TY - JOUR A1 - Grimm, Volker A1 - Augusiak, Jacqueline A1 - Focks, Andreas A1 - Frank, Beatrice M. A1 - Gabsi, Faten A1 - Johnston, Alice S. A. A1 - Liu, Chun A1 - Martin, Benjamin T. A1 - Meli, Mattia A1 - Radchuk, Viktoriia A1 - Thorbek, Pernille A1 - Railsback, Steven Floyd T1 - Towards better modelling and decision support: Documenting model development, testing, and analysis using TRACE JF - Ecological modelling : international journal on ecological modelling and engineering and systems ecolog N2 - The potential of ecological models for supporting environmental decision making is increasingly acknowledged. However, it often remains unclear whether a model is realistic and reliable enough. Good practice for developing and testing ecological models has not yet been established. Therefore, TRACE, a general framework for documenting a model's rationale, design, and testing was recently suggested. Originally TRACE was aimed at documenting good modelling practice. However, the word 'documentation' does not convey TRACE's urgency. Therefore, we re-define TRACE as a tool for planning, performing, and documenting good modelling practice. TRACE documents should provide convincing evidence that a model was thoughtfully designed, correctly implemented, thoroughly tested, well understood, and appropriately used for its intended purpose. TRACE documents link the science underlying a model to its application, thereby also linking modellers and model users, for example stakeholders, decision makers, and developers of policies. We report on first experiences in producing TRACE documents. We found that the original idea underlying TRACE was valid, but to make its use more coherent and efficient, an update of its structure and more specific guidance for its use are needed. The updated TRACE format follows the recently developed framework of model 'evaludation': the entire process of establishing model quality and credibility throughout all stages of model development, analysis, and application. TRACE thus becomes a tool for planning, documenting, and assessing model evaludation, which includes understanding the rationale behind a model and its envisaged use. We introduce the new structure and revised terminology of TRACE and provide examples. (C) 2014 Elsevier B.V. All rights reserved. KW - Standardization KW - Good modelling practice KW - Risk assessment KW - Decision support Y1 - 2014 U6 - https://doi.org/10.1016/j.ecolmodel.2014.01.018 SN - 0304-3800 SN - 1872-7026 VL - 280 SP - 129 EP - 139 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Augusiak, Jacqueline A1 - Van den Brink, Paul J. A1 - Grimm, Volker T1 - Merging validation and evaluation of ecological models to 'evaludation': A review of terminology and a practical approach JF - Ecological modelling : international journal on ecological modelling and engineering and systems ecolog N2 - Confusion about model validation is one of the main challenges in using ecological models for decision support, such as the regulation of pesticides. Decision makers need to know whether a model is a sufficiently good representation of its real counterpart and what criteria can be used to answer this question. Unclear terminology is one of the main obstacles to a good understanding of what model validation is, how it works, and what it can deliver. Therefore, we performed a literature review and derived a standard set of terms. 'Validation' was identified as a catch-all term, which is thus useless for any practical purpose. We introduce the term 'evaludation', a fusion of 'evaluation' and 'validation', to describe the entire process of assessing a model's quality and reliability. Considering the iterative nature of model development, the modelling cycle, we identified six essential elements of evaludation: (i) 'data evaluation' for scrutinising the quality of numerical and qualitative data used for model development and testing; (ii) 'conceptual model evaluation' for examining the simplifying assumptions underlying a model's design; (iii) 'implementation verification' for testing the model's implementation in equations and as a computer programme; (iv) 'model output verification' for comparing model output to data and patterns that guided model design and were possibly used for calibration; (v) 'model analysis' for exploring the model's sensitivity to changes in parameters and process formulations to make sure that the mechanistic basis of main behaviours of the model has been well understood; and (vi) 'model output corroboration' for comparing model output to new data and patterns that were not used for model development and parameterisation. Currently, most decision makers require 'validating' a model by testing its predictions with new experiments or data. Despite being desirable, this is neither sufficient nor necessary for a model to be useful for decision support. We believe that the proposed set of terms and its relation to the modelling cycle can help to make quality assessments and reality checks of ecological models more comprehensive and transparent. (C) 2013 Elsevier B.V. All rights reserved. KW - Model validation KW - Terminology KW - Decision support KW - Documentation KW - Ecological models KW - Risk assessment Y1 - 2014 U6 - https://doi.org/10.1016/j.ecolmodel.2013.11.009 SN - 0304-3800 SN - 1872-7026 VL - 280 SP - 117 EP - 128 PB - Elsevier CY - Amsterdam ER -