The Nation’s Science and Health Agencies Face a Credibility Crisis: Can Their Reputations Be Restored?
This article is part of the magazine, "The Future of Science In America: The Election Issue," co-published by LeapsMag, the Aspen Institute Science & Society Program, and GOOD.
It didn't have to be this way. More than 200,000 Americans dead, seven million infected, with numbers continuing to climb, an economy in shambles with millions out of work, hundreds of thousands of small businesses crushed with most of the country still under lockdown. And all with no end in sight. This catastrophic result is due in large part to the willful disregard of scientific evidence and of muzzling policy experts by the Trump White House, which has spent its entire time in office attacking science.
One of the few weapons we had to combat the spread of Covid-19—wearing face masks—has been politicized by the President, who transformed this simple public health precaution into a first amendment issue to rally his base. Dedicated public health officials like Dr. Anthony Fauci, the highly respected director of the National Institute of Allergies and Infectious Diseases, have received death threats, which have prompted many of them around the country to resign.
Over the summer, the Trump White House pressured the Centers for Disease Control, which is normally in charge of fighting epidemics, to downplay COVID risks among young people and encourage schools to reopen. And in late September, the CDC was forced to pull federal teams who were going door-to-door doing testing surveys in Minnesota because of multiple incidents of threats and abuse. This list goes on and on.
Still, while the Trump administration's COVID failures are the most visible—and deadly—the nation's entire federal science infrastructure has been undermined in ways large and small.
The White House has steadily slashed monies for science—the 2021 budget cuts funding by 10–30% or more for crucial agencies like National Oceanic and Atmospheric Administration (NOAA) and the Environmental Protection Agency (EPA)—and has gutted health and science agencies across the board, including key agencies of the Department of Energy and the Interior, especially in divisions that deal with issues they oppose ideologically like climate change.
Even farmers can't get reliable information about how climate change affects planting seasons because the White House moved the entire staff at the U.S. Department of Agriculture agency who does this research, relocating them from Maryland to Kansas City, Missouri. Many of these scientists couldn't uproot their families and sell their homes, so the division has had to pretty much start over from scratch with a skeleton crew.
More than 1,600 federal scientists left government in the first two years of the Trump Administration, according to data compiled by the Washington Post, and one-fifth of top positions in science are vacant, depriving agencies of the expertise they need to fulfill their vital functions. Industry executives and lobbyists have been installed as gatekeepers—HHS Secretary Alex Azar was previously president of Eli Lilly, and three climate change deniers were appointed to key posts at the National Oceanic and Atmospheric Administration, to cite just a couple of examples. Trump-appointed officials have sidelined, bullied, or even vilified those who dare to speak out, which chills the rigorous debate that is the essential to sound, independent science.
"The CDC needs to be able to speak regularly to the American people to explain what it knows and how it knows it."
Linda Birnbaum knows firsthand what it's like to become a target. The microbiologist recently retired after more than a decade as the director of the National Institute of Environmental Health Sciences, which is the world's largest environmental health organization and the greatest funder of environmental health and toxicology research, a position that often put her agency at odds with the chemical and fossil fuel industry. There was an attempt to get her fired, she says, "because I had the nerve to write that science should be used in making policy. The chemical industry really went after me, and my last two years were not so much fun under this administration. I'd like to believe it was because I was making a difference—if I wasn't, they wouldn't care."
Little wonder that morale at federal agencies is low. "We're very frustrated," says Dr. William Schaffner, a veteran infectious disease specialist and a professor of medicine at the Vanderbilt University School of Medicine in Nashville. "My colleagues within these agencies, the CDC rank and file, are keeping their heads down doing the best they can, and they hope to weather this storm."
The cruel irony is that the United States was once a beacon of scientific innovation. In the heady post World War II years, while Europe lay in ruins, the successful development of penicillin and the atomic bomb—which Americans believed helped vanquish the Axis powers—unleashed a gusher of public money into research, launching an unprecedented era of achievement in American science. Scientists conquered polio, deciphered the genetic code, harnessed the power of the atom, invented lasers, transistors, microchips and computers, sent missions beyond Mars, and landed men on the moon. A once-inconsequential hygiene laboratory was transformed into the colossus the National Institutes of Health has become, which remains today the world's flagship medical research center, unrivaled in size and scope.
At the same time, a tiny public health agency headquartered in Atlanta, which had been in charge of eradicating the malaria outbreaks that plagued impoverished rural areas in the Deep South until the late 1940s, evolved into the Centers for Disease Control and Prevention. The CDC became the world's leader in fighting disease outbreaks, and the agency's crack team of epidemiologists—members of the vaunted Epidemic Intelligence Service—were routinely dispatched to battle global outbreaks of contagions such as Ebola and malaria and help lead the vaccination campaigns to eradicate killers like polio and small pox that have saved millions of lives.
