Are Brain Implants the Future of Treatment for Depression and Anxiety?
When she woke up after a procedure involving drilling small holes in her skull, a woman suffering from chronic depression reported feeling “euphoric”. The holes were made to fit the wires that connected her brain with a matchbox-sized electrical implant; this would deliver up to 300 short-lived electricity bursts per day to specific parts of her brain.
Over a year later, Sarah, 36, says the brain implant has turned her life around. A sense of alertness and energy have replaced suicidal thoughts and feelings of despair, which had persisted despite antidepressants and electroconvulsive therapy. Sarah is the first person to have received a brain implant to treat depression, a breakthrough that happened during an experimental study published recently in Nature Medicine.
“What we did was use deep-brain stimulation (DBS), a technique used in the treatment of epilepsy,” says Andrew Krystal, professor of psychiatry at University of California, San Francisco (UCSF), and one of the study’s researchers. DBS typically involves implanting electrodes into specific areas of the brain to reduce seizures not controlled with medication or to remove the part of the brain that causes the seizures. Instead of choosing and stimulating a single brain site though, the UCSF team took a different approach.
They first used 10 electrodes to map Sarah’s brain activity, a phase that lasted 10 days, during which they developed a neural biomarker, a specific pattern of brain activity that indicated the onset of depression symptoms (in Sarah, this was detected in her amygdala, an almondlike structure located near the base of the brain). But they also saw that delivering a tiny burst of electricity to the patient’s ventral striatum, an area of the brain that sits in the center, above and behind the ears, dramatically improved these symptoms. What they had to do was outfit Sara’s brain with a DBS-device programmed to propagate small waves of electricity to the ventral striatum only when it discerned the pattern.
“We are not trying to take away normal responses to the world. We are just trying to eliminate this one thing, which is depression, which impedes patients’ ability to function and deal with normal stuff.”
“It was a personalized treatment not only in where to stimulate, but when to stimulate,” Krystal says. Sarah’s depression translated to low amounts of energy, loss of pleasure and interest in life, and feelings of sluggishness. Those symptoms went away when scientists stimulated her ventral capsule area. When the same area was manipulated by electricity when Sarah’s symptoms “were not there” though, she was feeling more energetic, but this sudden flush of energy soon gave way to feelings of overstimulation and anxiety. “This is a very tangible illustration of why it's best to simulate only when you need it,” says Krystal.
We have the tendency to lump together depression symptoms, but, in reality, they are quite diverse; some people feel sad and lethargic, others stay up all night; some overeat, others don’t eat at all. “This happens because people have different underlying dysfunctions in different parts of their brain. Our approach is targeting the specific brain circuit that modulates different kinds of symptoms. Simply, where we stimulate depends on the specific set of problems a person has,” Krystal says. Such tailormade brain stimulation for patients with long-term, drug-resistant depression, which would be easy to use at home, could be transformative, the UCSF researcher concludes.
In the U.S., 12.7 percent of the population is on antidepressants. Almost exactly the same percentage of Australians–12.5–take similar drugs every day. With 13 percent of its population being on antidepressants, Iceland is the world’s highest antidepressant consumer. And quite away from Scandinavia, the Southern European country of Portugal is the world’s third strongest market for corresponding medication.
By 2020, nearly 15.5 million people had been consuming antidepressants for a time period exceeding five years. Between 40 and 60 percent of them saw improvements. “For those people, it was absolutely what they needed, whether that was increased serotonin, or increased norepinephrine or increased dopamine, ” says Frank Anderson, a psychiatrist who has been administering antidepressants in his private practice “for a long time”, and author of Transcending Trauma, a book about resolving complex and dissociative trauma.
Yet the UCSF study brings to the mental health field a specificity it has long lacked. “A lot of the traditional medications only really work on six neurotransmitters, when there are over 100 neurotransmitters in the brain,” Anderson says. Drugs are changing the chemistry of a single system in the brain, but brain stimulation is essentially changing the very architecture of the brain, says James Giordano, professor of neurology and biochemistry at Georgetown University Medical Center in Washington and a neuroethicist. It is a far more elegant approach to treating brain disorders, with the potential to prove a lifesaver for the 40 to 50 percent of patients who see no benefits at all with antidepressants, Giordano says. It is neurofeedback, on steroids, adds Anderson. But it comes with certain risks.
