Accelerated climate change and human-induced disturbances are critical drivers of the decline in biodiversity and beneficial ecosystem services (Finzi et al. 2011; Kao et al. 2012; Singh 2010). South Korea’s ecosystem has experienced substantial changes during the industrialization period, such as land use changes, habitat fragmentation, and pollutant enrichment. Climate modeling results have revealed that the Korean Peninsula is vulnerable to climate change and extreme climate events. For example, the temperature increase rates for the Korean Peninsula were higher than Earth’s average from 1912 to 2014 (Park et al. 2017), and extreme climate events such as super typhoons, severe drought, and heat waves have frequently occurred since the 1980s (Min et al. 2003). These multiple environmental changes affect biogeochemistry, species distribution, and human health (Singh 2010). Thus, there is an urgent need to understand how ecosystems respond to these changes and to provide suggestions for policymakers to manage complex environmental challenges. However, the understanding and accumulated time series data regarding ecosystem responses to climate change or anthropogenic activity are insufficient for predicting these responses by using models. An ecosystem observatory network is required at the national scale to manage ecosystem challenges such as changing distributions of species and loss of habitat, forest dieback, increasing rates of soil heterotrophic respiration, and reductions in primary productivity (Allen et al. 2010; Cleverly et al. 2019; McCallum et al. 2014).

The concept of ecosystem observatory networks was introduced in the United States and Australia in the early 2000s. These observatories generate multidisciplinary datasets by using automatic sensor-based equipment for air, soil, and water testing; airborne remote sensing; and organismal sampling (Kao et al. 2012; Karan et al. 2016; Musinsky et al. 2022). They operate an observatory network to monitor biodiversity and ecosystem functions at a single location over long periods. Specifically, the Terrestrial Ecosystem Research Network (TERN) in Australia has a network of 16 supersites by augmenting previous infrastructure and constructing new sites from scratch. In the National Ecological Observatory Network (NEON) in the United States, 81 ecosystem observatory stations have been developed as a new continental monitoring system. The ecological data produced by these observatories are open source to help researchers, policymakers, and citizens identify the underlying mechanisms in response to climate change.

Most environmental scientists and governmental officials have agreed with the necessity of an ecological monitoring network in South Korea to manage the environmental crisis. Korean Long-Term Ecological Research (KLTER) has been conducted by academic groups since 2004 and has achieved valuable scientific results. However, the KLTER project has limitations: (i) integrating data from different sites was difficult because researchers followed different methodologies (protocols and instruments), (ii) its monitoring system could not explain the interactions among ecosystem components, and (iii) automated observatory was not able to be implemented in ecosystem monitoring because the budget and number of technicians has been insufficient. Therefore, providing national-scale ecological solutions was impossible. The Ministry of Environment (MOE) and the National Institute of Ecology (NIE) in South Korea established a plan for the Korean Ecological Observatory Network (KEON), which is benchmarking an advanced ecosystem observatory such as NEON and TERN; this new observatory system will reflect the environmental condition of the Korean Peninsula.

KEON focuses on multidisciplinary monitoring of physiochemical, meteorological, and biological components of ecosystems, which are necessary to deepen process-based understanding of ecosystem functions and detect changes. Coordinated and standardized ecosystem observatories will conduct intensive meteorological, organismal, pedological, biogeochemical, and hydrological monitoring at the five new KEON and augmented KLTER sites. KEON’s missions include (i) performing standardized ecological monitoring to record changes in ecosystem dynamics, processes, and function; (ii) conducting ecological research to understand the underlying mechanisms in response to climate change and human-induced disturbance; and (iii) providing data-driven suggestions to policymakers or resource managers to address environmental changes.

KEON aims to answer nationwide and long-term ecological questions by using a standardized monitoring approach. Urgent ecological questions are answered using automated sensing systems and standardized field surveys.

This study aimed to answer the following five research questions by using collected datasets or externally funded research projects by external researchers:

• 1. How are ecosystem structure, biodiversity, and community in the ecosystem changing?

• 2. What are the drivers of ecosystem functions and spatial distributions?

• 3. How are stocks and fluxes of energy, green-house gases, and water changing in response to environmental change?

