SPACE
Mapping plant functional diversity from space: HKU ecologists revolutionize ecosystem monitoring with novel field-satellite integration
THE UNIVERSITY OF HONG KONG
An international team of researchers, led by Professor Jin WU from the School of Biological Sciences at The University of Hong Kong (HKU), has made a promising advancement in mapping plant functional traits from space using time-series satellite data. The study, published in Remote Sensing of Environment, showcases the innovative combination of the Sentinel-2 satellite mission and its dynamic time-series capabilities. This innovative approach not only unlocks a deeper understanding of essential foliar traits, providing crucial insights into the functional diversity and ecosystem functioning of terrestrial ecosystems, but it also equips us with powerful tools to address pressing environmental challenges effectively.
Leveraging the Satellites for In-depth Observations
Plant traits are vital in regulating key ecosystem processes such as carbon sequestration, air temperature regulation, and large-scale hydrological regulation. They also determine how ecosystems respond to various environmental stressors, ultimately determining their health, resilience, and vulnerability to climate change. However, large-scale mapping of these traits has been challenging due to limitations in existing methodologies, such as the difficulty in capturing traits across vast areas and issues such as data availability, trait complexity, and measurement techniques.
To overcome these challenges, Professor Wu’s team harnessed the power of satellite technology and introduced a pioneering approach that combines vegetation spectroscopy and phenology. Their approach utilised high-resolution imagery from the Sentinel-2 satellite, which captured multispectral data on a weekly interval with a 10-metre resolution. By analysing these satellite images, the team observed and recorded the reflections of light from plant leaves, providing valuable insights into the physical and biochemical properties of the vegetation. These observations were then compared to the timing of plant life cycle events, known as phenology. By integrating the data from satellite imagery and phenological observations, the team has been able to obtain comprehensive information about plant functional traits across high dimensions. This integration holds great potential for extending to other dimensions of plant characteristics, such as plant health, functioning, and resilience.
This method underwent thorough and rigorous testing to evaluate its efficacy, applicability across different scales, and potential for high-throughput monitoring. The test utilised benchmark data of 12 foliar traits collected from 14 geographically distant sites within the National Ecological Observatory Network (NEON) in the eastern United States.
Shuwen LIU, the first author and a PhD candidate from Professor Wu’s lab, stated: "Our approach effectively captures the diversity of plant traits at fine spatial scales while maintaining accuracy over large areas." Liu further explained that their method overcomes the limitations of other methods that rely solely on plant functional types or single image acquisitions.
The proposed approach outperformed traditional methods that rely on environmental variables or single Sentinel-2 images as predictors without requiring environmental variables to enhance predictive capabilities. This finding underscores the significance of phenological information in trait prediction and suggests that the ‘leaf economics spectrum’ theory may be the underlying mechanism driving their technical success. Given the model's proven effectiveness in 14 diverse ecosystem sites across the United States, it shows great promise for expansion to national and global scales, thereby enabling the monitoring of plant functional traits from ecosystem to regional and national levels.
Reflecting on the future potential of this research, Professor Wu said: "Future studies will focus on broader validation to fully exploit this technology’s potential in frontier basic science, such as understanding terrestrial ecosystems’ sensitivity response to climate change and identifying their respective tipping points. Additionally, there is great potential for applied science, particularly in exploring nature-based climate solutions."
