Produtividade primária, uso da água e diversidade funcional a partir de um novo modelo vegetacional: primeira aplicação sob CO2 elevado
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Data
2017-07-27
Autores
Prado, Helena Alves do [UNESP]
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Universidade Estadual Paulista (Unesp)
Resumo
A importância das florestas tropicais para o ciclo de carbono global e a incerteza de suas respostas a novas condições ambientais evidenciam a necessidade de aprofundar o conhecimento acerca de como as mudanças climáticas repercutirão nas dinâmicas florestais e nos processos fisiológicos associados. Essa dissertação, vinculada ao experimento AmazonFACE, objetiva avaliar como o incremento de CO2 atmosférico poderia repercutir na produtividade e eficiência no uso da água da Floresta Amazônica; se atributos funcionais envolvidos nesses processos (vcmax e g1) seriam modificados; e se ocorreriam mudanças na configuração funcional modelada da região. Para melhor caracterizar a diversidade funcional e as diferentes estratégias de sobrevivência adotadas pelas plantas em um ecossistema hiperdiverso, desenvolveu-se o CAETÊ (Carbon and Ecosystem Functional-Trait Evaluation Model) que, diferentemente dos modelos baseados em tipos funcionais, não parametriza a priori as possíveis combinações de atributos funcionais e simula um número superior de estratégicas de vida (PLS), sendo essas amostradas semi-aleatoriamente pelo modelo. Ao avaliar a performance do CAETÊ, verificou-se que a consideração de um número elevado de PLS – em vez de uma abordagem baseada em poucos tipos funcionais – simula maiores taxas de produtividade e condutância estomática; e que esse aumento tende à estabilização, com o aumento de estratégias consideradas. A aplicação do modelo foi feita utilizando a concentração de CO2 a ser empregada no AmazonFACE, de 600 ppm. Nas simulações, verificou-se uma redução nos valores médios de vcmax e g1, assim como uma modificação nos seus padrões de distribuição. Essas alterações associaram-se a um incremento nas taxas modeladas de produtividade e no uso da água, nas florestas tropicais, próximo a 13.5% (GPP) e 14.2% (NPP); redução de 3.8% na condutância estomática; e maior eficiência no uso da água (+21.1%). O enriquecimento da atmosfera também esteve associado à redução de ~5.5% na riqueza funcional. À medida que se avança para condições ambientais sem precedentes, torna-se de grande valia o uso de novas abordagens pelos modelos vegetacionais, que possibilitem a consideração de um número superior de estratégias de sobrevivência das plantas; e a captação de possíveis alterações nas respostas de atributos funcionais essenciais e, consequentemente, na riqueza funcional dos ecossistemas. As florestas tropicais desempenham um papel essencial nessas dinâmicas, uma vez que, além de hiperdiversas, são centrais para o ciclo de carbono global.
The importance of tropical forests in the global carbon cycle and the uncertainty of the forest’s responses to new environmental conditions evidence the necessity of deepening our knowledge about how climate changes affect forest dynamics and the associated physiological processes. This dissertation, linked to the AmazonFACE experiment, aims to evaluate how increasing atmospheric levels of CO2 could influence primary productivity and water use efficiency of the Amazon Forest; if functional traits involved in such processes (vcmax e g1) would be modified; and if changes would occur in the region’s modeled functional configuration. Aiming for a better characterization of the functional diversity and the different survival strategies adopted by plants in a hyperdiverse ecosystem, we developed the CAETÊ (Carbon and Ecosystem Functional-Trait Evaluation Model) which, unlike models based on functional types, does not perform a priori parameterization of the possible combinations of functional traits and simulates a superior amount of life strategies (PLS), that are semi-randomly sampled by the model. When evaluating CAETÊ’s performance, we verified that the consideration high number of PLS – instead of a framework based in few functional types – simulates higher amounts of productivity and stomatal conductance; and that such increase tends to stabilization when more strategies are considered. The model was applied using the CO2 concentration to be used in AmazonFACE – 600ppm. Simulations showed a reduction in the average values of de vcmax and g1, as well as a change in their patterns of distribution. Such alterations are associated to an increase in modeled values of productivity and water use of tropical forests close to 13.5% (GPP) and 14.2% (NPP), a reduction of 3.8% in stomatal conductance, and higher efficiency in water use (+21.1%). The atmospheric enrichment was also associated with a ~5.5% reduction in the functional richness. As the environment advances to unprecedented conditions, it becomes clear how worthy is the use of new approaches by vegetational models that enable consideration of higher numbers of plant survival strategies; and the uptake of possible changes in responses of essential functional traits, therefore, in the functional richness of the environment. The tropical forests influence deeply such dynamics; once beyond hyperdiverse.
The importance of tropical forests in the global carbon cycle and the uncertainty of the forest’s responses to new environmental conditions evidence the necessity of deepening our knowledge about how climate changes affect forest dynamics and the associated physiological processes. This dissertation, linked to the AmazonFACE experiment, aims to evaluate how increasing atmospheric levels of CO2 could influence primary productivity and water use efficiency of the Amazon Forest; if functional traits involved in such processes (vcmax e g1) would be modified; and if changes would occur in the region’s modeled functional configuration. Aiming for a better characterization of the functional diversity and the different survival strategies adopted by plants in a hyperdiverse ecosystem, we developed the CAETÊ (Carbon and Ecosystem Functional-Trait Evaluation Model) which, unlike models based on functional types, does not perform a priori parameterization of the possible combinations of functional traits and simulates a superior amount of life strategies (PLS), that are semi-randomly sampled by the model. When evaluating CAETÊ’s performance, we verified that the consideration high number of PLS – instead of a framework based in few functional types – simulates higher amounts of productivity and stomatal conductance; and that such increase tends to stabilization when more strategies are considered. The model was applied using the CO2 concentration to be used in AmazonFACE – 600ppm. Simulations showed a reduction in the average values of de vcmax and g1, as well as a change in their patterns of distribution. Such alterations are associated to an increase in modeled values of productivity and water use of tropical forests close to 13.5% (GPP) and 14.2% (NPP), a reduction of 3.8% in stomatal conductance, and higher efficiency in water use (+21.1%). The atmospheric enrichment was also associated with a ~5.5% reduction in the functional richness. As the environment advances to unprecedented conditions, it becomes clear how worthy is the use of new approaches by vegetational models that enable consideration of higher numbers of plant survival strategies; and the uptake of possible changes in responses of essential functional traits, therefore, in the functional richness of the environment. The tropical forests influence deeply such dynamics; once beyond hyperdiverse.
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Palavras-chave
Efeito de fertilização por CO2, Modelos vegetacionais, Diversidade funcional, Florestas tropicais, CO2 fertilization effect, Vegetation models, Functional diversity, Tropical forests