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Written By: Jagriti Shahi
Rewilding, the process of restoring and protecting natural ecosystems, has gained significant momentum in the conservation world as a strategy to reverse biodiversity loss and combat climate change. Traditionally, rewilding has involved efforts such as reintroducing native species, allowing forests to regenerate, and removing human infrastructures that disturb natural processes. However, recent advances in artificial intelligence (AI) and other technologies are bringing a new dimension to these efforts, enhancing our ability to restore ecosystems more efficiently and sustainably.
The Role of AI in Rewilding
AI is revolutionizing rewilding in several ways, from monitoring wildlife populations to predicting the outcomes of restoration projects. Here are key areas where AI is making a difference:
1. Wildlife Monitoring and Species Reintroduction
AI-powered drones, satellite imagery, and camera traps are now widely used to track wildlife populations and behaviors. These technologies help conservationists gather large amounts of data on endangered species, allowing for more accurate predictions of where and when to reintroduce species into their natural habitats. AI algorithms can process the data to track species migration, breeding patterns, and habitat use, ensuring that reintroduction efforts are well-timed and strategically located.
For example, AI systems can analyze camera trap images to identify individual animals by their unique markings, greatly improving the accuracy of population counts for endangered species. This data is crucial for determining whether reintroduced species are thriving or need additional support.
2. Predicting Ecosystem Changes
AI models can predict how ecosystems will respond to different rewilding strategies. By simulating various scenarios, AI helps conservationists understand the potential long-term effects of reintroducing species, altering land use, or removing invasive species. For instance, AI can predict how reintroducing a keystone species like wolves or elephants might impact other species and the landscape as a whole, including vegetation growth, prey populations, and predator-prey dynamics.
These predictive models enable decision-makers to choose strategies that maximize biodiversity restoration while minimizing risks to other species or the environment.
3. Combatting Invasive Species
Invasive species pose a significant threat to biodiversity, often outcompeting or preying on native species. AI is being used to identify and manage invasive species in ecosystems targeted for rewilding. Machine learning algorithms analyze environmental data, such as soil conditions, water quality, and climate factors, to predict where invasive species are likely to spread. Conservationists can then prioritize areas for intervention, applying targeted control measures to prevent invasions or manage existing populations.
AI-powered robots and drones are also being developed to physically remove invasive plants or animals, such as invasive fish species in lakes and rivers, or to monitor and manage invasive plant growth in forests.
4. Restoring Degraded Landscapes
AI-driven tools are also helping with the physical restoration of degraded landscapes. Machine learning algorithms can assess soil health, vegetation cover, and water availability to recommend optimal strategies for reforestation or habitat restoration. AI can even be used to guide seed-planting drones, which distribute seeds across large areas in patterns that mimic natural ecosystems.
By using AI to automate and optimize these processes, rewilding efforts can be scaled up, restoring larger areas of land in less time and with greater precision.
5. Climate Adaptation Strategies
As climate change reshapes ecosystems, rewilding strategies need to account for shifting environmental conditions. AI helps conservationists develop climate-adaptive rewilding plans by modeling how climate change will affect species' habitats and migration patterns. These models can suggest where species are likely to find suitable habitats in the future and guide rewilding projects to areas that will remain viable for native species over the long term.
AI is also being used to develop more resilient plant species through selective breeding or genetic engineering, ensuring that reintroduced plants can thrive in changing climate conditions.
Case Studies in AI-Assisted Rewilding
Several real-world projects are already utilizing AI to support rewilding efforts. Here are two notable examples:
Zoological Society of London’s AI-Powered Conservation: In the UK, the Zoological Society of London (ZSL) has implemented AI systems to analyze camera trap data for monitoring the recovery of species in rewilding projects. AI helps process vast amounts of data quickly, identifying species and individuals from camera trap images, which supports decisions about species reintroductions and habitat restoration.
The Nature Conservancy’s Smart Forest Restoration in Mexico: The Nature Conservancy is using AI and drones to restore degraded forests in Mexico. AI algorithms help determine the best areas to plant trees, and drones are used to plant seeds across vast areas, increasing the efficiency of forest restoration efforts.
Challenges and Ethical Considerations
While AI offers tremendous potential for rewilding, it also presents challenges. High costs and the need for advanced technical expertise can limit the accessibility of AI-driven solutions, particularly for smaller conservation organizations or projects in developing regions. Additionally, ethical considerations must be addressed, such as ensuring that the use of AI does not result in further exploitation of natural resources or harm to local communities.
Moreover, while AI can assist with data analysis and decision-making, rewilding projects must also incorporate traditional ecological knowledge and local stakeholder input to ensure that restoration efforts align with the needs of the environment and local populations.
Key Players in AI-Powered Rewilding Technology
Several organizations and companies are pioneering the use of AI in rewilding and ecosystem restoration. Here are some of the key players:
Zoological Society of London (ZSL) ZSL is at the forefront of using AI for conservation, particularly in monitoring wildlife through AI-powered camera traps. Their projects support species reintroduction and habitat restoration, especially in rewilding areas across the UK.
The Nature Conservancy (TNC) The Nature Conservancy has adopted AI and drone technology for reforestation and ecosystem restoration, notably in projects such as the Smart Forest Restoration in Mexico. Their approach uses AI to optimize planting patterns and drone seeding.
