In Australia,the proportion of forest area that burns in a typical fire season is less than for other vegetation types.However,the 2019-2020 austral spring-summer was an exception,with over four times the previous max...In Australia,the proportion of forest area that burns in a typical fire season is less than for other vegetation types.However,the 2019-2020 austral spring-summer was an exception,with over four times the previous maximum area burnt in southeast Australian temperate forests.Temperate forest fires have extensive socio-economic,human health,greenhouse gas emissions,and biodiversity impacts due to high fire intensities.A robust model that identifies driving factors of forest fires and relates impact thresholds to fire activity at regional scales would help land managers and fire-fighting agencies prepare for potentially hazardous fire in Australia.Here,we developed a machine-learning diagnostic model to quantify nonlinear relationships between monthly burnt area and biophysical factors in southeast Australian forests for 2001-2020 on a 0.25°grid based on several biophysical parameters,notably fire weather and vegetation productivity.Our model explained over 80%of the variation in the burnt area.We identified that burnt area dynamics in southeast Australian forest were primarily controlled by extreme fire weather,which mainly linked to fluctuations in the Southern Annular Mode(SAM)and Indian Ocean Dipole(IOD),with a relatively smaller contribution from the central Pacific El Niño Southern Oscillation(ENSO).Our fire diagnostic model and the non-linear relationships between burnt area and environmental covariates can provide useful guidance to decision-makers who manage preparations for an upcoming fire season,and model developers working on improved early warning systems for forest fires.展开更多
Typical contourite deposits associated with submarine turbidite fan deposits are recognized for the first time from the Lower Devonian Liptrap Formation at Cape Liatrap, Victoria in southeast Australia. The contourite...Typical contourite deposits associated with submarine turbidite fan deposits are recognized for the first time from the Lower Devonian Liptrap Formation at Cape Liatrap, Victoria in southeast Australia. The contourites are well integrated within the turbidite fan deposits and are characterized by thin (5-8 cm), lenticular, well-sorted coarse-grained siltstones to fine-grained sandstones with current-ripples and cross beddings. The palaeocurrent directions of the turbidite fan and contourites are perpendicular to each other, with the former directed generally westward while the latter varying from 165° to 190° southward. In view of the facies types and architecture, we suggest that the turbidite fan was developed at the base of a westward inclined palaeo-slope, at the front of which the contourites were deposited as a result of southward flowing deep-sea contour (geostrophic) currents. The depositional setting inter- preted for the Liptrap Formation thus may provide a provisional model for the Lower Devonian conti- nental slope and abyssal basin environment in the southeastern part of the Melbourne Trough.展开更多
Since 1980, the white-browed crake(Porzana cinerea) has been experiencing an expansion from south of the Isthmus of Kra, northward to China. Recently, this species was observed in several locations throughout Southw...Since 1980, the white-browed crake(Porzana cinerea) has been experiencing an expansion from south of the Isthmus of Kra, northward to China. Recently, this species was observed in several locations throughout Southwest China, including Ningming and Baise, Guangxi(2012, 2013), and Xichang, Sichuan(2013). These sightings are the first distribution record of this species in China's Mainland, suggesting that the white-browed crake is following a natural species dispersal northward into China's Mainland from Southeast Asia.展开更多
东南印度洋中脊(Southeast Indian Ridge, SEIR)是印度洋中扩张速度最快的洋中脊,由SEIR增生的洋壳占印度洋总面积的50%以上,它是塑造印度洋现今构造格局的关键要素.相对西南印度洋中脊和西北印度洋中脊, SEIR具有更复杂的地质构造特征...东南印度洋中脊(Southeast Indian Ridge, SEIR)是印度洋中扩张速度最快的洋中脊,由SEIR增生的洋壳占印度洋总面积的50%以上,它是塑造印度洋现今构造格局的关键要素.相对西南印度洋中脊和西北印度洋中脊, SEIR具有更复杂的地质构造特征和演化过程.综合SEIR及邻区海底高原的地形地貌特征、重磁异常特征和玄武岩地球化学特征,探讨了SEIR的分段、洋中脊演化过程和地幔不均一性,以及板内火山作用与洋中脊的成因关系等.本文将有助于深入理解东南印度洋区域的构造演化历史,全面理解整个印度洋的洋中脊系统和大地构造格局,增进对冈瓦纳大陆裂解和印度洋演化过程的认识.初步研究认为东南印度洋区是多期洋中脊演化的结果,经历了北西向扩张、南北向扩张直至北东向扩张的三期洋壳增生过程.东南印度洋脊下的地幔源区存在不均一性,尤其是阿姆斯特丹-圣保罗海底高原和澳大利亚-南极错乱带两个区域.东南印度洋中的海底高原与热点火山作用密切相关,同时部分存在热点-洋脊相互作用或残留陆壳物质的影响.展开更多
