Wind Disturbance

Wind disturbance follows an approach similar to fire, except that wind is a top-down disturbance, where species susceptibility increases with age and size (Mladenoff and He 1999). A wind disturbance event can add fine fuel and coarse fuel and influence the potential fire-intensity class, depending on the decomposition dynamics of the particular ecoregion. Interactions between these two disturbances can be interesting and complex. Generally, wind disturbance becomes more important on ecoregions with long-lived species, and where fire frequency is low.

Wind disturbance events are stochastic for a single site, but have repeated patterns in terms of breakout location, size, and shape at landscape scales. It has long been noted that some areas are more prone to wind disturbance than others. The differences are often represented by using mean mean-return intervals-the mean number of years for wind to recur on a given area. Similar to the approaches used in other studies, in LANDIS the mean wind return interval is used to calculate wind probability using the following equation:

(6)

where P is the wind probability of a cell, MI is the mean wind return interval of a given ecoregion on which the cell resides, B is the wind probability coefficient designed for model calibration ( B = MI by default), and lw is the number of years since last wind on that cell. With the above distribution, P varies among ecoregions with MI s, and it can be further altered by lw recorded for each single cell. For example, if wind occurs at a given cell in a given time step, lw of the cell is reset to 0, and P for that cell is calculated as 0 during that time step. This eliminates the possibility of cells being blown down twice in the same time step regardless of how short MI is.

Another important feature of wind disturbance is wind size, defined from the following equation integrating random factors and the mean wind size:

(7)

where S is the wind size, is the mean wind size, A is the wind disturbance size coefficient designed for model calibration ( A =0.34 by default), and r is a normalized random number. Under similar mean wind return interval, one can have very different wind regimes ranging from small, frequent wind to large, infrequent wind, which are defined by S distribution.

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