• Energy Research

AbstractWidespread shifts in phenological events in response to climate change have inspired phenological monitoring programs and new methods for analyzing sparse phenological data. For example, the Weibull distribution is increasingly used to estimate the dates of hard‐to‐observe phenological events, such as first and last flowering dates, in sparsely or unsystematically sampled data sets. In contrast, recent application of the Weibull estimator to an intensely and systematically sampled flowering phenology data set unexpectedly found different results than a previous analysis of the observed dates; at issue is whether different aspects of phenological curves shift uniformly or disparately. We used this case study to (1) raise conceptual and technical issues around when and how to infer phenological events using Weibull (or other) estimates, and (2) re‐analyze the data set in question with these considerations in mind. Our re‐analysis using the Weibull estimator shows that first, peak, and last flowering dates shift disparately through time, supporting the original analysis of the observed dates. We show that off‐the‐shelf usage of statistical estimators to generalize about an unsampled population may be inappropriate without considering how well sampled the focal study population is and how biological features such as habitat heterogeneity influence the natural scope of the unsampled population.

Annual rates of sex- and size-specific growth and survival from tagged plants at four populations (1978-1981). See README.txt for column descriptions.

AbstractOrganisms use environmental cues to align their phenology—the timing of life events—with sets of abiotic and biotic conditions that favor the successful completion of their life cycle. Climate change has altered the environmental cues organisms use to track climate, leading to shifts in phenology with the potential to affect a variety of ecological processes. Understanding the drivers of phenological shifts is critical to predicting future responses, but disentangling the effects of temperature from precipitation on phenology is often challenging because they tend to covary. We addressed this knowledge gap in a high‐elevation environment where phenological shifts are associated with both the timing of spring snow melt and temperature. We factorially crossed early snow melt and passive warming treatments to (1) disentangle the effects of snow melt timing and warming on the phenology of flowering and fruiting and reproductive success in three subalpine plant species (Delphinium nuttallianum, Valeriana edulis, and Potentilla pulcherrima); and (2) assess whether snow melt acts via temperature accumulation or some other aspect of the environment (e.g., soil moisture) to affect phenological events. Both the timing and duration of flowering and fruiting responded to the climate treatments, but the effect of snow melt timing and warming varied among species and phenological stages. The combined effects of the treatments on phenology were always additive, and the snow melt treatment often affected phenology even when the warming treatment did not. Despite marked responses of phenology to climate manipulations, the species showed little change in reproductive success, with only one species producing fewer seeds in response to warming (Delphinium, −56%). We also found that snow melt timing can act both through temperature accumulation and as a distinct cue for phenology, and these effects are not mutually exclusive. Our results show that one environmental cue, here snow melt timing, may act through multiple mechanisms to shift phenology.

Pollen analogue (fluorescent dye) transfer by Valeriana edulis pollinators from dyed males to surrounding females. See README.txt for column descriptions.

This .zip archive contains a shapefile (including .shp, .shx, .dbf, and .prj components) that describes the boundary of a representative plot of Valeriana edulis plants growing at Emerald Lake.

Estimation of the mating function – how local operational sex ratio affects female reproductive success – of Valeriana edulis. This script includes a simulation of pollen limitation across a range of operational sex ratios.

Carbon isotope ratios of Valeriana edulis leaf samples used to test for sex differences in integrated water use efficiency. See README.txt for column descriptions.

The phenology of vegetation, namely leaf-out and senescence, can influence the Earth's climate over regional spatial scales and long time periods (e.g., over 30 years or more), in addition to microclimates over local spatial scales and shorter time periods (weeks to months). However, the effects of flowers on climate and microclimate are unknown. We investigate whether flowers can influence light reflected by the land surface and soil microclimate in a subalpine meadow. We conducted a flower removal experiment with a common sunflower species, Helianthella quinquenervis, for 3 years (2015, 2017, and 2019). The flower removal treatment simulates the appearance of the meadow when Helianthella flowers earlier under climate change and loses its flowers to frost (other plant structures are not damaged by frost). We test the hypotheses that a reduction in cover of yellow flowers leads to a greener land surface, lower reflectance, warmer and drier soils, and increased plant water stress. Flower removal plots are greener, reflect less light, exhibit up to 1.2 °C warmer soil temperatures during the warmest daylight hours, and contain ca. 1% less soil moisture compared to controls. However, soils were warmer in only 2 of the 3 years, when flower abundance was high. Helianthella water use efficiency did not differ between removal and control plots. Our study provides evidence for a previously undocumented effect of flowers on soil microclimate, an effect that is likely mediated by climate change and flowering phenology. Many anthropogenic environmental changes alter landscape albedo, all of which could be mediated by flowers: climate change, plant invasions, and agriculture. This study highlights how further consideration of the effects of flowers on land surface albedo could improve our understanding of the effects of vegetation on microclimate.

Snowmelt data used to test for an effect of elevation on snowmelt date. See README.txt for column descriptions.