This study aims at finding the dominant climate patterns that influence the precipitation anomalies for different regions over the world. To this end, a multiple linear regression model is employed to represent the im...This study aims at finding the dominant climate patterns that influence the precipitation anomalies for different regions over the world. To this end, a multiple linear regression model is employed to represent the impact of four major climate patterns(El Ni?o-Southern Oscillation(ENSO), Indian Ocean Dipole(IOD), Arctic Oscillation(AO) and Antarctic Oscillation(AAO)) on the global precipitation anomalies. The normalized climate pattern indexes and normalized precipitation anomalies are used in the regression model. For the Northern Hemisphere, the three predictors used are the normalized NINO3.4 index(representing ENSO), normalized DMI(representing IOD) and normalized AO index; for the Southern Hemisphere, also three indexes are used as three predictors, and the normalized AO index is replaced by the normalized AAO index. The influences brought by each climate pattern can be represented by the magnitude of the corresponding regression coefficients, and the dominant climate patterns are those with the largest magnitude. The study results show that the precipitation anomalies in the northern part of South America and the northwestern part of Southeast Asia are mainly influenced by ENSO. The precipitation anomalies in East Africa and the southwestern part of Southeast Asia are mainly influenced by IOD. The precipitation anomalies in Europe and west coast of North America are mainly influenced by AO; the precipitation anomalies in the eastern part and southern part of South America, southern part of Africa, and the northeastern Australia are mainly influenced by AAO. These findings are consistent with the general understanding on the teleconnection features of the four climate patterns. Further, the regression model can be used for predicting precipitation anomalies through use of these major climate patterns.展开更多
基金supported by the National Natural Science Foundation of China(42088101 and 42030605)support from the research project:Towards an Operational Fire Early Warning System for Indonesia(TOFEWSI)+1 种基金The TOFEWSI project was funded from October 2017-October 2021 through the UK’s National Environment Research Council/Newton Fund on behalf of the UK Research&Innovation(NE/P014801/1)(UK Principal InvestigatorAllan Spessa)(https//tofewsi.github.io/)financial support from the Natural Science Foundation of Qinghai(2021-HZ-811)。
文摘In Australia,the proportion of forest area that burns in a typical fire season is less than for other vegetation types.However,the 2019-2020 austral spring-summer was an exception,with over four times the previous maximum area burnt in southeast Australian temperate forests.Temperate forest fires have extensive socio-economic,human health,greenhouse gas emissions,and biodiversity impacts due to high fire intensities.A robust model that identifies driving factors of forest fires and relates impact thresholds to fire activity at regional scales would help land managers and fire-fighting agencies prepare for potentially hazardous fire in Australia.Here,we developed a machine-learning diagnostic model to quantify nonlinear relationships between monthly burnt area and biophysical factors in southeast Australian forests for 2001-2020 on a 0.25°grid based on several biophysical parameters,notably fire weather and vegetation productivity.Our model explained over 80%of the variation in the burnt area.We identified that burnt area dynamics in southeast Australian forest were primarily controlled by extreme fire weather,which mainly linked to fluctuations in the Southern Annular Mode(SAM)and Indian Ocean Dipole(IOD),with a relatively smaller contribution from the central Pacific El Niño Southern Oscillation(ENSO).Our fire diagnostic model and the non-linear relationships between burnt area and environmental covariates can provide useful guidance to decision-makers who manage preparations for an upcoming fire season,and model developers working on improved early warning systems for forest fires.