• 4. Can the thresholds or tipping points on the undesirable state of changes be identified?

• 5. Can the harmful effects of environmental change be minimized or solutions provided?

Notably, opportunities to obtain answers based on the coordinated infrastructure of ecosystem observatory sites across South Korea are increasing.

KLTER has been investigated by academic research groups funded by the Ministry of the Environment since 2004. For example, the species population dynamics, energy flow, and phenology of diverse ecosystems (forest, urban, wildfire zone, freshwater, and brackish water zone) have been investigated. Based on an intensive field study, 162 research papers have been published, and valuable ecological datasets were collected (Joo et al. 2013). Since 2014, the NIE has led the KLTER project in collaboration with university researchers. We outline the main research subjects and results from 2016 to 2022 in this paper.

Carbon flux

Quantitative estimation of the carbon budget in forests is crucial for understanding the global carbon balance and climate change (Cox et al. 2000). The CO₂ sink or source of forests is modified by complex component processes of carbon absorption and release depending on the climate, soil, age of the forest, and composition of plant species (Kim et al. 2022). CO₂ concentrations and fluxes were measured at a height of 33 m above the ground by using an open-path CO₂/H₂O analyzer and an ultrasonic anemometer at a broad-leaved deciduous forest (Quercus mongolica) site for the KLTER in Jeombong-san, Korea (Joo et al. 2011). The total average mean CO₂ flux was approximately –0.07 mg CO₂ m^-2 s^-1, with a maximum monthly mean flux of 0.03 mg CO₂ m^-2 s^-1 in April and a minimum value of –0.19 mg CO₂ m^-2 s^-1 in June. The hourly mean CO₂ flux showed a remarkable diurnal variation, with a maximum at 1100–1200 LST and a minimum at 0200–0400 LST throughout the growing season. As the total CO₂ flux between the atmosphere and forests was measured by an eddy covariance system, the estimated net ecosystem exchange was approximately –1.01 kg CO₂ m^-2, which revealed a carbon sink area in the Q. mongolica forest of Jeombong-san.

Soil respiration

Soil respiration is a key factor in the global carbon cycle and the second-largest carbon flux (Raich and Schlesinger 1992). More importantly, potential positive feedback between increasing temperature and enhanced soil respiration can accelerate global warming (Rodeghiero and Cescatti 2005; Schlesinger and Andrews 2000). This study investigated Jeombong-san, in the central part of the Korean Peninsula from 2017 to 2022 to understand the soil respiration characteristics of cool-temperate deciduous forests and to predict changes in the soil carbon cycle of the ecosystem due to long-term climate change. For this purpose, six collars (16 cm in diameter) were installed to collect soil respiration (Rs) data for each slope on the east, west, and ridge. Each collar was selected based on tree location, litter development, and slope and was installed to reflect various environmental conditions at the measurement site. In addition, three collars were installed to collect heterotrophic respiration (Rh) data from the root cutting-treated plots (80 cm depth, 100 × 100 cm). Soil respiration data were collected on approximately the 10th of every month from April to November, and the ground temperature and soil moisture content were measured at each measurement point. The Rs of the three slopes was calculated as an average of 10.3 tC/ha/yr. Additionally, the Rh was calculated an average of 5.88 tC/ha/yr (Fig. 1). Soil respiration was highly correlated with soil temperature in our study site, likewise the previous study (Knapp et al. 1998; Lee et al. 2012). We can predict that increased air temperature can enhance the CO₂ emission from forest soil (Bond-Lamberty and Thomson 2010).

Figure 1. Variations in soil carbon efflux in temperate broad-leaved ecosystem on Jeombong-san from 2017 to 2022. Data were collected from three slopes: west, ridge, and west. Rs: soil respiration; Rh: heterotrophic respiration.

