Browsing by Subject "uncertainty"

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  • Barton, David Nicholas; Kelemen, Eszter; Dick, Jan; Martín-López , Berta; Gomez-Baggethun, Erik; Jacobs, Sander; Hendriks, C.M.A.; Termansen, Mette; Garcia-Llorente, M.; Primmer, Eeva; Dunford, Rob; Harrison, Paula; Turkelboom, Francis; Saarikoski, Heli; van Dijk, J.; Rusch, Graciela M.; Palomo, Ignacio; Yli-Pelkonen, Vesa Johannes; Carvalho, Laurence; Baro, Francesc; Langemeyer, Johannes; Tjalling van der Wal, Jan; Mederly, Peter; Priess, Joerg; Luque, Sandra; Berry, Pam; Santos, Rui; Odee, David; Martinez Pastur, Guillermo; Garcia Blanco, Gemma; Saarela, Sanna-Riikka; Silaghi, Diana; Pataki, György; Masi, Fabio; Vadineanu, Angheluta; Mukhopadhyay, Raktima; Lapola, David (2018)
    The operational challenges of integrated ecosystem service (ES) appraisals are determined by study purpose, system complexity and uncertainty, decision-makers' requirements for reliability and accuracy of methods, and approaches to stakeholder-science interaction in different decision contexts. To explore these factors we defined an information gap hypothesis, based on a theory of cumulative uncertainty in ES appraisals. When decision context requirements for accuracy and reliability increase, and the expected uncertainty of the ES appraisal methods also increases, the likelihood of methods being used is expected to drop, creating a potential information gap in governance. In order to test this information gap hypothesis, we evaluate 26 case studies and 80 ecosystem services appraisals in a large integrated EU research project. We find some support for a decreasing likelihood of ES appraisal methods coinciding with increasing accuracy and reliability requirements of the decision-support context, and with increasing uncertainty. We do not find that information costs are the explanation for this information gap, but rather that the research project interacted mostly with stakeholders outside the most decision-relevant contexts. The paper discusses how alternative definitions of integrated valuation can lead to different interpretations of decision-support information, and different governance approaches to dealing with uncertainty. (C) 2017 Elsevier B.V. All rights reserved.
  • Miettinen, Katariina (Helsingin yliopisto, 2022)
    Objectives: Personality traits have been associated with fertility behaviour, but associations between personality and fertility intentions, especially uncertainty in fertility intentions, have not been studied before. Uncertainty in fertility intentions is the state in which an individual is not sure whether to have (more) children. Fertility intentions have been used to project population trends and to better understand reproductive decision-making processes. In this study, uncertainty in fertility intentions is studied from a biological point of view, by examining personality traits and their associations with uncertainty in fertility intentions, as well as how these associations differ between men and women. Methods: The data used in this study was from the German family panel (pairfam). The respondents (n=4420) were childless men and women aged 18-45 years. Long-term fertility intentions were assessed with a question about how many children the respondents realistically intended to have in their lifetime, and the answers were divided into three categories, one of which represented uncertain intentions. Personality traits were assessed using a short version of the Big Five Inventory. The associations were analyzed using multinomial logistic regression, and gender differences were analyzed using interaction terms between personality traits and gender. Age, partnership status, education and residence were controlled in the analysis. Results and conclusion: All personality traits, except extraversion, were associated with fertility intentions independent of socio-demographic factors. Higher neuroticism and openness were associated with higher uncertainty in fertility intentions, whereas higher conscientiousness and agreeableness were associated with higher likelihood of intending to have children. There were no differences between men and women in these associations. Male gender, older age, not having a partner, and higher education were related to higher uncertainty in fertility intentions. The results are mostly in line with previous studies on the associations between personality and actual number of children, except for conscientiousness, which has previously been associated with lower fertility. This study strengthens the notion that biological factors have associations with fertility behaviour, stressing the importance of further research on the topic.
