To ensure the success of this program of research, a number of resources will
need to be in place. Support is needed for interdisciplinary research involving
statisticians, applied mathematicians, computational scientists, and experts from multiple
fields, including, but not limited to, ecology, atmospheric science, oceanography,
epidemiology, sociology, and economics. In addition to research on basic methodology,
however, there are issues connected with constructing both datasets and computer
programs in a form that can be permanently archived and made available to other
researchers. This will require investment in database sciences and geographical
information sciences; there is also a need to involve statistical computing scientists to
develop efficient algorithms and user-friendly software required to implement modern
statistical and mathematical methods on the scale required for effective implementation.
As part of this, we envision the establishment of a national data center / portal for
sustainability research that would potentially house, maintain, and/or provide links to
publically available datasets relevant to sustainability research. This would greatly
facilitate the ability of members from the mathematical sciences community to tackle the
research themes outlined in Section 3.
Our recommendations to the mathematical sciences community can be
summarized by the following points:
- Build and evaluate tools that can be broadly applicable to a range of problems in
sustainability as identified in Section 3. - Develop the iterative process for combining data, models, and forecasting in the
context of the complexity discussed in Section 3. - Develop methods for estimating parameters and quantify uncertainty in complex
models. - Expand upon or develop new protocols for evaluating the agreement between
models and data in the context of the complexity discussed in Section 3. - Establish strategies for integrating data from different sampling designs.
- Establish strategies for acquiring data from multiple independent sources using the
same sampling design.
Our recommendations to funding agencies and the scientific community at large can be
summarized by the following points:
- Facilitate and promote multi-disciplinary research teams that support collaborations
between the mathematical sciences (mathematics, statistics, computational
scientists) and the subject/applied fields associated with addressing sustainability
problems (e.g., ecologists, atmospheric scientists, oceanographers, social scientists,
economists). - Provide mechanisms for improved infrastructure related to research support for the
development, maintenance, and querying of databases, and provide computing
support necessary for implementation of computational or statistical algorithms and
user-friendly software. An example of a particularly important resource is the creation
of a national data center for sustainability research.
- Final remarks