Drought control experiments

The Korean Peninsula has experienced an increase in extreme climatic events, such as drought and flooding, since the 1980s (Min et al. 2003). We investigated the effects of drought on the morphological, physiological, and biochemical traits of 12 tree species. The response to drought stress varied among these species, and we categorized them into three levels: highly, moderately, and susceptible. Species classified as highly resistant to drought stress showed high leaf mass per area (LMA), photosynthetic rate (Pn), and midday leaf water potential (ΨMD) and low carbon isotopic discrimination (δ¹³C), flavonoid and polyphenol content, superoxide dismutase, and DPPH radical scavenging activity (Bhusal et al. 2020, 2021). In the long-term drought experiment, Pinus koraensis was highly resistant, and Q. acutissima, Chamaecyparis obtusa, Betulapendula, Fraxinus rhynchophylla, and Acer mono showed susceptibility to drought. Pinus densiflora, Larix kaempferi, Prunu sargentii, Abies holophylla, and P. thunbergii are moderately resistant to drought (Bhusal et al. 2021). The response of plant biomass closely paralleled the changes in morphological, physiological, and biochemical traits. Whole tree biomass is positively correlated with leaf size, LMA, maximum photosynthesis rate, and leaf water potential (Bhusal et al. 2022). Short-term severe drought causes an imbalance in carbon metabolism, leading to an increase in the root volatile discharge (monoterpenes) of P. strobus (Chandrasekaran et al. 2022). Severe drought also disrupts nutrient acquisition in the roots of P. strobus (Chandrasekaran et al. 2023). These findings can be applied in the practice and management of afforestation programs to accurately predict ecosystem responses to extreme climate events.

Vegetation dynamic monitoring

Changes in tree biomass and population dynamics are crucial parameters for estimating the net primary product and the carbon cycle of terrestrial ecosystems (Jenkins et al. 2001). Furthermore, a set of vegetation monitoring plots can provide critical links to validate datasets between ground measurements and spectrophotometric and light detection and ranging (LiDAR) remote sensing instruments (Kao et al. 2012). The tree density per unit area of the Nam-san Q. mongolica forest will increase from 1,125 trees/ha in 2017 to 1,160 trees/ha by 2021. The plant density per unit area of Q. mongolica forests in Jiri-san decreased from 643 trees/ha in 2019 to 628 trees/ha in 2021. The population of Q. mongolica increased from 388 to 379 trees/ha. In the Hallasan A. koreana forest, tree density per unit area increased from 1,743 trees/ha in 2016 to 1,822 trees/ha in 2022, and A. koreana decreased from 680 to 678 trees/ha. The rate of population density change for Nam-san Q. mongolica (10.2%) and P. densflora (13.6%) was greater than that for Jiri-san Q. mongolica (2.3%) and P. densflora (2.1%). However, Jiri-san (3.9%) showed a greater change than Halla-san (0.2%) for A. koreana. We expect that continuous (long-term) monitoring will explain the causal relationship between climate change and tree population dynamics.

Insect dynamic monitoring

Moths are frequently used to assess species diversity in response to landscape management and climate change because of their diversity. They also play essential roles as herbivores and pollinators in terrestrial ecosystems (Choi et al. 2022). Our research group investigated moths to track changes in the number of species and individuals in two high mountains in southern South Korea: Jiri-san and Halla-san. Three sites representative of oak (Q. mongolica), Korean fir (A. koreana), and pine trees (P. densiflora) were selected from both mountains. The survey results from both mountains during the last decade (2005–2021 for Jiri-san and 2009–2020 for Halla-san) showed that the diversity was higher in pine forests on both mountains (545 species and 6,303 individuals on Jiri-san, and 306 species and 1,799 individuals on Halla-san), followed by Korean fir (515 species and 8,789 individuals) and oak (443 species and 6,282 individuals) on Jiri-san, and oak (157 species and 965 individuals) and Korean fir (61 species and 298 individuals). During the last decade, although the number of individuals has decreased, the number of species has increased. Overall, there were no significant changes in the number of species or individuals on either mountain except in the oak forest. On Halla-san, there was a significant increase in the number of species, and on Jiri-san, there was a significant decrease. The similarity of moth assemblages in the pine forest and Korean fir on Halla-san showed significant changes, indicating a drastic change in species composition over the last decade. We posit that further research is necessary to determine the causal relationship between changes in moth populations and recent climate warming.