基金the National Natural Science Foundation of China (Grant Nos. 40672080, 40621002)the Ministry of Education of China (Grant No. IRT0546)the Australian Research Council (Grant No. DP0772161 to GRS)
文摘Typical contourite deposits associated with submarine turbidite fan deposits are recognized for the first time from the Lower Devonian Liptrap Formation at Cape Liatrap, Victoria in southeast Australia. The contourites are well integrated within the turbidite fan deposits and are characterized by thin (5-8 cm), lenticular, well-sorted coarse-grained siltstones to fine-grained sandstones with current-ripples and cross beddings. The palaeocurrent directions of the turbidite fan and contourites are perpendicular to each other, with the former directed generally westward while the latter varying from 165° to 190° southward. In view of the facies types and architecture, we suggest that the turbidite fan was developed at the base of a westward inclined palaeo-slope, at the front of which the contourites were deposited as a result of southward flowing deep-sea contour (geostrophic) currents. The depositional setting inter- preted for the Liptrap Formation thus may provide a provisional model for the Lower Devonian conti- nental slope and abyssal basin environment in the southeastern part of the Melbourne Trough.
基金supported by the National Natural Science Foundation of China(31172123)
文摘Since 1980, the white-browed crake(Porzana cinerea) has been experiencing an expansion from south of the Isthmus of Kra, northward to China. Recently, this species was observed in several locations throughout Southwest China, including Ningming and Baise, Guangxi(2012, 2013), and Xichang, Sichuan(2013). These sightings are the first distribution record of this species in China's Mainland, suggesting that the white-browed crake is following a natural species dispersal northward into China's Mainland from Southeast Asia.
文摘东南印度洋中脊(Southeast Indian Ridge, SEIR)是印度洋中扩张速度最快的洋中脊,由SEIR增生的洋壳占印度洋总面积的50%以上,它是塑造印度洋现今构造格局的关键要素.相对西南印度洋中脊和西北印度洋中脊, SEIR具有更复杂的地质构造特征和演化过程.综合SEIR及邻区海底高原的地形地貌特征、重磁异常特征和玄武岩地球化学特征,探讨了SEIR的分段、洋中脊演化过程和地幔不均一性,以及板内火山作用与洋中脊的成因关系等.本文将有助于深入理解东南印度洋区域的构造演化历史,全面理解整个印度洋的洋中脊系统和大地构造格局,增进对冈瓦纳大陆裂解和印度洋演化过程的认识.初步研究认为东南印度洋区是多期洋中脊演化的结果,经历了北西向扩张、南北向扩张直至北东向扩张的三期洋壳增生过程.东南印度洋脊下的地幔源区存在不均一性,尤其是阿姆斯特丹-圣保罗海底高原和澳大利亚-南极错乱带两个区域.东南印度洋中的海底高原与热点火山作用密切相关,同时部分存在热点-洋脊相互作用或残留陆壳物质的影响.
基金supported by Hong Kong RGC GRF projects(Grant Nos.HKU 710712E and 7109010E)NSFC project(Grant No.51479224)
文摘This study aims at finding the dominant climate patterns that influence the precipitation anomalies for different regions over the world. To this end, a multiple linear regression model is employed to represent the impact of four major climate patterns(El Ni?o-Southern Oscillation(ENSO), Indian Ocean Dipole(IOD), Arctic Oscillation(AO) and Antarctic Oscillation(AAO)) on the global precipitation anomalies. The normalized climate pattern indexes and normalized precipitation anomalies are used in the regression model. For the Northern Hemisphere, the three predictors used are the normalized NINO3.4 index(representing ENSO), normalized DMI(representing IOD) and normalized AO index; for the Southern Hemisphere, also three indexes are used as three predictors, and the normalized AO index is replaced by the normalized AAO index. The influences brought by each climate pattern can be represented by the magnitude of the corresponding regression coefficients, and the dominant climate patterns are those with the largest magnitude. The study results show that the precipitation anomalies in the northern part of South America and the northwestern part of Southeast Asia are mainly influenced by ENSO. The precipitation anomalies in East Africa and the southwestern part of Southeast Asia are mainly influenced by IOD. The precipitation anomalies in Europe and west coast of North America are mainly influenced by AO; the precipitation anomalies in the eastern part and southern part of South America, southern part of Africa, and the northeastern Australia are mainly influenced by AAO. These findings are consistent with the general understanding on the teleconnection features of the four climate patterns. Further, the regression model can be used for predicting precipitation anomalies through use of these major climate patterns.