  • Kahiluoto, Joonas; Hirvonen, Jukka; Näykki, Teemu (Springer, 2019)
    Environmental Monitoring and Assessment 191, 259 (2019)
    Continuous sensor measurements are becoming an important tool in environmental monitoring. However, the reliability of field measurements is still too often unknown, evaluated only through comparisons with laboratory methods or based on sometimes unrealistic information from the measuring device manufacturers. A water turbidity measurement system with automatic reference sample measurement and measurement uncertainty estimation was constructed and operated in laboratory conditions to test an approach that utilizes validation and quality control data for automatic measurement uncertainty estimation. Using validation and quality control data for measurement uncertainty estimation is a common practice in laboratories and, if applied to field measurements, could be a way to enhance the usability of field sensor measurements. The measurement system investigated performed replicate measurements of turbidity in river water and measured synthetic turbidity reference solutions at given intervals during the testing period. Measurement uncertainties were calculated for the results using AutoMUkit software and uncertainties were attached to appropriate results. The measurement results correlated well (R2 = 0.99) with laboratory results and the calculated measurement uncertainties were 0.8–2.1 formazin nephelometric units (FNU) (k = 2) for 1.2–5 FNU range and 11–27% (k = 2) for 5–40 FNU range. The measurement uncertainty estimation settings (such as measurement range selected and a number of replicates) provided by the user have a significant effect on the calculated measurement uncertainties. More research is needed especially on finding suitable measurement uncertainty estimation intervals for different field conditions. The approach presented is also applicable for other online measurements besides turbidity within limits set by available measurement devices and stable reference solutions. Potentially interesting areas of application could be the measurement of conductivity, pH, chemical oxygen demand (COD)/total organic carbon (TOC), or metals.
  • Pihlajamäki, Mia-Elina; Helle, Inari; Haapasaari, Päivi; Sarkki, Simo; Kuikka, Sakari; Lehikoinen, Annukka (2020)
    Fisheries management aims to ensure that the fishing activities are environmentally sustainable in the long term, while also achieving the economic, social and food security related management objectives. To facilitate this, both the ecological and human dimensions of sustainability need to be included in fisheries assessment. In addition, assessing long-term sustainability calls for taking into account plausible changes in the surrounding societal conditions that shape the characteristics of the fisheries governance system, as well as the ecological conditions. The paper uses a combination of qualitative exploratory scenario storylines (ESS) and Bayesian belief networks (BBN) to integrate the environmental, economic, social and food security dimensions in an interdisciplinary assessment of the future sustainability of Baltic herring (Clupea harengus membras, Clupeidae) and salmon (Salmo salar, Salmonidae) fisheries. First, four alternative ESS were created based on plausible changes in societal drivers. The ESS were then formulated into a BBN to (a) visualize the assumed causalities, and (b) examine quantitatively how changes in the societal drivers affect the social-ecological fisheries system and ultimately the fisheries management objectives. This type of probabilistic scenario synthesis can help in thinking qualitative scenarios in a quantitative way. Moreover, it can increase understanding on the causal links between societal driving forces and the complex fisheries system and on how the management objectives can be achieved, thereby providing valuable information for strategic decision-making under uncertainty.
  • Lehtoranta, Virpi; Louhi, Pauliina (Elsevier Science, 2021)
    Environmental Science & Policy 124, 226-234
    Non-market values pose a challenge in decision making. In a contribution to the issue, the study assesses the potential positive impact on residents’ wellbeing of improving the ecological status of water bodies making up the Saarijärvi watercourse in Central Finland, a region with numerous Natura areas. The benefits provided by the aquatic environment and the factors affecting them were assessed using the contingent valuation method (CVM). A split-sample design made it possible to analyse expressed uncertainty with two payment vehicles: in one, the question of uncertainty was included in the willingness-to-pay (WTP) questions (multiple bounded discrete choice, MBDC); in the other, it was queried separately after the payment card (PC) question. Where respondents saw added value in Natura 2000 sites and received new information on water management, they experienced increased wellbeing from improved water quality. Perceived importance of sustainable hydropower and water regulation also figured in a desire to improve the ecological status of waters in the region. The results show that there is a noticeable positive WTP among residents (N = 473) for improved water status and that estimated WTP differs according to uncertainty: mean WTP every year per individual fell in the range EUR 29.70 to EUR 75.50. Improvement of water status and protection of Natura 2000 sites were found to be mutually reinforcing goals. Higher net social benefits could be realized if implementation of the applicable directives were more closely coupled to regional planning.
  • Rosenberg, Matts (Swedish School of Economics and Business Administration, 2002)
    Working Papers
    This paper analyzes the effect of uncertainty on investment and labor demand for Finnish firms during the time period 1987 – 2000. Utilizing a stock return based measure of uncertainty decomposed into systematic and idiosyncratic components, the results reveal that idiosyncratic uncertainty significantly reduces both investment and labor demand. Idiosyncratic uncertainty seems to influence investment in the current period, whereas the depressing effect on labor demand appears with a one-year lag. The results provide support that the depressing effect of idiosyncratic uncertainty on investment is stronger for small firms in comparison to large firms. Some evidence is reported regarding differential effects of uncertainty on labor demand conditional on firm characteristics. Most importantly, the depressing effect of lagged idiosyncratic uncertainty on labor demand tends to be stronger for diversified firms compared with focused firms.
