Accurate estimates of biodiversity and species composition are essential to understanding the assembly of communities, to predicting consequences of global change, and to prioritizing areas for conservation and management. However, accurate data remain limited in many hyperdiverse systems such as tropical forests, even for well inventoried groups such as trees, not only due to limited coverage of many field campaigns but also due to the arduous process of identifying and standardizing taxonomic determinations.
Here we propose a method to assess the uncertainty of tropical woody plant inventory data so that it can be propagated in models of species distribution, forest composition and associated ecosystem processes such as carbon cycling.
We define a putative novel species (PNS) as a taxonomic entity hypothesized to be distinct from all known sister taxa based on careful comparisons of vouchers identified by taxonomic specialists. PNS are often removed from large-scale meta-analyses of flora because they have not been standardized across datasets.
We assembled two coordinated datasets of Amazonian woody plants including 175 1-ha forest inventory plots representing 140,000 trees with DBH > 10 cm of 1900 distinct taxa, together with 74 0.1 ha plots representing 26,000 stems with DBH > 2.5cm of 2200 distinct taxa. We estimate the uncertainty of an inventory within a community of higher taxonomic clade, such as a family, as the proportion of stems represented by PNS; and we evaluated the taxonomic and geographic patterns of uncertainty and its consistency between the two inventories.
Results/Conclusions
Overall, PNS represent about 25% of taxa and >8% of stems, even though they are omitted from most regional modeling analyses. We report consistent variation even across the largest plant families, from less than 20% in Rubiaceae and Malvaceae, to more than 40% in Lauraceae and Myrtaceae.
Our study identifies the importance of taxonomic uncertainty in tropical forest inventories, even for relatively well-studied groups such as woody plants. Furthermore, our method of putative novel species allows for taxonomic uncertainty to be propagated in models of species distribution or regional ecosystem processes such as carbon stocks and fluxes.