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An HTML-based Concept Model of the Dry Savanna Woodland Ecosystem for Teaching and Learning

13 May 2003-Conservation Ecology (The Resilience Alliance)-Vol. 7, Iss: 1

About: This article is published in Conservation Ecology.The article was published on 2003-05-13 and is currently open access. It has received 2 citation(s) till now. The article focuses on the topic(s): Woodland.
Topics: Woodland (61%)

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Copyright © 2003 by the author(s). Published here under licence by The Resilience Alliance.
Graz, F. P. 2003. An HTML-based concept model of the dry savanna woodland ecosystem, for teaching
and learning. Conservation Ecology 7(1): 9. [online] URL:
An HTML-based Concept Model of the Dry Savanna Woodland
Ecosystem for Teaching and Learning
Friedrich Patrick Graz
ABSTRACT. This article introduces a web-based conceptual model of vegetation to facilitate an easy
understanding of the processes that govern the development of dry savanna woodlands. The model is based on a
simple table structure that can be interpreted by most web browsers, making it easily accessible. This latter
consideration is important because thetelecommunication link to most of the outlying areas in Namibia is weak.
The model may be accessed by community-based natural resource managers to provide an overview of the
complexity of the savanna woodland system.
The dry savanna woodlands of northern Namibia
provide a number of different resources to the rural
communities, ranging from construction material and a
source of energy to food and tools. In 1992, Ollikainen
(1992) estimated that, in total, 1.5 x 10
of wood
were used for firewood alone. In 1996, the National
Planning Commission determined a GDP (gross
domestic product, agricultural production) of
Namibian $2.6 billion, although the informal sector
was ignored. During the same year, the total woodland
resources that were used by the informal sector
amounted to an equivalent value of almost Namibian
$1060 million per annum (NFSP 1996:3).
Despite the dependence of rural people on woodland
resources, little management besides law enforcement
is currently implemented. This is partly due to the
limited financial and human resources available, but
also is due to limited knowledge of the woodlands and
their ecology, which slows the implementation of
management actions that support sustainable
utilization. Models of the woodland areas may assist in
directing data collection and identifying and testing
management options before they are implemented
(Starfield and Bleloch 1991:3).
Various models have been developed in the past to
examine the savanna system (Starfield et al. 1993,
Milton and Hoffman 1994, Jeltsch et al. 1996, Joubert
and Rothauge 2001). Starfield et al. (1993) developed
a frame-based model of woodlands in Zimbabwe, in
order to investigate the interaction between different
vegetation components. Graz (1996) simulated some
known ecological processes with a simple systems
model of the dry savanna woodlands in northern
Namibia. Jeltsch et al. (1996) developed a spatial
model to investigate the woody component in the
Negev. The state and transition models proposed by
Milton and Hoffman (1994) and Joubert and Rothauge
(2001) are descriptive and static in nature. The authors
describe the different states that the vegetation may
assume under various environmental conditions.
Changes in these conditions or in the intensity of
different factors may cause a transition of the
vegetation to another state. The two state and
transition models provide diagrams to depict the
interaction of ecological and management processes.
Accompanying descriptions provide details about the
different sections of these diagrams and the nature of
the interactions.
Although such illustrations are very useful tools for
obtaining a good overview of the savanna woodland
system, Graz (1996) experienced problems with
developing all of the necessary links, especially
feedback loops, despite the limited complexity of the
model. In order to cope with complexity, a top-down
approach may be used, together with stepwise
refinement. This technique that has been used in
computer programming to break down a problem into
components that can be worked on individually
(Sterling and Shapiro 1997:67) or broken down into
further sub-units. Analogous to this approach, a
number of submodels may be developed, to be
referenced by a parent diagram. Each of these
submodels may be maintained or updated
Polytechnic of Namibia

