Phenological plasticity is a poor predictor of subalpine plant population performance following experimental climate change

Abstract

Phenological shifts, changes in the seasonal timing of life cycle events, are among the best documented responses of species to climate change. However, the consequences of these phenological shifts for population dynamics remain unclear. Population growth could be enhanced if species that advance their phenology benefit from longer growing seasons and gain a pre-emptive advantage in resource competition. However, it might also be reduced if phenological advances increase exposure to stresses, such as herbivores and, in colder climates, harsh abiotic conditions early in the growing season. We exposed subalpine grasslands to ~ 3 K of warming by transplanting intact turfs from 2000 m to 1400 m elevation in the eastern Swiss Alps, with turfs transplanted within the 2000 m site acting as a control. In the first growing season after transplantation, we recorded species' flowering phenology at both elevations. We also measured species' cover change for three consecutive years as a measure of plant performance. We used models to estimate species' phenological plasticity (the response of flowering time to the change in climate) and analysed its relationship with cover changes following climate change. The phenological plasticity of the 18 species in our study varied widely but was unrelated to their changes in cover. Moreover, early- and late-flowering species did not differ in their cover response to warming, nor in the relationship between cover changes and phenological plasticity. These results were replicated in a similar transplant experiment within the same subalpine community, established one year earlier and using larger turfs. We discuss the various ecological processes that can be affected by phenological shifts, and argue why the population-level consequences of these shifts are likely to be species- and context-specific. Our results highlight the importance of testing assumptions about how warming-induced changes in phenotypic traits, like phenology, impact population dynamics.

Keywords: climate change; demography; global warming; phenological shifts; phenology; phenotypic plasticity; population dynamics; transplant experiment.

Figure 1

Mean daily temperatures during the growing season of 2014 and the preceding winter, recorded with temperature loggers placed at ground level on the high-elevation (blue line) and low-elevation (red line) sites.

Figure 2

(a) Species’ first flowering time in turfs transplanted to lower elevation (red triangles: climate change treatment) or within the same elevation (blue circles: control treatment). The arrows indicate the magnitude and direction of the phenological shift due to simulated climate change, estimated with a multiple regression of flowering time as a function of treatment, controlling for differences in species’ initial cover. Estimated effects (± 1 standard error) of climate change on species’ demographic trends (measured by the log ratio of final to initial percent cover) from a multiple regression with species’ initial cover as a covariate, for the main (b) and 4-year (c) experiments.

Figure 3

Relationship between phenological shifts and cover responses to climate change for early- and late-flowering species (black and grey dots, respectively) in the main (a) and 4-year (b) experiments. Climate change was simulated by transplanting turfs to a site 600 m lower in elevation (i.e., ca. 3 K warmer) than the site of origin. Phenological shift is the effect of climate change on species first flowering time estimated with a multiple regression including species initial cover as a covariate. Cover response to climate change is the effect of downslope transplantation on the logarithm of the ratio of final to initial cover of a species in a turf. This effect was estimated with a multiple regression including species’ initial cover as covariate. Mean estimates (± 1 standard error) are shown.

Figure 4

The demographic consequences of phenological plasticity depend on whether environmental cues regulating phenology maintain their association with the timing of optimal conditions for life history events. (a) Phenology has evolved to rely on cues that correlate with the timing of optimal conditions, such as low frost risk and low density of antagonist species. (b) If climate change alters the timing of these conditions, but not their association with phenological cues, then phenological plasticity should be advantageous. (c) However, when climate change alters the temporal association between phenological cues and optimal conditions, plasticity can be detrimental.