Even if the device generating the brain stimulation sits outside the skull and could be easily used at home, the whole process still involves neurosurgery. While the sophistication and precision of brain surgeries has significantly improved over the last years, says Giordano, they always carry risks, such as an allergic reaction to anesthesia, bleeding in the brain, infection at the wound site, blood clots, even coma. Non-invasive brain stimulation (NIBS), a technology currently being developed by the Defense Advanced Research Projects Agency (DARPA), could potentially tackle this. Patients could wear a cap, helmet, or visor that transmits electrical signals from the brain to a computer system and back, in a brain-computer interface that would not need surgery.
“This could counter the implantation of hardware into the brain and body, around which there is also a lot of public hesitance,” says Giordano, who is working on such techniques at DARPA.
Embedding a chip in your head is one of the finest examples of biohacking, an umbrella word for all the practices aimed at hacking one’s body and brain to enhance performance –a citizen do-it-yourself biology. It is also a word charged enough to set off a public backlash. Large segments of the population will simply refuse to allow that level of invasiveness in their heads, says Laura Cabrera, an associate professor of neuroethics at the Center for Neural Engineering, Department of Engineering Science and Mechanics at Penn State University. Cabrera urges caution when it comes to DBS’s potential.
“We've been using it for Parkinson's for over two decades, hoping that now that they get DBS, patients will get off medications. But people have continued taking their drugs, even increasing them,” she says. What the UCSF found is a proof of concept that DBS worked in one depressed person, but there’s a long way ahead until we can confidently say this finding is generalizable to a large group of patients. Besides, as a society, we are not there yet, says Cabrera. “Most people, at least in my research, say they don't want to have things in their brain,” she says. But what could really go wrong if we biohacked our own brains anyway?
In 2014, a man who had received a deep brain implant for a movement disorder started developing an affection for Johnny Cash’s music when he had previously been an avid country music fan. Many protested that the chip had tampered with his personality. Could sparking the brain with electricity generated by a chip outside it put an end to our individuality, messing with our musical preferences, unique quirks, our deeper sense of ego?
“What we found is that when you stimulate a region, you affect people’s moods, their energies,” says Krystal. You are neither changing their personality nor creating creatures of eternal happiness, he says. “’Being on a phone call would generally be a setting that would normally trigger symptoms of depression in me,’” Krystal reports his patient telling him. ‘I now know bad things happen, but am not affected by them in the same way. They don’t trigger the depression.’” Of the research, Krystal continues: “We are not trying to take away normal responses to the world. We are just trying to eliminate this one thing, which is depression, which impedes patients’ ability to function and deal with normal stuff.”
Yet even change itself shouldn't be seen as threatening, especially if the patient had probably desired it in the first place. “The intent of therapy in psychiatric disorders is to change the personality, because a psychiatric disorder by definition is a disorder of personality,” says Cabrera. A person in therapy wants to restore the lost sense of “normal self”. And as for this restoration altering your original taste in music, Cabrera says we are talking about rarities, extremely scarce phenomena that are possible with medication as well.
Maybe it is the allure of dystopian sci-fi films: people have a tendency to worry about dark forces that will spread malice across the world when the line between human and machine has blurred. Such mind-control through DBS would probably require a decent leap of logic with the tools science has--at least to this day. “This would require an understanding of the parameters of brain stimulation we still don't have,” says Cabrera. Still, brain implants are not fully corrupt-proof.
“Hackers could shut off the device or change the parameters of the patient's neurological function enhancing symptoms or creating harmful side-effects,” says Giordano.
There are risks, but also failsafe ways to tackle them, adds Anderson. “Just like medications are not permanent, we could ensure the implants are used for a specific period of time,” he says. And just like people go in for checkups when they are under medication, they could periodically get their personal brain implants checked to see if they have been altered or not, he continues. “It is what my research group refers to as biosecurity by design,” says Giordano. “It is important that we proactively design systems that cannot be corrupted.”
Two weeks after receiving the implant, Sarah scored 14 out of 54 on the Montgomery-Åsberg Depression Rating Scale, a ten-item questionnaire psychiatrists use to measure the severity of depressive episodes. She had initially scored 36. Today she scores under 10. She would have had to wait between four and eight weeks to see positive results had she taken the antidepressant road, says Krystal.
He and his team have enrolled two other patients in the trials and hope to add nine more. They already have some preliminary evidence that there's another place that works better in the brain of another patient, because that specific patient had been experiencing more anxiety as opposed to despondency. Almost certainly, we will have different biomarkers for different people, and brain stimulation will be tailored to a person’s unique situation, says Krystal. “Each brain is different, just like each face is different.”
