Résumé
We present a detailed analysis of a rare cross-taxa native species phenology dataset (plant flowering. insect first sighting, and amphibian first sighting) from Mohonk Lake, NY. This dataset is highly unusual in North America for its longevity of record. consistency of methodology and location, diversity of species available, and availability of local daily meteorological data. For each phenology series, we examined the flowering and first sighting Julian calendar dates for the existence of temporal trends. Only one of the five animal species (katydid) showed any evidence for a significant trend in first sighting. In contrast, the plant species showed a rich mixture of temporal trends in flowering that could be divided into four classes: woody plant-no trend, woody plant-negative trend, herbaceous plant-ne-ative trend, and herbaceous plant-positive trend. Many of the trends were found to be statistically significant and robust to the method of trend estimation. The data within each of the four plant classes were also pooled as anomalies to provide more complete temporal coverage for tests of trend robustness. The results were strongly consistent with the trends of the individual species Within each class and highly significant statistically. We next correlated the flowering and first sighting dates against growing degree-day (GDD) surninations for each day of the year to measure the sensitivity of each species to this common form of climatic forcing oil phenologoy. All species showed a significant sensitivity to GDD summations, with peak correlations falling oil or near the varying median flowering or first sighting dates. These results were robust Whether the GDD analyses were conducted over the complete set of observations for each species (beginning oil or after 1928) or over a latter period with a more serially complete set of cross-taxa observations (1970-2002). The GDD correlations indicate significant climate sensitivity in all species, but the different magnitudes of correlation and timing of maximum correlation imply that plant and animal responses to climate changes in the future Will not be homogeneous for the tested species at Mohonk Lake. Copyright (C) 2007 Royal Meteorological Society.