|Summary||On forest carbon cycle||
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|General description||Examples for model output||
Modelling the economic aspects of afforestations to sequester carbon is useful to study wheather it is worth investing in afforestations. On the other hand, analysing costs and revenues of the forestry sector can be compared with those of other sectors to optimize resources when it comes to carbon sequestration and the mitigation of climate change.
However it must be emphasized that forests bring a multitute of products and benefits. The economic calculations in CASMOFOR only cover costs and benefits associated with the establishement, the maintainance and harvestin of forests. It thus exludes the benefits from all other products and services forests may offer (from providing clean water to protecting soil, providing jobs and opportunities for healing, recreation, sport, hunting, aesthetics and many more). Depending on the type of forests, as well as ecological and social conditions, some of these co-benefits could be translated to monetary terms, some of them not. CASMOFOR only analyses the wood production and the carbon sequestration values, however, it is suggested that the user conducts additional analyses in case data are available to estimate the full economics of growing forests. When taking decisions on afforestations, all co-benefits, which are usually numerous in forests, must be seriously considered.
In forestry, costs and revenues of forestry operations occur at discrete points in time, i.e. when forestry operations are carried out. These operations include forestation (site preparation and planting or sowing), tending (controlling weed and undesirable seedlings), fertilizing (in some forest types), various types of thinnings (pre-commercial thinning, selection thinning, thinning for increment), and final harvesting. By calculating these costs and revenues, one can usually have an idea on the economics of timber production, as revenues are usually limited to marketing timber.
Modelling the economic aspects of afforestations is necessary to demonstrate that afforestations may be effective and relatively cheap means of sequestering carbon.
Mofelling forest economics requires data related to each forestry operation. Whereas there are some sporadic studies in this regard, only mean values for the following operations are available in Hungary: stand establishment (including site preparation and planting), tending, thinning of young stands, selection thinning, thinning for increment, and final cutting. In practice, there usually are several operations for tending, thinning of young stands, selection thinning and thinning for increment, always depending on tree species and site. These forestry operations are modelled by so called silvicultural models, which set the mean age of conducting the operation. Expert judgement was used to break up the economic data known for the above types of operations and related them to the specific ages that are set in the silvicultural model. As a result, thinnings (i.e., removals of wood from stands), as well as costs and revenues are always incurred at the same ages.
Both the silvicultural models, as well as the economic model include data by species and yield class. However, the economic model sometimes includes separate data for afforestations on mountains, as well as on the plains for the same species. Therefore, expert judgement was used to select data that are applicable for afforestations (mainly to be established in plains, as well as low hills).
Economic data include both costs, as well as revenues for each operation. For CASMOFOR, only the net costs (i.e., revenues minus costs) are used; negative values mean net costs, whereas positive values mean net revenues.
An example of the economic data available for Black locust (for Yield class I as an example), updated for 2008 (Marosi et al. 2008) can be found in the below table:
From the data above, as well as from the silvicultural model for Black locust, the following economic data was derived the age data of which exactly matches those in the silvicultural model for Black locust:
However, no economic data exists for all species separately, and for some species only data for three yield groups (good, medium, poor) exists for yield classes I and II, yield classes III and IV, and yield classes V and VI, respectively. In these cases, expert judgement was used to map economic data with those in the silvicultural model of the respective species. All in all, at least good approximative economic data are found in the database of the model for all species.
The economic and market conditions may become stabil for years or decades, however, they may become very instabile, too. This instability, that is almost sure to take place during rotation periods of decades or a century, highly adds to the uncertainty of mean economic data. Locally, even higher uncertainty may occur as the local silvicultural practice, as well as local maker conditions may considerably deviate from country-level conditions.
Note that thinning timing, harvest age, as well as thinning intensity in the silvicultural model, and also those in the forest economic model as included in CASMOFOR for single stands do sometimes deviate, therefore, cost data may not be accurate in the short term. However, these discrepancies are eliminated when several stands are afforested. Also, it happens that data for stands of both coppice and seed origin may be available in the silvicultural model, whereas only data for a species may be available in the forest economic model. Different sets of economic data were also available for the plains and for mountaneous conditions for some species for which only one set of silvicultural model and yield table exists. Therefore, an adjustment of the economic data to the yield table and silvicultural data was necessary (however, yield table or silviculural data were never adjusted to economic data). Because of all this, the timing of economic data may not be accurate in the short term (but less in the longer term). In any event, total costs and revenues for a rotation period fully correspond to those of the original economic data.
Carbon economics is the study of costs and revenues of fixing carbon by forestry means. In CASMOFOR, costs and revenues from forest economics are related to one tonne of CO2 fixed. This relationship changes over time, and depends much on the site and species selected.
If the net forestry costs are added up between year 0 and any other year of the afforestation program to get total costs, then they could be related to the total amount of carbon sequestered up to the same year of the afforestation program (i.e., total net costs up to year n / total amount of carbon sequestered up to the same year n). This index is also calculated over time, and, like many other values calculated by CASMOFOR, is reported both in a tabular, as well as in a graphical format for easy analysis.
Note that as the total amount sequestered in the forestry system can be regarded as a value of high uncertainty, the specific total net costs are not only calculated for the whole forestry system, but also for the aboveground biomass, which could be regarded as a more accurate value.
Further income can also be calculated if the net costs are reduced by the value of carbon removed within any framework of emission trading. Thus, if a certain amount of monetary value is attached to any tonne of CO2 sequestered, for example, 20 Euro/tCO2, then this value increases the economic value of sequestering carbon. The market value of a tonne of CO2 sequestered, as well as the HUF/EURO rate can of course be adjusted to analyse the possible effects of the market on the results.All economic analyses can be run either in HUF, or in EURO.
The accuracy of carbon economics highly depends on the accuracy of both the carbon budget estimates, as well as the forest economic estimates. This means that the absolute carbon economic values may have large uncertainties. However, it is suggested that the order of magnitude of the estimates is correct, and that the uncertainty of comparing options, or scenarios, is much smaller than that of a single scenario. Thus, the original objective of developing CASMOFOR, which is to support decision making, can be fully met by analysing scenarios.
This webpage was last modified by Zoltan Somogyi 29 June 2014.