Massive benefits of AI come with environmental and human costs. Can AI itself be part of the solution?
The recent explosion of generative artificial intelligence tools like ChatGPT and Dall-E enabled anyone with internet access to harness AI’s power for enhanced productivity, creativity, and problem-solving. With their ever-improving capabilities and expanding user base, these tools proved useful across disciplines, from the creative to the scientific.
But beneath the technological wonders of human-like conversation and creative expression lies a dirty secret—an alarming environmental and human cost. AI has an immense carbon footprint. Systems like ChatGPT take months to train in high-powered data centers, which demand huge amounts of electricity, much of which is still generated with fossil fuels, as well as water for cooling. “One of the reasons why Open AI needs investments [to the tune of] $10 billion from Microsoft is because they need to pay for all of that computation,” says Kentaro Toyama, a computer scientist at the University of Michigan. There’s also an ecological toll from mining rare minerals required for hardware and infrastructure. This environmental exploitation pollutes land, triggers natural disasters and causes large-scale human displacement. Finally, for data labeling needed to train and correct AI algorithms, the Big Data industry employs cheap and exploitative labor, often from the Global South.
Generative AI tools are based on large language models (LLMs), with most well-known being various versions of GPT. LLMs can perform natural language processing, including translating, summarizing and answering questions. They use artificial neural networks, called deep learning or machine learning. Inspired by the human brain, neural networks are made of millions of artificial neurons. “The basic principles of neural networks were known even in the 1950s and 1960s,” Toyama says, “but it’s only now, with the tremendous amount of compute power that we have, as well as huge amounts of data, that it’s become possible to train generative AI models.”
Though there aren’t any official figures about the power consumption or emissions from data centers, experts estimate that they use one percent of global electricity—more than entire countries.
In recent months, much attention has gone to the transformative benefits of these technologies. But it’s important to consider that these remarkable advances may come at a price.
AI’s carbon footprint
In their latest annual report, 2023 Landscape: Confronting Tech Power, the AI Now Institute, an independent policy research entity focusing on the concentration of power in the tech industry, says: “The constant push for scale in artificial intelligence has led Big Tech firms to develop hugely energy-intensive computational models that optimize for ‘accuracy’—through increasingly large datasets and computationally intensive model training—over more efficient and sustainable alternatives.”
Though there aren’t any official figures about the power consumption or emissions from data centers, experts estimate that they use one percent of global electricity—more than entire countries. In 2019, Emma Strubell, then a graduate researcher at the University of Massachusetts Amherst, estimated that training a single LLM resulted in over 280,000 kg in CO2 emissions—an equivalent of driving almost 1.2 million km in a gas-powered car. A couple of years later, David Patterson, a computer scientist from the University of California Berkeley, and colleagues, estimated GPT-3’s carbon footprint at over 550,000 kg of CO2 In 2022, the tech company Hugging Face, estimated the carbon footprint of its own language model, BLOOM, as 25,000 kg in CO2 emissions. (BLOOM’s footprint is lower because Hugging Face uses renewable energy, but it doubled when other life-cycle processes like hardware manufacturing and use were added.)
Luckily, despite the growing size and numbers of data centers, their increasing energy demands and emissions have not kept pace proportionately—thanks to renewable energy sources and energy-efficient hardware.
But emissions don’t tell the full story.
AI’s hidden human cost
“If historical colonialism annexed territories, their resources, and the bodies that worked on them, data colonialism’s power grab is both simpler and deeper: the capture and control of human life itself through appropriating the data that can be extracted from it for profit.” So write Nick Couldry and Ulises Mejias, authors of the book The Costs of Connection.
The energy requirements, hardware manufacture and the cheap human labor behind AI systems disproportionately affect marginalized communities.
Technologies we use daily inexorably gather our data. “Human experience, potentially every layer and aspect of it, is becoming the target of profitable extraction,” Couldry and Meijas say. This feeds data capitalism, the economic model built on the extraction and commodification of data. While we are being dispossessed of our data, Big Tech commodifies it for their own benefit. This results in consolidation of power structures that reinforce existing race, gender, class and other inequalities.
