China and India are winning the Green revolution!

NASA Ames

Feb. 11, 2019

Human Activity in China and India Dominates the Greening of Earth, NASA Study Shows

Over the last two decades, the Earth has seen an increase in foliage around the planet, measured in average leaf area per year on plants and trees. Data from NASA satellites shows that China and India are leading the increase in greening on land. The effect stems mainly from ambitious tree planting programs in China and intensive agriculture in both countries.

Credits: NASA Earth Observatory

The world is literally a greener place than it was 20 years ago, and data from NASA satellites has revealed a counterintuitive source for much of this new foliage: China and India. A new study shows that the two emerging countries with the world’s biggest populations are leading the increase in greening on land. The effect stems mainly from ambitious tree planting programs in China and intensive agriculture in both countries.

The greening phenomenon was first detected using satellite data in the mid-1990s by Ranga Myneni of Boston University and colleagues, but they did not know whether human activity was one of its chief, direct causes. This new insight was made possible by a nearly 20-year-long data record from a NASA instrument orbiting the Earth on two satellites. It’s called the Moderate Resolution Imaging Spectroradiometer, or MODIS, and its high-resolution data provides very accurate information, helping researchers work out details of what’s happening with Earth’s vegetation, down to the level of 500 meters, or about 1,600 feet, on the ground.

The world is a greener place than it was 20 years ago, as shown on this map, where areas with the greatest increase in foliage are indicated in dark green. Data from a NASA instrument orbiting Earth aboard two satellites show that human activity in China and India dominate this greening of the planet.

Credits: NASA Earth Observatory

Taken all together, the greening of the planet over the last two decades represents an increase in leaf area on plants and trees equivalent to the area covered by all the Amazon rainforests. There are now more than two million square miles of extra green leaf area per year, compared to the early 2000s – a 5% increase.

“China and India account for one-third of the greening, but contain only 9% of the planet’s land area covered in vegetation – a surprising finding, considering the general notion of land degradation in populous countries from overexploitation,” said Chi Chen of the Department of Earth and Environment at Boston University, in Massachusetts, and lead author of the study.

An advantage of the MODIS satellite sensor is the intensive coverage it provides, both in space and time: MODIS has captured as many as four shots of every place on Earth, every day for the last 20 years.

“This long-term data lets us dig deeper,” said Rama Nemani, a research scientist at NASA’s Ames Research Center, in California’s Silicon Valley, and a co-author of the new work. “When the greening of the Earth was first observed, we thought it was due to a warmer, wetter climate and fertilization from the added carbon dioxide in the atmosphere, leading to more leaf growth in northern forests, for instance. Now, with the MODIS data that lets us understand the phenomenon at really small scales, we see that humans are also contributing.”

China’s outsized contribution to the global greening trend comes in large part (42%) from programs to conserve and expand forests. These were developed in an effort to reduce the effects of soil erosion, air pollution and climate change. Another 32% there – and 82% of the greening seen in India – comes from intensive cultivation of food crops.

Land area used to grow crops is comparable in China and India – more than 770,000 square miles – and has not changed much since the early 2000s. Yet these regions have greatly increased both their annual total green leaf area and their food production. This was achieved through multiple cropping practices, where a field is replanted to produce another harvest several times a year. Production of grains, vegetables, fruits and more have increased by about 35-40% since 2000 to feed their large populations.

How the greening trend may change in the future depends on numerous factors, both on a global scale and the local human level. For example, increased food production in India is facilitated by groundwater irrigation. If the groundwater is depleted, this trend may change.

“But, now that we know direct human influence is a key driver of the greening Earth, we need to factor this into our climate models,” Nemani said. “This will help scientists make better predictions about the behavior of different Earth systems, which will help countries make better decisions about how and when to take action.”

The researchers point out that the gain in greenness seen around the world and dominated by India and China does not offset the damage from loss of natural vegetation in tropical regions, such as Brazil and Indonesia. The consequences for sustainability and biodiversity in those ecosystems remain.

Overall, Nemani sees a positive message in the new findings. “Once people realize there’s a problem, they tend to fix it,” he said. “In the 70s and 80s in India and China, the situation around vegetation loss wasn’t good; in the 90s, people realized it; and today things have improved. Humans are incredibly resilient. That’s what we see in the satellite data.”

This research was published online, Feb. 11, 2019, in the journal Nature Sustainability.

 

Credits: NASA Earth Observatory

For news media:

Members of the news media interested in covering this topic should get in touch with the science representative on the NASA Ames media contacts page.

