Bookkeeping estimates of the net land-use change flux a sensitivity study with the CMIP6 land-use dataset

We thus expect that improvements in other parts of the carbon budget would bring the budget imbalance closer to zero again. Our approach allows us to quantify SLAND under transient land cover (SLAND,trans), which globally averages at −3.0 (−3.9, −2.2) GtC yr−1 in 2012–2021 and amounts to a cumulative sink of −225 (−296, −160) GtC in 1850–2021 (Fig. 2, Table 2). SLAND,trans is substantially lower (i.e., a weaker sink) than SLAND estimated with the conventional approach under pre-industrial land cover SLAND,pi, which yields a sink of −3.7 (−2.6, −5.2) GtC yr−1 in 2012–2021.

• Our approach allows us to quantify SLAND under transient land cover (SLAND,trans), which globally averages at −3.0 (−3.9, −2.2) GtC yr−1 in 2012–2021 and amounts to a cumulative sink of −225 (−296, −160) GtC in 1850–2021 (Fig. 2, Table 2).
• Another difference that can influence results comparing bookkeeping models and DGVMs is that the former approach uses constant (present-day) carbon densities, while DGVMs work with variable carbon densities which respond to environmental conditions.
• The income statement is developed by using revenue from sales and other sources, expenses, and costs.
• Note that we assign the effects of transient environmental conditions on anthropogenic carbon fluxes to ELUC until the carbon stock prevalent at the time of the LULUCF event is reached again.
• In 850, the uncertainty around the baseline scenario is about 50 % for pasture and crop area, of which 1 % remain in 2014 (Fig. A1b).
• For the starting years presented here (850, 1700 or 1850), the spread in cumulative net LULCC flux is about the same order as that from including gross transitions but can be neglected for annual fluxes in recent years.

A1 Preparation of LUH2 data for BLUE

Neglecting wood harvest (NoH) or only using net transitions (net) leads to 3 times larger deviations from the reference (see Table 2) than LULCC uncertainties (first column) and reduces the net LULCC flux at most to about 1.1 PgC yr−1. The 5 %–10 % sensitivity of the net LULCC flux bookkeeping model to LULCC uncertainties (about 1.55 to 1.75 PgC yr−1) can mainly be explained by the uncertainty of transitions. Almost no sensitivity of the net LULCC flux to the starting year of the model simulations remains. The impact of StYr and LULCC uncertainty on the net LULCC flux in 2014 is similar to the characteristics discussed for the cumulative net LULCC flux estimates (Fig. 3). LULCC differences still modulate annual net LULCC flux estimates throughout the 20th century (Fig. S2), and the largest variability of net LULCC flux, about ±0.1 to 0.3 PgC yr−1, is due to uncertainties in harvest and abandonment.

Long-term national climate strategies bet on forests and soils to reach net-zero

• SLAND,trans excludes the purely hypothetical CO2 fluxes that would exist in ecosystems that in reality were lost due to LULUCF.
• Uncertainties for other data (TRENDY, GCB51, atmospheric O2 observations1, data from ref. 16, data from ref. 9) are indicated as one standard deviation around the mean.
• TRENDY models also deliver a transient estimate of ELUC (shown in Fig. 1a), which is however conceptually not comparable to ELUC,trans, as the transient ELUC estimate from TRENDY (which is also reported by ref. 16) includes the RSS term (see Methods).
• With the presented approach, land-use effects on SLAND can be separated from detrimental environmental impacts, both of which can put natural ecosystems under extensive stress42.

The three crosses in 2014 represent the total cumulative net LULCC flux of the three REG experiments (REG850, REG1700 and REG1850) if the flux is only calculated for the period 1850–2014. Figure 1Global annual net LULCC flux for simulations with start year 1700 and HI, REG and LO LULCC scenarios of the LUH2 dataset (LO1700, REG1700 and HI1700). From 2014 onwards, each of the three historical simulations is continued with four different scenarios of future LULCC. SSP4 describes an inequality scenario with Food Truck Accounting low challenges to mitigation and high challenges to adaptation. SSP5, on the other hand, is characterised by fossil-fuelled development with high challenges to mitigation and low challenges to adaptation. In the following, the scenarios are referred to by their SSPs and their Representative Concentration Pathways (RCPs) and not mainly by the Integrated Assessment Model (IAM) that produced them, i.e.

• This highlights that accounting for transient land cover and transient environmental conditions is crucial to accurately estimate SLAND, ELUC, and the net land flux and to reconcile existing approaches.
• This is crucial for correctly estimating the remaining carbon budget to limit global warming to 1.5 °C or 2.0 °C1,40.
• A bookkeeper collects the documentation for each financial transaction, records the transactions in the accounting journal, classifies each transaction as one or more debits and one or more credits, and organizes the transactions according to the firm’s chart of accounts.
• Interestingly, the cumulative net land-use change flux over Oceania is larger in HI1700 rather than LO1700 because few transitions occur before 1700, so basically all transitions are captured in the analysis period.
• By neglecting information on some of the LULCC activities from the input dataset, simulations without wood harvest and with net instead of gross transitions can be produced (see Table 2).
• We additionally perform five individual BLUE simulations using carbon density data from the five individual DGVMs that provide carbon density data for both vegetation and soil (CABLE-POP, CLASSIC, JSBACH, ORCHIDEE, and YIBs).

1.2 Comparison of components of uncertainty

Our updated estimates of global forest carbon stocks (Table 3) are also closer to other observation-based estimates23 than the estimates from the default setup. The largest differences to the default setup and the biggest improvements concerning the reconciliation with other datasets are found for tropical and boreal forests. In terms of the interannual variability (IAV) of the net carbon fluxes from global woody vegetation (Table 1), we find that retained earnings the IAV is on average around eight times larger when considering environmental effects on woody biomass carbon. In other words, ~88% (2.1 PgC yr−1) of the IAV of the net carbon fluxes from woody biomass (2.4 PgC yr−1) carbon is due to environmental effects and their synergies on ELUC or conversely ~12% of the IAV (0.3 PgC yr−1) is attributable to LULCC (Table 1). The same relation between biomass carbon simulated under fixed vs. transient climate is also shown for the TRENDY simulations, although our estimates suggest a stronger contribution of environmental processes to the IAV of carbon fluxes from vegetation. Between 2001 and 2018, SLAND,B amounts to −1.6 PgC yr−1 (−1.5 PgC yr−1 for 2001–2019) based on our BLUE simulations, suggesting a ~13% smaller sink than the TRENDY multi-model average (Supplementary Table 2).

2.2 Estimates of future emissions

Bookkeeping in a business firm is an important, but preliminary, function to the actual accounting function. A bookkeeper collects the documentation for each financial transaction, records the transactions in the accounting journal, classifies each transaction as one or more debits and one or more credits, and organizes the transactions according to the firm’s chart of accounts. The bookkeeping process should allow for communication of the financial results of the firm at the end of the year for income tax purposes and the preparation of financial statements by the firm’s accountant.