“The political economy around tech and tech companies, and the development in advances in AI contribute to massive displacement and pollution, and significantly changes the built environment,” says technologist and activist Yeshi Milner, who founded Data For Black Lives (D4BL) to create measurable change in Black people’s lives using data. The energy requirements, hardware manufacture and the cheap human labor behind AI systems disproportionately affect marginalized communities.
AI’s recent explosive growth spiked the demand for manual, behind-the-scenes tasks, creating an industry described by Mary Gray and Siddharth Suri as “ghost work” in their book. This invisible human workforce that lies behind the “magic” of AI, is overworked and underpaid, and very often based in the Global South. For example, workers in Kenya who made less than $2 an hour, were the behind the mechanism that trained ChatGPT to properly talk about violence, hate speech and sexual abuse. And, according to an article in Analytics India Magazine, in some cases these workers may not have been paid at all, a case for wage theft. An exposé by the Washington Post describes “digital sweatshops” in the Philippines, where thousands of workers experience low wages, delays in payment, and wage theft by Remotasks, a platform owned by Scale AI, a $7 billion dollar American startup. Rights groups and labor researchers have flagged Scale AI as one company that flouts basic labor standards for workers abroad.
It is possible to draw a parallel with chattel slavery—the most significant economic event that continues to shape the modern world—to see the business structures that allow for the massive exploitation of people, Milner says. Back then, people got chocolate, sugar, cotton; today, they get generative AI tools. “What’s invisible through distance—because [tech companies] also control what we see—is the massive exploitation,” Milner says.
“At Data for Black Lives, we are less concerned with whether AI will become human…[W]e’re more concerned with the growing power of AI to decide who’s human and who’s not,” Milner says. As a decision-making force, AI becomes a “justifying factor for policies, practices, rules that not just reinforce, but are currently turning the clock back generations years on people’s civil and human rights.”
Ironically, AI plays an important role in mitigating its own harms—by plowing through mountains of data about weather changes, extreme weather events and human displacement.
Nuria Oliver, a computer scientist, and co-founder and vice-president of the European Laboratory of Learning and Intelligent Systems (ELLIS), says that instead of focusing on the hypothetical existential risks of today’s AI, we should talk about its real, tangible risks.
“Because AI is a transverse discipline that you can apply to any field [from education, journalism, medicine, to transportation and energy], it has a transformative power…and an exponential impact,” she says.
AI's accountability
“At the core of what we were arguing about data capitalism [is] a call to action to abolish Big Data,” says Milner. “Not to abolish data itself, but the power structures that concentrate [its] power in the hands of very few actors.”
A comprehensive AI Act currently negotiated in the European Parliament aims to rein Big Tech in. It plans to introduce a rating of AI tools based on the harms caused to humans, while being as technology-neutral as possible. That sets standards for safe, transparent, traceable, non-discriminatory, and environmentally friendly AI systems, overseen by people, not automation. The regulations also ask for transparency in the content used to train generative AIs, particularly with copyrighted data, and also disclosing that the content is AI-generated. “This European regulation is setting the example for other regions and countries in the world,” Oliver says. But, she adds, such transparencies are hard to achieve.
Google, for example, recently updated its privacy policy to say that anything on the public internet will be used as training data. “Obviously, technology companies have to respond to their economic interests, so their decisions are not necessarily going to be the best for society and for the environment,” Oliver says. “And that’s why we need strong research institutions and civil society institutions to push for actions.” ELLIS also advocates for data centers to be built in locations where the energy can be produced sustainably.
Ironically, AI plays an important role in mitigating its own harms—by plowing through mountains of data about weather changes, extreme weather events and human displacement. “The only way to make sense of this data is using machine learning methods,” Oliver says.
Milner believes that the best way to expose AI-caused systemic inequalities is through people's stories. “In these last five years, so much of our work [at D4BL] has been creating new datasets, new data tools, bringing the data to life. To show the harms but also to continue to reclaim it as a tool for social change and for political change.” This change, she adds, will depend on whose hands it is in.
DNA gathered from animal poop helps protect wildlife
On the savannah near the Botswana-Zimbabwe border, elephants grazed contentedly. Nearby, postdoctoral researcher Alida de Flamingh watched and waited. As the herd moved away, she went into action, collecting samples of elephant dung that she and other wildlife conservationists would study in the months to come. She pulled on gloves, took a swab, and ran it all over the still-warm, round blob of elephant poop.
