Laboratory for
Climatology and Remote Sensing

Abstract:

Fog-driven epiphyte-rich tropical cloud forests were long believed to be restricted to mountainous regions. Recent studies have shown the occurrence of such forest types in the lowlands of French Guiana, where early morning radiation fog was shown to modify the water and energy cycles at the canopy level of the tropical lowland rain forest (Gehrig-Downie et al., 2012; Obregon et al., 2011). Since this newly discovered Tropical Lowland Cloud Forest (TLCF) harbours a unique biodiversity comparable to mountain cloud forests, knowledge of its spatial distribution across tropical lowland forests is of large ecological interest, but so far fully unknown. A prerequisite to detect potential TLCF stands is knowledge on the spatial occurrence of fog/low stratus clouds (FLS) over longer time scales, indicating fog frequency. We address this need on a continental scale by presenting the first spatially-explicit, high-resolution product on nocturnal FLS occurrence over the entire tropical lowland rain forest area of South America. The product is based on a new FLS retrieval scheme that uses brightness temperature (BT) information of night-time satellite images acquired by the Aqua Moderate Imaging Spectror­ adiometer (Aqua MODIS). Since landforms substantially influence small-scale FLS development, we used a dy­ namic threshold technique depending on the spatially variable subpixel information on landform suitability for FLS generation. The product was successfully validated against in-situ visibility measurements combined with a plausibility analysis based on the published but scarce fog observations over the Amazon. The independence of the new algorithm from measured total precipitable water (TPW) is an improvement over existing procedures that are limited to the availability of these ancillary data. The FLS frequency map for the entire tropical lowland forest of South America derived from over 52,000 scenes (18 years from 2003 to 2020 inclusive) indicates that FLS is widespread, though spatially differentiated, throughout the tropical lowland forests of South America, providing suitable environmental conditions for the TLCF. This knowledge on the spatial distribution of potential TLCF is of major importance for conservation efforts. The new FLS scheme is applicable to all tropical lowland forests and can therefore support global conservation efforts of the valuable TLCF ecosystems.

Abstract:

Up until now montane cloud forest (MCF) in Taiwan has only been mapped for selected areas of vegetation plots. This paper presents the first comprehensive map of MCF distribution for the entire island. For its creation, a Random Forest model was trained with vegetation plots from the National Vegetation Database of Taiwan that were classified as “MCF” or “non-MCF”. This model predicted the distribution of MCF from a raster data set of parameters derived from a digital elevation model (DEM), Landsat channels and texture measures derived from them as well as ground fog frequency data derived from the Moderate Resolution Imaging Spectroradiometer. While the DEM parameters and Landsat data predicted much of the cloud forest’s location, local deviations in the altitudinal distribution of MCF linked to the monsoonal influence as well as the Massenerhebung effect (causing MCF in atypically low altitudes) were only captured once fog frequency data was included. Therefore, our study suggests that ground fog data are most useful for accurately mapping MCF.

Abstract:

Up until now montane cloud forest (MCF) in Taiwan has only been mapped for selected areas of vegetation plots. This thesis presents the first comprehensive map of MCF distribution for the entire island. For its creation, a Random Forest model was trained with vegetation plots from the National Vegetation Database of Taiwan that were classified as “MCF” or “non-MCF”. This model predicted the distribution of MCF from a raster data set of parameters derived from a digital elevation model (DEM), Landsat channels and texture measures derived from them as well as ground fog frequency data. The latter have been derived from the Moderate Resolution Imaging Spectroradiometer (MODIS). For the detection of ground fog in MODIS imagery a new algorithm has been developed. It does not rely on cloud microphysical assumptions and was validated using camera data.

Abstract:

Recent work on bryophyte diversity in lowland forests of northern South America has suggested the existence of a new type of cloud forest, the ‘tropical lowland cloud forest’ (LCF). LCF occurs in river valleys in hilly areas with high air humidity and morning fog, and is rich in epiphytes. We explored epiphyte abundance and canopy microclimate of LCF in a lowland area (200–400 m asl) near Saül, central French Guiana. We analyzed the vertical distribution of epiphytic cover and biomass on 48 trees, in LCF and in lowland rain forest (LRF) without fog. Trees in LCF had significantly more epiphytic biomass than in LRF; mean total epiphytic biomass in LCF was about 59 g/m2, and 35 g/m2 in LRF. In all height zones on the trees, total epiphyte cover in LCF exceeded that in LRF, with ca 70 percent mean cover in LCF and ca 15 percent in LRF. During both wet and dry seasons, mean diurnal relative air humidity (RH) was higher in LCF than in LRF, and persistence of high RH after sunrise significantly longer in LCF. We suggest that the prolonged availability of high air humidity in LCF and the additional input of liquid water through fog, enhance epiphyte growth in LCF by shortening the desiccation period and lengthening the period of photosynthetic activity of the plants.