Browsing by Subject "modelling (creation related to information)"

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  • Kleemola, Sirpa; Forsius, Martin (Finnish Environment Institute, 2018)
    Reports of the Finnish Environment Institute 20 /2018
    The Integrated Monitoring Programme (ICP IM) is part of the effect-oriented activities under the 1979 Convention on Long-range Transboundary Air Pollution, which covers the region of the United Nations Economic Commission for Europe (UNECE). The main aim of ICP IM is to provide a framework to observe and understand the complex changes occurring in natural/semi natural ecosystems. This report summarizes the work carried out by the ICP IM Programme Centre and several collaborating institutes. The emphasis of the report is in the work done during the programme year 2017/2018 including: - A short summary of previous data assessments - A status report of the ICP IM activities, content of the IM data base, and geographical coverage of the monitoring network - A report on long-term changes in the inorganic nitrogen output fluxes in European ICP Integrated Monitoring catchments and an assessment of the role of internal nitrogen parameters - A progress report on dynamic soil-vegetation modelling - A literature review: Post disturbance vegetation succession and resilience in forest ecosystems - National Reports on ICP IM activities are presented as annexes.
  • Kleemola, Sirpa; Forsius, Martin (Finnish Environment Institute, 2019)
    Reports of the Finnish Environment Institute 33/2019
    The Integrated Monitoring Programme (ICP IM) is part of the effect-oriented activities under the 1979 Convention on Long-range Transboundary Air Pollution, which covers the region of the United Nations Economic Commission for Europe (UNECE). The main aim of ICP IM is to provide a framework to observe and understand the complex changes occurring in natural/semi natural ecosystems. This report summarizes the work carried out by the ICP IM Programme Centre and several collaborating institutes. The emphasis of the report is in the work done during the programme year 2018/2019 including: - A short summary of previous data assessments - A status report of the ICP IM activities, content of the IM database, and geographical coverage of the monitoring network - An interim report on aluminium fractions in surface waters draining catchments of ICP Integrated Monitoring network - National Reports on ICP IM activities are presented as annexes.
  • Forsius, Martin; Posch, Maximilian; Holmberg, Maria; Vuorenmaa, Jussi; Kleemola, Sirpa; Augustaitis, Algirdas; Beudert, Burkhard; Bochenek, Witold; Clarke, Nicholas; de Wit, Heleen A.; Dirnböck, Thomas; Frey, Jane; Grandin, Ulf; Hakola, Hannele; Kobler, Johannes; Krám, Pavel; Lindroos, Antti-Jussi; Löfgren, Stefan; Pecka, Tomasz; Rönnback, Pernilla; Skotak, Krzysztof; Szpikowski, Józef; Ukonmaanaho, Liisa; Valinia, Salar; Váňa, Milan (Elsevier, 2021)
    Science of The Total Environment 753 (2021), 141791
    Anthropogenic emissions of nitrogen (N) and sulphur (S) compounds and their long-range transport have caused widespread negative impacts on different ecosystems. Critical loads (CLs) are deposition thresholds used to describe the sensitivity of ecosystems to atmospheric deposition. The CL methodology has been a key science-based tool for assessing the environmental consequences of air pollution. We computed CLs for eutrophication and acidification using a European long-term dataset of intensively studied forested ecosystem sites (n = 17) in northern and central Europe. The sites belong to the ICP IM and eLTER networks. The link between the site-specific calculations and time-series of CL exceedances and measured site data was evaluated using long-term measurements (1990–2017) for bulk deposition, throughfall and runoff water chemistry. Novel techniques for presenting exceedances of CLs and their temporal development were also developed. Concentrations and fluxes of sulphate, total inorganic nitrogen (TIN) and acidity in deposition substantially decreased at the sites. Decreases in S deposition resulted in statistically significant decreased concentrations and fluxes of sulphate in runoff and decreasing trends of TIN in runoff were more common than increasing trends. The temporal developments of the exceedance of the CLs indicated the more effective reductions of S deposition compared to N at the sites. There was a relation between calculated exceedance of the CLs and measured runoff water concentrations and fluxes, and most sites with higher CL exceedances showed larger decreases in both TIN and H+ concentrations and fluxes. Sites with higher cumulative exceedance of eutrophication CLs (averaged over 3 and 30 years) generally showed higher TIN concentrations in runoff. The results provided evidence on the link between CL exceedances and empirical impacts, increasing confidence in the methodology used for the European-scale CL calculations. The results also confirm that emission abatement actions are having their intended effects on CL exceedances and ecosystem impacts.
