XIANGZHONG (REMI) LUO - FASS STAFF PROFILE

Brief Introduction

As a global change ecologist, my work centers on examining the impacts of climate change and anthropogenic land use change on terrestrial ecosystems. I am particularly interested in studying the dynamics of the terrestrial carbon cycle, which plays a significant role in mitigating climate change by taking up about one quarter of anthropogenic CO2 emissions. I use data from several networks of ecological observations (i.e. Fluxnet), state-of-the-art Earth System Models and remote sensing, with results from field experiments to gain a mechanistic understanding of the physical and biological processes that regulate the terrestrial carbon cycle.

Teaching Areas

Terrestrial ecosystems, climate change, ecological modelling, remote sensing

2020-2021 S2, GE3221 Ecological Systems (sole instructor, the module is merged into GE3256 2021 onwards)

2020-2021 S2, GE4211 Advanced Hydrology and Water Resource Management (w/ Dr Pierre Tailladart)

2021-2025 S1, GE4234 Environmental Change in the Tropics (sole instructor)

2021-2023 S2, GE3256 Earth Surface Processes, Landforms and Ecosystems (w/ Dr Nawaz in 2022; w/ Prof Lu Xixi in 2023)

2021-2025 S2, GE2103 Our Planet: An Earth Systems Science Perspective (w/ Prof Massino Lapascu)

Research Interests

Research interests: terrestrial carbon cycle and water cycle, eddy covariance, dynamic vegetation models, leaf traits, remote sensing.

We aim to answer the following questions at scales from leaf to the globe, from hours to decades -- How much carbon do plants take up? How much water do plants need? How do plants respond to climate change (e.g., rising temperature, water stress, CO2 fertilization)? How do we use knowledge on climate and ecology to mitigate climate change impacts?

Leaf

We measured the leaf traits of several species at a mixed forest over the course of 4 years. Our work demonstrated the seasonal variations in leaf photosynthetic capacity (Vcmax25), and highlighted that leaf chlorophyll content is a strong proxy for Vcmax25 than the commonly used leaf nitrogen content (Link). We further apply this chlorophyll – photosynthesis coupling to improve the estimation of ecosystem carbon and water fluxes by models (Link).

Canopy

We tested multiple hypotheses on radiative transfer and leaf-to-canopy upscaling using a terrestrial biosphere model BEPS at several eddy covariance sites, and demonstrated that for forests we need to consider sunlit and shaded leaves separately and avoid the use of canopy-scale parameters at all to better quantify ecosystem photosynthesis and evapotranspiration (Link).

We conducted a deep analysis of ecosystem photosynthetic capacity derived from eddy covariance data to provide first-hand evidence on the widespread light acclimation of photosynthesis and tested its consistence with the ecological optimality theory, highlighting the difference in light use strategy among plants on earth (Link).

Region

We used various satellite data to study the phenology (start and the end of the growing season; SOS and EOS) of deciduous forests in Northern China. We intensively validated the satellite-derived phenological metrics using large set of ground observations (Link), and found that the traditional degree-day phenological model can be used to simulate and predict satellite-derived phenology change in the coming century (Link).

Globe

We used multiple remote sensing-based terrestrial biosphere models and solar-induced fluorescence to study the response of global photosynthesis to climate anomalies. We found that savannah and rainforests contributed the most to the reduction of global GPP during the 2015-2016 El Nino, while grasslands in the Northern Hemisphere showed enhanced GPP (Link).

We used a machine learning approach – Random Forests, with a wide array of leaf traits, climate, soil and remote sensing datasets, to examine the global variations in the plants photosynthetic capacity and how plants adjust their nitrogen use strategy to realise the photosynthetic capacity (Link).

Publications

Please see the full list of publication on Google Scholar (https://scholar.google.com/citations?hl=en&user=iIEZtssAAAAJ)

Highlights:

Luo, X., Zhou, H., Satriawan, T.W., Tian, J., Zhao, R., Keenan, T.F., Griffith, D. M., Sitch, S. Smith, N.G. & Still, C.J. (2024). Mapping the global distribution of C4 vegetation using observations and optimality theory. Nature Communications. https://doi.org/10.1038/s41467-024-45606-3.

