Forest fires are natural disasters that can occur suddenly and can be very damaging,burning thousands of square kilometers.Prevention is better than suppression and prediction models of forest fire occurrence have dev...Forest fires are natural disasters that can occur suddenly and can be very damaging,burning thousands of square kilometers.Prevention is better than suppression and prediction models of forest fire occurrence have developed from the logistic regression model,the geographical weighted logistic regression model,the Lasso regression model,the random forest model,and the support vector machine model based on historical forest fire data from 2000 to 2019 in Jilin Province.The models,along with a distribution map are presented in this paper to provide a theoretical basis for forest fire management in this area.Existing studies show that the prediction accuracies of the two machine learning models are higher than those of the three generalized linear regression models.The accuracies of the random forest model,the support vector machine model,geographical weighted logistic regression model,the Lasso regression model,and logistic model were 88.7%,87.7%,86.0%,85.0%and 84.6%,respectively.Weather is the main factor affecting forest fires,while the impacts of topography factors,human and social-economic factors on fire occurrence were similar.展开更多
Green tidal algal Enteromorpha species complete their life cycles by the isomorphic alternation of generations.The provenance of green tide caused by them in the western Yellow Sea has been disputed. The cell reproduc...Green tidal algal Enteromorpha species complete their life cycles by the isomorphic alternation of generations.The provenance of green tide caused by them in the western Yellow Sea has been disputed. The cell reproduction derived from adult thallus was observed on E. clathrata collected from Shantou City, Guangdong Province in this study. Subsequently, it further found that E. proliferia collected from Qingdao City, Shandong Province and Qinhuangdao City, Hebei Province, produced reproductive cells by somatic cells of its early infantile thallus or branch. The latter is functionally similar to that the seedlings of red alga Porphyra yezoensis produce the monospores, and could exquisitely explain the ephemeral or opportunistic trait and environmental adaptation ability of Enteromorpha species. Changes in growth conditions may induce the two types of cell reproduction.They contribute to the bloom, and can effectively reveal the seasonally occurring large-scale and on-year and offyear phenomenon. The latter may have played a decisive role in its formation. This paper analyses the legal status of the species name, the type of generation during bloom, ephemeral traits, the role of microscopic propagule, the area of origin, on-year and off-year phenomenon, early warning and prevention and control of the species, and so on. On this basis, further study on the influence of environmental factors on cell reproduction of early infantile thalli or branches will achieve a positive effect for early warning and prevention and control of the green tidal algal bloom.展开更多
基金This research was funded by the National Natural Science Foundation of China(grant no.32271881).
文摘Forest fires are natural disasters that can occur suddenly and can be very damaging,burning thousands of square kilometers.Prevention is better than suppression and prediction models of forest fire occurrence have developed from the logistic regression model,the geographical weighted logistic regression model,the Lasso regression model,the random forest model,and the support vector machine model based on historical forest fire data from 2000 to 2019 in Jilin Province.The models,along with a distribution map are presented in this paper to provide a theoretical basis for forest fire management in this area.Existing studies show that the prediction accuracies of the two machine learning models are higher than those of the three generalized linear regression models.The accuracies of the random forest model,the support vector machine model,geographical weighted logistic regression model,the Lasso regression model,and logistic model were 88.7%,87.7%,86.0%,85.0%and 84.6%,respectively.Weather is the main factor affecting forest fires,while the impacts of topography factors,human and social-economic factors on fire occurrence were similar.
基金The National Natural Science Foundation of China under contract Nos 31970216 and 31670199。
文摘Green tidal algal Enteromorpha species complete their life cycles by the isomorphic alternation of generations.The provenance of green tide caused by them in the western Yellow Sea has been disputed. The cell reproduction derived from adult thallus was observed on E. clathrata collected from Shantou City, Guangdong Province in this study. Subsequently, it further found that E. proliferia collected from Qingdao City, Shandong Province and Qinhuangdao City, Hebei Province, produced reproductive cells by somatic cells of its early infantile thallus or branch. The latter is functionally similar to that the seedlings of red alga Porphyra yezoensis produce the monospores, and could exquisitely explain the ephemeral or opportunistic trait and environmental adaptation ability of Enteromorpha species. Changes in growth conditions may induce the two types of cell reproduction.They contribute to the bloom, and can effectively reveal the seasonally occurring large-scale and on-year and offyear phenomenon. The latter may have played a decisive role in its formation. This paper analyses the legal status of the species name, the type of generation during bloom, ephemeral traits, the role of microscopic propagule, the area of origin, on-year and off-year phenomenon, early warning and prevention and control of the species, and so on. On this basis, further study on the influence of environmental factors on cell reproduction of early infantile thalli or branches will achieve a positive effect for early warning and prevention and control of the green tidal algal bloom.
