Intra-lake patterns of aquatic insect and mite remains

Surface sediment samples from Lake Moaralmsee in the Austrian Alps were examined for fossil remains of aquatic insects and mites. This study investigated the influence of water depth on the fauna, to explore the possibility of using such fossil remains in sediment cores to reconstruct past water level changes. In addition, instar-specific patterns of chironomid (Diptera: Chironomidae) head capsule accumulation were examined to evaluate whether the smaller, lighter-weight early instars are more easily transported within the lake basin, creating a potential source of error for paleolimnological inferences. Results showed that intra-lake distribution of these zoological remains is closely related to water depth and suggested that the fossils accumulate near each species’ habitat. In addition, the ratio between exoskeletons of oribatid mites (Acari: Oribatida) and chironomid head capsules was strongly related to water depth. Examination of instar-specific accumulation patterns of all chironomid remains showed no significant relationship between specific instars and water depth, though littoral samples consisted only of the 3rd and 4th instars. A taxon-specific examination revealed that the early instars of Paracladius are significantly focused to the deeper parts of the basin. Because most taxa displayed significant relations with water depth, a transfer function was developed, relating fossil chironomids to water depth. This model has a high coefficient of determination and a low estimate of prediction error. In this study, Paracladius was found to prefer shallow and intermediate water depths, hence enhanced offshore transport of early instar head capsules may weaken model performance statistics. Results indicate that intra-lake calibration sets of invertebrate remains have great potential in paleolimnological research, though there is a possible risk of spatial autocorrelation. Such datasets also contribute to the understanding of the modern ecology of the fauna because fossil assemblages in surface deposits provide habitat-specific autecological information. More effort should be directed at evaluating how remains of different instars are transported within other lake basins, because selective offshore transport of head capsules of different larval stages can potentially cause bias in environmental reconstructions.     

Modelling patterned ground distribution in Finnish Lapland: an integration of topographical, ground and remote sensing information

New data technologies and modelling methods have gained more attention in the field of periglacial geomorphology during the last decade. In this paper we present a new modelling approach that integrates topographical, ground and remote sensing information in predictive geomorphological mapping using generalized additive modelling (GAM) . First, we explored the roles of different environmental variable groups in determining the occurrence of non‐sorted and sorted patterned ground in a fell region of 100 km2 at the resolution of 1 ha in northern Finland. Second, we compared the predictive accuracy of ground‐topography‐ and remote‐sensing‐based models. The results indicate that non‐sorted patterned ground is more common at lower altitudes where the ground moisture and vegetation abundance is relatively high, whereas sorted patterned ground is dominant at higher altitudes with relatively high slope angle and sparse vegetation cover. All modelling results were from good to excellent in model evaluation data using the area under the curve (AUC) values, derived from receiver operating characteristic (ROC) plots. Generally, models built with remotely sensed data were better than ground‐topography‐based models and combination of all environmental variables improved the predictive ability of the models. This paper confirms the potential utility of remote sensing information for modelling patterned ground distribution in subarctic landscapes.     

Downscaling of coarse‐grained geomorphological data

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.     

Can abundance of geomorphological features be predicted using presence–absence data?

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.     

Integrating climate and local factors for geomorphological distribution models

Earth surface processes (ESPs) drive landscape development and ecosystem processes in high‐latitude regions by creating spatially heterogeneous abiotic and biotic conditions. Ongoing global change may potentially alter the activity of ESPs through feedback on ground conditions, vegetation and the carbon cycle. Consequently, accurate modeling of ESPs is important for improving understanding of the current and future distributions of these processes. The aims of this study were to: (1) integrate climate and multiple local predictors to develop realistic ensemble models for the four key ESPs occurring at high latitudes (slope processes, cryoturbation, nivation and palsa mires) based on the outputs of 10 modern statistical techniques; (2) test whether models of ESPs are improved by incorporating topography, soil and vegetation predictors to climate‐only models; (3) examine the relative importance of these variables in a multivariate setting. Overall, the models showed high transferability with the mean area under curve of a receiver operating characteristics (AUC) ranging from 0.83 to 0.96 and true skill statistics (TSS) from 0.52 to 0.87 for the most complex models. Even though the analyses highlighted the importance of the climate variables as the most influential predictors, three out of four models benefitted from the inclusion of local predictors. We conclude that disregarding local topography and soil conditions in spatial models of ESPs may cause a significant source of error in geomorphological distribution models. Copyright © 2014 John Wiley & Sons, Ltd.     

