Forest Drought Resistance at Large Geographic Scales

Author:

Brodrick P. G.12ORCID,Anderegg L. D. L.13ORCID,Asner G. P.12ORCID

Affiliation:

1. Department of Global EcologyCarnegie Institution for Science Stanford CA USA

2. Center for Global Discovery and Conservation ScienceArizona State University Tempe AZ USA

3. Department of Integrative BiologyUniversity of California Berkeley Berkeley CA USA

Funder

National Science Foundation

Publisher

American Geophysical Union (AGU)

Subject

General Earth and Planetary Sciences,Geophysics

Reference56 articles.

1. Abadi M. Barham P. Chen J. Chen Z. Davis A. Dean J. Devin M. Ghemawat S. Irving G. Isard M. Kudlur M. Levenberg J. Monga R. Moore S. Murray D. G. Steiner B. Tucker P. Vasudevan V. Warden P. Wicke M. Yu Y. &Zheng X.(2016).TensorFlow: Large‐scale machine learning on heterogeneous distributed systems. InProceedings of the 12th USENIX Symposium on Operating Systems Design and Implementation (OSDI '16). ISBN: 978‐1‐931971‐33‐1.

2. Tracking Interannual Streamflow Variability with Drought Indices in the U.S. Pacific Northwest

3. On underestimation of global vulnerability to tree mortality and forest die-off from hotter drought in the Anthropocene

4. A global overview of drought and heat-induced tree mortality reveals emerging climate change risks for forests

5. Not all droughts are created equal: translating meteorological drought into woody plant mortality

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