Reviewed by Mila PereraNov 1 2022
A new analysis considers natural fluctuations and predictability to evaluate which parts of an ecosystem are most threatened by climate change and other disturbances.
Intertidal ecosystems containing species of mussels, barnacles, and algae were one of the systems with fluctuating populations analyzed by the team. They developed a new way to detect species that are vulnerable to perturbations, such as waves and storms that affect intertidal ecosystems. Image Credit: Courtesy of the researchers
Wildfires, pollution, floods, and overfishing are among several disruptions that could alter the balance of ecosystems, sometimes threatening the future of whole species. However, it is difficult to assess such ecosystems to identify which species are most at risk and to concentrate preservation actions and policies where they are required.
Most measures assume that ecosystems are basically in a state of equilibrium and that external perturbations induce a temporary shift before things ultimately return to that equilibrium state.
However, that assumption ignores the reality that ecosystems are frequently in flux, with the comparative abundances of their various components moving on their own timetables.
Currently, a research team at Massachusetts Institute of Technology (MIT) and elsewhere has created an improved and predictive method of assessing these systems to rank the comparable vulnerabilities of various species and to detect endangered species that could otherwise go unseen.
Compared to traditional ranking methods, they found that using the criteria of species with the fewest population numbers or those in the sharpest decline does not always accurately represent the species most at threat.
The study findings have been reported in the journal Ecology Letters, in a paper by MIT Associate Professor of Civil and Environmental Engineering Serguei Saavedra, recent doctoral student Lucas Medeiros Ph.D., and three others.
The study performed by Loren’s research indicated that minor disturbances could eventually result in severe consequences.
Even infinitesimally close initial conditions can diverge quite largely over a given period of time and therefore become unpredictable. We said, what would happen if we apply the same kind of perspective to trying to figure out which are the most sensitive species?
Edward Lorenz, Massachusetts Institute of Technology
In a few cases, as in aspects of weather forecasting, researchers understand the basic physics of the phenomena and can thus produce equations explaining their dynamics up to a point.
Lorenz stated that it is not the case with complicated ecosystems, where one does not have the basic equations for the dynamics of even single species, which is much less than the entire system.
However, over the last decade or so, Lorenz stated, the team has come up with mathematical methods so that “we can have a description of the dynamics without knowing the underlying equations,” as long as there is enough time series of data to work with.
The team came up with two different methods, known as Eigenvector ranking and expected sensitivity ranking. Both methods performed well in tests with the help of large sets of simulated data, thereby producing rankings that closely paired those expected given the basic assumptions of the simulation’s model.
Conventional attempts to rank the vulnerability of species tend to focus on measures such as body size, as larger species tend to be more vulnerable, and population size, both of which can often be useful indicators.
However, as Saavedra points out, “These species are embedded in communities, and these communities have nonlinear emergent behavior such that a small change in one place would change completely in a different way some other aspect of the system.”
The fact that species within an ecosystem may have abundances that rise and fall, sometimes cyclically, sometimes randomly, or determined by external forces, means that the exact timing of a given perturbation can make a big difference, which is something that equilibrium models fail to account for.
Approaches based on equilibrium dynamics have this static view of species interaction effects. Under nonequilibrium abundance fluctuations, these interaction effects can change over time, impacting the sensitivity of any given species to perturbations.
Lucas Medeiros, Doctoral Student, Massachusetts Institute of Technology
For instance, a species that is highly active in summer but dormant in winter might be powerfully affected by a heat wave or summer wildfire but entirely unmoved if the disruption takes place in winter.
Conversely, if interactions between a predator species and its prey change over a year, then the timing of disruption could be highly disruptive during some seasons compared to others.
Saavedra says that the novel analytical methods are extensively applicable to any ecosystem, whether it is terrestrial or marine, tropical or arctic. Indeed, the formulas are so general when employed in systems with several interactions and constant flux that few scientists have employed them successfully in anticipating the dynamics of financial markets.
The techniques are quite general for any nonlinear dynamics or dynamical systems in general out of equilibrium. He basically was able to apply these techniques, and they were working.
Serguei Saavedra, Associate Professor, Civil and Environmental Engineering, Massachusetts Institute of Technology
In the group, he states that one student working on such methods ended up collaborating for a hedge fund, and another took a sabbatical to work for a foreign bank.
However, the main goal of the work is evaluating species vulnerability, and the findings are already being used. For instance, Medeiros, the paper’s lead author, is working at the University of California at Santa Cruz and the National Oceanic and Atmospheric Administration, employing these methods in the management of fisheries.
With fisheries in particular, you have a lot of data series, looking at the rise and fall of these population sizes over time. Using those data, he says, it’s now possible “to predict precisely the species that should be most sensitive to, for example, climate change, or the highest rate of fishing quotas.
Serguei Saavedra, Associate Professor, Civil and Environmental Engineering, Massachusetts Institute of Technology
Additionally, the research team included Stefano Allesina, currently at the University of Chicago and Northwestern University; Vasilis Dakos, currently at the University of Montpelier, in France; and George Sugihara, now at the University of California at San Diego.
The work was financially supported by MIT’s Environmental Solutions Initiative, the Martin Family Society of Fellows for Sustainability, the U.S. Department of Defense Environmental Research and Development Program, the National Science Foundation, the Department of the Interior, and the MIT Sea Grant Program.
Journal Reference
Medeiros, L. P., et al. (2022) Ranking species based on sensitivity to perturbations under non-equilibrium community dynamics. Ecology Letters. doi.org/10.1101/2022.07.23.501258.