This is an audio long read from nature.

In this episode, I rarely get outside.

Scientists stitch fieldwork in the age of AI.

Written by Ashling Irwin and read by me, Benjamin Thompson.

Todayo Ramirez Perada studied the timing of plant flowering for his PhD, but he didn't touch a

single petal. Instead, he developed a machine learning algorithm to analyze the digitized captions

of one million herbarium species, which showed him how flowering times are changing with rising temperatures.

Ramirez-Pirada's work has helped to solve an important mystery in ecology, showing that as

temperatures change, plants shift their flowering times to cope with the heat, rather than adapting

through natural selection. Yet his work so far has been almost

entirely computer-based. I had to do very little experimental or field work, says Ramirez-Pirada,

who did his PhD at the University of California, Santa Barbara. Ramirez-Pirada's work is typical

of a change that is reaching into every part of

ecology. Whatever scientists are analysing, digitise specimens, images of the natural world,

DNA samples, or data streaming in from sensors, many are doing it indoors. The technologies

are creating a world that can be monitored at times,

places and scales that were previously unimaginable. We are moving towards the, quote,

fully automated monitoring of ecological communities, wrote Mark Besant, a marine scientist

at the Sorbonne University Ocean Observatory in Banules-Huilmer, France,

in a 2022 paper.

Many ecologists say this revolution offers huge potential for understanding the biodiversity crisis

and discerning patterns of global change.

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