  • Vepsäläinen, Jari; Ritari, Antti; Lajunen, Antti; Kivekäs, Klaus; Tammi, Kari (2018)
    Uncertainty in operation factors, such as the weather and driving behavior, makes it difficult to accurately predict the energy consumption of electric buses. As the consumption varies, the dimensioning of the battery capacity and charging systems is challenging and requires a dedicated decision-making process. To investigate the impact of uncertainty, six electric buses were measured in three routes with an Internet of Things (IoT) system from February 2016 to December 2017 in southern Finland in real operation conditions. The measurement results were thoroughly analyzed and the operation factors that caused variation in the energy consumption and internal resistance of the battery were studied in detail. The average energy consumption was 0.78 kWh/km and the consumption varied by more than 1 kWh/km between trips. Furthermore, consumption was 15% lower on a suburban route than on city routes. The energy consumption was mostly influenced by the ambient temperature, driving behavior, and route characteristics. The internal resistance varied mainly as a result of changes in the battery temperature and charging current. The energy consumption was predicted with above 75% accuracy with a linear model. The operation factors were correlated and a novel second-order normalization method was introduced to improve the interpretation of the results. The presented models and analyses can be integrated to powertrain and charging system design, as well as schedule planning.
  • Purtonen, Henni (Helsingin yliopisto, 2018)
    Managing uncertainty in change: a case study on communication and uncertainty in the Gulf of Finland Coast Guard District Besides the changes that have occurred in the Finnish security authorities’ operational environment, cuts in the financial resources of the Finnish Border Guard have intensified internal pressures for change in the line-and-staff organisation and the need to create new modes of operation. In this Master’s Thesis, the relationship between the uncertainty associated with change and the internal communication of the organisation was examined from the viewpoint of the complexity theory. The purpose of this case study was to extend our understanding of the phenomenon of uncertainty and to try and find better ways of managing uncertainty arising from change in the communication processes of the Finnish Border Guard. From the perspective of the philosophy of science, this study is based on hermeneutical thinking, in which knowledge is constructed through interpretation, layer by layer, from preliminary understanding to conclusions. The empirical data consist of eleven themed interviews of employees of the Gulf of Finland Coast Guard District, which were analysed by means of theory-led content analysis. The interview data were supplemented with documentary material, including a plan for economic and financial adjustment drawn up within the Finnish Border Guard. The perceptions of the interviewees were structured as narratives formed at different administrative levels of the organisation and were examined through the lenses of uncertainty, complexity, and change. The attained understanding of the uncertainty arising from change was deepened by means of a complexity-theoretical framework and the concept of sensemaking. It was found that the problem of managing a complex communication network and dynamic organisational processes boils down to information and interaction amongst the various actors. The experience of uncertainty is situative and subjective. Regardless of whether uncertainty in the organisation was examined from the point of view of external or internal change, uncertainty was seen as a factor impairing the organisation’s performance. The conclusion was drawn in the study that the uncertainty arising from change can be managed more effectively if the narrative of change is created from the points of view of both the organisation and the individual employee. Other helpful measures are ensuring the continuity of the communicative narrative and promoting multifaceted dialogue and interaction amongst the administrative levels. The results indicate that the organisation’s problem-solving ability is largely based on the management of uncertainty, i.e., that the organisation lends a sensitive ear to the dynamism of social systems and harnesses the information transmitted through the feedback processes into a part of the narrative of change-management communication. When communication is understood as an ever-changing and evolving narrative process, the management of uncertainty becomes closely linked with the management of complexity and the strengthening of the organisation’s resilience. This study supplements the scholarly discourse on the management of uncertainty and functions as an empirical window into the application of complexity-theoretical concepts to organisation research.
