Extreme climate events such as heat waves, drought, and heavy rainfall are occurring more frequently and are more intense due to ongoing climate change. This study evaluated the early growth performance of one-year-old Larix kaempferi (Lamb.) Carr. seedlings under open-field extreme climate conditions including experimental warming and different precipitation regimes. We recorded the survival rate, root collar diameter, height, biomass, shoot-to-root ratio, and seedling quality index using nine treatments (three temperature levels, i.e., control, warming by 3 °C and by 6 °C, × three precipitation levels, i.e., control, drought, and heavy rainfall) in July and August 2020. The survival rate of seedlings did not differ between treatments, showing high values exceeding 94% across treatments. The measured shoot height was largest under warming by 3 °C and high rainfall, indicating that moderate warming increased seedling height growth in a moist environment. Heavy rainfall decreased stem volume by 21% and 25% under control and warming by 6 °C treatments, respectively. However, drought manipulation using rain-out shelters did not decrease the growth performance. Overall, extreme climate events did not affect the survival rate, biomass, shoot-to-root ratio, and seedling quality index of L. kaempferi. We thus conclude that, regarding growth responses, L. kaempferi seedlings may be resistant to short-term extreme warming and drought events during summer.

Extreme climate events, generally defined as inordinately hotter, drier, or wetter compared to the historical period, are showing an increasing trend in terms of their frequency, intensity, and magnitude. They can impair the recovery system of plants, and thus, there is a need to understand their effects on plants. Here, we constructed a temperature and precipitation manipulation system to simulate extreme climate events for plants in the open field in April, 2020. We applied a factorial combination of three temperature levels (control, +3 °C, and +6 °C) and three precipitation levels (control, drought, and heavy rainfall) with six replicates (i.e., 54 plots of 1.5 m × 1.0 m) from April to June, 2020. Infrared heaters were adopted for simulating extreme heat since they are able to provide a realistic heating mechanism. The targeted temperature was automatically maintained by the data loggers and relays. For the extreme drought simulation, automatic rainout shelters intercepted ambient rainfall, closing only when detecting rainfall to avoid a disturbance of light absorption and passive warming. The rainfall simulator sprayed water from a height of 1.6 m above the ground using spraying nozzles and, the spraying time and pressure were set by the hooked-up pump and control panel to generate realistic rainfall. An infrared thermometer and a soil moisture and temperature sensor per plot measured the soil surface temperature and soil water content, respectively. As a result, the infrared heaters increased the mean soil surface temperature (°C ± standard error) by 2.7 ± 0.2 and 5.7 ± 0.5 in the +3 °C and +6 °C plots, respectively, compared to that in the control. The rainout shelter and rainfall simulator successfully produced extreme drought and heavy rainfall conditions, showing higher mean soil water contents (vol. %) of 4.44 ± 0.01 in the drought plots and 8.45 ± 0.03 in the heavy rainfall plots than that in the control (7.19 ± 0.03). Our multifactor manipulation system can provide a mechanistic understanding of the combined extreme stresses on soils and plants (e.g., soil microbial activity, seed germination, and growth of seedlings) through the comparison between the impact of single and multiple factors. Furthermore, the system has the advantage of applying diverse intensities of extreme climate events without restrictions on regions and scenarios by altering the settings of data loggers or the control panel. The system in this study can aid in investigating and modeling the mechanisms between extreme climate events, and soils and plants.Acknowledgment: This study was carried out with the support of the National Research Foundation, Republic of Korea (Project No. 2022R1A2C1011309) and Korea Forest Service (Project No. 2020181A00-2222-BB01).