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Ecological Modeling: An Introduction to the Art and Science of Modeling Ecological Systems, Volume 31, presents the skills needed to appropriately evaluate and use ecological models. Illustrated throughout with practical examples, the book discusses ecological modeling as both an art and a science, balancing the qualitative (artistic) side, with its foundations in common sense and modeling practice, against the quantitative (scientific) aspects of the modeling process. This book draws on the authors' extensive experience in both teaching and using these techniques to provide readers with a practical, user-friendly guide that supports and encourages the appropriate, effective use of these tools. Key Features: Provides readers with a commonsense understanding of the systems perspective and its foundations in general system theory; Highlights the importance of a solid understanding of the qualitative aspects of the modeling process; Facilitates the ability to appropriately evaluate and use ecological models; Supports learning with a variety of simple examples to instill the desire and confidence to embark upon the modeling experience. Readership: Primer and reference book for natural resource and environmental professionals at both managerial and policy levels whose jobs involve the development, evaluation, and/or use of ecological models. Professionals in programs dealing with wildlife and fisheries management, forestry, and environmental quality, as well as those focusing on more specific areas such as pest control and the management of endangered species, invasive species, and emerging diseases. Graduate-level and upper-division undergraduate-level students in courses covering topics related to the use of systems analysis and simulation in ecology, natural resource management, and the environment. --

The pathways taken throughout any model-based process are undoubtedly influenced by the modeling team involved and the decision choices they make. For interconnected socioenvironmental systems (SES), such teams are increasingly interdisciplinary to enable a more expansive and holistic treatment that captures the purpose, the relevant disciplines and sectors, and other contextual settings. In practice, such interdisciplinarity increases the scope of what is considered, thereby increasing choices around model complexity and their effects on uncertainty. Nonetheless, the consideration of scale issues is one critical lens through which to view and question decision choices in the modeling cycle. But separation between team members, both geographically and by discipline, can make the scales involved more arduous to conceptualize, discuss, and treat. In this article, the practices, decisions, and workflow that influence the consideration of scale in SESs modeling are explored through reflexive accounts of two case studies. Through this process and an appreciation of past literature, we draw out several lessons under the following themes: (1) the fostering of collaborative learning and reflection, (2) documenting and justifying the rationale for modeling scale choices, some of which can be equally plausible (a perfect model is not possible), (3) acknowledging that causality is defined subjectively, (4) embracing change and reflection throughout the iterative modeling cycle, and (5) regularly testing the model integration to draw out issues that would otherwise be unnoticeable. ; Australian Government Research Training Program ScholarshipAustralian GovernmentDepartment of Industry, Innovation and Science; Australian National University Hilda-John Endowment Fund; USDA Agricultural Research ServiceUnited States Department of Agriculture (USDA)USDA Agricultural Research Service [3072-22000-017-07-S]; National Centre for Groundwater Research and Training [MD2594]; National Science Foundation (NSF)National Science Foundation (NSF) [1937012]; National Socio-Environmental Synthesis Center [NSF DBI1639145] ; Published version ; The primary author (Takuya Iwanaga) is supported through an Australian Government Research Training Program Scholarship and a top-up scholarship from the Australian National University Hilda-John Endowment Fund. Hsiao-Hsuan Wang and Tomasz E. Koralewski acknowledge partial support from the USDA Agricultural Research Service provided through the Areawide Pest Management Program, "Areawide Pest Management of the Invasive Sugarcane Aphid in Grain Sorghum," project number 3072-22000-017-07-S. The Campaspe Integrated Model was developed as part of the Murray-Darling Basin Authority's partnership with the National Centre for Groundwater Research and Training under Contract No. MD2594. John Little acknowledges support from National Science Foundation (NSF) Award EEC 1937012. This work was also supported by the National Socio-Environmental Synthesis Center under funding received from the NSF DBI1639145.

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 socioenvironmental (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 socioenvironmental 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 the co-creation of knowledge and solutions to major socio-environmental problems. ; National Socio-Environmental Synthesis Center (SESYNC) under the National Science Foundation [DBI-1639145]; Australian Government Research Training Program (AGRTP) ScholarshipAustralian Government; ANU Hilda-John Endowment Fund; USDAUnited States Department of Agriculture (USDA); ARSUnited States Department of Agriculture (USDA)USDA Agricultural Research Service [58-3091-6-035]; Texas A&M AgriLife Research; Key Program of NSF of China [41930648]; NSFNational Science Foundation (NSF) [EEC 1937012] ; Published version ; This work was supported by the National Socio-Environmental Synthesis Center (SESYNC) under funding received from the National Science Foundation DBI-1639145. The primary author (Takuya Iwanaga) is supported through an Australian Government Research Training Program (AGRTP) Scholarship and a top-up scholarship from the ANU Hilda-John Endowment Fund. Hsiao-Hsuan Wang and Tomasz E. Koralewski acknowledge partial support from USDA, ARS Agreement No. 58-3091-6-035 with Texas A&M AgriLife Research, titled `Areawide pest management of the invasive sugarcane aphid in grain sorghum, regional population monitoring and forecasting.' Min Chen is supported by the Key Program of NSF of China (No. 41930648). John Little acknowledges partial support from NSF Award EEC 1937012. The authors would like to thank the three anonymous reviewers and Prof. Randall Hunt (USGS) for their constructive feedback and comments. The authors additionally thank Faye Duchin and Adrian Hindes for comments provided on an earlier draft. ; Public domain authored by a U.S. government employee