• 한국농림기상학회지
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• 제18권4호
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• pp.242-252
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• 2016

생태계 과정 모형인 BIOME-BGC를 이용해 국내 상록침엽수림의 탄소-물 순환 과정의 계절 및 연간 변화를 모의하여 국내의 소나무 고사 현상의 기후-토심 영향을 분석하였다. 연구지로 2009년과 2014년 각각 소나무 대량 고사가 발생한 밀양과 울진을 선정하였다. 두 지역의 표준강수지수를 산정한 결과 약 5년 내외의 주기의 가뭄현상을 판별하였다. 2000년 중반 이후 가뭄은 고온 건조 기후 특성을 보였다. 모형의 여러 변수를 조사한 결과, 임시탄소저장소인 Cpool 변수가 탄소기아에 의한 소나무고사 현상과 개연성이 큰 변수로 나타났다. Cpool의 감소는 총일차생산성(GPP) 감소 혹은 유지호흡(Rm) 증가의 결과로 발생하였고, 연구기간 중 Cpool이 최저값을 보인 해는 각 연구지역에서 소나무 대량 고사가 발생한 해와 잘 일치하였다. 두 지역 모두 가뭄에 의한 GPP 감소와 고온에 의한 Rm 증가가 Cpool의 감소를 초래하였는데, GPP와 Rm의 상대적 기여도는 지역별로 상이하였다. 특히 저온다습한 울진의 경우 Rm 증가 영향이 중요한 요인이었다. 한편 낮은 토심에서 생산성, 생체량, 증산량, Cpool 등 제반 탄소-물 관련 변수가 감소하였고 연간 변동폭이 증가하였다. 그러나 0.5 m 이하 토심에서는 Cpool에 큰 차이가 없는 것으로 보아 일정 수준 이하의 토심에서 생체량-생산성-유지호흡 간의 균형에 따라 Cpool이 유지되는 적응 메커니즘이 나타난 것으로 보인다. 이 연구의 결과 소나무 고사와 관련한 고온건조-탄소 기아 가설을 제안하였고, 보다 현실적 분석을 위한 향후 모형 개선 방향을 제안하였다.

• Asian-Australasian Journal of Animal Sciences
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• 제22권8호
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• pp.1209-1223
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• 2009

In this review, the terminology that is used to describe ileal amino acid (AA) digestibilities in piglet feed ingredients is defined. If one accepts that the determination of AA digestibilities should be based on the ileal analysis method, one should consider that ileal digesta contains variable amounts of endogenous crude protein (CP), which originates mainly from digestive secretions, sloughedoff epithelial cells and mucins. The ileal endogenous CP and AA losses are separated into basal ileal endogenous CP and AA losses ($IAAL_{B}$), which are not influenced by the feed ingredient composition, and specific ileal endogenous CP and AA losses ($IAAL_{S}$), which are induced by feed ingredient characteristics such as level and type of fiber and anti-nutritional factors (ANF). Depending how ileal endogenous CP and AA losses are considered in the measurement of CP and AA digestibilities, digestibility values are expressed as apparent (AID), standardized (SID), or true (TID) ileal digestibilities of CP and AA. The main concern associated with the use of AID values in diet formulation for pigs is that they are not additive in mixtures of feed ingredients. Consequently, the concept of standardized ileal CP and AA digestibilities was introduced by correcting AID values for basal ileal endogenous CP and AA losses ($IAAL_{B}$). The correction for both $IAAL_{B}$ and $IAAL_{S}$ yields TID values, however, routine procedures to measure $IAAL_{S}$ are not yet available. In principle, SID values should be preferred, because they represent the fundamental properties of the feed ingredient. There exist only few reports on SID of CP and AA in feedstuffs frequently used in piglet nutrition. These include soybeans (SB), soybean meal (SBM), soy proteins (SP), soy protein concentrate (SPC), soy protein isolate (SPI), corn gluten (CG), wheat gluten (WG), pea protein (PeaP), potato protein (PotP), fish meal (FM) and whey proteins (WP), but the results obtained are inconsistent. Differences in SID values within feed ingredients may, at least in part, be attributed to different processing conditions or inherent differences of the assay feed ingredients. Moreover, there is some evidence that the determination of SID values and $IAAL_{B}$ in piglets may be confounded by the dietary CP level of the assay diet, age and (or) body weight (BW), the level of feed intake or the methodological approach used to determine $IAAL_{B}$.

• 한국지형학회지
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• 제27권1호
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• pp.61-89
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• 2020

The objective of this study is to characterize landslide susceptibility depending on various geo-environmental variables as well as to compare the Frequency Ratio (FR) and Evidential Belief Function (EBF) methods for landslide susceptibility analysis of rainfall-induced landslides. In 2013, a total of 259 landslides occurred in Chuncheon, Gangwon Province, South Korea, due to heavy rainfall events with a total cumulative rainfall of 296~721mm in 106~231 hours duration. Landslides data were mapped with better accuracy using the geographic information system (ArcGIS 10.6 version) based on the historic landslide records in Chuncheon from the National Disaster Management System (NDMS), the 2013 landslide investigation report, orthographic images, and aerial photographs. Then the landslides were randomly split into a testing dataset (70%; 181 landslides) and validation dataset (30%; 78 landslides). First, geo-environmental variables were analyzed by using FR and EBF functions for the full data. The most significant factors related to landslides were altitude (100~200m), slope (15~25°), concave plan curvature, high SPI, young timber age, loose timber density, small timber diameter, artificial forests, coniferous forests, soil depth (50~100cm), very well-drained area, sandy loam soil and so on. Second, the landslide susceptibility index was calculated by using selected geo-environmental variables. The model fit and prediction performance were evaluated using the Receiver Operating Characteristic (ROC) curve and the Area Under Curve (AUC) methods. The AUC values of both model fit and prediction performance were 80.5% and 76.3% for FR and 76.6% and 74.9% for EBF respectively. However, the landslide susceptibility index, with classes of 'very high' and 'high', was detected by 73.1% of landslides in the EBF model rather than the FR model (66.7%). Therefore, the EBF can be a promising method for spatial prediction of landslide occurrence, while the FR is still a powerful method for the landslide susceptibility mapping.