Paleolimnological assessment of ecological integrity and eutrophication history for Lake Tiiläänjärvi (Askola,Finland)

In this study, we aim to reconstruct long-term limnoecological development of the clay-turbid Lake Tiiläänjärvi in Askola, southern Finland, using fossil Chironomidae assemblages. The study lake suffers from hypereutrophic conditions and late-winter and end-of-summer anoxia. The retrieved sediment record revealed a succession from oligo-mesotrophic (~AD 1940–2000) to eutrophic community (~AD 2000–2010) that finally reached hypereutrophic climax community in the most recent sediments. The initial state of the record was characterized by stable ecological conditions, but the biological integrity (community and functional diversity) was completely lost in the upper part of the sediment profile. The number of taxa markedly decreased following the nutrient enrichment and only one taxon (Chironomus plumosus-type), tolerant of temporary anoxia, remained in the surface sample. During the period of available observational data (since AD 1978), variance in midge community composition was mostly explained by limnological factors, namely total phosphorus (TP), whereas the influence of climate was statistically insignificant, thus enabling quantitative midge-based reconstruction of autumnal epilimnetic TP. The midge-based reconstruction showed an identical trend compared to sediment characteristics, which correspond to increased lake productivity and anthropogenic activities in the catchment. The inferred values for the initial state indicated mesotrophic conditions, which are typical for non-disturbed clay-turbid lakes in southern Finland, and a subsequent increase to eutrophic conditions, with hypereutrophic state reached at the top of the core. This development corresponds with the instrumentally monitored development. In addition, when the reconstruction was compared with the instrumental values, the inferences were mostly (75 % of the samples) within the error estimates of the model. The present results provide invaluable information on the limnoecological development of Lake Tiiläänjärvi, and more generally, support the theory that fossil remains of chironomids provide a useful tool for assessments of eutrophication history and biological integrity.     

Ecological responses to climate change in a bird-impacted High Arctic pond (Nordaustlandet,Svalbard)

A 28-cm sediment core from an Arctic pond (Nordaustlandet, Svalbard), which is currently subjected to the fertilizing effect of bird guano, was analysed for fossil invertebrates and the physical properties of the sediment. The objective was to examine aquatic community responses to climate warming. Our record reveals that faunal changes have occurred. Initially chironomid assemblages were dominated by a cold-indicating oligotrophic community but this was replaced by a community typical of more nutrient-enriched conditions and warmer water temperature at around AD 1,700–1,800. After AD 1,800, ostracods and Daphnia increase suggesting that a nutrient enrichment threshold was crossed, probably related to increased planktonic algal productivity. In the early twentieth century, organic content markedly increases and magnetic susceptibility values suddenly drop, indicating a further increase in nutrient input and lake productivity. Since the most likely source of nutrients in the lake is goose guano, this suggests that the size of the bird colony may also have increased over this period. These changes coincide with climate warming suggesting a positive feedback in which climate change is the primary driver of the increasing geese abundance and lake productivity. Our results further suggest that the predicted future warming in the Arctic will continue to have cascading effects on freshwater ecosystems in the region.     

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.     

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.     

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.     

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.     

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.     

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.