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Recent debates on the number of plant species in the vast lowland rain forests of the Amazon have been based largely on model estimates, neglecting published checklists based on verified voucher data. Here we collate taxonomically verified checklists to present a list of seed plant species from lowland Amazon rain forests. Our list comprises 14,003 species, of which 6,727 are trees. These figures are similar to estimates derived from nonparametric ecological models, but they contrast strongly with predictions of much higher tree diversity derived from parametric models. Based on the known proportion of tree species in neotropical lowland rain forest communities as measured in complete plot censuses, and on overall estimates of seed plant diversity in Brazil and in the neotropics in general, it is more likely that tree diversity in the Amazon is closer to the lower estimates derived from nonparametric models. Much remains unknown about Amazonian plant diversity, but this taxonomically verified dataset provides a valid starting point for macroecological and evolutionary studies aimed at understanding the origin, evolution, and ecology of the exceptional biodiversity of Amazonian forests.Amazonia | floristics | rain forests | seed plants | species diversity

Quantitative data are presented on the use of trees in terra firme dense forest by four indigenous Amazonian groups: the Ka'apor and Tembe, both Tupi‐Guarani‐speaking groups of Brazil; the Panare, a Cariban‐speaking group of Venezuela; and the Chácobo, a Panoan‐speaking group of Bolivia. In each case, an ethnoecological forest inventory was conducted of a 1‐hectare parcel of forest. All trees at least 10 centimeters diameter at breast height (DBH) were marked, and botanical specimens were collected Specimens were presented to indigenous informants to gather data on use. Based on these interviews and the identifcation of specimens collected, it was possible to calculate the percentage of tree species on each hectare that was useful to each group: Ka'apor, 768 percent; Tembe 61.3 percent; Panare, 48.6 percent; Chacobo, 78.7 percent. Furthermore, by dividing the trees into various use categories (food construction, technology, remedy, commerce, and other), and designating the cultural importance of each species as “major” or “minor,” it was possible to devise a “use value” for each species, and by summation, for each plant family. Based on these calculations, it was determined that the Palmae was the most useful family for all four indigenous groups. Our data support the assertion that the terra firme rainforests of Amazonia contain an exceptionally large number of useful species and that certain plant families (e.g. Palmae) deserve special consideration in terms of conservation. The fact that each indigenous group has different suites of most useful species is, in fact, more a reflection of plant endemism within Amazonia than intercultural differences per se. High indigenous plant use combined with high endemism has important implications for conservation policy: many reserves are needed throughout Amazonia

Despite the importance of species discovery, the processes including collecting, recognizing, and describing new species are poorly understood. Data are presented for flowering plants, measuring quantitatively the lag between the date a specimen of a new species was collected for the first time and when it was subsequently described and published. The data from our sample of new species published between 1970 and 2010 show that only 16% were described within five years of being collected for the first time. The description of the remaining 84% involved much older specimens, with nearly one-quarter of new species descriptions involving specimens >50 y old. Extrapolation of these results suggest that, of the estimated 70,000 species still to be described, more than half already have been collected and are stored in herbaria. Effort, funding, and research focus should, therefore, be directed as much to examining extant herbarium material as collecting new material in the field.herbarium specimen | monograph | taxonomy A ccurate species recognition underpins our knowledge of global biodiversity (1-3). In recent years, the lack of taxono mic activity has led to increased political (4) and scientific calls (3) to invest in the science of taxonomy, which is fundamental for what we know about species-level diversity. The assumptions behind these demands are that increased resources would necessarily lead to increased taxonomic productivity and accuracy. Given finite resources, it is essential that scientifically sound criteria regarding where funds should most usefully be targeted are used to determine priorities for taxonomic research. It is therefore surprising that the processes of collecting, recognizing, and describing species are poorly understood and only rarely discussed (5-7) and that there is little research focused on the processes that result in the recognition of new species. Many groups of organisms are so poorly known that measuring any aspect of the discovery process suffers from lack of data. In terms of completing the species-level "inventory of life," the flowering plants are viewed as an attainable priority research target because they are already relatively well known and the final inventory is estimated to be only 10-20% from completion (8). Furthermore, plants are pivotal organisms for monitoring and measuring global biodiversity because they comprise a species-rich component of almost all habitats on earth (9). An enhanced scientific understanding of the discovery process for flowering plants could help define specific priorities for funding agencies and facilitate the meeting of global biodiversity targets. Here, we focus on the temporal dynamics of the lag between the collection of flowering plant specimens and their subsequent recognition and description as new species (7). For a representative dataset, the discovery time (I) between the date of the earliest specimen collected (C) and date the description was published (D) was calculated for each species (Fig. 1). ResultsDiscovery I ranged fro...