Predicting lichen hydration using biophysical models.

• Two models for predicting the hydration status of lichens were developed as a first step towards a mechanistic lichen productivity model. A biophysical model included the water potential of the air, derived from measurements of air temperature, relative humidity and species-specific rate constants for desiccation and rehydration. A reduced physical model, included only the environmental parameters, assuming instantaneous equilibration between the lichen and the air. These models were developed using field and laboratory data for three green algal lichens; the foliose epiphytic Platismatia glauca (L.) W. Culb., the fruticose epiphytic Alectoria sarmentosa (Ach.) Ach., and the fruticose, terricolous and mat-forming Cladina rangiferina (L.) Weber ex Wigg. The models were compared and validated for the same three species using data from a habitat with a different microclimate. Both models predicted length and timing of lichen hydration periods with high accuracy for A. sarmentosa and P. glauca where near 100 percent of the total wet time was predicted by the biophysical and the physical model. Moreover, the models predicted an accurate timing of the total realized wet time for A. sarmentosa and P. glauca when the lichens were wet. The model accuracy was lower for C. rangiferina compared to the epiphytes, both for the total realized wet time and timing accuracy. The results demonstrate that the stochastic and continually varying hydration status of lichens can be simulated from biophysical data. Further development of these models to include also water related activity, light, and temperature conditions during the hydration events, will then be a potent tool to assess potential lichen productivity in landscapes and habitats of various microclimatic conditions.

Keyword

Biophysical Phenomena

Biophysics

Climate

Computer Simulation

Lichens/chemistry/*physiology

Models; Biological

Species Specificity

Sweden

Water/*analysis

Water Loss; Insensible/physiology

Publication and Content Type

ref (subject category)

art (subject category)