Innovations in Collaborative Modeling

William Porter

ISBN 10: 1611863546 / ISBN 13: 9781611863543

Published by Michigan State University Press, US, 2020

About this Item

Collaborative applications of a variety of modeling methodologies have multiplied in recent decades due to widespread recognition of the power of models to integrate information from multiple sources, test assumptions about policy and management choices, and forecast the future states of complex systems. However, information about these modeling efforts often is segregated by both discipline and modeling approach, preventing modelers from learning from one another. This volume addresses the need for cross-disciplinary and cross-methodological communication about collaborative modeling. To enhance a shared understanding of systems problems, scientists and stakeholders need strategies for integrating information from their respective fields, dealing with issues of scale and focus, and rigorously investigating assumptions. The chapters in this volume first explore modeling methodologies for enhanced collaboration, then offer case studies of collaborative modeling across different complex systems problems. The volume will be useful for experienced and beginning modelers as well as scientists and stakeholders who work with modelers.

Seller Inventory # LU-9781611863543

Bibliographic Details

• Title: Innovations in Collaborative Modeling
• Publisher: Michigan State University Press, US
• Publication Date: 2020
• Language: English
• ISBN 10: 1611863546
• ISBN 13: 9781611863543
• Binding: Paperback
• Condition: New

About this title

Synopsis

Collaborative applications of a variety of modeling methodologies have multiplied in recent decades due to widespread recognition of the power of models to integrate information from multiple sources, test assumptions about policy and management choices, and forecast the future states of complex systems. However, information about these modeling efforts often is segregated by both discipline and modeling approach, preventing modelers from learning from one another. This volume addresses the need for cross-disciplinary and cross-methodological communication about collaborative modeling. To enhance a shared understanding of systems problems, scientists and stakeholders need strategies for integrating information from their respective fields, dealing with issues of scale and focus, and rigorously investigating assumptions. The chapters in this volume first explore modeling methodologies for enhanced collaboration, then offer case studies of collaborative modeling across different complex systems problems. The volume will be useful for experienced and beginning modelers as well as scientists and stakeholders who work with modelers.

About the Authors

LAURA SCHMITT OLABISI is an Associate Professor in the Department of Community Sustainability and the Environmental Science and Policy Program at Michigan State University.

MILES MCNALL is the Director of the Community Evaluation and Research Collaborative at Michigan State University.

WILLIAM PORTER is a Professor and the first Boone and Crockett Chair of Wildlife Conservation in the Department of Fisheries and Wildlife at Michigan State University.

JINHUA ZHAO is a Professor in the Department of Economics and the Department of Agricultural, Food, and Resource Economics, and the Director of the Environmental Science and Policy Program at Michigan State University.