About the research team
The Global Ecology and Remote Sensing (GEARS) lab at HKU aims to uncover the fundamental mechanisms that regulate vegetation-climate interactions across various scales, ranging from leaves to the global level. It employs a diverse range of tools, including cutting-edge geospatial techniques, field observations, eco-evolutionary and ecophysiological theories, earth system models, and high-performance computing. Its research goals are twofold: firstly, to advance fundamental science by exploring the mechanisms that link climate, species (functional) composition, and ecosystem processes, and secondly, to bridge the gap between scientific and technological advancements in order to address pressing environmental issues related to climate change, such as forest health monitoring, food security, climate change impact assessments, and nature-based climate change mitigation. About GEARS: https://wu-jin.weebly.com/
About Professor Jin Wu
Jin Wu is an Assistant Professor at HKU School of Biological Sciences and a recipient of the NSFC-Excellent Young Scholar (Hong Kong & Macau) award in 2019. Prior to this, he held a Goldhaber Distinguished Fellow position at Brookhaven National Laboratory and earned his PhD from the University of Arizona. With a wide range of interests in biodiversity, conservation, global change, and sustainability sciences, he utilises an integrated approach (combining remote sensing, AI, and domain knowledge) to study these topics and aims to enhance how people experience, understand, and appreciate our living habitats and inspire actions to sustain our natural ecosystems. He has published over 100 peer-reviewed papers, including in prestigious journals such as Science, Nature, Global Change Biology, and Remote Sensing of Environment. Currently, he serves as an Associate Editor for Remote Sensing in Ecology and Conservation.
Link to the paper and key figure:
The journal paper, entitled ‘Spectra-phenology integration for high-resolution, accurate, and scalable mapping of foliar functional traits using time-series Sentinel-2 data’, can be found at the following link: https://doi.org/10.1016/j.rse.2024.114082
For media enquiries, please contact Ms Casey To, External Relations Officer (tel: 3917 4948; email: caseyto@hku.hk / Ms Cindy Chan, Assistant Director of Communications of HKU Faculty of Science (tel: 3917 5286; email: cindycst@hku.hk).
Land cover (a) and functional trait maps produced from Satellite images. The team used four traits - LMA (b), nitrogen (c), potassium (d) and chlorophyll a+b (e) - as examples for demonstration.
CREDIT
Figures adapted from Remote Sensing of Environment, 2024, doi.org/10.1016/j.rse.2024.114082.
JOURNAL
Remote Sensing of Environment
METHOD OF RESEARCH
Experimental study
SUBJECT OF RESEARCH
Not applicable
ARTICLE TITLE
Spectra-phenology integration for high-resolution, accurate, and scalable mapping of foliar functional traits using time-series Sentinel-2 data
Technical Trials for Easing the (Cosmological) Tension
A new study sorts through models attempting to solve one of the major challenges of contemporary cosmic science, the measurement of its expansion
Thanks to the dizzying growth of cosmic observations and measurement tools and some new advancements (primarily the “discovery” of what we call dark matter and dark energy) all against the backdrop of General Relativity, the early 2000s were a time when nothing seemed capable of challenging the advancement of our knowledge about the cosmos, its origins, and its future evolution.
Even though we were aware there was still much to uncover, the apparent agreement between our observations, calculations, and theoretical framework was indicating that our knowledge of the universe was set to grow significantly and without interruption.
However, thanks to increasingly sophisticated observations and calculations, the emergence of an apparently small “glitch” in our understanding of the Universe proved capable of jamming seemingly perfectly oiled gears. At first, it was thought it could be resolved it with even more precise calculations and measurements, but this was not the case. The "cosmological tension" (or Hubble Tension), is a discrepancy between the two ways in which we calculate the so-called Hubble parameter, H0, which describes the universe's expansion.
The Hubble parameter can be calculated following two paths:
- The astrophysical observations of celestial bodies defined as local, i.e., not very far from us: it is possible to calculate the speed at which bodies at different distances are moving away. The expansion and H0 in this case is calculated by comparing speeds and distances.
- The calculations based on data from the cosmic microwave background CMB, a faint and extremely distant radiation dating back to the very early Universe. The information we gather at that distance allows us to calculate the Universe's expansion rate and the Hubble parameter.
These two sources provided not exactly equal, but very close and consistent values of H0, and at the time it seemed that the two methods were showing good agreement. Bingo.
It was around 2013 when we realized that the "numbers didn't add up". “The discrepancy that emerged might seem small, but given that the error bars on both sides are becoming much smaller, this separation between the two measurements is becoming large”, Khalife explains. The initial two values of H0, in fact, were not too precise, and as the “error bars” were large enough to overlap, there was hope that future finer measurements would finally coincide. “Then the Planck experiment came along, giving very small error bars compared to the previous experiments” but still maintaining the discrepancy, dashing hopes for an easy resolution.
