Sci-tech helps protect south China biological treasure trove
Luo Shixiao, curator of the South China Botanical Garden (SCBG) herbarium, introduces the intelligent specimen management system in Guangzhou, south China's Guangdong Province, April 10, 2025. (Xinhua/Yu Fei)
GUANGZHOU (May 6): In the early 1880s, an American discovered a beautiful and mysterious flower on a cliff close to the Lianjiang River in northern Guangdong Province, south China. Later, a British botanist published research done on this flower.
However, for over a century after its discovery, no one saw this flower again. Named Primulina tabacum, it was once believed to be extinct.
It was not until the 1990s that the flower was rediscovered in Lianzhou, Guangdong. At that time, only three surviving plants were documented, and it was classified as critically endangered. This species typically inhabits specific microhabitats in the karst caves of southern China, where its survival faces severe threats.
In 2002, researchers from the South China Botanical Garden (SCBG) of the Chinese Academy of Sciences launched an ex-situ conservation program for Primulina tabacum.
They discovered that the plant grows on limestone cave cliffs with high carbon dioxide concentrations and does not require bees for pollination. Further studies revealed that when its petals fall, they trigger collisions between stamens and pistils, enabling self-pollination.
Notably, scientists have successfully applied cloning technology to cultivate this plant — mastering rapid propagation techniques and reintroducing about 3,000 individuals into the wild.
Currently, the SCBG has conserved 1,050 rare and endangered plant species, including 558 state-protected wild plants. Its dedicated rare and endangered plant breeding center spans 20 hectares and houses over 230 such species, making it one of China's largest germplasm banks for rare flora.
The botanical garden aims to ensure effective protection of 95 percent of south China's rare and endangered plants, and to reintroduce 20 species into their natural habitats.
'We protect each plant not because of its known value, but because we don't know its potential importance yet. With so few wild individuals left, conservation is imperative. Once a species vanishes, it's gone forever,' said Ning Zulin, deputy director of the garden's horticulture center.
AI ASSISTANCE
How many species exist on Earth? There remains no definitive answer. Historically, documenting and studying biodiversity relied on experts. Now, big data and AI technologies are revolutionizing public engagement, offering new ways to record, understand and protect biodiversity.
Luo Shixiao, curator of the SCBG herbarium, said through an independently developed intelligent specimen management system, named Cathaya, the herbarium in 2024 completed the reception of over 50,000 plant specimens and uploaded 300,000 pieces of spatiotemporal distribution information concerning the collected specimens. More than 250,000 pieces of specimen data were shared via the system.
This system has enabled efficient management of the entire process from field investigation to digital sharing of specimens — setting a new paradigm for biodiversity research and intelligent management.
The herbarium also developed the 'BioGrid' app, a biodiversity observation and identification tool, by using large-scale scientific data and artificial intelligence. This app addresses challenges such as precise plant localization and species identification, enhancing data collection and species recognition capabilities for both professionals and the public, according to Xu Zhoufeng, an engineer at the herbarium.
The app provides data collection, project organization, data perception and visualization services for professionals, while also enabling the public to conveniently participate in biodiversity science projects, Xu said.
Liu Shizhong, a senior engineer from the South China Botanical Garden (SCBG) of the Chinese Academy of Sciences, conducts observation at Dinghushan National Nature Reserve in Zhaoqing, south China's Guangdong Province, April 9, 2025. (Xinhua/Yu Fei)
GREEN PEARL
As a key participant in global ecological conservation, China continues to explore innovative approaches to biodiversity protection and ecosystem management.
Dinghushan National Nature Reserve, a model of ecological conservation in China, is not only the country's first nature reserve but also an important member of UNESCO's World Network of Biosphere Reserves. Its successful experience offers valuable lessons for global ecological conservation.
Located in Zhaoqing, Guangdong Province, the 1,133-hectare reserve, established in 1956 and managed by the SCBG, is hailed as the 'Green Pearl on the Tropic of Cancer Desert Belt,' due to its exceptional ecological value and striking contrast with the typically arid regions along the Tropic of Cancer.
In 1979, it became one of China's first three biosphere reserves under UNESCO's Man and the Biosphere (MAB) program.
