One Sentence Summary: Empirical evidence from grasslands around the world demonstrates a humped-back relationship between plant species richness and biomass at the 1 m 2 plot scale.Abstract: One of the central problems of ecology is the prediction of species diversity. The humped-back model (HBM) suggests that plant diversity is highest at intermediate levels of productivity; at low productivity few species can tolerate the environmental stresses and at high productivity a small number of highly competitive species dominate. A recent study claims to have comprehensively refuted the HBM. Here we show, using the largest, most geographically diverse dataset ever compiled and specifically built for testing this model that if the conditions are met, namely a wide range in biomass at the 1 m 2 plot level and the inclusion of plant litter, the relationship between plant biomass and species richness is hump shaped, supporting the HBM. Our findings shed new light on the prediction of plant diversity in grasslands, which is crucial for supporting management practices for effective conservation of biodiversity. 4Main Text: The relationship between plant diversity and productivity is a topic of intense debate (1-6). The HBM states that plant species richness peaks at intermediate productivity, taking above-ground biomass as a proxy for annual net primary productivity (ANPP) (7-9). This diversity peak is driven by two opposing processes; in unproductive and disturbed ecosystems where there is low plant biomass, species richness is limited by either stress, such as insufficient water and mineral nutrients, or high levels of disturbance-induced removal of biomass, which few species are able to tolerate. In contrast, in the low disturbance and productive conditions that generate high plant biomass it is competitive exclusion by a small number of highly competitive species that is hypothesized to constrain species richness (7-9). Other mechanisms proposed to explain the unimodal relationship between species richness and productivity include disturbance (10), evolutionary history and dispersal limitation (11,12), and density limitation affected by plant size (13).Different case studies have supported or rejected the HBM, and three separate meta-analyses reached different conclusions (14). This inconsistency may indicate a lack of generality of the HBM, or it may reflect a sensitivity to study characteristics including the type(s) of plant communities considered, the taxonomic scope, the length of the gradient sampled, the spatial grain and extent of analyses (14,15), and the particular measure of net primary productivity (16). Although others would argue (6), we maintain that the question remains whether the HBM serves as a useful and general model for grassland ecosystem theory and management. 5 We quantified the form and strength of the richness-productivity relationship using novel data from a globally-coordinated (17), distributed, scale-standardized and consistently designed survey, in which plant richness and biomass were m...

Shifts in biological communities are occurring at rapid rates as human activities induced global climate change increases. Understanding the effects of the change on biodiversity is important to reduce loss of biodiversity and mass extinction, and to insure the long-term persistence of natural resources and natures' services. Especially in remote landscapes of developing countries, precise knowledge about on-going processes is scarce. Here we apply satellite imagery to assess spatio-temporal land use and land cover change (LULCC) in the Bale Mountains for a period of four decades. This study aims to identify the main drivers of change in vegetation patterns and to discuss the implications of LULCC on spatial arrangements and trajectories of floral communities. Remote sensing data acquired from Landsat MSS, Landsat ETM + and SPOT for four time steps (1973, 1987, 2000, and 2008) were analyzed using 11 LULC units defined based on the dominant plant taxa and cover types of the habitat. Change detection matrices revealed that over the last 40 years, the area has changed from a quite natural to a more cultural landscape. Within a representative subset of the study area (7,957.5 km(-2)), agricultural fields have increased from 1.71% to 9.34% of the total study area since 1973. Natural habitats such as upper montane forest, afroalpine grasslands, afromontane dwarf shrubs and herbaceous formations, and water bodies also increased. Conversely, afromontane grasslands have decreased in size by more than half (going from 19.3% to 8.77%). Closed Erica forest also shrank from 15.0% to 12.37%, and isolated Erica shrubs have decreased from 6.86% to 5.55%, and afroalpine dwarf shrubs and herbaceous formations reduced from 5.2% to 1.56%. Despite fluctuations the afromontane rainforest (Harenna forest), located south of the Bale Mountains, has remained relatively stable. In conclusion this study documents a rapid and ecosystem-specific change of this biodiversity hotspot due to intensified human activities (e.g., deforestation, agriculture, infrastructure expansion). Specifically, the ecotone between the afromontane and the afroalpine area represent a "hotspot of biodiversity loss" today. Taking into consideration the projections of regional climate warming and modified precipitation regimes, LULCC can be expected to become even more intensive in the near future. This is likely to impose unprecedented pressures on the largely endemic biota of the area.

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Drought episodes are predicted to increase their intensity and frequency globally, which will have a particular impact on forest vitality, productivity, and species distribution. However, the impact of tree species interaction on forest vulnerability to drought is not yet clear. This study aims to assess how deciduous saplings react to drought and whether tree species diversity can buffer the impact of drought stress on tree saplings. Based on field measurements of crown defoliation and species diversity, vulnerability, drought recovery, and species interaction were analyzed. Fieldwork was carried out in Central Eastern Germany in 2018 during the vegetation season and repeated in 2019. Ten random saplings were measured in each of the 218 plots (15 × 15 m) with 2051 saplings in total out of 41 tree species. We found that 65% of the saplings experienced defoliation during the drought of 2018, of which up to 13% showed complete defoliation. At the species level, Fagus sylvatica L. and Betula pendula Roth. saplings were less affected (<55%), whereas Carpinus betulus L., Sorbus aucuparia L., and Frangula alnus Mill. saplings were the most affected (≥85%). One year later, in 2019, C. betulus and S. aucuparia had a faster recovery rate than F. sylvatica, B. pendula, Quercus spp., and Crataegus spp. (p < 0.001). Furthermore, we showed that forest stands with high sapling species diversity had a reduced vitality under drought stress (p < 0.001), indicating a higher competition for resources. The study provides evidence that F. sylvatica saplings can withstand and survive to persistent drought. Species-specific responses to drought are essential to be considered for implementing adaptive forest management strategies to mitigate the impact of climate change.

The monitoring of land cover and land use change is critical for assessing the provision of ecosystem services. One of the sources for long-term land cover change quantification is through the classification of historical and/or current maps. Little research has been done on historical maps using Object-Based Image Analysis (OBIA). This study applied an object-based classification using eCognition tool for analyzing the land cover based on historical maps in the Main river catchment, Upper Franconia, Germany. This allowed land use change analysis between the 1850s and 2015, a time span which covers the phase of industrialization of landscapes in central Europe. The results show a strong increase in urban area by 2600%, a severe loss of cropland (−24%), a moderate reduction in meadows (−4%), and a small gain in forests (+4%). The method proved useful for the application on historical maps due to the ability of the software to create semantic objects. The confusion matrix shows an overall accuracy of 82% for the automatic classification compared to manual reclassification considering all 17 sample tiles. The minimum overall accuracy was 65% for historical maps of poor quality and the maximum was 91% for very high-quality ones. Although accuracy is between high and moderate, coarse land cover patterns in the past and trends in land cover change can be analyzed. We conclude that such long-term analysis of land cover is a prerequisite for quantifying long-term changes in ecosystem services.