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SHELscape is a spatially-explicit agent-based model for understanding short-run post-natural disasters non-linear adjustment processes in a multi-market framework.
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A dataset to understand near-term emissions mitigation and adaptation efforts
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A software tool to to aggregate several probability distributions into a single integrated one
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A tool for exploratory statistical analysis on land use data
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A model for studying the ecology and evolution of plant communities
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Scenathons: Interactive Scenario and Development Pathway Planning
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The linkage algorithms solve the problem of linking models, e.g. sectorial and/or regional, into an inter-sectorial inter-regional integrated model. Linkage enables to avoid “hard linking” of models in a single code, which saves the programming time and enables parallel distributed computations of individual models instead of a large scale integrated model. Models linkage preserves the structure of the original models taking into account critically important details, which are usually missing in aggregate models.
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Stochastic Quasi-Gradient (SQG) methods have been developed for solving general optimization problems without exact calculation of objective function and constraints (let alone of their derivatives). SQG methods enable a sequential revision of approximate solutions towards the optimal using newly acquired information on the system, obtained via either direct on-line observations or(and) simulations.
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A tool to assess temporal verification of net greenhouse gas emission changes under the Kyoto Protocol
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The IIASA/ESM based BGC-MAN model was calibrated and validated with TrEco data for the dominant ecosystems and land use forms of the Congo basin, including virgin forests, managed forests, forest fallows after shifting cultivation and savannahs.
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Assessing management impacts on the BioGeoChemistry of ecosystems
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The BinD model is a new generation dynamic disaster-macroeconomic modeling framework that captures supply and demand-side constraints on a developing economy facing disaster risk.
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The Working Group on Fisheries-Induced Evolution (WGEVO) of the International Council for the Exploration of the Sea (ICES) has developed a general framework for investigating eco-evolutionary changes in fish stocks and their utilities in terms of ecosystem services and for assessing the management implications of fisheries-induced evolution through Evolutionary Impact Assessments (EvoIAs).
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Despite modern medical interventions, infectious diseases continue to generate huge socio-economic losses.
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Ensuring that common goods and open-access resources—everything from clean air and the global climate to the internet and civil security—are equitably and fairly available to everyone requires incentive mechanisms.
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The complexity and dynamical nature of community interactions make modelling a useful tool for understanding how biodiversity patterns in communities develop over time and how they respond to external perturbations.
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The Working Group on Fisheries-Induced Evolution (WGEVO) of the International Council for the Exploration of the Sea (ICES) has developed a general framework for investigating eco-evolutionary changes in fish stocks and their utilities in terms of ecosystem services and for assessing the management implications of fisheries-induced evolution through Evolutionary Impact Assessments (EvoIAs).
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The framework for eco-genetic modeling offers flexible tools for exploring the course and rates of multi-trait life-history evolution in natural populations.
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Biodiversity patterns in natural ecosystems are dynamically sustained by food webs, describing the feeding relations among all ecosystem compartments, including the involved animal and plants.