Fatores de variação das estimativas de precipitação interna em uma floresta secundária

• Ano de defesa: 2017
• Autor(a) principal: Lima, Raul Sampaio de
• Orientador(a): Tanaka, Marcel Okamoto
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de São Carlos; Câmpus São Carlos
• Programa de Pós-Graduação: Programa de Pós-Graduação em Ciências Ambientais - PPGCAm
• Palavras-chave em Português: Desenho experimental; Ecossistema tropical; Estabilidade temporal; Pluviômetros rotativos; Variabilidade espacial
• Palavras-chave em Inglês: Experimental design; Roving gauges; Spatial variability; Temporal stability; Tropical ecosystem
• Área do conhecimento CNPq: CIENCIAS BIOLOGICAS
• Link de acesso: https://repositorio.ufscar.br/handle/20.500.14289/9150

Throughfall (TF) is affected by different biotic and meteorological factors that can interact, resulting in high variability in estimates, increasing the uncertainty in hydrological models and the forecast of environmental impacts in watersheds. The knowledge of the relationship between rainfall (RF) and TF is a key factor for the definition of sampling strategies that result within commonly accepted error thresholds. Therefore, the main objective of this study was to analyze sources of TF variability in a secondary forest in SE Brazil, in order to understand the response of TF in function of different environmental drivers and sampling strategies. To attain these objectives, the influences of RF, sampling strategies, and stand structure on TF were analysed. The results indicated significant influence of RF on the response variables [TF volume (TFmm), TF fraction (TF%), and coefficient of variation of TF (CVTF)]. Whereas the linear model showed the best fit for TFmm, nonlinear models presented better fits for TF% and CVTF in response to RF. Regarding the influence of sampling strategies, there were no significant effects on average estimates of TFmm and CVTF. Based on the magnitude of the error, only treatments with 16 fixed gauges and nine roving gauges were able to provide estimates with errors smaller than 10%, both for all rainfall events and for those higher than 10.44 mm (median value). The results suggest that different vegetation structures affect TFmm at different spatial scales. For instance, a significant effect of canopy cover was observed on the point estimates of TFmm. However, no vegetation influences on this variable were observed at the plot scale. Regarding the temporal variability, significant effects were verified at two scales: distance to the nearest trunk at the point scale; and metrics of trees greater than 20 m at the plot scale. Finally, it was verified that combined effects of tree sizes and canopy cover influenced CVTF, indicating that the these variables reflect vegetation complexity. In general, the results suggest that RF is the main source of TF variability in the studied area. Therefore, it is necessary to consider both meteorological factors and characteristics of rainfall events to sample TF with adequate accuracy. Nevertheless, the interactions between biotic and meteorological factors affect their relative influences on TF, highlighting the need for further research in this area.