Abstract The highly biodiverse Atlantic Forest has been heavily exploited and its remnant areas, which are mostly composed of secondary forests, cover less than 20% of its original extension. This study analyzed the structure, aboveground biomass (AGB) and species diversity of a secondary evergreen rainforest in the state of Santa Catarina, southern Brazil. Individuals with diameter at breast height ≥ 5 cm on 22 sample plots were measured, totalizing 3.49 hectares of sampled area. A mean AGB of 201.6 Mg ha-1 (standard deviation = 35.5) was found; Hyeronima alchorneoides and Miconia cinnamomifolia represented 29.1% and 7.6% of the community AGB ha-1, respectively. A total of 153 species distributed in 107 genera and 55 families was observed; it was estimated that 121 species (95% confidence interval: [117, 125]) occurred in one hectare. These results highlight the importance of secondary forests for biodiversity restoration/conservation and carbon sequestration.

ABSTRACT: A key issue in large-area inventories is defining a suitable sampling design and the effort required to obtain reliable estimates of species richness and forest attributes, especially in species-diverse forests. To address this issue, data from 418 systematically distributed 0.4 ha plots were collected. Estimators of nonparametric species richness were employed to assess the floristic representativeness of data collected in three forest types in the Brazilian Atlantic Forest. The sampling sufficiency of forest attributes was evaluated as a function of sample size. Altogether, 831 tree/shrub species were recorded. The data acquired through the systematic sampling design were representative of both species richness and basal area. The confidence intervals’ length would not substantially decrease by using more than 70 % of the reference sample (n = 364), thereby reaching a length of ∼5 % of the sample mean. Nevertheless, reliable estimates of species richness for diverse forests demand a thorough sampling approach far more exacting so as to achieve acceptable population estimates of forest attributes. Though the study area is regarded as a biodiversity hotspot, the forest stands showed diminished species richness, basal area, stem volume and biomass when compared to old-growth stands. As regards species richness, the data provided evidence of contrasting great γ-diversity (at the forest type level) and small α-diversity (at the forest stand level). Amongst anthropic impacts, illegal logging and extensive cattle grazing within stands are undoubtedly key factors that threaten forest conservation in the study area.

ABSTRACT The effect of environmental variables on the plant species distribution in the Atlantic Forest raises the interest of researchers, but few studies, mainly at local scales, analyzed the influence of spatial factors on the environment and species distribution. Linear models and spatial correlograms were used to evaluate whether environment and space may predict variations in species composition of trees and shrubs in a Subtropical Rainforest remnant. The study area was divided in 25 plots of 400 m², systematically distributed, where individuals with DBH ≥ 5 cm were measured. Elevation and slope were the most important predictors of the floristic variations, but space, generally neglected in researches on South American's vegetation, had a relevant influence, as a structural component, in terms of environmental variables, and as intrinsic biological component, here probably as result of constraints in species dispersion. Although the origin of great part of the variation in species composition remained unknown, which is common in studies on vegetation, results indicated, for the first time, the complex role of spatial and environmental variables in the composition of trees and shrub species in a Subtropical Rainforest of Brazil.

<p>Em florestas naturais, a altura total das árvores (h) é, muitas vezes, difícil de medir. Nesses casos, modelos de regressão baseados em variáveis de fácil medição, como o DAP (d), são uma alternativa, desde que seus pressupostos sejam atendidos. Neste estudo, objetivou-se i) o ajuste de modelos hipsométricos para três tipologias florestais de Santa Catarina (Floresta Estacional Decidual, Floresta Ombrófila Mista, Floresta Ombrófila Densa), testando os pressupostos e avaliando a qualidade dos ajustes; ii) verificação de diferenças das relações hipsométricas entre as tipologias florestais e entre os modelos ajustados baseados em alturas medidas e estimadas. Os dados de 1.766 alturas medidas e 3.150 alturas estimadas em campo foram coletados pelo Inventário Florístico Florestal de Santa Catarina (IFFSC), em 418 unidades amostrais. Os modelos foram ajustados para ambos os conjuntos de dados. Modelos específicos foram ajustados para espécies com ≥ 30 árvores medidas; normalidade, aleatoriedade e homoscedasticidade dos resíduos foram avaliadas analiticamente. Bandas com intervalos de confiança foram construídas pelo método Working-Hotelling; teste z para médias foi aplicado para comparar os modelos baseados nos dois conjuntos de dados. Parâmetros estatísticos como o AIC evidenciaram melhor ajuste dos modelos logarítmicos. Foram encontradas diferenças nas relações h/d entre as tipologias florestais (DEN e MIX) e entre os conjuntos de dados. O uso de modelos hipsométricos é uma alternativa para estudar a relação h/d e para determinar padrões da estrutura vertical em comunidades florestais, quando a medição de h não é viável, embora em casos da necessidade de maior acurácia das alturas estimadas, os modelos nem sempre possam fornecê-las.</p>

<p>Total tree height (h) is often difficult to measure in natural forests. Regression models based on easily accessed variables like DBH (d) can be an alternative, since their assumptions are validated. The aims of this study are to: (i) calibrate specific and generic h-d models for three forest types (Seasonal Deciduous Forest, DEC; Mixed Ombrophilous Forest, MIX; and Dense Rainforest, DEN) in Santa Catarina state testing the regression assumptions and evaluating model quality; (ii) verify different h-d relationship between forest types. The dataset (1,766 measured tree h and 3,150 estimated h) was collected by Santa Catarina Forest and Floristic Inventory (IFFSC) in 418 systematically located sample plots. Models were calibrated for two datasets, one containing hypsometer measurements, the other h estimations made by field crews. Specific models were calibrated for species with at least 30 sampled trees. Residual normality, randomness and heteroskedasticity were evaluated by analytical methods. Confidence bands were generated by the Working-Hotelling method; z test for means was applied to compare models based on the two databases. The statistical parameters such as corrected Akaike Information Criterion provided evidences that logarithmic models were better adjusted to the data. Both datasets were statistically different for DEN and MIX. Differences in h-d relationships were found between forest types. The use of calibrated h-d models is an alternative for studying the relationships between these variables and to assess vertical structure patterns of forest communities, when h measurements are not feasible, although, for situations that more accurate h values are needed, they will not always provide reliable predictions.</p>