9.10 References
context. A process with many stakeholders in an
area with lots of data and good existing technical
resources should probably emphasize process and
conceptual tools. On the other hand, when there is
little existing data and few stakeholders, greater pri0rity may be put on technical data acquisition and
organization tools to develop the information base.
Many possible tools and approaches can foster integration of multidisciplinary information, as Figure 9.2 illustrates. A number of those listed are
complementary and ought to be a part of most integration exercises. Others, notably some of the
more advanced technical tools or large-scale facilitation and negotiation, may only be necessary in
particular circumstances. Practically speaking, the
choice of integration tools and effort should depend
on the decision costs and alternatives-how great
an expenditure can be justified economically and
scientifically.
Clearly, the most widely used tools ought to
be those with the potential to contribute to resolving many integration challenges; these include systems methods, simulation, teams, workshops, and
knowledge-based tools. What is critical is how they
are used, and earlier sections have sought to indicate useful ways. Making it all work together
means using effective, committed teams to coordinate, facilitate, and integrate. But teams cannot
work in isolation; they must have both support from
above and the opportunity to build support from
stakeholders and constituencies. And the whole
process requires time, access to data, and sufficient
funding. If integration is to get beyond lowest common denominator conclusions, public consultation
and involvement are necessary.
Critical needs are access to information, better
integrated tools, and more standardized data formats. More case studies of information integration,
such as those in this volume, would assist the planning of ecological assessment projects. Critical factors in determining success include defining goals
and products; adequate advance planning; fostering cooperation and standardization; choosing flexible, appropriate tools; using an appropriate transdisciplinary framework; and focusing on wholes,
not parts (cf. Holling, 1989). A successful exercise
in information integration is one that produces new
knowledge and understanding of the system and
new insights into appropriate management and the
effects of human activities; that broadens and
equalizes the base of understanding among stakeholders; and that creates flexible, adaptable products that can evolve and support future assessment
and planning exercises. This is a tall order, rarely
achieved as yet, but there is much experience in
129
this area and great potential for rapid learning in
the future.
9.9 Suggestions for
Additional Reading
Baskin, Y. 1997. Center seeks synthesis to make ecology more useful. Science 275: 31 0-11.
Born, S. M.; Sonzogni, W. C. 1995. Integrated environmental management: strengthening the conceptualization. Environ. Manage. 19(2):167-81.
Fedra, K. 1995. Decision support for natural resources
management: models, GIS, and expert systems. AI Applications 9(3):3-19.
GUnther, O. 1998. Environmental information systems.
Berlin: Springer-Verlag.
Weinberg, G. M. 1975. An introduction to general systems thinking. New York: John Wiley & Sons.
9.10 References
Adriaanse, A.; Jeltes, R.; Reiling, R. 1989. Information
requirements of integrated environmental policy experiences in the Netherlands. Environ. Manage.
13(3):309-315.
Alves, A. 1996. Parallel computing-windows style.
Byte, May:169-170.
Baird, 1. A.; Catling, P. c.; Ive, J. R 1994. Fire planning
for wildlife management: a decision support system
for Nadgee Nature Reserve, Australia. Int. J. Wildland
Fire 4(2):107-121.
Baskin, Y. 1997. Center seeks synthesis to make ecology more useful. Science 275:310-311.
Bastedo, J. D.; Nelson J. G.; Theberge, J. B. 1984. Ecological approach to resource survey and planning for
environmentally significant areas: the ABC method.
Environ. Manage. 8(2): 125-134.
Bisset, R 1987. Methods for environmental impact assessment: a selective survey with case studies. In:
Biswas, A.K.; Geping, Q., eds. Environmental impact
assessment for developing countries. Dublin: Tycooly
Int.: 5-64.
Born, S. M.; Sonzogni, W. C. 1995. Integrated environmental management: strengthening the conceptualization. Environ. Manage. 19(2):167-181.
Burns, T. R; Baumgartner, T.; DeVille, P. 1985. Man,
decisions, society: the theory of actor-system dynamics for social scientists. New York: Gordon and
Breach.
Clark, W. C. 1987. Scale relationships in the interactions
of climate, ecosystems, and societies. In: Land K. c.;
Schneider, S. R., eds. Forecasting in the social and
natural sciences. Dordrecht: D. Reidel: 337-378.
