RCP 기후변화 시나리오 따른 알팔파바구미(Hypera postica)의 서식지 분포 변화 예측 Prediction of Changes in Habitat Distribution of the Alfalfa Weevil (Hypera postica) Using RCP Climate Change Scenarios원문보기
기후변화는 곤충의 성장, 발육, 생존, 생식력, 분포범위 등 생활사의 변수들에 영향을 준다. 특히 외래곤충의 경우 생태계 정착 및 확산이 빨라지고 있으며, 생태계 교란, 토착종 감소 등 생물다양성을 감소시키는 직접적인 원인 중 하나이다. 알팔파바구미는 1990년대 제주도에서 처음 발견 후 남부지방에 대량 발생하여 농업해충으로 인식되었다. 최근 하면처로 이동하는 개체에 의한 밭작물의 피해와 여러 시군에서 서식이 확인되며 확산의 우려되고 있다. 본 연구에서는 기후변화가 알팔파바구미에 미치는 영향에 대해 파악하였다. 미래의 기후 시나리오 RCP 4.5와 RCP 8.5에서 알팔파바구미의 잠재적 분포를 추정하기 위해 MaxEnt 모델을 적용하였다. 모형의 변수는 2015~2017년까지 알팔파바구미의 서식이 확인된 66개 지점과 종의 생태특성 및 예측변수간 상관성을 고려한 6개(bio3, bio6, bio10, bio12, bio14, bio16)의 생물기후를 사용하였다. 예측된 모형의 적합도는 평균 0.765로 잠재력이 의미 있는 값이며, 최고 따뜻한 분기의 평균기온(bio10)이 60~70%로 높은 기여도를 나타냈다. 2050년과 2070년의 시나리오(RCP 4.5, RCP 8.5)에 대한 모형의 결과는 한반도 전역에서 알팔파바구미의 분포 변화를 보여 주었으며, 기온상승에 따른 전국적 확산이 예측되었다.
기후변화는 곤충의 성장, 발육, 생존, 생식력, 분포범위 등 생활사의 변수들에 영향을 준다. 특히 외래곤충의 경우 생태계 정착 및 확산이 빨라지고 있으며, 생태계 교란, 토착종 감소 등 생물다양성을 감소시키는 직접적인 원인 중 하나이다. 알팔파바구미는 1990년대 제주도에서 처음 발견 후 남부지방에 대량 발생하여 농업해충으로 인식되었다. 최근 하면처로 이동하는 개체에 의한 밭작물의 피해와 여러 시군에서 서식이 확인되며 확산의 우려되고 있다. 본 연구에서는 기후변화가 알팔파바구미에 미치는 영향에 대해 파악하였다. 미래의 기후 시나리오 RCP 4.5와 RCP 8.5에서 알팔파바구미의 잠재적 분포를 추정하기 위해 MaxEnt 모델을 적용하였다. 모형의 변수는 2015~2017년까지 알팔파바구미의 서식이 확인된 66개 지점과 종의 생태특성 및 예측변수간 상관성을 고려한 6개(bio3, bio6, bio10, bio12, bio14, bio16)의 생물기후를 사용하였다. 예측된 모형의 적합도는 평균 0.765로 잠재력이 의미 있는 값이며, 최고 따뜻한 분기의 평균기온(bio10)이 60~70%로 높은 기여도를 나타냈다. 2050년과 2070년의 시나리오(RCP 4.5, RCP 8.5)에 대한 모형의 결과는 한반도 전역에서 알팔파바구미의 분포 변화를 보여 주었으며, 기온상승에 따른 전국적 확산이 예측되었다.
Climate change can affect variables related to the life cycle of insects, including growth, development, survival, reproduction and distribution. As it encourages alien insects to rapidly spread and settle, climate change is regarded as one of the direct causes of decreased biodiversity because it d...
Climate change can affect variables related to the life cycle of insects, including growth, development, survival, reproduction and distribution. As it encourages alien insects to rapidly spread and settle, climate change is regarded as one of the direct causes of decreased biodiversity because it disturbed ecosystems and reduces the population of native species. Hypera postica caused a great deal of damage in the southern provinces of Korea after it was first identified on Jeju lsland in the 1990s. In recent years, the number of individuals moving to estivation sites has concerned scientists due to the crop damage and national proliferation. In this study, we examine how climate change could affect inhabitation of H. postica. The MaxEnt model was applied to estimate potential distributions of H. postica using future climate change scenarios, namely, representative concentration pathway (RCP) 4.5 and RCP 8.5. As variables of the model, this study used six bio-climates (bio3, bio6, bio10, bio12, bio14, and bio16) in consideration of the ecological characteristics of 66 areas where inhabitation of H. postica was confirmed from 2015 to 2017, and in consideration of the interrelation between prediction variables. The fitness of the model was measured at a considered potentially useful level of 0.765 on average, and the warmest quarter has a high contribution rate of 60-70%. Prediction models (RCP 4.5 and RCP 8.5) results for the year 2050 and 2070 indicated that H. postica habitats are projected to expand across the Korean peninsula due to increasing temperatures.
