![]() | Draft article not currently submitted for review.
This is a draft Articles for creation (AfC) submission. It is not currently pending review. While there are no deadlines, abandoned drafts may be deleted after six months. To edit the draft click on the "Edit" tab at the top of the window. To be accepted, a draft should:
It is strongly discouraged to write about yourself, your business or employer. If you do so, you must declare it. Where to get help
How to improve a draft
You can also browse Wikipedia:Featured articles and Wikipedia:Good articles to find examples of Wikipedia's best writing on topics similar to your proposed article. Improving your odds of a speedy review To improve your odds of a faster review, tag your draft with relevant WikiProject tags using the button below. This will let reviewers know a new draft has been submitted in their area of interest. For instance, if you wrote about a female astronomer, you would want to add the Biography, Astronomy, and Women scientists tags. Editor resources
Last edited by Luo-Ecolab (talk | contribs) 43 days ago. (Update) |
Yiqi Luo is a Liberty Hyde Bailey Professor at Cornell University. He is a modeler in the fields of biogeochemistry, ecosystem ecology, and global change ecology, but with extensive experimental experience in the past.
The overall goal of the research in his lab is to advance predictive understanding of biogeochemical cycles of terrestrial ecosystems under the global change. Key scientific questions to be addressed include: (1) how global change alters biogeochemistry of terrestrial ecosystems and what is the underlying mechanism for such alterations, and (2) how the changes in biogeochemistry of terrestrial ecosystems feedback to global change. These scientific questions are addressed by integrating data with ecosystem models. The main approaches include process-based modeling, data synthesis, data-model fusion via data assimilation and machine learning, and theoretical analysis.
His lab developed the DYNAMIC DISEQUILIBRIUM framework to assess future land carbon sink dynamics, the MATRIX APRROACH to unify land carbon cycle models, and the TRACEABILTY framework to diagnose the uncertainty in model predictions of land carbon cycle.