02003nas a2200181 4500008003900000022001300039245013200052210006900184260001200253300001200265490000700277520134100284100002001625700001501645700001701660700001701677856012701694 2015 d a2212041600aThe Multiscale Integrated Model of Ecosystem Services (MIMES): Simulating the interactions of coupled human and natural systems0 aMultiscale Integrated Model of Ecosystem Services MIMES Simulati c04/2015 a30 - 410 v123 aIn coupled human and natural systems ecosystem services form the link between ecosystem function and what humans want and need from their surroundings. Interactions between natural and human components are bidirectional and define the dynamics of the total system. Here we describe the MIMES, an analytical framework designed to assess the dynamics associated with ecosystem service function and human activities. MIMES integrate diverse types of knowledge and elucidate how benefits from ecosystem services are gained and lost. In MIMES, users formalize how materials are transformed between natural, human, built, and social capitals. This information is synthesized within a systems model to forecast ecosystem services and human-use dynamics under alternative scenarios. The MIMES requires that multiple ecological and human dynamics be specified, and that outputs may be understood through different temporal and spatial lenses to assess the effects of different actions in the short and long term and at different spatial scales. Here we describe how MIMES methodologies were developed in association with three case studies: a global application, a watershed model, and a marine application. We discuss the advantages and disadvantage of the MIMES approach and compare it to other broadly used ecosystem service assessment tools.1 aBoumans, Roelof1 aRoman, Joe1 aAltman, Irit1 aKaufman, Les u//www.simulistics.com/publications/multiscale-integrated-model-ecosystem-services-mimes-simulating-interactions-coupled-hu03363nas a2200445 4500008003900000020001800039245010000057210006900157260001400226300001200240490000600252520204200258653005002300653002902350653002202379653002102401653002502422100001702447700001702464700002102481700001602502700002202518700001702540700001802557700001302575700001702588700001602605700001402621700001602635700001402651700001702665700001602682700001502698700001302713700001702726700001602743700001702759700001402776856012702790 2008 d a978008056886700aChapter Seven Integrated Modelling Frameworks for Environmental Assessment and Decision Support0 aChapter Seven Integrated Modelling Frameworks for Environmental  b Elsevier a101-1180 v33 a

In this chapter we investigate the motivation behind the development of modelling frameworks that explicitly target the environmental domain. Despite many commercial and industrial-strength frameworks being available, we claim that there is a definite niche for environmental-specific frameworks. We first introduce a general definition of what is an environmental integrated modelling framework, leading to an outline of the requirements for a generic software architecture for such frameworks. This identifies the need for a knowledge layer to support the modelling layer and an experimentation layer to support the execution of models.

The chapter then focuses on the themes of knowledge representation, model management and model execution. We advocate that appropriate knowledge representation and management tools can facilitate model integration and linking. We stress that a model development process adhering to industry standards and good practices, called “model engineering,” is to be pursued. We focus on the requirements of the experimental frame, which can ensure transparency and traceability in the execution of simulation scenarios and optimisation problems associated with complex integrated assessment studies.

A promising trend for knowledge representation is the use of ontologies that have the capacity to elicit the meaning of knowledge in a manner that is logical, consistent and understandable by computers and the knowledge worker community. This new path in knowledge-based computing will support retention of institutional knowledge, while putting modelling back in the hands of modellers. Environmental modelling will then become a conceptual activity, focusing on model design rather than model implementation, with code generation being delegated to some degree to ontology-aware tools. In this respect, we envision the whole model lifecycle to change drastically, becoming more of a theoretical activity and less of a coding-intensive, highly engineering-oriented task.

10aenvironmental integrated modelling frameworks10aknowledge representation10amodel engineering10amodel management10amodelling frameworks1 aRizzoli, A E1 aLeavesley, G1 aII, Ascough, J C1 aArgent, R M1 aAthanasiadis, I N1 aBrilhante, V1 aClaeys, F H A1 aDavid, O1 aDonatelli, M1 aGijsbers, P1 aHavlik, D1 aKassahun, A1 aKrause, P1 aQuinn, N W T1 aScholten, H1 aSojda, R S1 aVilla, F1 aJakeman, A J1 aVoinov, A A1 aRizzoli, A E1 aChen, S H u//www.simulistics.com/publications/chapter-seven-integrated-modelling-frameworks-environmental-assessment-and-decision-sup01972nas a2200229 4500008003900000245005400039210005400093260001200147300001200159490000700171520127800178653003601456653001801492653001601510653001501526100002301541700002401564700002901588700002201617700001701639856008601656 2008 d00aSemantic links in integrated modelling frameworks0 aSemantic links in integrated modelling frameworks c07/2008 a412-4230 v783 a

It is commonly accepted that modelling frameworks offer a powerful tool for modellers, researchers and decision makers, since they allow the management, re-use and integration of mathematical models from various disciplines and at different spatial and temporal scales. However, the actual re-usability of models depends on a number of factors such as the accessibility of the source code, the compatibility of different binary platforms, and often it is left to the modellers own discipline and responsibility to structure a complex model in such a way that it is decomposed in smaller re-usable sub-components. What reusable and interchangeable means is also somewhat vague; although several approaches to build modelling frameworks have been developed, little attention has been dedicated to the intrinsic re-usability of components, in particular between different modelling frameworks. In this paper, we focus on how models can be linked together to build complex integrated models. We stress that even if a model component interface is clear and reusable from a software standpoint, this is not a sufficient condition for reusing a component across different integrated modelling frameworks. This reveals the need for adding rich semantics in model interfaces.

10aIntegrated modelling frameworks10aModel linking10aModel reuse10aOntologies1 aRizzoli, Andrea, E1 aDonatelli, Marcello1 aAthanasiadis, Ioannis, N1 aVilla, Ferdinando1 aHuber, David u//www.simulistics.com/publications/semantic-links-integrated-modelling-frameworks