Author: Abby Tabor, NASA's Ames Research Center, Silicon Valley

Last Updated: Feb. 11, 2019

Editor: Abigail Tabor

Tags:  Ames Research Center, Earth, Earth Research Findings, Land

Can A.I. diagnose a disease faster than humans?

Longevity & Vitality Part 3: AI Augments Healthcare and Longevity

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When it comes to the future of healthcare, perhaps the only technology more powerful than CRISPR is Artificial Intelligence. Over the past five years, healthcare AI startups around the globe raised over $4.3 billion across 576 deals, topping all other industries in AI deal activity. During this same period, the FDA has given 70 AI healthcare tools and devices ‘fast-tracked approval’ because of their ability to save both lives and money. The pace of AI-augmented healthcare innovation is only accelerating. In Part 3 of this blog series on Longevity & Vitality, I cover the different ways in which AI is augmenting our healthcare system, enabling us to live longer and healthier lives. In this blog, I’ll expand on: Machine learning and drug design Artificial Intelligence and Big Data in medicine Healthcare, AI & China Let’s dive in. Machine Learning in Drug Design What if AI systems, specifically neural networks, could predict the design of novel molecules (i.e. medicines) capable of targeting and curing any disease? Imagine leveraging cutting-edge artificial intelligence to accomplish with 50 people what the pharmaceutical industry can barely do with an army of 5,000. And what if these molecules, accurately engineered by AIs, always worked? Such a feat would revolutionize our $1.3 trillion global pharmaceutical industry, which currently holds a dismal record of 1 in 10 target drugs ever reaching human trials. It’s no wonder that drug development is massively expensive and slow. It takes over 10 years to bring a new drug to market, with costs ranging from $2.5 billion to $12 billion. This inefficient, slow-to-innovate, and risk-averse industry is a sitting duck for disruption in the years ahead.  One of the hottest startups in digital drug discovery today is Insilico Medicine. Leveraging AI in its end-to-end drug discovery pipeline, Insilico Medicine aims to extend healthy longevity through drug discovery and aging research.  Their comprehensive drug discovery engine uses millions of samples and multiple data types to discover signatures of disease, identify the most promising protein targets, and generate perfect molecules for these targets.  These molecules either already exist or can be generated de novo with the desired set of parameters. In late 2018, Insilico’s CEO Dr. Alex Zhavoronkov announced the groundbreaking result of generating novel molecules for a challenging protein target with an unprecedented hit rate in under 46 days. This included both synthesis of the molecules and experimental validation in a biological test system — an impressive feat made possible by converging exponential technologies. Underpinning Insilico’s drug discovery pipeline is a novel machine learning technique called Generative Adversarial Networks (GANs), used in combination with deep reinforcement learning.  Generating novel molecular structures for diseases both with and without known targets, Insilico is now pursuing drug discovery in aging, cancer, fibrosis, Parkinson’s disease, Alzheimer’s disease, ALS, diabetes, and many others. Once rolled out, the implications will be profound.  Dr. Zhavoronkov’s ultimate goal is to develop a fully automated Health-as-a-Service (HaaS) and Longevity-as-a-Service (LaaS) engine. Once plugged into the services of companies from Alibaba to Alphabet, such an engine would enable personalized solutions for online users, helping them prevent diseases and maintain optimal health. Insilico, alongside other companies tackling AI-powered drug discovery, truly represents the application of the 6 D’s. What was once a prohibitively expensive and human-intensive process is now rapidly becoming digitized, dematerialized, demonetized and, perhaps most importantly, democratized.  Companies like Insilico can now do with a fraction of the cost and personnel what the pharmaceutical industry can barely accomplish with thousands of employees and a hefty bill to foot. As I discussed in my blog on ‘The Next Hundred-Billion-Dollar Opportunity,’ Google’s DeepMind has now turned its neural networks to healthcare, entering the digitized drug discovery arena. In 2017, DeepMind achieved a phenomenal feat by matching the fidelity of medical experts in correctly diagnosing over 50 eye disorders. And just a year later, DeepMind announced a new deep learning tool called AlphaFold. By predicting the elusive ways in which various proteins fold on the basis of their amino acid sequences, AlphaFold may soon have a tremendous impact in aiding drug discovery and fighting some of today’s most intractable diseases.  Artificial Intelligence and Data Crunching AI is especially powerful in analyzing massive quantities of data to uncover patterns and insights that can save lives.  Take WAVE, for instance. Every year, over 400,000 patients die prematurely in U.S. hospitals as a result of heart attack or respiratory failure.  Yet these patients don’t die without leaving plenty of clues. Given information overload, however, human physicians and nurses alone have no way of processing and analyzing all necessary data in time to save these patients’ lives. Enter WAVE, an algorithm that can process enough data to offer a six-hour early warning of patient deterioration.  