Tian, J., Luo, X.*, Xu, H., Green, J.K., Tang, H., Wu, J. & Piao, S. (2024). Slower changes in vegetation phenology than precipitation seasonality in the dry tropics. Global Change Biology. https://doi.org/10.1111/gcb.17134.

Zhang, Z., Luo, X.*, Friess, D., Wang, S., Li, Y. & Li, Y. (2024). Stronger increases but greater variability in global mangrove productivity compared to that of adjacent terrestrial forests. Nature Ecology & Evolution. https://doi.org/10.1038/s41559-023-02264-w.

Luo, X., Keenan, T.F. (2022) Tropical extreme droughts drive long-term increase in atmospheric CO2 growth rate variability. Nature Communications, doi: 10.1038/s41467-022-28824-5. (Covered by The Straits Times)

Luo, X., Keenan, T.F., Chen, J.M., Croft, H., Prentice, I.C., Smith, N.G., Walker, A.P., Wang, H., Wang, R., Xu, C. & Zhang, Y. (2021) Global variation in the fraction of leaf nitrogen allocated to photosynthesis. Nature Communications, doi: 10.1038/s41467-021-25163-9. (Nature Communications Editors' Highlights)

Luo, X., Keenan, T.F. (2020) Global evidence for the acclimation of ecosystem photosynthesis to light. Nature Ecology & Evolution, doi:10.1038/s41559-020-1258-7.

Luo, X., Croft, H., Chen, J.M., He, L. & Keenan, T.F. (2019). Improved estimates of global photosynthesis using information on leaf chlorophyll content. Global Change Biology, doi: 10.1111/gcb.14624.

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Full list of publications (Group members highlighted in bold):

Leng, J., Chen, J.M., Li, W., Luo, X., Xu, M., Liu, J., Wang, R., Rogers, C., Li, B. & Yan Y. (2024). Global datasets of hourly carbon and water fluxes simulated using a satellite-based process model with dynamic parameterizations. Earth System Science Data. (accepted).

Green, J.K., Zhang, Y., Luo, X. & Keenan, T.F. (2024). Systematic underestimation of canopy conductance sensitivity to drought by earth system models. AGU Advances. https://doi.org/10.1029/2023AV001026.

Li, F., Hao, D., Zhu, Q., Yuan, K., Braghiere, R.K., He, L., Luo, X., Wei, S., Riley, W.J., Zeng, Y. & Chen, M. (2024). Global impacts of vegetation clumping on regulating land surface heat fluxes. Agricultural and Forest Meteorology. https://doi.org/10.1016/j.agrformet.2023.109820.

Keenan, T.F., Luo, X., Stocker, B., De Kauwe, M., Medlyn, B., Prentice, I.C., Smith, N., Terrer, C., Wang, H., Zhang, Y. & Zhou, S. (2023). A constraint on historic growth in global photosynthesis due to rising CO2. Nature Climate Change. https://doi.org/10.1038/s41558-023-01867-2.

Ma, Q., Su, Y., Niu, C., Ma, Q., Hu, T., Luo, X., Tai, X., Qiu, T., Zhang, Y., Bales, R.C., Liu, L., Kelly, M. & Guo, Q. (2023). Tree mortality during long-term droughts is lower in structurally complex forest stands. Nature Communications. https://doi.org/10.1038/s41467-023-43083-8.

Yang, Y., Roderick, M.L., Guo, H., Miralles, D. G., Zhang, L., Fatichi, S., Luo, X., Zhang, Y., McVicar, T.R., Tu, Z., Keenan, T.F., Fisher, J.B., Gan, R., Zhang, X., Piao, S., Zhang B. & Yang. D. (2023). Evapotranspiration on a greening Earth. Nature Reviews Earth & Environment, https://doi.org/10.1038/s43017-023-00464-3.

Sun, W., Luo, X., Fang, Y., Shiga, Y., Zhang, Y., Fisher, J., Keenan, T. & Michalak, A. (2023). Biome-scale temperature sensitivity of ecosystem respiration revealed by atmospheric CO2 observations. Nature Ecology & Evolution, https://doi.org/10.1038/s41559-023-02093-x.

Cao, J., Zhang, Z., Tao, F., Chen, Y., Luo, X. & Xie, J. (2023). Forecasting global crop yields based on El Nino Southern Oscillation early signals. Agricultural Systems, https://doi.org/10.1016/j.agsy.2022.103564.