Subfossil Chironomidae (Insecta: Diptera) along a latitudinal gradient in Finland: development of a new temperature inference model

Numerical techniques were used to study chironomid distribution and abundance in lakes from a 1000 km transect in Finland, with special interest on the effect of local summer air temperatures on chironomid assemblages. The final aim of the study was to develop a chironomid‐based palaeotemperature inference model. The dataset consisted of 82 lakes (of which 77 were used in the model after deletion of outliers), with catchments spanning from boreal coniferous forests to mountain birch woodland and tundra vegetation. Numerical analysis showed that the mean July air temperature was the most significant variable explaining the distribution and abundance of chironomids in Finnish lakes. Weighted‐averaging partial least squares techniques were used to develop a palaeotemperature inference model for mean July air temperature reconstructions. The model performance statistics were favourable, with cross‐validated coefficient of determination (r²) of 0.78, root mean squared error of prediction of 0.721°C and maximum bias of 0.794°C. Based on these values, the transfer function is a valid means of performing quantitative palaeotemperature estimates in downcore studies. Copyright © 2008 John Wiley & Sons, Ltd.     

Faunal (Chironomidae, Cladocera) responses to post-Little Ice Age climate warming in the high Austrian Alps

Present climate warming strongly affects limnological and ecological properties of lakes and may cause regime shifts that alter structure and function in the water bodies. Such effects are especially pronounced in climatologically extreme areas, e.g. at high altitudes. We examined a sediment core from Lake Oberer Landschitzsee, Austrian Alps, which spans the period from the Little Ice Age (LIA) to present. We investigated whether post-LIA climate warming altered aquatic invertebrate communities and limnological status in this sensitive high Alpine lake. Fossil Cladocera (Crustacea) and Chironomidae (Diptera) and organic matter in the core were analyzed. Chironomids were used to assess the lake??s benthic quality (i.e. oxygen availability). An instrumental Alpine temperature record was used to assess whether changes in the biotic assemblages correspond to post-LIA temperature trends. The planktonic and macro- and microbenthic invertebrate communities exhibit almost complete and simultaneous species turnover after the LIA, from about AD 1850 onward, when Sergentia coracina-type replaced oxyphilous Micropsectra contracta-type as the dominant macrobenthic taxon, and phytophilous Acroperus harpae outcompeted Alona affinis and Alona quadrangularis in the microbenthos. These directional community shifts corresponded with a period of reduced benthic quality, higher sediment organic content, and progressive climate warming, superimposed on Alpine land-use changes, until the early twentieth century. Detected changes suggest increased productivity and lower benthic oxygen availability. Faunal shifts were even more pronounced during the late twentieth century, simultaneous with enhanced warming. A new planktonic Cladocera species, Bosmina longirostris, typically absent from high Alpine lakes, colonized the lake and gradually became dominant toward the core top. Results show that post-LIA climate warming, coupled with increasing benthic and planktonic production, substantially altered the limnological and ecological status of this remote Alpine lake. Observed faunal turnovers provide evidence that temperature-driven ecological thresholds, whether associated directly or indirectly with greater human activity, have been crossed. Species abundances and distributions have changed in response to post-LIA and late twentieth century climate warming.     

A Finnish chironomid- and chaoborid-based inference model for reconstructing past lake levels

In the present study I utilize subfossil chironomid and chaoborid distributions in surface sediments of 68 shallow lakes. The aim is to develop a calibration model for past water-level reconstructions by applying weighted averaging-partial least squares (WA-PLS) techniques and to evaluate its potential applications and limitations. This study considers water depth at sampling sites, rather than maximum lake depth. The best of the water depth models developed uses three components and has a cross-validated coefficient of determination (r²_jack) of 0.68 and root-mean-squared error of prediction (RMSEP) of 0.78 m. The model performance is tested on the sediment sequence of a previously studied lake from southern Finland that is known to have experienced past fluctuations in its water level. The water levels inferred are compared with results of chironomid-inferred air temperature reconstruction to ease separation of the effects of the variables. The reconstruction shows consistent results similar to those of previously published cladoceran planktonic:littoral ratios (P:Ls) from the same lake. However, the results indicate that factors other than depth and temperature, such as pollution, may possibly distort the inference results. The results suggest that in applying the midge-based water depth calibration model, it would be advantageous to use it together with an inference model for temperature and preferably in a multiproxy content where changes in water chemistry may be detected. The model can be useful in studies on past effective moisture variability that is closely related to climatic changes.     

Geomorphological factors predict water quality in boreal rivers

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.