Short Story Contest Winner: "The Gerry Program"
It's an odd sensation knowing you're going to die, but it was a feeling Gerry Ferguson had become relatively acquainted with over the past two years. What most perplexed the terminally ill, he observed, was not the concept of death so much as the continuation of all other life.
Gerry's secret project had been in the works for two years now, ever since they found the growth.
Who will mourn me when I'm gone? What trait or idiosyncrasy will people most recall? Will I still be talked of, 100 years from now?
But Gerry didn't worry about these questions. He was comfortable that his legacy would live on, in one form or another. From his cozy flat in the west end of Glasgow, Gerry had managed to put his affairs in order and still find time for small joys.
Feeding the geese in summer at the park just down from his house, reading classics from the teeming bookcase in the living room, talking with his son Michael on Skype. It was Michael who had first suggested reading some of the new works of non-fiction that now littered the large oak desk in Gerry's study.
He was just finishing 'The Master Algorithm' when his shabby grandfather clock chimed six o'clock. Time to call Michael. Crammed into his tiny study, Gerry pulled his computer's webcam close and waved at Michael's smiling face.
"Hi Dad! How're you today?"
"I'm alright, son. How're things in sunny Australia?"
"Hot as always. How's things in Scotland?"
"I'd 'ave more chance gettin' a tan from this computer screen than I do goin' out there."
Michael chuckled. He's got that hearty Ferguson laugh, Gerry thought.
"How's the project coming along?" Michael asked. "Am I going to see it one of these days?"
"Of course," grinned Gerry, "I designed it for you."
Gerry's secret project had been in the works for two years now, ever since they found the growth. He had decided it was better not to tell Michael. He would only worry.
The two men chatted for hours. They discussed Michael's love life (or lack thereof), memories of days walking in the park, and their shared passion, the unending woes of Rangers Football Club. It wasn't until Michael said his goodbyes that Gerry noticed he'd been sitting in the dark for the best part of three hours, his mesh curtains casting a dim orange glow across the room from the street light outside. Time to get back to work.
*
Every night, Gerry sat at his computer, crawling forums, nourishing his project, feeding his knowledge and debating with other programmers. Even at age 82, Gerry knew more than most about algorithms. Never wanting to feel old, and with all the kids so adept at this digital stuff, Gerry figured he should give the Internet a try too. Besides, it kept his brain active and restored some of the sociability he'd lost in the previous decades as old friends passed away and the physical scope of his world contracted.
This night, like every night, Gerry worked away into the wee hours. His back would ache come morning, but this was the only time he truly felt alive these days. From his snug red brick home in Scotland, Gerry could share thoughts and information with strangers from all over the world. It truly was a miracle of modern science!
*
The next day, Gerry woke to the warm amber sun seeping in between a crack in the curtains. Like every morning, his thoughts took a little time to come into focus. Instinctively his hand went to the other side of the bed. Nobody there. Of course; she was gone. Rita, the sweetest woman he'd ever known. Four years this spring, God rest her soul.
Puttering around the cramped kitchen, Gerry heard a knock at the door. Who could that be? He could see two women standing in the hallway, their bodies contorted in the fisheye glass of the peephole. One looked familiar, but Gerry couldn't be sure. He fiddled with the locks and pulled the door open.
"Hi Gerry. How are you today?"
"Fine, thanks," he muttered, still searching his mind for where he'd seen her face before.
Noting the confusion in his eyes, the woman proffered a hand. "Alice, Alice Corgan. I pop round every now and again to check on you."
It clicked. "Ah aye! Come in, come in. Lemme get ya a cuppa." Gerry turned and shuffled into the flat.
As Gerry set about his tiny kitchen, Alice called from the living room, "This is Mandy. She's a care worker too. She's going to pay you occasional visits if that's alright with you."
Gerry poked his head around the doorway. "I'll always welcome a beautiful young lady in ma home. Though, I've tae warn you I'm a married man, so no funny business." He winked and ducked back into the kitchen.
Alice turned to Mandy with a grin. "He's a good man, our Gerry. You'll get along just fine." She lowered her voice. "As I said, with the Alzheimer's, he has to be reminded to take his medication, but he's still mostly self-sufficient. We installed a medi-bot to remind him every day and dispense the pills. If he doesn't respond, we'll get a message to send someone over."
