Some companies claim remote work hurts wellbeing. Research shows the opposite.
Many leaders at top companies are trying to get workers to return to the office. They say remote and hybrid work are bad for their employees’ mental well-being and lead to a sense of social isolation, meaninglessness, and lack of work-life boundaries, so we should just all go back to office-centric work.
One example is Google, where the company’s leadership is defending its requirement of mostly in-office work for all staff as necessary to protect social capital, meaning people’s connections to and trust in one another. That’s despite a survey of over 1,000 Google employees showing that two-thirds feel unhappy about being forced to work in the office three days per week. In internal meetings and public letters, many have threatened to leave, and some are already quitting to go to other companies with more flexible options.
Last month, GM rolled out a policy similar to Google’s, but had to backtrack because of intense employee opposition. The same is happening in some places outside of the U.S. For instance, three-fifths of all Chinese employers are refusing to offer permanent remote work options, according to a survey this year from The Paper.
For their claims that remote work hurts well-being, some of these office-centric traditionalists cite a number of prominent articles. For example, Arthur Brooks claimed in an essay that “aggravation from commuting is no match for the misery of loneliness, which can lead to depression, substance abuse, sedentary behavior, and relationship damage, among other ills.” An article in Forbes reported that over two-thirds of employees who work from home at least part of the time had trouble getting away from work at the end of the day. And Fast Company has a piece about how remote work can “exacerbate existing mental health issues” like depression and anxiety.
For his part, author Malcolm Gladwell has also championed a swift return to the office, saying there is a “core psychological truth, which is we want you to have a feeling of belonging and to feel necessary…I know it’s a hassle to come into the office, but if you’re just sitting in your pajamas in your bedroom, is that the work life you want to live?”
These arguments may sound logical to some, but they fly in the face of research and my own experience as a behavioral scientist and as a consultant to Fortune 500 companies. In these roles, I have seen the pitfalls of in-person work, which can be just as problematic, if not more so. Remote work is not without its own challenges, but I have helped 21 companies implement a series of simple steps to address them.
Research finds that remote work is actually better for you
The trouble with the articles described above - and claims by traditionalist business leaders and gurus - stems from a sneaky misdirection. They decry the negative impact of remote and hybrid work for wellbeing. Yet they gloss over the damage to wellbeing caused by the alternative, namely office-centric work.
It’s like comparing remote and hybrid work to a state of leisure. Sure, people would feel less isolated if they could hang out and have a beer with their friends instead of working. They could take care of their existing mental health issues if they could visit a therapist. But that’s not in the cards. What’s in the cards is office-centric work. That means the frustration of a long commute to the office, sitting at your desk in an often-uncomfortable and oppressive open office for at least 8 hours, having a sad desk lunch and unhealthy snacks, sometimes at an insanely expensive cost and, for making it through this series of insults, you’re rewarded with more frustration while commuting back home.
In a 2022 survey, the vast majority of respondents felt that working remotely improved their work-life balance. Much of that improvement stemmed from saving time due to not needing to commute and having a more flexible schedule.
So what happens when we compare apples to apples? That’s when we need to hear from the horse’s mouth: namely, surveys of employees themselves, who experienced both in-office work before the pandemic, and hybrid and remote work after COVID struck.
Consider a 2022 survey by Cisco of 28,000 full-time employees around the globe. Nearly 80 percent of respondents say that remote and hybrid work improved their overall well-being: that applies to 83 percent of Millennials, 82 percent of Gen Z, 76 percent of Gen Z, and 66 percent of Baby Boomers. The vast majority of respondents felt that working remotely improved their work-life balance.
Much of that improvement stemmed from saving time due to not needing to commute and having a more flexible schedule: 90 percent saved 4 to 8 hours or more per week. What did they do with that extra time? The top choice for almost half was spending more time with family, friends and pets, which certainly helped address the problem of isolation from the workplace. Indeed, three-quarters of them report that working from home improved their family relationships, and 51 percent strengthened their friendships. Twenty percent used the freed up hours for self-care.
Of the small number who report their work-life balance has not improved or even worsened, the number one reason is the difficulty of disconnecting from work, but 82 percent report that working from anywhere has made them happier. Over half say that remote work decreased their stress levels.
