This blog post was written by QBIC sophomore, Brian Ho.
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Heithaus, M., Frid, A., Wirsing, A., Dill, L., Fourqurean, J., Burkholder, D., Thomson, J. & Bejder, L. (2007). State-dependent risk-taking by green sea turtles mediates top-down effects of tiger shark intimidation in a marine ecosystem. Journal of Animal Ecology, 76, 837-844.
Predators
and prey have always been at odds with one another. Both dance to the tune of
essential components of the natural order: one seeks to live and pass on its
genes, the other fancies a satisfying meal. The result is a continuous, dynamic
arms race in all corners of the globe. Predators become better hunters, and
prey better at evading them. Ecosystem equilibria are thus maintained through
the balancing of these interactions.
Yet
the relationships between different species are often quite complex. Predators
are capable of affecting their ecosystems by influencing the behavior of their
prey, in addition to actually eating them. These non-lethal effects of
predation are often dependent upon the state, or physical body condition, of
the prey. They are also usually overlooked in community dynamics studies – i.e.
the study of how communities change over time as a result of species
interactions (Boundless, 2014) .
Between
1999 and 2006, Michael R. Heithaus, of Florida International University, and
his colleagues investigated these state-dependent behaviors in green sea
turtles, Chelonia mydas. The study
was carried out on the sand banks of Monkey Mia, in Western Australia’s Shark
Bay. The location was chosen for its near-pristine condition, meaning it has
been influenced very little by human activity. The green sea turtle population
in this area remains relatively constant, and they feed on two kinds of
seagrass, Amphibolis antarctica and Posidonia australis. Additionally, their lone predator in the area
is the tiger shark, Galeocerdo cuvier,
which varies in abundance over the seasons. Turtles are known to be able to
modify the nutrient composition and detrital cycles, which is the recycling of
nutrients from dead organic matter, of seagrass communities. They are also some
of the most long-lived organisms on earth. Since this population of C. mydas suffered a relatively low
mortality rate, it was considered an ideal model to study the influence of
state-dependent behavior on its ecosystem.
 |
| Green sea turtle eating seagrass. Photo provided by Jenn Sweatman. |
The
study area consisted of seagrass beds up to 4 meters underwater, with edges
that sloped down to between 6 and 12 meters. A. antarctica found on the banks’ edges tended to be lower in
organic carbon and nitrogen than those found towards the middle. Turtles favor
organic nutrients and thus would prefer to dine on the more nutritious grasses
towards the center of their feeding grounds. Feeding in the middle of the
seagrass bed would make it more difficult for the turtles to get away from
tiger sharks, should they come along. Turtles escape their predators by
combining bursts of speed with sharp turns to the left and right, as well as
suddenly diving and ascending. Sharks have trouble chasing them when they do
this. Shallow water towards the center of the seagrass beds limits
maneuverability, while deeper water near the edge of the banks facilitates it.
The authors determined that the turtles, as a consequence of this behavior,
would only risk grazing on more nutritious grasses if they were in poor physical
condition. Simply put, their state would dictate their choice of food. Those
content with their state would stay closer to the ends; those who needed extra
nutrition would take the risk and venture towards the middle of the banks.
Gathering
data on turtle condition was done by evaluating body mass behind the neck and
at the fore-flippers, as well as measuring the Curved Carapace Length (CCL),
i.e. the curvature of their undersides. Individuals with more concave
undersides were considered to be in poorer condition than those with more
convex or flat undersides. Higher neck and flipper body mass also implied
greater health. Activity level during capture, which was done by hand using
transect sampling, was also an indication of condition; the better their state,
the more resistance they put up. The researchers tagged each individual with
special GPS transmitters that could track their movements, and overall distance
from the edges of the seagrass beds.
As
the team predicted, turtles that were in poor condition constantly ventured
further into the grass beds than their healthier peers. This trend was observed
both when sharks were scarce and when they were abundant. These turtles did not
greatly change their distance from the banks regardless of shark density and,
on average, could be found about 350 to 400 meters away from the bank edges.
When these predators were scarce, though, better condition turtles also
ventured towards the more central seagrasses. Yet they never went as far inward
as those in poorer condition. On average, good condition individuals never
grazed more than 250 meters away from the banks.
Similar
studies had been conducted for grasshoppers by Ovadia and Schmitz (2002, 2004),
who published their results in 2002. They attempted to model community dynamics
based on grasshoppers’ risk-taking during foraging when under threat of spider
predation. Grasshoppers were found to adjust their foraging habits based on
size, but these adjustments were of no help in predicting shifts in community dynamics.
The study’s variable of interest was the effect of grasshopper feeding on
vegetation.
According
to Heithaus and his colleagues, Ovadia and Schmitz’s results may be due to the
short lifespan of grasshoppers. It is possible, they postulate, that spider
predation did induce a change in foraging effort, but the grasshopper dies
before it can make a lasting impact. Turtles like C. mydas, on the other hand, live for years. Enduring adjustments
in their feeding habits will influence their ecosystem for a significant period
of time; decades even. As such, one of the team’s hypotheses is that
longer-lived species will be more “risk-adverse” than short-lived ones, and as
such have greater potential to influence ecosystem dynamics.
The
data obtained in this study seems to uphold this hypothesis. The team
downplayed the possibility of sharks modifying turtle behavior by eating them
because G. cuvier feed little, and on
many different species. This means the green sea turtles in Shark Bay are
preyed upon at a low rate. Low actual predation rates indicate that the
intimidating nature of the predator is likely the cause of behavioral
modifications. Ovadia and Schmitz’s grasshopper study, while it did not find a
significant impact on community dynamics, saw similar patterns, which led the
authors to conclude that these trends may be seen in both terrestrial and
aquatic ecosystems.
Still,
given that turtles respond to the presence of sharks by modifying their grazing
patterns, one may speculate that these predators have an important role in
maintaining ecological balance. The authors state a reduction in shark
populations may lead to turtles being more liberal with their food intake. This
would be detrimental to seagrasses, and could influence the primary production of
the entire community as a result. They cite seagrass declines in Bermuda which seem
to correlate with increases in turtle populations, and a decline in shark
numbers.
Conservation
efforts often focus on the protection of species of interest, and that is a
good thing; a worthwhile thing. Care must be taken, however, to ensure that the
ecological balance of that species’ community is not distorted in the process.
Too much of a good thing may indeed be bad and, in the case of green sea
turtles, an over-abundance of herbivores can influence the primary production
of the entire ecosystem. Therefore, to echo the final words of this study,
conservation efforts must consider both the lethal and non-lethal effects of
predators outright during their planning phases.
References
Boundless. (2014, July 3). Community Dynamics. Retrieved from Boundless.com: https://www.boundless.com/biology/textbooks/boundless-biology-textbook/population-and-community-ecology-45/community-ecology-254/community-dynamics-939-12198/
Ovadia, O., &
Schmitz, O. (2002). Linking individuals with ecosystems: experimentally
identifying the relevant organizational scale for predicting trophic
abundances. Proceedings of the National Academy of Sciences, 99,
12927-12931.
Ovadia, O., & Schmitz, O. (2004). Scaling from individual food webs: the role of size-dependent responses of prey to predation risk. Israel Journal of Zoology, 50, 273-297.
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