  • Holopainen, Ida (Helsingin yliopisto, 2021)
    Traditional parametric statistical inference methods, such as maximum likelihood and Bayesian inference, cannot be used to learn parameter estimates if the likelihood is intractable, for example due to the complexity of the studied phenomenon. This can be overcome by using likelihood-free inference that is used with simulator-based models to learn parameter estimates. Also, traditional methods used in the estimation of uncertainties related to the parameter estimates typically require a likelihood function, and that is why these methods cannot be applied in likelihood-free inference. In this thesis, we present a novel way to compute confidence sets for parameter estimates obtained from likelihood-free inference using Jensen—Shannon divergence. We consider two test statistics that are based on mean Jensen—Shannon divergence and propose hypothesised asymptotic distributions for them. We test whether these hypothesised distributions can be used in the computation of confidence sets for parameter estimates obtained from likelihood-free inference, and we evaluate the produced confidence sets by studying their frequentist behaviour that is summarised with coverage probabilities. We compare this frequentist behaviour between Jensen —Shannon divergence estimates and confidence sets obtained from grid evaluation of Monte Carlo estimates and from Bayesian optimisation for likelihood-free inference (BOLFI) to the ones obtained from maximum likelihood inference with Wald’s and log likelihood-ratio confidence sets using three different models. We also use a simulator- based model with intractable likelihood to study the proposed confidence sets with BOLFI. In order to study the influence of observations on the parameter estimates and their confidence sets, we conducted these experiments with varying the number of observations. We show that Jensen—Shannon divergence based confidence sets meet the expected frequentist behaviour.
  • Bettencourt da Silva, Ricardo J.N; Saame, Jaan; Anes, Bárbara; Heering, Agnes; Leito, Ivo; Näykki, Teemu; Stoica, Daniela; Deleebeeck, Lisa; Bastkowski, Frank; Snedden, Alan; Camões, M. Filomena (Elsevier, 2021)
    Analytica Chimica Acta 1182 (2021), 338923
    The use of the unified pH concept, pHabsH2O, applicable to aqueous and non-aqueous solutions, which allows interpreting and comparison of the acidity of different types of solutions, requires reliable and objective determination. The pHabsH2O can be determined by a single differential potentiometry measurement referenced to an aqueous reference buffer or by a ladder of differential potentiometric measurements that allows minimisation of inconsistencies of various determinations. This work describes and assesses bottom-up evaluations of the uncertainty of these measurements, where uncertainty components are combined by the Monte Carlo Method (MCM) or Taylor Series Approximation (TSM). The MCM allows a detailed simulation of the measurements, including an iterative process involving in minimising ladder deviations. On the other hand, the TSM requires the approximate determination of minimisation uncertainty. The uncertainty evaluation was successfully applied to measuring aqueous buffers with pH of 2.00, 4.00, 7.00, and 10.00, with a standard uncertainty of 0.01. The reference and estimated values from both approaches are metrologically compatible for a 95% confidence level even when a negligible contribution of liquid junction potential uncertainty is assumed. The MCM estimated pH values with an expanded uncertainty, for the 95% confidence level, between 0.26 and 0.51, depending on the pH value and ladder inconsistencies. The minimisation uncertainty is negligible or responsible for up to 87% of the measurement uncertainty. The TSM quantified measurement uncertainties on average only 0.05 units larger than the MCM estimated ones. Additional experimental tests should be performed to test these uncertainty models for analysis performed in other laboratories and on non-aqueous solutions.
  • Ekholm, Bo-Göran; Wallin, Jan (Svenska handelshögskolan, 2006)
    Working Papers
    This paper examines the relationships between uncertainty and the perceived usefulness of traditional annual budgets versus flexible budgets in 95 Swedish companies. We form hypotheses that the perceived usefulness of the annual budgets as well as the attitudes to more flexible budget alternatives are influenced by the uncertainty that the companies face. Our study distinguishes between two separate kinds of uncertainty: exogenous stochastic uncertainty (deriving from the firm’s environment) and endogenous deterministic uncertainty (caused by the strategic choices made by the firm itself). Based on a structural equations modelling analysis of data from a mail survey we found that the more accentuated exogenous uncertainty a company faces, the more accentuated is the expected trend towards flexibility in the budget system, and vice versa; the more endogenous uncertainty they face, the more negative are their attitudes towards budget flexibility. We also found that these relationships were not present with regard to the attitudes towards the usefulness of the annual budget. Noteworthy is, however, that there was a significant negative relationship between the perceived usefulness of the annual budget and budget flexibility. Thus, our results seem to indicate that the degree of flexibility in the budget system is influenced by both general attitudes towards the usefulness of traditional budgets and by the actual degree of exogenous uncertainty a company faces and by the strategy that it executes.