  • Ärje, Johanna; Melvad, Claus; Jeppesen, Mads Rosenhoj; Madsen, Sigurd Agerskov; Raitoharju, Jenni; Rasmussen, Maria Strandgård; Iosifidis, Alexandros; Tirronen, Ville; Gabbouj, Moncef; Meissner, Kristian; Hoye, Toke Thomas (British Ecological Society, 2020)
    Methods in Ecology and Evolution 11 8 (2020)
    1. Understanding how biological communities respond to environmental changes is a key challenge in ecology and ecosystem management. The apparent decline of insect populations necessitates more biomonitoring but the time-consuming sorting and expert-based identification of taxa pose strong limitations on how many insect samples can be processed. In turn, this affects the scale of efforts to map and monitor invertebrate diversity altogether. Given recent advances in computer vision, we propose to enhance the standard human expert-based identification approach involving manual sorting and identification with an automatic image-based technology. 2. We describe a robot-enabled image-based identification machine, which can automate the process of invertebrate sample sorting, specimen identification and biomass estimation. We use the imaging device to generate a comprehensive image database of terrestrial arthropod species which is then used to test classification accuracy, that is, how well the species identity of a specimen can be predicted from images taken by the machine. We also test sensitivity of the classification accuracy to the camera settings (aperture and exposure time) to move forward with the best possible image quality. We use state-of-the-art Resnet-50 and InceptionV3 convolutional neural networks for the classification task. 3. The results for the initial dataset are very promising as we achieved an average classification accuracy of 0.980. While classification accuracy is high for most species, it is lower for species represented by less than 50 specimens. We found significant positive relationships between mean area of specimens derived from images and their dry weight for three species of Diptera. 4. The system is general and can easily be used for other groups of invertebrates as well. As such, our results pave the way for generating more data on spatial and temporal variation in invertebrate abundance, diversity and biomass.
  • García-Girón, Jorge; Heino, Jani; García-Criado, Francisco; Fernández-Aláez, Camino; Alahuhta, Janne (Wiley Online Library, 2020)
    Ecography 43 8 (2020)
    Biotic interactions are fundamental drivers governing biodiversity locally, yet their effects on geographical variation in community composition (i.e. incidence-based) and community structure (i.e. abundance-based) at regional scales remain controversial. Ecologists have only recently started to integrate different types of biotic interactions into community assembly in a spatial context, a theme that merits further empirical quantification. Here, we applied partial correlation networks to infer the strength of spatial dependencies between pairs of organismal groups and mapped the imprints of biotic interactions on the assembly of pond metacommunities. To do this, we used a comprehensive empirical dataset from Mediterranean landscapes and adopted the perspective that community assembly is best represented as a network of interacting organismal groups. Our results revealed that the co-variation among the beta diversities of multiple organismal groups is primarily driven by biotic interactions and, to a lesser extent, by the abiotic environment. These results suggest that ignoring biotic interactions may undermine our understanding of assembly mechanisms in spatially extensive areas and decrease the accuracy and performance of predictive models. We further found strong spatial dependencies in our analyses which can be interpreted as functional relationships among several pairs of organismal groups (e.g. macrophytes–macroinvertebrates, fish–zooplankton). Perhaps more importantly, our results support the notion that biotic interactions make crucial contributions to the species sorting paradigm of metacommunity theory and raise the question of whether these biologically-driven signals have been equally underappreciated in other aquatic and terrestrial ecosystems. Although more research is still required to empirically capture the importance of biotic interactions across ecosystems and at different spatial resolutions and extents, our findings may allow decision makers to better foresee the main consequences of human-driven impacts on inland waters, particularly those associated with the addition or removal of key species.
