Key points

  • Technology has rapidly changed the face of conservation and is now at a critical juncture where cutting edge tools are available, but aren’t necessarily as accessible or affordable as they need to be.
  • A recent survey by WILDLABS, an online platform connecting conservation technology experts, shows that environmental DNA, networked sensors and artificial intelligence tools are the fields that hold the most promise.
  • Yet despite the progress that’s been made, there are still many barriers to accessibility for local and Indigenous communities.
  • Experts say collaboration and partnerships between conservationists, tech developers and local and Indigenous communities will be key to ensuring that conservation tech can continue having an impact.

As a biology undergraduate, Talia Speaker spent a grueling summer hiking around the mountains near Santa Cruz, California, interning with a team that monitored puma behavior. In one hand she carried a clunky, outdated VHF tracker, trying to get close enough to download data from the cats’ radio collars. In her back pocket was a sleek, shiny iPhone.

The disparity between the two technologies wasn’t lost on her as she was also tasked with spending countless hours searching for insights by clicking through millions of camera images. She couldn’t help but think that there had to be a better way.

“Ecologists were stuck with such terrible tools while technology was doing so much to power the rest of the world,” Speaker tells Mongabay in a video interview.

For her senior thesis, Speaker wanted to use machine-learning models to process camera data, and managed to find people working in that space. Today, she’s the program officer at WWF for WILDLABS, an online platform that connects conservation technology experts.

Talia Speaker, the program officer for WWF at WILDLABS, conducts field testing of a new drone in Colorado. The drone will be used for ecological monitoring. Image courtesy of Vasco Chavez-Molina.

Over the past few decades, technology quickly changed the face of conservation. Camera traps, acoustic sensors, drones, satellites, and now genomic and machine-learning tools empower conservationists to better understand the ecosystems they work in. But conservation technology is now at a turning point. Despite the progress made in the field, there are still financial constraints and barriers to access, especially for local and Indigenous communities.

In a recent report, WILDLABS released the first global community-sourced assessment of its kind, showing the bigger picture of conservation technology. Nearly 250 experts from across 37 countries responded. The report shines a spotlight on the opportunities, the constraints, and what people are struggling with, says Speaker, who is also the lead author of the corresponding study.

‘Are we writing the obituary of a dying planet?’

In the survey, conservation technologists were asked to rate the current performance of the technologies they use as well as the potential for those technologies to advance conservation efforts.

They identified three areas with the highest untapped potential: environmental DNA, or eDNA; networked sensors; and artificial intelligence (AI) tools.

While DNA can be extracted from tissue taken directly from an animal or plant, eDNA comes from soil or water samples that may contain skin or fur or droppings, and can paint a rough sketch of what species are present in an area. Even small traces of DNA can show that an animal is present, even if it’s never been observed, helping conservationists make the case for greater protections in an area where rare or threatened species are detected.

Networked sensors, meanwhile, connect camera traps, acoustic recorders and other tracking devices online, making them the eyes and ears of conservationists and local communities to monitor and track when animals are present in real time.

Both eDNA and networked sensors can generate vast amounts of data — often too much to even analyze. That’s why AI tools are a critical area to invest in, says Stephanie O’Donnell, a co-author of the WILDLABS study and the community manager at WILDLABS and Fauna & Flora International.

Artificial intelligence plays a pivotal role in sifting through the troves of data that conservationists collect, such as camera-trap images and audio recordings, reducing manual labor.

Camera traps have been a game changer in capturing a lot of data in the field. For instance, the California Condor Recovery Program uses livestreaming cameras to remotely monitor condor nests, improve nest management techniques, and gain a better understanding of condor nesting behavior. Image courtesy of U.S. Fish and Wildlife Service.

And there’s also a dire need to analyze data quickly. As part of the report, the team talked with focus groups of 50 experts. O’Donnell recalls a statement from one of the focus groups: “If we go too slowly, are we just writing the obituary of a dying planet?”

“If you’re collecting all of this data, that’s great,” Speaker says. “But if you can’t translate it to conservation action, it’s meaningless.”

Tech constraints

The survey also identified the three biggest challenges facing conservation technology: unsustainable funding; lack of coordination across efforts; and poor capacity building.

