The key to invasive pest management lies in preemptive action. However, most current research using species distribution models is conducted after an invasion has occurred. This study modeled the potential distribution of the globally notorious sweet potato pest, the sweet potato weevil (Cylas formicarius), that has not yet invaded Korea using MaxEnt. Using global occurrence data, bioclimatic variables, and topsoil characteristics, MaxEnt showed high explanatory power as both the training and test areas under the curve exceeded 0.9. Among the environmental variables used in this study, minimum temperature in the coldest month (BIO06), precipitation in the driest month (BIO14), mean diurnal range (BIO02), and bulk density (BDOD) were identified as key variables. The predicted global distribution showed high values in most countries where the species is currently present, with a significant potential invasion risk in most South American countries where C. formicarius is not yet present. In Korea, Jeju Island and the southwestern coasts of Jeollanam-do showed very high probabilities. The impact of climate change under shared socioeconomic pathway (SSP) scenarios indicated an expansion along coasts as climate change progresses. By applying the 10th percentile minimum training presence rule, the potential area of occurrence was estimated at 1,439 km2 under current climate conditions and could expand up to 9,485 km2 under the SSP585 scenario. However, the model predicted that an inland invasion would not be serious. The results of this study suggest a need to focus on the risk of invasion in islands and coastal areas.

Many changes in the scale and structure of the Korean rice cropping system have been made over the past few decades. Still, insufficient research has been conducted on the sustainability of this system. This study analyzed changes in the Korean rice cropping system’s sustainability from a system ecology perspective using an emergy approach. For this purpose, an emergy table was created for the Korean rice cropping system in 2011, 2016, and 202, and an emergy-based indicator analysis was performed. The emergy analysis showed that the total emergy input to the rice cropping system decreased from 10,744E+18 sej year-1 to 8,342E+18 sej year-1 due to decreases in paddy field areas from 2011 to 2021, and the proportion of renewable resources decreased by 1.4%. The emergy input per area (ha) was found to have decreased from 13.13E+15 sej ha-1 year-1 in 2011 to 11.89E+15 sej ha-1 year-1 in 2021, and the leading cause was a decrease in nitrogen fertilizer usage and working hours. The amount of emergy used to grow 1 g of rice stayed the same between 2016 and 2021 (specific emergy: 13.3E+09 sej g-1), but the sustainability of the rice cropping system (emergy sustainability index, ESI) continued to decrease (2011: 0.107, 2016: 0.088, and 2021: 0.086). This study provides quantitative information on the emergy input structure and characteristics of Korean rice cropping systems. The results of this study can be used as a valuable reference in establishing measures to improve the ecological sustainability of the Korean rice cropping system.

Climate change and biological invasions are the greatest threats to biodiversity, agriculture, health and the global economy. Tomato leafminer(Tuta absoluta) (Meyrick) (Lepidoptera: Gelechiidae) is one of the most important threats to agriculture worldwide. This pest is characterized by rapid reproduction, strong dispersal ability, and highly overlapping of generations. Plants are damaged by direct feeding on leaves, stems, buds, calyces, young ripe fruits and by the invasion of secondary pathogens which enter through the wounds made by the pest. Since it invaded Spain in 2006, it has spread to Europe, the Mediterranean region, and, in 2010, to some countries in Central Asia and Southeast Asia. In East Asia, Tomato leafminer was first detected in China in Yili, Xinjiang Uygur Autonomous Region, in 2017. There is a possibility that this pest will invade South Korea as well. This study provides this by the use of MaxEnt algorithm for modelling the potential geographical distribution of Tomato Leafminer in South Korea Using presence-only data.

