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Understanding the importance of temperature and precipitation on plant productivity is beneficial, to reveal the potential impact of climate change on vegetation growth. Although some studies have quantified the response of vegetation productivity to climate change at local, regional, and global scales, changes in climatic constraints on vegetation productivity over time are not well understood. This study combines the normalized difference vegetation index (NDVI) and the net primary production (NPP) modeled by CASA during the plant-growing season, to quantify the interplay of climatic (growing-season temperature and precipitation, GST and GSP) constraints on alpine-grassland productivity on the Tibetan Plateau, as well as the temporal dynamics of these constraints. The results showed that (1) 42.2% and 36.3% of grassland NDVI and NPP on the Tibetan Plateau increased significantly from 2000 to 2019. GSP controlled grassland growth in dryland regions, while humid grasslands were controlled by the GST. (2) The response strength of the NDVI and NPP to precipitation (partial correlation coefficient RNDVI-GSP and RNPP-GSP) increased substantially between 2000 and 2019. Especially, the RNDVI-GSP and RNPP-GSP increased from 0.14 and 0.01 in the first 10year period (2000–2009) to 0.83 and 0.78 in the second 10-year period (2010–2019), respectively. As a result, the controlling factor for alpine-grassland productivity variations shifted from temperature during 2000–2009 to precipitation during 2010–2019. (3) The increase in precipitation constraints was mainly distributed in dryland regions of the plateau. This study highlights that the climatic constraints on alpine-grassland productivity might change under ongoing climate change, which helps the understanding of the ecological responses and helps predict how vegetation productivity changes in the future.

Two dimensional (2D) metal-organic frameworks (MOFs) is one of the most promising photocatalysts owing to its highly exposed active sites and superior charge mobility. However, the synthesis of high-stable 2D...

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Summary This paper introduces a new and unique full‐scale testbed site for structural health monitoring and soil–structure system identification studies being developed in southwest China. The site is a 48‐story skyscraper with an extended four‐level basement, supported by piles, located in Kunming, the capital of Yunnan Province. Located in the diffused zone of collision of the Indian and Eurasian tectonic plates, Yunnan is one of the most active seismic areas in mainland China. The final sensor deployment will consist of 43 triaxial accelerometers (129 channels) and one weather station. The accelerometer array comprises (a) a structural array of 25 accelerometers installed at 10 levels aboveground, (b) a basement array of 14 accelerometers distributed in the first and fourth basements, and (c) two borehole arrays installed close to the basement perimeter wall, each with one accelerometers at the surface and another one at 50‐m depth, which is the depth reached by the piles. With such dense instrumentation of structure, basement, and pile foundation, this site will be the first permanently instrumented full‐scale testbed to enable identification of a soil‐foundation–basement‐structure system and validation of many assumptions commonly made in the prediction of the soil–structure interaction effects. A high‐performance wired local area network has been installed in the building, featuring a Precision Time Protocol‐enabled time synchronization and real‐time remote access over the Internet. The site will be fully operational in late spring of 2020. Results of preliminary system identification of the structure from ambient vibration test data are presented.

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