Submitted by Automa??o e Estat?stica (sst@bczm.ufrn.br) on 2016-05-10T23:18:28Z
No. of bitstreams: 1
KionaraSarabellaTuribioESilva_DISSERT.pdf: 1524779 bytes, checksum: a034505b357fab3aef4e1f83a7bbc3d6 (MD5) / Approved for entry into archive by Arlan Eloi Leite Silva (eloihistoriador@yahoo.com.br) on 2016-05-18T19:54:55Z (GMT) No. of bitstreams: 1
KionaraSarabellaTuribioESilva_DISSERT.pdf: 1524779 bytes, checksum: a034505b357fab3aef4e1f83a7bbc3d6 (MD5) / Made available in DSpace on 2016-05-18T19:54:55Z (GMT). No. of bitstreams: 1
KionaraSarabellaTuribioESilva_DISSERT.pdf: 1524779 bytes, checksum: a034505b357fab3aef4e1f83a7bbc3d6 (MD5)
Previous issue date: 2015-06-15 / O bioma Caatinga, ecossistema de clima semi?rido localizado no nordeste do Brasil, apresenta forte sazonalidade com baixo regime de precipita??o. Esta regi?o possui as proje??es de mudan?as clim?ticas mais alarmantes do pa?s, com o aumento temperatura do ar e a redu??o da pluviosidade com tend?ncias mais fortes que as previs?es m?dias globais. As mudan?as clim?ticas no bioma podem acarretar na diminui??o da cobertura vegetal e altera??o de sua distribui??o, bem como do funcionamento ecossist?mico. Desta forma, influencia fortemente na diversidade de esp?cies. Nesse contexto, a proposta desse estudo ? modelar a din?mica da vegeta??o em fun??o das condi??es ambientais (pluviosidade e temperatura), bem como predizer as consequ?ncias das mudan?as clim?ticas, baseadas nesses determinantes ambientais para o verdor da vegeta??o. O ?ndice de vegeta??o EVI (Enhanced Vegetation Index) foi usado para estimar o verdor da vegeta??o no bioma. A fim de considerar a forte autocorrrela??o temporal e espacial, bem como a heterogeneidade presente nos dados, v?rios modelos GLS (Generalized Least Squares) foram desenvolvidos e comparados para se obter o melhor modelo. Tal modelo refletiu a influ?ncias das condi??es ambientais na previs?o do verdor da vegeta??o no futuro. Diante da aplica??o dos novos cen?rios de mudan?as clim?ticas no modelo, a modifica??o dos determinantes ambientais, pluviosidade e temperatura, influenciou negativamente no verdor da vegeta??o no bioma Caatinga. Esse modelo foi usado para criar imagens de vegeta??o potencial nos per?odos presente e futuro do bioma Caatinga considerando que at? 2040 haver? uma diminui??o de 20% da precipita??o e um aumento de 1?C na temperatura; at? 2070 haver? uma diminui??o de 35% na precipita??o e um aumento de 2,5?C na temperatura; e at? o final do s?culo o percentual de diminui??o das chuvas alcan?ar? 50% e a temperatura ter? um aumento de at? 4,5?C. Os resultados desse estudo sugerem que o funcionamento do ecossistema ser? afetado com a diminui??o de 5,9% do verdor da vegeta??o at? 2040, 14,2% at? 2070 e 24,3 % at? o final do s?culo. A vegeta??o da Caatinga em ?reas de baixa altitude (maior parte do bioma) ser? mais afetada pelas mudan?as clim?ticas. / The Caatinga biome, a semi-arid climate ecosystem found in northeast Brazil, presents low rainfall regime and strong seasonality. It has the most alarming climate change projections within the country, with air temperature rising and rainfall reduction with stronger trends than the global average predictions. Climate change can present detrimental results in this biome, reducing vegetation cover and changing its distribution, as well as altering all ecosystem functioning and finally influencing species diversity. In this context, the purpose of this study is to model the environmental conditions (rainfall and temperature) that influence the Caatinga biome productivity and to predict the consequences of environmental conditions in the vegetation dynamics under future climate change scenarios. Enhanced Vegetation Index (EVI) was used to estimate vegetation greenness (presence and density) in the area. Considering the strong spatial and temporal autocorrelation as well as the heterogeneity of the data, various GLS models were developed and compared to obtain the best model that would reflect rainfall and temperature influence on vegetation greenness. Applying new climate change scenarios in the model, environmental determinants modification, rainfall and temperature, negatively influenced vegetation greenness in the Caatinga biome. This model was used to create potential vegetation maps for current and future of Caatinga cover considering 20% decrease in precipitation and 1 ?C increase in temperature until 2040, 35% decrease in precipitation and 2.5 ?C increase in temperature in the period 2041-2070 and 50% decrease in precipitation and 4.5 ?C increase in temperature in the period 2071-2100. The results suggest that the ecosystem functioning will be affected on the future scenario of climate change with a decrease of 5.9% of the vegetation greenness until 2040, 14.2% until 2070 and 24.3% by the end of the century. The Caatinga vegetation in lower altitude areas (most of the biome) will be more affected by climatic changes.
| Identifer | oai:union.ndltd.org:IBICT/oai:repositorio.ufrn.br:123456789/20502 |
| Date | 15 June 2015 |
| Creators | Silva, Kionara Sarabella Tur?bio e |
| Contributors | 01086633709, http://lattes.cnpq.br/1733681004723492, Venticinque, Eduardo Martins, 07873068862, http://lattes.cnpq.br/3582966116563351, Silva, Thiago Sanna Freire, 03603892445, http://lattes.cnpq.br/2062933732399088, Almeida, Adriana Monteiro de |
| Publisher | Universidade Federal do Rio Grande do Norte, PROGRAMA DE P?S-GRADUA??O EM ECOLOGIA, UFRN, Brasil |
| Source Sets | IBICT Brazilian ETDs |
| Language | Portuguese |
| Detected Language | Unknown |
| Type | info:eu-repo/semantics/publishedVersion, info:eu-repo/semantics/masterThesis |
| Source | reponame:Repositório Institucional da UFRN, instname:Universidade Federal do Rio Grande do Norte, instacron:UFRN |
| Rights | info:eu-repo/semantics/openAccess |
Page generated in 0.0026 seconds