What is the impact of a single factor such as climate change on the ecosystem? Ecology is a complex science with multiple and interrelated factors. According to a new study led by scientists at Scripps Institution of Oceanography at UC San Diego, the forces behind the sardine mystery are a dynamic and interconnected moving target. Publishing in the Proceedings of the National Academy of Sciences, Scripps graduate student Ethan Deyle, professor George Sugihara, and their colleagues argue that problems lie in seeking answers one factor at a time, as scientists have done for decades. What is the singular impact of climate or overfishing? Focusing on single variables in isolation can lead to misguided conclusions, the researchers say. Instead, using novel mathematical methods developed last year at Scripps, the researchers argue that climate, human actions and ecosystem fluctuations combine to influence sardine and other species populations, and therefore such factors should not be evaluated independently.
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The technique developed by Sugihara and his colleagues, called “convergent cross mapping,” takes multiple variables into account and avoids the centuries-old “correlation does not imply causation” issue that has plagued single-factor studies. For example, based on data from the Scripps Institution of Oceanography Pier, studies in the 1990s showed that higher temperatures are beneficial for sardine production. By 2010 new studies proved that the temperature correlation was instead a misleading, or “mirage,” determination.
Convergent cross mapping (CCM) is a statistical test which, like the Granger causality test, tests whether one variable predicts another, unlike most other tests which establish a coefficient of correlation but not a cause-and-effect relationship. The Granger test determines causality but has problems when causality runs both ways; for example in a predator-prey relationship, predator numbers affect prey, but prey numbers, i.e. food supply, also affect predators. CCM deals with this by using a delay-embedding to embed each time series data set in the appropriate space and looking for correspondence between the values of one variable and the values of the other in this space. Points on one manifold may be used to predict points on the other, but not necessarily the other way round, allowing causal relationships of one direction or another to be measured separately.
“Mirages are associations among variables that spontaneously come and go or even switch sign, positive or negative,” said Sugihara. “Ecosystems are particularly perverse on this issue. The problem is that this kind of system is prone to producing mirages and conceptual sand traps, continually causing us to rethink relationships we thought we understood.”
By contrast, convergent cross mapping avoids the mirage issue by seeking evidence from dynamic linkages between factors, rather than one-to-one statistical correlations. The study applied this technique to sardine fishing.
“Sustainable sardine fishing based on ecosystem-based management should adapt to dynamic changes in the ocean environment, and future policies should incorporate these effects to avoid another cannery row,” said Deyle.
The investigation into the cause of the 1940s sardine collapse spawned the launch of the California Cooperative Oceanic Fisheries Investigations (CalCOFI), one of the world’s longest and most valuable marine research programs that continues today with support from Scripps, NOAA’s National Marine Fisheries Service (Southwest Fisheries Science Center), and the California Department of Fish and Game.
For further information see Ecology.
Sardine image via Wikipedia.
