A colorful selection of pressed plant specimens featuring leaves and flowers

Artificial intelligence: Unlocking the Power of Plants and Fungi (Draft)

Artificial intelligence is revolutionizing botanical research, offering unprecedented tools to explore, conserve, and utilize plant and fungal diversity. NYBG is actively integrating AI into its research infrastructure and scientific endeavors, enhancing and accelerating work on species identification, climate mitigation, biodiversity conservation, remote sensing, land-use planning, and collections-based discovery.

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Accelerating Collections-Based Discovery

NYBG’s Steere Herbarium is adopting machine learning tools to accelerate the transcription and databasing of specimen labels, addressing a significant bottleneck in digitizing collections. By implementing tools such as VoucherVision, we hope to double the rate of label transcription, unlocking data from thousands of specimens to support global research and conservation efforts. We are also exploring AI applications for measuring and analyzing plant traits, such as leaf morphology and flowering time, from herbarium specimens, to enhance understanding of plant ecology and evolution. These advances contribute to more efficient data processing and open new avenues for research and discovery.

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AI in Climate Mitigation and Biodiversity Conservation

AI’s capacity to analyze vast datasets is instrumental in addressing climate change and biodiversity loss. At NYBG, AI models predict how plant and fungal species respond to environmental change, informing conservation strategies and habitat restoration efforts. By identifying species resilient to climate fluctuations, AI aids in selecting candidates for reforestation and ecosystem rehabilitation projects, enhancing carbon sequestration and ecosystem stability. Image analysis algorithms developed to identify disease symptoms can assist in detecting and monitoring plant diseases, enabling early intervention that will reduce crop losses and support sustainable agriculture and food security.

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Remote Sensing and Land-use Planning

Integrating AI with remote sensing technologies, such as satellite imagery and drones, allows NYBG to monitor large-scale ecological patterns and land-use changes. AI algorithms process these data to detect deforestation, urban expansion, and habitat fragmentation, providing critical insights for conservation planning and policy development. This approach enables proactive measures to protect vital ecosystems and maintain biodiversity.

A dried plant labeled for an herbarium specimen

Advancements in Species Identification

Accurate species identification is fundamental to botanical science. NYBG is leveraging AI-powered computer vision to automate and refine this process. By training machine learning algorithms on extensive datasets of plant images, AI can swiftly and accurately identify species from photographs, facilitating rapid assessments of biodiversity and aiding in the discovery of new species.

Featured publication: New Phytologist, “AI for Difficult Herbarium Specimens“ featuring Damon Little, NYBG

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NYBG’s Vision for the Future

Embracing AI aligns with NYBG’s mission to advance botanical science and environmental stewardship. By integrating AI into research and conservation practices, NYBG enhances its capacity to address global challenges, from climate change to food security. These technologies not only accelerate scientific discovery but also democratize data access, engaging a broader community in the collective effort to understand and protect plant and fungal diversity.

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Flagship Project: Accelerating Species Discovery

NYBG is honored to be one of 15 global recipients of Phase II of the Bezos Earth Fund’s AI Grand Challenge for Climate Change and Nature to harnesses the power of cutting-edge Artificial Intelligence (AI) to unlock the vast, underutilized data in herbarium collections. Herbaria are scientific collections of plant specimens that contain data about species’ distributions, traits, and environmental responses that are critical for conservation, restoration, ecology, and foundational biology. Using AI, we are building scalable, open-access tools that can transform biodiversity science and conservation planning by unlocking the extraordinary amount of data contained in herbaria and other biodiversity collections worldwide.

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