Xia Hanping, director of the reserve, noted that its primary focus is protecting South Asian subtropical evergreen broad-leaved forests and their wildlife. Forest coverage in the reserve has remained around 98 percent, with 68 state-protected plant species and 73 protected animal species found there.
Populations of key protected species have either remained stable or increased significantly — while the area of subtropical evergreen broad-leaved forests has grown by over 70 percent since the reserve's establishment, Xia said.
Liu Juxiu, head of the Dinghushan research station, revealed that the reserve serves as a natural laboratory for scientific research.
Based on nearly two decades of investigation, researchers have found that previous estimates, relying primarily on forest above-ground biomass and surface water in carbonate rock regions, have led to a significant underestimation of China's terrestrial carbon sequestration capacity, with this miscalculation amounting to as much as 50 percent. The study further reveals that terrestrial carbon sinks across China are highly sensitive to regional environmental variability.
Scientists have also assessed the current state and temporal dynamics of carbon sequestration in China's forest ecosystems, providing estimates of forest carbon stocks and revealing considerable remaining sequestration potential. In examining ecosystem responses to global change, they have identified the mechanistic pathways through which nitrogen deposition modulates soil carbon emissions in tropical forests, and have further elucidated the biogeochemical cycles of carbon, nitrogen and phosphorus under climate warming.
Chu Guowei, deputy director of the Dinghushan research station, said that the station collaborates with research institutions in over 20 countries, including the United States, Australia, Canada, Germany, France, Sweden, Denmark, Japan and Kenya — thereby advancing multiple ecological studies.
The reserve's success lies not only in conservation but also in harmonizing humans and nature. In 2024, the Ministry of Natural Resources adopted a proposal by Ren Hai, director of the SCBG, to retain high-quality farmland within the reserve. 'Preserving farmland supports local livelihoods while providing food and habitat for wildlife, achieving a win-win balance between conservation and development,' Ren said.
Wang Ding, secretary-general of China's MAB National Committee, noted that nature reserves should act as bridges for socio-economic development, not barriers. 'The philosophy of harmonizing humans and nature aligns well with China's realities.' botanist China flora flower
Hashtags
Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles
The Star
3 hours ago
- The Star
China is working on an ultra-fast torpedo powered by AI for submarine warfare
In the recent Chinese blockbuster Operation Leviathan , an American nuclear submarine uses hi-tech acoustic holograms to bamboozle Chinese torpedoes and their human operators. Months after the film hit cinema screens, military researchers in China revealed they were working on an artificial intelligence system designed to cut through exactly this type of underwater deception. In a peer-reviewed paper published in Chinese-language journal Command Control & Simulation in April, the team from the PLA Navy Armament Department and China State Shipbuilding Corporation said their system had unprecedented accuracy for torpedoes travelling at high speeds. Tested against data from classified high-speed torpedo ranges, the technology achieved an average 92.2 per cent success rate in distinguishing real submarines from decoys even during tense exchanges, according to the paper. That is a leap from the legacy systems that often miss the target. Future submarine warfare hinges on deceiving torpedoes using illusions. Hi-tech decoys – as dramatised in Operation Leviathan – are used to replicate a vessel's acoustic signature, generate a false bubble trail to make it look like it is making an emergency turn, or deploy in coordinated swarms to project ghost targets across sonar screens. These tactics are particularly effective against what is known as ultra-fast supercavitating torpedoes – weapons that generate cavitation, or vapour bubbles, around their hulls to reduce drag. The resulting roar drowns out genuine target echoes while distorting acoustic fingerprints, according to the Chinese researchers. 'Current target recognition methods for China's underwater high-speed vehicles prove inadequate in environments saturated with advanced countermeasures, necessitating urgent development of novel approaches for feature extraction and target identification,' said the team led by senior engineers Wu Yajun and Liu Liwen. 