  • Global Burden of Disease Self-Harm Collaboration; Orpana, H.M.; Doku, D.T.; Meretoja, T.J.; Shiri, R.; Vasankari, T. (2019)
    Objectives To use the estimates from the Global Burden of Disease Study 2016 to describe patterns of suicide mortality globally, regionally, and for 195 countries and territories by age, sex, and Socio-demographic index, and to describe temporal trends between 1990 and 2016. Design Systematic analysis. Main outcome measures Crude and age standardised rates from suicide mortality and years of life lost were compared across regions and countries, and by age, sex, and Socio-demographic index (a composite measure of fertility, income, and education). Results The total number of deaths from suicide increased by 6.7% (95% uncertainty interval 0.4% to 15.6%) globally over the 27 year study period to 817 000 (762 000 to 884 000) deaths in 2016. However, the age standardised mortality rate for suicide decreased by 32.7% (27.2% to 36.6%) worldwide between 1990 and 2016, similar to the decline in the global age standardised mortality rate of 30.6%. Suicide was the leading cause of age standardised years of life lost in the Global Burden of Disease region of high income Asia Pacific and was among the top 10 leading causes in eastern Europe, central Europe, western Europe, central Asia, Australasia, southern Latin America, and high income North America. Rates for men were higher than for women across regions, countries, and age groups, except for the 15 to 19 age group. There was variation in the female to male ratio, with higher ratios at lower levels of Socio-demographic index. Women experienced greater decreases in mortality rates (49.0%, 95% uncertainty interval 42.6% to 54.6%) than men (23.8%, 15.6% to 32.7%). Conclusions Age standardised mortality rates for suicide have greatly reduced since 1990, but suicide remains an important contributor to mortality worldwide. Suicide mortality was variable across locations, between sexes, and between age groups. Suicide prevention strategies can be targeted towards vulnerable populations if they are informed by variations in mortality rates. © Published by the BMJ Publishing Group Limited.
  • 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.
  • Muscatello, Angela; Elith, Jane; Kujala, Heini (2021)
    Species distribution models (SDMs) are increasingly used in conservation and land-use planning as inputs to describe biodiversity patterns. These models can be built in different ways, and decisions about data preparation, selection of predictor variables, model fitting, and evaluation all alter the resulting predictions. Commonly, the true distribution of species is unknown and independent data to verify which SDM variant to choose are lacking. Such model uncertainty is of concern to planners. We analyzed how 11 routine decisions about model complexity, predictors, bias treatment, and setting thresholds for predicted values altered conservation priority patterns across 25 species. Models were created with MaxEnt and run through Zonation to determine the priority rank of sites. Although all SDM variants performed well (area under the curve >0.7), they produced spatially different predictions for species and different conservation priority solutions. Priorities were most strongly altered by decisions to not address bias or to apply binary thresholds to predicted values; on average 40% and 35%, respectively, of all grid cells received an opposite priority ranking. Forcing high model complexity altered conservation solutions less than forcing simplicity (14% and 24% of cells with opposite rank values, respectively). Use of fewer species records to build models or choosing alternative bias treatments had intermediate effects (25% and 23%, respectively). Depending on modeling choices, priority areas overlapped as little as 10-20% with the baseline solution, affecting top and bottom priorities differently. Our results demonstrate the extent of model-based uncertainty and quantify the relative impacts of SDM building decisions. When it is uncertain what the best SDM approach and conservation plan is, solving uncertainty or considering alterative options is most important for those decisions that change plans the most.
  • Nevalainen, Maisa Katariina; Vanhatalo, Jarno; Helle, Inari (2019)
    Risk of an Arctic oil spill has become a global matter of concern. Climate change induced opening of shipping routes increases the Arctic maritime traffic which exposes the area to negative impacts of potential maritime accidents. Still, quantitative analyses of the likely environmental impacts of such accidents are scarce, and our understanding of the uncertainties related to both accidents and their consequences is poor. There is an obvious need for analysis tools that allow us to systematically analyze the impacts of oil spills on Arctic species, so the risks can be taken into account when new sea routes or previously unexploited oil reserves are utilized. In this paper, an index‐based approach is developed to study exposure potential (described via probability of becoming exposed to spilled oil) and sensitivity (described via oil‐induced mortality and recovery) of Arctic biota in the face of an oil spill. First, a conceptual model presenting the relevant variables that contribute to exposure potential and sensitivity of key Arctic marine functional groups was built. Second, based on an extensive literature review, a probabilistic estimate was assigned for each variable, and the variables were combined to an index representing the overall vulnerability of Arctic biota. The resulting index can be used to compare the relative risk between functional groups and accident scenarios. Results indicate that birds have the highest vulnerability to spilled oil, and seals and whales the lowest. Polar bears’ vulnerability varies greatly between seasons, while ice seals’ vulnerability remains the same in every accident scenario. Exposure potential of most groups depends strongly on type of oil, whereas their sensitivity contains less variation.
