Kim, Eun-Sub;Kim, Hoseok;Lee, Dong-Kun;Choi, Yun-Yeong;Kim, Da-Seul
Journal of the Korean Society of Environmental Restoration Technology
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v.27
no.1
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pp.55-70
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2024
The loss of biodiversity poses a significant threat not only to business sustainability and investment risk but also to societal well-being. Nature serves as a crucial driver for long-term business viability and economic prosperity. The Task Force on Nature-related Financial Disclosures (TNFD), established in September 2023, mandates that companies assess and disclose their impacts on nature. Despite this, many businesses lack a full understanding of their reliance on and impact upon natural capital and ecosystem services, leading to insufficient disclosures. This study evaluates the applicability of TNFD's assessment methodologies and indicators within a domestic context, highlighting the condition of nature and ecosystem services, and exploring potential synergies with national biodiversity policies. Our analysis suggests that TNFD necessitates a unique approach to the spatial and temporal data and methodologies traditionally employed in environmental impact assessments. This includes assessing the reciprocal influences of corporate activities on natural capital and ecosystem services via the LEAP framework. Moreover, in industries where the choice of specific indicators depends on unique sectoral traits, developing a standardized strategy for data and assessment indicators-adapted to local conditions-is crucial due to the variability in the availability of assessment tools and data. The proactive engagement of the private sector in ecosystem restoration projects is particularly promising for contributing towards national biodiversity objectives. Although TNFD is in its nascent phase, its global adoption by numerous companies signifies its potential impact. Successful implementation of TNFD is anticipated to deepen businesses' and financial institutions' understanding of natural capital and ecosystem services, thereby reinforcing their commitment to sustainable development.
Katherine M. Thibault;Christine M, Laney;Kelsey M. Yule;Nico M. Franz;Paula M. Mabee
Journal of Ecology and Environment
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v.47
no.4
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pp.219-227
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2023
The US National Science Foundation's National Ecological Observatory Network (NEON) is a continental-scale program intended to provide open data, samples, and infrastructure to understand changing ecosystems for a period of 30 years. NEON collects co-located measurements of drivers of environmental change and biological responses, using standardized methods at 81 field sites to systematically sample variability and trends to enable inferences at regional to continental scales. Alongside key atmospheric and environmental variables, NEON measures the biodiversity of many taxa, including microbes, plants, and animals, and collects samples from these organisms for long-term archiving and research use. Here we review the composition and use of NEON resources to date as a whole and specific to biodiversity as an exemplar of the potential of national research infrastructure to contribute to globally relevant outcomes. Since NEON initiated full operations in 2019, NEON has produced, on average, 1.4 M records and over 32 TB of data per year across more than 180 data products, with 85 products that include taxonomic or other organismal information relevant to biodiversity science. NEON has also collected and curated more than 503,000 samples and specimens spanning all taxonomic domains of life, with up to 100,000 more to be added annually. Various metrics of use, including web portal visitation, data download and sample use requests, and scientific publications, reveal substantial interest from the global community in NEON. More than 47,000 unique IP addresses from around the world visit NEON's web portals each month, requesting on average 1.8 TB of data, and over 200 researchers have engaged in sample use requests from the NEON Biorepository. Through its many global partnerships, particularly with the Global Biodiversity Information Facility, NEON resources have been used in more than 900 scientific publications to date, with many using biodiversity data and samples. These outcomes demonstrate that the data and samples provided by NEON, situated in a broader network of national research infrastructures, are critical to scientists, conservation practitioners, and policy makers. They enable effective approaches to meeting global targets, such as those captured in the Kunming-Montreal Global Biodiversity Framework.
Kim, Song-Hyun;Nam, Won-Ho;Jeon, Min-Gi;Hong, Eun-Mi;Oh, Chansung
Journal of The Korean Society of Agricultural Engineers
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v.66
no.4
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pp.1-15
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2024
In recent years, climate change has been responsible for unusual weather patterns on a global scale. Droughts, natural disasters triggered by insufficient rainfall, can inflict significant social and economic consequences on the entire agricultural sector due to their widespread occurrence and the challenge in accurately predicting their onset. The frequency of drought occurrences in South Korea has been rapidly increasing since 2000, with notably severe droughts hitting regions such as Incheon, Gyeonggi, Gangwon, Chungbuk, and Gyeongbuk in 2015, resulting in significant agricultural and social damage. To prepare for future drought occurrences resulting from climate change, it is essential to develop long-term drought predictions and implement corresponding measures for areas prone to drought. The Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report outlines a climate change scenario under the Shared Socioeconomic Pathways (SSPs), which integrates projected future socio-economic changes and climate change mitigation efforts derived from the Coupled Model Intercomparison Project 6 (CMIP6). SSPs encompass a range of factors including demographics, economic development, ecosystems, institutions, technological advancements, and policy frameworks. In this study, various drought indices were calculated using SSP scenarios derived from 18 CMIP6 global climate models. The SSP5-8.5 scenario was employed as the climate change scenario, and meteorological drought indices such as the Standardized Precipitation Index (SPI), Self-Calibrating Effective Drought Index (scEDI), and Standardized Precipitation Evapotranspiration Index (SPEI) were utilized to analyze the prediction and variability of future drought occurrences in South Korea.
