Reconstructing 120years of climate change impacts on Joshua tree flowering

Quantifying how global change impacts wild populations remains challenging, especially for species poorly represented by systematic datasets. Here, we infer climate change effects on masting by Joshua trees (Yucca brevifolia and Y. jaegeriana), keystone perennials of the Mojave Desert, from 15 years...

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Bibliographic Details
Published in:Ecology letters 2024-08, Vol.27 (8)
Main Authors: Yoder, Jeremy B, Andrade, Ana Karina, DeFalco, Lesley A, Esque, Todd C, Carlson, Colin J, Shryock, Daniel F, Yeager, Ray, Smith, Christopher I
Format: Article
Language:English
Subjects:
Annual precipitation
Biodiversity
Climate change
Crowdsourcing
Drought
Environmental impact
Flowering
Frequency variation
Hindcasting
Machine learning
Yucca brevifolia
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Summary:Quantifying how global change impacts wild populations remains challenging, especially for species poorly represented by systematic datasets. Here, we infer climate change effects on masting by Joshua trees (Yucca brevifolia and Y. jaegeriana), keystone perennials of the Mojave Desert, from 15 years of crowdsourced observations. We annotated phenophase in 10,212 geo‐referenced images of Joshua trees on the iNaturalist crowdsourcing platform, and used them to train machine learning models predicting flowering from annual weather records. Hindcasting to 1900 with a trained model successfully recovers flowering events in independent historical records and reveals a slightly rising frequency of conditions supporting flowering since the early 20th Century. This reflects increased variation in annual precipitation, which drives masting events in wet years—but also increasing temperatures and drought stress, which may have net negative impacts on recruitment. Our findings reaffirm the value of crowdsourcing for understanding climate change impacts on biodiversity.
ISSN:1461-023X
1461-0248
DOI:10.1111/ele.14478