Planck was a satellite launched in space in 2007 to gather an image of the CMB as detailed as never before. Its results released a few years later confirmed the discrepancy was real and what was a moderate concern turned into a significant crisis. In short: the most recent and near sections of the universe we observe tell a different story, or rather seem to obey a different physics, than the oldest and most distant ones, a very unlikely possibility.
If it's not a problem of measurements then it could be a flaw in the theory, many thought. The current accepted theoretical model is called ΛCDM. ΛCDM is largely based on General Relativity - the most extraordinary, elegant, and repeatedly observationally confirmed theory about the universe formulated by Albert Einstein more than a century ago - and takes into account dark matter (interpreted as cold and slow-moving) and dark energy as a cosmological constant.
Over the last years, various alternative models or extensions to the ΛCDM model have been proposed, but so far, none have proven convincing (or sometimes even trivially testable) in significantly reducing the "tension". “It is important to test these various models, see what works and what can be excluded, so that we can narrow the path or find new directions to turn to”, explains Khalife. In their new paper, he and his colleagues on the basis of previous research lined up 11 of these models, bringing some order to the theoretical jungle that has been created. The models were tested with analytical and statistical methods on different sets of data, both from the near and distant universe, including the most recent results from the SH0ES (Supernova H0 for the Equation of State) collaboration and SPT-3G (the new upgraded camera of the South Pole Telescope, collecting the CMB).
Three of the selected models that were shown in previous works to be viable solutions were ultimately excluded by the new data this research considers. On the other hand, other three models still seem capable of reducing the tension, but this doesn’t solve the problem. “We found that those could reduce the tension in a statistically significant way, but only because they have very large error bars and the predictions they make are too uncertain for the standards of cosmology research”, says Khalife. “There is a difference between solving and reducing: these models are reducing the tension from a statistical point of view, but they're not solving it”, meaning that none of them is predicting a large value of H0 from CMB data alone. More in general none of the models tested proved superior to the others studied in this work in reducing the tension.
“From our test we now know which are the models that we should not look at to solve the tension,” concludes Khalife, “and we also know the models that we might be looking at in the future”. This work could be a base for the models that will be developed in the future, and by constraining them with increasingly precise data, we could move closer to developing a new model for our Universe.
JOURNAL
Journal of Cosmology and Astroparticle Physics
METHOD OF RESEARCH
Data/statistical analysis
SUBJECT OF RESEARCH
Not applicable
ARTICLE TITLE
Review of Hubble tension solutions with new SH0ES and SPT-3G data
ARTICLE PUBLICATION DATE
19-Apr-2024
Scientists discover new way to extract cosmological information from galaxy surveys
Scientists at the National Astronomical Observatories of the Chinese Academy of Sciences (NAOC) and their international collaborators have recently developed a new method for efficiently extracting information from galaxy surveys.
Their research results were published online in the latest issue of Communications Physics.
Massive galaxy redshift surveys are powerful tools for probing the Universe in this era of precision cosmology. By observing a great number of spectra from distant galaxies, astronomers are able to create density fields of galaxies at different epochs of the Universe. These density fields carry crucial information about the clustering of galaxies, which is quantified by two-point and N-point (N>2) correlation functions.
“The information content in the N-point functions is highly complementary to that in the two-point functions,” said ZHAO Gongbo, lead author of the study and a researcher at NAOC. “The N-point functions play an important role in studies of the nature of dark energy, dark matter and gravity.”
However, it is difficult to make use of the N-point functions in practice due to various complexities, including the measurement and modeling of these quantities.
After working on this challenging task for a few years, ZHAO and his collaborators have developed a new method for extracting information in the N-point functions from the two-point functions.
This new method, which is based on a technology called density reconstruction, makes it possible to extract the primary information in the three-point and four-point functions by a joint analysis of the two-point functions measured from the pre- and post-reconstructed density fields, respectively.
