Resumo

ARTURI, Marcelo F et al. Spatial trends and tree canopy incidence in Austrocedrus chilensis regeneration. Ecol. austral [online]. 2001, vol.11, n.1, pp.31-38. ISSN 1667-782X.

We analyzed the relationships among the type of canopy in Austrocedrus chilensis forests, the density of saplings (individuals <5 cm DBH) and their spatial trends. We classified saplings into three height classes (0.5-1 m, 1-2 m, and >2 m), and we measured its densities in two sites, each one corresponding to a protected area (El Guadal and Loma del Medio) located in SW Río Negro Province, Argentina. We recorded the number of Austrocedrus chilensis individuals in each class. Also, we annotated the presence-absence of tree species in the canopy, defining canopy types, in each sample unit. Canopy type data was employed for sample units-ordination through Principal Coordinates Analysis. We performed a correlation analysis between sapling density and a competition index that quantifies the degree of site occupation by adult individuals (>5 cm DBH). Additionally, we analyzed the spatial trend of the density of each sapling height class and of the type of canopy variable obtained by multivariate analysis. We used polynomial regressions on x and y spatial coordinates defined as the sides of a 50 x 50 m quadrat in each site. The highest density of saplings of the tallest class preferred sites without canopy of the same species. Sapling individuals of the lowest class were distributed independently of the canopy type, but were positively associated to sites with a larger occupation by adults in both sites. Sapling height growth was strongly and positively associated to its height. Taller saplings showed well-defined spatial trends. However, we did not detected spatial trends in the canopy type. Saplings with greater growth established more than 40 years ago, and the canopy type of the sites probably changed from that time until our sampling date. The canopy type observed would be not favorable to regeneration and, then, it is not reliable to predict the recruitment success taking into account the actual canopy condition.

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