relation to phosphorus and nitrogen based on both NMDS and HP analyses. For example, clay-silt cover explained over 40% of the variation in these nutrients according to HP. The variation in river water pH was best explained by the covers of sand and open bedrock terrain as well as by catchment topography. Geomorphological variables differed in their effect and relative significance, and thus several geomorphological attributes need to be considered when examining variation in water quality. In conclusion, these results demonstrate that geomorphological factors can be used to predict physical–chemical water quality in a cost-efficient manner in boreal rivers. NMDS was successfully applied in water quality analyses at the catchment scale. Copyright © 2014 John Wiley & Sons, Ltd.

Environmental factors that affect the activity-inactivity variation of periglacial features may differ from those factors that control the distributional patterns of active features. To explore this potential difference, a statistically based modelling approach and comprehensive data on active and inactive cryoturbation and solifluction features from a subarctic area of Finnish Lapland are investigated at a landscape scale. In the cryoturbation modelling, vegetation abundance is the most important environmental variable explaining both the activity-inactivity variation and the distribution of active sites. The next most important variables are soil moisture and (micro)climatological conditions in the activity modelling, and slope angle and ground material in the distribution modelling. For solifluction, the key variables determining the activity-inactivity variation are mean annual air temperature and mean maximum snow depth, whereas vegetation abundance and slope angle control the distribution of active sites. Comparison between the environmental conditions of active and inactive periglacial features may provide new insights into activity-environment relationships, which in turn are valuable when the effects of climate change on periglacial processes are explored. Copyright © 2014 John Wiley & Sons, Ltd.

Robust models of geomorphic process–environment relationships are important to advance theoretical knowledge of geomorphic systems. Here, we examined a generalized additive modeling (GAM) based approach to provide new theoretical insights into process–environment relationships. More precisely, we (i) simulated the shapes of the relationships between geomorphic processes and environmental variables based on GAM and (ii) compared the shapes of the simulated response curves to (a) the hypothetical curves based on theory and (b) the response curves produced by generalized linear modeling (GLM). Hitherto, GLM was the most common technique to study the relationships between environmental gradients and geomorphic processes. The study is based on empirical cryoturbation and solifluction data and environmental variables from subarctic Finland. Our results showed that non-linear relationships were more common than linear responses and the simulated GAM based response curves coincided more closely with the hypothetical response curves than did the response curves derived from GLM. The simulated response curves showed high potential in geomorphic hypothesis testing. In conclusion, our findings indicate that careful examination of the response curves may provide new insights into theoretical debates in the earth sciences. Copyright © 2010 John Wiley and Sons, Ltd.

The effects of scale (modelling resolution) and sources of data were explored in relation to periglacial distribution modelling for an area on western Svalbard in the High Arctic. To assess the effects of scale on predictive performance, the distributions of sorted circles and solifluction lobes were modelled at two resolutions (20 × 20 m and 200 × 200 m) using a boosted regression tree, a novel statistical ensemble method. To analyse the effects of sources of data on periglacial distribution modelling, a generalised linear model and a variation partitioning method were used. The explanatory variables were topographic parameters computed from a digital elevation model, vegetation and soil moisture indices derived from a Landsat TM 5 scene, and field survey-based information on surficial materials. Firstly, similar levels of success were achieved in predicting the periglacial feature distributions at the local (20 m) and landscape (200 m) scales. Secondly, results indicated the potential for modelling to replace labour-intensive field observations. The importance of topographic parameters for predicting the distribution of periglacial features in the sparsely vegetated High Arctic environment was also evident. Methodologically, novel statistical techniques and earth observation data provided an efficient combination for analysing periglacial landforms and processes in this remote region. Copyright © 2010 John Wiley & Sons, Ltd.

Aim We test how productivity, disturbance rate, plant functional composition and species richness gradients control changes in the composition of high-latitude vegetation during recent climatic warming. Location Northern Fennoscandia, Europe. Methods We resampled tree line ecotone vegetation sites sampled 26 years earlier. To quantify compositional changes, we used generalized linear models to test relationships between compositional changes and environmental gradients. Results Compositional changes in species abundances are positively related to the normalized difference vegetation index (NDVI)-based estimate of productivity gradient and to geomorphological disturbance. Competitive species in fertile sites show the greatest changes in abundance, opposed to negligible changes in infertile sites. Change in species richness is negatively related to initial richness, whereas geomorphological disturbance has positive effects on change in richness. Few lowland species have moved towards higher elevations. Main conclusions The sensitivity of vegetation to climate change depends on a complex interplay between productivity, physical and biotic disturbances, plant functional composition and richness. Our results suggest that vegetation on productive sites, such as herb-rich deciduous forests at low altitudes, is more sensitive to climate warming than alpine tundra vegetation where grazing may have strong buffering effects. Geomorphological disturbance promotes vegetation change under climatic warming, whereas high diversity has a stabilizing effect.

