Reproductive character displacement and potential underlying drivers in a species‐rich and florally diverse lineage of tropical angiosperms (Ruellia; Acanthaceae)

Reproductive character displacement is a pattern whereby sympatric lineages diverge more in reproductive character morphology than allopatric lineages. This pattern has been observed in many plant species, but comparably few have sought to disentangle underlying mechanisms. Here, in a diverse lineage of Neotropical plants (Ruellia; Acanthaceae), we present evidence of reproductive character displacement in a macroevolutionary framework (i.e., among species) and document mechanistic underpinnings. In a series of inter-specific hand pollinations in a controlled glasshouse environment, we found that crosses between species that differed more in overall flower size, particularly in style length, were significantly less likely to produce viable seeds. Further, species pairs that failed to set seed were more likely to have sympatric distributions in nature. Competition for pollinators and reinforcement to avoid costly inter-specific mating could both result in these patterns and are not mutually exclusive processes. Our results add to growing evidence that reproductive character displacement contributes to exceptional floral diversity of angiosperms

A State-of-the-Art Vegetation Map for Jordan: A New Tool for Conservation in a Biodiverse Country

In many countries, including Jordan, the updating of vegetation maps is required to aid in formulating development and management plans for agriculture, forest, and rangeland sectors. Remote sensing data contributes widely to vegetation mapping at different scales by providing multispectral information that can separate and identify different vegetation groups at reasonable accuracy and low cost. Here, we implemented state-of-the-art approaches to develop a vegetation map for Jordan, as an example of how such maps can be produced in regions of high vegetation complexity. Specifically, we used a reciprocal illumination technique that combines extensive ground data (640 vegetation inventory plots) and Sentinel-2 satellite images to produce a categorical vegetation map (scale 1:50,000). Supervised classification was used to translate the spectral characteristics into vegetation types, which were first delimited by the clustering analyses of species composition data from the plots. From the satellite image interpretation, two maps were created: an unsupervised land cover/land use map and a supervised map of present-day vegetation types, both consisting of 18 categories. These new maps should inform ecosystem management and conservation planning decisions in Jordan over the coming years

A framework to study and predict functional trait syndromes using phylogenetic and environmental data

Traits do not evolve in isolation but often as part of integrated trait syndromes, yet the relative contributions of environmental effects and evolutionary history on traits and their correlations are not easily resolved.In the present study, we develop a methodological framework to elucidate eco-evolutionary patterns in functional trait syndromes. We do so by separating the amount of variance and covariance related to phylogenetic heritage and environmental variables (environmental phylogenetic conservatism), only phylogenetic heritage (non-attributed phylogenetic conservatism) and only to environmental variables (evolutionarily labile environmental effects). Variance–covariance structures of trait syndromes are displayed as networks. We then use this framework to guide a newly derived imputation method based on machine learning models that predict trait values for unsampled taxa, considering environmental and phylogenetic information as well as trait covariation. TrEvol is presented as an R package providing a unified set of methodologies to study and predict multivariate trait patterns and improve our capacity to impute trait values.To illustrate its use, we leverage both simulated data and species-level traits related to hydraulics and the leaf economics spectrum, in relation to an aridity index, demonstrating that most trait correlations can be attributed to environmental phylogenetic conservatism.This conceptual framework can be employed to examine issues ranging from the evolution of trait adaptation at different phylogenetic depths to intraspecific trait variation

Phylogenomic Study of Monechma Reveals Two Divergent Plant Lineages of Ecological Importance in the African Savanna and Succulent Biomes

Monechma Hochst. s.l. (Acanthaceae) is a diverse and ecologically important plant group in sub-Saharan Africa, well represented in the fire-prone savanna biome and with a striking radiation into the non-fire-prone succulent biome in the Namib Desert. We used RADseq to reconstruct evolutionary relationships within Monechma s.l. and found it to be non-monophyletic and composed of two distinct clades: Group I comprises eight species resolved within the Harnieria clade, whilst Group II comprises 35 species related to the Diclipterinae clade. Our analyses suggest the common ancestors of both clades of Monechma occupied savannas, but both of these radiations (~13 mya crown ages) pre-date the currently accepted origin of the savanna biome in Africa, 5-10 mya. Diversification in the succulent biome of the Namib Desert is dated as beginning only ~1.9 mya. Inflorescence and seed morphology are found to distinguish Groups I and II and related taxa in the Justicioid lineage. Monechma Group II is morphologically diverse, with variation in some traits related to ecological diversification including plant habit. The present work enables future research on these important lineages and provides evidence towards understanding the biogeographical history of continental Africa