Mandy nodded and scribbled notes in a pad.
"When I'm gone, Michael will have somethin' to remember me by."
"Also, and this is something we've been working on for a few months now, Gerry is convinced he has something…" her voice trailed off. "He thinks he has cancer. Now, while the Alzheimer's may affect his day-to-day life, it's not at a stage where he needs to be taken into care. The last time we went for a checkup, the doctor couldn't find any sign of cancer. I think it stems from--"
Gerry shouted from the other room: "Does the young lady take sugar?"
"No, I'm fine thanks," Mandy called back.
"Of course you don't," smiled Gerry. "Young lady like yersel' is sweet enough."
*
The following week, Mandy arrived early at Gerry's. He looked unsure at first, but he invited her in.
Sitting on the sofa nurturing a cup of tea, Alice tried to keep things light. "So what do you do in your spare time, Gerry?"
"I've got nothing but spare time these days, even if it's running a little low."
"Do you have any hobbies?"
"Yes actually." Gerry smiled. "I'm makin' a computer program."
Alice was taken aback. She knew very little about computers herself. "What's the program for?" she asked.
"Well, despite ma appearance, I'm no spring chicken. I know I don't have much time left. Ma son, he lives down in Australia now, he worked on a computer program that uses AI - that's artificial intelligence - to imitate a person."
Alice still looked confused, so Gerry pressed on.
"Well, I know I've not long left, so I've been usin' this open source code to make ma own for when I'm gone. I've already written all the code. Now I just have to add the things that make it seem like me. I can upload audio, text, even videos of masel'. That way, when I'm gone, Michael will have somethin' to remember me by."
Mandy sat there, stunned. She had no idea anybody could do this, much less an octogenarian from his small, ramshackle flat in Glasgow.
"That's amazing Gerry. I'd love to see the real thing when you're done."
"O' course. I mean, it'll take time. There's so much to add, but I'll be happy to give a demonstration."
Mandy sat there and cradled her mug. Imagine, she thought, being able to preserve yourself, or at least some basic caricature of yourself, forever.
*
As the weeks went on, Gerry slowly added new shades to his coded double. Mandy would leaf through the dusty photo albums on Gerry's bookcase, pointing to photos and asking for the story behind each one. Gerry couldn't always remember but, when he could, the accompanying stories were often hilarious, incredible, and usually a little of both. As he vividly recounted tales of bombing missions over Burma, trips to the beach with a young Michael and, in one particularly interesting story, giving the finger to Margaret Thatcher, Mandy would diligently record them through a Dictaphone to be uploaded to the program.
Gerry loved the company, particularly when he could regale the young woman with tales of his son Michael. One day, as they sat on the sofa flicking through a box of trinkets from his days as a travelling salesman, Mandy asked why he didn't have a smartphone.
He shrugged. "If I'm out 'n about then I want to see the world, not some 2D version of it. Besides, there's nothin' on there for me."
Alice explained that you could get Skype on a smartphone: "You'd be able to talk with Michael and feed the geese at the park at the same time," she offered.
Gerry seemed interested but didn't mention it again.
"Only thing I'm worried about with ma computer," he remarked, "is if there's another power cut and I can't call Michael. There's been a few this year from the snow 'n I hate not bein' able to reach him."
"Well, if you ever want to use the Skype app on my phone to call him you're welcome," said Mandy. "After all, you just need to add him to my contacts."
Gerry was flattered. "That's a relief, knowing I won't miss out on calling Michael if the computer goes bust."
*
Then, in early spring, just as the first green buds burst forth from the bare branches, Gerry asked Mandy to come by. "Bring that Alice girl if ya can - I know she's excited to see this too."
The next day, Mandy and Alice dutifully filed into the cramped study and sat down on rickety wooden chairs brought from the living room for this special occasion.
An image of Gerry, somewhat younger than the man himself, flashed up on the screen.
With a dramatic throat clearing, Gerry opened the program on his computer. An image of Gerry, somewhat younger than the man himself, flashed up on the screen.
The room was silent.