Sequencing DNA from fecal matter is a safe, non-invasive way to track and ultimately help protect over 42,000 species currently threatened by extinction. Scientists are using this DNA to gain insights into wildlife health, genetic diversity and even the broader environment. Applied to elephants, chimpanzees, toucans and other species, it helps scientists determine the genetic diversity of groups and linkages with other groups. Such analysis can show changes in rates of inbreeding. Populations with greater genetic diversity adapt better to changes and environmental stressors than those with less diversity, thus reducing their risks of extinction, explains de Flamingh, a postdoctoral researcher at the University of Illinois Urbana-Champaign.
Analyzing fecal DNA also reveals information about an animal’s diet and health, and even nearby flora that is eaten. That information gives scientists broader insights into the ecosystem, and the findings are informing conservation initiatives. Examples include restoring or maintaining genetic connections among groups, ensuring access to certain foraging areas or increasing diversity in captive breeding programs.
Approximately 27 percent of mammals and 28 percent of all assessed species are close to dying out. The IUCN Red List of threatened species, simply called the Red List, is the world’s most comprehensive record of animals’ risk of extinction status. The more information scientists gather, the better their chances of reducing those risks. In Africa, populations of vertebrates declined 69 percent between 1970 and 2022, according to the World Wildlife Fund (WWF).
“We put on sterile gloves and use a sterile swab to collect wet mucus and materials from the outside of the dung ball,” says Alida de Flamingh, a postdoctoral researcher at the University of Illinois Urbana-Champaign.
“When people talk about species, they often talk about ecosystems, but they often overlook genetic diversity,” says Christina Hvilsom, senior geneticist at the Copenhagen Zoo. “It’s easy to count (individuals) to assess whether the population size is increasing or decreasing, but diversity isn’t something we can see with our bare eyes. Yet, it’s actually the foundation for the species and populations.” DNA analysis can provide this critical information.
Assessing elephants’ health
“Africa’s elephant populations are facing unprecedented threats,” says de Flamingh, the postdoc, who has studied them since 2009. Challenges include ivory poaching, habitat destruction and smaller, more fragmented habitats that result in smaller mating pools with less genetic diversity. Additionally, de Flamingh studies the microbial communities living on and in elephants – their microbiomes – looking for parasites or dangerous microbes.
Approximately 415,000 elephants inhabit Africa today, but de Flamingh says the number would be four times higher without these challenges. The IUCN Red List reports African savannah elephants are endangered and African forest elephants are critically endangered. Elephants support ecosystem biodiversity by clearing paths that help other species travel. Their very footprints create small puddles that can host smaller organisms such as tadpoles. Elephants are often described as ecosystems’ engineers, so if they disappear, the rest of the ecosystem will suffer too.
There’s a process to collecting elephant feces. “We put on sterile gloves (which we change for each sample) and use a sterile swab to collect wet mucus and materials from the outside of the dung ball,” says de Flamingh. They rub a sample about the size of a U.S. quarter onto a paper card embedded with DNA preservation technology. Each card is air dried and stored in a packet of desiccant to prevent mold growth. This way, samples can be stored at room temperature indefinitely without the DNA degrading.
Earlier methods required collecting dung in bags, which needed either refrigeration or the addition of preservatives, or the riskier alternative of tranquilizing the animals before approaching them to draw blood samples. The ability to collect and sequence the DNA made things much easier and safer.
“Our research provides a way to assess elephant health without having to physically interact with elephants,” de Flamingh emphasizes. “We also keep track of the GPS coordinates of each sample so that we can create a map of the sampling locations,” she adds. That helps researchers correlate elephants’ health with geographic areas and their conditions.
Although de Flamingh works with elephants in the wild, the contributions of zoos in the United States and collaborations in South Africa (notably the late Professor Rudi van Aarde and the Conservation Ecology Research Unit at the University of Pretoria) were key in studying this method to ensure it worked, she points out.
Protecting chimpanzees
Genetic work with chimpanzees began about a decade ago. Hvilsom and her group at the Copenhagen Zoo analyzed DNA from nearly 1,000 fecal samples collected between 2003 and 2018 by a team of international researchers. The goal was to assess the status of the West African subspecies, which is critically endangered after rapid population declines. Of the four subspecies of chimpanzees, the West African subspecies is considered the most at-risk.
In total, the WWF estimates the numbers of chimpanzees inhabiting Africa’s forests and savannah woodlands at between 173,000 and 300,000. Poaching, disease and human-caused changes to their lands are their major risks.
