Food webs have received global attention as next-generation biomonitoring tools; however, it remains challenging because revealing trophic links between species is costly and laborious. Although a link-extrapolation method utilizing published trophic link data can address this difficulty, it has limitations when applied to construct food webs in domestic streams due to the lack of information on endemic species in global literature. Therefore, this study aimed to develop a link extrapolation-based food web model adapted to Korean stream ecosystems. We considered taxonomic similarity of predation and dominance of generalists in aquatic ecosystems, designing taxonomically higher-level matching methods: family matching for all fish (Family), endemic fish (Family-E), endemic fish playing the role of consumers (Family-EC), and resources (Family-ER). By adding the commonly used genus matching method (Genus) to these four matching methods, a total of five matching methods were used to construct 103 domestic food webs. Predictive power of both individual links and food web indices were evaluated by comparing constructed food webs with corresponding empirical food webs. Results showed that, in both evaluations, proposed methods tended to perform better than Genus in a data-poor environment. In particular, Family-E and Family-EC were the most effective matching methods. Our model addressed domestic data scarcity problems when using a link-extrapolation method. It offers opportunities to understand stream ecosystem food webs and may provide novel insights into biomonitoring.

Through sample-size-based rarefaction analyses, we tried to suggest the appropriate degree of sample concentration and sub-sample extraction, as a way to estimate more accurate zooplankton species diversity when assessing biodiversity. When we collected zooplankton from three reservoirs with different environmental characteristics, the estimated species richness (S) and Shannon’s Hʹ values showed different changing patterns according to the amount of sub-sample extracted from the whole sample by reservoir. However, consequently, their zooplankton diversity indices were estimated the highest values when analyzed by extracting the largest amount of sub-sample. As a result of rarefaction analysis about sample coverage, in the case of deep eutrophic reservoir (Juam) with high zooplankton species and individual numbers, it was analyzed that 99.8% of the whole samples were represented by only 1 mL of sub-sample based on 100 mL of concentrated samples. On the other hand, in Soyang reservoir, which showed very small species and individual numbers, a relatively low representation at 97% when 10 mL of sub-sample was extracted from the same amount of concentrated sample. As such, the representation of sub-sample for the whole zooplankton sample varies depending on the individual density in the sample collected from the field. If the degree of concentration of samples and the amount of subsample extraction are adjusted according to the collected individual density, it is believed that errors that occur when comparing the number of species and diversity indices among different water bodies can be minimized.

목적：본 연구에서는 간세포암 환자들을 대상으로 직접 얻은 2000 s/㎟의 높은 b-value의 확산강조영상(diffusion weighted image, DWI)과 낮은 b-value들을 외삽(外揷, extrapolation) 하여 재구성한 2000 s/㎟의 같은 b-value의 확산강조영상 (computed diffusion weighted image, cDWI)을 비교하여 cDWI의 유용성을 평가해보고자 한다. 대상 및 방법：총 30명의 간세포암(hepatocellular carcinoma, HCC) 환자를 대상으로 실험하였다. b-value 0, 50, 800, 2000 s/㎟을 이용한 DWI를 획득하고, b-value 0, 50, 800 s/㎟의 DWI만을 외삽하여 b-value 2000 s/㎟의 cDWI를 재구성하였다. 직접 얻은 b-value 2000 s/㎟의 DWI와 재구성으로 얻은 b-value 2000 s/㎟의 cDWI의 신호 대 잡음비 (Signal-to-noise ratio, SNR), 대조도 대 잡음비(Contrast-to-noise ratio, CNR)를 정량평가하였다. 또한 자기공명영상(magnetic resonance imaging, MRI) 검사 경력이 서로 다른 방사선사 2 명이 각각 시각적인 영상의 질에 대해 정성평가를 하였다. 정량평가는 대응표본 t-검정을 통해 통계적 유의성을 검정하였다. 정성평가는 대응표본 t-검정과 함께, 각 평가자 간 평가 점수의 일치도 분석을 위해 급내상관계수(Intraclass correlation coefficient, ICC)를 실시하였다. 결과：정량평가 결과는 DWI의 SNR이 각각 간실질에서 40.68±1.94, HCC에서 90.8±6.12, 문맥에서 62.69±5.08이었다. cDWI의 SNR은 각각 간실질에서 38.36±4.55, HCC에서 100.52±9.33, 문맥에서 3.6±0.43이었다. DWI의 CNR은 각각 간실질과 HCC 사이에서 48.31±5.72, 간 실질과 문맥 사이에서 22.01±3.2, HCC와 문맥 사이에서 49.71±5.14이었다. cDWI의 CNR은 각각 간실질과 HCC 사이에서 57.66±6.16, 간 실질과 문맥 사이에서 34.76±4.18, HCC와 문맥 사이에서 96.2±8.87이었다. 정성평가 결과, 방사선사1이 DWI를 1.14±0.36, cDWI을 3.36±0.49로 평가하였다. 방사선 사2는 DWI를 1.18±0.39, cDWI를 3.43±0.5로 평가하였다. 정량평가와 정성평가 모두에서 대응표본 t-검정은 통계적 유의성을 나타냈다(p<0.05). 정성평가에서 급내상관계수는 DWI에서 0.932 (95% CI 0.852-0.968, p=0.000), cDWI에서 0.925 (95% CI 0.838-0.965, p=0.000)으로 매우 높은 일치도를 보였다. 결론：병소 외의 간의 구조물에서는 고식적인 b-value 2000 s/㎟의 DWI의 SNR이 높았다. 하지만 간세포암의 SNR과 모든 경우의 CNR, 시각적 평가는 b-value 2000 s/㎟의 cDWI에서 더 높았다. 특히 혈관 등 구조물들의 경계에서 cDWI의 구별 능력이 뛰어났다. 따라서 2000 s/㎟의 높은 b-value의 cDWI은 기존의 DWI 방식을 대체하여, 간에서 구조물 간에 더 나은 분해능을 제공하고, 검사시간 단축을 실현할 수 있다.

Effects of environmental stressors such as pollutants and anthropogenic perturbance on the health of aquatic/terrestrial ecosystems usually involve a series of biological responses ranging from the biomarkers to the individual, population and community levels. Extrapolation is the use of existing information for the prediction of events in another situation that is biologically different from that where the existing information was gathered. To establish relationships and to determine the feasibility of extrapolating between higher and lower levels of biological organization, temporal or spatial patterns in organism responses to contaminant Invertebrates are widely regarded as powerful monitoring tools in environmental management because of their great abundance, diversity and functional importance, their sensitivity to perturbation, and the ease with which they can be sampled loading have been studied with various living organisms and ecosystems. By identifying and establishing relationships between levels of biological organization of invertebrates we should be better able to understand the mechanisms of stress responses in ecological systems that could ultimately result in improved predictive capability of ecological risk assessment and also allow for more informed decisions regarding remedial actions.