Just last year, the FDA approved WAVE as an AI-based predictive patient surveillance system to predict and thereby prevent sudden death. Another highly valuable yet difficult-to-parse mountain of medical data comprises the 2.5 million medical papers published each year.  For some time, it has become physically impossible for a human physician to read — let alone remember — all of the relevant published data. To counter this compounding conundrum, Johnson & Johnson is teaching IBM Watson to read and understand scientific papers that detail clinical trial outcomes.  Enriching Watson’s data sources, Apple is also partnering with IBM to provide access to health data from mobile apps.  One such Watson system contains 40 million documents, ingesting an average of 27,000 new documents per day, and providing insights for thousands of users. After only one year, Watson’s successful diagnosis rate of lung cancer has reached 90 percent, compared to the 50 percent success rate of human doctors.  But what about the vast amount of unstructured medical patient data that populates today's ancient medical system? This includes medical notes, prescriptions, audio interview transcripts, pathology and radiology reports. In late 2018, Amazon announced a new HIPAA-eligible machine learning service that digests and parses unstructured data into categories, such as patient diagnosis, treatments, dosages, symptoms and signs.  Taha Kass-Hout, Amazon’s senior leader in health care and artificial intelligence, told the WSJ that internal tests demonstrated that the software even performs as well as or better than other published efforts. On the heels of this announcement, Amazon confirmed it was teaming up with the Fred Hutchinson Cancer Research Center to evaluate "millions of clinical notes to extract and index medical conditions.”  Having already driven extraordinary algorithmic success rates in other fields, data is the healthcare industry’s goldmine for future innovation.  Healthcare, AI & China  In 2017, the Chinese government published its ambitious national plan to become a global leader in AI research by 2030, with healthcare listed as one of four core research areas during the first wave of the plan.  Just a year earlier, China began centralizing healthcare data, tackling a major roadblock to developing longevity and healthcare technologies (particularly AI systems): scattered, dispersed, and unlabeled patient data. Backed by the Chinese government, China’s largest tech companies — particularly Tencent — have now made strong entrances into healthcare. Just recently, Tencent participated in a $154 million megaround for China-based healthcare AI unicorn iCarbonX. Hoping to develop a complete digital representation of your biological self, iCarbonX has acquired numerous U.S. personalized medicine startups. Considering Tencent’s own Miying healthcare AI platform — aimed at assisting healthcare institutions in AI-driven cancer diagnostics — Tencent is quickly expanding into the drug discovery space, participating in two multimillion-dollar, U.S.-based AI drug discovery deals just this year. China’s biggest, second-order move into the healthtech space comes through Tencent’s WeChat. In the course of a mere few years, already 60 percent of the 38,000 medical institutions registered on WeChat allow patients to digitally book appointments through Tencent’s mobile platform.  At the same time, 2,000 Chinese hospitals accept WeChat payments. Tencent has additionally partnered with the U.K.’s Babylon Health, a virtual healthcare assistant startup whose app now allows Chinese WeChat users to message their symptoms and receive immediate medical feedback. Similarly, Alibaba’s healthtech focus started in 2016 when it released its cloud-based AI medical platform, ET Medical Brain, to augment healthcare processes through everything from diagnostics to intelligent scheduling. Conclusion As Nvidia CEO Jensen Huang has stated, “Software ate the world, but AI is going to eat software.” Extrapolating this statement to a more immediate implication, AI will first eat healthcare, resulting in dramatic acceleration of longevity research and an amplification of the human healthspan. Next week, I’ll continue to explore this concept of AI systems in healthcare. Particularly, I’ll expand on how we’re acquiring and using the data for these doctor-augmenting AI systems: from ubiquitous biosensors, to the mobile healthcare revolution, and finally, to the transformative power of the health nucleus. As AI and other exponential technologies increase our healthspan by 30 to 40 years, how will you leverage these same exponential technologies to take on your Moonshots and live out your Massively Transformative Purpose? Join Me (1) A360 Executive Mastermind: This is one of the key conversations I’ll be exploring at my Executive Mastermind group called Abundance 360. The program is highly selective, for 360 abundance- and exponentially minded CEOs (running $10M to $50B companies). If you’d like to be considered, apply here. Share this with your friends, especially if they are interested in any of the areas outlined above. (2) Abundance-Digital Online Community: I’ve also created a Digital/Online community of bold, abundance-minded entrepreneurs called Abundance-Digital. Abundance-Digital is my ‘onramp’ for exponential entrepreneurs – those who want to get involved and play at a higher level. Click here to learn more.

