These technologies may help more animals and plants survive climate change
This article originally appeared in One Health/One Planet, a single-issue magazine that explores how climate change and other environmental shifts are making us more vulnerable to infectious diseases by land and by sea - and how scientists are working on solutions.
Along the west coast of South Florida and the Keys, Florida Bay is a nursery for young Caribbean spiny lobsters, a favorite local delicacy. Growing up in small shallow basins, they are especially vulnerable to warmer, more saline water. Climate change has brought tidal floods, bleached coral reefs and toxic algal blooms to the state, and since the 1990s, the population of the Caribbean spiny lobster has dropped some 20 percent, diminishing an important food for snapper, grouper, and herons, as well as people. In 1999, marine ecologist Donald Behringer discovered the first known virus among lobsters, Panulirus argus virus—about a quarter of juveniles die from it before they mature.
“When the water is warm PaV1 progresses much more quickly,” says Behringer, who is based at the Emerging Pathogens Institute at the University of Florida in Gainesville.
Caribbean spiny lobsters are only one example of many species that are struggling in the era of climate change, both at sea and on land. As the oceans heat up, absorbing greenhouse gases and growing more acidic, marine diseases are emerging at an accelerated rate. Marine creatures are migrating to new places, and carrying pathogens with them. The latest grim report in the journal Science, states that if global warming continues at the current rate, the extinction of marine species will rival the Permian–Triassic extinction, sometimes called the “Great Dying,” when volcanoes poisoned the air and wiped out as much as 90 percent of all marine life 252 million years ago.
Similarly, on land, climate change has exposed wildlife, trees and crops to new or more virulent pathogens. Warming environments allow fungi, bacteria, viruses and infectious worms to proliferate in new species and locations or become more virulent. One paper modeling records of nearly 1,400 wildlife species projects that parasites will double by 2070 in the far north and in high-altitude places. Right now, we are seeing the effects most clearly on the fringes—along the coasts, up north and high in the mountains—but as the climate continues changing, the ripples will reach everywhere.
Few species are spared
On the Hawaiian Islands, mosquitoes are killing more songbirds. The dusky gray akikiki of Kauai and the chartreuse-yellow kiwikiu of Maui could vanish in two years, under assault from mosquitoes bearing avian malaria, according to a University of Hawaiʻi 2022 report. Previously, the birds could escape infection by roosting high in the cold mountains, where the pests couldn’t thrive, but climate change expanded the range of the mosquito and narrowed theirs.
Likewise, as more midge larvae survive over warm winters and breed better during drier summers, they bite more white-tailed deer, spreading often-fatal epizootic hemorrhagic disease. Especially in northern regions of the globe, climate change brings the threat of midges carrying blue tongue disease, a virus, to sheep and other animals. Tick-borne diseases like encephalitis and Lyme disease may become a greater threat to animals and perhaps humans.
"If you put all your eggs in one basket and then a pest comes a long, then you are more vulnerable to those risks," says Mehroad Ehsani, managing director of the food initiative in Africa for the Rockefeller Foundation. "Research is needed on resilient, climate smart, regenerative agriculture."
In the “thermal mismatch” theory of wildlife disease, cold-adapted species are at greater risk when their habitats warm, and warm-adapted species suffer when their habitats cool. Mammals can adjust their body temperature to adapt to some extent. Amphibians, fish and insects that cannot regulate body temperatures may be at greater risk. Many scientists see amphibians, especially, as canaries in the coalmine, signaling toxicity.
Early melting ice can foster disease. Climate models predict that the spring thaw will come ever-earlier in the lakes of the French Pyrenees, for instance, which traditionally stayed frozen for up to half the year. The tadpoles of the midwife toad live under the ice, where they are often infected with amphibian chytrid fungus. When a seven-year study tracked the virus in three species of amphibians in Pyrenees’s Lac Arlet, the research team found that, the earlier the spring thaw arrived, the more infection rates rose in common toads— , while remaining high among the midwife toads. But the team made another sad discovery: with early thaws, the common frog, which was thought to be free of the disease in Europe, also became infected with the fungus and died in large numbers.
Changing habitats affect animal behavior. Normally, spiny lobsters rely on chemical cues to avoid predators and sick lobsters. New conditions may be hampering their ability to “social distance”—which may help PaV1 spread, Behringer’s research suggests. Migration brings other risks. In April 2022, an international team led by scientists at Georgetown University announced the first comprehensive overview, published in the journal Nature, of how wild mammals under pressure from a changing climate may mingle with new populations and species—giving viruses a deadly opportunity to jump between hosts. Droughts, for example, will push animals to congregate at the few places where water remains.
