Understanding topography-fog-vegetation relationships in central southern Arabia

Excited to share this new research in the fantastic Remote Sensing in Ecology and Conservation journal.

The cloud forests in Dhofar may be the driest on earth. They receive just 200 mm of rain each year, but during the monsoon/khareef, as much moisture is intercepted from the fog by the forest canopy! This is critical to ecosystem functions and services. Therefore, we hypothesized that vegetation patterns might correlate with fog distributions, which themselves might be affected by the complex mountain topography.

To investigate this, we first needed to map fog distributions at a high resolution (to see the effects of the complex topography). We found that many Landsat scenes showed the fog events, with little interference from other cloud types. So, using Google Earth Engine we extracted fog cover from 257 scenes, and calculated mean (average fog distributions) and SD (fog variability). We used recursive partitioning to analyse how topographic variables influence fog distributions and how fog distributions influence vegetation patterns (NDVI).

We found that fog accumulates against steep windward slopes and landforms, resulting in hotspots of fog interception, while lower fog densities occur in leeward locations. We also found a strong positive correlation between fog density and vegetation greenness. We found hotspots of fog interception, with consistently high fog densities and cloud forest over rough terrain. Complex forest canopy structures intercept more fog moisture than a smooth canopy. We found fog distributions describe patterns of vegetation greenness more accurately than topographic variables alone, and thus, we propose that regional vegetation patterns more closely follow a fog gradient, than an altitudinal gradient as previously supposed.

The Dhofar mountains are home to endemic and threatened biodiversity, and a wealth of archaeological and geological heritage. We hope that our layer of fog density, which is hosted in the PANGAEA data repository (doi.org/10.1594/PANGAE), will enable an improved understanding of how species and in Dhofar respond to local variability in topoclimatic conditions.