The process of biological invasion is led by the dynamics of a population as a demographic and evolutionary unit. Spatial structure can affect the population dynamics, and it is worth being considered in research on biological invasion which is always accompanied by dispersal. Metapopulation theory is a representative approach to spatially structured populations, which is chiefly applied in the field of ecology and evolutionary biology despite the controversy about its definition. In this study, metapopulation was considered as a spatially structured population that includes at least one subpopulation with significant extinction probability. The early phase of the invasion is suitable to be analyzed in aspects of the metapopulation concept because the introduced population usually has a high extinction probability, and their ecological·genetic traits determining the invasiveness can be affected by the metapopulation structure. Although it is important in the explanation of the prediction of the invasion probability, the metapopulation concept is rarely used in ecological research about biological invasion in Korea. It is expected that applying the metapopulation theory can supply a more detailed investigation of the invasion process at the population level, which is relatively inadequate in Korea. In this study, a framework dividing the invasive metapopulation into long- and middle-distance scales by the relative distance of movement to the natural dispersal range of species is proposed to easily analyze the effect of a metapopulation in real cases. Increased understanding of the mechanisms underlying invasions and improved prediction of future invasion risk are expected with the metapopulation concept and this framework.

공간 샘플링은 공간모델링 연구에 활용되어 샘플링 비용을 줄이면서 모델링의 효율성을 높이는 역할을 한다. 농업분야에서는 기후변화 영향을 예측하고 평가하기 위한 고해상도 공간자료 기반 모델링에 대한 연구 수요가 빠르게 증가하고 있으며, 이에 따라 공간 샘플링의 필요성과 중요성이 증가하고 있다. 본 연구는 국내 농지 공간샘플링 연구를 통해 농업분야 기후변화연구의 공간자료 활용의 효율성을 제고하고자 하였다. 본 연구는 층화랜덤샘플링 을 기반으로 하였으며, 1 km 해상도의 농지 공간격자자료 모집단 (11,386개 격자)에 대해서 RCP 시나리오별 (RCP 4.5/8.5) 연대별 (2030/2050/2080년대) 공간샘플링을 설 계하였다. 국내 농지는 기상 및 토양 특성에 따라 계층화 되었으며, 샘플링 효율 극대화를 위해 최적 층화 및 샘플 배정 최적화를 수행하였다. 최적화는 작물수량, 온실가스 배출량, 해충 분포 확률을 포함하는 16개 목표 변수에 대해 주어진 정밀도 제한 내에서 샘플 수를 최소화하는 방향으로 진행되었다. 샘플링의 정밀도와 정확도 평가는 각각 변동계수 (CV)와 상대적 편향을 기반으로 하였다. 국내 농지 공간격자 모집단 계층화 및 샘플 배정 및 샘플 수 최적화 결과, 전체 농지는 5~21개 계층, 46~69개 샘플 수 수준에서 최적화되었다. 본 연구결과물들은 국내 농업시스템 대표 공간격자로써 널리 활용될 수 있을 것으로 기대된다. 또한, 기후변화 영향예측 공간모델링 연구들에 활용되어 샘플링 비용 및 계산 시간을 줄이면서도 모델의 효율성을 높이는 데에 기여할 수 있다.

Prediction of the behavior of heavy metals over time is important to evaluate the heavy metal toxicity in algae species. Various modeling studies have been well established, but there is a need for an improved model for predicting the chronic effects of metals on algae species to combine the metal kinetics and biological response of algal cells. In this study, a kinetic dynamics model was developed to predict the copper behavior (5 μg L-1, 10 μg L-1, and 15 μg L-1) for two freshwater algae (Pseudokirchneriella subcapitata and Chlorella vulgaris) in the chronic exposure experiments (8 d and 21 d). In the experimental observations, the rapid change in copper mass between the solutions, extracellular and intracellular sites occurred within initial exposure periods, and then it was slower although the algal density changed with time. Our model showed a good agreement with the measured copper mass in each part for all tested conditions with an elapsed time (R 2 for P. subcapitata: 0.928, R 2 for C. vulgaris: 0.943). This study provides a novel kinetic dynamics model that is compromised between practical simplicity and realistic complexity, and it can be used to investigate the chronic effects of heavy metals on the algal population.

