The Groundbreaking Science Shaping Our World in 2016
A Portal to Progress
The year 2016 wasn't just about political upheaval or viral apps—it marked a watershed moment for interdisciplinary science tackling humanity's most pressing challenges. The inaugural issue of Environment Systems & Decisions (Volume 36, Issue 1) served as a microcosm of this progress, publishing research that reshaped our understanding of risk, resilience, and environmental trade-offs 1 . From the psychology of disaster preparedness to the hidden environmental costs of our diets, scientists deployed innovative methodologies to cut through complexity. This work transcended academic silos, influencing policy debates and even pop culture—while battling the perils of sensationalism. Let's revisit the breakthroughs that defined a year of scientific daring.
The 2016 issue championed systems-based approaches, recognizing that environmental, social, and technological challenges are interconnected.
Dillon and Tinsley's experiments revealed that people often interpret "near-miss" events as evidence of increased safety rather than a warning, leading to reduced preparedness 1 .
Tom, Fischbeck, and Hendrickson's study quantified the full environmental footprint of U.S. diets using Life Cycle Assessment, revealing surprising trade-offs 1 .
Prosperi et al. framed food systems as intertwined networks requiring diversity, modularity, and adaptive governance 1 .
How does exposure to near-miss information influence people's willingness to invest in disaster preparedness?
Dillon and Tinsley designed a controlled experiment with sequential phases 1 :
| Group | Information Provided | Sample Size |
|---|---|---|
| Near-Miss | Hurricane passed 20 miles offshore | 120 |
| Clear-Miss | Hurricane passed 100+ miles away | 120 |
| Direct-Hit | City suffered major damage | 120 |
Participants exposed to near-misses invested 22% less in preparedness than the clear-miss group and 35% less than the direct-hit group. Surveys showed they interpreted the near-miss as evidence of "good luck" or "city resilience," reducing perceived future risk.
| Group | Investment (Pre-Test) | Investment (Post Near-Miss) | Change |
|---|---|---|---|
| Near-Miss | $4.2M | $3.3M | ↓ 22% |
| Clear-Miss | $4.1M | $4.2M | ↑ 2% |
| Direct-Hit | $5.0M | $5.1M | ↑ 2% |
Implications: This work explained why communities underprepare after narrow escapes (e.g., avoiding predicted floods). It underscored the need for risk communication strategies that reframe near-misses as "near hits" to trigger proactive behavior.
Tom et al.'s LCA study quantified three key impacts across 10 dietary scenarios 1 :
| Diet Type | GHG Emissions (kg CO₂e) | Blue Water Use (Liters) | Energy Use (MJ) |
|---|---|---|---|
| Standard American | 5.8 | 1,520 | 25.1 |
| USDA Recommended | 5.4 | 1,840 | 24.3 |
| Lacto-Vegetarian | 4.1 | 1,290 | 19.7 |
Lettuce cultivation required ~60 L water per kcal—tripling bacon's GHG impact per kcal and sparking media frenzy.
Headlines like "Eating Lettuce is Three Times Worse Than Bacon!" misrepresented the science. The study never compared bacon to lettuce; it highlighted that low-calorie foods can have high resource costs per calorie. Tomato production, for example, used 14x more water per calorie than chicken. The authors clarified: reducing red meat and seafood still offered the greatest environmental benefits 1 .
These studies relied on cutting-edge tools bridging data and decision-making:
| Reagent/Method | Function | Study Example |
|---|---|---|
| Life Cycle Inventory Databases | Provide pre-verified data on resource inputs/emissions for materials/processes | Tom et al. diet LCA |
| Agent-Based Modeling | Simulates decisions of individuals within systems to predict macro-behavior | Smith et al.'s Twitter network analysis |
| Fuzzy Logic Classifiers | Handles imprecise data using probabilistic rules | Kizhisseri's wastewater tool |
| Eye-Tracking Software | Measures attention and cognitive load during risk assessments | Dillon & Tinsley's experiment |
The 2016 issue of Environment Systems & Decisions proved that rigorous science could illuminate paths forward—even when distorted by viral headlines. Its legacy endures: near-miss psychology now informs disaster drills; LCA reshapes sustainable diet guidelines; and systems models underpin climate adaptation. Yet the lettuce-bacon saga remains a cautionary tale. As we face escalating environmental crises, translating nuanced science into public action demands not just data, but context—and a media landscape that prioritizes accuracy over alarm. As the editors urged in 2016: "Scholarly discourse must bridge the gap between the lab and the living room" 1 . In an era of AI and climate chaos, that mission has never been more vital.