Li, F., Hao, D., Zhu, Q., Yuan, K., Braghiere, R.K., He, L., Luo, X., Wei, S., Riley, W. J., Zeng, Y. & Chen, M. (2023). Vegetation clumping modulates global photosynthesis through adjusting canopy light environment. Global Change Biology, https://doi.org/10.1111/gcb.16503.

Teo, H.C., Raghavan, S.V., He, X., Zeng, Z., Cheng, Y., Luo, X., Lechner, A.M., Ashfold, M.L., Lamba, A., Sreekar, R., Zheng, Q., Chen, A. & Koh, L.P. (2022). Large-scale reforestation can increase water yield and reduce drought risk for water-insecure regions in the Asia-Pacific. Global Change Biology, https://doi.org/10.1111/gcb.16404.

Chen, J.M., Wang, R., Liu, Y., He, L., Croft, H., Luo, X., Wang, H., Smith, N.G., Keenan, T.K., Prentice, I.C., Zhang, Y., Ju, W. & Dong, N. (2022) Global datasets of leaf photosynthetic capacity for ecological and Earth System research. Earth System Science Data, https://doi.org/10.5194/essd-14-4077-2022.

Zhang, Y., Gentine, P., Luo, X., Lian, X., Liu, Y., Zhou, S., Michalak, A.M., Sun, W., Fisher, J.B., Piao, S., Keenan, T.F. (2022) Increasing sensitivity of dryland vegetation greenness to precipitation due to rising atmospheric CO2. Nature Communications, https://doi.org/10.1038/s41467-022-32631-3.

Luo, X., Keenan, T.F. (2022) Tropical extreme droughts drive long-term increase in atmospheric CO2 growth rate variability. Nature Communications, doi: 10.1038/s41467-022-28824-5.

Dong, N., Wright, I., Chen, J., Luo, X., Wang, H., Keenan, T.F., Smith, N. & Prentice, I.C. (2022) Rising CO2 and warming reduce global canopy demand for nitrogen. New Phytologist, doi: 10.1111/nph.18076.

Fu, Z., Ciais, P., Prentice, I.C., Gentine, P., Makowski, D., Bastos, A., Luo, X., Green, J., Stoy, P., Yang, H. & Hajima, T. (2022) Atmospheric dryness reduces photosynthesis along a large range of soil water deficits. Nature Communications, doi: 10.1038/s41467-022-28652-7

Keenan, T.F., Luo, X., De Kauwe, M., Medlyn, B., Prentice, I.C., Stocker, B., Smith, N., Terrer, C., Wang, H., Zhang, Y. & Zhou, S. (2021) A constraint on historic growth in global photosynthesis due to increasing CO2. Nature, doi: 10.1038/s41586-021-04096-9.

Zhang, M., Keenan, T.F., Luo, X. et al. [9 additional co-authors] (2021) Elevated CO2 moderates the impact of climate change on future bamboo distribution in Madagascar. Science of The Total Environment. doi: 10.1016/j.scitotenv.2021.152235.

Luo, X., Keenan, T.F., Chen, J.M., Croft, H., Prentice, I.C., Smith, N.G., Walker, A.P., Wang, H., Wang, R., Xu, C. & Zhang, Y. (2021) Global variation in the fraction of leaf nitrogen allocated to photosynthesis. Nature Communications. doi: 10.1038/s41467-021-25163-9. (Nature Communications Editors' Highlights)

Li, Y., Ma, Q., Chen, J.M., Croft, H., Luo, X., Zheng, T., Rogers, C. & Liu, J. (2021). Fine-scale leaf chlorophyll distribution across a deciduous forest through two-step model inversion from Sentinel-2 data. Remote Sensing of Environment. doi: 10.1016/j.rse.2021.112618.

Sun, W., Fang, Y., Luo, X., Shiga, Y.P., Zhang, Y., Andrews, A.E., Thoning, A.W., Fisher, J.B., Keenan, T.F. & Michalak, A.M. (2021) Midwest U.S. croplands determine model divergence in North American carbon fluxes. AGU Advances. doi: 10.1029/2020AV000310.

Rogers C.A., Chen, J.M., Croft, H., Gonsamo, A., Luo, X., Bartlett, P. & Staebler, R.M. (2021) Daily leaf area index from photosynthetically active radiation for long term records of canopy structure and leaf phenology. Agricultural and Forest Meteorology. doi: 10.1016/j.agrformet.2021.108407.