“This opens a new window for using the high-order information in galaxy surveys in an efficient way,” said ZHAO. “and that’s important for cosmological implications for forthcoming galaxy surveys including Dark Energy Spectroscopic Instrument (DESI), Prime Focus Spectrograph (PFS) and China Space Station Telescope (CSST).”
This work was funded by the Natural Science Foundation of China (NSFC), China’s Ministry of Science and Technology (MOST), and the Chinese Academy of Sciences (CAS).
JOURNAL
Communications Physics
ARTICLE TITLE
Extracting high-order cosmological information in galaxy surveys with power spectra
ARTICLE PUBLICATION DATE
18-Apr-2024
Cosmic rays streamed through Earth’s atmosphere 41,000 years ago
EUROPEAN GEOSCIENCES UNION
Earth’s magnetic field cocoons our planet from the onslaught of cosmic radiation streaming through space while also shielding us from charged particles hurled outward by the sun. But the geomagnetic field is not stationary. Not only does magnetic north wobble, straying from true north (a geographically defined location), but occasionally, it flips. During these reversals, north becomes south, south becomes north, and in the process, the intensity of the magnetic field wanes.
But there’s also something called magnetic field excursions, brief periods in which the intensity of the magnetic field wanes and the dipole (or two magnetic poles) that we’re familiar with can disappear, replaced with multiple magnetic poles. The Laschamps excursion that occurred around 41,000 years ago is among the best studied. It features a low magnetic field intensity that implies less protection for Earth’s surface from harmful space rays. Periods of low magnetic field intensity could correlate to major upheavals in the biosphere.
To see when cosmic rays were heavily bombarding Earth’s surface, scientists can measure cosmogenic radionuclides in cores from both ice and marine sediment. These special isotopes are produced by the interaction between cosmic rays and Earth’s atmosphere; they are born of cosmic rays, hence they are cosmogenic.
Times of lower paleomagnetic field intensity—less shielding—should correlate to higher rates of cosmogenic radionuclide production in the atmosphere. Sanja Panovska, a researcher at GFZ Potsdam, Germany will present her findings about the relationship between paleomagnetic field intensity and cosmogenic nuclides during the Laschamps excursion, with a focus on space climate, next week during the European Geosciences Union (EGU) General Assembly 2024.
Variations in cosmogenic radionuclides like beryllium-10 provide an independent proxy of how Earth’s paleomagnetic intensity changed. Indeed, Panovska found that the average production rate of beryllium-10 during the Laschamps excursion was two times higher than present-day production, implying very low magnetic field intensity and lots of cosmic rays reaching Earth’s atmosphere.
To wring more information from both cosmogenic radionuclide and paleomagnetic data, Panovska reconstructed the geomagnetic field using both datasets. Her reconstructions show that during the Laschamps excursion, the magnetosphere shrank when the field dramatically decreased, “thus reducing the shielding of our planet,” she said. “Understanding these extreme events is important for their occurrence in the future, space climate predictions, and assessing the effects on the environment and on the Earth system.”
To learn more about this work, Panovska will give an oral presentation during session EMRP3.3 at EGU 2024 on Friday, 19 April, 14:05-14:15 CEST, Room -2.20
More Information
When reporting on this story, please mention the EGU General Assembly 2024, which is taking place from 14-19 April 2024. This talk will be presented in session EMRP3.3 on Friday, 19 April, 14:05-14:15 CEST in Room -2.20. If reporting online, please include a link to the abstract: https://meetingorganizer.copernicus.org/EGU24/EGU24-10977.html
DOI
Weather prediction models can also forecast satellite displacements
New research finds that modern weather models can accurately predict satellite movements due to the energy emitted and reflected by the Earth.
