This spring, due to unusual cold weather, spring flower festivals across the country were held as 'flowerless flower festivals.' At the Gwangyang Plum Blossom Festival and Yangsan Wondong Plum Blossom Festival, the lack of blooming flowers on the event day raised alarms, leading local governments, including Seoul, to struggle in scheduling festival events.
As climate change has made the changes in plants more evident, the National Arboretum is strengthening its nationwide observation of plant seasonal phenomena and launching research to predict future changes. Accurately predicting the blooming period is expected to increase the likelihood of success for flower festivals.
On the 28th, the National Arboretum held a scientific media seminar and presented the results of monitoring the seasonal changes in plants and research predicting changes in plant distribution due to climate change. Seasonal phenomena refer to the changes in plants that occur according to the seasons, such as flowers blooming or leaves coloring. The National Arboretum is observing the seasonal changes of 219 plant species across 47 regions nationwide in collaboration with various institutions.
According to the monitoring results, the blooming period of the cherry tree, a representative spring flower, is found to be advancing by an average of 0.8 days each year. Just over a decade ago, cherry blossoms typically bloomed around April 11, but recently they have bloomed as early as April 3, more than a week earlier. Azaleas are also blooming 1.2 days earlier each year, while gingers are advancing by 1 day each year.
Since 2020, the National Arboretum has published maps predicting changes in spring flower blooming and autumn foliage based on observational data. Initially, the foliage prediction was focused only on one type of maple, but it has since expanded to include various species such as the Zelkova and Ginkgo. The monitoring of spring flowers is also being broadened to include a wider range of species.
Im Young-seok, director of the National Arboretum, noted, "After accumulating various data, we will gradually reduce the errors between the prediction results and the actual blooming periods through deep learning." Deep learning is a machine learning method where artificial intelligence (AI) learns large amounts of information to identify patterns independently. Researcher Kim Dong-hak stated, "Even now, the gap between the prediction model and the observational results is narrowing each year."
The sophistication of observation methods is also being advanced. Previously, investigators would visit sites to check plant changes, but plans are in place to introduce a system that will analyze the degree of blooming progress using only photographs through drones and AI technology. Researcher Kim added, "In the future, we will install observation towers like overseas to enable more objective and continuous monitoring."
The National Arboretum will also utilize the latest life science techniques. Director Im stated, "Research has recently started to explore whether it is possible to predict blooming periods based on changes in ribonucleic acid (RNA) and proteins." RNA is the genetic material that copies DNA information for protein synthesis.
The National Arboretum is preparing a plant seasonal observation program that allows citizens to participate directly. Researcher Kim Dong-hak stated, "We will make it easy for citizens to report the blooming and foliage timing of trees from anywhere in the country," adding, "We plan to publicly launch the service as early as the second half of this year." This program is expected to be utilized in university education courses in collaboration with Mokpo National University, Kyungpook National University, and Chungbuk National University.
The National Arboretum is also conducting research on changes in plant distribution due to climate change. Researcher Jo Yong-chan noted, "The significant decrease in the coniferous tree colonies on Hallasan and Jirisan over the past decade indicates that the damage from climate change is becoming visible," explaining that "we are currently conducting research to predict changes in plant distribution based on various climate change scenarios."
In particular, modeling conducted on over 180 plant species native to the Korean Peninsula predicts that climate change will gradually reduce plant diversity in the southern coastal regions, Honam Inland areas, and eastern coastal areas. Researcher Jo stated, "The regions experiencing a decline in diversity need the influx of new species, but in coastal areas like the southern coast, it is not easy, so careful management is required," adding, "Some species, such as bellflower, may face habitat collapse and extinction due to climate change, requiring proactive responses like developing resilient varieties for preservation."
The National Arboretum is currently searching for species among the 450 native species in Korea that are at high risk of extinction due to climate change. In the future, it plans to understand distribution changes at the community level of plants to establish more precise response strategies.
Director Im stated, "The changes in plant ecosystems due to climate change may not be gradual but could occur rapidly," adding, "The National Arboretum will actively continue research to enhance prediction accuracy using accumulated data alongside deep learning technology and forest satellites, enabling proactive responses to future ecosystem changes."