Stress is a significant issue in modern society, often triggered by external or internal factors that are difficult to manage. When high stress persists over a long term, it can develop into a chronic condition, negatively impacting health and overall well-being. However, it is challenging for individuals experiencing chronic stress to recognize their condition, making early detection and management crucial. Using biosignals measured from wearable devices to detect stress could lead to more effective management. However, there are two main problems with using biosignals: first, manually extracting features from these signals can introduce bias, and second, the performance of classification models can vary greatly depending on the subject of the experiment. This paper proposes a model that reduces bias using convo utional autoencoders, which can represent the key features of data, and enhances generalizability by employing soft voting, a method of ensemble learning, to minimize performance variability. To verify the generalization performance of the model, we evaluate it using LOSO cross-validation method. The model proposed in this paper has demonstrated superior accuracy compared to previous studies using the WESAD dataset.
In this study, we analyzed the long-term distribution patterns of $CH_4$ determined from the Moo-Ahn (MAN) observatory in relation with those derived from the world major background monitoring sites. Comparison of the data were made using those data sets collected for the period between Aug. 1995 to Dec. 1991. The mean $CH_4$ concentration of MAN observatory was measured to be 1898${\pm}$85.3 ppb, recording the highest concentration of all the monitoring sites. When the concentration of $CH_4$ for different stations was compared over latitudinal scale, its concentration appeared to increase systematically as a function of latitude with an exception of MAN (and the other Korean monitoring site at Tae Ahn). Moreover, such phenomenon was more distinctive in Northern than Southern Hemisphere. According to the analysis of the monthly distribution patterns of $CH_4$ at MAN observatory, its concentration level began to increase from the months of February/March and peaked during August. In addition, when the level of oscillation in monthly concentrations (between the maximum and minimum values) was checked, differences were significant between MAN and other monitoring stations. If the rate of concentration change was checked using the data sets collected for this limited time period in terms of linear regression analysis, results for MAN showed the highest annual increasing rate of 16.5 ppb. It is hence suggested that the largest variability in the $CH_4$ distribution patterns at MAN observatory may be reflected by the high irregularity in its source/sink processes.
The major purpose of this study is to construct an in-situ soil moisture verification network employing Frequency Domain Reflectometry (FDR) sensors for Cosmic-ray soil moisture observation system operation as well as long-term field-scale soil moisture monitoring. The test bed of Cosmic-ray and FDR verification network system was established at the Sulma Catchment, in connection with the existing instrumentations for integrated data provision of various hydrologic variables. This test bed includes one Cosmic-ray Neutron Probe (CRNP) and ten FDR stations with four different measurement depths (10 cm, 20 cm, 30 cm, and 40 cm) at each station, and has been operating since July 2018. Furthermore, to assess the reliability of the in-situ verification network, the volumetric water content data measured by FDR sensors were compared to those calculated through the core sampling method. The evaluation results of FDR sensors- measured soil moisture against sampling method during the study period indicated a reasonable agreement, with average values of $bias=-0.03m^3/m^3$ and RMSE $0.03m^3/m^3$, revealing that this FDR network is adequate to provide long-term reliable field-scale soil moisture monitoring at Sulmacheon basin. In addition, soil moisture time series observed at all FDR stations during the study period generally respond well to the rainfall events; and at some locations, the characteristics of rainfall water intercepted by canopy were also identified. The Temporal Stability Analysis (TSA) was performed for all FDR stations located within the CRNP footprint at each measurement depth to determine the representative locations for field-average soil moisture at different soil profiles of the verification network. The TSA results showed that superior performances were obtained at FDR 5 for 10 cm depth, FDR 8 for 20 cm depth, FDR2 for 30 cm depth, and FDR1 for 40 cm depth, respectively; demonstrating that those aforementioned stations can be regarded as temporal stable locations to represent field mean soil moisture measurements at their corresponding measurement depths. Although the limit on study duration has been presented, the analysis results of this study can provide useful knowledge on soil moisture variability and stability at the test bed, as well as supporting the utilization of the Cosmic-ray observation system for long-term field-scale soil moisture monitoring.
