The high species richness of tropical forests has long been recognized, yet there remains substantial uncertainty regarding the actual number of tropical tree species. Using a pantropical tree inventory database from closed canopy forests, consisting of 657,630 trees belonging to 11,371 species, we use a fitted value of Fisher's alpha and an approximate pantropical stem total to estimate the minimum number of tropical forest tree species to fall between ∼ 40,000 and ∼ 53,000, i.e., at the high end of previous estimates. Contrary to common assumption, the Indo-Pacific region was found to be as species-rich as the Neotropics, with both regions having a minimum of ∼ 19,000-25,000 tree species. Continental Africa is relatively depauperate with a minimum of ∼ 4,500-6,000 tree species. Very few species are shared among the African, American, and the Indo-Pacific regions. We provide a methodological framework for estimating species richness in trees that may help refine species richness estimates of tree-dependent taxa.

Forest restoration by planting trees often accelerates succession, but the trajectories toward reference ecosystems have rarely been evaluated. Using a chronosequence (4–53 years) of 26 riparian forest undergoing restoration in the Brazilian Atlantic Forest, we modeled how the variables representing forest structure, tree species richness and composition, and the proportion of plant functional guilds change through time. We also estimated the time required for these variables to reach different types of reference ecosystems: old‐growth forest (OGF), degraded forest, and secondary forest. Among the attributes which follow a predictable trajectory over time are: the basal area, canopy cover, density and tree species richness, as well as proportions of shade tolerant and slow growing species or individuals. Most of the variation in density of pteridophythes, lianas, shrubs and phorophythes, proportion of animal‐dispersed individuals, rarefied richness and floristic similarity with reference ecosystems remain unexplained. Estimated time to reach the reference ecosystems is, in general, shorter for structural attributes than for species composition or proportion of functional guilds. The length of this time varies among the three types of reference ecosystems for most attributes. For instance, tree species richness and proportion of shade tolerant or slow growing individuals become similar to secondary forests in about 40 years, but is estimated to take 70 years or more to reach the OGF. Of all the variables considered, canopy cover, basal area, density, and richness of the understory—by their ecological relevance and predictability—are recommended as ecological indicators for monitoring tropical forest restoration success.

SignificanceIdentifying and explaining regional differences in tropical forest dynamics, structure, diversity, and composition are critical for anticipating region-specific responses to global environmental change. Floristic classifications are of fundamental importance for these efforts. Here we provide a global tropical forest classification that is explicitly based on community evolutionary similarity, resulting in identification of five major tropical forest regions and their relationships: (i) Indo-Pacific, (ii) Subtropical, (iii) African, (iv) American, and (v) Dry forests. African and American forests are grouped, reflecting their former western Gondwanan connection, while Indo-Pacific forests range from eastern Africa and Madagascar to Australia and the Pacific. The connection between northern-hemisphere Asian and American forests is confirmed, while Dry forests are identified as a single tropical biome.

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Question:Identifying the factors that lead to the success of restoration projects has been a major challenge in ecological restoration. Here we ask which factors, aside from time since restoration began, drive the recovery of tree biomass, density and richness of the understorey in riparian forests undergoing restoration.Location: Semideciduous Atlantic Forest with tropical climate and deep, fertile soils, southeast Brazil. Methods:We sampled tree basal area (DBH ≥ 5 cm), density and richness of the understorey (DBH < 5 cm) in 26 riparian forests undergoing restoration (a chronosequence spanning 4-53 years). We assessed the following variables as possible factors, besides time, influencing community attributes: (1) planting design: density and richness of seedlings planted; (2) landscape features: proximity index measuring forest cover within a 1.5-km radius, distance and size of the nearest forest remnant; and (3) environmental factors: invasive grasses, soil fertility, drought, average annual precipitation and proportion of fine particles in the soil. We performed correlation analyses including predictor and response variables, followed by stepwise backward regression (AIC), multiple and simple linear regressions, to investigate the relationships between those factors and the community attributes.

