When we compare vegetation zonation in smaller and isolated mountains with that in large mountain ranges, we often find that in smaller mountains, the same vegetation zones occur in lower elevations than in larger, more “massive” ones. This pattern, first described from European Alps by German researchers at the beginning of the 20th century, is known as Massenerhebung effect, or mass elevation effect (Massen = mass, erhebung = uprising or elevation). In Taiwan, this pattern has been pointed out by Su (1984a,b), who plotted elevation ranges of main vegetation zones in Taiwan along latitude (see below). Since Taiwan island stretches mainly in a latitudinal direction, one would expect that vegetation zonation will steadily decrease toward the northern, cooler part of the island. Instead, the schema from Su (1984b) shows quite clearly that “[t]he altitudinal level of these zones shift downward towards both northern and southern tips as a result of Massenerhebung”, a pattern which is most obvious for lower Quercus zone (lower cloud forest).
Scientific literature recognises three potential reasons why Massenerhebung effect occurs. First is the landmass heating effect: large mountainous masses slow down the speed at which temperature decreases with elevation (or, in other words, decreases the lapse rate). The temperature at mountains in certain elevation is always higher than the temperature of the free air at the same elevation; this is because the solar rays reflected by mountains have a considerable heating effect on the surrounding air. A solitary mountain (e.g. volcano) is not capable of reflecting as much heat as an entire mountain range, and as a result, the temperature at the same elevation in the solitary mountain will be cooler than at comparable elevation in an extensive (“massive”) mountain range. The other is the effect of wind: wind will cool down the outer mountain margins or isolated mountains more than inner parts of mountain ranges. Windward parts of the mountains are usually more humid, which means that more heat has to be spent to evaporate the water instead of heating the ground. Inner parts of the mountains will be dryer and warmer (having more “continental” climate). The last is the effect of cloud: isolated mountains and mountains in outer margins of mountain ranges in coastal regions will be more exposed to prevailing cloud formations. High air humidity causes lower air temperature, and high water content in the soil results into slower humus decomposition. Slow decomposition rate causes lack of nutrients available for vegetation, typical for the mountain cloud forest; this may be partly the reason why at isolated mountains and mountains at the margin of mountain ranges the cloud forest occurs at lower elevations than in the central parts of the mountain ranges. Some authors consider as Massenerhebung only the first effect (landmass heating), others include all three together since their effect is not easy to be separated.
On a large scale, Massenerhebung effect is noticeable for example in Himalaya, where the timberline (the upper climatic boundary of the forest) shifts to a considerably higher elevation than in smaller mountains of comparable latitude. On a scale of Taiwan, along with the descriptive study of Su (1984b), the pattern can be recognised also on the distribution of cloud forest from data in the vegetation database (Schultz et al. 2017, their Figure 2), which shows the hump shape pattern (red crosses indicate cloud forest plots).
As far as I know, there is only a single study which is attempting to explain the environmental correlates of Massenerhebung effect in Taiwan. Chiou et al. (2010) used data from National Vegetation Database of Taiwan, and concluded that the cooling effect of northeastern monsoon is more important than Massenerhebung effect caused by the landmass heating. Authors selected 76 woody species occurring commonly across the island, and for each of them estimated the upper altitudinal limit based on the database data. If only data from the eastern part of Taiwan were used, results showed decreasing elevation pattern with increasing latitude (lowest in the northern part of Taiwan and higher in the central and southern part), while in the case of the dataset from western part there was no clear trend. Authors concluded that since they have not detected the decrease in the altitudinal limits in the southern parts of Taiwan, the “[h]eat retention of Massenerhebung is not the mechanism which can best explain the patterns of species altitudinal distribution in Taiwan”.
My modest opinion is that although authors of Chiou et al. (2011) use a rather large dataset of vegetation plots (1604 vegetation plots, each 400 m2), the analysis itself is not too persuasive, and I would be more careful with bold conclusions of no Massenerhebung in Taiwan. It seems that in their definition, Massenerhebung effect includes only the landmass heating effect, while the effect of wind and cloud are considered separately. But at the same times, authors have chosen three areas in Taiwan of comparable elevation span (each reaches the elevation well over 3000 m asl), while not including the marginal mountain systems at the northern and southern part. But this means that the massiveness of all three selected regions is comparable, so I am not sure why authors expect to see the decreasing trend caused by lower landmass heating effect. Additionally, authors used only 76 out of almost two thousands woody species in Taiwan, including only the most common species occurring in all three selected regions. So, not including marginal mountains (the less “massive” far north and far south part of the island) and using only the limited number of species may be exactly those reasons why the hump shape pattern was not detected. But who knows.
