Liana communities exhibit different species composition, diversity and community structure across forest types in the Congo Basin

Lianas are poorly characterized for central African forests. We quantify variation in liana composition, diversity and community structure in different forest types in the Yangambi Man and Biosphere Reserve, Democratic Republic of Congo. These attributes of liana assemblages were examined in 12 1-ha plots, randomly demarcated within regrowth forest, old growth monodominant forest, old growth mixed forest and old growth edge forest. Using a combination of multivariate and univariate community analyses, we visualize the patterns of these liana assemblage attributes and/or test for their significant differences across forest types. The combined 12 1-ha area contains 2,638 lianas (>= 2 cm diameter) representing 105 species, 49 genera and 22 families. Liana species composition differed significantly across forest types. Taxonomic diversity was higher in old growth mixed forests compared to old growth monodominant and regrowth forests. Trait diversity was higher than expected in the regrowth forest as opposed to the rest of forest types. Similarly, the regrowth forest differed from the rest of forest types in the pattern of liana species ecological traits and diameter frequency distribution. The regrowth forest was also less densely populated in lianas and had lower liana total basal area than the rest of forest types. We speculate that the mechanism of liana competitive exclusion by dominant tree species is mainly responsible for the lower liana species diversity in monodominant compared to mixed forests. We attribute variation in liana community structure between regrowth and old growth forests mostly to short development time of size hierarchies

Drivers of plant diversity in Bulgarian dry grasslands vary across spatial scales and functional-taxonomic groups

Questions: Studying dry grasslands in a previously unexplored region, we asked: (a) which environmental factors drive the diversity patterns in vegetation; (b) are taxonomic groups (vascular plants, bryophytes, lichens) and functional vascular plant groups differently affected; and (c) how is fine-grain beta diversity affected by environmental drivers? Location: Northwestern and Central Bulgaria. Methods: We sampled environmental data and vascular plant, terricolous bryophyte and lichen species in 97 10-m2 plots and 15 nested-plot series with seven grain sizes (0.0001–100 m2) of ten grassland sites within the two regions. We used species richness as measure of alpha-diversity and the z-value of the power-law species–area relationship as measure of beta-diversity. We analysed effects of landscape, topographic, soil and land-use variables on the species richness of the different taxonomic and functional groups. We applied generalised linear models (GLMs) or, in the presence of spatial autocorrelation, generalised linear mixed-effect models (GLMMs) in a multi-model inference framework. Results: The main factors affecting total and vascular plant species richness in 10-m2 plots were soil pH (unimodal) and inclination (negative). Species richness of bryophytes was positively affected by rock cover, sand proportion and negatively by inclination. Inclination and litter cover were also negative predictors of lichen species richness. Elevation negatively affected phanerophyte and therophyte richness, but positively that of cryptophytes. A major part of unexplained variance in species richness was associated with the grassland site. The z-values for total richness showed a positive relationship with elevation and inclination. Conclusions: Environmental factors shaping richness patterns strongly differed among taxonomic groups, functional vascular plant groups and spatial scales. The disparities between our and previous findings suggest that many drivers of biodiversity cannot be generalised but rather depend on the regional context. The large unexplained variance at the site level calls for considering more site-related factors such as land-use history

How do steppe plants follow their optimal environmental conditions or persist under suboptimal conditions? The differing strategies of annuals and perennials

International audienceFor a species to be able to respond to environmental change, it must either succeed in following its optimal environmental conditions or in persisting under suboptimal conditions, but we know very little about what controls these capacities. We parameterized species distribution models (SDMs) for 135 plant species from the Algerian steppes. We interpreted low false-positive rates as reflecting a high capacity to followoptimal environmental conditions and high false-negative rates as a high capacity to persist under suboptimal environmental conditions. We also measured functional traits in the field and built a unique plant trait database for the North-African steppe.For both perennial and annual species, we explored how these two capacities can be explained by species traits and whether relevant trait values reflect species strategies or biases in SDMs. We found low false-positive rates in species with small seeds, flowers attracting specialist pollinators, and specialized distributions (among annuals and perennials), low root:shoot ratios, wide root-systems, and large leaves (perennialsonly) (R2 = .52–58). We found high false-negative rates in species with marginal environmental distribution (among annuals and perennials), small seeds, relatively deep roots, and specialized distributions (annuals) or large leaves, wide root-systems, and monocarpic life cycle (perennials) (R2 = .38 for annuals and 0.65 for perennials). Overall, relevant traits are rarely indicative of the possible biases of SDMs, but ratherreflect the species’ reproductive strategy, dispersal ability, stress tolerance, and pollination strategies. Our results suggest that wide undirected dispersal in annual species and efficient resource acquisition in perennial species favor both capacities, whereas short life spans in perennial species favor persistence in suboptimal environmental conditions and flowers attracting specialist pollinators in perennial and annual speciesfavor following optimal environmental conditions. Species that neither follow nor persist will be at risk under future environmental change