A First-Of-Its-Kind Magazine On Environment Which Is For Nature, Of Nature, By Us (RNI No.: UPBIL/2016/66220)

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Prof CP Rajendran

TreeTake is a monthly bilingual colour magazine on environment that is fully committed to serving Mother Nature with well researched, interactive and engaging articles and lots of interesting info.

Prof CP Rajendran

Prof CP Rajendran

Prof CP Rajendran

Expert Expressions

What has brought us to this?

The number of infectious disease outbreaks, due to microbes breaking the species barrier and cross from other animals to humans, has been on the rise in recent decades. The current pandemic of the new coronavirus has precipitated an acute health crisis around the world, spreading rapidly to tens of thousands of people, and requiring the healthcare systems of various countries to be mobilised on a scale the world hasn’t witnessed since the Spanish flu outbreak of 1918. Of course, a huge gulf of acquired knowledge separates the people of 2020 from those of 1918 – but the fear has stayed the same.

No doubt these are unsettling times, but it is important to understand what got us near this precipice in the first place. Doctors in China initially reported the presence of a new coronavirus towards the end of December 2019 from Wuhan, a the capital of China’s Hubei province. By the middle of January 2020, Chinese researchers had sequenced the new virus’s genome and published it for other researchers around the world to study. Subsequent analyses revealed that the new virus, since called called SARS-CoV-2, shares a common pedigree with a family of coronaviruses known to cause acute respiratory syndromes. Perhaps the most prominent example of these viruses is the SARS virus, which caused the first known pandemic due to a coronavirus in 2002-2003. The first report of an infection was made in the Guangdong province of China, wherefrom the virus later spread to five cities and eventually to 30 countries around the world. Researchers defined the virus’s disease as an acute community-acquired atypical pneumonia syndrome. In all, the SARS virus infected 8,096 people and killed 774. As with the new coronavirus, the index case patient in Guangdong was known to have had regular contact with game animals. So as such, the SARS pandemic was a warning of sorts.

To quote at length from a paper published by a group of researchers from Hong Kong University in October 2007: The rapid economic growth in southern China has led to an increased demand for animal proteins, including those from exotic game food animals such as civets. Large numbers and varieties of these wild game mammals in overcrowded cages and the lack of biosecurity measures in wet markets allowed the jumping of this novel virus from animals to humans. Its capacity for human-to-human transmission, the lack of awareness in hospital infection control, and international air travel facilitated the rapid global dissemination of this agent. The acute and dramatic impact on health impact on health care systems, economics and societies of affected countries within a few months of early 2003 was unparalleled since the last plague. The small reemergence of SARS in late 2003 after the resumption of the wildlife market in southern China and recent discovery of a very similar virus in horseshoe bats bat SARS-CoV suggested that SARS can return if conditions are fit for the introduction, mutation, amplification and transmission of this dangerous virus. The authors added also that coronaviruses have a “propensity to undergo genetic recombination” – that is, exchange genetic material with other viruses – “which may lead to new genotypes and outbreaks”. They then qualify the culture of eating exotic mammals in southern China as a time bomb and conclude that a SARS-type disease and other novel viruses could reemerge from animals and laboratories in southeast China.

After the outbreak concluded, China banned the trade of wildlife, although not for long. Within a few years, the Chinese government allowed wildlife markets to resume operations in southeastern China; an American veterinarian called the region a “cauldron of contagion” in an interview to National Geographic. The Chinese traditional medicines industry has been the main driver of these markets, exploiting belief among locals as well as people abroad that different animal parts have healing powers. Finally, after the COVID-19 outbreak this year, China amended its Wildlife Protection Act on February 24 and invoked a permanent ban on the trade of live wild-animals, although only for food. The similarities between SARS and COVID-19 can’t go unnoticed. Why did the world ignore multiple warnings that deadlier viruses could emerge from wildlife in the context of SARS outbreak? Why did China allow its huge wild-animal markets to thrive all these years? Finally, why did the WHO play mute spectator to this obvious threat, especially since the current outbreak could have been toned down, if not staved off entirely, wildlife trade had been better regulated sooner? The present crisis is only the price we pay for ignoring these warnings.

The Science and Chaos of Complex Systems

Twentieth century physics rests on three pillars: the theories of relativity, quantum mechanics and chaos theory. “A butterfly flapping its wings in Brazil can produce a tornado in Texas.” When Edward Lorenz, a North American theoretical meteorologist studying weather systems, introduced this sentence in the title of a lecture he delivered in 1972, it created a flutter, and some amusement, among scientists. The term ‘butterfly effect’ has since entered the public consciousness thanks to James Gleick’s 1987 bestseller Chaos. The butterfly effect is a metaphor to explain how small differences in a single variable can affect a system’s evolution in big ways. This and other early insights by Lorenz marked the beginning of a new science that impacted the study of all complex systems, such as the climate, economics, social groups, population biology and even biomedicine.

Ideas about chaos theory had originated a decade before 1972. Lorenz, a professor at the department of meteorology at the Massachusetts Institute of Technology, arrived at his seminal conclusions based on simulations on archaic computers in use at the time. When it wasn’t impossible to model the weather using these machines, it was extremely challenging. Rapidly shifting atmospheric circulation patterns, cyclonic conditions and the underlying processes that governed them captivated Lorenz. He had already understood that such processes couldn’t be explained by simple mathematical formulations. Instead, he constructed a set of equations to model air convection and programmed them into his cabinet-sized, vacuum-tube-based Royal McBee computer and obtained predictive results. Then he applied Isaac Newton’s second law of motion – that the net force on an object equals its mass times its acceleration (F = m × a) – to further refine his simulation. Since a set of measurable parameters – temperature, pressure and wind velocity – determine the weather, conventional wisdom at the time was that a well-developed model, a good data set and a powerful computer should suffice to predict future weather conditions.

But as Lorenz played with different datasets and studied the output, he discovered that small changes in the input parameters could drastically affect results. That is, even in a straightforward set of differential equations, a minute change in initial conditions yielded radically different results. To make sense of this he turned to math, and it was fortunate that he was a formidable mathematician. Although each iteration of the same simulation yielded different results, Lorenz was able to discern some order in the disorder, associated with feedback loops, self-similarities and patterns of self-organisation. After further calculations, Lorenz found he could explain the complexity of Earth’s atmosphere with three nonlinear equations that captured the randomness in the sequence of processes he’d been trying to model. To visualise the product of his efforts, he had his computer plot the equations’ outputs in a three-dimensional graph. In response, the machine drew a strange and beautiful double spiral that resembled the wings of a butterfly. The curve never intersected with itself nor retraced a path, but looped around forever, sometimes spending more time in one wing before switching to the other. It was a picture of chaos containing multiple elements of both order and disorder.

Scientists today call this curve the Lorenz attractor. It’s the state to which a dynamic system evolves towards, as if the curve exerts an attractive force. There are different attractors corresponding to different types of systems; the Lorenz attractor for example is denoted ‘strange’ because the butterfly wings of its curve are never completely congruent. Lorenz establishing the importance of his attractor for the study of Earth’s atmospheric systems allowed meteorology to breakaway from the staid determinism of science of the 18th and 19th centuries – a break that other fields of science, such as physics, had made decades earlier. Twentieth century physics rests on three pillars: the theories of relativity, quantum mechanics and chaos theory. The first two provide the physical and mathematical bases for natural processes; the third is an analytical tool that helps us tease order out of disorder. And if we are to surmount the climate crisis – the principal issue of the twenty-first century – we’ll have to plumb the depths of chaos to find new ways to change, adapt and survive.

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