Spatial Decision Support Systems for Ecological Restoration and Management
Leonard G. Pearlstine and Frank J. Mazzotti
Department of Wildlife Ecology and Conservation, University of Florida, Ft.
Lauderdale, FL
Donald L. DeAngelis
US Geological Survey, University of Miami, Coral Gables, FL
Decision support systems (DSS) are broadly defined as computer-based systems
used to aid decision makers using data and models to solve unstructured problems
(Sprague and Carlson 1982). Support methodologies that help authorities involved
in ecological restoration sort out all the decision variables and parameters,
categorize problem solving heuristics, and appreciate the impacts of potential
policy actions are critical to successful planning and management (Kersten et al.
2000). DSS supports adaptive management initiatives by facilitating the planning
process in goal formation, selection of alternative strategies for implementation,
and targeting monitoring.
A complete spatial DSS requires more than just the provision of a simple interface
for viewing spatial data. Components of a DSS may include: (1) knowledge
acquisition and representation, (2) goals and issues identification and conflict
resolution, (3) alternatives evaluation, and (4) group negotiation support.
Establishing a modular design and evaluating the need for these components as
DSS development progresses can seamlessly integrate them as necessary and as
funding and time permits.
Knowledge acquisition and representation is principally the ability to bring in and
update spatial data layers used to portray landscape and habitat variables, the
decision rules for how these data layers interact, and easy to navigate viewers for
display of the data. A preliminary list of available spatially explicit data layers
from modeled output that may be a part of the decision process in south Florida
includes: (1) Vegetation Classification and Modeling; (2) Wildlife Species
Habitats; (3) Hydrology; (4) Urban Growth and Socioeconomic; and Sealevel
Rise Models.
Defining a goal or multiple goals establishes endpoints. The DSS helps the user
evaluate compatibility of the goals, resolve conflicts in the proposed goal set, and
estimate how successful a particular alternative will be in achieving a set of goals
(Nute et al 2000).
A DSS should provide tools for priority setting and for measuring changes in the
landscape with indices of landscape pattern, linkages and fragmentation, diversity,
ecological integrity that match published success criteria such those prepared for
the Working Group of the South Florida Ecosystem Restoration Taskforce
(Science Subgroup 1997).
It is also in alternative evaluation that we need to deal explicitly with the
limitations of our data and models. There is uncertainty in all science to varying
degrees, but that is not a reason to discard that information; that is the reason for
uncertainty analyses and sensitivity analyses as an integral part of DSS.
Group negotiation management helps the decision makers organize their ideas,
formulate relationships surrounding issues and arguments, and refine their
understanding of the problem and their own value systems (Holsapple and
Whinston 1996).
Adaptive Management
Decision Support
Structured Issues
Well defined statement
of management
goals and objectives
But…
“Real world” issues
are Ill-Structured
* Conflicting objectives
* Ambiguities in criteria for
success
* Institutional confusion
* Unknown contribution of
environmental drivers
* Lack of sci. understanding
of management
consequences
* Turbulent political agencies
Alternatives
Evaluation
&
Ranking
Issues &
Goals
Identification
& Conflict
Resolution
Group
Negotiation
Support
Knowledge
Acquisition
&
Representation
Figure 1. Implementation of decision support systems within the adaptive
management structure.
Evolutionary prototyping Sprague and Carlson (1982) is a development cycle of
prototype DSS development, evaluation, and refinement, repeated continually
until (and beyond) its implementation. Verification, validation, and extensive user
involvement are vital parts of the evaluation cycle (D’Erchia et al. 2001). Any
successful support system will be characterized by concise and succinct
presentation of the issue and consistency of internal data and procedures (Hill
1982).
None of this works without knowing the culture and legal requirements of the
agencies that will be using the DSS. Development must include the user. The
collaboration of key agency individuals, their interaction with other agencies, and
their knowledge of other agencies’ needs helps to ensure that this effort will be
focused on the needs and objectives of on-the-ground natural resource planners
and managers. A DSS will only be successful if it contributes to the
implementation of agency objectives and is valued by the decision-makers.
Literature Cited
D’Erchia, F., C. Korschegen, M. Nyquist, R. Root, R. Sojda, and P. Stine. 2001.
A framework for ecological decision support systems: building the right
system and building systems right. U.S. Department of the Interior, U.S.
Geological Survey, Information and Technology Report USGS/BRD/ITR2001-0002. Reston, VA. 50 p.
Hill, P.H. (editor), 1982. Making decisions: a multidisciplinary introduction.
Addison-Wesley, Reading, MA. 264pp.
Holsapple, C.W. and A.B. Whinston. 1996. Decision support systems: a
knowledge-based approach. West Publishing Co., St. Paul Minn., 713 p.
Kersten, G.E., Z. Mikolajuk, and A.G. Yeh, 2000. Decision support systems for
sustainable development: a resource book of methods and applications.
Kluwer Academic, Boston, MA. 423pp.
Nute, D., G. Rosenberg, S. Nath, B. Verma, H.M. Rauscher, M.J. Twery, M.
Grove. 2000. Goals and goal orientation in decision support systems for
ecosystem management. Computers and Electronics in Agriculture
27:355-375.
Science Subgroup. 1997. Ecologic and precursor success criteria for South Florida
ecosystem restoration. Report to the Working Group of the South Florida
Ecosystem Restoration Taskforce.
Sprague, R.H., Jr., and E.D. Carlson. 1982. Building effective decision support
systems. Englewood, Cliffs, NJ, Printice-Hall, 329 p.
Leonard G. Pearlstine, Department of Wildlife Ecology and Conservation,
University of Florida, 3205 College Ave., Ft. Lauderdale, FL 33314
Phone: 954-577-6354, email: pearlstn@ufl.edu