In the Korea Flux Monitoring Network, Haenam Farmland has the longest record of carbon/water/energy flux measurements produced using the eddy covariance (EC) technique. Unfortunately, there are long gaps (i.e., gaps longer than 30 days), particularly in 2007 and 2014, which hinder attempts to analyze these decade-long time-series data. The open source and standardized gap-filling methods are impractical for such long gaps. The data-driven approach using machine learning and remote-sensing or reanalysis data (i.e., interpolating/extrapolating EC measurements via available networks temporally/spatially) for estimating terrestrial CO₂/H₂O fluxes at the regional/global scale is applicable after appropriate modifications. In this study, we evaluated the applicability of the data-driven approach for filling long gaps in flux data (i.e., gross primary production, ecosystem respiration, net ecosystem exchange, and evapotranspiration). We found that using a longer training dataset in the machine learning generally produced better model performance, although there was a greater possibility of missing interannual variations caused by ecosystem state changes (e.g., changes in crop variety). Based on the results, we proposed gap-filling strategies for long-period flux data gaps and used them to quantify the annual sums with uncertainties in 2007 and 2014. The results from this study have broad implications for long-period gap-filling at other sites, and for the estimation of regional/global CO₂/H₂O fluxes using a data-driven approach.

Understanding patterns of biodiversity and their drivers along environmental gradients is one of the central topics in ecology. However, whether diversity patterns along environmental gradients differ among diversity components as well as life forms and what kind of variables control or interact to shape the diversity patterns are poorly known. This study scrutinized the distribution patterns of three plant groups with four diversity indices and evaluated the effects of regional area, topography, topographic heterogeneity, climate, primary productivity, vegetation structure diversity and vegetation type diversity along an extensive elevational gradient on the Baekdudaegan Mountains in South Korea. Different elevational patterns, including hump-shaped, reversed hump-shaped, increasing, multimodal and no relationship, were observed among both the diversity indices and the plant groups. Regional area, habitat heterogeneity and climate were included to explain most of the elevational diversity patterns. In particular, habitat heterogeneity was the most important variable for explaining the patterns of diversity. The results suggest that patterns of elevational diversity may differ not only among plant groups but also among diversity indices and that such patterns are primarily caused by habitat heterogeneity in the Baekdudaegan Mountains because more heterogeneous and diverse habitats can support more coexisting species.

Leaf area index is a key structural parameter for biological and physical processes. Korea is planning to launch CAS500-4 in 2025, so in situ data is needed to validate the leaf area index. Unlike other networks (e.g., NEON and TERN), establishing an elementary sampling unit is difficult in Korea due to the complex forest structure and rugged terrain. Therefore, pixel-level correspondence between the satellite product and fisheye footprints is the best way to verify in complex terrain. In this study, we analyzed the spatial footprint of fisheye lenses in different forest types using terrestrial LiDAR data for the first time. The three-dimensional forest structure was analyzed at various viewing zenith angles, and the footprint radius was approximately 3 m at view zenith angle (VZA) 20° and approximately 10 m at VZA 90°. We also analyzed the Z-values from terrestrial laser data and the plant area index on leafless seasons to assess the impact of obstacles, such as tree trunks, under various viewing zenith angles. The analysis showed that the influence of woody components increases dramatically as the VZA exceeds 40°. Such factors influenced the increase in LAI and the decrease in the clumping index as the VZA increased. Overall, we concluded that narrowing VZA between 20° and 40° is appropriate for Korean forests with complex structures.

Comprehensive research on the structural and functional variability of benthic macroinvertebrate communities within headwater streams is limited, despite the fact that the majority of streams within a watershed are headwater streams that form the primary link between terrestrial and aquatic ecosystems. Therefore, we investigated the structure and function of benthic macroinvertebrate communities in four headwater streams at two different spatial scales (i.e., sampling sites (i.e., reaches) >samples (i.e., riffles)) over three seasons (i.e., spring, summer and autumn) of the year. Community indices, functional feeding guilds and habit trait guilds varied significantly depending on the seasons rather than on sites in two-way ANOVA based on spatial (i.e., sampling sites) and seasonal effects in each headwater stream. Non-metric multidimensional scaling analyses showed the differences between communities according to the considered spatial and temporal scales. At the individual stream scale, the differences between samples followed seasonal variation more than spatial differences. Site differences became more important when performing an ordination within a single season (i.e., spring, summer, and autumn). Continued research and monitoring employing both multidisciplinary and multidimensional approaches are required to maintain macroinvertebrate diversity within headwater streams.