Is the age of plant communities predicted by the age, stability and soil composition of the underlying landscapes? An investigation of OCBILs

Abstract

Old, climatically buffered, infertile landscapes (OCBILs) have been hypothesized to harbour an elevated number of persistent plant lineages and are predicted to occur across different parts of the globe, interspersed with other types of landscapes. We tested whether the mean age of a plant community is associated with occurrence on OCBILs, as predicted by climatic stability and poor soil environments. Using digitized occurrence data for seed plants occurring in Australia (7033 species), sub-Saharan Africa (3990 species) and South America (44 482 species), regions that comprise commonly investigated OCBILs (Southwestern Australian Floristic Region, Greater Cape Floristic Region and campos rupestres), and phylogenies pruned to match the species occurrences, we tested for associations between environmental data (current climate, soil composition, elevation and climatic stability) and two novel metrics developed here that capture the age of a community (mean tip length and mean node height). Our results indicate that plant community ages are influenced by a combination of multiple environmental predictors that vary globally; we did not find statistically strong associations between the environments of OCBIL areas and community age, in contrast to the prediction for these landscapes. The Cape Floristic Region was the only OCBIL that showed a significant, although not strong, overlap with old communities.

Looking similar but all different: Phylogenetic signature of Brazilian rocky outcrops and the influence of temperature variability on their phylogenetic structure

“…is relatively low across rocky outcrops, our results add evidence to previous studies on the association between old lineages and OCBILs (Cortez et al, 2021). Lineages might be comparably old but have undergone recent and fast diversification, as shown for campo rupestre (Vasconcelos et al, 2020), likely influencing our results (e.g.…”

“…Overall, our results add evolutionary insights to the Old, Climatically Buffered, Infertile Landscapes (OCBIL) theory. Specifically, by demonstrating that phylogenetic diversity is lower than expected by chance, the phylogenetic structure is clustered, and the median community age at the species level is relatively low across rocky outcrops, our results add evidence to previous studies on the association between old lineages and OCBILs (Cortez et al, 2021). Lineages might be comparably old but have undergone recent and fast diversification, as shown for campo rupestre (Vasconcelos et al, 2020), likely influencing our results (e.g.…”

“…Additionally, further studies addressing the relationship between the age of lineages and phylogenetic diversity could reveal that even though some OCBILs might have old lineages (e.g. campo rupestre; Cortez et al, 2021), most evolutionary changes happened later, as indicated by short phylogenetic distances among species in our study.…”

“…To calculate the median community age (MeCA) for each site at the species level, we used the tip length value (Cortez et al, 2021) of the largest phylogenetic tree based on molecular data derived from GenBank taxa (79,689 seed plant species; Smith & Brown, 2018). We used this tree for this specific analysis because smaller trees could have overestimated tip lengths due to sampling issues or extinct taxa, and the larger tree from the same reference has many unresolved taxa (Smith & Brown, 2018).…”

Land use changes result in increased phylogenetic clustering and preferential loss of species-rich sites for Michigan floral assemblages.

“…Often, a general goal of biodiversity mapping studies is to quantify metrics across large spatial scales. In doing so, areas of exceptional species richness (Soltis and Soltis 2016) or phylodiversity (Figueroa et al 2022;De Souza et al 2021) can be highlighted, and that information can be used subsequently to assist in biodiversity maintenance planning and assessment. And while some studies have incorporated land use types to compare species richness (e.g., Schuster et al 2019), and many studies have employed SDMs to identify biodiversity hotspots (e.g., Soltis and Soltis 2016), weaving together an SDM approach to compare biodiversity metrics with and without accounting for land use is less common, especially for phylodiversity metrics.…”