Modelos preditivos para estimar a biomassa de 'Spartina argentinensis'
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Na Argentina, as pastagens naturais cobrem vastas áreas, prestando importantes serviços ecossistêmicos. Tradicionalmente, a pecuária tem sido a principal atividade produtiva nesses ambientes, com o uso do fogo como prática comum de manejo. Embora as queimadas estimulem o rebrote de gramíneas com melhor qualidade forrageira, elas também resultam na emissão de CO2eq na atmosfera, o que apresenta desafios ambientais. Diante da crescente demanda por fontes de energia renovável, as pastagens naturais, manejadas em sistemas pecuários com queimadas frequentes, apresentam-se como uma alternativa sustentável para a produção de bioenergia. Na província de Santa Fe, as pastagens de esparto dominadas por Spartina argentinensis nos Baixos Submeridionais, cobrindo mais de dois milhões de hectares, têm um elevado potencial para a produção de bioenergia sem comprometer a biodiversidade existente. Este trabalho foca no desenvolvimento e avaliação de modelos preditivos de biomassa de S. argentinensis utilizando imagens espectrais obtidas por drones. Foram desenvolvidos modelos de regressão linear múltipla e de classificação, considerando variáveis espectrais, locais e sazonais, para predizer a biomassa total e suas frações verdes e senescentes. Os modelos obtidos para estimar a biomassa total de Spartina permitiram explicar até 62% de sua variabilidade. As frações de biomassa verde e senescente puderam ser previstas com maior precisão, apresentando um R² de 66% para cada uma. Essas descobertas destacam o potencial da tecnologia de sensoriamento remoto para otimizar o planejamento e manejo sustentável dos recursos de biomassa nas pastagens argentinas.
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