Effects of Top Predators on Ecosystem Functioning in Pitcher Plants (Sarracenia
purpurea)
Nisha Patel and Jennie Zhang
with T. E. Miller
DEPARTMENT OF BIOLOGICAL SCIENCE, FLORIDA STATE UNIVERSITY
ABSTRACT
Species in natural communities are linked together by the transfer of energy and
nutrients. We investigated the effects of top predators on nutrient flow and nitrogen production
in a community, particularly as a function of resource levels. To predict the effects of top
predators, we created a simulation model of the small aquatic community found in the leaves
of carnivorous pitcher plants, using the R programming language. We then tested the
predictions of the model with experiments that varied predator (larval mosquito) and resource
(dead ant) abundances and quantifying the subsequent community changes. The experimental
results are consistent with the model predictions for the effects of resources. However, the
experiments suggested that mosquitoes have very little effect on lower trophic levels, which
contradicts the predictions of the model.
PITCHER PLANT
FOOD CHAIN
Nisha and Jennie at the
Mud Swamp Field Site
in the Apalachicola
National Forest
collecting fluid from
pitcher plant leaves.
Mosquito Larvae
N
RESULTS
Protozoa
•
mosquito,
protozoa
•
ants,
protozoa
• The data supports our prediction.
INTRODUCTION
The transfer of energy and nutrients through consumption (i.e. predation and herbivory) links
together species in natural communities. Communities are structured by what ecologists call topdown effects (changes in the lower trophic levels as a result of top predators) and bottom-up effects
(changes in higher trophic levels due to differences in available resources at the lower levels).
The water-filled leaves of the carnivorous purple pitcher plant, Sarracenia purpurea, contain
small communities of invertebrates and microorganisms. While most plants are generally able to
obtain nutrients necessary for photosynthesis through their root systems, carnivorous plants evolved
to use the insects they capture for nutrients. In pitcher plants, the insect prey also support a small
community within the leaves (see food web figure). The host plant benefits because the rate at which
nitrogen is released from decomposition of the prey is increased by the lower trophic levels (mostly
bacteria) in this community. The effect of higher trophic levels on the plant’s nitrogen intake is
uncertain because they may suppress bacteria abundance and nutrient availability due to their feeding
habits. In addition, individuals of the higher trophic levels exit the ecosystem as they mature, taking
away nitrogen that might have been used by the plant.
Our study first used a simulation program to model nitrogen and energy flow through the
pitcher plant community. The model predicted how changes in nutrients or top-predators affect the
biomass and availability of nutrients in this system. Second, we varied amounts of ants (resource) and
mosquito larvae (top predators) in order to test these predictions.
EXPERIMENTAL METHODS
The Sarracenia purpurea habitat was simulated in the lab using twenty-four 50 mL
macrocentrifuge tubes. Each tube contained 20 mL of sterile water to imitate the gathered rainfall and
5 mL of plastic beads to resemble sediments at the bottoms of natural leaves. Varying amounts of
predators (mosquito larvae) and resource input (ants) were added to each tube in order to test the
predictions of our simulation model. We used a factorial design to test all possible combinations of
resources and predator levels, either low (2 ants), and high (10 ants) and either 1, 3, 7, or 10 mosquito
larvae with three replicates of each treatment combination.
The experiments were initiated on July 1, 2010 and sampled after 5 and 12 days. The reported
results for bacteria and protozoa were collected on Day 12. To estimate bacterial abundance, 0.05 mL
of each sample were removed and serially diluted to 10-5 and spread onto half-strength Luria agar
plates. Protozoa abundance was determined by transferring 0.1 mL of each type onto a Palmer cell.
All living cells were classified into different species and counted at 100X using a phase-contrast
microscope.
On Day 14, all remaining prey and mosquitoes were removed, dried, and later weighed. Then
15 mL of fluid from each macrocentrifuge tube were removed and passed through a 0.2 ml filter to
remove most living individuals. These samples were frozen until nitrate, nitrite, and phosphorous
analyses can be performed in several weeks when a Lachat analyzer is available.
The results can be compared against our predictions about the biomass of prey, bacteria and
protozoa. Nitrogen comparisons will wait until the nutrients can be processed.
MODEL
PREDICTIONS
Bacteria
•
mosquito, no effect on bacteria
•
ants, no effect on bacteria
• The data supports our prediction for ants, but
does not support the prediction that an increase
in mosquitoes results in an increase in bacteria.
Ants
•
mosquito, no effect on protozoa
•
ants,
protozoa
• The data supports our prediction for ants, but
does not support the prediction that an increase
in mosquitoes results in an increase in bacteria.
Mosquito Predation Rate
Mosquito Population
PREDICTION MODELS
We constructed a computer simulation model to understand the effects of resource
availability and top-predator abundance on the ecosystem. Mouquet et al (2009) determined
changes in prey biomass (ants), bacteria, protozoa, and nutrients using linked continuous
equations. Using the R programming language, we wrote a program with discrete
approximations of these equations in order to predict the effects of varying the amounts of
ants and mosquito larvae on the community. The basic equations and parameters are:
DÝ A  mB B  mP P  uB DB  sD
BÝ u DB  (m  r )B  u BP
B
B
B
P
PÝ uP BP  (mP  rP )P  uM P
rB B  rP P  rM uM P
Ý
N  N 
 yN
D
B
P
N
(Detritus biomass)
(Bacteria biomass)
(Bacterivores biomass)
(Nitrogen concentration)


A
mP
uB
s
(Carbon input flux from detritus) = 5.39

(Bacterivores mortality rate) = 0.01
(Bacteria consumption rate of detritus) = 0.001
(Sedimentation rate) = 0.01
m B (Bacteria mortality rate) = 0.001
rB (Bacteria respiration rate) = 0.0005
u p (Bacterivores predation rate) = 0.014
rP
uM
N
(Bacterivores respiration rate) = 0.0014
rM
y

(Mosquitoes respiration rate) = 0.01
(Mosquitoes predation rate) = 0.5872
(Flux of inorganic nitrogen due to rainwater) = 0.751
(Uptake rate of nitrogen by the plant) = 0.1026
(C:N ratio in the organic matter) = 6.625
CONCLUSION
Our computer model predicts that top predators (top-down
effects) as well as resource input (bottom-up effects) will affect
populations of organisms within the natural community in the
pitcher plant. An increase in resource input was predicted to result
in an increase in protozoa and captured prey, but no change in
bacteria biomass. We expected that an increase in mosquito
predation would decrease protozoa and captured prey biomass, as
well as increase bacteria biomass.
In contrast with our models, our experiments with the
species found in pitcher plants showed no effect of increasing
predator abundance on either bacteria abundances or captured prey
biomass. This deviation from the predicted model suggests that the
assumptions of the model may need to be reconsidered. One
possible explanation of our experimental result is that omnivorous
feeding by mosquito larvae suppressed bacteria as well as protozoa
abundances.
We conclude that predators do affect the abundance of their
immediate prey, but that these predation effects do not filter down
to lower trophic levels in our system. Our experiments were
conducted in a small-scale natural community, but the conclusions
may also apply to larger ecosystems in which omnivory is present.