An official website of the United States government
Summary Joshua trees are long‐lived perennial monocots native to the Mojave Desert in North America. Composed of two species,Yucca brevifoliaandY. jaegeriana(Asparagaceae), Joshua trees are imperiled by climate change, with decreases in suitable habitat predicted under future climate change scenarios. Relatively little is understood about the ecophysiology of Joshua trees across their range, including the extent to which populations are locally adapted or phenotypically plastic to environmental stress.Plants in our common gardens showed evidence of Crassulacean acid metabolism photosynthesis (CAM) in a pilot experiment, despite no prior report of this photosynthetic pathway in these species. We further studied the variation and strength of CAM within a single common garden, measuring seedlings representing populations across the range of the two species.A combination of physiology and transcriptomic data showed low levels of CAM that varied across populations but were unrelated to home environmental conditions. Gene expression confirmed CAM activity and further suggested differences in carbon and nitrogen metabolism betweenY. brevifoliaandY. jaegeriana.Together the results suggest greater physiological diversity between these species than initially expected, particularly at the seedling stage, with implications for future survival of Joshua trees under a warming climate.
more »
« less
Unprecedented distribution data for Joshua trees (Yucca brevifolia and Y. jaegeriana) reveal contemporary climate associations of a Mojave Desert icon
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.
more »
« less
- PAR ID:
- 10516841
- Publisher / Repository:
- Frontiers Media SA
- Date Published:
- Journal Name:
- Frontiers in Ecology and Evolution
- Volume:
- 11
- ISSN:
- 2296-701X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
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.more » « less
-
Abstract AimBiogeographers have used three primary data types to examine shifts in tree ranges in response to past climate change: fossil pollen, genetic data and contemporary occurrences. Although recent efforts have explored formal integration of these types of data, we have limited understanding of how integration affects estimates of range shift rates and their uncertainty. We compared estimates of biotic velocity (i.e. rate of species' range shifts) using each data type independently to estimates obtained using integrated models. LocationEastern North America. TaxonFraxinus pennsylvanicaMarshall (green ash). MethodsUsing fossil pollen, genomic data and modern occurrence data, we estimated biotic velocities directly from 24 species distribution models (SDMs) and 200 pollen surfaces created with a novel Bayesian spatio‐temporal model. We compared biotic velocity from these analyses to estimates based on coupled demographic‐coalescent simulations and Approximate Bayesian Computation that combined fossil pollen and SDMs with population genomic data collected across theF. pennsylvanicarange. ResultsPatterns and magnitude of biotic velocity over time varied by the method used to estimate past range dynamics. Estimates based on fossil pollen yielded the highest rates of range movement. Overall, integrating genetic data with other data types in our simulation‐based framework reduced apparent uncertainty in biotic velocity estimates and resulted in greater similarity in estimates between SDM‐ and pollen‐integrated analyses. Main ConclusionsBy reducing uncertainty in our assessments of range shifts, integration of data types improves our understanding of the past distribution of species. Based on these results, we propose further steps to reach the integration of these three lines of biogeographical evidence into a unified analytical framework.more » « less
-
Abstract AimSpecies distribution models (SDMs) are increasingly applied across macroscales using detection‐nondetection data. These models typically assume that a single set of regression coefficients can adequately describe species–environment relationships and/or population trends. However, such relationships often show nonlinear and/or spatially varying patterns that arise from complex interactions with abiotic and biotic processes that operate at different scales. Spatially varying coefficient (SVC) models can readily account for variability in the effects of environmental covariates. Yet, their use in ecology is relatively scarce due to gaps in understanding the inferential benefits that SVC models can provide compared to simpler frameworks. InnovationHere we demonstrate the inferential benefits of SVC SDMs, with a particular focus on how this approach can be used to generate and test ecological hypotheses regarding the drivers of spatial variability in population trends and species–environment relationships. We illustrate the inferential benefits of SVC SDMs with simulations and two case studies: one that assesses spatially varying trends of 51 forest bird species in the eastern United States over two decades and a second that evaluates spatial variability in the effects of five decades of land cover change on grasshopper sparrow (Ammodramus savannarum) occurrence across the continental United States. Main conclusionsWe found strong support for SVC SDMs compared to simpler alternatives in both empirical case studies. Factors operating at fine spatial scales, accounted for by the SVCs, were the primary divers of spatial variability in forest bird occurrence trends. Additionally, SVCs revealed complex species–habitat relationships with grassland and cropland area for grasshopper sparrow, providing nuanced insights into how future land use change may shape its distribution. These applications display the utility of SVC SDMs to help reveal the environmental factors that drive species distributions across both local and broad scales. We conclude by discussing the potential applications of SVC SDMs in ecology and conservation.more » « less
-
Summary Anthropogenetic climate change has caused range shifts among many species. Species distribution models (SDMs) are used to predict how species ranges may change in the future. However, most SDMs rarely consider how climate‐sensitive traits, such as phenology, which affect individuals' demography and fitness, may influence species' ranges.Using > 120 000 herbarium specimens representing 360 plant species distributed across the eastern United States, we developed a novel ‘phenology‐informed’ SDM that integrates phenological responses to changing climates. We compared the ranges of each species forecast by the phenology‐informed SDM with those from conventional SDMs. We further validated the modeling approach using hindcasting.When examining the range changes of all species, our phenology‐informed SDMs forecast less species loss and turnover under climate change than conventional SDMs. These results suggest that dynamic phenological responses of species may help them adjust their ecological niches and persist in their habitats as the climate changes.Plant phenology can modulate species' responses to climate change, mitigating its negative effects on species persistence. Further application of our framework will contribute to a generalized understanding of how traits affect species distributions along environmental gradients and facilitate the use of trait‐based SDMs across spatial and taxonomic scales.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3389/fevo.2023.1266892
