Fully Dynamic Input-Output/System Dynamics Modeling for Ecological-Economic System Analysis

Takuro Uehara,Mateo Cordier,Bertrand Hamaide

doi:10.3390/su10061765

Abstract

The complexity of ecological-economic systems significantly reduces our ability to investigate their behavior and propose policies aimed at various environmental and/or economic objectives. Following recent suggestions for integrating nonlinear dynamic modeling with input-output (IO) modeling, we develop a fully dynamic ecological-economic model by integrating IO with system dynamics (SD) for better capturing critical attributes of ecological-economic systems. We also develop and evaluate various scenarios using policy impact and policy sensitivity analyses. The model and analysis are applied to the degradation of fish nursery habitats by industrial harbors in the Seine estuary (Haute-Normandie region, France). The modeling technique, dynamization, and scenarios allow us to show trade-offs between economic and ecological outcomes and evaluate the impacts of restoration scenarios and water quality improvement on the fish population.

Highlights

Ecological-economic systems are “undeniably” [1] or even “devilishly” [2] complex
Following recent suggestions for integrating nonlinear dynamic modeling with input-output (IO) modeling, we develop a fully dynamic ecological-economic model by integrating IO with system dynamics (SD) for better capturing critical attributes of ecological-economic systems
While dynamic modeling captures the nonlinear dynamics of ecological-economic systems, IO enables the study of sectoral impacts [13,14]

Summary

Introduction

Ecological-economic systems are “undeniably” [1] or even “devilishly” [2] complex. Their complexity and nonlinear dynamic behaviors are due to interactions and feedback between components, processes, and systems [1,3]; non-marginal regimes with multiple equilibria [1]; non-convexity [4,5]; ecological and ecological-economic thresholds [6]; strategic interactions [7]; adaptive processes [6,7]; individual and spatial heterogeneity [7]; and varying time scales and lags [2,7].This complexity significantly reduces our ability to understand the way ecological-economic systems behave and provide useful policy insights [3,8]. Ecological-economic systems are “undeniably” [1] or even “devilishly” [2] complex Their complexity and nonlinear dynamic behaviors are due to interactions and feedback between components, processes, and systems [1,3]; non-marginal regimes with multiple equilibria [1]; non-convexity [4,5]; ecological and ecological-economic thresholds [6]; strategic interactions [7]; adaptive processes [6,7]; individual and spatial heterogeneity [7]; and varying time scales and lags [2,7]. There have been few attempts to integrate these two modeling approaches [15,16,17]

Methods

Results

Conclusion