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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.
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Clustering future scenarios based on predicted range maps
Abstract Predictions of biodiversity trajectories under climate change are crucial in order to act effectively in maintaining the diversity of species. In many ecological applications, future predictions are made under various global warming scenarios, as described by a range of different climate models. We propose a clustering methodology to synthesize and interpret the outputs of these various predictions.We propose an interpretable and flexible two‐step methodology to measure the similarity between predicted species range maps and to cluster the future scenario predictions utilizing a spectral clustering technique. We implement and provide code for this method.We find that clustering based on predicted species range maps is mainly driven by the amount of warming rather than climate model or future scenario. We contrast this with clustering based only on predicted climate variables, which is driven primarily by climate models, that is, scenarios of the same climate model are clustered together, even when the amount of warming input to the models is varied.The differences between species‐based and climate‐based clusterings illustrate that it is crucial to incorporate ecological information to understand the relevant differences between climate models. Our findings can be used to better synthesize forecasts of biodiversity change under the wide spectrum of results that emerge when considering potential future scenarios.
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- PAR ID:
- 10580765
- Publisher / Repository:
- Wiley
- Date Published:
- Journal Name:
- Methods in Ecology and Evolution
- Volume:
- 14
- Issue:
- 5
- ISSN:
- 2041-210X
- Page Range / eLocation ID:
- 1346 to 1360
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1111/2041-210X.14080
