and potential threats to system integrity (Lauenroth et al. 1998). Increased
understanding of system behavior resulting from model predictions
and exploration can be very useful in guiding management decisions. For
example, simulation results from a spatially explicit, cell-based model of
vegetation and fire dynamics at Eglin Air Force Base in Florida helped
natural resource managers understand that current and planned fire management would not maintain the desired extent of longleaf pine (Pinus
palustris) habitat across the base (Hardesty et al. 2000). The model showed
that, after a period of 50 years, many primary longleaf pine habitats would
be converted to hardwoods (mainly Quercus laevis) and sand pine (Pinus
clausa). Managers realized from these predictions that prescribed fire management needed to be doubled to maintain and restore the desired amount
and quality of longleaf pine habitat. Moreover, the model allowed managers
to select and implement an adaptive approach that promised to reduce
greatly the per-acre cost of burning while maximizing desired ecological
effects (J. Hardesty, The Nature Conservancy, personal communication,
November 2001).
Models also document and record major assumptions and current understanding and help organize our knowledge about a particular ecological
system or process (Maddox et al. 1999). Developing a simple conceptual
model of the koa/’ohi’a (Metrosideros polymorpha) mesic forest on the
island of Hawai’i, has helped The Nature Conservancy scientists and
on-the-ground practitioners articulate and document dominant system
dynamics and understand key processes and threats to these forests (S. Gon,
The Nature Conservancy, personal communication, October 2001).The conceptual model also incorporated potential conservation and management
strategies that could be used to reverse the current trend of unchecked
degradation. Such conceptual models and the information contained within
them provide a powerful communication tool for both managers and key
stakeholders.
14.2.2 Sensitivities and Uncertainties of Models
Ecological models, however, are not a panacea for solving every management problem or answering every question, and managers and decision
makers must understand the sources of variation in a model [e.g., Reed et
al. (1998)]. Models are a means of integrating data to more comprehensively understand complex ecological dynamics. Managers must realize
that models are not answers in and of themselves. They are useful tools
for organizing and communicating ideas, synthesizing current understanding and data, developing management goals and objectives, elucidating
unknowns, and generating hypotheses. In the best of circumstances, they
provide a glimpse into the future to help guide present decisions [e.g.,
Gustafson et al. (2000)]. Users and managers must exercise caution in interpreting model results and in using resulting information to make decisions.
14. Educational Investments
265
understanding of system behavior resulting from model predictions
and exploration can be very useful in guiding management decisions. For
example, simulation results from a spatially explicit, cell-based model of
vegetation and fire dynamics at Eglin Air Force Base in Florida helped
natural resource managers understand that current and planned fire management would not maintain the desired extent of longleaf pine (Pinus
palustris) habitat across the base (Hardesty et al. 2000). The model showed
that, after a period of 50 years, many primary longleaf pine habitats would
be converted to hardwoods (mainly Quercus laevis) and sand pine (Pinus
clausa). Managers realized from these predictions that prescribed fire management needed to be doubled to maintain and restore the desired amount
and quality of longleaf pine habitat. Moreover, the model allowed managers
to select and implement an adaptive approach that promised to reduce
greatly the per-acre cost of burning while maximizing desired ecological
effects (J. Hardesty, The Nature Conservancy, personal communication,
November 2001).
Models also document and record major assumptions and current understanding and help organize our knowledge about a particular ecological
system or process (Maddox et al. 1999). Developing a simple conceptual
model of the koa/’ohi’a (Metrosideros polymorpha) mesic forest on the
island of Hawai’i, has helped The Nature Conservancy scientists and
on-the-ground practitioners articulate and document dominant system
dynamics and understand key processes and threats to these forests (S. Gon,
The Nature Conservancy, personal communication, October 2001).The conceptual model also incorporated potential conservation and management
strategies that could be used to reverse the current trend of unchecked
degradation. Such conceptual models and the information contained within
them provide a powerful communication tool for both managers and key
stakeholders.
14.2.2 Sensitivities and Uncertainties of Models
Ecological models, however, are not a panacea for solving every management problem or answering every question, and managers and decision
makers must understand the sources of variation in a model [e.g., Reed et
al. (1998)]. Models are a means of integrating data to more comprehensively understand complex ecological dynamics. Managers must realize
that models are not answers in and of themselves. They are useful tools
for organizing and communicating ideas, synthesizing current understanding and data, developing management goals and objectives, elucidating
unknowns, and generating hypotheses. In the best of circumstances, they
provide a glimpse into the future to help guide present decisions [e.g.,
Gustafson et al. (2000)]. Users and managers must exercise caution in interpreting model results and in using resulting information to make decisions.
14. Educational Investments
265