Labs focused on specific tasks face unique challenges, plus some similar ones
In the United States, the remains of more than 40,000 people linger unidentified. On top of that, about 230,000 homicides go unsolved every year, and that can add to the challenge of human identification. “Unless you’re affected, you don’t realize it’s a problem,” says Erin Kimmerle, associate professor of anthropology at the University of South Florida (USF, Tampa). “Despite the scope of the problem, most agencies don’t have units dedicated to identifying human remains.” In many case, that problem is finding a way to identify lost loved ones. This is just one example of the problems faced by dedicated labs.
Kimmerle started a forensic anthropology lab at USF in 2006, and it took a couple of years to get it running. “Now, we’re a service provider for the State of Florida,” she says, “and we do a lot of work for people outside of the state.” This work includes trauma analysis and challenges related to missing and unidentified people, largely for law-enforcement agencies and medical examiners. “These are very practical problems,” Kimmerle explains. “We’re getting at identifying unknown people and returning that to the family.”
To complete such dedicated tasks, Kimmerle and her colleagues face a host of problems.
Finding the funding
Funding creates the top challenge for Kimmerle, and it’s an even bigger challenge than most scientists face. Standard grants do not exist for the services that the USF lab provides. Instead, Kimmerle and her colleagues must find creative ways of funding the work. Sometimes, this involves running research projects that include work that can be applied to cases. “Research is often to answer questions that come up in casework,” she explains. “You come up with a problem, and you do a research study to understand it.”
In addition, Kimmerle’s group reaches out through education to inform the public about the problem in identification. As an example, she says, “We write op-ed pieces.” They also seek private funding. This team needs the funding, because they receive more than 250 cases a year, and “some of the cases are 20 or 30 years old,” Kimmerle notes.
Tools of the identification trade
Kimmerle’s team tries to help investigators get one step closer to solving a case or to move in a new direction in the search. That takes the application of a range of tools.
For instance, when unidentified remains are found, a researcher can ask: Did the person come from the geographical area where he or she was found? “Isotope analysis helps there,” Kimmerle explains. The ratio of isotopes of an element varies by geographical location. So, measuring that ratio in human remains can provide some indication of where the person lived.
Beyond isotope analysis, Kimmerle relies on classic forensic anthropology, including skeletal analysis, radiology, and three-dimensional laser scanning, and she sends DNA samples to labs for analysis. “We try to piece together that information to determine the person’s age, sex, ancestry, stature, and health,” she says. “We even use Photoshop to come up with a composite face that can be used in facial recognition.”
Some of the solutions are information databases. “To figure out who someone is,” Kimmerle says, “you need to know who you might be looking for.” That turns out to be challenging. Before 1980, there was no centralized database of missing people in the United States. Even today, many local agencies maintain only local databases—ones that are not necessarily connected to others. Today, the National Unidentified Persons System (NamUs) houses data from across the country, but many agencies don’t use it, even though it’s free for law enforcement and medical examiners.
All of these challenges require equipment and trained technicians—all of which Kimmerle’s lab struggles to afford.
Instead of criminal activities, other labs focus on nature’s predator–prey interactions. At the University of California at Davis, Stacey Combes, assistant professor of neurobiology, physiology, and behavior, studies interactions between one flying animal hunting another. That takes place in turbulent skies.
To see how an insect, for instance, handles the changing wind currents, Combes must first measure the conditions in the environment. “Then, you recreate that in a wind tunnel and look closely at the insect flying with high-speed video,” she explains. “The behavioral challenge is finding insects that perform the behavior that we’re interested in studying.”
Although past studies of such behaviors relied on very small datasets—like three wingbeats from a single insect—Combes and her colleagues dig deeper. “We really come up with massive datasets that we collect, store, and analyze as automatically as we can,” she explains. “We’re getting into mega-data challenges, just like DNA labs.”
Getting from three wingbeats to many, especially in turbulent conditions, depends on a broad collection of technology. “We work with engineers sometimes,” Combes says, “because they might have a technology that is way beyond anything we have.” She adds, “It’s impossible for me alone.” So, her graduate students and postdocs dig into new areas—from coding to electronics and beyond—and then the lab runs tutorials to help others learn the new techniques.
From forensics to flying insects, scientists face unique—and sometimes similar—challenges to get the job done. With so much technology available, getting the best results usually depends on teamwork. The days of one person in a lonely lab changing the world are largely gone. We live in a data environment that demands collaboration.