  • Hämäläinen, Heikki; Aroviita, Jukka; Jyväsjärvi, Jussi; Kärkkäinen, Salme (Ecological Society of America, 2018)
    Ecological Applications 28 (5): 1260-1272
    The ecological assessment of freshwaters is currently primarily based on biological communities and the reference condition approach (RCA). In the RCA, the communities in streams and lakes disturbed by humans are compared with communities in reference conditions with no or minimal anthropogenic influence. The currently favored rationale is using selected community metrics for which the expected values (E) for each site are typically estimated from environmental variables using a predictive model based on the reference data. The proportional differences between the observed values (O) and E are then derived, and the decision rules for status assessment are based on fixed (typically 10th or 25th) percentiles of the O/E ratios among reference sites. Based on mathematical formulations, illustrations by simulated data and real case studies representing such an assessment approach, we demonstrate that the use of a common quantile of O/E ratios will, under certain conditions, cause severe bias in decision making even if the predictive model would be unbiased. This is because the variance of O/E under these conditions, which seem to be quite common among the published applications, varies systematically with E. We propose a correction method for the bias and compare the novel approach to the conventional one in our case studies, with data from both reference and impacted sites. The results highlight a conceptual issue of employing ratios in the status assessment. In some cases using the absolute deviations instead provides a simple solution for the bias identified and might also be more ecologically relevant and defensible.
  • da Silva, Pedro Giovâni; Cañedo-Argüelles, Miguel; Bogoni, Juliano André; Heino, Jani (Frontiers Media S.A., 2021)
    Frontiers in Ecology and Evolution 9: 670212
    According to metacommunity theory (Leibold et al., 2004), the structure of local communities results from the interplay between local factors (e.g., environmental filtering, species interactions) and regional factors (e.g., dispersal rates, landscape configuration). The relative importance of these factors is highly dependent on the organisms’ biological traits, landscape connectivity, and the spatial and temporal scales considered (Heino et al., 2015; Tonkin et al., 2018; Viana and Chase, 2019; Almeida-Gomes et al., 2020; Cañedo-Argüelles et al., 2020; Lansac-Tôha et al., 2021). However, the differences in metacommunity assembly mechanisms found among studies are far from being fully understood. The evaluation of temporal dynamics of metacommunities has only emerged recently (Cañedo-Argüelles et al., 2020; Jabot et al., 2020; Li et al., 2020; Lindholm et al., 2021) and the application of the metacommunity theory in other fields, such as biomonitoring, conservation biology or ecosystem restoration, is yet to be fully explored (Bengtsson, 2010; Heino, 2013; Leibold and Chase, 2018; Chase et al., 2020; Cid et al., 2020; Heino et al., 2021). In this Research Topic, our aim was to invite researchers working in different biogeographic regions and ecological systems (Figure 1) to publish a number of innovative papers on metacommunity spatio-temporal dynamics. We expect to obtain a better understanding of how the factors and processes that structure metacommunities vary in space and time, as well as the implications of such dynamics for biodiversity conservation and ecosystem management.
