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Our work yields insights into climate change impacts on land ecosystems and provides data-informed predictions of how forests and grasslands respond to a climatic extreme events, rising CO2 and changes in nutrient cycles. We use Earth observation data and develop process-based models that are founded on eco-evolutionary optimality principles to explain plant traits and their adaptation and acclimation to the environment. In more data-driven approaches, we apply machine learning and data assimilation techniques using diverse ecological data (ecosystem flux measurements, forest inventories, remote sensing, and manipulation experimental data, etc.). In brief, we are building models, as simple as possible and as complex as necessary to learn the most. All open access, of course.
研究兴趣
论文共 172 篇作者统计合作学者相似作者
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biorxiv(2024)
Huanyuan Zhang-zheng, Xiongjie Deng,Benjamin Stocker, Ruijie Ruijie,Eleanor Thomson,Stephen Adu-Bredu,Akwasi Duah-Gyamfi, Agne Gvozdevaite,Sam Moore, Imma Oliveras Menor,I. Colin Prentice,Yadvinder Malhi
biorxiv(2024)
crossref(2024)
crossref(2024)
crossref(2024)
bioRxiv (Cold Spring Harbor Laboratory) (2023)
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T. F. Keenan, X. Luo,B. D. Stocker,M. G. De Kauwe,B. E. Medlyn,I. C. Prentice,N. G. Smith,C. Terrer,H. Wang, Y. Zhang, S. Zhou
Nature Climate Changeno. 12 (2023): 1376-1381
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