By analyzing genetics obtained from fecal samples, Hvilsom estimated the chimpanzees’ population, ascertained their family relationships and mapped their migration routes.
“One of the threats is mining near the Nimba Mountains in Guinea,” a stronghold for the West African subspecies, Hvilsom says. The Nimba Mountains are a UNESCO World Heritage Site, but they are rich in iron ore, which is used to make the steel that is vital to the Asian construction boom. As she and colleagues wrote in a recent paper, “Many extractive industries are currently developing projects in chimpanzee habitat.”
Analyzing DNA allows researchers to identify individual chimpanzees more accurately than simply observing them, she says. Normally, field researchers would install cameras and manually inspect each picture to determine how many chimpanzees were in an area. But, Hvilsom says, “That’s very tricky. Chimpanzees move a lot and are fast, so it’s difficult to get clear pictures. Often, they find and destroy the cameras. Also, they live in large areas, so you need a lot of cameras.”
By analyzing genetics obtained from fecal samples, Hvilsom estimated the chimpanzees’ population, ascertained their family relationships and mapped their migration routes based upon DNA comparisons with other chimpanzee groups. The mining companies and builders are using this information to locate future roads where they won’t disrupt migration – a more effective solution than trying to build artificial corridors for wildlife.
“The current route cuts off communities of chimpanzees,” Hvilsom elaborates. That effectively prevents young adult chimps from joining other groups when the time comes, eventually reducing the currently-high levels of genetic diversity.
“The mining company helped pay for the genetics work,” Hvilsom says, “as part of its obligation to assess and monitor biodiversity and the effect of the mining in the area.”
Of 50 toucan subspecies, 11 are threatened or near-threatened with extinction because of deforestation and poaching.
Identifying toucan families
Feces aren't the only substance researchers draw DNA samples from. Jeffrey Coleman, a Ph.D. candidate at the University of Texas at Austin relies on blood tests for studying the genetic diversity of toucans---birds species native to Central America and nearby regions. They live in the jungles, where they hop among branches, snip fruit from trees, toss it in the air and catch it with their large beaks. “Toucans are beautiful, charismatic birds that are really important to the ecosystem,” says Coleman.
Of their 50 subspecies, 11 are threatened or near-threatened with extinction because of deforestation and poaching. “When people see these aesthetically pleasing birds, they’re motivated to care about conservation practices,” he points out.
Coleman works with the Dallas World Aquarium and its partner zoos to analyze DNA from blood draws, using it to identify which toucans are related and how closely. His goal is to use science to improve the genetic diversity among toucan offspring.
Specifically, he’s looking at sections of the genome of captive birds in which the nucleotides repeat multiple times, such as AGATAGATAGAT. Called microsatellites, these consecutively-repeating sections can be passed from parents to children, helping scientists identify parent-child and sibling-sibling relationships. “That allows you to make strategic decisions about how to pair (captive) individuals for mating...to avoid inbreeding,” Coleman says.
Jeffrey Coleman is studying the microsatellites inside the toucan genomes.
Courtesy Jeffrey Coleman
The alternative is to use a type of analysis that looks for a single DNA building block – a nucleotide – that differs in a given sequence. Called single nucleotide polymorphisms (SNPs, pronounced “snips”), they are very common and very accurate. Coleman says they are better than microsatellites for some uses. But scientists have already developed a large body of microsatellite data from multiple species, so microsatellites can shed more insights on relations.
Regardless of whether conservation programs use SNPs or microsatellites to guide captive breeding efforts, the goal is to help them build genetically diverse populations that eventually may supplement endangered populations in the wild. “The hope is that the ecosystem will be stable enough and that the populations (once reintroduced into the wild) will be able to survive and thrive,” says Coleman. History knows some good examples of captive breeding success.
The California condor, which had a total population of 27 in 1987, when the last wild birds were captured, is one of them. A captive breeding program boosted their numbers to 561 by the end of 2022. Of those, 347 of those are in the wild, according to the National Park Service.
Conservationists hope that their work on animals’ genetic diversity will help preserve and restore endangered species in captivity and the wild. DNA analysis is crucial to both types of efforts. The ability to apply genome sequencing to wildlife conservation brings a new level of accuracy that helps protect species and gives fresh insights that observation alone can’t provide.
“A lot of species are threatened,” Coleman says. “I hope this research will be a resource people can use to get more information on longer-term genealogies and different populations.”