  • Lehtiniemi, Heidi (Helsingin yliopisto, 2020)
    Computing complex phenomena into models providing information of the causalities and future scenarios is a very topical way to present scientific information. Many claim models to be the best available tool to provide decision making with information about near-future scenarios and the action needed (Meah, 2019; Schirpke et al., 2020). This thesis studies global climate models based on objective data compared to local ecosystem services models combining ecological and societal data offer an extensive overview of modern environmental modelling. In addition to modelling, the science-policy boundary is important when analyzing the societal usefulness of models. Useful and societally-relevant modelling is analyzed with an integrative literature review (Whittemore & Knafl, 2005) on the topics of climate change, ecosystem services, modelling and science-policy boundary, n=58. Literature from various disciplines and viewpoints is included in the material. Since the aim is to create a comprehensive understanding of the multidisciplinary phenomenon of modelling, the focus is not on the technical aspects of it. Based on the literature, types of uncertainty in models and strategies to manage them are identified (e.g. van der Sluijs, 2005). Characteristics of useful models and other forms of scientific information are recognized (e.g. Saltelli et al., 2020). Usefulness can be achieved when models are fit for purpose, accessible and solution-oriented, and sufficient interaction and trust is established between the model users and developers. Climate change and ecosystem services are analyzed as case studies throughout the thesis. The relationship of science and policy is an important discussion especially important when solving the sustainability crisis. Because modelling is a boundary object (Duncan et al., 2020), the role of boundary work in managing and communicating the uncertainties and ensuring the usefulness of models is at the center of the analysis.
  • Kujala, Heini; Lahoz-Monfort, José Joaquín; Elith, Jane; Moilanen, Atte (2018)
    Decisions about land use significantly influence biodiversity globally. The field of spatial conservation prioritisation explores allocation of conservation effort, including for reserve network expansion, targeting habitat restoration, or minimising ecological impacts of development. Inevitably, the utility of such planning depends on the quantity and quality input data, including spatial information on biodiversity, threats, and cost of action. In this work we systematically develop understanding about the significance of these different data types in spatial conservation prioritisation. We clarify the common ways different data types enter an analysis, develop mathematical models to understand the effects of data in spatial prioritisation, and survey literature to establish typical quantities of different types of data used. We use Jackknife analysis to derive the expected change in site values, when a single new data layer is added to a prioritisation. We validate mathematical formulae for expected impacts using simulations. A survey of scientific literature reveals that typical spatial prioritisation analyses include hundreds of biodiversity feature layers (species, habitat types, ecosystem services), but the count of cost, threat or habitat condition layers is typically 0-5. Due to these differences, and the mathematical formulations commonly used to combine data types, the influence of a single cost, threat, or habitat condition data layer can be an order or two higher than the influence of a single biodiversity feature layer. In a classical cost-effectiveness formulation (benefits divided by costs, B/C) the influence of a single cost layer can even be as large as the joint influence of thousands of species distributions. We also clarify how changes in data impact site values and spatial priority rankings differently, with the latter being further influenced by data correlations, the spread of numeric values inside data layers and other data characteristics. For example, costs influence priorities significantly if cost is positively correlated with biodiversity, but the correlation is the other way around for biodiversity and habitat condition. This work helps conservation practitioners to direct efforts when collating data for spatial conservation planning. It also helps decision makers understand where to focus attention when interpreting conservation plans and their uncertainties.
  • Härkönen, Heidi Kristiina (2016)
    Losing its closest socialist ally, the Soviet Union, launched Cuba into a severe economic and political crisis that forced the state to make several concessions to its earlier ideals. State services and contributions to the population were severely cut, the country was opened to international tourism and day-to-day life became increasingly monetised, favouring some whilst marginalising others. Expectations of the crisis were that it would create widespread popular resistance to the state. Drawing on ethnographic evidence from contemporary Havana, this report explores how individuals relate to Cuba’s current state discourse in the context of the island’s recent political and economic transformations. The dynamics between large-scale developments and individuals’ everyday lives is approached through the notion of dialectics of care, which highlights the multifaceted relationships that people maintain with state institutions, whilst simultaneously finding inventive ways to negotiate the continuing political and economic precarity.
  • 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.
  • Jaakkola, Olli (Finnish Geodetic Institute, 1996)
    FGI Publications 122