Global effectiveness of group decision-making strategies in coping with forage and price variabilities in commercial rangelands: A modelling assessment

Implementing climate change projections in System Dynamics models

Desertification is the degradation of drylands, which occupy an increasing proportion of the Earth's surface due to global warming. It is currently the most extensive biome on Earth, occupying 45% and one out of every three inhabitants of the planet live in them. One of the most effective ways to face desertification, as Land Degradation Neutrality points out, is prevention. For this purpose, simulation models are very useful tools. Specifically, System Dynamics models are particularly effective, since they allow bringing together the biophysical and socioeconomic variables involved in the formation of the problem. These integrative models, coupled with other tools such as sensitivity analyses, are used to generate desertification early warning indicators. The objective of this programming routine is to implement climate change scenarios in these simulation models. The script presented here was used to evaluate the sensitivity of dehesa rangelands productivity to the increase in the frequency and intensity of droughts due to climate change.•Integrated simulation models are useful tools to understand complex socioecosystems.•Land-use changes foster the alteration of key hydro-bio-geochemical processes.•By means of automated import processes and data analysis programming, it is possible to implement desertification early warning systems.

Environment, Business, and Health Care Prevail: A Comprehensive, Systematic Review of System Dynamics Application Domains

System dynamics, as a methodology for analyzing and understanding various types of systems, has been applied in research for several decades. We undertook a review to identify the latest application domains and map the realm of system dynamics. The systematic review was conducted according to the PRISMA methodology. We analyzed and categorized 212 articles and found that the vast majority of studies belong to the fields of business administration, health, and environmental research. Altogether, 20 groups of modeling and simulation topics can be recognized. System dynamics is occasionally supported by other modeling methodologies such as the agent-based modeling approach. There are issues related to published studies mostly associated with testing of validity and reasonability of models, leading to the development of predictions that are not grounded in verified models. This study contributes to the development of system dynamics as a methodology that can offer new ideas, highlight limitations, or provide analogies for further research in various research disciplines.

Exploring the economic, social and environmental prospects for commercial natural annual grasslands by performing a sensitivity analysis on a multidisciplinary integrated model

This paper presents an integrated modelling study aimed at exploring the possible effects of drivers of change in commercial natural annual grasslands. We consider drivers as factors that affect the rangeland but are not affected by it. Thus, the stocking rate is not treated as a driver, but as an endogenous factor ultimately determined by drivers. This approach, which call for integrated multidisciplinary studies, is rare in the rangeland literature. We try to alleviate this lack by presenting and utilizing a novel multidisciplinary integrated system-dynamics model (108 equations) which represents an area of privately owned extensive farms, its farmers (their numbers and decisions), herds or flocks, herbage production, soil erosion and the linked local markets. By means of a global sensitivity analysis of this model we evaluated the sensitivities of key endogenous factors to the same percentage variation in 70 factors, including economic and climate drivers. The analysis considered the behaviours of 288,000 variants of the modelled system, each under a different 300-year driver scenario. We found that the environmental component of the model was almost exclusively sensitive to biophysical factors, whereas the socio-economic component was almost exclusively sensitive to socio-economic factors, despite the model takes account of key feedbacks connecting both components. Our results suggest that cautiously-managed commercial natural grasslands could socially and economically cope with climate change, especially in a scenario of rising prices of animal products, and also that, even though stocking rates would increase due to an increase in the demand for livestock products, the main threat to the provision of ecosystem services in the studied system would be climate change.