Premise of research. Flowering times are sensitive indicators of climate change. This study explores important methodological issues in the use of samples of phenological records, quantifies change in flowering times, and examines causes of variability among species.Methodology. I used Monte Carlo simulations to explore effects of sample size on estimates of phenological statistics. I documented 60 yr of change in temperature and flowering times of forbs in Worcester County, Massachusetts, a largely nonurban area, using a combination of herbarium specimens and observations, and I tested several hypotheses using these data. I also compared changes in flowering times in eastern North America from several published studies.Pivotal results. Average spring temperatures increased 1.4°C (0.24°C/decade) during the last 60 yr. Mean and median flowering dates were most robust for small sample sizes, while early and late flowering dates and ranges were least stable. Mean flowering time advanced 2.9 d (0.4°C/decade), with greatest advances in early-flowering species. The predicted advance for a spring-flowering species was 4–10 d (0.6°–1.5°C/decade) using different models, corresponding to 2.5–6.3 d/°C of springtime warming. Flowering advanced more in species with shorter blooming periods than in species with longer blooming periods. Flowering advance was unaffected by a species’ native status and by whether it was locally increasing or declining. Phenological advances reported for the same species in different studies showed no significant correlation.Conclusions. Advances in flowering times were comparable to those in other north temperate studies, as was the large change in spring-flowering species. Contrary to other studies, phenological changes were unrelated to a species’ native status and to changes in species frequency. Results of simulations and comparisons across studies suggest that sampling error may contribute substantially to reported variation among species.
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Robert I. Bertin (2014) studied this question.
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