Floods, wildfires, overfishing, and pollution are some of the many disruptions that can change the balance of ecosystems, often endangering entire species. However, evaluating these ecosystems to assess which species are most at risk, in order to focus conservation efforts and policies where they are most needed, is a highly challenging task.
While previous attempts assumed that ecosystems are essentially in a state of equilibrium, with external perturbations causing only temporary shifts before things eventually return to an equilibrium state, a study led by the Massachusetts Institute of Technology (MIT) has now argued that ecosystems are in fact often in flux, with the relative abundances of their different components shifting on timetables of their own. By starting with this more realistic assumption, the experts devised a better, predictive way of evaluating these systems in order to rank the relative vulnerabilities of different species, and to detect which of these species are most at risk.
This study is analogous to Edward Lorenz’s groundbreaking analyses of weather patterns decades ago, in which he argued that tiny perturbations in a complex system could eventually lead to disproportionately large outcomes – famously exemplified by the idea that the flapping of a butterfly’s wings in one place could ultimately lead to a massive hurricane somewhere else (the so-called “butterfly effect”).
However, while in cases such as weather forecasting, scientists largely understand the underlying physics of the phenomena and can produce equations to describe their dynamics, in the case of complex ecosystems, this is much more difficult. Nevertheless, over the past decade, scientists have managed to develop mathematical techniques that could provide descriptions of complex ecosystems without knowing the underlying equations.
The MIT researchers and their colleagues developed two such approaches – called “expected sensitivity ranking” and “Eigenvalue ranking” – which performed well in tests using large sets of simulated data, producing rankings that closely matched those expected. While traditional attempts to rank the vulnerability of species tended to focus on measures such as body or population size, “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,” as study senior author Serguei Saavedra (an associate professor of Civil and Environmental Engineering at MIT) put it.
“Approaches based on equilibrium dynamics have this static view of species interaction effects,” added study lead author Lucas Medeiros, a former PhD student at MIT. “Under nonequilibrium abundance fluctuations, these interaction effects can change over time, impacting the sensitivity of any given species to perturbations.”
For instance, species that are highly active during summer, but dormant in winter may be strongly affected by summer wildfires or heatwaves, but completely unaffected by various disruptions happening in the winter.
The techniques developed by the researchers are general enough to be applied for any out-of-equilibrium dynamical system, and have even been used to predict fluctuations in financial markets. However, their primary goal remains the assessment of species vulnerabilities, which is crucial in times of marked environmental disruptions such as ours.
The study is published in the journal Ecology Letters.
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