Community-level phenological response to climate change

Abstract

Climate change may disrupt interspecies phenological synchrony, with adverse consequences to ecosystem functioning. We present here a 40-y-long time series on 10,425 dates that were systematically collected in a single Russian locality for 97 plant, 78 bird, 10 herptile, 19 insect, and 9 fungal phenological events, as well as for 77 climatic events related to temperature, precipitation, snow, ice, and frost. We show that species are shifting their phenologies at dissimilar rates, partly because they respond to different climatic factors, which in turn are shifting at dissimilar rates. Plants have advanced their spring phenology even faster than average temperature has increased, whereas migratory birds have shown more divergent responses and shifted, on average, less than plants. Phenological events of birds and insects were mainly triggered by climate cues (variation in temperature and snow and ice cover) occurring over the course of short periods, whereas many plants, herptiles, and fungi were affected by long-term climatic averages. Year-to-year variation in plants, herptiles, and insects showed a high degree of synchrony, whereas the phenological timing of fungi did not correlate with any other taxonomic group. In many cases, species that are synchronous in their year-to-year dynamics have also shifted in congruence, suggesting that climate change may have disrupted phenological synchrony less than has been previously assumed. Our results illustrate how a multidimensional change in the physical environment has translated into a community-level change in phenology.

Keywords: boreal forest; global warming; mismatch; trophic interactions.

Fig. 1.

Seasonal patterns of temperature, precipitation, and snow cover. The upper panels (A–C) show averages over the study period, and the lower panels (D–F) show the mean annual change (the slope of linear regression for climatic variable vs. year) for temperature (°C; A and D), precipitation (mm/day; B, E), and snow cover (cm; C, F). For temperature, black corresponds to daily mean, blue to daily minimum, and red to daily maximum. All data averaged over 10-d periods. The lines show periodic regressions. To measure the rate of thermal change in the units of days, we examined the time derivative of the periodic regression line for mean temperature (A). We defined the mean date of spring and the mean date of autumn as the times at which the derivative was minimized and maximized, respectively. We computed the change in spring (autumn) temperature by averaging the slope (D) during the period of 0.3 y centered at the mean date of spring and autumn, yielding 0.027 °C and 0.039 °C, respectively. Given the rate at which spring and autumn advance (slope of periodic regression, 0.23 °C per day for both), the changes in temperature correspond to the shifts of −0.12 and 0.17 d/y for spring and autumn, respectively.

Fig. 2.

Patterns of climatic and phenological shift and variance. (A) Phenological shifts for the first occurrence of the common lizard (Zootoca vivipara; cyan), the start of the display flight of the Eurasian woodcock (Scolopax rusticola; blue), and the climatic event of daily average temperature moving above 0 °C (black). The lizard, bird, and temperature events have shifted at rates of −0.36, −0.39, and −0.19 (day/year), and their phenological variances are 7.3², 5.8², and 13.9² (day²), respectively. (B–E) Dots depict shifts (day/year) in plant phenology (B); bird phenology (C); insect, fungal, and herptile phenology (D); and climatic events (E). (F) Distributions of residual variances. The lines in B, C, and E show linear regression models through the part of the year with the most data (spring for bird and plant events and winter for weather events). The circles indicate shifts greater than 0.5 for which the location of the dot has been truncated in the figure. Significant shifts (P < 0.05; 61/213 phenological events and 15/77 climatic events) are indicated with a white center. The thick gray lines depict the pace of climate change from the point of view of average temperature (Fig. 1). (Left) Color key of the different taxonomical and climatic groups.

Fig. 3.

Year-to-year variation in phenological timing explained by climatic variation. (A) Number of climatic variables included in the selected model of each phenological event. (B and C) Kinds of climatic variables included in the models: (B) type of climatic variable and (C) period during which the climatic variable was averaged. Above the bars are shown the numbers of data points from which the percentages were calculated.

Fig. 4.

Patterns of phenological synchrony and divergence in shift. (A) Date of first appearance of bumblebees (Bombus spp.; black) and the blooming of the plants goat willow Salix caprea (cyan) and coltsfoot Tussilago farfara (blue). (B) Illustration of the high level of phenological synchrony (with a value of 0.77) between the appearance of bumblebees and the blooming of goat willow, measured as the correlation coefficient for the residuals from the regression of A. (C) Bars showing distributions of within- and between-group phenological synchronies. The stars indicate cases for which the median correlation was significantly (P < 0.05) greater than zero (star above the bar) or smaller than zero (star below the bar). The arrows point out cases with a statistically significant (P < 0.05) negative (red arrows) or positive (blue arrows) correlation between synchrony and divergence in shift (see Datasets S3 and S4 for the full results and Materials and Methods for details on the randomization tests). Pairs of events of the same species are excluded for these analyses.