Abstract
Premise: Although many studies document advancing phenology in response to warming, it is challenging to identify which environmental drivers influence phenology and whether phenological shifts suitably track changing environmental conditions. By examining phenological trends on a climate-relevant scale (e.g., heat accumulated at flowering or days between snowmelt and flowering), we can test whether climate change outpaces phenological shifts. If these climate-relevant phenology metrics remain constant over time, that would suggest perfect phenological tracking to match the climate conditions under which plants historically flowered. Methods: We analyzed a long-term data set on timing of first flower and climate from 1995 to 2024 in 25 species in a semiarid intermontane grassland in west-central Montana, United States. We used an information theoretic approach to examine how flowering phenology shifted over time and in response to a suite of environmental variables (temperature, growing degree days [GDD], precipitation, snowmelt, drought), whether responses were nonlinear, and whether responses differed between early- vs. late-spring flowering species. We then asked whether climate-relevant measures of phenology remained constant over time, which would suggest tracking of suitable environmental conditions. Results: Flowering phenology advanced nonlinearly over time and under warmer and drier conditions. In particular, early-spring flowering species advanced flowering under drought conditions. Plants flowered with fewer GDD accumulated and sooner post-snowmelt than historically. Conclusions: Phenological shifts keep pace with climate change in our system. However, nonlinear phenological responses to climate indicate that phenological shifts are slowing. Phenological shifts in spring flowering species may be limited as temperatures continue to increase.
| Original language | English |
|---|---|
| Journal | American Journal of Botany |
| DOIs | |
| State | E-pub ahead of print - May 14 2026 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 13 Climate Action
Keywords
- climate change
- drought
- grassland
- long-term data
- nonlinear
- phenological shift
- phenology
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