  • Tohka, Antti; Karvosenoja, Niko (Finnish Environment Institute, 2006)
    Reports of the Finnish Environment Institute 21/2006
  • Laakom, Firas; Raitoharju, Jenni; Passalis, Nikolaos; Iosifidis, Alexandros; Gabbouj, Moncef (Institute of Electrical and Electronics Engineers (IEEE), 2022)
    IEEE Access
    Spectral-based subspace learning is a common data preprocessing step in many machine learning pipelines. The main aim is to learn a meaningful low dimensional embedding of the data. However, most subspace learning methods do not take into consideration possible measurement inaccuracies or artifacts that can lead to data with high uncertainty. Thus, learning directly from raw data can be misleading and can negatively impact the accuracy. In this paper, we propose to model artifacts in training data using probability distributions; each data point is represented by a Gaussian distribution centered at the original data point and having a variance modeling its uncertainty. We reformulate the Graph Embedding framework to make it suitable for learning from distributions and we study as special cases the Linear Discriminant Analysis and the Marginal Fisher Analysis techniques. Furthermore, we propose two schemes for modeling data uncertainty based on pair-wise distances in an unsupervised and a supervised contexts.
  • Janssen, Annette B. G.; Janse, Jan H.; Beusen, Arthur H. W.; Chang, Manqi; Harrison, John A.; Huttunen, Inese; Kong, Xiangzhen; Rost, Jasmijn; Teurlincx, Sven; Troost, Tineke A.; van Wijk, Dianneke; Mooij, Wolf M. (Elsevier, 2019)
    Current Opinion in Environmental Sustainability 36 (2019), 1-10
    Algal blooms increasingly threaten lake and reservoir water quality at the global scale, caused by ongoing climate change and nutrient loading. To anticipate these algal blooms, models to project future algal blooms worldwide are required. Here we present the state-of-the-art in algal projection modelling and explore the requirements of an ideal algal projection model. Based on this, we identify current challenges and opportunities for such model development. Since most building blocks are present, we foresee that algal projection models for any lake on earth can be developed in the near future. Finally, we think that algal bloom projection models at a global scale will provide a valuable contribution to global policymaking, in particular with respect to SDG 6 (clean water and sanitation).
  • Rankinen, Katri; Enrique, José; Bernal, Cano; Holmberg, Maria; Vuorio, Kristiina; Granlund, Kirsti (Elsevier, 2019)
    Science of The Total Environment 658 (2019), 1278-1292
    In Finland, a recent ecological classification of surface waters showed that the rivers and coastal waters need attention to improve their ecological state. We combined eco-hydrological and empirical models to study chlorophyll-a concentration as an indicator of eutrophication in a small agricultural river. We used a modified story-and-simulation method to build three storylines for possible changes in future land use due to climate change and political change. The main objective in the first storyline is to stimulate economic activity but also to promote the sustainable and efficient use of resources. The second storyline is based on the high awareness but poor regulation of environmental protection, and the third is to survive as individual countries instead of being part of a unified Europe. We assumed trade of agricultural products to increase to countries outside Europe. We found that chlorophyll-a concentration in the river depended on total phosphorus concentration. In addition, there was a positive synergistic interaction between total phosphorus and water temperature. In future storylines, chlorophyll-a concentration increased due to land use and climate change. Climate change mainly had an indirect influence via increasing nutrient losses from intensified agriculture. We found that well-designed agri-environmental measures had the potential to decrease nutrient loading from fields, as long as the predicted increase in temperature remained under 2 °C. However, we were not able to achieve the nutrient reduction stated in current water protection targets. In addition, the ecological status of the river deteriorated. The influence of temperature on chlorophyll-a growth indicates that novel measures for shading rivers to decrease water temperature may be needed in the future.
  • Holman, Ian P.; Brown, Calum; Carter, Timothy R.; Harrison, Paula A.; Rounsevell, Mark (Springer, 2019)
    Regional Environmental Change 19, 711–721 (2019)
    Climate change adaptation is a complex human process, framed by uncertainties and constraints, which is difficult to capture in existing assessment models. Attempts to improve model representations are hampered by a shortage of systematic descriptions of adaptation processes and their relevance to models. This paper reviews the scientific literature to investigate conceptualisations and models of climate change adaptation, and the ways in which representation of adaptation in models can be improved. The review shows that real-world adaptive responses can be differentiated along a number of dimensions including intent or purpose, timescale, spatial scale, beneficiaries and providers, type of action, and sector. However, models of climate change consequences for land use and water management currently provide poor coverage of these dimensions, instead modelling adaptation in an artificial and subjective manner. While different modelling approaches do capture distinct aspects of the adaptive process, they have done so in relative isolation, without producing improved unified representations. Furthermore, adaptation is often assumed to be objective, effective and consistent through time, with only a minority of models taking account of the human decisions underpinning the choice of adaptation measures (14%), the triggers that motivate actions (38%) or the time-lags and constraints that may limit their uptake and effectiveness (14%). No models included adaptation to take advantage of beneficial opportunities of climate change. Based on these insights, transferable recommendations are made on directions for future model development that may enhance realism within models, while also advancing our understanding of the processes and effectiveness of adaptation to a changing climate.
