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Quantifying species’ niches across a clade reveals how environmental tolerances evolve, and offers insights into present and future distributions. We use herbarium specimens to explore climate niche evolution across 14 annual species of theStreptanthus(s.l.) clade (Brassicaceae), which originated in deserts and diversified into cooler, moister areas. To understand how climate niches evolved, we used historical climate records to estimate each species’ 1) classic annual climate niche, averaged over specimen collection sites; 2) growing season niche, from estimated specimen germination date to collection date, averaged across specimens (specimen-specific niche); and 3) standardized seasonal niche based on average growing seasons of all species (clade-seasonal niche). In addition to estimating how phenological variation maps onto climate niche evolution, we explored how spatial refugia shape the climate experienced by species by 1) analyzing how field soil texture changes relative to the climate space that species occupy and 2) comparing soil water holding capacity from each specimen locality to that of surrounding areas. Specimen-specific niches exhibited less clade-wide variation in climatic water deficit (CWD) than did annual or clade-seasonal niches, and specimen-specific temperature niches showed no phylogenetic signal, in contrast to annual and clade-seasonal temperature niches. Species occupying cooler regions tracked hotter and drier climates by growing later into the summer, and by inhabiting refugia on drought-prone soils. These results underscore how phenological shifts, spatial refugia, and germination timing shape “lived” climate. Despite occupying a large range of annual climates, we found these species are constrained in the conditions under which they thrive.
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On the spatial and temporal shift in the archetypal seasonal temperature cycle as driven by annual and semi‐annual harmonics
Abstract Statistical methods are required to evaluate and quantify the uncertainty in environmental processes, such as land and sea surface temperature, in a changing climate. Typically, annual harmonics are used to characterize the variation in the seasonal temperature cycle. However, an often overlooked feature of the climate seasonal cycle is the semi‐annual harmonic, which can account for a significant portion of the variance of the seasonal cycle and varies in amplitude and phase across space. Together, the spatial variation in the annual and semi‐annual harmonics can play an important role in driving processes that are tied to seasonality (e.g., ecological and agricultural processes). We propose a multivariate spatiotemporal model to quantify the spatial and temporal change in minimum and maximum temperature seasonal cycles as a function of the annual and semi‐annual harmonics. Our approach captures spatial dependence, temporal dynamics, and multivariate dependence of these harmonics through spatially and temporally varying coefficients. We apply the model to minimum and maximum temperature over North American for the years 1979–2018. Formal model inference within the Bayesian paradigm enables the identification of regions experiencing significant changes in minimum and maximum temperature seasonal cycles due to the relative effects of changes in the two harmonics.
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- PAR ID:
- 10449980
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Environmetrics
- Volume:
- 32
- Issue:
- 6
- ISSN:
- 1180-4009
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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