In order to understand the temporal changes of botanical composition in grassland ecosystem, and to clarify the relation between these changes and environmental impacts, such as climatic factors and artificial disturb...In order to understand the temporal changes of botanical composition in grassland ecosystem, and to clarify the relation between these changes and environmental impacts, such as climatic factors and artificial disturbance, a grazing trail was carried out during a 21-year period from 1974 at a sown grassland of the National Grassland Research Institute, located in Nishinasuno, the central area of Japan. The data sets of biomass for each mouth(from April to November)of the 21 year period were analyzed in this paper. The botanical composition of aboveground biomass varied greatly with both season and year. The biomass ratio of improved herbage species to invaded native plants gradually decreased each year. This may have been owing to meteorological factors, such as low air-temperature in winter, dry and hot summers, grassland management(including grazing intensity and fertilizer application), and inter-specific competition between native and introduced herbage plants.展开更多
Agrometeorological disasters severely impact agriculture in Heilongjiang Province.Flood is one of the main agrometeorological disasters in Heilongjiang Province.The temporal change in flood events in Heilongjiang Prov...Agrometeorological disasters severely impact agriculture in Heilongjiang Province.Flood is one of the main agrometeorological disasters in Heilongjiang Province.The temporal change in flood events in Heilongjiang Province from 1986to 2015 was studied using Mann-Kendall and Morlet wavelet methods,respectively.The results of Mann-Kendall analysis showed that the disaster rates of flood gradually stabilized from 1986 to 2015 with a confidence level of 99%.The Morlet wavelet variance analysis revealed that disaster rates of flood changed periodically at time scales of 3a,7a and 18a in Heilongjiang Province during1986-2015.The dominant period of the variation of flood disaster rate was about 18a over the past 30 years.The flood disaster rates were indicated in a positive phase during the period of 2016-2020 by the fitting curve of Morlet wavelet analysis.The annual average flood disaster indexes of single station,during 1986-2015 years were calculated,according to the precipitation data at 31 stations in Heilongjiang Province and the GIS software was used to analyze the spatial change in flood disasters in Heilongjiang Province from1986-2015.The results demonstrated that the southwest area of Heilongjiang Province was highly hazardous region of flood.The flood indices in the northern part of Songnen Plain and southwest of Heilongjiang Province presented the increment trends.展开更多
Climate sequences can be applied to defining sensitive climate zones, and then the mining of spatio-temporal teleconnection patterns is useful for learning from the past and preparing for the future. However, scale-de...Climate sequences can be applied to defining sensitive climate zones, and then the mining of spatio-temporal teleconnection patterns is useful for learning from the past and preparing for the future. However, scale-dependency in this kind of pattern is still not well handled by existing work. Therefore, in this study, the multi-scale regionalization is embedded into the spatio-temporal teleconnection pattern mining between anomalous sea and land climatic events. A modified scale-space clustering algorithm is first developed to group climate sequences into multi-scale climate zones. Then, scale variance analysis method is employed to identify climate zones at characteristic scales, indicating the main characteristics of geographical phenomena. Finally, by using the climate zones identified at characteristic scales, a time association rule mining algorithm based on sliding time windows is employed to discover spatio-temporal teleconnection patterns. Experiments on sea surface temperature, sea level pressure, land precipitation and land temperature datasets show that many patterns obtained by the multi-scale approach are coincident with prior knowledge, indicating that this method is effective and reasonable. In addition, some unknown teleconnection patterns discovered from the multi-scale approach can be further used to guide the prediction of land climate.展开更多
文摘In order to understand the temporal changes of botanical composition in grassland ecosystem, and to clarify the relation between these changes and environmental impacts, such as climatic factors and artificial disturbance, a grazing trail was carried out during a 21-year period from 1974 at a sown grassland of the National Grassland Research Institute, located in Nishinasuno, the central area of Japan. The data sets of biomass for each mouth(from April to November)of the 21 year period were analyzed in this paper. The botanical composition of aboveground biomass varied greatly with both season and year. The biomass ratio of improved herbage species to invaded native plants gradually decreased each year. This may have been owing to meteorological factors, such as low air-temperature in winter, dry and hot summers, grassland management(including grazing intensity and fertilizer application), and inter-specific competition between native and introduced herbage plants.
基金Supported by China Clean Development Mechanism Project(2014101)。
文摘Agrometeorological disasters severely impact agriculture in Heilongjiang Province.Flood is one of the main agrometeorological disasters in Heilongjiang Province.The temporal change in flood events in Heilongjiang Province from 1986to 2015 was studied using Mann-Kendall and Morlet wavelet methods,respectively.The results of Mann-Kendall analysis showed that the disaster rates of flood gradually stabilized from 1986 to 2015 with a confidence level of 99%.The Morlet wavelet variance analysis revealed that disaster rates of flood changed periodically at time scales of 3a,7a and 18a in Heilongjiang Province during1986-2015.The dominant period of the variation of flood disaster rate was about 18a over the past 30 years.The flood disaster rates were indicated in a positive phase during the period of 2016-2020 by the fitting curve of Morlet wavelet analysis.The annual average flood disaster indexes of single station,during 1986-2015 years were calculated,according to the precipitation data at 31 stations in Heilongjiang Province and the GIS software was used to analyze the spatial change in flood disasters in Heilongjiang Province from1986-2015.The results demonstrated that the southwest area of Heilongjiang Province was highly hazardous region of flood.The flood indices in the northern part of Songnen Plain and southwest of Heilongjiang Province presented the increment trends.
基金Projects(41601424,41171351)supported by the National Natural Science Foundation of ChinaProject(2012CB719906)supported by the National Basic Research Program of China(973 Program)+2 种基金Project(14JJ1007)supported by the Hunan Natural Science Fund for Distinguished Young Scholars,ChinaProject(2017M610486)supported by the China Postdoctoral Science FoundationProjects(2017YFB0503700,2017YFB0503601)supported by the National Key Research and Development Foundation of China
文摘Climate sequences can be applied to defining sensitive climate zones, and then the mining of spatio-temporal teleconnection patterns is useful for learning from the past and preparing for the future. However, scale-dependency in this kind of pattern is still not well handled by existing work. Therefore, in this study, the multi-scale regionalization is embedded into the spatio-temporal teleconnection pattern mining between anomalous sea and land climatic events. A modified scale-space clustering algorithm is first developed to group climate sequences into multi-scale climate zones. Then, scale variance analysis method is employed to identify climate zones at characteristic scales, indicating the main characteristics of geographical phenomena. Finally, by using the climate zones identified at characteristic scales, a time association rule mining algorithm based on sliding time windows is employed to discover spatio-temporal teleconnection patterns. Experiments on sea surface temperature, sea level pressure, land precipitation and land temperature datasets show that many patterns obtained by the multi-scale approach are coincident with prior knowledge, indicating that this method is effective and reasonable. In addition, some unknown teleconnection patterns discovered from the multi-scale approach can be further used to guide the prediction of land climate.
