Data For: Herbarium specimens provide reliable estimates of phenological responsiveness to climate at unparalleled taxonomic and spatiotemporal scales
收藏DataCite Commons2026-03-05 更新2026-04-25 收录
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https://datadryad.org/dataset/doi:10.25349/D9TK64
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资源简介:
Understanding the effects of climate change on the phenological structure
of plant communities will require measuring variation in sensitivity among
thousands of co-occurring species across regions. Herbarium collections
provide vast resources with which to do this, but may also exhibit biases
as sources of phenological data. Despite general recognition of these
caveats, validation of herbarium-based estimates of phenological
sensitivity against estimates obtained using field observations remain
rare and limited in scope. Here, we leveraged extensive datasets of
herbarium specimens and of field observations from the USA National
Phenology Network for 21 species in the United States and, for each
species, compared herbarium- and field-based standardized estimates of
peak flowering dates and of sensitivity of peak flowering time to
geographic and interannual variation in mean spring minimum temperatures
(TMIN). We found strong agreement between herbarium- and field-based
estimates for standardized peak flowering time (r=0.91, p<0.001)
and for the direction and magnitude of sensitivity to both geographic TMIN
variation (r=0.88, p <0.001) and interannual TMIN variation
(r=0.82, p<0.001). This agreement was robust to substantial
differences between datasets in 1) the long-term TMIN conditions observed
among collection and phenological monitoring sites and 2) the interannual
TMIN conditions observed in the time periods encompassed by both datasets
for most species. Our results show that herbarium-based sensitivity
estimates are reliable among species spanning a wide diversity of life
histories and biomes, demonstrating their utility in a broad range of
ecological contexts, and underscoring the potential of herbarium
collections to enable phenoclimatic analysis at taxonomic and
spatiotemporal scales not yet captured by observational data.
提供机构:
Dryad
创建时间:
2022-04-15



