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Abstract In Mediterranean climates, the timing of seasonal rains determines germination, flowering phenology and fitness. As climate change alters seasonal precipitation patterns, it is important to ask how these changes will affect the phenology and fitness of plant populations. We addressed this question experimentally with the annual plant speciesArabidopsis thaliana.In a first experiment, we manipulated the date of rainfall onset and recorded germination phenology on sand and soil substrates. In a second experiment, we manipulated germination date, growing season length and mid‐season drought to measure their effects on flowering time and fitness. Within each experiment, we manipulated seed dormancy and flowering time using multilocus near‐isogenic lines segregating strong and weak alleles of the seed dormancy geneDOG1and the flowering time geneFRI. We synthesized germination phenology data from the first experiment with fitness functions from the second experiment to project population fitness under different seasonal rainfall scenarios.Germination phenology tracked rainfall onset but was slower and more variable on sand than on soil. Many seeds dispersed on sand in spring and summer delayed germination until the cooler temperatures of autumn. The high‐dormancyDOG1allele also prevented immediate germination in spring and summer. Germination timing strongly affected plant fitness. Fecundity was highest in the October germination cohort and declined in spring germinants. The late floweringFRIallele had lower fecundity, especially in early fall and spring cohorts. Projections of population fitness revealed that: (1) Later onset of autumn rains will negatively affect population fitness. (2) Slow, variable germination on sand buffers populations against fitness impacts of variable spring and summer rainfall. (3) Seasonal selection favours high dormancy and early flowering genotypes in a Mediterranean climate with hot dry summers. The high‐dormancyDOG1allele delayed germination of spring‐dispersed fresh seeds until more favourable early fall conditions, resulting in higher projected population fitness.These findings suggest that Mediterranean annual plant populations are vulnerable to changes in seasonal precipitation, especially in California where rainfall onset is already occurring later. The fitness advantage of highly dormant, early flowering genotypes helps explain the prevalence of this strategy in Mediterranean populations. Read the freePlain Language Summaryfor this article on the Journal blog.
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This content will become publicly available on December 1, 2025
Modeling cheatgrass distribution, abundance, and response to climate change as a function of soil microclimate
Abstract Exotic annual grass invasions in water‐limited systems cause degradation of native plant and animal communities and increased fire risk. The life history of invasive annual grasses allows for high sensitivity to interannual variability in weather. Current distribution and abundance models derived from remote sensing, however, provide only a coarse understanding of how species respond to weather, making it difficult to anticipate how climate change will affect vulnerability to invasion. Here, we derived germination covariates (rate sums) from mechanistic germination and soil microclimate models to quantify the favorability of soil microclimate for cheatgrass (Bromus tectorumL.) establishment and growth across 30 years at 2662 sites across the sagebrush steppe system in the western United States. Our approach, using four bioclimatic covariates alone, predicted cheatgrass distribution with accuracy comparable to previous models fit using many years of remotely‐sensed imagery. Accuracy metrics from our out‐of‐sample testing dataset indicate that our model predicted distribution well (72% overall accuracy) but explained patterns of abundance poorly (R2 = 0.22). Climatic suitability for cheatgrass presence depended on both spatial (mean) and temporal (annual anomaly) variation of fall and spring rate sums. Sites that on average have warm and wet fall soils and warm and wet spring soils (high rate sums during these periods) were predicted to have a high abundance of cheatgrass. Interannual variation in fall soil conditions had a greater impact on cheatgrass presence and abundance than spring conditions. Our model predicts that climate change has already affected cheatgrass distribution with suitable microclimatic conditions expanding 10%–17% from 1989 to 2019 across all aspects at low‐ to mid‐elevation sites, while high‐ elevation sites (>2100 m) remain unfavorable for cheatgrass due to cold spring and fall soils.
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- Award ID(s):
- 1927282
- PAR ID:
- 10563440
- Publisher / Repository:
- Wiley
- Date Published:
- Journal Name:
- Ecological Applications
- Volume:
- 34
- Issue:
- 8
- ISSN:
- 1051-0761
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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