@Article{SeixasBruMorOliMat:2022:ExEcRe,
               author = "Seixas, Hugo Tameir{\~a}o and Brunsell, Nathaniel A. and Moraes, 
                         Elisabete Caria and Oliveira, Gabriel de and Mataveli, Guilherme 
                         Augusto Verola",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {University 
                         of Kansas} and {Instituto Nacional de Pesquisas Espaciais (INPE)} 
                         and {University of South Alabama} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)}",
                title = "Exploring the ecosystem resilience concept with land surface model 
                         scenarios",
              journal = "Ecological Modelling",
                 year = "2022",
               volume = "464",
                pages = "e109817",
                month = "Feb.",
             keywords = "Drought, Ecosystem resilience, Land surface model, Primary 
                         productivity, Semi-arid.",
             abstract = "The concept of resilience can be helpful in describing the 
                         relationship between vegetation and climate, especially when 
                         considering the likelihood of more extreme climate events due to 
                         global warming. However, the quantification and characterization 
                         of resilience is a challenge, due to the inherent complexity of 
                         the concept, as well as difficulty in comparing different 
                         ecosystems across the globe. In order to explore ecosystem 
                         resilience to drought, we estimated the resilience and related 
                         metrics from a series of land surface model (LSM) simulations with 
                         altered climate forcing data, focusing on the responses to 
                         changing precipitation. These simulations were performed in the 
                         semi-arid region of Caatinga biome, northeastern Brazil. Results 
                         showed that the quantification of resilience can be represented as 
                         a function between precipitation variation and gross primary 
                         productivity (GPP) variation. We compared the resilience 
                         components estimated for different vegetation types, which showed 
                         differences in the response of vegetation to precipitation 
                         variability. The study shows the potential of using LSMs to 
                         improve our understanding of the vegetation response to climate 
                         change, allowing us to explore possible scenarios that are usually 
                         not available in field experiments.",
                  doi = "10.1016/j.ecolmodel.2021.109817",
                  url = "http://dx.doi.org/10.1016/j.ecolmodel.2021.109817",
                 issn = "0304-3800",
             language = "en",
           targetfile = "seixas_exploring.pdf",
        urlaccessdate = "04 maio 2024"
}