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IntroductionForecasting range shifts in response to climate change requires accurate species distribution models (SDMs), particularly at the margins of species' ranges. However, most studies producing SDMs rely on sparse species occurrence datasets from herbarium records and public databases, along with random pseudoabsences. While environmental covariates used to fit SDMS are increasingly precise due to satellite data, the availability of species occurrence records is still a large source of bias in model predictions. We developed distribution models for hybridizing sister species of western and eastern Joshua trees (Yucca brevifoliaandY. jaegeriana, respectively), iconic Mojave Desert species that are threatened by climate change and habitat loss. MethodsWe conducted an intensive visual grid search of online satellite imagery for 672,043 0.25 km²grid cells to identify the two species' presences and absences on the landscape with exceptional resolution, and field validated 29,050 cells in 15,001 km of driving. We used the resulting presence/absence data to train SDMs for each Joshua tree species, revealing the contemporary environmental gradients (during the past 40 years) with greatest influence on the current distribution of adult trees. ResultsWhile the environments occupied byY. brevifoliaandY. jaegerianawere similar in total aridity, they differed with respect to seasonal precipitation and temperature ranges, suggesting the two species may have differing responses to climate change. Moreover, the species showed differing potential to occupy each other's geographic ranges: modeled potential habitat forY. jaegerianaextends throughout the range ofY. brevifolia, while potential habitat forY. brevifoliais not well represented within the range ofY. jaegeriana. DiscussionBy reproducing the current range of the Joshua trees with high fidelity, our dataset can serve as a baseline for future research, monitoring, and management of this species, including an increased understanding of dynamics at the trailing and leading margins of the species' ranges and potential for climate refugia. 

Abstract 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 brevifoliaandY. 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. 

Yucca moths ( Tegeticula and Parategeticula) are specialized pollinators of yucca plants, possessing unique, tentacle-like mouthparts used to actively collect pollen and deposit it onto the flowers of their hosts. The moths' larvae feed on the developing seeds and fruit tissue. First described in 1873, the yucca–yucca moth pollination system is now considered the archetypical example of a coevolved intimate mutualism. Research conducted over the past three decades has transformed our understanding of yucca moth diversity and host plant interactions. We summarize the current understanding of the diversity, ecology, and evolution of this group, review evidence for coevolution of the insects and their hosts, and describe how the nature of the interaction varies across evolutionary time and ecological contexts. Finally, we identify unresolved questions and areas for future research.