  • Krogerus, Kirsti; Pasanen, Antti (Suomen ympäristökeskus, 2016)
    Reports of the Finnish Environment Institute 39/2016
    Although mining companies have long been conscious of water related risks, they still face environmental management challenges. Several recent environmental incidents in Finnish mines have raised questions regarding mine site environmental and water management practices. This has increased public awareness of mining threats to the environment and resulted in stricter permits and longer permitting procedures. Water balance modelling aids in predictive water management and reduces risks caused by an excess or shortage of water at a mining site. In this study the primary objective was to exploit online water quantity and water quality measurements to better serve water balance management. The second objective was to develop and test mathematical models to calculate the water balance in mining operations. The third objective was to determine how monitoring and modelling tools can be integrated into the management system and process control. According to the experience gained from monitoring water balances, the main recommendation is that the data should be stored in a database where it is easily available for water balance calculations. For real-time simulations, online measurements should be available from strategically defined positions in the mine site. Groundwater may also act as a source or sink with respect to mine site surface water, and therefore monitoring and investigations should be designed to account for the full water balance. In Finland it is possible to calculate water balance for planning or for operative purposes by using the Watershed Simulation and Forecasting System (WSFS) developed at the Finnish Environment Institute (SYKE). This system covers every sub-basin (10-50 km2) over the whole of Finland. WSFS automatically obtains the latest observations of temperature, precipitation, water level, discharge and other needed data provided by the Finnish Meteorological Institute (FMI), SYKE, as well as other sources. The system also uses these observations to follow-up on simulation and forecasting accuracy. The water balance model was further developed to simulate and forecast the water balance at the Yara Siilinjärvi mine site. The WSFS-model was also extended with one-way coupling to the groundwater flow model. The model is operated via a web-based user interface and can produce water-balance forecasts automatically, if necessary, several times a day. The water balance and water flow in the area are simulated using real-time weather observations. The model enables forecasting water levels and planning discharges and pumping at the mine site. Possible uses of the model include preparation for spring floods by emptying ponds for storage of water from snow melt, estimation of the effect of heavy rainfall and calculating the required outflow from the mine site reservoir. Thus, overflows and dam-breaks can be avoided and consequently prevent the leakage of contaminated water. Furthermore, as the model can be modified to simulate changes at the mine site, it can also be beneficial during the mine site-planning process. The water balance model is currently operational for Yara Siilinjärvi mine site and hydrological forecasts are produced on a daily basis. Water level, discharge and pumping data, essential for modelling the area, are provided by the mine operator and EHP-Tekniikka Ltd. The model uses meteorological observations and forecasts from FMI as inputs for the simulations and forecasts. In addition to the accurate weather forecasts, the real time observations are a key factor in the accuracy of the model forecasts. GoldSim is the most popular commercial simulation software solution chosen, not only by mines worldwide, but also in many other sectors. One of the main reasons for its extensive use is its versatility and the ability to expand the program as the needs of the mine require. As the mine project progresses, one of GoldSim’s strongest assets is risk analysis at different phases during both the planning and execution of mine operations. The use of the GoldSim platform was tested during the project and some new features were developed. The project has paid special attention to commercialization of the developed products and well thought out policies for possible joint bids.