"Hiya Michael!" AI Gerry blurted. The real Gerry looked flustered and clicked around the screen. "I forgot to put the facial recognition on. Michael's just the go-to name when it doesn't recognize a face." His voice lilted with anxious excitement. "This is Alice," Gerry said proudly to the camera, pointing at Alice, "and this is Mandy."
AI Gerry didn't take his eyes from real Gerry, but grinned. "Hello, Alice. Hiya Mandy." The voice was definitely his, even if the flow of speech was slightly disjointed.
"Hi," Alice and Mandy stuttered.
Gerry beamed at both of them. His eyes flitted between the girls and the screen, perhaps nervous that his digital counterpart wasn't as polished as they'd been expecting.
"You can ask him almost anything. He's not as advanced as the ones they're making in the big studios, but I think Michael will like him."
Alice and Mandy gathered closer to the monitor. A mute Gerry grinned back from the screen. Sitting in his wooden chair, the real Gerry turned to his AI twin and began chattering away: "So, what do you think o' the place? Not bad eh?"
"Oh aye, like what you've done wi' it," said AI Gerry.
"Gerry," Alice cut in. "What did you say about Michael there?"
"Ah, I made this for him. After all, it's the kind o' thing his studio was doin'. I had to clear some space to upload it 'n show you guys, so I had to remove Skype for now, but Michael won't mind. Anyway, Mandy's gonna let me Skype him from her phone."
Mandy pulled her phone out and smiled. "Aye, he'll be able to chat with two Gerry's."
Alice grabbed Mandy by the arm: "What did you tell him?" she whispered, her eyes wide.
"I told him he can use my phone if he wants to Skype Michael. Is that okay?"
Alice turned to Gerry, who was chattering away with his computerized clone. "Gerry, we'll just be one second, I need to discuss something with Mandy."
"Righto," he nodded.
Outside the room, Alice paced up and down the narrow hallway.
Mandy could see how flustered she was. "What's wrong? Don't you like the chatbot? I think it's kinda c-"
"Michael's dead," Alice spluttered.
"What do you mean? He talks to him all the time."
Alice sighed. "He doesn't talk to Michael. See, a few years back, Michael found out he had cancer. He worked for this company that did AI chatbot stuff. When he knew he was dying he--" she groped in the air for the words-- "he built this chatbot thing for Gerry, some kind of super-advanced AI. Gerry had just been diagnosed with Alzheimer's and I guess Michael was worried Gerry would forget him. He designed the chatbot to say he was in Australia to explain why he couldn't visit."
"That's awful," Mandy granted, "but I don't get what the problem is. I mean, surely he can show the AI Michael his own chatbot?"
"No, because you can't get the AI Michael on Skype. Michael just designed the program to look like Skype."
"But then--" Mandy went silent.
"Michael uploaded the entire AI to Gerry's computer before his death. Gerry didn't delete Skype. He deleted the AI Michael."
"So… that's it? He-he's gone?" Mandy's voice cracked. "He can't just be gone, surely he can't?"
The women stood staring at each other. They looked to the door of the study. They could still hear Gerry, gabbing away with his cybercopy.
"I can't go back in there," muttered Mandy. Her voice wavered as she tried to stem the misery rising in her throat.
Alice shook her head and paced the floor. She stopped and stared at Mandy with grim resignation. "We don't have a choice."
When they returned, Gerry was still happily chatting away.
"Hiya girls. Ya wanna ask my handsome twin any other questions? If not, we could get Michael on the phone?"
Neither woman spoke. Gerry clapped his hands and turned gaily to the monitor again: "I cannae wait for ya t'meet him, Gerry. He's gonna be impressed wi' you."
Alice clasped her hands to her mouth. Tears welled in the women's eyes as they watched the old man converse with his digital copy. The heat of the room seemed to swell, becoming insufferable. Mandy couldn't take it anymore. She jumped up, bolted to the door and collapsed against a wall in the hallway. Alice perched on the edge of her seat in a dumb daze, praying for the floor to open and swallow the contents of the room whole.
Oblivious, Gerry and his echo babbled away, the blue glow of the screen illuminating his euphoric face. "Just wait until y'meet him Gerry, just wait."
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.”