| 299 | | === Prescribe initial vegetation (CHECK) === |
| 300 | | +++UPDATE+++ |
| 301 | | At the start of the model run or after a die-back or clear-cut new vegetation needs to be planted as ORCHIDEE does not grow vegetation from seeds. The initial dimensions of the vegetation is thus prescribed. Given that the allocation follows allometric relationships, any of the tree dimensions or any mass of any component could have been used to prescribe. The variable height was chosen because it is easy to (mentally) visualize the prescribed vegetation. In the run.def '''height_init_min''' and '''height_init_max''' need to be prescribed. Typical values are 2 to 5 meter. If more than one diameter class is used, '''height_init_max ''' needs to larger than '''height_init_min'''. The larger the difference between the min and max, the more vegetation layers the canopy will be composed from. |
| 302 | | |
| 303 | | In addition, the initial number of seedlings needs to be prescribed as well. For this the parameter '''nmaxtrees''' needs to be set. '''nmaxtrees''' is a critical parameter to obtain acceptable model behaviour. If it is too high, lai saturates but the stand-level GPP will be distributed over too many individuals, each individual will grow very little and so it will take very long before self-thinning is reached. If it is set too low, LAI will be too low resulting in a too low GPP and thus very slow growth. A good starting values is a bit below self-thinning. That way the vegetation starts growing, individual are killed thanks to the background mortality and within 10 to 20 years self-thinning is reached. Why not starting at self-thinning? During code development it was tried to have the model start at the exact number of trees at which self-thinning will start given the diameter of the tree. One issues was that when prescribing small individuals (2-3 m) the calculated number of trees could in the millions and so the GPP had to be distributed over too many individuals. |
| 304 | | |
| 305 | | The way the initial vegetation is prescribed can also be used to prescribe a mature vegetation right at the start of the simulation. One could set '''height_init_min''' and '''height_init_max''' to for example 15 and 20. If '''nmaxtrees''' is not adjusted, massive self-thinning will take place on the first day. It is better to set '''nmaxtrees''' to a value just below the exact self-thinning value. Prescribing mature vegetation has been tested and works but it is very sensitive. If the combination of '''nmaxtrees''', '''height_init_min''' and '''height_init_max''' are far from realistic, the model may crash (the change in KF following the change in gap probability could result in problems in allocation) and N-feedbacks will become apparent in for example the leaf mass (likely because when mature vegetation is prescribed at the start of a run, there is not enough soil N to maintain a mature vegetation). Although this was a convenient feature in ORCHIDEE-CAN, it lost much of it power after merging it into ORCHIDEE-CN-CAN. |
| 306 | | ++++++++++++ |
| 307 | | |
| | 301 | |
| | 302 | === Prescribe initial vegetation (r6614) === |
| | 303 | At the start of the model run or after a die-back or clear-cut new vegetation needs to be planted as ORCHIDEE does not grow vegetation from seeds. The initial dimensions of the vegetation are thus prescribed. Given that the allocation follows allometric relationships, any of the tree dimensions or any mass of any component could have been used to prescribe. The variable diameter was chosen because it is easy to (mentally) visualize the prescribed vegetation. In the run.def '''dia_init_min''' and '''dia_init_max''' need to be prescribed. Typical values are 1 to 3 cm. If more than one diameter class is used, '''dia_init_max ''' needs to larger than '''dia_init_min'''. The larger the difference between the min and max, the more vegetation layers the canopy will be composed from. |
| | 304 | |
| | 305 | In addition, the initial number of seedlings needs to be prescribed as well. For this a parameter needs to be set. This is a critical parameter to obtain acceptable model behaviour. If it is too high, lai saturates but the stand-level GPP will be distributed over too many individuals, each individual will grow very little and so it will take very long before self-thinning is reached. If it is set too low, LAI will be too low resulting in a too low GPP and thus very slow growth. A good starting values is a bit below self-thinning. That way the vegetation starts growing, individual are killed thanks to the background mortality and within 10 to 20 years self-thinning is reached. Why not starting at self-thinning? During code development it was tried to have the model start at the exact number of trees at which self-thinning will start given the diameter of the tree. One issues was that when prescribing small individuals (1 to 3 |
| | 306 | cm) the calculated number of trees could in the millions and so the GPP had to be distributed over too many individuals. |
| | 307 | |
| | 308 | ++++CONTINUE+++++ |
| | 309 | Depending on whether a stand is managed or not, the initial number of trees is calculated in a different way (see stomate_prescribe.f90). The second paragraph is very informative and refer now to alpha_rdi_upper, beta_rdi_upper for managed forest and grad_thin,alpha_rdi_upper, beta_rdi_upper for unmanaged forest |
| | 310 | +++++++++++++++++ |
| | 311 | |
| | 312 | |