In this study, we analysed hydrologic variability in quantity and onset of annual maximum flow and low flow by impacts of the different phases of ENSO (El Ni$\tilde{n}$o Southern Oscillation) over the Han River Basin. The results show that annual maximum flow has increased statistically significant about 48.3% of all over the watershed. The onset of annual maximum flow was delayed in the west of the Han River basins and in the east of the basins was likely to be rapid onset. Also, this study shows that 7-day low flow was deceased statistically significant about 26.0% of the total area in the Han River Basin, and onset of 7-day low flow tends to be faster in the upper-middle basins of the Han River. The onset of annual maximum flow shows similar pattern during the CT (Cold tongue)/WP (Warm-pool) El Ni$\tilde{n}$o years, but annual maximum flow appeared less in 89.0% of all basins during the CT El Ni$\tilde{n}$o years. In addition, the onset of 7-day low flow tended to be faster about 17 days on average during the WP El Ni$\tilde{n}$o years, and 72.7% of the basins show significant increase during the CT El Ni$\tilde{n}$o years. Consequently, it was found that the different phases of CT/WP El Ni$\tilde{n}$o have effects on sensitivity to variability in quantity and onset of water resources over the Han River Basin. We expect that the present diagnostic study on hydrological variability during different phases of ENSO will provide useful information for long-term prediction and water resources management.
The SLODSVAT consists of interrelated submodels that simulate : the transfer of radiation, water vapour, sensible heat, carbon dioxide and momentum in two canopy layers determined by environmental conditions and ecophysiological properties of the vegetation ; uptake and storage of water in the "root-stem-leaf" system of plants ; interception of rainfall by the canopy layers and infiltration and storage of rain water in the four soil layers. A comparison of the results of modeling experiments and field micro-climatic observations in a spruce forest(Picea abies [L].Karst) in the Soiling hills(Germany) shows, that the SLODSVAT can describe and simulate the short-term(diurnal) as well as the long-term(seasonal) variability of water vapour and sensible heat fluxes adequately to natural processes under different environmental conditions. It proves that it is possible to estimate and predict the transpiration and evapotranspiration rates for spruce forest ecosystems on the patch and landscape scales for one vegetation period, if certain meteorological, botanical and hydrological information for the structure of the atmospheric boundary layer, the canopy and the soil are available.
Korean Journal of Agricultural and Forest Meteorology
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v.11
no.1
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pp.27-38
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2009
The multi-level profile system is designed to measure the vertical profile of $H_2O$ and $CO_2$ concentrations in the surface layer to estimate the storage effects within the plant canopy. It is suitable for long-term experiments and can be used also in advection studies for estimating the spatial variability and vertical gradients in concentration. It enables the user to calculate vertical fluxes of water vapor, $CO_2$ and other trace gases using the surface layer similarity theory and to infer their sources or sinks. The profile system described in this report includes the following components: sampling system, calibration and flow control system, closed path infrared gas analyzer(IRGA), vacuum pump and a datalogger. The sampling system draws air from 8 inlets into the IRGA in a sequence, so that for 80 seconds air from all levels is measured. The calibration system, controlled by the datalogger, compensates for any deviations in the calibration of the IRGA by using gas sources with known concentrations. The datalogger switches the corresponding valves, measures the linearized voltages from the IRGA, calculates the concentrations for each monitoring level, performs statistical analysis and stores the final data. All critical components are mounted in an environmental enclosure and can operate with little maintenance over long periods of time. This report, as a practical manual, is designed to provide helpful information for those who are interested in using profile system to measure evapotranspiration and net ecosystem exchanges in complex terrain.
Journal of Korean Society of Coastal and Ocean Engineers
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v.24
no.4
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pp.269-276
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2012
Salinity distribution in estuary and tidal river is presented by many parameters including tidal forcing, river discharge and geographical effect. Understanding the characteristics of salinity structure is very important in the aspect of water-quality, ecological, and engineering viewpoint. Field measurement was carried out to study the distribution of salinity structure at 2 surface stations at Yeomha channel in the Han River estuary. The results of short- and long-term salinity change according to short and long tidal variability is investigated. For analyzing the axial salinity distribution at Yeomha channel, the salinity data from NFRDI is used in this study. The relationship between freshwater discharge and salinity distribution is represented through the nonlinear regression equation. The empirical equation for salt intrusion length scale, including tide, river discharge, and topographical effect is presented. As the comparison of empirical equation and existing data collected in study area, the characteristic of salt intrusion length and salinity distribution is changed by tide, fresh water, and geographical effect.
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