The active development of the global marine trade industries has been known to increase the inflows of marine invasive species and harmful organisms into the ecosystem, and the marine ecological disturbances. One of these invasive species, Ciona robusta, has now spread to the Korea Strait, the East Sea, and Jeju Island in connection with the climate change but not the Yellow Sea in Korea. Currently, the spread and distribution of C. robusta is increasingly damaging aquaculture and related facilities. Therefore, this study aims to identify the spread of C. robusta and potential habitats and to secure a data for the prevention of effective management measures due to climate change as well as damage the reduction in future through the prediction of spread. We used environmental variables in BioOracle. Also, the potential habitat and distribution of C. robusta was predicted using MaxEnt, a species distribution model. Two different RCP scenarios (4.5 and 8.5) were specified to predict the future distributions of C. robusta. The results showed that the biggest environmental factor affecting the distribution of C. robusta was the salinity as well as

The long-term biological monitoring data in domestic streams need to be appropriately analyzed. Food-web analysis using network-based approach can give ecological implications on these kinds of data by including interactions between species. The purpose of this study is constructing food-webs as a preliminary step of the analysis. We used observed species list data for 8 years (2008-2015) provided in Water Information System (WIS), focusing cheonggye streams as a case study. On the basis of species interaction dataset extracted from Global Biotic Interactions (GloBI) database, 96 food-webs were constructed. In further studies, these food-webs could be analyzed in various ways such as static, dynamic and spatial approaches.

From simple niche models to machine learning methods, there have been intensive efforts to understand the potentialdistribution of species in last two decades. Especially in the agricultural sector, recent SDM, Species Distribution Models,studies highly enthused to predict the potential distribution of invasive species under Climate Change. Beyond the distribution,efforts are needed to assess potential risk caused by the target pest. The Shared Socio-Economic Pathways (SSPs) are scenariosfor climate change impacts and adaptation measures. We used MaxEnt model to predict potential distribution of melonthrips with two RCPs (4.5, 8.5) and three SSPs (SSP1, SSP2, SSP3) scenarios. In agricultural land, the potential distributionof melon thrips increases under climate change, but the impact is reduced with the development-oriented scenario, SSP3.

To assess the temperature change effects on Collembola communities, we selected 9 Korean mountains in different latitudes. Top soil was collected and Collembola extracted from 3 sites in different elevation in each mountain. Extracted Collembola were sorted to genera and this data were summarized as total abundance, family richness and diversity. Additionally, soil temperature in each plot, physical and chemical properties of the soil was investigated and that correlated with Collembola community data. Average soil temperature and soil properties affected patterns in Collembola abundance and family richness. The results indicate that temperature change and soil properties strongly affected Collembola communities. Therefore, Climate change has high potential to affect Collembola communities.

Global warming can seriously influence on the interaction between pest and natural enemy in the agroecosystem due to the differences in optimal temperature ranges. Two aphid-ladybug systems, Myzus persicae-Coccinella septempunctata (M-C) and Aphis gossypii-Coccinella septempunctata (A-C) in the pepper crop were simulated, respectively under four different temperature scenarios including crop development over 244 days with the assumption that the average temperature is higher by 1, 3, and 5 °C than that in Seoul in 2000. Temperature-dependent functions for each aphid-ladybug system were embedded in Rosenzweig-Macathur predator-prey model to explore their population dynamics, and then Dynamic Index was used to quantify the strengths of species interactions. The result shows that the predator-prey population cycles as well as species interactions are getting shorter and stronger in both systems as temperature increased. Especially, the excessively high temperature scenario in Aphis gossypii-Coccinella septempunctata system could result in the extreme species interaction. Therefore, the increasing temperature can facilitate the effectiveness of biological control because of growing crop plant development and much stronger species interaction, although there are increases of the frequency of pest occurrences.

The first record of Melon thrips, Thrips palmi Karny, was in 1993 in Korea, and the species has become severe pest in agricultural industry. We used two different SDMs(Species Distribution Model) which have different approaches to analyse potential distribution of the pest species in climate change scenario, MaxEnt and CLIMEX. The MaxEnt model uses historical occurrence records with environmental variables to estimate the realized niche, and CLIMEX model simulates the fundamental niche of the object based on the seasonal phenology. In MaxEnt simulation, we reduced the number of variables to avoid multi-collinearity problem until we had no pairs with an absolute Pearson correlation coefficient higher than 0.8. BIO1(Annual Mean Temperature), BIO2(Mean diurnal range), BIO3(Isothermality), BIO4(Temperature seasonality) were finally selected as predictor, and we used 10 fold cross validation option to replicate. The averaged results were used to index analysis. The CLIMEX results, The Ecoclimate Index(EI), were also normalized in 0 to 1 scale to analysis. Under RCP 8.5 climate change scenario, in 2070s, the distribution of Thrips palmi was predicted to expand their territory overall agricultural area in Korea.

