Fatores de variação das estimativas de precipitação interna em uma floresta secundária
Autor(a) principal: | |
---|---|
Data de Publicação: | 2017 |
Tipo de documento: | Dissertação |
Idioma: | por |
Título da fonte: | Repositório Institucional da UFSCAR |
Texto Completo: | https://repositorio.ufscar.br/handle/ufscar/9150 |
Resumo: | 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. |
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Lima, Raul Sampaio deTanaka, Marcel Okamotohttp://lattes.cnpq.br/2768658925977757Bourscheidt, Vandoirhttp://lattes.cnpq.br/8224261649535795http://lattes.cnpq.br/5256512160106710b22c991c-eec3-45a2-bae1-cb54dde346042017-10-11T11:52:44Z2017-10-11T11:52:44Z2017-07-05LIMA, Raul Sampaio de. Fatores de variação das estimativas de precipitação interna em uma floresta secundária. 2017. Dissertação (Mestrado em Ciências Ambientais) – Universidade Federal de São Carlos, São Carlos, 2017. Disponível em: https://repositorio.ufscar.br/handle/ufscar/9150.https://repositorio.ufscar.br/handle/ufscar/9150Throughfall (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.A precipitação interna (PI) é afetada por diferentes fatores bióticos e meteorológicos que podem interagir entre si, resultando numa elevada variabilidade em suas estimativas, aumentando a incerteza em modelos hidrológicos e na previsão de impactos ambientais em bacias hidrográficas. A compreensão da relação entre a precipitação em aberto (PA) e a PI é importante para a definição de estratégias de amostragem com limiares de erros aceitáveis. Portanto, o objetivo geral deste estudo foi analisar os fatores de variação da PI em uma floresta secundária, localizada no sudeste brasileiro, a fim de compreender o comportamento desse processo em função de diferentes fatores ambientais e de estratégias de amostragem. Para isto, foram analisadas as influências da PA, das estratégias de amostragem e da estrutura da vegetação sobre a PI. Os resultados indicaram influência significativa da PA sobre as variáveis resposta [volume de PI (PImm), fração de PI (PI%) e coeficiente de variação da PI (CVPI)]. Enquanto o modelo linear apresentou o melhor ajuste para PImm, os modelos não lineares tiveram melhores ajustes para PI% e CVPI em função de PA. Quanto à influência das estratégias de amostragem, não houve efeitos significativos sobre as estimativas médias de PImm e CVPI. Com base na magnitude do erro, apenas tratamentos com 16 pluviômetros fixos e nove rotativos foram capazes de fornecer estimativas com erros inferiores a 10%, tanto para o conjunto completo de dados quanto para chuvas superiores a 10,44 mm (valor mediano). Os resultados sugerem que diferentes estruturas da vegetação afetam a PImm em diferentes escalas espaciais. Por exemplo, foi verificado efeito significativo da cobertura do dossel sobre as estimativas pontuais de PImm. No entanto, não foram verificadas influências da vegetação sobre esta variável na escala da parcela. Em relação à variabilidade temporal, verificaram-se efeitos significativos nas duas escalas: da distância para o tronco mais próximo na pontual; e de métricas de árvores maiores que 20 m na escala parcela. Por fim, verificou-se que os efeitos combinados do tamanho das árvores e da cobertura do dossel influenciaram CVPI, indicando que essas variáveis refletem a complexidade da vegetação. Em geral, os resultados sugerem que PA é a principal fonte de variabilidade de PI na área estudada. Portanto, é necessário considera características meteorológicas e dos eventos de chuva para amostrar a PI com precisão adequada. Contudo, as interações entre fatores bióticos e meteorológicos afetam suas influências relativas sobre a PI, destacando a necessidade de mais pesquisas nessa área.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)porUniversidade Federal de São CarlosCâmpus São CarlosPrograma de Pós-Graduação em Ciências Ambientais - PPGCAmUFSCarDesenho experimentalEcossistema tropicalEstabilidade temporalPluviômetros rotativosVariabilidade espacialExperimental designRoving gaugesSpatial variabilityTemporal stabilityTropical ecosystemCIENCIAS BIOLOGICASFatores de variação das estimativas de precipitação interna em uma floresta secundáriainfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisOnline600600fa5182ab-01d1-42af-9ec5-d9c364d79b6finfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFSCARinstname:Universidade Federal de São Carlos (UFSCAR)instacron:UFSCARORIGINALDissRSL.pdfDissRSL.pdfapplication/pdf2218443https://repositorio.ufscar.br/bitstream/ufscar/9150/1/DissRSL.pdf6c095cccc15f22c3fe747197514a5b16MD51LICENSElicense.txtlicense.txttext/plain; charset=utf-81957https://repositorio.ufscar.br/bitstream/ufscar/9150/2/license.txtae0398b6f8b235e40ad82cba6c50031dMD52TEXTDissRSL.pdf.txtDissRSL.pdf.txtExtracted