Conservation Ecology 7(1): 9.
independently. Alternative approaches for coping with
complexity are described by du Toit et al. (1995:64)
for the development of mind maps, and by Novak
(undated) for concept maps. These methods identify a
core thought to which influencing factors or more
specific concepts are linked by a series of lines. Links
are extended not only toward the core, but also
between the influencing factors, thus potentially
forming complex networks.
Diagrams such as those provided by Joubert and
Rothauge (2001) or Graz (1996) are used to show the
relationship between different components of a
system. Flow diagrams may be developed easily with
standard office software such as Microsoft
Powerpoint, whereas more sophisticated applications
such as Vensim (Ventana Systems, accessed in 2001)
provide a tool to develop causal loop diagrams that
may be expanded into dynamic systems models.
The model presented in the Appendix consolidates
existing information on the dry savanna ecosystem
into a conceptual model, using an approach that
combines stepwise refinement and the method for
creating mind maps. Literature for the model is cited
in the Appendix.
Another popular method of showing relationships
between factors is through the implementation of mind
maps (du Toit et al. 1995:64) or concept maps (Novak,
undated). These techniques identify influencing factors
and components that affect a specific concept. These
techniques display information schematically, but
without the addition of descriptive text. As detail and
scope increase, however, it becomes increasingly
difficult to depict a model on paper, particularly if the
number of feedback loops increases, and text is then
This paper presents the various factors that determine
and modify the structure of the dry savanna
woodlands, and identifies and describes the
interactions between the different factors. Unlike the
models previously referred to, this model is developed
using Hypertext Markup Language (HTML), which is
used in the development of Internet web pages.
HTML, click-able diagrams, Java, and JavaScripts
may be used to develop an interlinked/cross-linked
hierarchy of text and figures as described in Graham
(1997) and Kidder and Harris (1997). In this way,
stepwise refinement may be implemented almost
boundlessly, while retaining simple diagrammatic
To illustrate the problem, consider the two sections of
a woodland model in Figs. 1 and 2. Fig. 1 depicts the
factors that affect the mortality of adult trees in the
woodlands. Tree mortality is affected by the severity
of damage by fire, the availability of soil water, the
vigor of the plants, and the effects of pests and
diseases. Each of these factors is affected by others.
For instance, the degree of fire damage is a function of
the fire frequency, fire intensity, and fire season.
A further advantage of this approach is that the model
may be accessed using standard Internet web
browsers, making it a useful teaching tool. Students,
managers, and community leaders may browse
through different components and levels of complexity
on their own, backtracking to previous screens as
desired. Additionally, the various components of the
model may be revised and updated individually at a
central point.
Fig. 2 shows the factors that govern the establishment
of seedlings in dry woodlands. Here, the core
component, seedling establishment, is affected by fruit
production, germination, soil water availability, and
fire damage. The figure shows that the components not
only affect the establishment of seedlings, but also
have an effect on each other, although indirectly.
The structure used in compiling the model was chosen
primarily to maintain easy access to the model. Parts
of Namibia are served by slow communication lines,
with substantial downloading times. A more
sophisticated approach would make the model less
accessible in these areas simply because of
communication technology. Images, although very
useful for the illustration of various aspects, were
excluded for similar reasons.
Both sections are relatively simple and easy to
understand, as links may be followed between the core
components and the factors that affect them.
Additionally, each section only includes the factors
relevant to the topic at hand, i.e., mortality of trees
(Fig. 1) and the establishment of seedlings (Fig. 2).
The reader is therefore less likely to digress from the
topic. There are relatively few factors in each of the
two diagrams, so they may be loosely spaced on paper,
thus improving readability.

Conservation Ecology 7(1): 9.
Fig. 1.
Schematic presentation of the factors that affect the mortality of adult trees in dry savanna woodlands.
Fig. 2.
Schematic presentation of the factors that affect seedling establishment in dry savanna woodlands.

Conservation Ecology 7(1): 9.
Because both sections reference water availability, fire
damage, and the vigor of trees, they could also be
combined to form a single diagram, linked through
these three factors. This is done in Fig. 3, in a causal
loop-type diagram, using Vensim (Ventana Systems,
accessed in 2001). Although the combination of the
two diagrams provides a more complete picture, it also
becomes increasingly complex and more difficult to
read. Therefore, in order to ease comparison with the
previous diagrams, the core components of Figs. 1 and
2 have been highlighted using different colors. In order
to maintain readability, the factors might be spaced
more widely on paper. This would result in a drawn-
out diagram. On the other hand, the figure could be
restricted in size, thus making some sections appear
very busy. Consider, for instance, “vigor of parent
trees” and its influencing factors in Fig. 3. Although
the vigor of the parent trees is an important aspect, the
number of uni- and bi-directional links seems to
emphasize the significance of that factor above others,
subsequently causing bias in the interpretation of the
Fig. 3.
A causal loop-type diagram that combines the mortality of trees in Fig. 1 and the establishment of seedlings in Fig. 2.
The + and - signs indicate positive and negative relationships between factors, respectively.
It must be noted that the complexity of Figs. 1–3 has
been restricted by summarizing factors. Water
availability is, for instance, influenced by soil
conditions, rainfall, and competition with other
woodland plants. The factors “soil condition” and
“competition with other woodland plants” could again
be subdivided. The expansion of the factors would,
however, make the figure less legible and the reader