Chu, H., Luo, X., Yang, Z & 72 co-auhtors. (2021) Representativeness of Eddy-Covariance Flux Footprints for Areas Surrounding AmeriFlux Sites. Agricultural and Forest Meteorology, doi: 10.1016/j.agrformet.2021.108350.

Luo, X., Keenan, T.F. (2020) Global evidence for the acclimation of ecosystem photosynthesis to light. Nature Ecology & Evolution, doi:10.1038/s41559-020-1258-7.

Keenan T.F., Luo X., Zhang Y. & Zhou S. (2020) Ecosystem aridity and atmospheric CO2. Science, 368, 251.2-252, doi: 10.1126/science.abb5449.

Croft, H., Chen, J.M., Mo, G., Luo, S., Luo, X., Arabian, J., Zhang, Y., Simic, A., Noland, T.L., He, Y., Homolová, L., Malenovský, Z., Yi, Q., Beringer, J., Amiri, R., Hutley, L., Arellano, P., Stahl, C. & Bonal, D. (2020). Global distribution of leaf chlorophyll content. Remote Sensing of Environment, doi: 10.1016/j.rse.2019.111479.

Luo, X., Keenan, T.F., Fisher, J.B., Jiménez, J., Chen, J.M., Jiang, C., Ju, W., Perakalapudi, N., Ryu, Y. & Tadić, J.M. (2018). The impact of the 2015-2016 El Niño on global photosynthesis using satellite remote sensing. Philosophical Transactions of the Royal Society B, 373, 20170409.

Luo, X., Croft, H., Chen, J.M., Bartlett, P., Staebler, R. & Froelich, N. (2018). Incorporating leaf chlorophyll content as a proxy for photosynthetic parameters for estimating carbon and water fluxes at a forest site. Agricultural and Forest Meteorology, 248, 156-168.

He, L., Chen, J.M., Gonsamo, A., Luo, X., Wang, R., Liu, Y. & Liu, R. (2018) Changes in the shadow: the shifting role of shaded leaves in global carbon and water cycles under climate change. Geophysical Research Letters, 10.1029/2018GL077560.

Luo, X., Chen, J.M., Liu, J., Black, T.A., Croft, H., Staebler, R., He, L., Arain, M.A., Chen, B., Mo, G., Gonsamo, A. & McCaughey, H. (2018). Comparison of big-leaf, two-big-leaf and two-leaf upscaling schemes for evapotranspiration estimation using coupled carbon-water modelling. Journal of Geophysical Research - Biogeoscience, 10.1002/2017JG003978.

Croft, H., Chen, J.M., Luo, X., Bartlett, P., Chen, B. & Staebler, R. (2017). Leaf chlorophyll content as a proxy for leaf photosynthetic capacity. Global Change Biology, 10.1111/gcb.13599.

He, L., Chen, J.M., Liu, J., Bélair, S. & Luo, X. (2017). Assessment of SMAP soil moisture for global simulation of gross primary production. Journal of Geophysical Research - Biogeoscience, 10.1002/2016JG003603.

Luo, X., Chen, X., Wang, L., Xu, L. & Tian, Y. (2014). Modeling and predicting spring land surface phenology of the Deciduous Broadleaf Forest in northern China, Agricultural and Forest Meteorology, 198-199, 33-41.

Luo, X., Chen, X., Xu, L., Myneni, R. B. & Zhu, Z. (2013). Assessing performance of NDVI and NDVI3g in monitoring leaf unfolding dates of the deciduous broadleaf forest in northern China, Remote Sensing, 5, 845-861.