“Conservationists are forever underresourced and overworked and have so much to do without enough funding or support to do it,” Speaker says.

But in conservation technology, the situation is a bit different because there the private technology sector has so much money and resources, she adds.

“We just have to figure out how to sustainably bring in conservation-type efforts. We see a lot of opportunity for pulling new resources into conservation and addressing things like climate change.”

These financial constraints include not only upfront costs, but also continued funding to maintain equipment.

And while lack of sustainable funding was a consistent message from the respondents, the survey showed that that women and individuals in less-industrialized countries were disproportionally affected by access to funding. These findings point to more intersectional assessments of conservation technology so that communities can receive targeted resources and support, Speaker says.

A major challenge that remains is “getting technologies to be accessible to the communities who mean the most,” she adds.

“Local communities are super critical stakeholders … but so far have not been very well included, especially in the tech aspect of conservation work.”

Artificial intelligence can be used to parse through the thousands of images that researchers collect from camera traps. Image courtesy of Sarah Bassing and the Washington Predator-Prey Project.

‘We are always years behind’

In Aotearoa New Zealand, more than 11,000 kilometers (nearly 7,000 miles) from where Speaker got her start using conservation technology, Te Tui Shortland had her own introduction to the field. When she was 18 years old she loved hiking around the bush, taking photos of flowers with her smartphone.

One day she spotted the white rātā (Metrosideros albiflora), a vine endemic to the forests of the North Island. She typed down the name and later showed it off to her cousin, a network analyst, who showed her how to geolocate the image.

Smartphones are everywhere, so apps can be especially helpful in getting local and Indigenous communities to engage with conservation technology, says Shortland, a member of the
Ngati Hine, Ngatiwai, Ngapuhi, Ngati Raukawa ki te Tonga, Te Rarawa, Te Arawa, Kai Tahu
peoples and works in Indigenous diplomacy.

Living a traditional lifestyle is grueling work and having apps is one step toward making conservation technology more accessible, she says. Most of the conservation technology that Indigenous communities engage with are for mapping and remote sensing.

“I feel like we are always years behind because we often have to get what is the latest free and open-source technology,” Shortland says.

What local and Indigenous communities really need are partnerships and allies to help bring tech to their communities and teach them how to use it, she says.

“Indigenous people are on the front lines of so many environmental challenges, but there is a long and unfortunate legacy of ignoring the priceless knowledge that resides with the traditional occupants of the land and their stewardship of it,” says Lindsay Starke, a community manager at FieldKit, a company that strives to make networked sensors more affordable and accessible.

“In truly listening, we can start to reverse this process and develop technology that is human driven.”

Machine learning, thermal cameras and drones can be used together to find and monitor endangered animals automatically. Animals glow brightly in thermal images, making them easy to spot, and then machine learning can tell species apart from their unique thermal shapes. Image courtesy of Claire Burke.

Collaborating, the key to accessibility

Just over half of the survey respondents said they felt more optimistic about the future of the conservation technology field than they did a year ago. They cited the growing accessibility; the rate at which the field is evolving; and the culture of collaboration.

With the technology already there, conservationists and tech developers need to collaborate and create partnerships with local and Indigenous communities for it to continue to have an impact, O’Donnell says. There’s an excitement and willingness from the tech industry, she adds.

But it’s important that tech developers get out into the field to see the conditions that conservationists deal with, O’Donnell says. Whether it’s heat and humidity, or the fact that data can only be collected once every two years, there are real challenges in using these tools that are new to conservation settings, she says.

More efforts are popping up to collaborate and include local and Indigenous communities, who must have ownership over these tools and the resulting data, Speaker says.

“Conservation technologies can either be used to empower these groups to have agency over their local resources and management and conservation actions. Or they can further separate them from the data and decision-making, which can be super damaging,” she says.

The key to this is collaborating with local and Indigenous communities, not only in using the technology, but in creating it, Starke says.

“We as Indigenous peoples, we see things in this holistic and connected way,” Shortland says. “But there is another whole skillset with the scientific way of viewing the world.

“And with these big problems that we have,” she adds, “we need multiple minds and ideas to make it work.”

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