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Wednesday, Aug. 22, 2018

NOTE: Martin Smith is available for additional comment at (919) 613-8028 or marsmith@duke.edu. Paul Ferraro is available at (410) 234-9389 or pferraro@jhu.edu. James Sanchirico is available at (530) 754-9883 or jsanchirico@ucdavis.edu.

DURHAM, N.C. – Ancient mariners used triangulation to navigate unknown seas. Modern researchers trying to chart causal links in fisheries or other coupled human and natural systems (CHANS) would do well to follow that example – not with a compass, but by employing multiple points of reference when evaluating impacts, a new analysis by researchers at 91��������, Johns Hopkins University and the University of California Davis shows.

“Stick a marine protected area in a fishery and ask if that caused fish stocks to increase. It sounds like a simple question, but fish move, people move and the oceans are changing. There’s a lot going on,” said Martin D. Smith, George M. Woodwell Distinguished Professor of Environmental Economics at Duke’s Nicholas School of the Environment.

“Simply put: If you’re going to study linkages between human and natural systems, you need to look at the two systems together under similar controls,” Smith said.

To make credible inferences about causal linkages in complex systems, scientists often implicitly make two very basic assumptions when analyzing their data: excludability and no interference. In non-technical terms, these assumptions are akin to what lab scientists assume when randomizing treatments across petri dishes that do not interact. Yet these assumptions rarely are satisfied in most published studies on CHANS, in which multiple confounding variables, observed and unobserved, creates complex feedback across social and environmental dimensions.

“Observational data only gets you so far. Modeling only gets you so far. You need to use multiple approaches, with the aim of identifying sources of bias in each approach and then triangulating on credible inferences,” Smith said. “The trouble is, few studies do this.”

Paul J. Ferraro of Johns Hopkins University and James N. Sanchirico of the University of California Davis and Resources for the Future conducted the analysis with Smith.

They published their work August 20 in a peer-reviewed paper in the Proceedings of the National Academy of Sciences.

In their analysis, the researchers reviewed one of the largest CHANS literatures: studies measuring the impacts of marine protected areas on fisheries. Among nearly 200 studies that aimed to determine if protected areas helped or harmed fisheries and the communities that depended on them, only one study address whether the two basic assumptions of excludability and no interference were satisfied.  

This failure to verify the foundation on which scientific conclusions are being drawn – a failure common across much of the CHANS literature – makes it tricky to gauge the legitimacy of the studies’ findings and undercuts their credibility with policymakers.

“Policymakers increasingly are demanding empirical evidence about what works to benefit both people and the environment, but scientists who study CHANS are often pure modelers. To bridge this divide, we have to reframe our approach, using observed data in a way that puts the alleged causal links in the models on firmer scientific ground,” said Ferraro.  

One possible solution would be to combine approaches from other branches of economics and ecology.  

“No single methodological approach, or disciplinary perspective, can provide the evidence that scientists and policymakers need to advance our understanding of how humans and the environment interact,” said Sanchirico. Our tools for understanding the impacts of human activities that disturb the environment, as well as human attempts to mitigate or reverse that disturbance, are flawed and biased in a variety of ways. Understanding those flaws and biases, and how combinations of empirical methods can mitigate them, is where scientific attention should be directed.”

The researchers’ paper derives from materials they presented at the National Academy of Sciences’ Arthur M. Sackler Colloquium, “Economics, Environment and Sustainable Development,” Jan. 17-18, 2018, in Irvine, Calif.

CITATION: “Causal Inference in Coupled Human and Natural Systems,” Paul J. Ferraro, James N. Sanchirico and Martin D. Smith; Proceedings of the National Academy of Sciences, Aug. 20, 2018. DOI: 10.1073/pnas.1805563115
 
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