Reconstructing 120 years 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 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 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 o..., , , # Studying Joshua tree flowering with crowd-sourced observations

Readme updated 13 June 2024.

## Project description

This repo contains code to (1) use the [iNaturalist](https://inaturalist.org) API to download species observations based on phenology annotations, by modifying code from the [`rinat`](https://cran.r-project.org/web/packages/rinat/index.html) package, and (2) model the relationship between flowering and weather using spatially interpolated records from [PRISM](https://prism.oregonstate.edu) and Bayesian additive regression tree methods implemented in [`dbarts`](https://cran.r-project.org/web/packages/dbarts) with utilities from [`embarcadero`](https://github.com/cjcarlson/embarcadero).

The code is provided as supporting data for

> Yoder JB, AK Andrade, LA Defalco, TC Esque, CJ Carlson, DF Shryock, R Yeager, and CI Smith. 2024. Reconstructing 120 years of climate change impacts on Joshua tree flowering. Ecology Letters.

## Contents

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