  • Mattinen, Maija; Heljo, Juhani (Finnish Environment Institute, 2016)
    Reports of the Finnish Environment Institute 26/2016
    Monitoring needs have increased in recent years, and answers to various questions related to the energy use of the building stock are needed faster than before. POLIREM model is a calculation model that assesses the effect of different policy scenarios on the Finnish building stock. The model determines the energy consumption and greenhouse gas emissions, and its purpose is to assist in the reporting and scenario work. The model has a strong linkage with the statistical data, and a top-down approach, which makes the POLIREM different from previous bottom-up style building stock models. The POLIREM model was originally developed at the Tampere University of Technology in MS excel environment. In this work, the model was converted into a coded version that ensures flexible scenario building, including ease of updating the input data, as well as enabling further integration of new features and/or data sources. This report provides a technical specification of the python-coded scenario model POLIREM. This report is part of development work to establish national reporting system/evaluation scheme, and fulfils requirements for openness by describing transparently the used evaluation method for building stock modelling.
  • Ropponen, Janne; Arola, Hanna; Kiuru, Petri; Huttula, Timo (Suomen ympäristökeskus, 2013)
    Reports of the Finnish Environment Institute 36/2013
    The City of Lappeenranta is considering options for its wastewater discharge sites in the future. One possibility is to release the treated wastewater into River Vuoksi, flowing through the City of Imatra, approximately 35 kilometres northeast from Lappeenranta. This report contains results from nutrient and fecal bacteria water quality modelling along River Vuoksi. The model endeavours to answer how the possible changes in wastewater discharge amounts and locations affect the river water quality near the freshwater intake at Svetogorsk, Russia. The river model was built using a river modelling system SOBEK from Deltares Systems. Calibration was done using data from the year 2010 and actual scenario simulations used 2011 data. According to the simulations there are no major water quality deviations compared to the current situation in normal operating scenarios, but there is some risk of water quality deterioration in certain catastrophic scenarios. The location of the discharge site might have some effect on the water quality due to the time required for the effluent to fully mix with the river water. Additionally a 3D research model of the southern Lake Saimaa was built to study passive tracer transport from two different sites near the City of Lappeenranta. The open source modelling software COHERENS was used to simulate scenarios during the open water period in years 2010 and 2011.
  • Kiczko, Adam; Västilä, Kaisa; Kozioł, Adam; Kubrak, Janusz; Kubrak, Elzbieta; Krukowski, Marcin (EGU, 2020)
    Hydrology and Earth System Sciences 24 8 (2020)
    Despite the development of advanced process-based methods for estimating the discharge capacity of vegetated river channels, most of the practical one-dimensional modeling is based on a relatively simple divided channel method (DCM) with the Manning flow resistance formula. This study is motivated by the need to improve the reliability of modeling in practical applications while acknowledging the limitations on the availability of data on vegetation properties and related parameters required by the process-based methods. We investigate whether the advanced methods can be applied to modeling of vegetated compound channels by identifying the missing characteristics as parameters through the formulation of an inverse problem. Six models of channel discharge capacity are compared in respect of their uncertainty using a probabilistic approach. The model with the lowest estimated uncertainty in explaining differences between computed and observed values is considered the most favorable. Calculations were performed for flume and field settings varying in floodplain vegetation submergence, density, and flexibility, and in hydraulic conditions. The output uncertainty, estimated on the basis of a Bayes approach, was analyzed for a varying number of observation points, demonstrating the significance of the parameter equifinality. The results showed that very reliable predictions with low uncertainties can be obtained for process-based methods with a large number of parameters. The equifinality affects the parameter identification but not the uncertainty of a model. The best performance for sparse, emergent, rigid vegetation was obtained with the Mertens method and for dense, flexible vegetation with a simplified two-layer method, while a generalized two-layer model with a description of the plant flexibility was the most universally applicable to different vegetative conditions. In many cases, the Manning-based DCM performed satisfactorily but could not be reliably extrapolated to higher flows.