Toward a complete interdisciplinary treatment of scale

Abstract

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.

Importance of Anthropogenic Determinants of Tubastraea coccinea Invasion in the Northern Gulf of Mexico

“…The relative importance of independent variables may also vary with the stage of invasion [40,49]. The selection of specific independent variables may have markedly changed the model development and likelihood estimates [41], which is a general problem related to structural uncertainty in the quantitative representation of natural systems [50,51]. In our study, the possibility always remains that we failed to include some important independent variables, and that the relative importance of those variables we included depends on the current state of the system [35,40].…”

Scale decisions and good practices in socio-environmental systems modelling: guidance and documentation during problem scoping and model formulation

“…Problem scoping and conceptual model formulation ideally are conducted within the context of a well-defined model purpose. For modelling that addresses problems requiring interdisciplinary scientific expertise and input from a heterogeneous group of stakeholders, identifying appropriate model objectives is particularly challenging (Elsawah et al, 2020;Iwanaga et al, 2021b;Jakeman et al, 2006). Most commonly a general statement of project objectives from a funding source is what brings modelling groups together in the first place.…”