Cleaves, D. A. 1995. Assessing and communicating uncertainty in decision support systems: lessons from an
ecosystem policy analysis. AI Applications 9(3):87102.
context. A process with many stakeholders in an
area with lots of data and good existing technical
resources should probably emphasize process and
conceptual tools. On the other hand, when there is
little existing data and few stakeholders, greater pri0rity may be put on technical data acquisition and
organization tools to develop the information base.
Many possible tools and approaches can foster integration of multidisciplinary information, as Figure 9.2 illustrates. A number of those listed are
complementary and ought to be a part of most integration exercises. Others, notably some of the
more advanced technical tools or large-scale facilitation and negotiation, may only be necessary in
particular circumstances. Practically speaking, the
choice of integration tools and effort should depend
on the decision costs and alternatives-how great
an expenditure can be justified economically and
scientifically.
Clearly, the most widely used tools ought to
be those with the potential to contribute to resolving many integration challenges; these include systems methods, simulation, teams, workshops, and
knowledge-based tools. What is critical is how they
are used, and earlier sections have sought to indicate useful ways. Making it all work together
means using effective, committed teams to coordinate, facilitate, and integrate. But teams cannot
work in isolation; they must have both support from
above and the opportunity to build support from
stakeholders and constituencies. And the whole
process requires time, access to data, and sufficient
funding. If integration is to get beyond lowest common denominator conclusions, public consultation
and involvement are necessary.
Critical needs are access to information, better
integrated tools, and more standardized data formats. More case studies of information integration,
such as those in this volume, would assist the planning of ecological assessment projects. Critical factors in determining success include defining goals
and products; adequate advance planning; fostering cooperation and standardization; choosing flexible, appropriate tools; using an appropriate transdisciplinary framework; and focusing on wholes,
not parts (cf. Holling, 1989). A successful exercise
in information integration is one that produces new
knowledge and understanding of the system and
new insights into appropriate management and the
effects of human activities; that broadens and
equalizes the base of understanding among stakeholders; and that creates flexible, adaptable products that can evolve and support future assessment
and planning exercises. This is a tall order, rarely
achieved as yet, but there is much experience in
129
this area and great potential for rapid learning in
the future.
9.9 Suggestions for
Additional Reading
Baskin, Y. 1997. Center seeks synthesis to make ecology more useful. Science 275: 31 0-11.
Born, S. M.; Sonzogni, W. C. 1995. Integrated environmental management: strengthening the conceptualization. Environ. Manage. 19(2):167-81.
Fedra, K. 1995. Decision support for natural resources
management: models, GIS, and expert systems. AI Applications 9(3):3-19.
GUnther, O. 1998. Environmental information systems.
Berlin: Springer-Verlag.
Weinberg, G. M. 1975. An introduction to general systems thinking. New York: John Wiley & Sons.
9.10 References
Adriaanse, A.; Jeltes, R.; Reiling, R. 1989. Information
requirements of integrated environmental policy experiences in the Netherlands. Environ. Manage.
13(3):309-315.
Alves, A. 1996. Parallel computing-windows style.
Byte, May:169-170.
Baird, 1. A.; Catling, P. c.; Ive, J. R 1994. Fire planning
for wildlife management: a decision support system
for Nadgee Nature Reserve, Australia. Int. J. Wildland
Fire 4(2):107-121.
Baskin, Y. 1997. Center seeks synthesis to make ecology more useful. Science 275:310-311.
Bastedo, J. D.; Nelson J. G.; Theberge, J. B. 1984. Ecological approach to resource survey and planning for
environmentally significant areas: the ABC method.
Environ. Manage. 8(2): 125-134.
Bisset, R 1987. Methods for environmental impact assessment: a selective survey with case studies. In:
Biswas, A.K.; Geping, Q., eds. Environmental impact
assessment for developing countries. Dublin: Tycooly
Int.: 5-64.
Born, S. M.; Sonzogni, W. C. 1995. Integrated environmental management: strengthening the conceptualization. Environ. Manage. 19(2):167-181.
Burns, T. R; Baumgartner, T.; DeVille, P. 1985. Man,
decisions, society: the theory of actor-system dynamics for social scientists. New York: Gordon and
Breach.
Clark, W. C. 1987. Scale relationships in the interactions
of climate, ecosystems, and societies. In: Land K. c.;
Schneider, S. R., eds. Forecasting in the social and
natural sciences. Dordrecht: D. Reidel: 337-378.
Cleaves, D. A. 1995. Assessing and communicating uncertainty in decision support systems: lessons from an
ecosystem policy analysis. AI Applications 9(3):87102.