Gross Primary

Gross Primary Production (GPP), the rate at which plants convert carbon dioxide into organic matter through photosynthesis, is a critical component of the global carbon cycle. Current research focuses on improving GPP estimation using advanced machine learning techniques, such as recurrent neural networks (RNNs, LSTMs, GRUs), and process-informed models that integrate ecological knowledge with data-driven approaches, including Temporal Fusion Transformers. These efforts aim to overcome limitations of traditional methods, particularly the sparsity of ground-based measurements, leading to more accurate and spatially-resolved GPP estimates crucial for understanding climate change impacts and informing carbon mitigation strategies. Improved GPP modeling also extends to marine ecosystems, with research focusing on predicting coral reef productivity based on environmental factors.