Other Info

Education and work experience:

· Assistant Professor. National University of Singapore, 2020.11 - now (NUS Presidential Young Professor)

· Postdoctoral Researcher. Lawrence Berkeley National Laboratory & UC Berkeley, 2017.11 - 2020.11

· Ph.D. Physical Geography, University of Toronto. 2013 - 2017.11

· M.Sc. Physical Geography, Peking University. 2010 - 2013

· B.Sc. Environment and Resource Management (GIS & Remote sensing). Wuhan University. 2006 - 2010

Academic Service:

Review: Nature Climate Change, Nature Geoscience, Nature Ecology and Evolution, Nature Communications, Global Change Biology, New Phytologist, Ecology Letters, Remote Sensing of Environment, Global Ecology and Biogeography, Global Biogeochemical Cycles, Geophysical Research Letters, JGR-Biogeoscience, JGR-Atmosphere, Water Resources Research, Environmental Research Letters, Biogeoscience, Earth System Science Data, Earth System Dynamics, Journal of Advances in Modelling Earth Systems, Philosophical Transactions of the Royal Society B, ISPRS Journal of Photogrammetry and Remote Sensing, Agricultural and Forest Meteorology, Cell One Earth, Journal of Hydrology, International Journal of Remote Sensing, Remote Sensing, Canadian Journal of Forest Research, Scientifica Data, Scientific report, Carbon Balance and Management.

Academic associations:

· American Geophysical Union, 2014-now;

· FLUXNET, 2017-now;

· USA-National Phenology Network, 2012-now.

· Asiaflux, 2020-now;

· Canadian Remote Sensing Society, 2018-2019;

Online talks and Media:

CNCS talk - Global photosynthesis in a changing climate

Geoinsider talk (in Mandarin) - Reduce the uncertainty of global photosynthesis simulation

NUS News featured article - Studying the invisible in Earth’s ecosystems to save our planet

The Straits Times - Droughts may affect forest's ability to take in carbon dioxide: NUS study

Others services:

2023 AOGS session co-convenor for League of geophysical research eXcellences for tropical asia (LeXtra)

2023 USGS Powell workshop on integrated understanding of terrestrial evapotranspiration topic lead.

2022 Ameriflux Evapotranspiration workshop topic lead.

2021 US Department of Energy Artificial Intelligence for Earth System Predictability invited participant.

2019 AGU session 2019-B059 Vegetation and leaf traits session co-convener.

Code & Data

Global C4 distribution

Using a photosynthetic optimality theory, in combination with observations from the TRY database and the global nutrient network, and remote sensing, we produced a new observation-constrained estmiate of global C4 distribution (including C4 natural grasses and C4 crops) from 2001 to 2019. We found globally C4 accounted for ~16% of the vegetated surface area and ~18% of global photosynthetic carbon assimilation. The global C4 distribution decreased from 16.6% of the global land surface to 15.9% during the study period, as a result of a decrease in C4 natural grasses (due to elevated CO2) and an increase in C4 crops (due to maize expansion).

Link to data: https://zenodo.org/records/10516423

Reference:

Luo, X., Zhou, H., Satriawan, T.W., Tian, J., Zhao, R., Keenan, T.F., Griffith, D. M., Sitch, S. Smith, N.G. & Still, C.J. Mapping the global distribution of C4 vegetation using observations and optimality theory. Nature Communications. https://doi.org/10.1038/s41467-024-45606-3.

Global distribution of leaf photosynthetic capacity

Using leaf trait databases, remote sensing leaf chlorophyll content, gridded climate and soil data, in combination with a Random Forest approach, we derived one of the first data-driven maps of the maximum leaf carboxylate rate (Vcmax25) and the fraction of leaf nitrogen allocated to Rubisco (fLNR) - both are critical to the estimation of plant photosynthesis. This dataset can be used to constrain global photosynthesis and the carbon cycle estimates from Earth system models.

Link to data: https://zenodo.org/record/5090497

Reference:

Luo, X., Keenan, T.F., Chen, J.M., Croft, H., Prentice, I.C., Smith, N.G., Walker, A.P., Wang, H., Wang, R., Xu, C. & Zhang, Y. (2021) Global variation in the fraction of leaf nitrogen allocated to photosynthesis. Nature Communications. doi: 10.1038/s41467-021-25163-9.

Biosphere-atmosphere Exchange Process Simulator (BEPS)

BEPS is a two-leaf enzyme kinetic Terrestrial Biosphere Model that is used to simulate hourly and daily gross primary productivity, evapotranspiration and net primary productivity. It has been intensively validated on a wide range of biomes and participated in North American Carbon Program. The global estimates of GPP and ET by BEPS are available from 1980 to 2016.

BEPS version 4.11 Link to code.

Reference:

Chen, J. M., Liu, J., Cihlar, J., & Goulden, M .(1999). Daily canopy photosynthesis model through temporal and spatial scaling for remote sensing applications. Ecological Modelling, 124(2–3), 99–119.

