ECOL203/403 – Ecology: Populations to Ecosystems
Assignment 2: Predator-Prey Interactions
T1 2020
Figure 0. Tarantula Theraphosa blondi pulling a captured giant earthworm (presumably
Rhinodrilus sp.) into its burrow in rainforest in French Guiana. Photo by C.E. Timothy Paine. Find
more information about earthworm-eating tarantulas in Nyffler et. al. 2017. Journal of
Arachnology 45:242–247.
Objective
The purpose of this assignment is for you to run a manipulative experiment using
a realistic predator-prey model. In so doing, you will
1. explore how predators affect prey populations and vice versa
2. explore the linkages between ecological processes and their
representations in models
3. design and execute an ecological experiment
Introduction
This assignment demonstrates how the actions of individuals compound to
generate population dynamics. We know that all populations can grow
exponentially, and we also know that never occurs for long, as the resources
available to populations eventually restrict their growth. In this practical, you will
explore how and when this occurs. You will further explore conditions under
which more complicated – and even interesting – population dynamics occur.
In simple models, one could assume that all predators had access to all prey at
all times. In reality, however, populations have spatial structure, because
individuals are located at specific locations in space. This has several effects on
their ecology. First, an individual’s spatial location restricts the set of individuals
that it can interact with to be those in its local neighborhood. Second, space
(together with the sensory organs of the organism in question) affects the
detectability of predators and prey. Third, heterogeneity in the spatial distribution
of resource availability, refuges, mates, and abiotic conditions (etc) can strongly
influence ecological processes. Finally, the viscosity (or ‘thickness’) of the
environment, together with the dispersal abilities of the organism, affects how
quickly they can move through space. All of these factors influence ecological
interactions among organisms. A final consideration is the dimensionality of
space. For terrestrial organisms, the world is (to a first approximation) flat,
whereas for aquatic, marine or airborne organisms it is three-dimensional. In the
sky, a predator may be above you. In water, predators may lurk above or below
you. In this model, we assume that the predators and prey exist in a flat (twodimensional) homogeneous field.
Modeling platform
You will use a modeling platform, NetLogo, in which the spatially explicit twospecies model has been developed. NetLogo is a multi-agent programmable
modeling environment used by tens of thousands of students, teachers and
researchers worldwide. Models are written in the NetLogo language, which
provides a graphical user interface for users.
Description of model
ARENA: You will simulate predator-prey dynamics in a homogeneous, twodimensional closed habitat. The habitat is rectangular, with dimensions you
specify. The model is spatially explicit, with each individual having a set location.
By joining the top and bottom edges of the arena, and the left and right edges,
we create a torus (a donut). These manipulations make the spatial area of
simulation endless. Prey are shown as “bird” symbols, and predators as “cats”.
These symbols were chosen to remind you of the devastating impact that feral
cats have had on the native fauna of Australia. This is a general model, however.
You can simulate ANY type of predators, and ANY type of prey, depending on
the parameters you choose (see below). So don’t get trapped into thinking it’s
only two particular species.
MOVEMENT: Prey move throughout
the habitat at a speed you determine
(“Prey_speed” Note: you can adjust all
the parameters in italic text. See
Figure 1 for an overview). They move
in random directions, unless there is a
predator within their “Dodge_distance”),
in which case they move away from
that predator. Predators, likewise,
move at a speed you determine
(“Pred_speed”). They also move
randomly, unless an individual prey
comes within their “Search_distance”.
When that happens, they move
towards that prey. When a prey is
located within the “Catch_distance” of
a predator it is considered to be caught
and eaten by that predator. Note that
the “Catch_distance” should never be
larger than the “Search_distance”, as
that would make no biological sense.
If several predators catch a prey
simultaneously, they share it. We
assume that all prey contain the same level of resources, as far as the predator
is concerned.
GROWTH: Individual prey grow by acquiring resources from the environment.
This occurs at a constant rate. Individual predators, on the other hand, grow only
by consuming prey.
REPRODUCTION: Prey and predators must obtain a threshold level of resources
before they’re able to reproduce. Reproduction is by asexual budding: each new
individual is generated at the same location as the parent, with a minimal level of
resources. The threshold levels of resources necessary for reproduction by prey
and predators (“Prey_energy_to_reproduce” and “Pred_energy_to_reproduce”)
are set by you.
DEATH: Mortality for the prey occurs only when they are consumed by predators.
Predators have a per-capita probability of death (“Pred_prob_death”) in every
time-step.
INITIAL CONDITIONS: The indicates how many predators and prey are initially
present in the habitat (“Pred_number_initial” and “Prey_number_initial”,
respectively). Individuals are located randomly, with a random initial energy level.
Figure 1. Model parameters you can adjust.
Parameters for the predators are on the left.
Parameters for Prey are on the right. The
length of the simulation is at the bottom.
Note: The parameters provided here
generate stable coexistence of predators and
prey (for at least 10000 time-steps. If you
find that your populations consistently go
extinct, reset the parameters to these values!
Model outputs
The model outputs several variables. First, you can watch the predators and prey
as they move around the arena (Figure 2). Additionally, you can monitor the
changes in the population size of predators and prey. This information is
provided graphically over the course of the simulation, and the current population
sizes for predators and prey are provided numerically (Figure 3).