What will it take to rebuild our federal science infrastructure and restore not only the public's confidence but the respect of the world's scientific community? There are some hopeful signs that there is pushback against the current national leadership, and non-profit watchdog groups like the Union of Concerned Scientists have mapped out comprehensive game plans to restore public trust and the integrity of science.
These include methods of protecting science from political manipulation; restoring the oversight role of independent federal advisory committees, whose numbers were decimated by recent executive orders; strengthening scientific agencies that have been starved by budget cuts and staff attrition; and supporting whistleblower protections and allowing scientists to do their jobs without political meddling to restore integrity to the process. And this isn't just a problem at the CDC. A survey of 1,600 EPA scientists revealed that more than half had been victims of political interference and were pressured to skew their findings, according to research released in April by the Union of Concerned Scientists.
"Federal agencies are staffed by dedicated professionals," says Andrew Rosenberg, director of the Center for Science and Democracy at the Union of Concerned Scientists and a former fisheries biologist for NOAA. "Their job is not to serve the president but the public interest. Inspector generals are continuing to do what they're supposed to, but their findings are not being adhered to. But they need to hold agencies accountable. If an agency has not met its mission or engaged in misconduct, there needs to be real consequences."
On other fronts, last month nine vaccine makers, including Sanofi, Pfizer, and AstraZeneca, took the unprecedented stop of announcing that their COVID-19 vaccines would be thoroughly vetted before they were released. In their implicit refusal to bow to political pressure from the White House to have a vaccine available before the election, their goal was to restore public confidence in vaccine safety, and ensure that enough Americans would consent to have the shot when it was eventually approved so that we'd reach the long-sought holy grail of herd immunity.
"That's why it's really important that all of the decisions need to be made with complete transparency and not taking shortcuts," says Dr. Tom Frieden, president and CEO of Resolve to Save Lives and former director of the CDC during the H1N1, Ebola, and Zika emergencies. "A vaccine is our most important tool, and we can't break that tool by meddling in the science approval process."
In late September, Senate Democrats introduced a new bill to halt political meddling in public health initiatives by the White House. Called Science and Transparency Over Politics Act (STOP), the legislation would create an independent task force to investigate political interference in the federal response to the coronavirus pandemic. "The Trump administration is still pushing the president's political priorities rather than following the science to defeat this virus," Senate Minority Leader Chuck Schumer said in a press release.
To effectively bring the pandemic under control and restore public confidence, the CDC must assume the leadership role in fighting COVID-19. During previous outbreaks, the top federal infectious disease specialists like Drs. Fauci and Frieden would have daily press briefings, and these need to resume. "The CDC needs to be able to speak regularly to the American people to explain what it knows and how it knows it," says Frieden, who cautions that a vaccine won't be a magic bullet. "There is no one thing that is going to make this virus go away. We need to continue to limit indoor exposures, wear masks, and do strategic testing, isolation, and quarantine. We need a comprehensive approach, and not just a vaccine."
We must also appoint competent and trustworthy leaders, says Rosenberg of the Union of Concerned Scientists. Top posts in too many science agencies are now filled by former industry executives and lobbyists with a built-in bias, as well as people lacking relevant scientific experience, many of whom were never properly vetted because of the current administration's penchant for bypassing Congress and appointing "acting" officials. "We've got great career people who have hung in, but in so much of the federal government, they just put in 'acting' people," says Linda Birnbaum. "They need to bring in better, qualified senior leadership."
Open positions need to be filled, too. Federal science agencies have been seriously crippled by staffing attrition, and the Trump Administration instituted a hiring freeze when it first came in. Staffing levels remain at least ten percent down from previous levels, says Birnbaum and in many agencies, like the EPA, "everything has come to a screeching halt, making it difficult to get anything done."
But in the meantime, the critical first step may be at the ballot box in November. Even Scientific American, the esteemed consumer science publication, for the first time in its 175-year history felt "compelled" to endorse a presidential candidate, Joe Biden, because of the enormity of the damage they say Donald Trump has inflicted on scientists, their legal protections, and on the federal science agencies.
"If the current administration continues, the national political leadership will be emboldened and will be even more assertive of their executive prerogatives and less concerned about traditional niceties, leading to further erosion of the activities of many federal agencies," says Vanderbilt's William Schaffner. "But the reality is, if the team is losing, you change the coach. Then agencies really have to buckle down because it will take some time to restore their hard-earned reputations."
[Editor's Note: To read other articles in this special magazine issue, visit the beautifully designed e-reader version.]
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.”