Other surveys back up Cisco’s findings. For example, a 2022 Future Forum survey compared knowledge workers who worked full-time in the office, in a hybrid modality, and fully remote. It found that full-time in-office workers felt the least satisfied with work-life balance, hybrid workers were in the middle, and fully remote workers felt most satisfied. The same distribution applied to questions about stress and anxiety. A mental health website called Tracking Happiness found in a 2022 survey of over 12,000 workers that fully remote employees report a happiness level about 20 percent greater than office-centric ones. Another survey by CNBC in June found that fully remote workers are more often very satisfied with their jobs than workers who are fully in-person.
Academic peer-reviewed research provides further support. Consider a 2022 study published in the International Journal of Environmental Research and Public Health of bank workers who worked on the same tasks of advising customers either remotely or in-person. It found that fully remote workers experienced higher meaningfulness, self-actualization, happiness, and commitment than in-person workers. Another study, published by the National Bureau of Economic Research, reported that hybrid workers, compared to office-centric ones, experienced higher satisfaction with work and had 35 percent more job retention.
What about the supposed burnout crisis associated with remote work? Indeed, burnout is a concern. A survey by Deloitte finds that 77 percent of workers experienced burnout at their current job. Gallup came up with a slightly lower number of 67 percent in its survey. But guess what? Both of those surveys are from 2018, long before the era of widespread remote work.
By contrast, in a Gallup survey in late 2021, 58 percent of respondents reported less burnout. An April 2021 McKinsey survey found burnout in 54 percent of Americans and 49 percent globally. A September 2021 survey by The Hartford reported 61 percent burnout. Arguably, the increase in full or part-time remote opportunities during the pandemic helped to address feelings of burnout, rather than increasing them. Indeed, that finding aligns with the earlier surveys and peer-reviewed research suggesting remote and hybrid work improves wellbeing.
Remote work isn’t perfect – here’s how to fix its shortcomings
Still, burnout is a real problem for hybrid and remote workers, as it is for in-office workers. Employers need to offer mental health benefits with online options to help employees address these challenges, regardless of where they’re working.
Moreover, while they’re better overall for wellbeing, remote and hybrid work arrangements do have specific disadvantages around work-life separation. To address work-life issues, I advise my clients who I helped make the transition to hybrid and remote work to establish norms and policies that focus on clear expectations and setting boundaries.
For working at home and collaborating with others, there’s sometimes an unhealthy expectation that once you start your workday in your home office chair, and that you’ll work continuously while sitting there.
Some people expect their Slack or Microsoft Teams messages to be answered within an hour, while others check Slack once a day. Some believe email requires a response within three hours, and others feel three days is fine. As a result of such uncertainty and lack of clarity about what’s appropriate, too many people feel uncomfortable disconnecting and not replying to messages or doing work tasks after hours. That might stem from a fear of not meeting their boss’s expectations or not wanting to let their colleagues down.
To solve this problem, companies need to establish and incentivize clear expectations and boundaries. They should develop policies and norms around response times for different channels of communication. They also need to clarify work-life boundaries – for example, the frequency and types of unusual circumstances that will require employees to work outside of regular hours.
Moreover, for working at home and collaborating with others, there’s sometimes an unhealthy expectation that once you start your workday in your home office chair, and that you’ll work continuously while sitting there (except for your lunch break). That’s not how things work in the office, which has physical and mental breaks built in throughout the day. You took 5-10 minutes to walk from one meeting to another, or you went to get your copies from the printer and chatted with a coworker on the way.
Those and similar physical and mental breaks, research shows, decrease burnout, improve productivity, and reduce mistakes. That’s why companies should strongly encourage employees to take at least a 10-minute break every hour during remote work. At least half of those breaks should involve physical activity, such as stretching or walking around, to counteract the dangerous effects of prolonged sitting. Other breaks should be restorative mental activities, such as meditation, brief naps, walking outdoors, or whatever else feels restorative to you.
To facilitate such breaks, my client organizations such as the University of Southern California’s Information Sciences Institute shortened hour-long meetings to 50 minutes and half-hour meetings to 25 minutes, to give everyone – both in-person and remote workers – a mental and physical break and transition time.
Very few people will be reluctant to have shorter meetings. After that works out, move to other aspects of setting boundaries and expectations. Doing so will require helping team members get on the same page and reduce conflicts and tensions. By setting clear expectations, you’ll address the biggest challenge for wellbeing for remote and hybrid work: establishing clear work-life boundaries.
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.”