Yeast colonies shown close up. Image: wikimedia commons/Lilly M. |
In the early 1990s,
overfishing led to the collapse of one of the most bountiful cod fisheries in
the world, off the coast of Newfoundland.
Twenty years later, the cod population still has not recovered, dramatically
affecting the economic life of the region.
To explain this kind
of collapse, ecologists have long theorized that populations suffering a
decline in environmental conditions (such as overfishing) appear stable until
they reach a tipping point where the population plummets. Recovery from such collapses
is nearly impossible.
“This is thought to
underlie lots of sudden transitions—in populations, ecosystems or climate
regime shifts,” says Jeff Gore, an assistant professor of physics at Massachusetts
Institute of Technology (MIT).
Gore and his students
have now offered the first experimental validation of this theory. They showed
that in populations of yeast subject to increasingly stressful conditions,
populations became less and less resilient to new disturbances until they reached
a tipping point at which any small disruption could wipe out a population.
“In the wild, you do
see things change suddenly, and this model is a reasonable explanation, but
it’s very hard to prove that this is happening,” Gore says. “This is the kind
of thing we can do in the laboratory that you can’t do in the wild.”
The findings, published
in Science, could help fishery and wildlife managers identify warning
signs so interventions can be made before total collapse occurs. Lead authors
of the paper are MIT graduate student Lei Dai and visiting student Daan
Vorselen. Pappalardo Postdoctoral Fellow Kirill Korolev is also an author.
Stress response
Gore and his coauthors did their experiments with populations of yeast growing
in test tubes. Each of the organisms secretes an enzyme that breaks down
sucrose in the environment into smaller sugars that it can use as a food
source. All of the yeast benefit from this process, so the population is most
successful when it maintains a certain density—not too low, not too high.
This phenomenon, known
as the “strong Allee effect,” occurs whenever members of a population profit
from having other individuals nearby. For example, fish benefit from traveling
in a school, which offers protection from predators. The theoretical model
tested in this paper should hold true for any population that shows a strong
Allee effect.
In this study, the
researchers simulated a decline in environmental conditions by removing a
certain percentage of each yeast population from its test tube every day,
representing the populations’ death rate. In real life, such deteriorating
conditions could result from lack of food, overfishing, climate change,
acidification of the ocean, or anything else detrimental to a population.
The researchers found
that as conditions decline, the population becomes less resilient. Whenever it
suffers any kind of perturbation, the population is more prone to extinction,
requiring more time to recover to a stable population size.
In this case, the
disturbance was a salt shock, which disrupts many cellular functions in yeast
and can lead to death. Populations that were closer to the tipping point
collapsed, while those living in better environmental conditions were able to
bounce back. “In the more challenging environments, the populations are not as
robust,” Gore says. “Moreover, it is often difficult to predict an upcoming
collapse by simply monitoring the decrease in population size.”
But there is cause for
some optimism: The researchers found that the fluctuations in yeast population
became larger and slower near the tipping point. Thus, an increase in size and
timescale of fluctuations may serve as indicators of how fragile a population
is and provide advance warning of its impending collapse.
Stephen Carpenter, a
professor of zoology at the University
of Wisconsin at Madison, says the new study’s biggest
contribution is that the researchers were able to both map the location of the
tipping point, or threshold, and measure the early warning signs that predict
it.
“Many systems are so
complicated that you can’t really measure resilience,” he says. “You might be
pretty sure that there’s a threshold, and you can move from one side to the
other, but you don’t know exactly where the threshold is.”
In the wild
While this phenomenon is easier to observe in a laboratory than in wild
populations, the researchers believe that the warning signs they have
identified—most importantly, the loss of resilience as the tipping point is
approached—could help wildlife and fishery managers monitor their populations.
This could be achieved
by measuring population levels and comparing them with the fluctuations
predicted by the researchers’ model. The team is also studying the spatial
patterns of populations as they decline, in hopes of identifying warning signs
that might be easier to monitor than population fluctuations.
The researchers are
also looking at more complex systems to see if they can find the same effect.
“This is the simplest case
you could possibly imagine—a single species in a test tube. We’re interested in
trying to start adding a second species, or at least a second strain … to see
if the same dynamics will be there,” Gore says.
