세계 100대 악성 침입외래종인 유리알락하늘소(Anoplophora glabripennis)와 근연종인 노랑알락하늘소(가 칭, Anoplophora horsfieldii (Hope, 1843))가 2019년 제주도에서 처음 발견된 후 2023년까지 지속적으로 확인되었 다. 본 연구는 MaxEnt 알고리즘을 기반으로 하는 생물종 분포 모델을 이용하여 19개의 기후변화 변수에 노랑알락 하늘소(가칭) 먹이식물 5종(차나무, 팽나무, 멀구슬나무, 종가시나무, 비술나무)의 변수를 추가하여 외래해충인 노랑알락하늘소(가칭)의 현재·미래의 분포 가능지역에 대한 공간적 분포 특성을 규명하고 국가적 확산을 대응 하고자 한다. 모델 예측 정확도(AUC)는 0.983으로 출현지점을 정확하게 예측하는 비율이 매우 높다고 할 수 있다. 모델 예측 정확도의 증감에 영향을 주는 환경변수 중 먹이식물의 기여도가 70%를 상회하는 것으로 나타났다. 현재 75% 이상 분포 가능지역은 전라남도 진도군 일대와 경상북도 포항시 일대로 나타났으나 2050년에는 서해안을 따라 태안군까지 동해안을 따라 북한의 고성군까지 분포가 가능한 것으로 나타났다. 또한 75% 이상 분포 가능 면적은 현재 423㎢에서 2050년에는 9,270㎢로 약 대한민국 면적의 1/10 정도 확산될 것으로 예측된다.

Climate and atmospheric carbon dioxide are significant factors in ecological risk assessments, suggesting their consideration is required in predicting potential distribution of a invasive species. CLIMEX model is one of species distribution models (SDMs) and provides potential geographical distribution by focusing on climatic effect on species inhabitation. Most SDMs, such as Bioclim, Domain, GARP and MaxEnt, focus on relationship between the occurrences of the species and static environmental covariates, whereas CLIMEX model depends on limitations of species' geographical distribution and reactions to climatic variables at an appropriate temporal scale (called seasonal phenology). In this study, we described the basic concept of CLIMEX and reviewed previous applications. Also, we demonstrated the various utilization of CLIMEX differed by study purposes and methodology for analyzing the model.

Solenopsis geminata has been found in South Korea, suggesting a risk of its invasion has been increased by rapid climate change. This situation requires species distribution modeling to predict possibility of Solenopsis geminata introduction, but information necessary for performing it is very limited. In this study, we developed a map for global distribution of Solenopsis geminata so that the map can be used for future species distribution modeling. Also, as the first step to assess Solenopsis geminata introduction, climatic similarity between its origin (Puerto Rico) and major cities in South Korea was compared. We used ArcMap (version 10.0) for creating the distribution map by obtaining current habitat from public database, and CLIMEX was used to compare climates based on CMI value. The result showed that climates were not similar as indicated by CMI less than 0.52, suggesting the risk of intial introduction is low under the current climatic condition. However, it should be noted that climatic similarity did not consider biological characteristics of Solenopsis geminata and climate change. Thus, the next study will be devoted to climatic suitability simultaneously considers meteorological data, distribution and biological information.

Sampling insect pest population is often a necessary component of a proposed pest control strategy. Insect populations are poikilothermal animal and readily applied to model systems in several ways. When insect population immigrate to new possible habitats, they should be related with biotic and abiotic environments for survive and settle down. Based on climate change scenario, invasive insect species would be overcome its geographical limitation as well as local distribution of well-known species should be changed in near future. In this study, Species distribution modeling of native and invasive species were developed, compared and discussed for developing sampling strategies for invasive insect pest populations.

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.

Quantitative habitat model is established with species occurrence and spatial abundance data, which were usually acquired by professional field ecologists and citizen scientists. The importance of citizen science data is increasing, but the quality of these data needs to be evaluated. This study aims to identify and compare both expert-based data and citizen science data based on the performance power of quantitative models derived from both data sets. A Maximum Entropy (MaxENT) model was developed using eight environmental variables, including climate, topography, landcover and distance to forest edge. The AUC values derived from the MaxENT model were 0.842 and 0.809, respectively, indicating a high level of explanatory power. All environmental variables has similar values for both data sets, except for the distance to forest edge and rice paddy, which was relatively higher for expert-based survey data than that of the citizen science data as the distances increased. This result suggests that habitat model derived from expert-based survey data shows more ecological niche including wider ranges from forest edges and isolated habitat patches of rice paddy. This is presumably because citizen scientists focuses on direct observation methods, whereas professional field surveys investigate a wider variety of methods.