Wildlife 1995). This species was later listed as threatened under Oregon’s
Endangered Species Act.
In another case, a metapopulation model was used to evaluate the effectiveness of translocation as a management tool for the endangered helmeted honeyeater (Akçakaya et al. 1995). An updated version of this model
is currently being used to support the decision regarding timing of release.
Data from a geographic information system and a RAMAS metapopulation model were used to determine the viable population size for the
Florida scrub jay (Root 1998). This model was used in the context of
four reserve designs developed as part of a habitat-conservation planning
process focusing on scrub habitat on nonfederal lands in Brevard County,
Florida (Brevard County Office of Natural Resources 1995).
A metapopulation model for a threatened land snail species (Regan et
al. 1999) is contributing to planning outcomes in the Togari Forest of northwest Tasmania. Another metapopulation model was applied to the redhorse
populations in the Muskingum river in Ohio (Root et al. 1997) to model
the thermal impact that might result from a proposed increase in power
plant operation. The proposed increase was approved by the Ohio
Environmental Protection Agency.
Brook et al. (2000) applied several existing models (including RAMAS
Metapop, RAMAS Stage, Vortex, Inmat, and Gapps) to 21 populations. The
results both validated the predictions of these models by comparing them
with observations and showed that models developed with different software gave similar results when used with the same data sets.
In summary, a large variety of existing ecological models can be applied
to support or guide management decisions. Such applications require the
collection of site-specific data and statistical analysis of the data to estimate model parameters. Once the model parameters have been determined
(together with their uncertainties resulting from measurement error and
their natural variabilities), the application of an existing model requires
very little research effort. Therefore, the major scientific issues in the
application of existing models involve data analysis methods. These
methods include survival estimation methods based on mark–recapture
data; methods for estimating spatial, temporal, and error variance components; as well as variance caused by such components as age and sex.
Most of the models considered in this paper, as well as most successful
applications of modeling to management questions, are at the population
level rather than the community or ecosystem levels. This selectivity reflects
the state of ecological modeling: the theory of single-species dynamics is
more complete than that of species interactions and community dynamics. The disadvantage of the ecosystem approach is the complexity of
interactions among species and our lack of understanding of community
and ecosystem dynamics. As our understanding increases, conservation and
management practices will likely become more ecosystem-based. However,
the contingencies and complexities involved may make it impossible to find
13. Science and Management Investments
253
Endangered Species Act.
In another case, a metapopulation model was used to evaluate the effectiveness of translocation as a management tool for the endangered helmeted honeyeater (Akçakaya et al. 1995). An updated version of this model
is currently being used to support the decision regarding timing of release.
Data from a geographic information system and a RAMAS metapopulation model were used to determine the viable population size for the
Florida scrub jay (Root 1998). This model was used in the context of
four reserve designs developed as part of a habitat-conservation planning
process focusing on scrub habitat on nonfederal lands in Brevard County,
Florida (Brevard County Office of Natural Resources 1995).
A metapopulation model for a threatened land snail species (Regan et
al. 1999) is contributing to planning outcomes in the Togari Forest of northwest Tasmania. Another metapopulation model was applied to the redhorse
populations in the Muskingum river in Ohio (Root et al. 1997) to model
the thermal impact that might result from a proposed increase in power
plant operation. The proposed increase was approved by the Ohio
Environmental Protection Agency.
Brook et al. (2000) applied several existing models (including RAMAS
Metapop, RAMAS Stage, Vortex, Inmat, and Gapps) to 21 populations. The
results both validated the predictions of these models by comparing them
with observations and showed that models developed with different software gave similar results when used with the same data sets.
In summary, a large variety of existing ecological models can be applied
to support or guide management decisions. Such applications require the
collection of site-specific data and statistical analysis of the data to estimate model parameters. Once the model parameters have been determined
(together with their uncertainties resulting from measurement error and
their natural variabilities), the application of an existing model requires
very little research effort. Therefore, the major scientific issues in the
application of existing models involve data analysis methods. These
methods include survival estimation methods based on mark–recapture
data; methods for estimating spatial, temporal, and error variance components; as well as variance caused by such components as age and sex.
Most of the models considered in this paper, as well as most successful
applications of modeling to management questions, are at the population
level rather than the community or ecosystem levels. This selectivity reflects
the state of ecological modeling: the theory of single-species dynamics is
more complete than that of species interactions and community dynamics. The disadvantage of the ecosystem approach is the complexity of
interactions among species and our lack of understanding of community
and ecosystem dynamics. As our understanding increases, conservation and
management practices will likely become more ecosystem-based. However,
the contingencies and complexities involved may make it impossible to find
13. Science and Management Investments
253