Luo, X., Chen, J.M., Liu, J., Black, T.A., Croft, H., Staebler, R., He, L., Arain, M.A., Chen, B., Mo, G., Gonsamo, A. & McCaughey, H. (2018). Comparison of big-leaf, two-big-leaf and two-leaf upscaling schemes for evapotranspiration estimation using coupled carbon-water modelling. Journal of Geophysical Research - Biogeoscience, 10.1002/2017JG003978.

He, L., Chen, J. M., Gonsamo, A., Luo, X., Wang, R., Liu, Y., & Liu, R. (2018). Changes in the Shadow: The Shifting Role of Shaded Leaves in Global Carbon and Water Cycles Under Climate Change. Geophysical Research Letters, 82(3), 387.

Satellite-derived Leaf Chlorophyll Content

Global leaf chlorophyll content (Chl) were derived from MERIS surface reflectance, using a two-step process-based algorithm. The first step was to retrieve leaf reflectance spectra from satellite-derived canopy reflectance spectra through the inversion of canopy radiative transfer models (4-Scale and SAIL). The second step was to use the retrieved leaf reflectance spectra from step 1 to estimate Chl by inverting a leaf radiative transfer model (PROSPECT).

Satellite-derived Chl v1.0 for 124 eddy covariance sites. Link to data.

Reference:

Croft, H., Chen, J.M., Mo, G., Luo, S., Luo, X., Arabian, J., Zhang, Y., Simic, A., Noland, T.L., He, Y., Homolová, L., Malenovský, Z., Yi, Q., Beringer, J., Amiri, R., Hutley, L., Arellano, P., Stahl, C. & Bonal, D. (2020). Global distribution of leaf chlorophyll content. Remote Sensing of Environment, 10.1016/j.rse.2019.111479.

Luo, X., Croft, H., Chen, J.M., He, L. & Keenan, T.F. (2019) Improved estimates of global photosynthesis using information on leaf chlorophyll content. Global Change Biology, 10.1111/gcb.14624.

Lab Members

PhD students/candidates

Tin Widyani Satriawan (she/her), 2022.08 - now

Email: tin.satriawan@u.nus.edu; Google scholar: #; Twitter: @SatriawanTin

Research area: eddy covariance, carbon fluxes

MSc. University of British Columbia, Canada; BSc. Institut Teknologi Bandung (ITB), Indonesia

Yiguang Zou (he/his), 2023.08 - now

Email: zou.yiguang@u.nus.edu; Google scholar: https://scholar.google.com.hk/citations?user=JlUtuEsAAAAJ&hl=en; Twitter: #

Research area: Terrestrial carbon and water cycles

MSc. Southern University of Science and Technology, China; BSc. China University of Geosciences (Wuhan), China

Wee Han Chua (he/his), 2023.08 - now. co-advised with Prof. Gopal Penny

Email: weehanchua@u.nus.edu; Google scholar: #; Twitter: #

Research area: Agriculture landscape, social-ecological systems

MSc. National University of Singapore, Singapore; BSc. National University of Singapore, Singapore

Ng Tan Ting, Diane (she/her), 2024.01 - now.

Email: e1322736@u.nus.edu; Google scholar: #; Twitter: #

Research area: leaf traits, chlorophyll

M.Phil. The Chinese University of Hong Kong, China; BSc. The Chinese University of Hong Kong, China.

Postdoctoral Research Fellows

Jiaqi Tian (he/his), 2022.03 - now

Email: jq.tian@nus.edu.sg; Google scholar: https://scholar.google.com/citations?user=RNCJZEYAAAAJ&hl=en; Twitter: @jackie_x7

Research area: vegetation dynamics, remote sensing

Ph.D. The Hong Kong Polytechnic University, China; MSc. The Hong Kong Polytechnic University, China; BSc. Northeast Agriculture University, China

Ruiying Zhao (she/her), 2023.02 - now

Email: ruiying@nus.edu.sg; Google scholar: https://scholar.google.com/citations?hl=zh-CN&tzom=-480&user=3aOO-j4AAAAJ; Twitter: @ruiying_z

Research area: Terrestrical carbon cycle, process-based model, machine learning

Ph.D. Zhejiang University, China; BSc. Wuhan University.