texttext/plain223148https://repositorio.ufscar.br/bitstream/ufscar/9150/3/DissRSL.pdf.txtd25a95129c10f613dbe9d5e95176869fMD53THUMBNAILDissRSL.pdf.jpgDissRSL.pdf.jpgIM Thumbnailimage/jpeg6361https://repositorio.ufscar.br/bitstream/ufscar/9150/4/DissRSL.pdf.jpg9376c7777f569f5e87212b64fe1ce6d5MD54ufscar/91502023-09-18 18:31:26.467oai:repositorio.ufscar.br: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Repositório InstitucionalPUBhttps://repositorio.ufscar.br/oai/requestopendoar:43222023-09-18T18:31:26Repositório Institucional da UFSCAR - Universidade Federal de São Carlos (UFSCAR)false |
dc.title.por.fl_str_mv |
Fatores de variação das estimativas de precipitação interna em uma floresta secundária |
title |
Fatores de variação das estimativas de precipitação interna em uma floresta secundária |
spellingShingle |
Fatores de variação das estimativas de precipitação interna em uma floresta secundária Lima, Raul Sampaio de Desenho experimental Ecossistema tropical Estabilidade temporal Pluviômetros rotativos Variabilidade espacial Experimental design Roving gauges Spatial variability Temporal stability Tropical ecosystem CIENCIAS BIOLOGICAS |
title_short |
Fatores de variação das estimativas de precipitação interna em uma floresta secundária |
title_full |
Fatores de variação das estimativas de precipitação interna em uma floresta secundária |
title_fullStr |
Fatores de variação das estimativas de precipitação interna em uma floresta secundária |
title_full_unstemmed |
Fatores de variação das estimativas de precipitação interna em uma floresta secundária |
title_sort |
Fatores de variação das estimativas de precipitação interna em uma floresta secundária |
author |
Lima, Raul Sampaio de |
author_facet |
Lima, Raul Sampaio de |
author_role |
author |
dc.contributor.authorlattes.por.fl_str_mv |
http://lattes.cnpq.br/5256512160106710 |
dc.contributor.author.fl_str_mv |
Lima, Raul Sampaio de |
dc.contributor.advisor1.fl_str_mv |
Tanaka, Marcel Okamoto |
dc.contributor.advisor1Lattes.fl_str_mv |
http://lattes.cnpq.br/2768658925977757 |
dc.contributor.advisor-co1.fl_str_mv |
Bourscheidt, Vandoir |
dc.contributor.advisor-co1Lattes.fl_str_mv |
http://lattes.cnpq.br/8224261649535795 |
dc.contributor.authorID.fl_str_mv |
b22c991c-eec3-45a2-bae1-cb54dde34604 |
contributor_str_mv |
Tanaka, Marcel Okamoto Bourscheidt, Vandoir |
dc.subject.por.fl_str_mv |
Desenho experimental Ecossistema tropical Estabilidade temporal Pluviômetros rotativos Variabilidade espacial |
topic |
Desenho experimental Ecossistema tropical Estabilidade temporal Pluviômetros rotativos Variabilidade espacial Experimental design Roving gauges Spatial variability Temporal stability Tropical ecosystem CIENCIAS BIOLOGICAS |
dc.subject.eng.fl_str_mv |
Experimental design Roving gauges Spatial variability Temporal stability Tropical ecosystem |
dc.subject.cnpq.fl_str_mv |
CIENCIAS BIOLOGICAS |
description |
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. |
publishDate |
2017 |
dc.date.accessioned.fl_str_mv |
2017-10-11T11:52:44Z |
dc.date.available.fl_str_mv |
2017-10-11T11:52:44Z |
dc.date.issued.fl_str_mv |
2017-07-05 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.citation.fl_str_mv |
LIMA, Raul Sampaio de. Fatores de variação das estimativas de precipitação interna em uma floresta secundária. 2017. Dissertação (Mestrado em Ciências Ambientais) – Universidade Federal de São Carlos, São Carlos, 2017. Disponível em: https://repositorio.ufscar.br/handle/ufscar/9150. |
dc.identifier.uri.fl_str_mv |
https://repositorio.ufscar.br/handle/ufscar/9150 |
identifier_str_mv |
LIMA, Raul Sampaio de. Fatores de variação das estimativas de precipitação interna em uma floresta secundária. 2017. Dissertação (Mestrado em Ciências Ambientais) – Universidade Federal de São Carlos, São Carlos, 2017. Disponível em: https://repositorio.ufscar.br/handle/ufscar/9150. |
url |
https://repositorio.ufscar.br/handle/ufscar/9150 |
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por |
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info:eu-repo/semantics/openAccess |
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openAccess |
dc.publisher.none.fl_str_mv |
Universidade Federal de São Carlos Câmpus São Carlos |
dc.publisher.program.fl_str_mv |
Programa de Pós-Graduação em Ciências Ambientais - PPGCAm |
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UFSCar |
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Universidade Federal de São Carlos Câmpus São Carlos |
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