'Only those underwater high-speed systems equipped with long-range detection capabilities and high target recognition rates can deliver sufficient operational effectiveness,' they added. The solution they proposed came from an unorthodox combination of physics and machine learning. Facing scarce real-world combat data, the team began by simulating decoy profiles using hydrodynamic models of bubble collapse patterns and turbulence. To do that they used raw data collected from the PLA Navy's high-speed torpedo test range. These simulations were then added to a 'generative adversarial network' – a duelling pair of AI systems. One of them, the generator, refined decoy signatures by studying submarine physics and acoustic principles. Its opponent, the discriminator, trained to detect flaws in these forgeries using seven layers of sonic pattern analysis. After many rounds of training, the system had created a huge collection of artificial decoy profiles. The AI uses a specialised neural network architecture inspired by image recognition, according to the paper. Sonar signals go through a process where they are normalised for amplitude, filtered through correlation receivers to suppress noise, and finally rendered as spectral 'thumbnails' using a mathematical tool known as a Fourier transform. These sonic snapshots then pass through convolutional layers in the neural network that are tuned to detect anomalies in frequency modulation. Pooling operations then average out distortions like bubble interference. The team said that when confronted with the most sophisticated type of decoys, detection rates went from 61.3 per cent to more than 80 per cent. It comes amid a global race to develop 'smart' torpedoes. Russia's VA-111 Shkval torpedo and its US counterparts under development all rely on supercavitation at present, and they struggle with target discrimination at extreme speeds. 'With continuous advancements in modern underwater acoustics, electronic technologies and artificial intelligence, today's underwater battlespace often contains multiple simultaneous threats within a single operational area – including decoys, electro-acoustic countermeasure systems, electronic jammers and diverse weapon systems,' the paper said. In such intense underwater environments where multiple targets or decoys can appear simultaneously, these systems must be able to instantly distinguish authentic targets from false ones to avoid mission failure or a wasted trajectory and to prioritise the highest-threat targets, according to the team. 'Critically, given the autonomous nature of underwater high-speed vehicles, all decisions must be made without real-time external communication support, substantially increasing algorithmic complexity and computational demands,' the team said. 'The deep-learning recognition model proposed in this study, combined with the generative adversarial networks' small-sample identification solution, enables effective underwater target discrimination. This lays the technical groundwork for field deployment,' they added. – South China Morning Post
The Star
13 hours ago
- The Star
California freshwater fish found to be teeming with parasites
NEW YORK, June 4 (Xinhua) -- More than 90 percent of popular freshwater fish in U.S. Southern California are carrying human-infecting parasites, posing a significant danger for those who like to eat freshly caught freshwater fish, according to a study published on Tuesday in the Journal of Infectious Diseases. The parasites are called trematodes. Two species of the flatworms were discovered in California's freshwater fish. The tiny, flattened and sluglike creatures can cause gastrointestinal problems, weight loss and lethargy when a person eats an infected fish. In some rare and severe cases, the parasites have caused strokes or heart attacks. "Americans don't usually think about parasites when they eat freshwater fish because it hasn't historically been an issue here," the Los Angeles Times quoted Ryan Hechinger, the study's senior author, as saying. In fact, even when a person has fallen ill from a locally caught infected freshwater fish, their healthcare provider will typically ask if the patient has recently traveled outside of the United States, Hechinger said.
The Star
15 hours ago
- The Star
3 generations of dolphins spotted off Israeli coast in rare sighting
JERUSALEM, June 4 (Xinhua) -- Israeli marine researchers have documented a rare sighting of three generations of bottlenose dolphins swimming together in the Mediterranean Sea off the coast of Tel Aviv, the University of Haifa said in a statement on Wednesday. The group included a grandmother, her daughter, and a newborn calf -- all belonging to the Tursiops truncatus species, commonly known as the bottlenose dolphin. The sighting was captured during a routine weekly marine survey, part of a long-running study by the university's Mediterranean research station in partnership with Delphis, a non-profit organization focused on marine mammal conservation. According to the researchers, it is the first time in 25 years of ongoing observation that a three-generation dolphin family has been photographed together in Israeli waters. The common bottlenose dolphin is the most frequently sighted species along Israel's coastline, with a local population estimated at around 360. While not classified as endangered, researchers say consistent monitoring remains critical. The grandmother dolphin, already familiar to the team, was previously recorded with calves in 2018 and 2021, underscoring the continuity of reproductive behavior in this small coastal population. Researchers noted that relatively few calves are identified after separating from their mothers, making the latest sighting a rare and valuable contribution to the long-term dataset.
