ASA Program aims to discover, develop, and deploy new, more effective, and efficient ways of infusing systems science into policy and decision making for sustainable development.
Despite numerous success stories, many policies and decisions that currently aim to deal with global change are not sufficiently informed by cutting-edge science. Among the major barriers that prevent the effective input of science into policy are perceived shortfalls in agility, realism, and relevance of the current generation of methods and models from the standpoint of end users. To address these barriers, ASA strives to advance agile, realistic, and relevant systems analytical tools and methods, and facilitate a shared understanding of the capabilities and limits of these tools and methods with end users. Consequently, ASA’s efforts span the full range, from advancing research methods and tools of systems analysis to innovating at the interface between policy- and decision making, as well as with society at large.
ASA Program’s major objectives are:
- To innovate approaches and tools to analyze increasingly systemic, social-ecological risks and support decisions aimed at enhancing resilience and facilitating sustainability transitions and transformations.
- To further the capacity of agile, on-demand systems analysis underpinned by a suite of modeling frameworks of appropriate complexity.
- To mobilize multiple sources of data and the power of data science to diagnose and identify solutions to reduce vulnerabilities and risks.
- To advance feasible and effective ways of engagement with policymakers, the private sector, and citizens.
- To enhance trust and shared understanding of systems analysis methods and tools, in particular, through open science.
Models, tools, datasets
15 March 2023
Helping young Africans innovate for climate resilience
03 February 2023
Exceptional young scientists awarded
25 January 2023
Driving inclusive and green urban transitions
28 March 2023
The future of biodiversity monitoring in Europe
15 February 2023
From farm to space and back: adapting Austrian agriculture to climate change
Juan Carlos Laso Bayas and colleagues reflect on the outcomes of the SATFARM Services project, which set out to create models that demonstrate the potential of satellite data to track climate-smart agricultural practices and visualize indicators to track their success in a prototype web platform for Austrian farmers.
05 December 2022
In pursuit of resilience at 1.5°C
Msangi, H.A., Waized, B., Lohr, K., Sieber, S., & Ndyetabula, D.W. (2023). Development outcomes of land tenure formalization under customary and statutory land tenure systems in Tanzania: a multinomial endogenous switching regression approach. Agriculture & Food Security 11 (1) 10.1186/s40066-022-00403-3.
Atolia, M., Loungani, P., Maurer, H., & Semmler, W. (2023). Optimal control of a global model of climate change with adaptation and mitigation. Mathematical Control and Related Fields 13 (2) 583-604. 10.3934/mcrf.2022009.
Neuvonen, L., Wildemeersch, M. , & Vilkkumaa, E. (2023). Supporting strategy selection in multiobjective decision problems under uncertainty and hidden requirements. European Journal of Operational Research 307 (1) 279-293. 10.1016/j.ejor.2022.09.036.
Zhang, Z., Yu, Y., & Kharrazi, A. (2023). Unstable decoupling of CO2 emissions from sectoral economic growth calls for decarbonization policies based on multi-perspective accounting: a case study of Zhejiang, China. Environmental Science and Pollution Research 10.1007/s11356-023-26513-4. (In Press)