@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/ibi/8JMKD3MGP3W34R/4297UL2",
targetfile = "publicacao_FA provisoria.pdf",
urlaccessdate = "23 set. 2024"
}