(c) Suppose that you were examining the distribution of a plant, instead of the millipede. Describe modifications in the experiment that you designed in (b) that would be required to determine whether the abiotic factor you chose affects the distribution of the plant.
Answers
Answer:
On a trip to a dense forest, a biologist noticed that millipedes (small invertebrates) were plentiful under
logs but were rarely seen in any other location.
(a) Propose THREE environmental variables (two abiotic and one biotic) that could explain why
millipedes are found more frequently under logs. (1 point each; 3 points maximum)
The following list is not exhaustive.
Abiotic factors
2 points maximum
Biotic factors
1 point maximum
Light Reproduction
Temperature Predation
Water Food supply
Soil
Texture
Nutrients
pH
Competition
Wind
Periodic disturbances —
fire/storms/volcanoes
Note: Nutrient can be abiotic or biotic depending on how it is used. Climate/weather/shelter are too
general!
(b) For ONE of the abiotic environmental variables you chose above, design a controlled experiment to
test a hypothesis that this factor affects the distribution of millipedes on the forest floor. Describe data
that would support your hypothesis. (1 point each; 6 points maximum)
Must relate to one of the two abiotic factors accepted in part (a) AND measure/relate to millipede
distribution.
• Hypothesis — proposes a relationship between one abiotic factor and the distribution of
millipedes.
• Prediction/expected results — states what should be observed if the hypothesis is supported.
Can be in an “if … then” format.
• Design — describes an experiment that manipulates one abiotic independent variable/factor.
• Constants — explicitly holds all other factors constant.
• Control — indicates a valid control group that serves as a comparison
• Data collection — describes what observations will be collected or how they will be collected, or
both.
for experimental groups.
• Sample size — indicates test of multiple millipedes or replicates.
• Statistical analysis — suggests a mathematical and/or statistical comparison of control and
experimental groups or of observed and expected. A specific statistical test need not be
mentioned.
• Feasibility — experiment could be performed and would yield data that would answer the
question posed.
On a trip to a dense forest, a biologist noticed that millipedes (small invertebrates) were plentiful under
logs but were rarely seen in any other location.
(a) Propose THREE environmental variables (two abiotic and one biotic) that could explain why
millipedes are found more frequently under logs. (1 point each; 3 points maximum)
The following list is not exhaustive.
Abiotic factors
2 points maximum
Biotic factors
1 point maximum
Light Reproduction
Temperature Predation
Water Food supply
Soil
Texture
Nutrients
pH
Competition
Wind
Periodic disturbances —
fire/storms/volcanoes
Note: Nutrient can be abiotic or biotic depending on how it is used. Climate/weather/shelter are too
general!
(b) For ONE of the abiotic environmental variables you chose above, design a controlled experiment to
test a hypothesis that this factor affects the distribution of millipedes on the forest floor. Describe data
that would support your hypothesis. (1 point each; 6 points maximum)
Must relate to one of the two abiotic factors accepted in part (a) AND measure/relate to millipede
distribution.
• Hypothesis — proposes a relationship between one abiotic factor and the distribution of
millipedes.
• Prediction/expected results — states what should be observed if the hypothesis is supported.
Can be in an “if … then” format.
• Design — describes an experiment that manipulates one abiotic independent variable/factor.
• Constants — explicitly holds all other factors constant.
• Control — indicates a valid control group that serves as a comparison
• Data collection — describes what observations will be collected or how they will be collected, or
both.
for experimental groups.
• Sample size — indicates test of multiple millipedes or replicates.
• Statistical analysis — suggests a mathematical and/or statistical comparison of control and
experimental groups or of observed and expected. A specific statistical test need not be
mentioned.
• Feasibility — experiment could be performed and would yield data that would answer the
question posed.