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@MastersThesis{Seixas:2020:UsLaSu,
               author = "Seixas, Hugo Tameir{\~a}o",
                title = "Using land surface models to explore and improve estimations of 
                         resilience of vegetation to droughts",
               school = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                 year = "2020",
              address = "S{\~a}o Jos{\'e} dos Campos",
                month = "2020-03-31",
             keywords = "resilience, drought, primary productivity, land surface model, 
                         Caatinga, resili{\^e}ncia, secas, produ{\c{c}}{\~a}o 
                         prim{\'a}ria, modelo de superf{\'{\i}}cie terrestre.",
             abstract = "The concept of resilience can be helpful in describing the 
                         relationship between vegetation and climate, specially in a 
                         context of climate change. However, the quantification and 
                         characterization of resilience is a great challenge, due to the 
                         high complexity of this concept, and also the difficulty in 
                         comparing different ecosystems across the globe. Many studies were 
                         already made with the effort of creating methods which enables the 
                         comparison between different systems, however, there are still 
                         limitations, and there is still space to improve these methods. In 
                         order to explore the quantification of resilience of vegetation to 
                         drought, we performed a series of simulations by a land surface 
                         model (LSM) by manipulating climate data, which was used to 
                         estimate the resilience and its components over a dataset with 
                         high variation of precipitation regimes. These simulation were 
                         performed in the semi-arid region of Caatinga. We also performed 
                         an assessment of the LSM performance over the area, in order to 
                         give support to the resilience characterization by the model. 
                         Results shows that the model was able to represent annual fluxes 
                         of water, energy and carbon, and thus, it was possible to use its 
                         outputs to estimate the resilience.We also showed that the 
                         quantification of resilience can be represented as a function 
                         between precipitation variation with gross primary productivity 
                         (GPP), which enables a more detailed characterization of the 
                         resilience of the vegetation to droughts. RESUMO: O conceito de 
                         resili{\^e}ncia pode ser {\'u}til para descrever a 
                         rela{\c{c}}{\~a}o entre vegeta{\c{c}}{\~a}o e clima, 
                         especialmente em um contexto de mudan{\c{c}}as clim{\'a}ticas. 
                         No entanto, a quantifica{\c{c}}{\~a}o e 
                         caracteriza{\c{c}}{\~a}o da resili{\^e}ncia {\'e} um grande 
                         desafio, devido {\`a} alta complexidade desse conceito e 
                         tamb{\'e}m {\`a} dificuldade em comparar diferentes ecossistemas 
                         ao redor do mundo. Muitos estudos j{\'a} foram feitos com o 
                         objetivo de criar m{\'e}todos que possibilitem a 
                         compara{\c{c}}{\~a}o entre diferentes ecosistemas, no entanto, 
                         ainda existem limita{\c{c}}{\~o}es e ainda h{\'a} espa{\c{c}}o 
                         para aprimoramento desses m{\'e}todos. Para explorar a 
                         quantifica{\c{c}}{\~a}o da resili{\^e}ncia da 
                         vegeta{\c{c}}{\~a}o {\`a} seca, realizamos uma s{\'e}rie de 
                         simula{\c{c}}{\~o}es por um modelo de superf{\'{\i}}cie 
                         terrestre (LSM), manipulando dados clim{\'a}ticos, que foram 
                         utilizados para estimar a resili{\^e}ncia e seus componentes, em 
                         um conjunto de dados com alta varia{\c{c}}{\~a}o de regimes de 
                         precipita{\c{c}}{\~a}o. Essas simula{\c{c}}{\~o}es foram 
                         realizadas na regi{\~a}o do semi-{\'a}rido brazileiro 
                         (Caatinga). Tamb{\'e}m realizamos uma avalia{\c{c}}{\~a}o do 
                         desempenho do LSM na {\'a}rea, a fim de dar suporte {\`a} 
                         caracteriza{\c{c}}{\~a}o da resili{\^e}ncia pelo modelo. Os 
                         resultados mostram que o modelo foi capaz de representar fluxos 
                         anuais de {\'a}gua, energia e carbono e, portanto, foi 
                         poss{\'{\i}}vel usar seus resultados para estimar a 
                         resili{\^e}ncia da vegeta{\c{c}}{\~a}o da {\'a}rea de estudo. 
                         Tamb{\'e}m mostramos que a quantifica{\c{c}}{\~a}o da 
                         resili{\^e}ncia pode ser representada como uma fun{\c{c}}{\~a}o 
                         entre a varia{\c{c}}{\~a}o da precipita{\c{c}}{\~a}o com 
                         produtividade prim{\'a}ria bruta (GPP), que permite uma 
                         caracteriza{\c{c}}{\~a}o mais detalhada da resili{\^e}ncia da 
                         vegeta{\c{c}}{\~a}o {\`a}s secas.",
            committee = "Moraes, Elisabete Caria (presidente/orientadora) and Brunsell, 
                         Nathaniel Alan (orientador) and Lapola, David Montenegro and 
                         Oliveira, Gabriel de",
         englishtitle = "Usando modelos de superf{\'{\i}}cie terrestre para explorar e 
                         melhorar estimativas de resili{\^e}ncia da vegeta{\c{c}}{\~a}o 
                         {\`a} secas",
             language = "en",
                pages = "68",
                  ibi = "8JMKD3MGP3W34R/4297UL2",
                  url = "http://urlib.net/rep/8JMKD3MGP3W34R/4297UL2",
           targetfile = "publicacao_FA provisoria.pdf",
        urlaccessdate = "12 abr. 2021"
}


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