Liyao Yu (he/his), 2023.02 - now

Email: liyaoyu@nus.edu.sg; Google scholar: https://scholar.google.com/citations?user=BruFn2eY5DYC&hl=en; Twitter: @yuliyao13

Research area: leaf ecophysiology, photosynthesis, light acclimation

Ph.D. The University of Tokyo, Japan; MSc. Shanghai Jiaotong University, China; BSc. Shanghai Jiaotong University, China

Luri Nurlaila Syahid (she/her), 2023.06 - now

Email: luri@nus.edu.sg; Google scholar: # Twitter: #

Research area: remote sensing, ecosystem restoration

Ph.D. Bandung Institute of Technology, Indonesia; MSc. Bandung Institute of Technology, Indonesia; BSc. University of Diponegoro, Indonesia

Undergraduate Research Assistants

Rachel Teo (she/her), 2023.01 to now; research area: photosynthesis of major tree species in Singapore

Department of Geography, National University of Singapore, Singapore

Visiting Students

Xinrong Zhu (she/her; 2021.11-2022.05; Peking University; research area: soil and vegetation interaction); Zhen Zhang (he/his; 2021.08 - 2022.12; Xiamen University; research area: remote sensing, mangroves); Juan Cao (she/her; 2021.6 - 2022.06; Beijing Normal University; research area: machine learning, food security)

Alumni

Willis Lau (he/his), undergraduate research assistant. 2021.6 to 2023.10. NUS Biological Sciences. Move on to MSc at the University College London.

Join Us

Current opportunities:

1. PhD students: we are constantly looking for motivated graduate students to join us! If you are interested in vegetation dynamics, climate change, remote sensing, ecological models and the terrestrial carbon cycle, feel free to drop me an email w/ your CV. PhD students at NUS will be fully funded through Reseaerch Scholarship and other merit-based scholarhips (here). Note that the graduate student applications will be reviewed by a committee within the geography department. The general requirement for PhD admission is available here.

2. One postdoc fellow: we have one position related to remote sensing, statisical modelling and plant physiology will open soon. It will be funded by a project support by National Environment Agency to study trees in Singapore. Please apply here https://careers.nus.edu.sg/job-invite/23558/.

3. Visiting students/scholars: we are happy to host students/scholars from other institutions. Please email me with a brief introduction about your research, your CV and a short statement on how you think we can help you make progress in science. Please note that our department has implemented a quota for visiting students each year, therefore we would not be able to make committeement before we assess all visiting student applicants (usually in March).

Past opportunities:

Closed on Nov 20th, 2023. One postdoc reserach fellow on terrestrial biosphere modelling for a Tier II project.

Closed on March 20th, 2023. One postdoc research fellow: we are looking for one postdoc broadly in the field of remote sensing of vegetation dynamics to join us. Experience with plant physiology, eddy covariance will be a plus. The position will be initially funded for 1 yr but can be extended up to 3 yrs.

Closed on November 22nd, 2022. We finsihed our search for the two postdocs working on terrestrial biosphere modelling and leaf traits study for tropical Asia forests.

Closed on March 31st, 2022. We look for a postdoc to lead a SgEC-funded project to examine the gross CO2 emissions and uptake from land use change in Southeast Asia.

Closed on April 20th, 2021. We have one postdoc openning (details available at careers.nus.edu.sg/s/zpTg7n). The postdoc will lead a MOE-funded project to examine the structural and physiological changes of vegetation in tropical Asia.

Closed on May 1st, 2021. We have hosted 3 visiting PhD students supported by CSC for 2021-2022.

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ASSISTANT PROFESSOR XIANGZHONG (REMI) LUO
ASSISTANT PROFESSOR
DEPARTMENT of GEOGRAPHY

Brief Introduction

Teaching Areas

Research Interests

Publications

Other Info

Code & Data

Lab Members

Join Us

Sidebar

FASS: Quick Links

FASS Staff Profile

ASSISTANT PROFESSOR XIANGZHONG (REMI) LUO ASSISTANT PROFESSOR DEPARTMENT of GEOGRAPHY

Brief Introduction

Teaching Areas

Research Interests

Publications

Other Info

Code & Data

Lab Members

Join Us

ASSISTANT PROFESSOR XIANGZHONG (REMI) LUO
ASSISTANT PROFESSOR
DEPARTMENT of GEOGRAPHY