Detalhes bibliográficos
| Ano de defesa: |
2017 |
| Autor(a) principal: |
Tymus, Julio Ricardo Caetano
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| Orientador(a): |
Oliveira Filho , Paulo Costa de
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| Banca de defesa: |
Não Informado pela instituição |
| Tipo de documento: |
Dissertação
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| Tipo de acesso: |
Acesso aberto |
| Idioma: |
por |
| Instituição de defesa: |
Universidade Estadual do Centro-Oeste
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| Programa de Pós-Graduação: |
Programa de Pós-Graduação em Ciências Florestais (Mestrado)
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| Departamento: |
Unicentro::Departamento de Ciências Florestais
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| País: |
Brasil
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| Palavras-chave em Português: |
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| Palavras-chave em Inglês: |
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| Área do conhecimento CNPq: |
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| Link de acesso: |
http://tede.unicentro.br:8080/jspui/handle/jspui/1377
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Resumo: |
Climate change threats have spurred discussions and initiatives around the globe in recent years to restore natural ecosystems - especially forests - to mitigate and adapt to possible scenarios related to it. To contribute to international restoration goals, Brazil will seek to recover 12 million hectares of forests by 2030. To achieve this goal, inter alia, it is necessary to increase knowledge about the environmental factors that drive the forests’ natural regeneration process, considering increasing the use of passive restoration techniques. This research sought to analyze if only landscape environmental factors could be applied to identify lands suitable for passive restoration techniques in tropical forests, as there are many studies reporting such potentiality. Thus, 78 plots of 4m X 25m (sample units - SUs) were evaluated in restoration areas of the Atlantic forest biome, located in Camboriú river watershed, southern of Brazil. In these plots, development parameters of native tree and shrub vegetation (response variables), as well local factors that could influence the natural regeneration (local predictors) were measured. Through geoprocessing techniques and tools, in nine of 78 plots, the percentages of area represented by different classes of land use and occupation were analyzed - considering a 100m radius plot from the geographical center of each sample (landscape predictors). Data from nine SUs were statistically analyzed to verify the ability of landscape and local variables to explain natural regeneration results. For this, regression models were applied using the akaike information criterion (AIC). The importance of each variable was determined by adding the % explanation of the determination coefficient, when the predictor was inserted in the model. In addition, analyzes of variance with one factor and Fisher's test were performed to all 78 SUs, seeking to prove the significance (p <0.05) of the effects of "Initial Scenario" and "Herbaceous Infestation" variables on the results of development of natural regeneration. The results showed a higher percentage of explanation for local predictors, to the detriment of the predictive landscape. The predictive variables with the highest percentage of individual explanation in the selection of models were “Herbaceous Infestation” and “Initial Scenario”. These local predictors allowed to submit the data matrix to a new analysis and with a greater number of sample units (78), improving results’ strength. The percentage of herbaceous infestation was again evaluated, showing negative effects (p < 0.05) to passive restoration, as its percentage increased; and the initial scenario, demonstrating that less disturbed areas present better natural regeneration development results. Among the landscape environmental factors, only "Rural Roads" and " Propagules’ Source Fragments" presented significant effects - the highest percentages of explanation attributed to the last one. Landscape environmental factors, although relevant, cannot explain the development of natural forest regeneration process in the Atlantic forest biome. This can limit the exclusive use of landscape features in the identification of lands suitable for the use of passive restoration techniques. |
