Unseen rare tree species in southeast Brazilian forests : a species abundance distribution approach

Terra, M.C.N.S. and Silveira, E.M.O. and Withey, K.D. and de Mello, J.M. and Cordeiro, N.G. and Pereira, K.M.G. and Scolforo, J.R.S. (2020) Unseen rare tree species in southeast Brazilian forests : a species abundance distribution approach. Community Ecology, 21. 229–238.

Abstract

Rarity is an important aspect of biodiversity often neglected in ecological studies. Species abundance distributions (SADs) are useful tools to describe patterns of commonness–rarity in ecological communities. Most studies assume field observations of species relative abundances are approximately equal to their true relative abundances, thus dismissing the potential for, and importance of unseen rare species. Here, we adopted the approach proposed by Chao et al. (Ecol, 96:1189–1201, 2015) to estimate the number and abundance of unseen species, and thus the true SADs, for tree species in 48 forest sites in Minas Gerais state, Brazil (4 rainforests, 35 semideciduous forests, and 9 deciduous forests). Also, we assessed the correlations between both unseen and rare species and sampling protocol and environment characteristics (climate, terrain, terrain heterogeneity). We found estimated true SADs invariably had higher species richness values than observed in the surveys, due to the increase in rare species. We estimate that up to 55.6% of tree species per site were unseen (8.5–55.6%), with an average of 26.6%. The estimated percentage of rare species per site was between 31.9% and 72.8%, with an average of 57.78%. We found rarity to be most strongly correlated with the percentage of unidentified trees, local terrain conditions and heterogeneity at site-level. Semideciduous forest and rainforest had similar higher percentages of unseen species (c. 27.2%) when compared to deciduous forests, probably due to the relatively higher local heterogeneity of these forests, which may provide more niches for rare species. Future studies should consider estimating true species abundances to better assess biodiversity. © 2020, Akadémiai Kiadó Zrt.