The disadvantage of the schema drawn by Su (1984b) is in a relatively subjective nature of the data it builds upon. Although it is based on more than 200 vegetation records from different elevation zones and different watersheds, combined with data from published studies, still, the boundaries of vegetation zones are delineated somewhat arbitrarily, not really using any quantitative tool. But since now we have data from the National Vegetation Database of Taiwan and the classification of forest vegetation types according to the study of Li et al. (2013), it is possible to construct similar schema using the real vegetation plots. This study, which Woody wrote together with co-authors as a part of his PhD during his study in Brno (Czech Republic), contains a description of 21 zonal and azonal forest vegetation types in Taiwan (zonal types are those determined by climate, while azonal are those determined mainly by edaphic conditions). The paper additionally contains one convenient instrument: Cocktail Determination Key (CoDeK), an R-based application which allows automatic determination of vegetation plots into vegetation types described in the paper, based on plot species composition. I used CoDeK to assign plots into vegetation types, chose only plots belonging to zonal vegetation types and merged analogous tropical and subtropical types into the same units. I plotted latitudinal-altitudinal distribution of the plots and fitted the lower boundaries of each vegetation type with quadratic quantile regression. Except for high-elevation conifer-dominated forest types, all other types show clear hump shaped pattern, with a decrease not only in the northern, but also in the southern part of Taiwan. And since zonal forest types in Li et al. (2013) are largely analogous to vegetation types in Su (1984b), the schema shows a nice agreement with the one in Su (1984b) and supports his observation.
Indeed, the hump shape pattern of vegetation types along latitude is just an empirical observation and does not say anything about factors which are is causing it. In fact, it is quite likely that the resulting pattern is a result of all three factors together – landmass heating effect may be responsible for uplift of vegetation zones in central, drier and less windy parts of the mountain ranges, while the effect of wind and cloud may be responsible for downslope shift in the marginal areas. Additionally, land-use changes caused by human activities also may play a role. With all data readily available, it should not be so difficult to find it out.
- Chiou, C.-R., Song, G.-Z.M., Chien, J.-H., Hsieh, C.-F., Wang, J.-C., Chen, M.-Y., Liu, H.-Y., Hsia, Y.-J., & Chen, T.-Y. (2010). Altitudinal distribution patterns of plant species in Taiwan are mainly determined by the northeast monsoon rather than the heat retention mechanism of Massenerhebung. Botanical Studies, 51: 89-97. https://ejournal.sinica.edu.tw/bbas/content/2010/1/Bot511-11.pdf
- Li C.-F., Chytrý M., Zelený D., Chen M.-Y., Chen T.-Y., Chiou C.-R., Hsia Y.-J., Liu H.-Y., Yang S.-Z., Yeh C.-L., Wang J.-C., Yu C.-F., Lai Y.-J., Chao W.-C., & Hsieh C.-F. (2013). Classification of Taiwan forest vegetation. Applied Vegetation Science, 16: 698–719. https://doi.org/10.1111/avsc.12025
- Schulz, H.M., Li, C.-F., Thies, B., Chang, S.-C., & Bendix, J. (2017). Mapping the montane cloud forest of Taiwan using 12 year MODIS-derived ground fog frequency data. Plos One, 12: e0172663. https://doi.org/10.1371/journal.pone.0172663
- Su, H.-J. (1984a). Studies on the climate and vegetation types of the natural forests in Taiwan (I): Analysis of the variations in climatic factors. Quarterly Journal of Chinese Forestry, 17: 57–73.
- Su, H.-J. (1984b). Studies on the climate and vegetation types of the natural forests in Taiwan (II): Altitudinal vegetation zones in relation to temperature gradient. Quarterly Journal of Chinese Forestry, 17: 1–14.