Remote Sensing in Ecology and Conservation: https://doi.org/10.1002/rse2.151

In the central South Arabian mountains of Yemen and Oman, monsoon fog interception by the endemic cloud forest is essential for ecosystem functions and services. Yet, we know little about the local factors affecting fog distributions and their cumulative effects on vegetation. To examine these relationships, we developed a novel method of high‐resolution fog detection using Landsat data, and validated the results using occurrence records of eight moisture‐sensitive plant species. Regression tree analysis was then used to examine the topographic factors influencing fog distributions and the topoclimatic factors influencing satellite‐derived vegetation greenness. We find that the interplay between the complex mountain topography and the incoming fog results in heterogeneous fog densities. Specifically, fog accumulates against steep windward slopes and landforms, resulting in hotspots of fog interception, while lower fog densities occur in leeward locations. We also find that fog distributions correlate with patterns of vegetation greenness, and overall, that greenness increases with fog density. The layer of fog density describes 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 layer of fog density will enable an improved understanding of how species and communities, many of which are endemic, range‐restricted and in decline, respond to local variability in topoclimatic conditions.