Detalhes bibliográficos
| Ano de defesa: |
2020 |
| Autor(a) principal: |
SALAMI, Gabriela
 |
| Orientador(a): |
FERREIRA, Rinaldo Luiz Caraciolo |
| Banca de defesa: |
GUERA, Ouorou Ganni Mariel,
FINGER, César Augusto Guimarães,
MEUNIER, Isabelle Maria Jacqueline,
GALLO, Ricardo |
| Tipo de documento: |
Tese
|
| Tipo de acesso: |
Acesso aberto |
| Idioma: |
por |
| Instituição de defesa: |
Universidade Federal Rural de Pernambuco
|
| Programa de Pós-Graduação: |
Programa de Pós-Graduação em Ciências Florestais
|
| Departamento: |
Departamento de Ciência Florestal
|
| País: |
Brasil
|
| Palavras-chave em Português: |
|
| Área do conhecimento CNPq: |
|
| Link de acesso: |
http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/8938
|
Resumo: |
Studies that aim to quantify biomass and its carbon stored in different successional stages are important with regard to obtaining information for forest management and conservation over time, especially after processes of landscape degradation, since these actions cause changes that considerably alter the balance and forest dynamics. Therefore, the main objective of this study was to analyze the biomass and carbon stock dynamics in a tropical dry forest in the semiarid region of Pernambuco from 2008 to 2018; as such, the dynamics and carbon stocks of aerial and soil biomass were estimated in two areas with different history of disturbance and use; verifying whether the forest is functioning as a carbon source or fixer, in addition to analyzing and representing the spatial distribution of the carbon stock in aerial biomass. Permanent plots of 20 m x 20 m (400 m²) were set up in two areas with different history of use and conservation: LCA – less conserved area and CA – conserved area. Between 2008 and 2018, the remeasurement of tree individuals was carried out through a forest inventory of permanent plots, where all individuals with a circumference at 1.30 m from the ground (CAP) ≥ 6 cm were identified and labeled. To estimate the biomass stock, exclusive allometric equations for eight species of the Caatinga were used, in addition to a general equation for the other species, and the carbon stock was estimated by the biomass product of each individual by their respective carbon percentage. To estimate the carbon stock of the soil, allometric equations were used for the total carbon and for the fractions of humic substances (humic acid, fulvic acid and humine) in the initial 0-0.20 m layer of the soil. For the biomass and carbon dynamics in vegetation, growth estimates were obtained through gross and net growth (including and excluding inflow respectively) between the intervals of each measurement. To analyze and represent the spatial distribution of the biomass and carbon stocks, the 80 plots were georeferenced with sub-metric precision and, from the generated coordinate tables, the biomass and carbon stock data were associated, in addition to the number of individuals and shafts for each plot, performing then the procedures of variographic analysis, cross-validation and data interpolation. The statistical analysis of the biomass and carbon stock data was carried out through multivariate analysis of variance of repeated measures using the differences in carbon accumulation in the vegetation over time (from 2008 to 2018); for carbon stock variations over the years, non-parametric analysis of variance was used by employing the Friedman test and the Wilcoxon post-test. Spatial distribution analyzes and the thematic map elaboration were carried out through Geostatistics, by using Kriging interpolations in the GS+ program. The results found show that in the period of 10 years there was an increase in the stocks of biomass and carbon for LPA while for PA there was a reduction. They also show that in the first, aerial biomass is functioning as a carbon fixer, but in the second, although there was a decrease in the biomass carbon stock, it can continue to act as a fixative, since an increase in soil carbon has been observed over the same period. Due to the influence of the land use history and the preservation time of the areas, the spatial distribution of the biomass and carbon stocks showed high spatial dependence. |