Climate change can affect variables related to the life cycle of insects, including growth, development, survival, reproduction and distribution. As it encourages alien insects to rapidly spread and settle, climate change is regarded as one of the direct causes of decreased biodiversity because it disturbed ecosystems and reduces the population of native species. Hypera postica caused a great deal of damage in the southern provinces of Korea after it was first identified on Jeju lsland in the 1990s. In recent years, the number of individuals moving to estivation sites has concerned scientists due to the crop damage and national proliferation. In this study, we examine how climate change could affect inhabitation of H. postica. The MaxEnt model was applied to estimate potential distributions of H. postica using future climate change scenarios, namely, representative concentration pathway (RCP) 4.5 and RCP 8.5. As variables of the model, this study used six bio-climates (bio3, bio6, bio10, bio12, bio14, and bio16) in consideration of the ecological characteristics of 66 areas where inhabitation of H. postica was confirmed from 2015 to 2017, and in consideration of the interrelation between prediction variables. The fitness of the model was measured at a considered potentially useful level of 0.765 on average, and the warmest quarter has a high contribution rate of 60-70%. Prediction models (RCP 4.5 and RCP 8.5) results for the year 2050 and 2070 indicated that H. postica habitats are projected to expand across the Korean peninsula due to increasing temperatures.
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문제 정의
This study analyzed the spread of H. postica habitat according to rising temperature. The MaxEnt model predicted that the habitat of H.
This study presents a preliminary map of the potential distribution of H. postica in South Korea using an SDM. The model was considered potentially useful, and temperature was found to be an important factor in determining the distribution.
제안 방법
Due to the fact that H. postica inhabits flat lands such as rice paddies and upland fields, as well as the edges of forests, this study excludes geographical variables and uses only climate variables as explanatory variables. In terms of climate variables, the study used past mean temperature data from the 1950s to 2000s provided by worldclim (http://www.
postica inhabits flat lands such as rice paddies and upland fields, as well as the edges of forests, this study excludes geographical variables and uses only climate variables as explanatory variables. In terms of climate variables, the study used past mean temperature data from the 1950s to 2000s provided by worldclim (http://www.worldclim. org) and future mean temperatures for the 2050s and 2070s predicted by HadGEM2-AO as bio-climatic data. Bio-climatic data provided by worldclim contain 19 kinds of climate data parameters based on temperature and precipitation, and is the most widely used database for biogeographic and bioecological studies (Nix, 1986; Hijmans et al.
, 2008; Flanklin, 2009). The model determines the maximum entropy distribution and assesses the odds of existence of the species based on appearance records and randomly created background points, and uses the normalization of parametric variables to control overfitting. Continuous and categorical variables can be used as environmental variables, and distribution probability is a continuous set of numbers from 0 to 1, used to evaluate the fitness of a form.
This study applies RCP scenarios from the 5th IPCC Report and divides them into analyses of the year 2050 (2041-2060) and the year 2070 (2061-2080). Representative concentration pathway (RCP) scenarios are those offered by the IPCC, and suggest a total of four pathways that depending on the policy execution level.
Using climate models such as RCP 4.5 and RCP 8.5, this study produced predictions of the changes in future potential habitats of H. postica for the years 2050 and 2070 (Fig. 4). As a result of predicting the changes, if RCP 4.
대상 데이터
Distribution data of H. postica were collected from 66 places where inhabitation was confirmed by a field test (Fig. 1). The field survey was conducted on riversides, in forest, in parks, and on arable land and farmland across the country in consideration of the ecological characteristics from March to June of 2015 to 2017.
1). The field survey was conducted on riversides, in forest, in parks, and on arable land and farmland across the country in consideration of the ecological characteristics from March to June of 2015 to 2017. Inhabitations are indicated with longitudes and altitudes, and are converted into a *.
데이터처리
In terms of the main variables of the model, their relative significance was measured through variable contribution and jackknife tests. The analysis of variable contributions shows the predictive contribution percentage each variable contributes to the model, while the jackknife tests identify the most important variables by running a test for each variable in isolation and comparing it to all of the variables (Dowling, 2015).
이론/모형
2. Jackknife test of the individual environmental variable importance (blue bars) relative to all environmental variables (red bar) for the MaxEnt model. Values shown are averages over 10 replicate runs.
To identify potential inhabitation spread of H. postica due to climate change, this study used an algorithm with the MaxEnt model (version 3.3.3k)(Phillips et al., 2006). As the MaxEnt model enables a prediction based on appearance information of the species, it is widely used in various disciplines including environment, ecology, and geology due to its usability, statistical excellence, and ease of interpretation (Phillips et al.
성능/효과
4). As a result of predicting the changes, if RCP 4.5 was applied, the potential habitat areas were projected to increase by 38,758.11 km2 from the current level to 81,256.65 km2 in the year 2050 (an almost 191% increase), and were expected to increase by 46,499.24 km2 to 88,997.78 km2 in the year 2070 (an almost 209% increase). In contrast, if RCP 8.
In the current climate, the warmest quarter’s mean temperature (bio10) and the coldest quarter’s mean temperature (bio6) were the most powerful predictive factors, and their contribution levels were measured at 64.3% and 24.6%, respectively (Table 3).
3B, C). Results showed that high probabilities were recorded when yearly precipitation (bio12) were over 2,000 mm, when precipitation of the dry month (bio14) was more than 80 mm, and when rainfall of the warm quarter (bio18) was 700 mm (Fig. 3D, E, F). If one looked at the results after applying the threshold value, potential inhabitation areas account for 42,498.
Scenarios are consistent descriptions of future situations and are mainly used for the evaluation of adaptation to climate change impact and vulnerability. This study compares the effects of habit distribution by alien species in both RCP 4.5, in which greenhouse emission reduction policies may have been substantially realized, and RCP 8.5, in which greenhouse emissions continue to increase at the current pace in absence of reduction policies.
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