Ball, Lawrence, Tzanopoulos, Joseph (2020) Interplay between topography, fog and vegetation in the central South Arabian mountains revealed using a novel Landsat fog detection technique. Remote Sensing in Ecology and Conservation, . ISSN 2056-3485. (doi:10.1002/rse2.151) (KAR id:79969)
PDF
Publisher pdf
Language: English
This work is licensed under a Creative Commons Attribution 4.0 International License.
|
|
Download this file (PDF/8MB) |
|
Request a format suitable for use with assistive technology e.g. a screenreader | |
PDF
Author's Accepted Manuscript
Language: English |
|
Download this file (PDF/2MB) |
Preview |
Request a format suitable for use with assistive technology e.g. a screenreader | |
Official URL: https://doi.org/10.1002/rse2.151 |
Abstract
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 topography affects fog distributions. Specifically, steep windward slopes obstruct the inland movement of fog, resulting in heterogenous fog densities and hotspots of fog interception. We find that fog distributions explain 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.
Item Type: | Article |
---|---|
DOI/Identification number: | 10.1002/rse2.151 |
Uncontrolled keywords: | topography, fog, vegetation, regression tree analysis (RTA), central South Arabian mountains (CSAM), Dhofar Oman, Mahra Yemen, monsoon, khareef, Anogeissus dhofarica, cloud forest, Normalized Difference Vegetation Index (NDVI) |
Subjects: |
G Geography. Anthropology. Recreation > G Geography (General) G Geography. Anthropology. Recreation > GE Environmental Sciences |
Divisions: | Divisions > Division of Human and Social Sciences > School of Anthropology and Conservation |
Depositing User: | Joseph Tzanopoulos |
Date Deposited: | 06 Feb 2020 20:42 UTC |
Last Modified: | 05 Nov 2024 12:45 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/79969 (The current URI for this page, for reference purposes) |
- Link to SensusAccess
- Export to:
- RefWorks
- EPrints3 XML
- BibTeX
- CSV
- Depositors only (login required):