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Journal Article

Traits and climate are associated with first flowering day in herbaceous species along elevational gradients

MPS-Authors
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Migliavacca,  Mirco
Biosphere-Atmosphere Interactions and Experimentation, Dr. M. Migliavacca, Department Biogeochemical Integration, Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society;

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BGC2795.pdf
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BGC2795s1.zip
(Supplementary material), 484KB

Citation

Bucher, S. F., König, P., Menzel, A., Migliavacca, M., Ewald, J., & Römermann, C. (2018). Traits and climate are associated with first flowering day in herbaceous species along elevational gradients. Ecology and Evolution, 8(2), 1147-1158. doi:10.1002/ece3.3720.


Cite as: https://hdl.handle.net/21.11116/0000-0000-6E1B-8
Abstract
Phenological responses to changing temperatures are known as “fingerprints of climate change,” yet these reactions are highly species specific. To assess whether different plant characteristics are related to these species-specific responses in flowering phenology, we observed the first flowering day (FFD) of ten herbaceous species along two elevational gradients, representing temperature gradients. On the same populations, we measured traits being associated with (1) plant performance (specific leaf area), (2) leaf biochemistry (leaf C, N, P, K, and Mg content), and (3) water-use efficiency (stomatal pore area index and stable carbon isotopes concentration). We found that as elevation increased, FFD was delayed for all species with a highly species-specific rate. Populations at higher elevations needed less temperature accumulation to start flowering than populations of the same species at lower elevations. Surprisingly, traits explained a higher proportion of variance in the phenological data than elevation. Earlier flowering was associated with higher water-use efficiency, higher leaf C, and lower leaf P content. In addition to that, the intensity of shifts in FFD was related to leaf N and K. These results propose that traits have a high potential in explaining phenological variations, which even surpassed the effect of temperature changes in our study. Therefore, they have a high potential to be included in future analyses studying the effects of climate change and will help to improve predictions of vegetation changes.