Sustainable Business News: April 12, 2019

Investors pressure soy companies to live up to commitments against deforestation. [link]

Natural forests have high potential to address climate change. [link]

Developed countries in the EU have stable forests, but they import food produced through deforestation [link]

Scientists map network of marine protected reserves that would cover 30% of the ocean and all ocean ecosystem categories [link]

Sustainable Business Headlines: April 11 2019

Shell Oil is investing $300M over three years in ecosystem-based projects, primarily reforestation, as part of its ongoing attempt to shift strategies away from oil and natural gas to a broader focus on clean energy technology and reduced carbon emissions. [link]

The World Meteorological Organization released its 25th State of the Climate Report, an annual report on the planet’s climate. According to this year’s report, the physical and financial impacts of climate change are accelerating. [link]

The New York Times covers Chevron, Occidental, and BHP’s investments in carbon capture and storage technology, including tech that removes carbon from the atmosphere and converts it to liquid fuel. [link]

The New York Times covers activist legal strategies to sue companies for carbon pollution. [link]

The Book of Why: Chapter 2

This post continues the series of posts on Judea Pearl and Dana Mackenzie’s “The Book of Why.” This post covers Chapter 2: From Buccaneers to Guinea Pigs: The Genesis of Causal Inference.

Francis Galton

Galton’s development of regression arose from his interest in predicting the inheritance of traits between human generations. He first interpreted the patterns he found as causal. He eventually weakened his causal interpretation of regression to the mean by noting it occurred mathematically regardless of whether there was a cause or not.

Karl Pearson

Karl Pearson, Galton’s disciple, extended Galton’s work by further focusing on correlation rather than causation. Pearson subscribed to a positivist philosophy that viewed the universe as a product of the human mind. Science, then, was incapable of observing the world absent the human mind and was instead a description of human thought about the world. Causation “as an objective process that happens in the world outside the human brain” is not compatiable with the positivist philosophy (p. 67). Patterns of thought can be described by correlation, though.

Galton passed away and left money to establish a professorship in biometrics (statistics) at University College London, conditional on Pearson being the first holder. From that position of power, Pearson, who sounds like a controlling, domineering personality, led the development of the field of statistics for several decades, including supervising assistants like George Udny Yule.

Despite Pearson’s enthsuiasm for correlation, he did right papers mentioning spurious correlation and admitted it was easy to find examples of silly correlations

Udny Yule

Yule eventually broke with Pearson’s disdain for causal explanation after studying whether providing assistance to the poor in their own homes or in poorhouses affected poverty in London. The data showed districts with more at-home assistance were poorer, and Yule suspected the correlation was spurious because such districts might have more elderly people, who tended to be poor. But he then compared districts with similar proportions of elderly residents and found the same correlation. From this he concluded that higher poverty in such districts was due to more at-home poverty releif. But in a footnote, he hedged: “Strickly speaking, for ‘due to’ read ‘associated with.'”

Sewall Wright

Wright completed a doctorate in genetics in 1915 and took a US government job managing resaerch guinea pigs. From that position, he built a career theorizing about evolution, differing from Darwin by arguing evolution could happen in rapid bursts rather than gradually.

He worked on explaining the inheritance of coat color in guinea pigs, which did not follow Mendelian inheritance rules. Even highly inbred lines never produced controllable coat color, contradicting the Mendellian rule that a trait should become “fixed” after multiple generations of inbreeding.

Wright theorized that genetics were not the only determinant of coat color. He thought developmental factors might play a role, and he developed some mathematical theory and graphical representations of how genes and developmental factors interacted to produce coat color. These graphics were the roots of today’s causal path diagrams. Wright published a paper in 1920 with what was probably the first causal path diagram to appear in the scientific literature.

Wright’s diagram married two mathematical languages that had been separate: qualitative arrow information with quantitative data information. Wright’s work also separated causation and correlation into separate constructs. Prior to Wright, causation had been thought a special case of correlation = 1.

Unfortunately, Wright’s work went unnoticed in academia for decades until sociologists and then economists rediscovered it and developed similar ideas as structural equation modeling (SEM) and simultaneous equation modeling. However, these methods tend to obscure the scientific causal logic Wright emphasized behind automated procedures for estimating path coefficients.

One source of resistance to Wright’s diagrams might have been how they highlight the subjectivity of objectivity. Path diagrams encode assumptions about causal processes that are then used to make claims about how processes work. Those who favor presenting objectivity as outside the human mind might not have been interested in path diagrams that undermine the image of objectivity.

However, in the past few decades, even the most objectivity-minded fields have started to embrace approaches that make subjective assumptions explicit, like Bayesian analysis.

Report on Great Lakes climate change impacts

The Environmental Law & Policy Center recently assessed the impacts of climate change on the Great Lakes. The report is available here.

The report makes many high-level conclusions, several of which are:

  1. Winters and springs will have higher precipitation and more frequent high-precipitation events. Summers will be drier.
  2. By 2100, 30-60 days of the year will reach extremely high temperatures above 90-degrees Fahrenheit, compared to today.
  3. The number of extremely cold days below freezing will dramatically decrease.
  4. Changes in precipitation and temperature will impact agriculture, a major industry in the region.
  5. Water quality challenges will become more frequent, especially due to increased pollutant runoff into the Great Lakes system associated with increased precipitation.

Overall, increased precipitation and temperatures might have the greatest impact on the Great Lakes and Midwest region.

Increased precipitation will cause more frequent flooding and flooding in areas historically thought safe from flood risks. In the short term, this will cause economic losses as properties not covered by flood insurance flood and infrastructure built in more flood-prone areas might need to be relocated or abandoned. Government bodies will face pressure to build new water management infrastructure, which is expensive and will strain government budgets already stressed by declining populations and economic activities in many Midwestern communities, especially rural communities.

Increased precipitation will also elevate soil erosion from agricultural land, a long-standing problem in the region that contributes to decreasing soil yields and increasing reliance on ag inputs like fertilizer and manure. More precipitation will increase the rate at which fertilizer and manure wash into streams, drinking water systems, and, ultimately, the Gulf of Mexico through the Mississippi River. The current vicious cycle in which more soil erosion motivates more inputs, which in turn cause elevated pollution problems might intensify.

Higher temperatures will alter economic and cultural patterns in the region. Many Great Lakes states have rich winter-time cultural traditions such as hockey, ice fishing, and skiing. As temperatures rise, snow quality and amount might decline as more precipitation falls as rain or mixed precipitation. Lakes might freeze later and thaw earlier, reducing frozen lakes as economic and cultural resources.

The Great Lakes region underwent rapid economic and social disruption with deindustrialization over the past several decades. The next few could see similar disruption, but this time from climate change impacts.