Checking billy barr’s snow log…
Evolutionary adaptation can allow a population to persist in the face of a new environmental challenge. With many populations now threatened by environmental change, it is important to understand whether this process of evolutionary rescue is feasible under natural conditions, yet work on this topic has been largely theoretical. We used unique long-term data to parameterize deterministic and stochastic models of the contribution of one trait to evolutionary rescue using field estimates for the subalpine plant Ipomopsis aggregata and hybrids with its close relative I. tenuituba. In the absence of evolution or plasticity, the two studied populations are projected to go locally extinct due to earlier snowmelt under climate change, which imposes drought conditions. Phenotypic selection on specific leaf area (SLA) was estimated in 12 years and multiple populations. Those data on selection and its environmental sensitivity to annual snowmelt timing in the spring were combined with previous data on heritability of the trait, phenotypic plasticity of the trait, and the impact of snowmelt timing on mean absolute fitness. Selection favored low values of SLA (thicker leaves). The evolutionary response to selection on that single trait was insufficient to allow evolutionary rescue by itself, but in combination with phenotypic plasticity it promoted evolutionary rescue in one of the two populations. The number of years until population size would stop declining and begin to rise again was heavily dependent upon stochastic environmental changes in snowmelt timing around the trend line. Our study illustrates how field estimates of quantitative genetic parameters can be used to predict the likelihood of evolutionary rescue. Although a complete set of parameter estimates are generally unavailable, it may also be possible to predict the general likelihood of evolutionary rescue based on published ranges for phenotypic selection and heritability and the extent to which early snowmelt impacts fitness.
Knowledge graph centered on Data for: Predicting the contribution of single tr with 15 nodes and 90 connections. Top connected: Rocky Mountain Biological Laboratory, Scarlet Gilia, Slender-tube Skyrocket, Penstemon strictus, Diane R. Campbell.
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