Hannon and Ruth (1997); Jackson et al. (2000)]. For example, Madonna,
ModelMaker, SimuLink, PowerSim, and STELLA are icon-driven programs useful for introducing students to the basics of quantitative modeling, allowing the student to build a quantitative model from start to finish.
Such software simplifies model building by generating equations defined by
constructing graphical relationships between input parameters in an ecological system of interest (Costanza 1987). In some cases, simulations
displayed as graphs, tables, or animations can be automatically generated
from mathematical formulae. These programs are valuable and popular in
teaching environments because simple quantitative models can be easily
constructed to illustrate diverse phenomena, from simple logistic growth
to percolation models of landscape pattern, to movement of phosphorus
through a salt marsh, to complex predator–prey relationships. Excellent
software packages, such as RAMAS and Populus, or texts, such as the
Applied Population Ecology (Akçakaya et al. 1999) and A Primer of
Ecology (Gotelli 1998), introduce basic quantitative approaches specific to
population dynamics and conservation biology with applied, interactive
examples. In addition, simple spreadsheet programs, such as Excel, can also
be effectively and creatively used to construct basic quantitative ecological
models, including simple spatial process models (Weldon 1999; Gergel and
Reed 2001). Although many of these programs may be limited to relatively
simple models, they provide tractable, creative segues into the sometimes
daunting world of quantitative modeling by removing the hurdles of arcane
programming languages (Jackson et al. 2000). There is a broad array of
ecological models and texts that can be useful in integrating a variety of
modeling exercises into the classroom, which may increase quantitative
literacy and competence critical to effective environmental management
[e.g., Alstad (2001); Bossel (1994); Brown and Rothery (1993); Gergel and
Turner (2001); Hannon and Ruth (1997); Othmer et al. (1997); Starfield
et al. (1990)].
14.4.4 The Process of Modeling and Environmental
Decision Making
Abundant research suggests that transdisciplinary education is best pursued
not in the abstract but by means of applied problem solving [e.g., Grigg
(1995); Scott and Oulton (1999); Wheeler and Lewis (1997)]. This approach
forces students and faculty to integrate and synthesize the methods and
insights of the various disciplines. Rather than mastering a single set of tools
to apply to all problems, students should learn to select and apply the tools
required by the specific problem they address in their research. Modeling
toolkits can facilitate this synthetic approach to learning (see Chapters 11
and 12, this volume). Providing real-life scenarios in classroom modeling
exercises is critical.
14. Educational Investments
275
ModelMaker, SimuLink, PowerSim, and STELLA are icon-driven programs useful for introducing students to the basics of quantitative modeling, allowing the student to build a quantitative model from start to finish.
Such software simplifies model building by generating equations defined by
constructing graphical relationships between input parameters in an ecological system of interest (Costanza 1987). In some cases, simulations
displayed as graphs, tables, or animations can be automatically generated
from mathematical formulae. These programs are valuable and popular in
teaching environments because simple quantitative models can be easily
constructed to illustrate diverse phenomena, from simple logistic growth
to percolation models of landscape pattern, to movement of phosphorus
through a salt marsh, to complex predator–prey relationships. Excellent
software packages, such as RAMAS and Populus, or texts, such as the
Applied Population Ecology (Akçakaya et al. 1999) and A Primer of
Ecology (Gotelli 1998), introduce basic quantitative approaches specific to
population dynamics and conservation biology with applied, interactive
examples. In addition, simple spreadsheet programs, such as Excel, can also
be effectively and creatively used to construct basic quantitative ecological
models, including simple spatial process models (Weldon 1999; Gergel and
Reed 2001). Although many of these programs may be limited to relatively
simple models, they provide tractable, creative segues into the sometimes
daunting world of quantitative modeling by removing the hurdles of arcane
programming languages (Jackson et al. 2000). There is a broad array of
ecological models and texts that can be useful in integrating a variety of
modeling exercises into the classroom, which may increase quantitative
literacy and competence critical to effective environmental management
[e.g., Alstad (2001); Bossel (1994); Brown and Rothery (1993); Gergel and
Turner (2001); Hannon and Ruth (1997); Othmer et al. (1997); Starfield
et al. (1990)].
14.4.4 The Process of Modeling and Environmental
Decision Making
Abundant research suggests that transdisciplinary education is best pursued
not in the abstract but by means of applied problem solving [e.g., Grigg
(1995); Scott and Oulton (1999); Wheeler and Lewis (1997)]. This approach
forces students and faculty to integrate and synthesize the methods and
insights of the various disciplines. Rather than mastering a single set of tools
to apply to all problems, students should learn to select and apply the tools
required by the specific problem they address in their research. Modeling
toolkits can facilitate this synthetic approach to learning (see Chapters 11
and 12, this volume). Providing real-life scenarios in classroom modeling
exercises is critical.
14. Educational Investments
275