Back to Search
Start Over
Later springs green-up faster: the relation between onset and completion of green-up in deciduous forests of North America
- Source :
- International Journal of Biometeorology, International Journal of Biometeorology, Springer Verlag, 2018, 62 (9), pp.1645-1655. ⟨10.1007/s00484-018-1564-9⟩
- Publication Year :
- 2018
-
Abstract
- International audience; In deciduous forests, spring leaf phenology controls the onset of numerous ecosystem functions. While most studies have focused on a single annual spring event, such as budburst, ecosystem functions like photosynthesis and transpiration increase gradually after budburst, as leaves grow to their mature size. Here, we examine the "velocity of green-up," or duration between budburst and leaf maturity, in deciduous forest ecosystems of eastern North America. We use a diverse data set that includes 301 site-years of phenocam data across a range of sites, as well as 22 years of direct ground observations of individual trees and 3 years of fine-scale high-frequency aerial photography, both from Harvard Forest. We find a significant association between later start of spring and faster green-up: - 0.47 ± 0.04 (slope ± 1 SE) days change in length of green-up for every day later start of spring within phenocam sites, - 0.31 ± 0.06 days/day for trees under direct observation, and - 1.61 ± 0.08 days/day spatially across fine-scale landscape units. To explore the climatic drivers of spring leaf development, we fit degree-day models to the observational data from Harvard Forest. We find that the default phenology parameters of the ecosystem model PnET make biased predictions of leaf initiation (39 days early) and maturity (13 days late) for red oak, while the optimized model has biases of 1 day or less. Springtime productivity predictions using optimized parameters are closer to results driven by observational data (within 1%) than those of the default parameterization (17% difference). Our study advances empirical understanding of the link between early and late spring phenophases and demonstrates that accurately modeling these transitions is important for simulating seasonal variation in ecosystem productivity.
- Subjects :
- 0106 biological sciences
Atmospheric Science
green-up
010504 meteorology & atmospheric sciences
Range (biology)
[SDV]Life Sciences [q-bio]
Health, Toxicology and Mutagenesis
ecosystem model
Forests
phenology
010603 evolutionary biology
01 natural sciences
Trees
Ecosystem model
medicine
Ecosystem
0105 earth and related environmental sciences
Transpiration
forest productivity
Ecology
Phenology
15. Life on land
Seasonality
medicine.disease
Plant Leaves
Deciduous
Productivity (ecology)
13. Climate action
[SDE]Environmental Sciences
North America
Environmental science
Physical geography
Seasons
Subjects
Details
- ISSN :
- 14321254 and 00207128
- Volume :
- 62
- Issue :
- 9
- Database :
- OpenAIRE
- Journal :
- International journal of biometeorology
- Accession number :
- edsair.doi.dedup.....008768775c28fca5c5535770de338c7a
- Full Text :
- https://doi.org/10.1007/s00484-018-1564-9⟩