EARTHSHOT INSTITUTE
The Assisted Forest Regeneration Lab will expand the possibilities of the traditional scientific literature review by calling on numerous participants around the world. Leland Werden, of ETH Zürich, is leading this effort to bring together a polyglot team of forestry data scouts to look well beyond the usual journals and databases and synthesize the world’s under-appreciated wisdom about what interventions work to regenerate forests. To join this lab, one just needs a bit of familiarity with forestry, or ecology, or a related field, and an interest in putting one’s data-digging skills to work. The lab also needs project managers.
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The Beaver Lab, led by Grace Lindsay, of NYU, returns to one of Earthshot’s foundational ideas: If we could use satellite imagery and machine learning to identify beaver dams, maybe we could start to understand—and even forecast—how these relatively small additions to a river result in dramatic transformation of local ecology. Beaver dams have been shown to result in greener, more drought-resilient waterways in semi-arid environments. By learning from their new database of natural dams, the lab will predict how humans can emulate their effects on biological productivity, carbon sequestration, and drought resilience. This lab will be calling for experts in remote sensing, machine learning, and riparian ecology, as well as a project manager.
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The Ganges Lab, led by Anthony Acciavatti, of Yale University, will map and analyze a key feature of the Ganges basin—naalas—to understand how new forms of green infrastructure, such as parks, bioswales, and bioremediation, can rejuvenate this vital and sacred river. The lab will need a project manager in addition to people with expertise in remote sensing and machine learning (to identify and map naalas), river ecology and hydrology (to understand how they function and generate ideas for better management), as well as permaculture techniques and anthropology (to plan interventions on the ground).
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The goal of our lab is to create a high-spatial resolution map of coastal forested wetlands at global scale. If we know precisely where these ecologically critical but fragile forests are located, we can manage freshwater flows to counteract saltwater introgression due to rising sea levels, and we can assist in their migration inland, preserving their critical function in protecting coastlines and sequestering carbon.
Across the continent, a number of first nations are in the process of reintroducing bison to the grasslands in which they were once the primary grazer and an ecologically vital species. Initial experiences and evolutionary considerations suggest that this may be ecologically beneficial in terms of grassland biodiversity, carbon cycle, and resilience to climate change. However, these questions have not yet been studied at scale. In this lab, we will leverage remote sensing to scale up from ground measurements, establishing the large-scale patterns of bison impact.
Beaver dams are known to result in greener, more drought-resilient waterways in semi-arid environments. We are using computer vision to spot dams in satellite imagery, generating a large dataset that we can use to train models that will tell us what the ecological effects of a dam will be at any point on a waterway. The goal is to create a tool to guide efficient restoration through the introduction of small dams.
Markets in voluntary carbon credits are increasingly providing a flow of capital for regenerating ecosystems. The problem is, thriving and resilient ecosystems are not just carbon. We need to find ways to structure credits to incentivize the diverse and functional ecosystems we want, not merely high-concentrations of carbon. We will design the technological tools to support a market in bundled ecological credits.
We are building an accurate and global model for predicting potential rates of reforestation and resulting carbon sequestration. Such a model could have a transformational impact on global reforestation efforts by opening new streams of financing in the form of carbon credit futures.
Leveraging The Earthshot Institute’s broad scientific and technical expertise, the Impact and Risk Lab helps investors and governments who earnestly want to forecast, measure, and address the socio-ecological risks to and/or impacts from their work. For a given system, we build simple process-based models to identify key socio-ecological risks and outcomes. We then draw on big data to improve and train our models, generating quantitative predictions and developing measurement systems for verification.
