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A general understanding of grazing effects on plant diversity in drylands is still missing, despite an extensive theoretical background. Cross-biome syntheses are hindered by the fact that the outcomes of disturbance studies are strongly affected by the choice of diversity measures, and the spatial and temporal scales of measurements. The aim of this study is to overcome these weaknesses by applying a wide range of diversity measures to a data set derived from identical sampling in three distinct ecosystems. We analyzed three fence-line contrasts (heavier vs. lighter grazing intensity), representing different degrees of aridity (from arid to semiarid) and precipitation regimes (summer rain vs. winter rain) in southern Africa. We tested the impact of grazing intensity on multiple aspects of plant diversity (species and functional group level, richness and evenness components, alpha and beta diversity, and composition) at two spatial scales, and for both 5-yr means and interannual variability. Heavier grazing reduced total plant cover and substantially altered the species and functional composition at all sites. However, a significant decrease in species alpha diversity was detected at only one of the three sites. By contrast, alpha diversity of plant functional groups responded consistently across ecosystems and scales, with a significant decrease at heavier grazing intensity. The cover-based measures of functional group diversity responded more sensitively and more consistently than functional group richness. Beta diversity of species and functional types increased under heavier grazing, showing that at larger scales, the heterogeneity of the community composition and the functional structure were increased. Heavier grazing mostly increased interannual variability of alpha diversity, while effects on beta diversity and cover were inconsistent. Our results suggest that species diversity alone may not adequately reflect the shifts in vegetation structure that occur in response to increased grazing intensity in the dryland biomes of southern Africa. Compositional and structural changes of the vegetation are better reflected by trait-based diversity measures. In particular, measures of plant functional diversity that include evenness represent a promising tool to detect and quantify disturbance effects on ecosystems.

Questions Which plant traits consistently respond to grazing in different years and across habitat‐related environmental heterogeneity? Does the proposed partial RLQ approach allow partitioning of grazing‐related environmental parameters from other environmental and temporal variations? Location Semi‐arid savannas of central Namibia. Methods We recorded nine quantitative and 12 categorical traits from 87 plant species along grazing gradients in semi‐arid Namibian rangelands. We sampled from gradients in different habitat settings in 2 yr with differing total rainfall amounts. We first examined trait–environment relations with RLQ analysis. To remove confounding effects of temporal and habitat‐related environmental variation on trait performance, we introduced a novel partial RLQ analysis approach. Furthermore, we used the fourth‐corner statistic to quantify and test relations between traits, environmental factors and RLQ axes. Results Habitats and years had strong influences on trait patterns. After removing environmental variation caused by habitats and years, grazing became the most influential factor on trait responses. Traits negatively correlated with increasing grazing pressure were common to perennial grasses, such as long and entire leaves, anemochorous dispersal and rhizomatous growth. Positively correlated traits were those common to herbaceous, annual plants with a prostrate–creeping habit, compound leaves, high specific leaf area (SLA) and exo‐ or endozoochorous dispersal. Some previously acknowledged grazing response traits, like growth form and plant height, were strongly influenced by variations in habitats and years and showed no significant correlation with grazing pressure. Conclusion We emphasize that some traits that respond to grazing may also vary under different habitat conditions and among years, especially in highly variable environments like semi‐arid savannas. When analysing trait–environment relations we recommend using approaches that partition environmental variation, particularly when applying broad sampling schemes at larger geographical scales.

Bush encroachment is a form of land degradation prominent worldwide, but particularly present in semi-arid areas. In this study, we mapped the spatial distribution of the two encroacher species, Acacia mellifera and Acacia reficiens, in Central Namibia, based on their different phenological behavior. We used constrained principal curves to extract a one dimensional gradient of phenological change from two hyperspectral images taken in different seasons. Field measurements of species composition and cover values were statistically related to bi-temporal differences in hyperspectral vegetation indices in a direct gradient analysis. The extracted gradient reflected the relationship between species composition and cover values, and the phenological pattern as captured by the image data. Cover values of four dominant plant species were mapped and species responses along the phenological gradient were interpreted.

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Few studies exist that explicitly analyse the effect of grain, i.e. the sampling unit dimension, on vascular plant species turnover (beta-diversity) among sites. While high beta-diversity is often a result of high environmental heterogeneity, remotely sensed spectral distances among sampling units may be used as a proxy of environmental gradients which spatially shape the patterns of species turnover. In this communication, we aimed to (i) test the potential relation between spectral variation and species beta-diversity in a savanna environment and to (ii) investigate the effect of grain on the achieved patterns. Field data gathered by the BIOTA Southern Africa biodiversity monitoring programme were used to model the relation between spectral variation and species turnover at different spatial grains (10 m x 10 m and 20 m x 50 m). Our results indicate that the overall fit was greater at the larger grain size, confirming the theoretical assumption that using a lower grain size would generally lead to a higher noise in the calculation of species turnover. This communication represents one of the first attempts at relating beta-diversity to spectral variation, while incorporating the effects of grain size in the study. The results of this study could have significant implications for biodiversity research and conservation planning at a regional or even larger spatial scale.

Databases on plant traits as well as the availability of global coverage of high spatial and spectral resolution remote-sensing data are constantly growing. However, little effort has been made to analyse the relationship between plant traits and remote-sensing data while simultaneously taking species identity and abundance into consideration. We correlated quantitative and qualitative plant traits from a dwarf shrub savanna in Namibia, with spectral indices derived from two hyperspectral sensors, HyMap and the Compact High Resolution Imaging Spectrometer Project for On-Board Autonomy (CHRIS-PROBA), which differ in their spatial and spectral resolution. We used RLQ analysis and the fourthcorner statistic, which are two three-table ordination approaches that circumvent the so-called fourth-corner problem. A higher spatial resolution helped to identify trait-index correlations linked to vegetation structure, while a lower spatial resolution pointed at traits linked to vegetation cover. A higher spectral resolution did not improve the relationships between spectral indices and plant traits. However, continuous hyperspectral signatures allowed for the calculation of spectral indices that make use of the detailed spectra allowing for more sophisticated spectral indices. We propose RLQ and the fourth-corner statistic as suitable tools for the remote sensing and Earth observation community that allow the direct correlation of trait databases with remotely sensed information.

How farmers perceive the state of their pastures is an important component of their management decisions and affects natural resources in arid and semi-arid regions.In an explorative study conducted in the Rehoboth farm area of central Namibia, we addressed the question whether the judgments of commercial farmers on pasture conditions are consistent with a botanical assessment of these pastures based on measurements. The perceptions were inferred from the comparative statements of farmers on the pasture quality of adjacent farm pairs. For the botanical assessment, biomass and plant species frequency counts of the same pastures were used. The results of the statistical analysis show a large agreement between perceived and measured pasture states of corresponding farm pairs, thus pasture quality dimensions perceived by the farmers agreed with the measured pasture quality variables. We also discuss the problems of designing more elaborate studies of this type.