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| Titel |
Estimating national forest carbon stocks and dynamics: combining models and remotely sensed information |
| VerfasserIn |
Luke Smallman, Mathew Williams |
| Konferenz |
EGU General Assembly 2016
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| Medientyp |
Artikel
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| Sprache |
en
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 18 (2016) |
| Datensatznummer |
250123714
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| Publikation (Nr.) |
 EGU/EGU2016-3012.pdf |
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| Zusammenfassung |
| Forests are a critical component of the global carbon cycle, storing significant amounts of
carbon, split between living biomass and dead organic matter. The carbon budget of forests is
the most uncertain component of the global carbon cycle – it is currently impossible to
quantify accurately the carbon source/sink strength of forest biomes due to their
heterogeneity and complex dynamics. It has been a major challenge to generate robust carbon
budgets across landscapes due to data scarcity. Models have been used but outputs have
lacked an assessment of uncertainty, making a robust assessment of their reliability and
accuracy challenging.
Here a Metropolis Hastings - Markov Chain Monte Carlo (MH-MCMC) data
assimilation framework has been used to combine remotely sensed leaf area index
(MODIS), biomass (where available) and deforestation estimates, in addition to forest
planting and clear-felling information from the UK’s national forest inventory, an
estimate of soil carbon from the Harmonized World Database (HWSD) and plant trait
information with a process model (DALEC) to produce a constrained analysis with a
robust estimate of uncertainty of the UK forestry carbon budget between 2000 and
2010.
Our analysis estimates the mean annual UK forest carbon sink at -3.9 MgC ha−1yr−1
with a 95 % confidence interval between -4.0 and -3.1 MgC ha−1 yr−1. The UK national
forest inventory (NFI) estimates the mean UK forest carbon sink to be between -1.4 and -5.5
MgC ha−1 yr−1. The analysis estimate for total forest biomass stock in 2010 is estimated at
229 (177/232) TgC, while the NFI an estimated total forest biomass carbon stock of 216 TgC.
Leaf carbon area (LCA) is a key plant trait which we are able to estimate using our analysis.
Comparison of median estimates for LCA retrieved from the analysis and a UK land
cover map show higher and lower values for LCA are estimated areas dominated by
needle leaf and broad leaf forests forest respectively, consistent with ecological
expectations. Moreover, the retrieved LCA is positively correlated with leaf-life span and
negatively correlated with allocation of photosynthate to foliage, supported by field
observations.
This emergence of key plant traits and correlations between traits increases our
confidence in the robustness of this analysis. Furthermore, this framework also allows us to
search for additional emergent properties from the analysis such as spatial variation of
retrieved drought tolerance. Finally our analysis is able to identify components of the carbon
cycle with the largest uncertainty providing targets for future observations (e.g. remotely
sensed biomass). Our Bayesian analysis system is ideally suited for assimilation
of multiple biomass estimates and their associated uncertainties to reduce both
uncertainty in the state of the system but also process parameters (e.g. wood residence
time). |
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