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| Titel |
On the uncertainty of phenological responses to climate change, and implications for a terrestrial biosphere model |
| VerfasserIn |
M. Migliavacca, O. Sonnentag, T. F. Keenan, A. Cescatti, J. O'Keefe, A. D. Richardson |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1726-4170
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| Digitales Dokument |
URL |
| Erschienen |
In: Biogeosciences ; 9, no. 6 ; Nr. 9, no. 6 (2012-06-08), S.2063-2083 |
| Datensatznummer |
250007118
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| Publikation (Nr.) |
 copernicus.org/bg-9-2063-2012.pdf |
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| Zusammenfassung |
Phenology, the timing of recurring life cycle events, controls numerous land
surface feedbacks to the climate system through the regulation of exchanges
of carbon, water and energy between the biosphere and atmosphere.
Terrestrial
biosphere models, however, are known to have systematic errors in the
simulation of spring phenology, which potentially could propagate to
uncertainty in modeled responses to future climate change. Here, we used the
Harvard Forest phenology record to investigate and characterize sources of
uncertainty in predicting phenology, and the subsequent impacts on model
forecasts of carbon and water cycling. Using a model-data fusion approach, we
combined information from 20 yr of phenological observations of 11 North
American woody species, with 12 leaf bud-burst models that varied in
complexity.
Akaike's Information Criterion indicated support for spring warming models
with photoperiod limitations and, to a lesser extent, models that included
chilling requirements.
We assessed three different sources of uncertainty in phenological forecasts:
parameter uncertainty, model uncertainty, and driver uncertainty. The latter
was characterized running the models to 2099 using 2 different IPCC climate
scenarios (A1fi vs. B1, i.e. high CO2 emissions vs. low CO2 emissions
scenario). Parameter uncertainty was the smallest (average 95% Confidence
Interval – CI: 2.4 days century−1 for scenario B1 and
4.5 days century−1 for A1fi), whereas driver uncertainty was the
largest (up to 8.4 days century−1 in the simulated trends). The
uncertainty related to model structure is also large and the predicted
bud-burst trends as well as the shape of the smoothed projections varied
among models (±7.7 days century−1 for A1fi,
±3.6 days century−1 for B1). The forecast sensitivity of bud-burst
to temperature (i.e. days bud-burst advanced per degree of warming) varied
between 2.2 days °C−1 and 5.2 days °C−1 depending
on model structure.
We quantified the impact of uncertainties in bud-burst forecasts on simulated
photosynthetic CO2 uptake and evapotranspiration (ET) using a
process-based terrestrial biosphere model. Uncertainty in phenology model
structure led to uncertainty in the description of forest seasonality, which
accumulated to uncertainty in annual model estimates of gross primary
productivity (GPP) and ET of 9.6% and 2.9%, respectively. A sensitivity
analysis shows that a variation of ±10 days in bud-burst dates led to a
variation of ±5.0% for annual GPP and about ±2.0% for ET.
For phenology models, differences among future climate scenarios (i.e.
driver) represent the largest source of uncertainty, followed by
uncertainties related to model structure, and finally, related to model
parameterization. The uncertainties we have quantified will affect the
description of the seasonality of ecosystem processes and in particular the
simulation of carbon uptake by forest ecosystems, with a larger impact of
uncertainties related to phenology model structure, followed by uncertainties
related to phenological model parameterization. |
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