Conservation Ecology 7(1): 9.
would be more likely to digress because of an
information overload.
Although the diagrams in Figs. 1 and 2 show the
various factors that affect one another, they do not
provide information on the type of association. The
causal loop diagram in Fig. 3 attempts to resolve this
by indicating a positive relationship (indicated by a
“+”) or a negative relationship (indicated by a “-”)
between the factors. Here, a positive relationship
implies that an increase in one factor would result in
an increase in the other, whereas a negative
relationship indicates that an increase in one factor
would cause a decrease in the other. Because the
nature of the links are only known in a general way,
they cannot be quantified using constants or equations.
However, not all relationships can be labeled in this
way. For example, the effect of fire may initially
increase germination, but as fires become more
intense, seed is damaged. Van Daalen (1991) found
that a higher percentage of Pterocarpus angolensis
seed germinated in response to medium-intensity fires
as compared to very high or very low intensity fires.
To compound the problem, the nature of the links from
one factor to the others may differ. For instance, water
availability affecting seedling establishment refers to
the amount of soil water; fire frequency is indirectly
affected by the development of herbaceous vegetation
as a result of water; and the breaking of dormancy
considers the amount of water that may remove
inhibitory chemicals.
Milton and Hoffman (1994) and Joubert and Rothauge
(2001) attempted to overcome this problem by
numbering the individual states and transitions, and by
providing descriptive text separately. A disadvantage
of this system is that a reader is required to cross-
reference the diagram and text on different pages. The
problem would not be solved by using a larger sheet of
paper. The user of the model would be required to
view the model from a greater distance to see it in its
entirety, in which case the writing would become
increasingly less readable.
A further alternative would be to combine space and
color coding, i.e., allocating different colors to
different submodules of the model. However, as the
number of submodules increases, different shades of
the same color become increasingly difficult to
distinguish. This problem is similar to the allocation of
colors when preparing maps (ESRI 1994). Also, this
approach would require decisions about where such
color-coded submodels would begin or end.
The technique described here presents a simple tool to
break down a complex model into sub-units that can
be displayed separately or in groups. The various
sections of the model are stored in separate HTML
documents that are linked to a parent document using
uniform resource locators (URL) (Graham, 1997).
Each of the sub-documents, in turn, may act as parent
document for further refinement. Similar to the
implementation of hyperlinks on the Internet, many
documents may point to one parent; conversely, a
single document may point to many parent or child
documents. The various child documents may also
cross-reference one another.
This characteristic has important implications for
model development. Once a section has been
developed, it may be referenced by multiple higher
level models. For instance, a subsection that deals with
the development of soil moisture is important for
seedling development, plant vigor, and growth. The
subsection can therefore be referenced by all three.
Similarly, the vigor of adult trees affects not only tree
survival and seed production, but also the plants’
susceptibility to attacks by pests and diseases.
An important advantage of the use of URLs is the ease
of dealing with feedback loops. For instance, reduced
light intensity on the woodland floor due to shading by
woody plants results in a weaker herbaceous layer.
This, in turn, eases the establishment of woody
seedlings and the subsequent development of the
woody layer.
To facilitate easy access and navigation through the
model and its component descriptions, the browser
window is divided into three horizontal sections using
frames; with the implementation of frames, the
individual sections of the screen may be changed
independently. The uppermost frame (model frame)
permits the reader to navigate through the individual
submodels, whereas the central frame (description
frame) is used to display the descriptive text requested
by the reader. The last frame contains a menu that
provides navigation aids and access to a list of the
literature referenced by the model. The menu could be
extended to solicit feedback from the readers.

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16 Sep 2011
Abstract: Dans les paysages soudaniens, embrases lors de la saison seche, les importantes mutations engendrees par l'intensification agricole recomposent les espaces et les modes de gestion associes. Dans ce contexte, le feu, symbole passe de la degradation des forets devient un outil d'ingenierie ecologique aux services des savanes desormais menacees. Afin d'analyser ces bouleversements complexes des paysages-objets et des representations associees aux enjeux modernes qui se tissent, une caracterisation spatiale fine du feu a ete entreprise. Ce travail, central dans la recherche menee, permet alors d'apprehender l'evolution des modes de gestion et les trajectoires paysageres. Contrairement aux observations releguant les pratiques du feu comme anecdotiques ou anarchiques en saison seche, nous montrons que la dynamique complexe des feux de brousse est principalement structuree par la combinaison locale d'une pratique reguliere et de facteurs pedoclimatiques. L'interaction locale entre le moment de la mise a feu et la combustibilite de la vegetation est le critere determinant des regimes de feux observes a l'echelle regionale. Les dernieres pluies correspondent ainsi a l'eclosion des premiers feux sur les sols squelettiques, puis petit a petit, les feux parcourent des milieux aux sols plus profonds ou la vegetation reste humide plus longtemps. Le recours a l'analyse et a la simulation spatiale a permis de faciliter les echanges entre observations de terrain et cartes regionales, pour ainsi explorer les interactions locales entre mise a feu et dynamique saisonniere des espaces. Cependant si cette dynamique saisonniere est confirmee, elle devoile au-dela-des variables biophysiques, la place nouvelle des territoires dedies a la protection de la nature et l'heterogeneite des regards portes sur la gestion des espaces ruraux.

33 citations

Additional excerpts

  • ...A l’inverse, des fortes densités d’arbres limitent l’extension du tapis graminéen par compétition pour la lumière (Graz, 2003)....


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