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      Socio-technical scales in socio-environmental modeling: managing a system-of-systems modeling approach

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          Abstract

          System-of-systems approaches for integrated assessments have become prevalent in recent years. Such approaches integrate a variety of models from different disciplines and modeling paradigms to represent a socio-environmental (or social-ecological) system aiming to holistically inform policy and decision-making processes. Central to the system-of-systems approaches is the representation of systems in a multi-tier framework with nested scales. Current modeling paradigms, however, have disciplinary-specific lineage, leading to inconsistencies in the conceptualization and integration of socio-environmental systems. In this paper, a multidisciplinary team of researchers, from engineering, natural and social sciences, have come together to detail socio-technical practices and challenges that arise in the consideration of scale throughout the socio-environmental modeling process. We identify key paths forward, focused on explicit consideration of scale and uncertainty, strengthening interdisciplinary communication, and improvement of the documentation process. We call for a grand vision (and commensurate funding) for holistic system-of-systems research that engages researchers, stakeholders, and policy makers in a multi-tiered process for co-creation of knowledge and solutions to major socio-environmental problems.

          Highlights

          • Scale incompatibilities among system representations of constituent systems are identified as a key challenge in socio-environmental systems modeling.

          • Issues of scale arise from the complexity, size and heterogeneity of the constituent systems and their interactions.

          • A more holistic systems-of-systems modeling framework is needed within which to integrate current approaches and tools.

          • A range of system modeling considerations within the socio-technical context of system-of-systems modeling is presented based on input from a variety of disciplinary and interdisciplinary experts.

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          Observation of a new particle in the search for the Standard Model Higgs boson with the ATLAS detector at the LHC

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            The use of the multi-model ensemble in probabilistic climate projections.

            Recent coordinated efforts, in which numerous climate models have been run for a common set of experiments, have produced large datasets of projections of future climate for various scenarios. Those multi-model ensembles sample initial condition, parameter as well as structural uncertainties in the model design, and they have prompted a variety of approaches to quantify uncertainty in future climate in a probabilistic way. This paper outlines the motivation for using multi-model ensembles, reviews the methodologies published so far and compares their results for regional temperature projections. The challenges in interpreting multi-model results, caused by the lack of verification of climate projections, the problem of model dependence, bias and tuning as well as the difficulty in making sense of an 'ensemble of opportunity', are discussed in detail.
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              Reproducible research in computational science.

              Roger Peng (2011)
              Computational science has led to exciting new developments, but the nature of the work has exposed limitations in our ability to evaluate published findings. Reproducibility has the potential to serve as a minimum standard for judging scientific claims when full independent replication of a study is not possible.
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                Author and article information

                Journal
                Environ Model Softw
                Environ Model Softw
                Environmental Modelling & Software
                Published by Elsevier Ltd.
                1364-8152
                1873-6726
                6 October 2020
                6 October 2020
                : 104885
                Affiliations
                [1 ]Institute for Water Futures and Fenner School of Environment and Society, The Australian National University, Canberra, Australia
                [2 ]Ecological Systems Laboratory, Department of Ecology and Conservation Biology, Texas A&M University, College Station, TX, 77843, USA
                [3 ]CSIRO Land & Water, Canberra, Australia
                [4 ]Helmholtz Centre for Environmental Research - UFZ, Department of Ecological Modelling, Leipzig, Germany
                [5 ]University of Potsdam, Plant Ecology and Nature Conservation, Potsdam, Germany
                [6 ]Grado Department of Industrial and Systems Engineering, Virginia Tech, Blacksburg, VA, 24061, USA
                [7 ]School of Electrical Engineering and Information Technology, University of New South Wales, Australian Defence Force Academy, Canberra, ACT, Australia
                [8 ]Global Institute for Water Security, School of Environment and Sustainability, Department of Civil, Geological, and Environmental Engineering, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
                [9 ]National Institute of Water and Atmospheric Research, New Zealand
                [10 ]U.S. Department of the Interior, U.S. Geological Survey, Reston, Virginia, USA
                [11 ]Centre for Research in Social Simulation, University of Surrey, Guildford, GU2 7XH, United Kingdom
                [12 ]Center on Persuasive Systems for Wise Adaptive Living (PERSWADE), Faculty of Engineering & IT, University of Technology, Sydney, Australia
                [13 ]Key Laboratory of Virtual Geographic Environment (Nanjing Normal University), Ministry of Education, Nanjing, 210023, China
                [14 ]Environmental Science and Engineering Program, University of Texas at El Paso, El Paso, TX, 79968, USA
                [15 ]U.S Geological Survey, Chesapeake Bay Program, Annapolis, MD, 21403, USA
                [16 ]Center for Social Dynamics & Complexity, School of Human Evolution & Social Change, Arizona State University, Tempe, Arizona
                [17 ]Department of Civil and Environmental Engineering, Virginia Tech, Blacksburg, VA, 24061, USA
                Author notes
                []Corresponding author.
                Article
                S1364-8152(20)30942-7 104885
                10.1016/j.envsoft.2020.104885
                7537632
                f015031d-0863-4213-8c8e-024abcd6b61c
                © 2020 Published by Elsevier Ltd.

                Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

                History
                : 29 September 2020
                Categories
                Article

                social-ecological modeling,interdisciplinary modeling,integrated modeling,scale issues,system-of-systems approach

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