By: Colin Averill, Postdoc and Ambizione Research Fellow at Crowther Lab
We are witnessing a global movement to protect what is left of nature, as well as restore as much as we can. When we work to restore natural ecosystems, we generally start with the plants. In tropical forest ecosystems, we are often logistically constrained to planting just a subset of the original tree species that were once present. The idea is that this initial planting will “jump-start” the natural process of forest succession, leading to the recruitment of even greater biodiversity than we put in at planting, and eventually develop into a thriving forest ecosystem. Yet, so many restoration efforts fail. The trees we plant often die in places they once thrived, outcompeted by new species that have invaded the site. However, perhaps only considering the vegetation is too limited a view of what an ecosystem is, and which parts of the ecosystem are missing.
When we think of forests, we generally focus on what we can see – the plants and animals inhabiting the aboveground. However, just below the earth live incredibly diverse and complex communities of bacteria and fungi. These microorganisms are essential to how plants interact with the soil environment, and are necessary to access critically limiting soil resources. Many soil fungi form belowground networks among trees, allowing trees to share resources and buffer one another in stressful environments. These microorganisms are the forest microbiome. Yet, many key forest microbial species are missing in the post-agricultural landscapes where most forest restoration happens. It begs the question, what would happen if while planting trees we also “planted” the forest microbiome, jumpstarting not just the plants, but also their associated bacteria and fungi?
This is what our Ph.D. student, Felix Finkbeiner (also founder of Plant-for-the-Planet), is investigating with our team within the tropical dry forests of the Yucatán Peninsula of México. We’ve collected soil from intact forest remnants in the surrounding landscape, and use this soil as microbial inocula for soil microbiome restoration. The experimental setup is analogous to a randomized controlled drug trial. We’ve established 144 “blocks” of 100 trees across the landscape (14,400 trees!), and then randomly assigned the blocks to one of two treatment conditions. Half of the trees get a small scoop of forest inocula at the time of planting, while the other half gets a “placebo” dose of soil from the post-agricultural site we’re working to restore. Over the next several years we will be monitoring these trees to ask questions like:
Does soil microbiome inoculation increase the recovery of native forest microbial biodiversity?
Can microbiome inoculation increase tree growth, survival and carbon capture rates?
Will microbiome introduction increase the recruitment of other tree species into the plots, above and beyond what we planted?
We are excited to discover what happens. But, success or failure, we will learn more about how forest ecosystems assemble and gain a deeper knowledge of when restoration succeeds and fails. Beyond questions of the forest microbiome, this project is an example of how restoration and science can happen at the same time. By nesting experiments within larger restoration projects, we can learn more about how forests work on a fundamental level, while simultaneously learning how to do restoration better.
We’ve established a similar trial in Wales, UK in collaboration with The Carbon Community, a UK charity. We’re excited to replicate and expand this work across more restoration sites in diverse parts of the world. By doing so, we can generate truly general knowledge about how the global forest system works, and how best to restore and protect it.
Learn more about our soil microbiome research project in Yucatán, Mexico:
By: Kenza Amara, master’s student at ETH Zurich, part of Crowther Lab and DS3Lab
Artificial intelligence (AI) for the environment: It first seems somewhat paradoxical. But could the rise of these new technologies be in line with forest landscape restoration and environmental protection? Seeking out an answer to this question is a challenge that I have set for myself. But why and how?
From Paris to Zurich… and OneForest
With a strong background in mathematics, physics and computer science, I have always been motivated to be involved in solving the great challenges of our era. This motivation became even stronger when I was studying my first Master’s degree in Data Science at the Ecole Polytechnique Paris. I still remember one specific day: I was attending a conference on the damages humanity has caused on the environment – and left it in tears. Seeing the environmental distress our planet is under was the final straw: I had to do something!
I decided to do a second Master’s degree in environmental sciences at ETH Zurich. I wanted to learn more about our environment and the processes underlying it, and with full knowledge of those facts, put my technical skills in deep learning, and more broadly in computer science, to practical use. The following study year was very different from the past years at the French Grand École: I read a lot of articles on climate policies, studied conflicts over international waters and learned about international and European environmental laws. But for my Master’s thesis I decided to go back to my favourite field: neural networks and their many applications. I contacted David Dao from DS3Lab to start a multi-disciplinary project with Crowther Lab. This gave rise to OneForest, a fantastic initiative to merge drone imagery and citizen science to build informative maps of our forests worldwide.
Putting drone images and citizen science on the map
We started with the disappointing observation that one major issue for forest monitoring was the lack of information on the forests. There is no existing high-resolution labelled dataset on trees at scale. Therefore, we decided to build a global map of our forests that would gather all existing trees and document their exact position and characteristics. This large-scale data source would enable scientists, farmers and policymakers around the world to reference the same global database and monitor forest landscapes in even the most isolated parts of our planet.
From having to create our own species training dataset, to dealing with the various noise sources in the data, or developing an algorithm that could reliably match drone images with citizen-made ground measurements: our project was for sure riddled with (exciting!) challenges. Now, OneForest is able to return stable mappings and offer up rich information about the trees’ attributes such as name, species, genus, height and trunk diameter for any given forest landscape area. With OneForest we can begin to better understand and answer questions about forest ecosystems on a global scale.
Global maps for global impact
What simply began as my Master’s thesis project has, after its completion, drawn the attention of multiple NGOs and academic research groups. Back when I was developing this end-to-end method, I definitely did not expect so much enthusiasm for OneForest from the scientific community! But I soon realised that there was great potential to create wider impact. As an integral part of Crowther Lab, OneForest also became a promising tool for the new open-data ecosystem restoration platform Restor. OneForest provides automated ecological insights on individual tree level: therefore, it can generate localised information about trees no matter where on the planet – even in the most isolated places where data is difficult to collect in large amounts!
To go back to the question in the beginning: AI and environmental sciences are a pair not to be missed out on. Artificial intelligence has long been used and explored for robotics, marketing or the industry. But working on OneForest and seeing the feedback it received has reinforced my belief that there is also a lot of potential for AI to generate a deeper understanding of our environment and identify global ecological patterns. From checking how much carbon storage is in a specific group of trees, or observing the evolution of a forest in terms of tree size, to detecting whether the right species have been planted – I can envision many future applications.
A backpack full of new experiences
At Crowther Lab I discovered an academic environment with unwavering team spirit that encourages participation in diverse activities and the sharing of ideas and experiences. It’s still very rare to have computer and environmental scientists working hand in hand and I’m glad that exceptions like Crowther Lab made this collaboration possible! This teamwork between us scientists results in innovative solutions that seem to be truly appreciated by NGOs, private companies and political actors. It shows how vital interdisciplinary work is to bringing our understanding of the world further.
But now my Master’s thesis and my time at the lab has come to an end. Where to go from here? With a backpack full of new, enriching experiences, I decided to continue my interdisciplinary research at the ETH AI Center. This brand-new centre encourages AI to be put to service for society in domains such as sustainability, health and robotics, opening up new horizons to collaborate with the industry, public administrations and international universities.
And what about OneForest? My hope is to see OneForest grow, be developed further, improved, and of course, used by scientists, restoration agencies and farmers. It will hopefully open the doors to faster and easier forest monitoring, necessary for effective forest landscape restoration. And maybe, just maybe, it will serve as an inspiration for the next generation of students wanting to take part in solving the global problems of our time.