Input sheets

In order to run the model, approppriate information must be provided. Three types of information are needed: the definition of the scenarios (e.g. duration of forestation program, is the rate of forestation constant or not etc.), the specifications of the scenarios (e.g. the annual rate of forestation), and the characteristics of the forest at the first year of the run. On input sheet 1, some very general parameters of the scenario(s) are set. Based on some of these parameters, other, more detailed parameters can be set in input sheet 2. All inputs are set in four steps.

Additionally, if you want to run sensitivity analysis, you need to specify its conditions. This setting is done on a separate sheet.

Input sheet one

Step 1

    First calendar year of the simulation

   Length of projection

Specify the number of years you want to simulate the carbon dynamics and carbon economics of the afforestation program. The number of years, a maximum of 200 years, will determine the time span for which calculations will be made, and for which output tables and graphs will show the results.

   Name of run

All output will be placed in a fila starting with sim_ and ending with the specific name of the run that you specify here in this box.
 

    Parameters: default (D), user (U), or variable over time (V)?

Step 2

    Is the rate of afforestation constant over time? (Y/N)

Increasing forest area can happen in two ways: either at a fix rate over the years and species, or in either a non-linear manner over time, or linearly over time, but not accross species, or at a varying rate accross both time and species.

In the first case, the user must only set, in the second input sheet, the overall rate and, in this input sheet right below, the length of the afforestation program. Note that the rate must be constant not only over time, but also accross species.

In all other cases, the user must type in the area of afforestations for each year of the scenario in the user.xls file. (If this has not been done, the user must quit from this program, load user.xls, type in the figures in Table 2, then rerun the program.)

    Number of species

    Number of yield classes

CASMOFOR can handle forest stands that are classified into one of the six yield classes that are used to assess the growth of the trees. The distribution of the forest, or the afforested area, by yield classes can either be done by typing in the overall ratios, in percent of the total area, on the second input sheet, if the rate is constant over the afforestation period, or in the user.xls file, if the rate changes from year to year.

   How much soil carbon (tC/ha) is lost on average due to afforestation?

When conducting an afforestation, soil is usually disturbed. This is often needed to get rid of weeds, to break up compacted soil, to open up soil to insert seeds or saplings into the soil, and to help seeds to germinate, and saplings to get access to the nutrients and the water of the soil. However, some of the organic matter in the soil gets in contact with oxigen-containing air, oxidizes, and is emitted to air. CASMOFOR allows the user to include this loss in the simulation. However, the extent of this loss is usually not know, so cannot be modelled. Therefore, the user is asked to enter a value that may be potentially emitted. If you are not sure how much is to be entered here, leave this cell empty. In this case, however, your net carbon removal estimate may be overestimated.

   What is the share of grassland of all land afforested (%)?

When grassland is converted to forest, come of the carbon is the soil is permanently lost. This loss is simulated by the model for each ha of grassland converted. To enable the model to correctly simulate this loss, the user must provide an approximate share (in %) of grassland of all area afforested.

    Is mortality randomly generated? (Y/N)

Input sheet two

Step 3

    Length of afforestation program (yr)

This is the length of period, in years, during which afforestations are made. This information is necessary to be set only if the afforestation rate is constant, otherwise this is inherently set when the user provides the afforestation rate for each year of the afforestation program.

The length of this period is not necessariliy equal to the length of the scenarios, rather, it can be longer than that.

    Rate of annual afforestations

Step 4

    Species

    Distribution of forest area

    Yield class

Yield class is one of (usually) six classes that reflects that site quality (e.g. availability of water and nutrient for the roots in the soil by time and space) considerably affects how much biomass can be produced by the trees of a species. Yield class one refers to the best site and the best performance of the species (in terms of yield), whereas yield class six refers to the poorest site and the poorest performance of the species. See details here.

    Ratio values

Sensitivity / Monte Carlo analysis

For this analysis, two types of data can be entered. One is the possible error of the various variables, and the other is whether this error is assumed random or as a systematic error, i.e. bias.

If the error is to be assumed random, then standard deviation of the assumed error distribution of the various variables of the model by species must be entered. There are three columns on this sheet to enter this data by species, and, for each variable, the assumed or measured standard deviation of the error of the variable can be entered in each column. The number must be in percent, and be a positive number. If the error to be analysed is a bias, then the number to be entered is the assumed size of the error in percent, positive or negative.

It is the fourth column for each variable is to tell the model if the values in the first three columns are random errors, or biases. If this column (with green cells) is left empty or contains 0 for a variable, it means that random errors are assumed. On the other hand, if the number 1 is entered for a variable, it means that the error is assumed to be a bias.

Care must be taken to provide realistic values for the analysis, otherwise either the program will not run or not run correctly, or the calculated values will be realistic.