This paper provides a snapshot of the permafrost thermal state in the Nordic area obtained during the International Polar Year (IPY) 2007-2009. Several intensive research campaigns were undertaken within a variety of projects in the Nordic countries to obtain this snapshot. We demonstrate for Scandinavia that both lowland permafrost in palsas and peat plateaus, and large areas of permafrost in the mountains are at temperatures close to 0 degrees C, which makes them sensitive to climatic changes. In Svalbard and northeast Greenland, and also in the highest parts of the mountains in the rest of the Nordic area, the permafrost is somewhat colder, but still only a few degrees below the freezing point. The observations presented from the network of boreholes, more than half of which were established during the IPY, provide an important baseline to assess how future predicted climatic changes may affect the permafrost thermal state in the Nordic area. Time series of active-layer thickness and permafrost temperature conditions in the Nordic area, which are generally only 10 years in length, show generally increasing active-layer depths and risings permafrost temperatures. Copyright (C) 2010 John Wiley & Sons, Ltd. (Less)

We assessed the applicability of a boosting method in periglacial distribution modelling using empirically derived data on cryoturbation, sporadic permafrost and sorted solifluction from an area of 600 km2 in sub-Arctic Finland. The main aims were: (1) to compare the predictive ability of the generalised boosting method used with more common parametric techniques (generalised linear model) and machine-learning methods (artificial neural networks) and (2) to assess the tenability of the explanatory variables highlighted by the generalised boosting method. The results showed the robustness of the boosting method in predicting the distribution of periglacial phenomena in the sub-Arctic landscape. Furthermore, the environmental factors selected by the boosting method coincided well with the expected controls of the phenomena. The strengths of the generalised boosting method lie in its high predictive ability, flexibility in capturing complex process-environment relationships and realistic model outcomes. Copyright © 2008 John Wiley & Sons, Ltd.

Geomorphological models are useful tools for assessing the impacts of changing environmental conditions on earth surface processes and landforms. Here we evaluate the feasibility of predicting the abundance (spatial coverage) of geomorphological features using presence–absence data. To achieve the study goals, generalized linear models (GLMs), spatial predictors and geomorphological data from a thoroughly inventoried area of 600 km2 in sub-Arctic Finland at a resolution of 25 ha were utilized in the exercise. The key finding was that the GLMs derived from presence–absence data performed as consistently, as a relative index of abundance, as models derived directly from the abundance data. Thus, predictions based on presence–absence data may serve as a reasonable surrogate for abundance of geomorphological features. Copyright © 2007 John Wiley & Sons, Ltd.

One of the basic limitations to the use of geomorphological maps is their coarse resolution relative to the needs of pure and applied geomorphological research. In response to this, attempts have been made to ‘downscale’ geomorphological information to finer spatial resolutions. However, the potential of statistical downscaling in geomorphology has been insufficiently examined. We downscaled four different periglacial features (wind deflation, palsa mire, earth hummock and sorted solifluction sheet) from a 100 ha grid to a 1 ha grid resolution utilizing two different techniques: point sampling (PSA) and direct (DA) approaches. We assessed the predictive accuracy of the models with the area under the curve (AUC) of a receiver operating characteristic plot using independent evaluation data. The PSA technique yielded encouraging results with a mean accuracy of 0·81, whereas the performance of DA was poorer. The predictive performance of the palsa mire and solifluction sheet models was excellent (AUC values from 0·89 to 0·96), whereas the AUC values of deflation and earth hummock models were lower (AUC = 0·57–0·81). The application of a point sampling approach as used here provides an efficient method to translate geomorphological information to finer resolution. However, further testing of the downscaling approaches is required before they can be applied to real-world situations. Copyright © 2007 John Wiley & Sons, Ltd.

Identification of the environmental drivers of geomorphological processes in cold regions is a central topic in periglacial research. The objective of this study was to develop and test a methodology to: (1) predict the occurrence of palsas, earth hummocks, sorted solifluction sheets and periglacial deflation sites in a subarctic landscape and (2) determine the most important environmental factors affecting the distribution of these features at the landscape scale. The study was performed using an empirically-derived data-set of landforms from an area of 600 km 2 in northern Finland at a 25 ha resolution (n ¼ 2272). Logistic regression and hierarchical partitioning were used to analyse the data and the predictive performance of the models was evaluated using area under the curve (AUC) measures. The explanatory variables highlighted as important predictors of the occurrence of periglacial features coincided well with the hypothesised determinants. Predictions for palsa, earth hummock and sorted solifluction sheet models were excellent (AUC ¼ 0.92–0.95) and the deflation site model was good (AUC ¼ 0.81). The results encourage further application of the grid-based modelling approach, for example in predicting feature occurrences in other periglacial regions, studying scale dependency of process-environment interactions and determining the effect of climate change on the distribution of frost-related processes. Copyright # 2007 John Wiley & Sons, Ltd.

Generalized linear models (GLM) are mathematical extensions of linear models. GLM models are more flexible and better suited for analysing relationships of spatial data, which can often be poorly represented by classical Gaussian distributions such as least-square-regression techniques. This paper demonstrates GLM model-building procedures step-by-step for the distribution and abundance of active patterned ground in northern Finland. The exercise is based on data from an area of 200 km2 (800 modelling squares of 0.25 km2). Both the distribution and abundance models clearly indicate an increasing activity of patterned ground with (1) increasing soil moisture and (2) proportion of concave topography. Activity decreases with increasing altitude. We conclude that GLM techniques combined with a geographic information system can play an important role in analysing and modelling periglacial data sets. Copyright © 2004 John Wiley & Sons, Ltd.