Figure 1.
Multimodeling approach: Individually modelled bushes and trees are embedded in a grid-based difference equation model.
All stated processes may take place in all cells. Arrows represent interactions.
Table 1.
Model components.
Table 2.
Characteristics of bramble (Rubus sp.) and blackthorn (Prunus spinosa).
Figure 2.
Flow chart of processes taking place in the individual-based WoodS-Model.
Table 3.
Parameter values for the modelled tree and bush species.
Table 4.
Parameter values for calculating red deer demand for woody browse.
Figure 3.
Simulated growth model (black line) fitting observed data of four tree species and one bush species.
Model efficiency EF is calculated as described by [119]. Grey lines are the standard deviation (2s for broom).
Figure 4.
Crown diameter as an allometric function of height fitting observed data of solitary bushes and trees in the Eifel National Park.
Raw data is publicly available online [34].
Figure 5.
Proportion of seeds landing in the sink cell along one axis for studied bushes and trees starting from one parent plant as calculated from the LANDIS II double exponential seed dispersal function [49].
Figure 6.
Wood encroachment starting with one parent plant in a 1 ha scenario (c.f. Fig. 7) without inhibition by the herbaceous layer.
Figure 7.
Encroachment of beech (green: cells with a cover >50%) and broom (orange: cells with a cover >50%) on an area of 1 ha starting with one parent plant without inhibition by the herbaceous layer and not influenced by red deer.
Table 5.
Observed mean number of broom individuals (Ind) in recently abandoned meadows and pastures on the Dreiborner Hochfläche (Heilburg (2008, unpublished), Krämer [58], Engler [57] and own data), and simulation results after calibration. n: number of field surveys.
Figure 8.
Wood encroachment on a fallow grassland starting with one parent plant in a 1 ha scenario not influenced by red deer but considering the inhibition of the herbaceous layer.
Figure 9.
Biomass of twigs as an allometric function of length fitting observed data of collected twigs (raw data is publicly available online [34]).
Figure 10.
Simulation of the landscape development in the southern part of the Dreiborner Hochfläche with the actual population density of red deer (22 animals per 100 ha).
Names of bushes refer to shrub patches with a bush cover ≥10%. In forest cells, cover of trees is ≥50%.
Figure 11.
Simulation: Vegetation dynamics depending on initial state and neighborhood.
Details of the simulation shown in Fig. 10.
Figure 12.
Observation vs. simulation: Examples of typical patterns of succession from vegetation mapping [59] of areas of known age after abandonment, and results of simulations showing same successional patterns over time.
A: Encroachment of broom on abandoned field paths. B: Spread of bramble and blackthorn into fallow grasslands and subsequent development of new forests from within thorny scrub. Since the observation is time point 0 for the simulation, a direct comparison is not possible. Therefore, we show examples of typical patterns in the observation and simulation for the same landscape. The intention is not to provide a direct comparison, but the changes of landscape structure within a given time frame.
Figure 13.
Observation vs. simulation: Black bars are related to the relative number of established trees observed in the field surveys with a height >2 m [34], [57], [59], [69].
Grey bars are related to the number of simulated cells with emerging new forests.
Figure 14.
Simulated vegetation development of the southern part of the Dreiborner Hochfläche if abandoned with different population densities of red deer.
Initial vegetation composition as in Fig. 10.
Figure 15.
Forest development after 100 simulated years in the southern part of the Dreiborner Hochfläche if abandoned with different population densities of red deer (R).
Same simulation as in Fig. 14. Please note that succession within forests (e.g. from birch to beech or oak) is not included in our model.