Master Thesis

Mediterranean high mountain flora: patterns of endemism, species richness and leaf colours along an elevational gradient in the Spanish Sierra Nevada

Pia Eibes (12/2016-05/2017)

Support: Carl Beierkuhnlein

Mountains are important hotspots of biodiversity and often contain rare, endemic or threatened species. Therefore, elevational gradients pose ideal conditions to study the distribution and characteristics of species richness, endemism and adaptive plant traits. The following study aims to test if commonly reported patterns of decreasing species richness and increasing percentage of endemism also apply for the flora of Mediterranean high mountains. According to their biogeographic origins, endemic plant species of the study area can be divided into different endemic classes, respectively. This enables a detailed analysis of immigration paths and main drivers of endemic species with differently narrow distribution areas. A further analysis on how leaf colours of theses species change with elevation allows an insight into adaptive strategies of high mountain plant species. Finally, I investigated to what extent vegetation patterns and colour information recorded during fieldwork correspond to vegetation indices derived from remote sensing methods.

The study was conducted in the Sierra Nevada National Park in southern Spain, which contains outstanding numbers of endemic plant species. The study transect was placed between 2,000 and 3,470 m a.s.l. on a southern slope towards the Muhlacén, the highest summit in the Iberian Peninsula.

Within twenty sampling sites along approximately 1,500 meters of elevation, all present vascular plant species have been recorded. Furthermore, total vegetation cover and proportions of soil particles were estimated. Leaf colours of the main species have been measured using the Munsell colourspace for plant tissues. Subsequently, all endemic species have been categorised into four different endemic classes in accordance with their biogeographic origins. Different vegetation indices and RGB colours were calculated from a Sentinel satellite image, which was taken within the sampling period. Linear models were performed to test how vegetation patterns and leaf colours are related to elevation and to the patterns derived from remote sensing methods, respectively.

While species richness monotonically decreased with elevation, general percentage of endemic species significantly increased. Different endemic classes showed variable patterns. The lightness of leaf colours decreased, while blue and green proportions increased with elevation. Some vegetation indices correlated with the observed vegetation patterns and colour information was partly reflected.

When analysing total numbers, findings of species richness and percentage of endemism correspond to commonly reported patterns with a general decrease for species richness and a proportional increase of endemism at high-elevation sites. When focusing on individual endemic classes, the relationship with elevation differs strongly. This highlights the importance of detailed analyses of endemic plant species to better understand main drivers of endemism. The fact that leaf colours change with elevation indicates that high mountain plants have characteristic colour adaptations. Remote sensing products might constitute an additional tool to predict floral biodiversity of mountain ranges, but reach their limits at sparsely vegetated sites around summits.