The Changing Role of Technology in Wildlife Conservation.

How Technology Is Changing the Way Wildlife Conservation Is Done

As the world struggles with biodiversity loss and climate change, conservationists are increasingly turning to technology to monitor wildlife and track trends. But the tools available often lack performance and accessibility.

Fortunately, frugal hardware and open-source software are changing that. Here are four ways technology is transforming conservation. Featuring Jorge Ahumada, whose passion for sea creatures turned into a career protecting species and habitats around the globe.

On-the-ground technologies

Many conservation technologies are being used on the ground by field staff to make their work more efficient. Camera traps, for example, can capture large amounts of data that can then be analyzed by computers to identify patterns and detect poachers.

Smartphone apps, such as iNaturalist and eBird, allow people to contribute to wildlife monitoring by sharing their sightings. And devices such as ear tags, collars and satellite tracking systems can help researchers follow animal movements.

However, a number of systemic challenges inhibit the development and use of technology in conservation. Survey respondents ranked upfront costs and insufficient technical skills as the top constraints to developing and using technology for conservation. They also cited the need for sustained funding to enable developers and testers from developing economies. Inequity in the provision of such funding disproportionately affects women. Some respondents urged the establishment of a convening body or national lab to facilitate collaboration and define industry standards.

Remote sensing

In addition to tracking wildlife populations and their movement, remote sensing technologies enable conservationists to monitor biodiversity at a global scale. This allows projects to better understand the ‘where’ and ‘why’ of species deterioration, and respond accordingly.

While many survey respondents reported regularly engaging with multiple tools, they also highlighted three technologies as having the most untapped potential: ML/computer vision, environmental DNA (eDNA), and networked sensors. However, these same tools were ranked comparatively low on current performance.

To address these gaps, some projects are developing purpose-built research and monitoring tools based on open-source hardware and software. For example, a collaborative project called Wildlife Insights uses machine learning to automatically identify and count individual animals in camera trap images. These insights can then be shared with partners and policymakers to help inform decisions and actions.

Geographic information systems (GIS)

GIS mapping is a powerful conservation technology that’s used to analyze the geographic distribution of species and help wildlife conservationists identify threats. It also facilitates collaboration among researchers, organizations, and governments. This is crucial to identifying the best ways to protect wildlife and its habitats.

While there is a lot of excitement and enthusiasm for conservation technology, it’s important to keep in mind that the tech industry needs to get out into the field and see how ecologists actually use these tools. Many of the technologies are still not fit-for-purpose for conservationists, and they often lack the durability needed in harsh environmental conditions.

Additionally, networked sensors like remote camera traps and acoustic monitoring devices generate vast amounts of data that can be difficult to sift through. This is where software-based automation tools are key, such as eDNA analysis and automated identification of animals in camera-trap images. This will reduce manual labor and allow conservationists to focus more time on the most pressing conservation challenges.

Artificial intelligence (AI)

Our wildlife and biodiversity face several threats, including climate change, habitat loss, and illegal killings. Using AI, conservationists can monitor animals and help them to survive in their natural habitats. AI can be used in animal recognition, monitoring, tracking, and in predicting changes in animals’ habitats.

ML algorithms can recognize different types of animals through images captured by drones or heat signatures from thermal cameras. They can also identify their vocalizations through acoustic sensors. They can also forecast their migration patterns.

For instance, lions in Tanzania can be saved from poachers using AI-enabled security surveillance deployed at suspicious locations. The technology detects a human presence even in the dark or at night, making it difficult for poachers to escape. This can also reduce costs and increase the speed of patrols. This is one of the reasons why PAWS, an artificial intelligence-enabled patrol system is being used in Lake Itezhi-Tezhi national park to boost wildlife protection.

Go Home

Leave a Reply

Your email address will not be published. Required fields are marked *