Google AI for Social Good Google’s AI division has contributed to several conservation efforts by providing machine learning tools that help track wildlife populations, fight illegal poaching, and monitor forest health. Google’s AI models are also being used in predictive analytics for ecosystem restoration.
EarthRanger EarthRanger, developed by Vulcan Inc., provides AI-powered software that integrates data from camera traps, drones, and GPS trackers to help conservationists monitor wildlife and enforce anti-poaching measures. It plays a significant role in rewilding projects by ensuring safe habitats for reintroduced species.
Wildlife Insights Wildlife Insights is an AI platform developed by Conservation International in collaboration with Google and other partners. It analyzes data from camera traps to provide real-time insights into wildlife populations, helping conservationists track progress in rewilding efforts.
Dendra Systems Dendra Systems uses AI and drones for large-scale ecosystem restoration, particularly in reforestation. Their AI models guide drones that plant seeds in degraded landscapes, making restoration more efficient and scalable.
Microsoft AI for Earth Microsoft's AI for Earth initiative provides cloud-based tools and AI services to help environmental organizations develop innovative solutions for conservation. AI for Earth supports projects related to wildlife monitoring, habitat restoration, and land use optimization, all crucial aspects of rewilding.
RESOLVE’s TrailGuard AI RESOLVE has developed TrailGuard AI, an AI-enabled camera system that detects wildlife and poachers in real-time. This technology is being used in several national parks and conservation areas, aiding in wildlife protection and enabling the reintroduction of species in safe environments.
Restor Restor is a global restoration platform powered by machine learning and satellite data, providing tools for tracking ecosystem health. It supports rewilding initiatives by offering insights into soil, vegetation, and biodiversity across restoration sites.
WILDLABS India WILDLABS is a global community that also operates in India, promoting the use of AI, machine learning, and other technological tools for wildlife conservation and habitat restoration. They collaborate with conservationists and technologists to create solutions for tracking endangered species, rewilding efforts, and fighting poaching.
Wildlife Institute of India (WII) WII is involved in several AI-powered conservation projects, particularly in wildlife monitoring and species restoration. They collaborate with tech companies and research institutions to integrate AI for tracking endangered species and habitat management, which supports rewilding initiatives.
Indian Institute of Science (IISc), Bengaluru IISc has ongoing research focused on using AI and data science for biodiversity conservation. They are involved in projects that use AI to map ecosystems, track wildlife, and support rewilding efforts through predictive modeling and habitat restoration.
National Remote Sensing Centre (NRSC), ISRO NRSC uses AI and satellite remote sensing technology to monitor environmental changes and forest health in India. Their data is crucial for rewilding initiatives, providing real-time information on deforestation, habitat degradation, and wildlife corridors.
Sanctuary Nature Foundation While primarily a conservation organization, Sanctuary Nature Foundation works with AI-powered camera traps and drones for monitoring wildlife in rewilding areas. Their work helps protect endangered species and restore degraded ecosystems across India.
WWF India WWF India is integrating AI and machine learning into its conservation strategies, particularly for wildlife monitoring and habitat management. They are using AI to track species such as tigers and elephants, crucial for rewilding efforts in protected areas like national parks and wildlife corridors.
Tech for Wildlife Tech for Wildlife, based in India, is focused on using technology, including AI, drones, and GIS mapping, to support conservation projects. They assist with rewilding efforts by monitoring forest regeneration, wildlife movements, and mapping critical habitats for restoration.
AI4Bharat While not exclusively focused on conservation, AI4Bharat is an initiative that provides AI tools for social good, including environmental conservation projects. Their AI-driven research helps monitor land use changes and ecosystem degradation, contributing to rewilding and restoration efforts across India.
Ashoka Trust for Research in Ecology and the Environment (ATREE) ATREE is a leading research institute in India focused on biodiversity conservation and sustainability. They are incorporating AI and data analytics into their rewilding projects, helping to restore ecosystems and monitor biodiversity in regions like the Western Ghats.
Agnikul Cosmos (in collaboration with ISRO) Though primarily a space technology startup, Agnikul Cosmos works with satellite data and AI-driven analytics, which can also be applied to environmental monitoring. Their technology has potential applications in rewilding projects for tracking large-scale environmental changes in India.
The Future of Rewilding with AI
The use of AI in rewilding is still in its early stages, but its potential is vast. As technologies continue to improve, we can expect AI to play an even more significant role in ecosystem restoration. By combining AI with other emerging technologies such as the Internet of Things (IoT), remote sensing, and bioengineering, we can develop more sophisticated and large-scale rewilding strategies to tackle the challenges of biodiversity loss and climate change.
In the future, AI may not only guide rewilding efforts but also help manage ecosystems in real-time, continuously monitoring and adjusting rewilding strategies based on new data and changing environmental conditions. This could lead to more resilient ecosystems that are better able to withstand human pressures and climate disruptions.
Conclusion
Rewilding with AI is an exciting frontier in conservation technology. By integrating AI’s powerful data processing and predictive capabilities with on-the-ground restoration efforts, we can accelerate ecosystem recovery, making it possible to restore vast landscapes and revive biodiversity at unprecedented scales. With AI as an ally, the dream of reviving ecosystems to their natural glory is becoming more attainable.
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