The pitfalls of biodiversity proxies: Differences in richness patterns of birds, trees and understudied diversity across Amazonia

Abstract

Most knowledge on biodiversity derives from the study of charismatic macro-organisms, such as birds and trees. However, the diversity of micro-organisms constitutes the majority of all life forms on Earth. Here, we ask if the patterns of richness inferred for macro-organisms are similar for micro-organisms. For this, we barcoded samples of soil, litter and insects from four localities on a west-to-east transect across Amazonia. We quantified richness as Operational Taxonomic Units (OTUs) in those samples using three molecular markers. We then compared OTU richness with species richness of two relatively well-studied organism groups in Amazonia: trees and birds. We find that OTU richness shows a declining west-to-east diversity gradient that is in agreement with the species richness patterns documented here and previously for birds and trees. These results suggest that most taxonomic groups respond to the same overall diversity gradients at large spatial scales. However, our results show a different pattern of richness in relation to habitat types, suggesting that the idiosyncrasies of each taxonomic group and peculiarities of the local environment frequently override large-scale diversity gradients. Our findings caution against using the diversity distribution of one taxonomic group as an indication of patterns of richness across all groups.

Assessing biotic and abiotic interactions of micro-organisms in Amazonia through co-occurrence networks and DNA metabarcoding

“…General networks composition: Overall, the key nodes of our networks are mainly a liated to Proteobacteria (29 nodes, of which 17 belong to Alphaproteobacteria), Acidobacteria (19), Planctomycetes (12), and Actinobacteria (10, Table S3). These are common groups of bacteria in soils in general [52] and also in our samples [36,37], being the most frequent groups in our networks. Alphaproteobacteria are a highly diverse clade of Gram-negative bacteria with several biological functions, including metabolizing C1 compounds [98], xating nitrogen [99], endosymbiosis such as the widespread and important genus Wolbachia [100], and also intracellular pathogenicity [101].…”

“…1) in November 2015, a month of the dry season without inundation of seasonally ooded forests (around 5 months after inundation peak). The data was previous published in Ritter et al [27,36,37]. In each locality, we sampled all of the four habitats (terra-rme, campinas, várzea, and igapó) whenever they were present ( Fig.…”

The utility of a metagenomics approach for marine biomonitoring

“…This demonstrates that while both techniques are able to distinguish the sampling sites from each other, the exact taxa that are used to do so are completely different. In this way, a metagenomics assay can be seen as an independent confirmation of biological trends observed within metabarcoding experiments, since different taxonomic groups are likely to respond to similar ecological gradients (Ritter et al 2019). Figure 5: The beach samples cluster separately from the other samples in the metabarcoding data (A), and this is also true of the metabarcoding data (B), although with greater variation primarily due to two odd datapoints from deep-and moderate-depth water.…”

Assessing Biotic and Abiotic Interactions of Microorganisms in Amazonia through Co-Occurrence Networks and DNA Metabarcoding

“…Recent studies have shown that Amazonian habitat types influence the composition of microbial communities [36]. Microorganism diversity is the richest in campina habitats [36,37], in contrast to known patterns of macro-organisms that show low diversity in these habitats [38,39]. Campinas have a highly specialized biota, probably explained by multiple stressors that affect the habitat, such as poor soils and insular distribution [38].…”