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In this study, we reported a case of insect‐plant‐bird interactions under climate warming. With a succession of warmer winters from 2013 to 2015, successive outbreaks of the moth Pantana phyllostachysae, a common defoliator for most bamboo species, occurred in the Wawushan Nature Reserve of Southwest China, leading to a rapid altitudinal range expansion from 1650 to 2050 m in P. phyllostachysae. The bamboo Chimonobambusa szechuanensis that is largely distributed at moderate altitudes consequently suffered much loss. Accumulated infested area of C. szechuanensis within the reserve during the 3 years covered ~90% of the suitable breeding habitats of Emei Shan Liocichla Liocichla omeiensis, a threatened songbird preferring to nest in the bamboo, which led to diversified nesting‐plant selection and a significant reduction in nesting success of the babbler. Our findings provide new evidence of the plasticity of avian breeding behavior, and of the impact of climate change on ecological communities through multi‐species interactions. The study has important conservation implications. [ABSTRACT FROM AUTHOR]

Abstract In this study, we reported a case of insect‐plant‐bird interactions under climate warming. With a succession of warmer winters from 2013 to 2015, successive outbreaks of the moth Pantana phyllostachysae, a common defoliator for most bamboo species, occurred in the Wawushan Nature Reserve of Southwest China, leading to a rapid altitudinal range expansion from 1650 to 2050 m in P. phyllostachysae. The bamboo Chimonobambusa szechuanensis that is largely distributed at moderate altitudes consequently suffered much loss. Accumulated infested area of C. szechuanensis within the reserve during the 3 years covered ~90% of the suitable breeding habitats of Emei Shan Liocichla Liocichla omeiensis, a threatened songbird preferring to nest in the bamboo, which led to diversified nesting‐plant selection and a significant reduction in nesting success of the babbler. Our findings provide new evidence of the plasticity of avian breeding behavior, and of the impact of climate change on ecological communities through multi‐species interactions. The study has important conservation implications.

In recent years, climate abnormalities have been observed globally. Consequently, the scale and size of natural disasters, such as typhoons, wind wave, heavy snow, downpours, and storms, have increased. However, compared to other disasters, predicting the timing, location and severity of damages associated with typhoons and other extreme wind wave events is difficult. Accurately predicting the damage extent can reduce the damage scale by facilitating a speedy response. Therefore, in this study, a model to estimate the cost of damages associated with wind waves and their impacts during coastal storms was developed for the Republic of Korea. The history of wind wave and typhoon damages for coastal areas in Korea was collected from the disaster annual report (1991–2020), and the damage cost was converted such that it reflected the inflation rate as in 2020. Furthermore, data on ocean meteorological factors were collected for the events of wind wave and typhoon damages. Using logistic and linear regression, a wind wave damage prediction model reflecting the coastal regional characteristics based on 74 regions nationwide was developed. This prediction model enabled damage forecasting and can be utilized for improving the law and policy in disaster management.

Recently, the frequency of severe torrential rain storms has been continuously increasing as an effect of abnormal climate. Annual flood damages and water quality degradation continuously worsen despite the imposition of flood and water quality managements. Hence, suitable analyses should be made to mitigate future flood damages and water quality degradation in riverine systems. In this study, two major analyses were done: analysis on the variation of the flood frequency and water quality. The principal method used to analyze variation of the flood frequency is through the application of flood-frequency analysis in time series on flood discharges. For the flood-frequency analysis, the stream flow data used were gathered from 25 gauging stations located in Geum River Basin. The Log Pearson Type III distribution was used to determine the probability of the flood discharges. The annual maximum series of the flood discharge data from stations was divided into two parts: the historical data and the present data. Flood-frequency analysis was performed to determine the influence of the effects of abnormal climate to the flood discharge in Bugil and Seokhwa stations. For the second part of this study, the water quality data such as BOD, COD, and SS for 24 years were also collected for the analysis of variation patterns of water quality induced by abnormal climate. This study showed that the flood frequency by flood-frequency analysis using the present data was higher compared with the historical data. Further findings showed that, both COD and SS consistently increase while BOD decreases in a yearly basis. [ABSTRACT FROM AUTHOR]

In recent years, climate abnormalities have been observed globally. Consequently, the scale and size of natural disasters, such as typhoons, wind wave, heavy snow, downpours, and storms, have increased. However, compared to other disasters, predicting the timing, location and severity of damages associated with typhoons and other extreme wind wave events is difficult. Accurately predicting the damage extent can reduce the damage scale by facilitating a speedy response. Therefore, in this study, a model to estimate the cost of damages associated with wind waves and their impacts during coastal storms was developed for the Republic of Korea. The history of wind wave and typhoon damages for coastal areas in Korea was collected from the disaster annual report (1991–2020), and the damage cost was converted such that it reflected the inflation rate as in 2020. Furthermore, data on ocean meteorological factors were collected for the events of wind wave and typhoon damages. Using logistic and linear regression, a wind wave damage prediction model reflecting the coastal regional characteristics based on 74 regions nationwide was developed. This prediction model enabled damage forecasting and can be utilized for improving the law and policy in disaster management. [ABSTRACT FROM AUTHOR]