Toxicity test of contaminate soil is very complex because of differential bioavailability in the soil. Therefore, bioavailability of metals in soil is a major factor influencing estimates of toxicity. In this study, the two major test was conducted. First, the toxicity of arsenic for the Collembola, Paronychiurus kimi, was assessed by determining the effects of increasing arsenic concentration on survival, reproduction and body concentration of As in five forested soils with different available phosphate and oxide-metal concentration. Second, the sequential extraction procedure (SEP) for arsenic by choosing extraction reagents commonly used for sequential extraction of metals was tested. The EC50 based on total As concentration in soil was estimated respectively. The available phosphate and oxide-metal concentration in soil influenced on As fraction in soil. Especially, As in soil which is non specifically and specifically sorbed (fraction 1, 2) has strong correlation with available phosphate and oxide-metal concentration (p<0.05). The toxicity is more higher in the soil with high available phosphate and low oxide-metal concentration. In addition, the high arsenic concentration in fraction which is amorphous and poor-crystalline hydrous oxide of Fe and Al (fraction 3) had effect to the toxicity. As a result, the toxicity of As is related with As concentration in fraction 1, 2 and 3 and the soil properties and the arsenic fractionation in soil have a influence on the bioavailability and toxicity.

Araneae species are predators in natural ecosystem interact with various prey species. These linkage can be affected under climate change because species react not just individually but systematically. We focused on potential impact of climate change in Araneae fauna in national scale. In this study, potential species richness of Araneae in South Korea was predicted with MaxEnt (Maximum Entropy) model. Korea Forest Research Institute conducted national scale research of wandering arthropods. They monitored in uniformly set 366 points, and the data contain exact GPS points of study sites. Occurrence data were extracted from Prediction of Distribution and Abundance of Forest Spiders According to Climate Scenario (Korea Forest Research Institute, 2013). With the report, dominant 21 Araneae species that appeared more than 10% study sites were selected to estimate species richness. Training climate data were prepared from observation source of Korea Meteorological Administration. RCP 8.5 scenario data which represent future (2050, 2070) climate condition were downloaded from WORLDCLIM web site. In MaxEnt simulation, occurrence data for 21 species and 19 bioclimatic variables were used. Because the model outputs are expressed in index, the minimum training presence threshold rule was applied to distinguish presence/absence of each 21 species distribution model. We overlaid whole 21 thresholded output to get species richness map. The fluctuation between current and future species richness was calculated to observe changing trend in national scale. The results of Araneae fauna tends to move higher altitude and latitude. Species richness of lowlands is predicted to be diminished, but higher mountains are expected to be more suitable for many spider species. In some South Western coastal areas showed reduced richness in 2050 but will recover in 2070.

Thc climate change has the potential to significantly modify the actual distribution of insect pest with unknown consequences on agricultural systems and management strategies. In this study, Thrips palmi Karny was selected to predict distribution under climate change. T. palmi was introduced and first recorded in 1993 in Korea, and has become a serious pest of vegetable and ornamental crops. The MaxEnt was applied to T. palmi to predict its potential geographic distribution in Korea and Japan under the RCP 8.5 climate changing scenario. The MaxEnt software package is one of the most popular tools for species distribution and environmental niche modeling. The habitat prediction model of T. palmi in Korea was validated by the distribution of T. palmi in Japan. Based on the MaxEnt modeling, T. palmi would expand their potential distribution to whole Korean peninsula except the alpine region in Gangwon-do and Yanggang-do and Hamgyeongbuk-do in 2070s. Therefore, the monitoring system and management strategy for T. palmi should be reconsidered and re-evaluated.