The core consideration in establishing a nationwide ecological observatory is the development of standardized protocols for monitoring ecosystem changes (Metzger et al. 2019). Cross-site comparisons cannot be secured without coordinated and standardized approaches that derive national-scale nature-based solutions (Karan et al. 2016). A key monitoring strategy is to apply the same methodology and comparable measurement items at all observatory sites and to select representative sites on the Korean Peninsula. First, multidisciplinary ecological and environmental monitoring (e.g., meteorological, biological, pedological, biogeochemical, and hydrological elements) was conducted at the two supersites to compare ecosystem responses depending on the climate zones. To select the monitoring sites, we evaluated 13 candidate sites proposed by the Korean Ecological Society according to the following five criteria (representativeness of the ecosystem, comprehensive research possibility, facility availability, continuity over 30 years, and convenience for maintenance). We conducted climate and terrain analyses and consulted forest ecology and meteorology experts through field trips. Finally, Gyeryong- san for temperate forests and Wando for warm-temperate forests were selected as the two supersites. Next, ecosystem-specific monitoring was conducted at three local sites (wetland, urban, and Gotjawal ecosystems). Wetland ecosystem monitoring focuses on methane emission and aquatic organism dynamics. Urban ecosystem monitoring is conducted to determine human-induced effects on species populations, habitats, and the density of disease-carrying animals. The Gotjawal ecosystem monitors the carbon and groundwater budgets and the dynamics of evergreen broad-leaved forests. Last, the mobile observatory system (mobile deployment platform) is designed for rapid deployment to manage urgent ecological events (e.g., fires, mass dieback, and insect outbreaks) across the nation, as well as the standardization of research locations. This mobile observatory is equipped with meteorological, water, and soil measurement sensing systems (Table 1).

Table 1 . Three observatory types of Korean Ecological Observatory Network and their observation lists.

Category	Supersites (2)	Local sites (3)	MDP (2)
Definition	Integrated terrestrial ecosystem observatory, depending on the climate-vegetation zones (temperate and warm-temperate zone)	Automatic ecosystem observatory considering the characteristics of local scale three ecosystem types	Take action on the urgent ecological concern (e.g., outbreak, wildfire, mass mortality)
Observation	e.g., Meteorology, hydrology, biogeochemistry, phenology, remote sensing, land cover, population dynamics, pedology	Wetland: e.g., population dynamics, hydrology & water quality, methane emission Urban: e.g., pollutants, carbon cycle, disease-carrying animals, pedology Gotjawal: e.g., population dynamics, phenology, carbon cycle	e.g., meteorology, carbon cycle, pollutants, soil sampling, unmanned aerial vehicle remote sensing

MDP: mobile deployment platform.

Biogeochemistry

The movement and forms of carbon (C), methane (CH4), and other nutrients (e.g., nitrogen [N] and phosphorus [P]) in the soil, atmosphere, and water are critical for the overall health and function of terrestrial and aquatic ecosystems (Likens and Bormann 1974). Furthermore, understanding the flux of greenhouse gases in ecosystems is a key element in predicting climate change impacts and developing adaptation strategies for climate change. Developed countries (United States, Europe, Australia, and Japan) have tower-based eddy covariance and nutrient deposition monitoring equipment to provide long-term records of nutrient cycles (Karan et al. 2016). In addition, the quantification of plant productivity, dead plant biomass, soil microbial community composition, and isotopic measurements can provide more specific information on nutrient cycles.

Carbon flux

In 2016, an ecosystem CO₂ flux observation tower was constructed in Jeombong-san. The carbon measurement system applied the eddy covariance technique and a chamber-based method to measure the changes in carbon across soils, plants, and the atmosphere at the site. The amount of carbon discharged through the stream was measured using a V-notch weir. These whole carbon flux measurement systems will be applied to the supersites of KEON. First, a three-dimensional anemometer and an enclosed-path CO₂/H₂O infrared gas analyzer were equipped with flux towers. The system operated at 20 Hz. The eddy covariance assembly also required sophisticated meteorological sensors for temperature, humidity, radiation, and precipitation across the tower elevation. The sizes of the towers ranged from 3 m in the wetland to 60 m above the tall evergreen tree forest. For calculating soil respiration and CO₂ flux, vertical profiles of soil temperature, moisture, and CO₂ concentration were measured over a 1 ha plot. The radiation and through-fall precipitation were measured near the soil surface. This equipment and technique will be developed and expanded to five KEON sites and four KLTER sites, considering the latitude and ecosystem types of South Korea (Table 2). The combined valuable datasets at the national scale make predicting the spatiotemporal variability of carbon and methane cycles under various climate change scenarios possible (Fig. 2).

