- Mathematical scientists, in partnerships with scientists in other disciplines,
should develop mathematical theories of sustainability science. The integration of
science, data and computational models is critical. Current or emerging areas of
the mathematical sciences that are relevant to this activity include uncertainty
quantification, massive datasets, complex adaptive systems, parameter
estimation and model selection, integrating data from different sampling designs,
stochastic optimization and game theory, inverse problems and multi-scale
systems.
- Scientists working in areas related to sustainability should form
interdisciplinary teams with mathematical scientists, including mathematicians,
statisticians, operations researchers, computer scientists and mathematical
economists, together with experts from many subject matter fields. Researchers
should also collaborate with industry.
- There should be a focus on education at all levels, including new courses and
research seminars on the mathematics of sustainability for graduate students,
activities aimed at undergraduates and K-12, and communication with
policymakers and the general public.
- It is essential to develop paradigms for sharing data and models. One possible
mechanism is a national sustainability data center containing links to publicly
accessible datasets, computer programs and models.
- Funding agencies should consider the most appropriate funding mechanisms
for encouraging research in mathematical sustainability science. One possibility
is a grants competition requiring collaboration between researchers from two or
more disciplines, similar to NSF's Collaborations in Mathematical Geosciences
initiative. Funding for such a program needs to include specific resources for data
processing and computer programming.