This is one outlet's own report from Phys.org — the article as it was filed.
AIPROPX ReportPhys.org · 1h ago
AI and 8 million digitized plant specimens reveal how the climate is changing nature in large parts of the world
edited by Swati Mestri , reviewed by Robert Egan
This article has been reviewed according to Science X's editorial process and policies . Editors have highlighted the following attributes while ensuring the content's credibility:
Add as preferred source AI optimists will be encouraged by a recent report on the state of the world's plants and fungi by the Royal Botanic Gardens, Kew.
The report examines the role that digitization and AI are playing in botany and nature management. Four hundred researchers in 40 countries contributed to the report, including scientists from NTNU.
James Speed, a professor of plant ecology at the NTNU University Museum in Trondheim, was one of the contributors to the report.
"For hundreds of years, naturalists have collected plants and fungi, pressed and dried them so they could be preserved for the future in herbaria around the world. In recent years, more and more specimens have been photographed and made available online," Speed explains.
"More than 145 million plant and fungi preparations have been digitized worldwide, from more than 170 institutions in 40 countries. This opens up completely new opportunities for research."
David Williamson is a postdoctoral researcher in machine learning for natural history at the NTNU University Museum.
Williamson, along with Speed and botanists from the Trondheim herbarium, trained a machine learning model to recognize whether plants are in flower on digitized herbarium specimens. The model was used on 8 million preserved specimens collected from around the world, representing 200,000 species.
"What's so exciting is that we're taking collections that have existed for centuries, combining them with machine learning and AI technologies that are barely five years old, and we can then answer big, important questions about nature," Williamson says.
"Machines can't do the work of biologists, but they can help experts analyze datasets that would previously have taken a lifetime," Williamson says. "By way of comparison, the machine here took one week to do something that would have taken a human about 40,000 hours."
To put that number in perspective, 40,000 hours equal about 20 working years.
"These analyses showed that global flowering times have shifted by an average of 2.5 days per decade over the past century," Speed says.
Flowering has shifted both earlier and later, and the differences are greatest in tropical areas.
The greatest temperature increases due to climate change tend to be in the far north, so researchers were surprised to learn that the most dramatic flowering changes were in the tropics.
"In the tropics, flowering is more closely related to precipitation, and in a changing climate, the rainy season can come earlier, later—or not at all," Speed explains.
When the flowering timeline changes, a mismatch can arise between flowering and pollinating insects. This can, in turn, have ripple effects, for example, on insect-eating birds and food production.
The effects of climate change on flowering time are only one of the questions that digital herbarium specimens can answer. The same methods can be used in the fight against species extinction.
Millions of plants and fungi are still unknown to science. Fungi are the basis for almost all life on Earth, but more than 90% of species are still unmapped.
Meanwhile, species extinction and climate change are accelerating, with the result that some species are disappearing faster than scientists can map them. Just 1,000 plant species have been officially declared extinct, but the actual number is likely to be much higher.
AI and machine learning cannot solve these problems, but they can provide scientists with far-reaching mapping tools.
Statistical models can also calculate the probability that a species is extinct, as opposed to undiscovered. AI can recognize unknown species in digitized collections and flag them for experts, speeding up the naming process.
"I think the potential for AI is enormous, but it is still currently potential," says Martin Cheek, a researcher and taxonomist at the Royal Botanic Gardens, Kew, and co-author of the State of the World's Plants and Fungi report.
"It would be very useful to be able to name stuff reliably more rapidly. You'd still need taxonomists to check those names were accurate and that there were no mistakes. But with less time spent on identifying the more common 90% of species, we'd have more time to get on and describe the unknown species and to do things to conserve the threatened species."
Before getting carried away by technological optimism, it is worth considering that less than 16% of the world's herbarium specimens are digitally accessible. Furthermore, the biggest gaps are found in countries with rich biodiversity, where collections are understaffed and underdocumented and not connected to global databases.
Williamson concurs: "While AI is a useful tool for researchers, it doesn't think for us. Our models are only as good as the data they are trained on. Experts need to be involved at every step—from asking the right research questions to validating the model design and interpreting the results."
The NTNU postdoctoral researcher adds that new technologies underscore the critical importance of the work that humans are doing on museum collections.
Report: State of the World's Plants and Fungi
Provided by Norwegian University of Science and Technology
Swati Mestri holds a bachelor's degree in Electronics Engineering and has worked as a content editor since 2019. She has experience editing research documents across technology, health care, and materials science, and has a particular interest in technology and space. Full profile →
Bachelor's in mathematical biology, Master's in creative writing. Well-traveled with unique perspectives on science and language. Full profile →
AIPROPX is an independent multi-source news index — we track, compare, and connect coverage from across the web into one place you won't find anywhere else.