Table 2 . Dominant vegetation and weather conditions at the nine greenhouse gas flux towers across South Korea.

Sites	Observatory	Dominant tree	Elevation (m)	Annual precipitation (mm/yr)	Mean annual temperature (°C)	Min. temperature in Jan (°C)	Max. temperature in Aug (°C)
JB_forest	KLTER	Quercus mongolica	800	1,721	7.0	–9.2	23.8
NS_urban	KLTER	Quercus mongolica	240	1,195	13.2	–3.9	30.9
GR_forest	KEON	Quercus variabilis	235	1,203	12.0	–5.4	30.4
DJ_urban	KEON	Pinus rigida	80	1,274	13.1	–4.1	30.9
SC_suburban	KLTER	Pinus thunbergii	15	1,225	12.6	–3.5	30.4
UP_wetland	KEON	Salicaceae spp.	10	1,313	13.1	–5.1	31.4
JR_forest	KLETR	Quercus mongolica	750	2,173	10.1	–4.9	25.8
WD_forest	KEON	Quercus acuta	360	2,434	12.3	–1.7	28.8
JG_forest	KEON	Lauraceae spp.	220	2,239	14.6	2.9	29.1

Weather datasets (mean value from 1991 to 2020 with raster format) were derived from the Korea Meteorological Administration (http://www.climate.go.kr/).

Min: minimum; Max: maximum; JB: Jeombong-san; NS: Nam-san; GR: Gyeryong-san; DJ: Daejeon-si; SC: Seocheon-gun; UP: Upo wetland; JR: Jiri-san; WD: Wando; JG: Jeju gotjawal; KLTER: Korean Long-Term Ecological Research; KEON: Korean Ecological Observatory Network.

Figure 2. The ecological observatory locations for (A) flux towers, (B) phenoCams, and (C) species monitoring. JB: Jeombong-san; NS: Nam-san; GR: Gyeryong-san; DJ: Daejeon-si; SC: Seocheon-gun; UP: Upo wetland; JR: Jiri-san; WD: Wando; JG: Jeju gotjawal; KEON: Korean Ecological Observatory Network; KLTER: Korean Long-Term Ecological Research.

Phenology

Vegetation phenology is one of the most sensitive, clear-cut indicators of biotic responses (Menzel et al. 2006). All flux towers will be equipped with PhenoCam to record time series images of vegetation phenology in the canopy and understory areas. Image data from PhenoCams on the KEON flux tower and KLTER PhenoCams were combined and analyzed to determine the phenological response of vegetation to climate change. Fluctuations in vegetation phenology can affect the life cycles of animals and food web dynamics (Parmesan 2006). Our automated phenology camera system will be involved in the global phenology network (Phenological Eyes Network). Bird and mammal phenological events, such as migration, mating, and egg laying, will be checked in the core 1 ha plots with an acoustic recorder or field monitoring.

Species diversity and population dynamics

We focused on providing a standardized coordinated sampling strategy across sites. KEON’s primary goal is to understand and predict species population dynamics and biodiversity in response to environmental changes. Each monitoring site covered a minimum of 1 ha and a maximum of 16 ha to determine species diversity and population dynamics. Extensive field surveys of small mammal populations, bird and insect abundance and diversity, plant diversity and biomass, and soil microbial community structure will be conducted regularly. Plant productivity data were collected from all plots to estimate the aboveground biomass and productivity near the flux tower. The collected data will be used to calculate net ecosystem productivity and serve as a calibration for the remote sensing data. Changes in soil microbial functional communities can explain fluctuations in soil respiration. Finally, these data can be used to predict food web distortions in response to extreme climatic events.

