The cumulative net LULCC flux exhibits a reduced sensitivity to LULCC uncertainty with starting year 1850 (compare vertical spread of blue markers in the LULCC column) since the input data have smaller uncertainty in more recent years (Fig. A1). At the same time, the largest estimates of the cumulative net LULCC flux comparing experiments with different StYr are produced in simulations from 1850 (second column). The net cumulative LULCC flux is more sensitive to the LULCC uncertainty (22 % range in flux) and less sensitive to the starting year of the simulation (15 %). The magnitude of the net LULCC flux of HI – REG is often not the same as the REG – LO difference even though the variability of LULCC is asymmetric around REG. For the standard setup (REG1700), the influence of LULCC uncertainty (HI1700 and LO1700) is about 3 times larger than the sensitivity to StYr (REG850, REG1850).

We design additional artificial sensitivity experiments to disentangle the uncertainty from the initial land-cover distribution and the uncertainty from LULCC activities (transitions). By extending the historical simulations under future LULCC scenarios, we can then estimate the impact of past uncertainty on future estimates of the net LULCC flux. Over the period 1850–2014, baseline and low LULCC scenarios produce a comparable cumulative net LULCC flux, while the high LULCC estimate initially produces a larger net LULCC flux which decreases towards the end of the period and even becomes smaller than in the baseline estimate. LULCC bookkeeping model uncertainty leads to slightly higher sensitivity in the cumulative net LULCC flux (up to 22 %; references are the baseline simulations) compared to the starting year of a model simulation (up to 15 %). The contribution from neglecting wood harvest activities (up to 28 % cumulative net LULCC flux) is larger than that from LULCC uncertainty, and the implementation of land-cover transitions (gross or net transitions) exhibits the smallest sensitivity (up to 13 %). At the end of the historical LULCC dataset in 2014, the LULCC uncertainty retains some impact on the net LULCC flux (±0.15 PgC yr−1 at an estimate of 1.7 PgC yr−1).

Forest expansion dominates China’s land carbon sink since 1980

Pasture expansion and harvest on primary forested land are only relevant from around 1700 onwards and affect less area than the other LULCC activities. These results are also largely consistent with the findings of Hurtt et al. (2011), in which the contributions of shifting cultivation and wood harvesting were the model factors that the simulation output, in terms of the net LULCC flux, was most sensitive to. In comparison to Hurtt et al. (2011), it can be noted that sensitivities might look different in other metrics like forest age or area. Although the spatial and temporal representation of these processes has been significantly improved in LUH2 (versus LUH1), the choice of whether or not to include these processes in DGVM simulations is still a large contributor to the overall uncertainty in LULCC fluxes.

Cumulative net LULCC flux estimates are most sensitive to harvest uncertainties, mainly over northern Europe, northern Asia and south-eastern Asia (China and north-eastern India). Components of the cumulative net LULCC flux due to uncertainty of crop expansion and abandonment follow the pattern of shifting cultivation in the tropics, which means that the sensitivity to uncertainties in abandonment and crops is balanced with the opposite sign. The largest sensitivity of the cumulative net land-use flux to LULCC using net transitions is present over Europe from abandonment and over India and south-east Asia from uncertainties in crop transitions.

1 The bookkeeping model BLUE

This approach allows us to disentangle the observation-based carbon fluxes by terrestrial woody vegetation into anthropogenic and environmental contributions. Estimated emissions (from land-use and land cover changes) between 2000 and 2019 amount to 1.4 PgC yr−1, reducing the difference to other carbon cycle model estimates by up to 88% compared to previous estimates with the BKM (without the data assimilation). Our estimates suggest that the global woody vegetation carbon sink due to environmental processes (1.5 PgC yr−1) is weaker and more susceptible to interannual variations and extreme events than estimated by state-of-the-art process-based carbon cycle models. These findings highlight the need to advance model-data integration to improve estimates of the terrestrial carbon cycle under the Global Stocktake. Our approach introduces various important novelties compared to DGVMs and to BKMs with fixed contemporary carbon densities.

• FB,j,l varies for different PFTs and land cover types, depending on their history of LULCC and their potential for carbon uptake (i.e., the potential carbon densities).
• Our study thus provides an extension to previous studies comparing sensitivities across a different set of factors by also disentangling the relevance of the initial land-cover distribution compared to the uncertainties in LULCC activities on the net LULCC flux.
• There are different types and methods of bookkeeping which are practised in managing books of accounts.
• Net transitions slightly decrease the contribution from harvest and increase the contribution from pasture expansion to the net LULCC flux, both by about 10 %.
• You can also choose to become a certified public bookkeeper to market yourself better as a bookkeeping professional.

Your business name is the first thing that lets customers, clients, competitors and others in the marketplace know about who you are and what you do. For businesses in Europe (Germany, in particular), the type of product or service you invoice determines the timing of the tax origin and hence, which options to apply. If you are going to offer your customers credit or if you are going to request credit from your suppliers, then you have to use an accrual accounting system. Figure 5Cumulative net LULCC flux for the period 1850–2014 from REG1700 (a) as well as the difference HI1700 – REG1700 (b) and LO1700 – REG1700 (c). A supertype is a generic entity type that has a relationship with one or more subtypes.

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