Researchers at the Institute for Atmospheric and Earth System Research (INAR) at the University of Helsinki have found that modern weather models can accurately predict the energy that Earth emits and reflects into space, which directly affects the movements of low Earth-orbiting (LEO) satellites. By leveraging these models, the researchers gained insights into how LEO satellites respond to weather events below, such as tropical cyclones with tall and reflective clouds. The results were published in the Journal of Geophysical Research in April.
In the study, the researchers utilized numerical weather models. They are sophisticated computer simulators that predict future atmospheric conditions based on current observations and laws of physics.
“Numerical weather models not only simulate weather patterns but also calculate various parameters, including the Earth's energy emissions and reflections under various weather conditions. By analysing these simulations, we sought to understand how changes in weather, such as cloud cover and storms, influence the movement of satellites, affecting their ability to fulfil their intended duties”, says Sanam Motlaghzadeh, lead author of the study and doctoral researcher at INAR, funded by the Nessling Foundation.
Improved satellite operations
The significance of the findings lies in their potential to enhance satellite tracking and control, improving the efficiency and reliability of satellite operations.
“Understanding how weather affects satellites also enhances the accuracy of satellite-based measurements used in climate studies. These findings address a critical challenge in satellite data reliability, namely, determining the precise orbits of satellites, on which the weather events have effect”, Motlaghzadeh explains.
Satellites play a crucial role in monitoring vegetation, tracking water resources, and observing glacier evolution through various measurement techniques. These measurements, including image capture and height and gravity field measurements, are essential for studying climate change and its impacts.
A better understanding of satellite movements can also aid in climate monitoring and disaster management. Utilizing advanced weather models can further refine satellite-based measurements, facilitating more effective study and mitigation of environmental issues.
“Understanding how satellites interact with Earth's atmosphere offers valuable insights into our planet and how it changes over time. The findings contribute to more accurate satellite-based monitoring of terrestrial water resources, and hence to food security, Motlaghzadeh says.
JOURNAL
Journal of Geophysical Research Atmospheres
METHOD OF RESEARCH
Observational study
SUBJECT OF RESEARCH
Not applicable
ARTICLE TITLE
Weather-induced satellite orbit perturbations.
ARTICLE PUBLICATION DATE
16-Apr-2024
Unraveling water mysteries beyond Earth
The first clue for finding life on other planets is finding liquid water. The moons of Saturn and Jupiter like Enceladus, Ganymede, Europa, and Callisto are suspected of holding oceans of liquid water beneath icy crusts. Similarly, some exoplanets beyond our solar system likely host liquid water, crucial for habitability. But detecting water, when we can’t physically access these celestial bodies, poses challenges. Ice-penetrating radar, a geophysical tool, has proven capable of detecting liquid water on Earth and beneath Mars’ South polar cap.
Now, this instrument is aboard the JUICE spacecraft and it is on its way to Jupiter’s icy moon Ganymede and will also be aboard the Europa Clipper spacecraft, which will be launched to Europa later this year. What can we expect to learn from these missions and how can we use ice-penetrating radar for future planetary exploration? Dr Elena Pettinelli of Roma Tre University, with extensive experience in planetary exploration using ice-penetrating radar, will delve into the utility of this technology in her presentation next week at the European Geosciences Union General Assembly EGU24.
Dr. Pettinelli, who was part of the team that discovered a subglacial stable body of liquid water on Mars, will trace the historical applications of ice-penetrating radar in planetary exploration before she dives into prospective uses of ice-penetrating radar in locating and characterizing liquid water.
Scientists hope to use ice-penetrating radar to determine the depth and chemistry of water beneath the icy surface of Jovian moons. Dr. Pettinelli explains that the radar’s penetration depth correlates with ice salinity; saltier ice impedes radar transmission to a greater extent. “Depending on the behavior of the radio waves, we might be able to better tell the distribution of salt,” she says, which her team then ground-truths through laboratory experiments.
“We can use all this information to improve our understanding of the distribution of liquid water in the solar system,” Dr. Pettinelli says. “There’s much more water than we thought 20 or 30 years ago, and it’s really interesting to use this technique to try to understand where the water could be.”
No comments:
Post a Comment