You’ll see that, often, the predators
drive the prey to extinction. Or,
conversely, that the predators go extinct,
allowing the prey population size to
increase indefinitely. A key question of
interest, therefore, is under what
conditions the predator and prey
populations can coexist stably. We
evaluate stability as the time of
persistence of the two species.
Furthermore, we can obtain from the
model the mean population size of the
prey and predators, as well as their
ranges, which gives an indication of the
degree of variation in population sizes.
Greater oscillations, and oscillations
that grow larger through time, are
indicators of instability, whereas small
and damped oscillations indicate
relative stability.
In addition to population dynamics,
we can observe the spatial patterning
of predators and prey in the arena –
are they all spread out? Do predators
hunt as a group? Do prey disperse
from one another, or from the
predators?
Because this model allows individual
predators and prey to move randomly
around the arena, no two runs are
identical. In other words, this model
is stochastic. To evaluate its
behavior, therefore, you need to
observe multiple runs. Use a
minimum of 10 repetitions of every set of parameter values you evaluate, and
record your response values after every replicate.
Figure 2. Example graphical output from the
model. Prey are shown as blue birds and
predators as black cats. Their size indicates their
current level of resources.
Figure 3. Example output from the model, showing
changes in population sizes through time, as well as
numeric values of the population sizes.
Flexibility of the model
You can explore a wide variety of predator prey interactions using this model. For
example…
• You could create a plant-herbivore system by decreasing the speed of the
prey to almost 0. (Don’t decrease it to 0, or new plants will be placed at
exactly the same location as their parents)
• You could create sit-and-wait predators by making them extremely slowmoving. (Don’t decrease their speed to 0, or new predators will be placed
at exactly the same location as their parent).
Hypotheses
For your experiment, you can use one of the following hypotheses, or you can
come up with your own. You can use this system to investigate a wide variety of
ecological scenarios! If you use your own hypothesis, you MUST verify its
suitability in writing with Dr Paine (timothy.paine@une.edu.au) prior to
running your experiment.
1. The probability of prey survival decreases as their speed decreases.
2. The probability of prey survival decreases the speed of the predators
increases.
3. Increasing the predator’s search radius decreases the likelihood of stable
coexistence of the two species, whereas decreasing the search radius
increases it.
4. Increasing the level of resources needed for prey reproduction increases
the likelihood of stable coexistence.
How to evaluate the support for your hypothesis
Students are often uncertain about what data they should collect in order to
examine the support for their chosen hypothesis. In general, the population
dynamics, in other words, the changes in population size that occur during a
single run of the model, are of less interest than is the final outcome: which
species are present at the system at the end of the run. Ultimately, the data that
you collect and present will depend on the hypothesis you test. If, for example,
you hypothesize that prey population sizes will be more variable as their speed
increases, then you should report how strongly their population sizes vary. Or, if
you choose to test Hypotheses 1 or 2, above, then you should report the percent
of model runs in which the prey survive to the end of the model run. In
Hypotheses 3 and 4, above, the term ‘stable coexistence’ appears. By this, we
mean the persistence of both the predator and the prey species until the end of
the model run.
A note on how to run the model
By default, the model is set to run for 10,000 timesteps. You may find that
running the time necessary for the model to run to 10,000 timesteps is too great.
Additionally, you may find that the two species almost never are able to stably
coexist through 10,000 timesteps. In either of those cases, you should reduce the
“Max_simulation_duration” (Figure 1) to a smaller number. Don’t reduce it below
1,000 timesteps. If you do change this setting, be sure to explain that you do so,
and why, in your methods section.
Assignment
Write a brief but insightful scientific paper, using the predator-prey model,
evaluating the support for the hypothesis of your choice. In preparation to do so,
consider what parameters of the model you will manipulate, and what response
variables you will measure to evaluate your hypothesis. As noted above, you
must replicate your experiment to obtain confidence in your results. Use the
following sections in your paper:
• An appropriate, clever, and interesting title. Note that ‘Predator-prey
dynamics’ is not a clever or interesting title!
• In your abstract, provide a brief overview of your key results,
interpretation and recommendations (150 words, maximum).
• In your introduction, provide enough background and context so that the
reader clearly understands the importance of the hypothesis you will test.
A clear statement of your hypothesis should appear in the last paragraph
of your introduction. Be sure to justify why you expect your hypotheses to
be supported by the data. Refer to peer-reviewed literature to
contextualize your results.
• In your methods, briefly state how you manipulated the model. What
parameter(s) did you vary, and over what range? How did you replicate
your sampling? There is no need to describe the basis of the model itself.
Nor are you required to use statistical tests. Doing so would be a nice
addition, but is not required.
• In the results, lay out your findings clearly, using figures, and if necessary,
tables. The results section should present results suitable to evaluate the
support for your hypothesis. Remember that a results section MUST
include a text description of your key results. Use the text to highlight the
key results shown in your figures. Be sure that your figures are legible,
illustrate your findings, and include complete captions.
• In the discussion, interpret your findings in terms of your hypothesis.
Refer to peer-reviewed literature to interpret your results.
Use no more than 1200 words for ECOL203 (1500 words for ECOL403) in total
(excluding abstract, captions, and references). The rubric that provides the
benchmarks against which your paper will be judged is available on Moodle.
Your report must be written in your own words. Write your report
independently. Turn in this assignment by Moodle. Indicate your identity with
your student number, and only your student number.
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