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Qualitative nonsimulated models (causal loop diagrams, stock‐flow diagrams, or hybrids of both) have been used since within a decade after the inception of system dynamics (SD). In this article, we assert that the well‐known weaknesses of nonsimulated models need to be balanced against the contexts, purposes, and strengths that nonsimulated models provide. We propose a framework consisting of a set of best practices for model reporting and documentation that would improve the quality, consistency, and transparency of nonsimulated models. Several high‐quality examples are described and referenced in the framework to illustrate support of each criterion. The framework's purpose is help improve the transparency around the creation and evaluation of nonsimulated models, thereby enhancing their confidence and legitimate use in SD practice. Ultimately, high‐quality nonsimulated models can offer broader access to the powerful body of SD knowledge to audiences likely never to have access to formal SD simulation models. © 2023 System Dynamics Society.

 

Systems involving agriculture and natural resources (AGNR) management and representing integrations of biologic, geologic, socio-economic, and climatic characteristics are incredibly complex. AGNR managers purport using a systems-oriented mental model while many observed management and policy strategies remain linear or symptom-driven. To improve AGNR professionals’ systems thinking abilities, two programs, the King Ranch® Institute for Ranch Management at Texas A&M University-Kingsville (KRIRM) and the Honors College at South Dakota State University (SDSUHC), implemented the famous Production Distribution Simulation Game (a.k.a. the Beer Game) into their programs beginning in 2003 and 2011. A Beer Game database consisting of 10 years of trials or over 270 individual players was compared to seminal work in the literature as well as to one another. We found that AGNR managers and students performed worse than players in a seminal Beer Game study. More interestingly, we found that younger players adapted more readily to inventory surpluses by reducing the order rates and effective inventories significantly when compared to older players (p < 0.10 for retailer and distributors, and p < 0.05 for wholesales and factories). We substantiated our results to those in more recent studies of age-related decision-making and in the context of common learning disabilities. Lastly, we discuss some implications of such decision-making on 21st century AGNR problems and encourage AGNR disciplines to better integrate system dynamics-based education and collaboration in order to better prepare for such complex issues. 

Aeolian dust deposition is an important phosphorus (P) input to terrestrial ecosystems, but its influence on P dynamics during long-term ecosystem development remains poorly understood. In this study, we characterized P speciation using P K-edge XANES spectroscopy in surface soils (0–15 cm, A horizon) and contemporary aeolian dust collected at each site of a 3000-ky volcanic soil chronosequence in a cool, semi-arid environment. Phosphorus speciation in dust was dominated by calcium-bound P (Ca-P; 54–74%), with 11–23% iron and aluminum-bound P [(Fe + Al)-P] and 7–25% organic P (Po). In soils, Po contributed 1–23% of total P, being greater in older soils; however, the proportions of Ca-P (16–39%) and (Fe + Al)-P (48–82%) fluctuated with increasing weathering over the soil chronosequence. These soil fluctuations resulted from the accumulation and preservation of alkaline aeolian dust during pedogenesis in the semi-arid climate, which significantly increased soil Ca-P while decreasing the total amounts and relative abundances of soil (Fe + Al)-P. We suggest that the effects of an aeolian dust input on soil P transformations are functions of the relative magnitude and chemical composition of the dust input and the soil weathering intensity. For a given source of dust, when the net dust flux is greater than the weathering rate, dust accumulates and thus alters the pattern of P transformations during pedogenesis; otherwise, the dust influence on soil P transformations is negligible. By accurately identifying the chemical nature of P pools, our work highlights the advantage of P K-edge XANES spectroscopy over chemical extractions in examining soil P dynamics, and demonstrates how dust inputs can modify the Walker and Syers model of pedogenic P transformations in semi-arid environments. Overall, this work provides a foundation for understanding how dust influences P cycling during soil and ecosystem development, and indicates that dust inputs and composition, and the soil weathering rate, all must be considered for developing integrated climate-biogeochemical models with predictive power in terrestrial ecosystems. 

Aeolian dust deposition is an important phosphorus (P) input to terrestrial ecosystems, but its influence on P dynamics during long-term ecosystem development remains poorly understood. In this study, we characterized P speciation using P K-edge XANES spectroscopy in surface soils (0–15 cm, A horizon) and contemporary aeolian dust collected at each site of a 3000-ky volcanic soil chronosequence in a cool, semi-arid environment. Phosphorus speciation in dust was dominated by calcium-bound P (Ca-P; 54–74%), with 11–23% iron and aluminum-bound P [(Fe + Al)-P] and 7–25% organic P (Po). In soils, Po contributed 1–23% of total P, being greater in older soils; however, the proportions of Ca-P (16–39%) and (Fe + Al)-P (48–82%) fluctuated with increasing weathering over the soil chronosequence. These soil fluctuations resulted from the accumulation and preservation of alkaline aeolian dust during pedogenesis in the semi-arid climate, which significantly increased soil Ca-P while decreasing the total amounts and relative abundances of soil (Fe + Al)-P. We suggest that the effects of an aeolian dust input on soil P transformations are functions of the relative magnitude and chemical composition of the dust input and the soil weathering intensity. For a given source of dust, when the net dust flux is greater than the weathering rate, dust accumulates and thus alters the pattern of P transformations during pedogenesis; otherwise, the dust influence on soil P transformations is negligible. By accurately identifying the chemical nature of P pools, our work highlights the advantage of P K-edge XANES spectroscopy over chemical extractions in examining soil P dynamics, and demonstrates how dust inputs can modify the Walker and Syers model of pedogenic P transformations in semi-arid environments. Overall, this work provides a foundation for understanding how dust influences P cycling during soil and ecosystem development, and indicates that dust inputs and composition, and the soil weathering rate, all must be considered for developing integrated climate-biogeochemical models with predictive power in terrestrial ecosystems.