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Local properties of patterned vegetation: quantifying endogenous and exogenous effects.
Gopal G Penny1, Karen E Daniels, Sally E Thompson
1Department of Civil and Environmental Engineering, University of California, , Berkeley, CA 94710, USA.
Summary
Vegetation banding in drylands, driven by water competition, shows variable patterns influenced by topography and soil. Local analysis reveals soil depth and water accumulation impact pattern wavelength and coherence.
Area of Science:
- Ecology
- Geomorphology
- Remote Sensing
Background:
- Dryland ecosystems often display periodic vegetation bands.
- These patterns are hypothesized to result from plant competition for scarce, unevenly distributed water.
Purpose of the Study:
- To develop and apply a Fourier method for analyzing local vegetation pattern characteristics.
- To investigate the drivers of variation in vegetation pattern wavelength and orientation in dryland environments.
Main Methods:
- A novel Fourier method was developed to identify local pattern wavenumber and orientation.
- The method was applied to aerial imagery from a vegetation patterning site near Fort Stockton, Texas.
- Analysis incorporated ancillary soil and topographic datasets.
Main Results:
- Local vegetation pattern wavelength and orientation were found to be generally coherent but exhibited significant variation.
- Variations were correlated with changes in hillslope gradient, orientation, water accumulation potential, and soil type.
- Simulations of endogenous pattern dynamics under uniform conditions produced less variable patterns than observed in nature.
- A correlation was identified between soil depth, pattern coherence, vegetation cover, and pattern wavelength.
- Downslope water accumulation was suggested as a factor influencing vegetation pattern properties.
Conclusions:
- Local pattern analysis, integrating environmental data, is crucial for understanding vegetation patterning in drylands.
- Environmental factors, particularly soil depth and water dynamics, play a significant role in modulating vegetation pattern characteristics.
- Observed pattern variability in natural systems exceeds predictions from models assuming homogeneous conditions, highlighting the importance of spatial heterogeneity.