RESUMO -Os objetivos deste trabalho foram: (1) registrar as vantagens e desvantagens de cinco metodologias utilizadas para avaliar a cobertura do dossel (interpretação de ecounidades, densiômetro esférico, fotografia hemisférica com lente de 8 mm e fotografia digital com lente de 32 mm) e a quantidade de luz que o atravessa (luxímetro e fotografia hemisférica com lente de 8 mm); e (2) comparar a estrutura do dossel de um reflorestamento e de um fragmento de Floresta Estacional Semidecídual no norte do Paraná. A classificação em ecounidades é uma metodologia rápida e barata, mas com baixa reprodutibilidade. O densiômetro produz medidas rápidas e confiáveis, e o luxímetro e a fotografia com lente de 32 mm forneceram dados com pouca precisão, pois são sensíveis a pequenas variações do dossel, e a fotografia com lente de 8 mm é uma metodologia rápida e de alta precisão, mas apresenta alto custo. Analisando-se a estrutura do dossel, não houve diferenças significativas entre o densiômetro e a fotografia em 8 mm em nenhum dos dois ambientes; a fotografia em 32 mm apresentou resultados diferentes, com grande variação nas médias, indicando alta sensibilidade a pequenas alterações no dossel. Na avaliação da quantidade de luz que penetra no sub-bosque, o luxímetro e a lente de 8 mm foram diferentes. Todas as metodologias apresentaram diferenças entre a floresta madura e o reflorestamento.Palavras-chave: Cobertura do dossel, densiômetro e ecounidades. COMPARING METHODOLOGIES TO ASSESS CANOPY COVER AND UNDERSTOREY LIGHT ENVIRONMENT OF A REFORESTATION AREA AND A MATURE FOREST

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The absence of species composition among the indicators of restoration success, recommended for the Brazilian Atlantic Forest by Suganuma and Durigan, was criticized by Reid. In his critic, Reid argues that species composition can be (1) predictable from site history and restoration technique and (2) a surrogate for poor ecosystem functioning and lack of resilience. We disagree on the deterministic view behind the first argument, and the latter is still controversial. Even though, we recommended richness as a good indicator of ecosystem functioning instead of composition-which depends on the exhaustive labor of botanical identification.Choosing ecological indicators is always challenging and that has been a hot topic in both the science and practice of restoration. We recently modeled the trajectories of riparian forests undergoing restoration using a chronosequence of their attributes, and recommended a set of indicators to assess restoration success (Suganuma & Durigan 2015). In a reply, Reid (2015) criticized the exclusion of species composition from the set of indicators we suggested. Here, we provide a counter-response and consider this constructive debate can substantially advance our understanding and predictive capability to restore riparian forests.We did not include species composition because this attribute (1) is not predictable over time, (2) does not become similar to the reference ecosystems in a reasonable time period, and (3) relies on the exhaustive labor of botanical identification. Therefore, instead of species composition, we recommended the number of species regenerating as a surrogate for biodiversity recovery and persistency. Reid (2015) argues that our indicator selection method was flawed, resulting in a set of indicators that are insensitive to common restoration failures, such as poor ecosystem functioning and lack of resilience, and that if, in addition to age, site history or restoration technique had been included as predictor variables in our models, species composition should then be predictable.Reid (2015) argues that good chronosequences rely on the assumption that age is the primary difference between sites and that this assumption was not met by this study because our sites varied in size, land use history, and restoration technique. In this study, however, we acknowledge and discuss the limitations of chronosequences. These limitations can generate false unpredictability for variables not following an expected trajectory for the entire region, when, in a particular site, they can clearly increase or decrease over time. For this reason, our set of recommended indicators includes only those attributes strongly influenced by age and for which we found a consistent pattern for the entire region, despite differences in site history and restoration techniques. We argue that unexplained variation of the valid models, as well as the broad variation found in nonarboreal life forms or relative abundance of animal-dispersed species, suggests that other processes (restoration technique, ...