Phenology is one of the best ways to observe effects of climate change on plant or animal life cycles, but there are few long-term records of this important ecological component of life histories. Some proxies have been described, such as using herbarium collections to reconstruct flowering dates or agricultural harvest records to gain insights into historical temperatures. At high altitudes, snowpack and snowmelt date, which can have important effects on ecosystem phenology, are sometimes observed directly and recorded, but long-term records are not typically available. To reconstruct their history it may be possible to use data from stream gages with good hydrograph data such as dates and volumes of peak runoff. We linked observed (1975-2017) snowpack and snowmelt from near the Rocky Mountain Biological Laboratory to historical data (1935 – 2017) from a stream gage on the East River at Almont, Colorado, 35 km away and 479m lower. We used the date of peak runoff to estimate date of snowmelt in Gothic, and peak volume of runoff to estimate the winter snowpack. We estimated the dates of snowmelt and total snowfall at our study site for the pre-observation period 1935-1974.
Results/Conclusions
The date of peak runoff from 1975-2017 ranged from 16 May (2001) to 25 June (1983), with a mean of 3 June. In the earlier time period it ranged from 6 May (1936) to 29 June (1957) (mean 1 June). Snowfall from 1975-2017 ranged from 474cm to 1,641cm (mean 1,080cm), and estimates for the earlier time period range from 856cm to 1759cm (mean 1177 cm). We used these data to estimate the date of snowmelt in Gothic from 1935 – 1974, ranging from 9 May (1954) to 21 June (1957) with a mean of 24 May, compared to a range of 23 April (2012) to 19 June (1995), mean 20 May. There is a strong correlation between snowmelt date and flowering phenology for 120+ species of wildflowers for which we have data, and for a few species, also a strong correlation between snowfall total and flower abundance the next summer. Thus by estimating historic snowpack and snowmelt, we can extend our understanding of how the phenology and abundance of wildflowers have changed, and potentially how that affected pollinator populations. This technique adds to the toolkit ecologists can use to estimate important environmental and ecological parameters from pre-observation periods.