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Potentially deadly genetically modified plants!

"The team found that one insertion attempt could result in as many as seven unintended insertions or manipulations of the host’s genome. Some of these were up to ten times larger than intended, resulting in large segments of the host’s DNA being damaged or relocated. Furthermore, the incoming DNA was sometimes found to be out of place, cut in half, or out of sequence."

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Demystifying GMOs: New Research Shows Unexpected Changes in Plant DNA

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 Scott Simonsen

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Feb 11, 2019

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Genetically modified organisms (GMOs) are one of the most contentious topics in science today. But a study from the Salk Institute, published last month in PLOS Genetics, may help clear up some of the confusion. Using a combination of techniques known as nanopore sequencing and optical mapping, researchers believe they have a clearer picture of what happens when genes are spliced into the genomes of plants and animals.

In particular, the study showed that scientists can determine to what extent surrounding areas of the host DNA have been affected by gene splicing, a point that is often a source of concern for those worried about the possible long-term impacts of GMO consumption.

How GMOs Are Created

To genetically modify a plant or animal, scientists first sequence the entire genome of the organism to determine which stretches of DNA have beneficial qualities. These would include traits that help the organism survive drought, produce higher nutrient densities, be less susceptible to insects or diseases, or be able to withstand certain pesticides, among many others. The DNA sequence containing desirable traits is then removed and implanted into the genome of the host organisms, thereby transferring the beneficial properties.

The most common method of doing this is by using the bacteria Agrobacterium tumefaciens. Several decades ago, it was discovered that when this bacteria caused crown gall tumors on tree trunks, some of the bacteria’s DNA was transferred into the DNA of the tree; the bacteria’s transfer DNA (T-DNA), a circular piece of DNA that can bind with other DNA sequences, was found to be scattered throughout the tree. Since then, researchers have used this bacteria’s T-DNA to help carry the desired genes into all kinds of organisms.

Known Unknowns

However, the problem with this method is its lack of precision. That is, when this process occurs, researchers are not sure exactly what happens. Recent advancements in DNA sequencing techniques led some scientists to suspect that the structure and chemistry of the host DNA might be changed more than originally thought due to unknown interactions with the T-DNA, as well as the amount and length of the T-DNA transferred into the host.

Those designing and selling genetically modified products merely test the new organism for the desired traits and, if they are present, the process is considered a success.

Nanopore Sequencing and Optical Mapping

Originally created in the mid 1990s, nanopore sequencing is considered one of the most effective methods of detecting genetic changes on a molecular level. It works by placing two tiny electrodes near a nano-sized hole in a membrane filled with an electrolyte. When a strand of DNA is sent through this hole, the different bases that make up this molecule create unique variations in the electric current, which can be detected and analyzed. This allows researchers to know in great detail the structure of the molecule that just passed through the hole.

Optical mapping is a technique that creates a high-resolution map of a genome by severing a strand of DNA at specific sites with restriction enzymes, creating a unique fingerprint. That is, restriction enzymes digest specific sequences of DNA, separating the strand into various fragments, the distribution of which is inevitably different from other strands.

While neither of these methods is entirely new, the Salk Institute team combined them, creating a picture with an unprecedented level of detail. They employed a new nanopore long-read DNA sequencing technique, which made assembling the picture of a complete genome much easier because it extends the size of the data that can be collected, reducing the complexity of assembling the pieces. They also created optical genome maps by using the Bionano Genomics Irys system, which they demonstrated can achieve levels of resolution on the scale of a single molecule.

The team found that one insertion attempt could result in as many as seven unintended insertions or manipulations of the host’s genome. Some of these were up to ten times larger than intended, resulting in large segments of the host’s DNA being damaged or relocated. Furthermore, the incoming DNA was sometimes found to be out of place, cut in half, or out of sequence.

To GMO Or Not to GMO?

What these new results mean for the GMO debate is open to interpretation. Whatever side you might be on, this research demonstrates there’s more happening on the molecular scale than we originally thought.

Feeding the world’s future population is not only going to involve genetically modified foods, it’s going to require them. Current agricultural yields are not nearly high enough for the projected 9.7 billion people of 2050 to live on.

So what comes next to help determine whether GMOs are the way to go, and how to make sure they’re safe? More research.

Image Credit: science photo / Shutterstock.com

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• TAGS
• Biotechnology
• Food and Agriculture
• Future of Food

SCOTT SIMONSEN

Scott is currently doing research and editing for the UN. He's most interested in sustainable energy, global politics, and cryptocurrencies. In his spare time, he enjoys reading and being outdoors.

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