Ching-Feng Li

Mapping tree density at a global scale

The global extent and distribution of forest trees is central to our understanding of the terrestrial biosphere. We provide the first spatially continuous map of forest tree density at a global scale. This map reveals that the global number of trees is approximately 3.04 trillion, an order of magnitude higher than the previous estimate. Of these trees, approximately 1.30 trillion exist in tropical and subtropical forests, with 0.74 trillion in boreal regions and 0.66 trillion in temperate regions. Biome-level trends in tree density demonstrate the importance of climate and topography in controlling local tree densities at finer scales, as well as the overwhelming effect of humans across most of the world. Based on our projected tree densities, we estimate that over 15 billion trees are cut down each year, and the global number of trees has fallen by approximately 46% since the start of human civilization.

Better environmental data may reverse conclusions about niche‐ and dispersal‐based processes in community assembly

Variation partitioning of species composition into components explained by environmental and spatial variables is often used to identify a signature of niche- and dispersal-based processes in community assembly. Such interpretation, however, strongly depends on the quality of the environmental data available. In recent studies conducted in forest dynamics plots, the environment was represented only by readily available topographical variables. Using data from a subtropical broad-leaved dynamics plot in Taiwan, we focus on the question of how would the conclusion about importance of niche- and dispersal-based processes change if soil variables are also included in the analysis. To gain further insight, we introduced multiscale decomposition of a pure spatial component [c] in variation partitioning. Our results indicate that, if only topography is included, dispersal-based processes prevail, while including soil variables reverses this conclusion in favor of niche-based processes. Multiscale decomposition of [c] shows that if only topography was included, broad-scaled spatial variation prevails in [c], indicating that other as yet unmeasured environmental variables can be important. However, after also including soil variables this pattern disappears, increasing importance of meso- and fine-scaled spatial patterns indicative of dispersal processes.

Comparison of MODIS land surface temperature and ground-based observed air temperature in complex topography

Near-ground air temperature (T a) and land surface temperature (T s) are important parameters in studies related to variations in hydrology, biodiversity and climate change. However, complicated mountainous terrain tends to hinder observations in such areas. The scarce observations from mountainous areas can be augmented with data from a 1 km high spatial resolution data set. This data set is obtained from the land surface temperature element of the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments installed on the Aqua and Terra Earth observation satellites from NASA. This study used regional monthly mean T a data for Taiwan as a reference to assess the monthly mean T s data set. The results showed that the two sets of data had correlation coefficients of 0.91–0.96, and the standard deviations of the differences between the two sets were 1.25–1.77°C. These results could serve as a reference for research related to climate and ecology. Further analysis indicated some possible sources of bias between T s and T a: (1) the significant influences caused by soil moisture between wet and dry seasons; (2) the difference between ground-based weather station elevation and 1 km grid-averaged elevation; and (3) interaction among the satellite view, solar zenith angle and terrain gradient. When the T s product (V005) is used directly in ecological study and application, it is essential to have a clear knowledge of the bias and its possible causes.

Classification of the High-Mountain Coniferous Forests in Taiwan

Vegetation of boreal coniferous forests has been extensively studied in many areas of northern Eurasia and North America, but similar forests in the high mountains of subtropical and tropical eastern Asia have been poorly documented so far. This paper, focusing on such forests, is the first phytosociological study at a national scale in Taiwan. The relevés from the National Vegetation Diversity Inventory and Mapping Project database were used to define vegetation types of the high-mountain coniferous forests and to characterize their distribution in Taiwan. Environmental variables such as aspect, elevation, soil rockiness and slope were related to species composition. Cluster analysis was used to classify vegetation plots and establish groups that were interpreted as nine associations belonging to two alliances. The alliance Juniperion squamatae represents woodlands and forests scattered in the subalpine belt, in which Juniperus squamata dominates the canopy and subalpine meadow species occur in the understorey. The Abieti kawakamii-Tsugion formosanae alliance includes forests dominated by Abies kawakamii and Tsuga chinensis var. formosana with shade-tolerant herb species in the upper montane belt. In addition to regional vegetation description, an identification key for the studied forests was developed based on the classification tree technique.

Frequency of Low Clouds in Taiwan Retrieved from MODIS Data and Its Relation to Cloud Forest Occurrence

The relationship between satellite-derived low cloud frequency and the occurrence of tropical montane cloud forest (TMCF) in Taiwan was investigated. From daily MODIS cloud mask products between 2003 and 2012 the low cloud class was extracted and mean low cloud frequency was calculated for Taiwan. This low cloud frequency map was blended with an existing plot-based vegetation classification for Taiwan to analyze the relationship between low cloud frequency and TMCF occurrence. Receiver operating characteristics curves and the area under the ROC curve (AUC) were used to analyze if a relationship exists. No relationship was found for all four TMCF types taken together (AUC = 0.61) and for the dominant TMCF type, Quercus montane evergreen broad-leaved cloud forest (AUC = 0.5). Strong relationships were found for the two spatially-restricted TMCF types, Fagus montane deciduous broad-leaved cloud forest (AUC = 0.91) and Pasania-Elaeocarpus montane evergreen broad-leaved forest (AUC = 0.84), as well as for the second dominant type Chamaecyparis montane mixed cloud forest (AUC = 0.74). The results show that low cloud frequency thresholds might be associated with specific cloud forest types in Taiwan. Further studies should incorporate information about cloud base height, cloud density, and cloud immersion time as well as satellite-based cloud frequency information with a higher temporal resolution. Combination with satellite-based land cover classifications for Taiwan would allow quasi-continuous observation of TMCF changes. Such knowledge would be the precondition for effective protective actions concerning this exceptional but threatened ecosystem.

Is the clouded leopard Neofelis nebulosa extinct in Taiwan, and could it be reintroduced? An assessment of prey and habitat

During 1997–2012 we conducted a nationwide camera-trapping survey and assessed the availability of prey and habitat for the clouded leopard Neofelis nebulosa in Taiwan. We surveyed 1,249 camera-trap sites over 113,636 camera-trap days, from the seashore to an altitude of 3,796 m and covering various types of vegetation. No clouded leopards were photographed during 128,394 camera-trap days, including at 209 sites in other studies, confirming the presumed extinction of clouded leopards in Taiwan. Assessment of the prey base revealed altitudinal distribution patterns of prey species and prey biomass. Areas at lower altitudes and with less human encroachment and hunting supported a higher prey biomass and more of the typical prey species of clouded leopards. Habitat analysis revealed 8,523 km2 of suitable habitat but this was reduced to 6,734 km2 when adjacent areas of human encroachment were subtracted. In the absence of hunting and large mammalian carnivores the major prey of clouded leopards in Taiwan, such as Formosan macaques Macaca cyclopis, Reevess muntjacs Muntiacus reevesi, Formosan serow Capricornis swinhoei and sambar Rusa unicolor, could become over-abundant. Thus, it is important to address the cascading effect of the disappearance of top-down predator control. Our assessment indicated that, with proper regulation of hunting, habitat restoration and corridor improvement, it may be possible to reintroduce the clouded leopard.

Mapping the montane cloud forest of Taiwan using 12 year MODIS-derived ground fog frequency data

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.

Corrigendum: Mapping tree density at a global scale

This corrects the article DOI: 10.1038/nature14967