In:
Geoscientific Model Development, Copernicus GmbH, Vol. 15, No. 12 ( 2022-06-21), p. 4783-4803
Kurzfassung:
Abstract. Terrestrial biosphere models (TBMs) are invaluable tools for
studying plant–atmosphere interactions at multiple spatial and temporal
scales, as well as how global change impacts ecosystems. Yet, TBM
projections suffer from large uncertainties that limit their usefulness.
Forest structure drives a significant part of TBM uncertainty as it
regulates key processes such as the transfer of carbon, energy, and water
between the land and the atmosphere, but it remains challenging to observe and
reliably represent. The poor representation of forest structure in TBMs
might actually result in simulations that reproduce observed land fluxes
but fail to capture carbon pools, forest composition, and demography.
Recent advances in terrestrial laser scanning (TLS) offer new opportunities
to capture the three-dimensional structure of the ecosystem and to transfer
this information to TBMs in order to increase their accuracy. In this study,
we quantified the impacts of prescribing initial conditions (tree size
distribution), constraining key model parameters with observations, as well
as imposing structural observations of individual trees (namely tree height,
leaf area, woody biomass, and crown area) derived from TLS on the state-of-the-art Ecosystem Demography model (ED2.2) of a temperate forest site (Wytham Woods, UK). We assessed the relative contributions of initial
conditions, model structure, and parameters to the overall output
uncertainty by running ensemble simulations with multiple model
configurations. We show that forest demography and ecosystem functions as
modelled by ED2.2 are sensitive to the imposed initial state, the model
parameters, and the choice of key model processes. In particular, we show
that:
Parameter uncertainty drove the overall model uncertainty, with a mean
contribution of 63 % to the overall variance of simulated gross primary
production. Model uncertainty in the gross primary production was reduced fourfold when
both TLS and trait data were integrated into the model configuration. Land fluxes and ecosystem composition could be simultaneously and accurately
simulated with physically realistic parameters when appropriate constraints
were applied to critical parameters and processes.
We conclude that integrating TLS data can inform TBMs of the most adequate
model structure, constrain critical parameters, and prescribe representative
initial conditions. Our study also confirms the need for simultaneous
observations of plant traits, structure, and state variables if we seek to
improve the robustness of TBMs and reduce their overall uncertainties.
Materialart:
Online-Ressource
ISSN:
1991-9603
DOI:
10.5194/gmd-15-4783-2022
DOI:
10.5194/gmd-15-4783-2022-supplement
Sprache:
Englisch
Verlag:
Copernicus GmbH
Publikationsdatum:
2022
ZDB Id:
2456725-5
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