BEIJING, May 23 (Xinhua) -- Wildlife conservation in China has been increasingly focusing on using the latest technologies. Smart monitoring systems, far-infrared cameras, big data, the Internet of Things, AI identification, and other high technologies have played pivotal roles in China's wildlife protection, promoting the stability of wildlife populations and restoring the ecological balance.
SMART MONITORING SYSTEMS
In 2021, China established the first batch of national parks, covering nearly 30 percent of the primary terrestrial wildlife species found in the country.
Smart monitoring systems have provided a new opportunity to protect wild animals in these national parks, according to a recent report by Science and Technology Daily.
In the Baishuijiang National Nature Reserve in northwest China's Gansu Province, reserve staff had to count the number of pandas by collecting their feces, hair, and other organic materials in the past. This method had many shortcomings, such as consuming a lot of manpower and time.
After the installation of the smart monitoring system, when wild animals enter the monitored area, the system can automatically photograph them and accurately identify their species type.
Reserve staff can now watch the real-time situation in their offices, effectively improving the efficiency of wildlife monitoring and protection.
In the Sanjiangyuan National Park in northwest China's Qinghai Province, an aerial monitoring platform mounted on helicopters and tethered balloons improves the collection and management of environmental monitoring data, the efficiency of data product development and sharing, and the level of decision-making.
According to the Sanjiangyuan National Park authorities, the park's grassland vegetation coverage rate reached 67.31 percent with the help of the monitoring platform. The Tibetan antelope, the park's key species, increased from less than 20,000 at the initial stage to about 70,000 by the end of 2022.
Infrared cameras are everyday equipment for wildlife investigation. When wild animals enter the sensing area of an infrared camera, an infrared sensing module will trigger the camera to take photos or videos.
The Shan Shui Conservation Center (an ecological environment organization), Peking University, and other partners have conducted infrared camera investigations in Qinghai, Tibet, Sichuan, Yunnan, and Beijing since 2011.
The wide use of infrared cameras helps researchers record many species' activity images, difficult to observe before the technology, said Zhao Xiang, a senior center manager.
Based on the long-term accumulation of these images, continuous research can be carried out on the activity rhythm of species, habitat selection, and inter-species relationships, thus helping reserves to make more science-based strategies.
After the spread of wildlife images on the internet, the general public's knowledge and understanding of wildlife have also significantly improved, he added.
Collar GPS tracking and genetics are also widely used in wildlife monitoring and research, according to Zhao.
For example, by extracting DNA from animal feces and hair, researchers can study the genetic relationship between different wildlife populations, and evaluate the barriers set by roads and other infrastructure to inter-species communication, thus promoting the construction of wildlife corridors.
Individual identification of wild animals used to be one of the hard nuts to crack in wildlife protection. For example, the individual identification of golden monkeys was done by manual marking, which often requires a researcher to observe for one or two months.
Zoologist Guo Songtao at China's Northwest University and some computer science experts used the principle of neural networks, and they developed the golden monkey individual recognition system for the first time, realizing accurate identification and continuous tracking and sampling of golden monkey individuals.
"We can't tag thousands of golden monkeys in the wild," he said, adding that the traditional DNA recognition from feces or hair does not meet the need for real-time recognition.
At present, the average recognition accuracy of the system has reached 94 percent. In the past, it focused on primate recognition, but now it has expanded to more than 40 different animals, such as canines and felines.
In addition to monkeys, big cats are also the target of AI identification. The National Forestry and Grassland Administration worked with the Harbin Institute of Technology to develop a smart platform to monitor wildlife.
It used technologies such as Internet of Things perception, big data, and intelligent machine vision to identify Siberian tigers, Amur leopards, and their prey.