Remote sensing

KEON plans to collect hyperspectral, LiDAR, and photogrammetric data from five forest plots by using ground-based and unmanned aerial vehicle-based remote sensing equipment (Kwak et al. 2010; Lamchin et al. 2018). Leaf area index (LAI) is a key proxy variable for estimating other crucial ecological responses, including plant biomass, photosynthesis, transpiration, carbon balance, and ecosystem energy flux, and is a required input for ecological process models such as carbon cycling (Bonan 1993). Although national-scale LAI is derived from satellite data, calibrating satellite data using an unmanned aerial vehicle and ground- collected data is necessary (Kao et al. 2012). National-scale carbon cycling models are possible after rigorously developing calibrated ground truth estimates of LAI (Yoo et al. 2013). Additionally, the combination of ground and remote sensing LAI data can be used to quantify the damage to the carbon cycle caused by climate extremes such as drought, heat waves, heavy precipitation, and typhoons.

Data stream

All KEON-generated data products are open source via the Ecobank (https://www.nie-ecobank.kr/) and an integrated eco-climate data platform. All site datasets will be available to the research, education, and policy development communities. All site datasets undergo a year-long data quality control process before being open to the public. These datasets include site monitoring datasets for meteorological, hydrological, ecological, and biological features and greenhouse gas changes at the KEON site. Data standardization and formatting (i.e., nationally and internationally) will be conducted to encourage the exchange of data among scientists.

Collaborations with KEON

The infrastructure and datasets of KEON will be designed similarly to other national ecosystem monitoring systems (e.g., NEON in the United States, TERN in Australia, JaLTER [Japan Long-Term Ecological Research] in Japan, and CERN [Chinese Ecosystem Research Network] in China) to improve cross-continental data sharing and comparison. An agreement has been signed for data sharing and technical support from NEON and TERN. Furthermore, there will be a close collaboration with AsiaFlux, a regional network for observing carbon flux, and the International Long-Term Ecological Research (ILTER). It is necessary for data sharing and cooperation with other observation sites in South Korea, such as Gwangneung flux observation site which has been operated since 2002. KEON will also cooperate with universities to conduct more specific ecological research. Visiting researchers from universities or other institutes are encouraged to conduct independent research at KEON sites and automated long-term ecological monitoring. Research facilities, infrastructure, and raw data can be provided to researchers. The only requirement for collaboration with KEON is that the collected data are submitted to the data portal after the research and journal publication are complete. In addition, several KEON websites support public education and outreach programs for university and high school students.

KEON, the first national-scale observation project in South Korea, will produce multidisciplinary data to understand ecological changes in biodiversity, species population dynamics, phenology, and biogeochemistry. In addition, KEON and KLTER, two similar long-term observatory systems, will be incorporated into one network for the intensive monitoring of the environmental and biological components of the ecosystem. The main principles of the design are consistent methodology, long-term collection, calibration, and standardized data processing. Notably, collecting long-term timescales and a broad range of unprecedented spatial datasets to reveal the impacts of climate change on biotic communities and ecosystem functions is necessary. The KEON project is the start of systematic ecosystem monitoring. Expansion of the KEON infrastructure requires evidence-based prioritization and gap analyses of existing monitoring sites. More importantly, successful data collection requires a well-organized design and effective collaboration with external partners. KEON has well- developed partnerships with NEON, TERN, and AsiaFlux for technical support and data sharing. We believe that KEON will play an important role in ecological observations and provide clues for finding nature-based solutions to environmental crises.

We would like to thank all researchers who carried out the field surveys of KLTER. We thank the MOE of the Republic of Korea for their assistance.

TERN: Terrestrial Ecosystem Research Network

NEON: National Ecological Observatory Network

KLTER: Korean Long-Term Ecological Research

MOE: Ministry of Environment

NIE: National Institute of Ecology

KEON: Korean Ecological Observatory Network

LMA: Leaf mass per area

LiDAR: Light detection and ranging

LAI: Leaf area index

JSP designed the study, manuscript writing, and reviewed the manuscript. SJJ, JL, DS, HSK, JJ, CWY, JEL, SWC, and JYL performed the data collection, analysis, and manuscript writing. JSP received a research grant. All authors have read and approved the final manuscript.

This study was supported by the NIE (Project No. NIE-B-2023-02 and NIE-C-2023-102).

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The authors declare that they have no competing interests.