Abstract
Temperature and precipitation determine the conditions where plant species can occur. Despite their significance, to date, surprisingly few demographic field studies have considered the effects of abiotic drivers. This is problematic because anticipating the effect of global climate change on plant population viability requires understanding how weather variables affect population dynamics. One possible reason for omitting the effect of weather variables in demographic studies is the difficulty in detecting tight associations between vital rates and environmental drivers. In this paper, we applied Functional Linear Models (FLMs) to long-term demographic data of the perennial wildflower, Astragalus scaphoides, and explored sensitivity of the results to reduced amounts of data. We compared models of the effect of average temperature, total precipitation, or an integrated measure of drought intensity (standardized precipitation evapotranspiration index, SPEI), on plant vital rates. We found that transitions to flowering and recruitment in year t were highest if winter/spring of year t was wet (positive effect of SPEI). Counterintuitively, if the preceding spring of year t - 1 was wet, flowering probabilities were decreased (negative effect of SPEI). Survival of vegetative plants from t - 1 to t was also negatively affected by wet weather in the spring of year t - 1 and, for large plants, even wet weather in the spring of t - 2 had a negative effect. We assessed the integrated effect of all vital rates on life history performance by fitting FLMs to the asymptotic growth rate, log(λt). Log(λt) was highest if dry conditions in year t - 1 were followed by wet conditions in the year t. Overall, the positive effects of wet years exceeded their negative effects, suggesting that increasing frequency of drought conditions would reduce population viability of A.scaphoides. The drought signal weakened when reducing the number of monitoring years. Substituting space for time did not recover the weather signal, probably because the weather variables varied little between sites. We detected the SPEI signal when the analysis included data from two sites monitored over 20yr (2×20 observations), but not when analyzing data from four sites monitored over 10yr (4×10 observations).
Highlights
Only the positive effect of standardized precipitation evapotranspiration index (SPEI) over time lags 0 to À6 was significant for the observed population growth rate the sign of the signals is consistent with the log(kt) analysis
This study demonstrates clear associations between drought measured as SPEI and plant demography when using long-term demographic and climate data (≥20 years from two sites)
A. scaphoides populations do best if dry conditions in one growing season are followed by wet conditions in the following growing season
Summary
Temperature and precipitation are key drivers of plant population dynamics (e.g., Doak and Morris 2010, Nicole et al 2011, Salguero-Gomez et al 2012, Sletvold et al 2013, Dahlgren et al 2016) and are essential components for predicting the distribution of species in space and time (Huntley et al 1995, Carey 1996, Bakkenes et al 2002, Pearson et al 2002, Pearson and Dawson 2003, Box 1981).
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