Search results for "pää"
showing 10 items of 880 documents
Modelling circulation in an ice-covered lake
2010
In deep ice-covered lakes with temperatures below 4 °C the heat flux from the bottom sediment results in a horizontal density gradient and a consequent flow along the bottom slope. Measurements in Lake Paajarvi, Finland, show a stable temperature field where a heat gain through the bottom and a heat loss through the ice nearly balance each other. The circulation is thermal with low velocities (less than 1.5 cm s -1 ). We used the 3D hydrodynamic Princeton Ocean Model as a tool to simulate the water circulation and the temperature distribution under the ice. The model forcing was based on field temperature measurements. The model simulations suggest that in midwinter the velocity field of th…
Calibrating Expert Assessments Using Hierarchical Gaussian Process Models
2020
Expert assessments are routinely used to inform management and other decision making. However, often these assessments contain considerable biases and uncertainties for which reason they should be calibrated if possible. Moreover, coherently combining multiple expert assessments into one estimate poses a long-standing problem in statistics since modeling expert knowledge is often difficult. Here, we present a hierarchical Bayesian model for expert calibration in a task of estimating a continuous univariate parameter. The model allows experts' biases to vary as a function of the true value of the parameter and according to the expert's background. We follow the fully Bayesian approach (the s…
Guidelines for risk management in forest planning – what is risk and when is risk management useful?
2018
Managing forest resources occurs under various sources of uncertainty. Depending on the management problem, this uncertainty may have a substantial impact on the quality of the solution. As our knowledge on the sources and magnitude of uncertainty improves, integrating this knowledge into the development of management plans becomes increasingly useful, as additional information can improve the decision-making process. This adjustment requires a fundamental shift in how planning problems are viewed: instead of interpreting risk management as a technique needed only for addressing problems with natural hazards, risk management should be an integral part of most planning problems. Managing ri…
Value of information in multiple criteria decision making: an application to forest conservation
2019
Abstract Developing environmental conservation plans involves assessing trade-offs between the benefits and costs of conservation. The benefits of conservation can be established with ecological inventories or estimated based on previously collected information. Conducting ecological inventories can be costly, and the additional information may not justify these costs. To clarify the value of these inventories, we investigate the multiple criteria value of information associated with the acquisition of improved ecological data. This information can be useful when informing the decision maker to acquire better information. We extend the concept of the value of information to a multiple crite…
Sustainable Mixed Cropping Systems for the Boreal-Nemoral Region
2020
Mixed cropping, including intercropping, is the oldest form of systemized agricultural production and involves the growing of two or more species or cultivars of the same species simultaneously in the same field. However, mixed cropping has been little by little replaced by sole crop systems, especially in developed countries. Some of the advantages of mixed cropping are, for example, resource use efficiency and yield stability, but there are also several challenges, such as weed management and competition. The boreal-nemoral region lies within the region 55° to 70° N. In this area, for example in Finland, the length of the thermal growing season varies from less than 105 to over 185 days. …
Quantifying and addressing the prevalence and bias of study designs in the environmental and social sciences
2020
Building trust in science and evidence-based decision-making depends heavily on the credibility of studies and their findings. Researchers employ many different study designs that vary in their risk of bias to evaluate the true effect of interventions or impacts. Here, we empirically quantify, on a large scale, the prevalence of different study designs and the magnitude of bias in their estimates. Randomised designs and controlled observational designs with pre-intervention sampling were used by just 23% of intervention studies in biodiversity conservation, and 36% of intervention studies in social science. We demonstrate, through pairwise within-study comparisons across 49 environmental da…
Epiphytic bacteria make an important contribution to heterotrophic bacterial production in a humic boreal lake
2017
Bacterial production (BP) in lakes has generally only been measured in the pelagic zone without accounting for littoral BP, and studies of BP at the whole-lake scale are very scarce. In the dystrophic humic lakes, which are common throughout the boreal region, low light penetration through water has been assumed to seriously limit available habitats for littoral organisms. However, many highly humic boreal lakes have extensive partly submerged vegetation around the lake perimeter which can provide well-lit substrata for highly productive epiphyton. We measured epiphytic BP on the littoral vegetation and pelagic BP in a small highly humic boreal lake in Finland during an open-water season an…
Patented intelligence: Cloning human decision models for Industry 4.0
2018
Industry 4.0 is a trend related to smart factories, which are cyber-physical spaces populated and controlled by the collective intelligence for the autonomous and highly flexible manufacturing purposes. Artificial Intelligence (AI) embedded into various planning, production, and management processes in Industry 4.0 must take the initiative and responsibility for making necessary real-time decisions in many cases. In this paper, we suggest the Pi-Mind technology as a compromise between completely human-expert-driven decision-making and AI-driven decision-making. Pi-Mind enables capturing, cloning and patenting essential parameters of the decision models from a particular human expert making …
DESDEO: The Modular and Open Source Framework for Interactive Multiobjective Optimization
2021
Interactive multiobjective optimization methods incorporate preferences from a human decision maker in the optimization process iteratively. This allows the decision maker to focus on a subset of solutions, learn about the underlying trade-offs among the conflicting objective functions in the problem and adjust preferences during the solution process. Incorporating preference information allows computing only solutions that are interesting to the decision maker, decreasing computation time significantly. Thus, interactive methods have many strengths making them viable for various applications. However, there is a lack of existing software frameworks to apply and experiment with interactive …
Comparing interactive evolutionary multiobjective optimization methods with an artificial decision maker
2021
AbstractSolving multiobjective optimization problems with interactive methods enables a decision maker with domain expertise to direct the search for the most preferred trade-offs with preference information and learn about the problem. There are different interactive methods, and it is important to compare them and find the best-suited one for solving the problem in question. Comparisons with real decision makers are expensive, and artificial decision makers (ADMs) have been proposed to simulate humans in basic testing before involving real decision makers. Existing ADMs only consider one type of preference information. In this paper, we propose ADM-II, which is tailored to assess several …