Plants face threats also. At the timberline of the cold, windy, snowy mountains of the U.S. west, whitebark pine forests are facing a double threat, from white pine blister rust, a fungal disease, and multiplying pine beetles. “If we do nothing, we will lose the species,” says Robert Keane, a research ecologist for the U.S. Forest Service, based in Missoula, Montana. That would be a huge shift, he explains: “It’s a keystone species. There are over 110 animals that depend on it, many insects, and hundreds of plants.” In the past, beetle larvae would take two years to complete their lifecycle, and many died in frost. “With climate change, we're seeing more and more beetles survive, and sometimes the beetle can complete its lifecycle in one year,” he says.
Quintessential crops are under threat too
As some pathogens move north and new ones develop, they pose novel threats to the crops humans depend upon. This is already happening to wheat, coffee, bananas and maize.
Breeding against wheat stem rust, a fungus long linked to famine, was a key success in the mid-20th century Green Revolution, which brought higher yields around the world. In 2013, wheat stem rust reemerged in Germany after decades of absence. It ravaged both bread and durum wheat in Sicily in 2016 and has spread as far as England and Ireland. Wheat blast disease, caused by a different fungus, appeared in Bangladesh in 2016, and spread to India, the world’s second largest producer of wheat.
Insects, moths, worms, and coffee leaf rust—a fungus now found in all coffee-growing countries—threaten the livelihoods of millions of people who grow coffee, as well as everybody’s cup of joe. More heat, more intense rain, and higher humidity have allowed coffee leaf rust to cycle more rapidly. It has grown exponentially, overcoming the agricultural chemicals that once kept it under control.
To identify new diseases and fine-tune crops for resistance, scientists are increasingly relying on genomic tools.
Tar spot, a fungus native to Latin America that can cut corn production in half, has emerged in highland areas of Central Mexico and parts of the U.S.. Meanwhile, maize lethal necrosis disease has spread to multiple countries in Africa, notes Mehrdad Ehsani, Managing Director for the Food Initiative in Africa of the Rockefeller Foundation. The Cavendish banana, which most people eat today, was bred to be resistant to the fungus Panama 1. Now a new fungus, Panama 4, has emerged on every continent–including areas of Latin America that rely on the Cavendish for their income, reported a recent story in the Guardian. New threats are poised to emerge. Potato growers in the Andes Mountains have been shielded from disease because of colder weather at high altitude, but temperature fluxes and warming weather are expected to make this crop vulnerable to potato blight, found plant pathologist Erica Goss, at the Emerging Pathogens Institute.
Science seeks solutions
To protect food supplies in the era of climate change, scientists are calling for integrated global surveillance systems for crop disease outbreaks. “You can imagine that a new crop variety that is drought-tolerant could be susceptible to a pathogen that previous varieties had some resistance against,” Goss says. “Or a country suffers from a calamitous weather event, has to import seed from another country, and that seed is contaminated with a new pathogen or more virulent strain of an existing pathogen.” Researchers at the John Innes Center in Norwich and Aarhus University in Denmark have established ways to monitor wheat rust, for example.
Better data is essential, for both plants and animals. Historically, models of climate change predicted effects on plant pathogens based on mean temperatures, and scientists tracked plant responses to constant temperatures, explains Goss. “There is a need for more realistic tests of the effects of changing temperatures, particularly changes in daily high and low temperatures on pathogens,” she says.
To identify new diseases and fine-tune crops for resistance, scientists are increasingly relying on genomic tools. Goss suggests factoring the impact of climate change into those tools. Genomic efforts to select soft red winter wheat that is resistant to Fusarium head blight (FHB), a fungus that plagues farmers in the Southeastern U.S., have had early success. But temperature changes introduce a new factor.
A fundamental solution would be to bring back diversification in farming, says Ehsani. Thousands of plant species are edible, yet we rely on a handful. Wild relatives of domesticated crops are a store of possibly useful genes that may confer resistance to disease. The same is true for livestock. “If you put all your eggs in one basket and then a pest comes along, then you are more vulnerable to those risks. Research is needed on resilient, climate smart, regenerative agriculture,” Ehsani says.
Jonathan Sleeman, director of the U.S. Geological Survey National Wildlife Health Center, has called for data on wildlife health to be systematically collected and integrated with climate and other variables because more comprehensive data will result in better preventive action. “We have focused on detecting diseases,” he says, but a more holistic strategy would apply human public health concepts to assuring animal wellbeing. (For example, one study asked experts to draw a diagram of relationships of all the factors affecting the health of a particular group of caribou.) We must not take the health of plants and animals for granted, because their vulnerability inevitably affects us too, Sleeman says. “We need to improve the resilience of wildlife populations so they can withstand the impact of climate change.”
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.”