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Inferring population trends of Araucaria angustifolia (Araucariaceae) using a transition matrix model in an old-growth forest


Giovani F. Paludo
Miguel B. Lauterjung
Maurício S. dos Reis
Adelar Mantovani

Abstract

Matrix population models may generate important information to prevent undesirable outcomes for endangered species. This is the case for Araucaria angustifolia, a Critically Endangered conifer, with little knowledge regarding its life history and trends in development over time. This study sought to investigate life-history trends of an A. angustifolia population in a subtropical forest in Santa Catarina, Brazil. Predictions based on the Lozenge regeneration model were established in order to determine if this model could predict changes in the species’ population dynamics: (1) the established individuals exhibit long persistence and (2) seedling and sapling abundance, as well as population descriptors, should exhibit behaviour that indicates one of the stages prescribed by the model. All A. angustifolia individuals were evaluated within a 5.1 ha plot at the study site over a six-year period. Lefkovitch’s transition model was used and population descriptors were calculated. Both predictions were fulfilled. The population had λ = 0.9977 (0.9864 < λ < 1.0020; CI 95%), indicating a declining stability. The basal area remained stable, whereas tree density tended to decrease, and seedlings and saplings did not promote an increase in λ. These results indicate that the population was in a phase called thinning, defined by the Lozenge model. The results led to three conclusions: recruitment seems insufficient; survival of reproductive individuals is responsible for the longevity of the population; and the predictions did not refute the Lozenge model. According to this model, the population is expected to regenerate in the future. However, the species exhibits declining stability, which aggravates the endangerment situation.

Keywords: Araucaria forest, Brazilian pine, mixed ombrophilous forest, natural regeneration, population dynamics


Journal Identifiers


eISSN: 2070-2639
print ISSN: 2070-2620